U.S. patent application number 13/367582 was filed with the patent office on 2012-09-06 for micro-rna biomarkers and methods of using same.
This patent application is currently assigned to BioMirna Holdings Ltd.. Invention is credited to Mattia Boeri, Ugo Pastorino, Gabriella Sozzi.
Application Number | 20120225925 13/367582 |
Document ID | / |
Family ID | 46062629 |
Filed Date | 2012-09-06 |
United States Patent
Application |
20120225925 |
Kind Code |
A1 |
Sozzi; Gabriella ; et
al. |
September 6, 2012 |
Micro-RNA Biomarkers and Methods of Using Same
Abstract
A procedure and an apparatus are described for identifying
individuals at risk of pulmonary tumour and/or for diagnosing a
pulmonary tumour using the study of levels of expression of miRNA
in the blood or another biological fluid. Also described are a
method and a compound for reducing or eliminating a risk of
pulmonary tumour by rebalancing the miRNAs that are underexpressed
or overexpressed.
Inventors: |
Sozzi; Gabriella; (US)
; Pastorino; Ugo; (US) ; Boeri; Mattia;
(Milan, IT) |
Assignee: |
BioMirna Holdings Ltd.
Dublin
IE
|
Family ID: |
46062629 |
Appl. No.: |
13/367582 |
Filed: |
February 7, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61522328 |
Aug 11, 2011 |
|
|
|
Current U.S.
Class: |
514/44A ; 506/16;
506/39; 506/9 |
Current CPC
Class: |
C12Q 2600/158 20130101;
A61P 3/00 20180101; C12Q 2600/118 20130101; C12Q 2600/178 20130101;
A61P 35/00 20180101; C12Q 1/6886 20130101 |
Class at
Publication: |
514/44.A ; 506/9;
506/16; 506/39 |
International
Class: |
A61K 31/7088 20060101
A61K031/7088; A61P 35/00 20060101 A61P035/00; C40B 60/12 20060101
C40B060/12; C40B 30/04 20060101 C40B030/04; C40B 40/06 20060101
C40B040/06 |
Foreign Application Data
Date |
Code |
Application Number |
Feb 7, 2011 |
IT |
MI2011A000172 |
Feb 7, 2011 |
IT |
MI2011A000173 |
Feb 7, 2011 |
IT |
MI2011A000174 |
Claims
1. A method comprising: determining the level of expression of at
least two miRNA from the miRNA listed in Tables Ia, Ic, IIa, IIc,
Va, Vc, VIa, or VIc in a biological sample from a subject, and
comparing the level of expression of said miRNA from said sample
from said subject to the level of expression of said miRNA from a
control biological sample.
2. The method of claim 1, comprising determining the level of
expression of at least six miRNA from the miRNA listed in Tables
Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.
3. A method comprising: determining the level of expression of at
least two miRNA listed in Table Ib or Id in a biological sample
from a subject, and comparing the level of expression of said miRNA
from said sample from said subject to the level of expression of
said miRNA from a control biological sample, wherein a change or
deviation in the level of expression of said at least two miRNA in
said biological sample from said control biological sample
identifies a subject at risk of manifesting a tumor.
4. The method of claim 3, comprising determining the level of
expression of at least six miRNA listed in Table Ib or Id.
5. The method of claim 3, wherein said miRNA are the miRNA listed
in Table Ie.
6. A method comprising: determining the level of expression of at
least two miRNA listed in Table IIb or IId in a biological sample
from a subject, and comparing the level of expression of said miRNA
from said sample from said subject to the level of expression of
said miRNA from a control biological sample, wherein a change or
deviation in the level of expression of said at least two miRNA in
said biological sample from said control biological sample
identifies a subject at risk of manifesting an aggressive
tumor.
7. The method of claim 6, comprising determining the level of
expression of the six miRNA listed in Table IIb or IId.
8. The method of claim 6, wherein said miRNA are the miRNA listed
in Table IIe, IIf or IIg.
9. A method comprising: determining the level of expression of at
least two miRNA listed in Table Vb or Vd in a biological sample
from a subject, and comparing the level of expression of said miRNA
from said sample from said subject to the level of expression of
said miRNA from a control biological sample, wherein a change or
deviation in the level of expression of said at least two miRNA in
said biological sample from said control biological sample
determines the presence of a tumor in said subject.
10. The method of claim 9, comprising determining the level of
expression of the six miRNA listed in Table Vb or Vd.
11. The method of claim 9, wherein said miRNA are the miRNA listed
in Tables Ve or Vf
12. A method comprising: determining the level of expression of at
least two miRNA listed in Table VIb or VId in a biological sample
from a subject, and comparing the level of expression of said miRNA
from said sample from said subject to the level of expression of
said miRNA from a control biological sample, wherein a change or
deviation in the level of expression of said at least two miRNA in
said biological sample from said control biological sample
determines the presence of an aggressive tumor in said subject.
13. The method of claim 12, comprising determining the level of
expression of the six miRNA listed in Table VIb or VId.
14. The method of claim 12, wherein said miRNA are the miRNA listed
in Tables VIe or VIf.
15. The method of claim 1, further comprising calculating a
plurality of real quotients by determining a ratio between the
level of expression of at least one pair of miRNA from at least two
miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc;
comparing each of the real quotients with a respective control
value; and determining the real quotients which deviate from the
respective control quotient value.
16. The method of claim 15, comprising determining a ratio between
the level of expression of at least one pair of miRNA from at least
six miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or
VIc.
17. The method of claim 15, wherein said miRNA are the miRNA listed
in Tables Ie, IIe, IIf, IIg, Ve, Vf, VIe or VIf.
18. The method of claim 15, further comprising determining a number
or percentage of real quotients which deviate from the respective
control value.
19. The method of claim 15, wherein for each of the calculated
quotients a respective control quotient is associated, represented
by a ratio of the levels of expression for the miRNA in a control
biological sample relative to a biological sample of a same
type.
20. The method of claim 15, wherein calculating the plurality of
real quotients comprises using the expression level of at least two
miRNA from the miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc,
VIa, or VIc.
21. The method of claim 15, wherein calculating the plurality of
real quotients comprises determining a predetermined number or a
predetermined percentage of quotients from among the levels of
expression, wherein the quotients are selected from at least one of
the quotients as listed in Tables IIIa, IIIc, IVa, IVc, VIIa, VIIc,
VIIIa, or VIIIc.
22. The method of claim 21, wherein the quotients are selected from
at least six of the quotients as listed in Tables IIIa, IIIc, IVa,
IVc, VIIa, VIIc, VIIIa, or VIIIc.
23. An article comprising: a support having a plurality of sites,
wherein each site is capable of receiving a quantity of a
biological sample, wherein each of the sites comprises at least one
reagent capable of binding with at least one miRNA listed in Tables
Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.
24. The article of claim 23, wherein each of the sites comprises at
least one reagent capable of binding with at least two miRNA listed
in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.
25. The article of claim 23, wherein each of the sites comprises at
least one reagent capable of binding with at least six miRNA listed
in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.
26. The article of claim 23, wherein the reagent is selected from
group consisting of: a polynucleotide comprising a nucleotide
sequence of at least one miRNA from the miRNA listed in Tables Ia,
Ic, IIa, IIc, Va, Vc, VIa, or VIc; a polynucleotide comprising a
nucleotide sequence which is complementary to a sequence of at
least one miRNA from the miRNA listed in Tables Ia, Ic, IIa, IIc,
Va, Vc, VIa, or VIc; and a molecular probe configured such as to
recognize a sequence of at least one miRNA from the miRNA listed in
Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.
27. The article of claim 26, wherein comprising at least two miRNA
listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.
28. The article of claim 26, wherein comprising at least six miRNA
listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.
27. An article comprising: a support having a plurality of sites,
wherein each site is capable of receiving a quantity of a
biological sample, wherein each of the sites comprises at least one
reagent capable of binding with at least two miRNA listed in Tables
Ib, Id, IIb, IId, Vb, Vd, VIb or VId.
28. The article of claim 27, wherein each of the sites comprises at
least one reagent capable of binding with at least six miRNA listed
in Tables Ib, Id, IIb, IId, Vb, Vd, VIb or VId.
29. The article of claim 27, wherein said miRNA are the miRNA
listed in Tables Ie, IIe, IIf, IIg, Ve, Vf, VIe or VIf.
30. An apparatus comprising: at least one unit capable of receiving
at least one of the articles of claim 23; means for determining the
level of expression of at least one miRNA from the miRNA listed in
Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, and means for
calculating the real quotients from among the levels of expression
of at least one pair of miRNA from the pairs of miRNA listed in
Tables IIIa, IIIc, IVa, IVc, VIIa, VIIc, VIIIa, or VIIIc.
31. The method of claim 3, further comprising altering the level of
expression of at least one miRNA for which the level of expression
changes or deviates, thereby reducing or eliminating the risk of
developing a tumor in said subject.
32. The method of claim 6, further comprising altering the level of
expression of at least one miRNA for which the level of expression
changes or deviates, thereby reducing or eliminating the risk of
developing an aggressive tumor in said subject.
33. The method of claim 9, further comprising altering the level of
expression of at least one miRNA for which the level of expression
changes or deviates, thereby treating a tumor in said subject.
34. The method of claim 12, further comprising altering the level
of expression of at least one miRNA for which the level of
expression changes or deviates, thereby treating an aggressive
tumor in said subject.
35. The method of claim 31, wherein altering the level of
expression of said at least one miRNA comprises administering to
said subject a therapeutically effective amount of at least one
miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, or a
chemically synthesized miRNA mimetic or recombinant thereof, if the
level of expression of said at least one miRNA is lower than the
control level of expression or administering to said subject a
therapeutically effective amount of a compound capable of
inhibiting the expression of at least one miRNA listed in Tables
Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, if the level of expression
of said at least one miRNA is higher than the control level of
expression.
36. The method of claim 35, comprising administering a
therapeutically effective amount of a composition comprising at
least one miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or
VIc, or a chemically synthesized miRNA mimetic or recombinant
thereof or administering a therapeutically effective amount of a
composition comprising an inhibitor of at least one miRNA listed in
Tables Ib, Id, IIb, Hd, Vb, Vd, VIb or VId.
37. A pharmaceutical compound comprising: at least one miRNA listed
in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, chemically
synthesized miRNA mimetic or recombinant thereof, or an inhibitor
of the expression of at least one miRNA listed in Tables Ia, Ic,
IIa, IIe, Va, Vc, VIa, or VIc and a pharmaceutically acceptable
carrier.
38. The pharmaceutical compound of claim 37 comprising at least two
miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc
39. The pharmaceutical compound of claim 37 comprising at least six
miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc
40. A pharmaceutical compound comprising: at least one miRNA listed
in Tables Ib, Id, IIb, IId, Vb, Vd, VIb or VId, chemically
synthesized miRNA mimetic or recombinant thereof, or an inhibitor
of the expression of at least one miRNA listed in Tables Ib, Id,
IIb, IId, Vb, Vd, VIb or VId and a pharmaceutically acceptable
carrier.
41. The pharmaceutical compound of claim 40 comprising at least two
miRNA listed in Tables Ib, Id, IIb, IId, Vb, Vd, VIb or VId
42. The pharmaceutical compound of claim 40 comprising at least six
miRNA listed in Tables Ib, Id, IIb, IId, Vb, Vd, VIb or VId
43. The pharmaceutical compound of claim 40, wherein said miRNA are
the miRNA listed in Tables Ie, IIe, IIf, IIg, Ve, Vf, VIe or VIf
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims the benefit of Italian Patent
Application Nos. MI2011A000172, MI2011A000173 and MI2011A000174,
each filed Feb. 7, 2011 and U.S. Provisional Application No.
61/522,328, filed Aug. 11, 2011. The contents of each of these
applications are incorporated herein by reference in their
entirety.
FIELD OF THE INVENTION
[0002] The present invention concerns methods for identifying and
using, in pre-diagnostic and/or diagnostic stages, special
molecular bio-markers identifiable in biological samples, such as
for example whole blood, serum, plasma, saliva or bronchia
condensate collected from an individual.
[0003] In more detail, the invention relates to methods for
identifying individuals at risk of tumour, in particular pulmonary
tumour. The invention also concerns methods for determining a
presence and/or level of aggressiveness of a tumour, for example a
pulmonary tumour, in an individual.
[0004] The invention also relates to diagnostic kits and apparatus
usable for setting up one or more stages of the methods.
[0005] Further, the invention concerns methods and pharmaceutical
compounds for treating an individual in whom presence of a tumour
has been diagnosed, for example a pulmonary tumour.
[0006] The invention also concerns methods and pharmaceutical
compounds for treating an individual in whom a risk of developing a
tumour has been identified, for example a pulmonary tumour, for
reducing and/or eliminating the risk of developing a tumour.
BACKGROUND OF THE INVENTION
[0007] As is known, tumours are one of the main causes of death in
the world. In particular, pulmonary tumours are the highest in
terms of incidence, as they represent about 12% of all the new
cases of cancer, and constitute the main cause of death by cancer
in the world, in both men and women.
[0008] In Europe about 400,000 new cases are diagnosed per year
(80% men, 20% women). In Italy the epidemiology of pulmonary cancer
is similar, with an incidence of 34,000 cases per year of which
7,000 are women and 27,000 men.
[0009] Sadly the incidence and the mortality are very similar due
to the highly lethal nature of pulmonary tumour: world-wide
mortality 27,500, of which 22,000 mend and 5,500 women. This
epidemiological data and the scarce level of treatability of the
illness underline the importance of identifying methods which are
able to identify as soon as possible any subjects who might be at
risk of developing pulmonary cancer. Further, it is of great
interest to develop procedures which can help in the correct
diagnosis of tumours, in particular pulmonary tumours present in an
individual subject under examination.
[0010] Notwithstanding these needs, tumour markers available today
are for diagnostic use, i.e. they identify the patients when the
disease has already developed such as to be identifiable with
imaging methods (spiral CT scan). These markers are however few and
not specific and essentially comprise biochemical markers such as
the evaluation of the protein CEA (Carcinoembryonic Antigene) and
some cytokeratins such as TPA, TPS and Cyfra 21.1.
[0011] Also known is a proteomic test (5-protein profile) on the
serum, at present proposed by Vermillion Inc. and used to indicate
a probability (score from 1 to 10) that ovarian masses might be of
a malignant nature. This test is used for women who already present
ovarian masses of a non-defined nature.
[0012] With specific reference to pulmonary tumours, although in
recent years important improvements have been made in the treatment
of oncological patients, there is however a need to develop more
effective methods which can lead to a faster therapeutic
intervention in clinical management of many types of tumours.
[0013] At present the majority of pulmonary tumours are diagnosed
at a late stage, when the symptoms are clinically evident and, for
example with reference to Non-small-cell lung carcinoma (NSCLC),
only a third of patients with NSCLC exhibits a
surgically-resectable disease, an approach which remains the most
effective treatment for this type of tumour.
[0014] Notwithstanding recent progress in treatment of pulmonary
cancer after resection and the use of specific treatments for
determined molecular targets, the rate of healing of non-small-cell
lung carcinoma (NSCLC) remains low due to the reappearance thereof
in patients that are resistant to drugs or who present
metastasis.
[0015] The effectiveness of the spiral CT scan in identification of
pulmonary cancer in heavy smokers is under evaluation in various
randomized clinical studies in Europe and the United States. Owing
to the its high level of sensitivity there remain various critical
points for its use in modern clinical practice, such as
over-diagnosis of indolent nodules, with a consequently high
frequency of non-necessary treatments and the verification of the
effective impact on mortality.
[0016] In this context, in recent years microRNAs have been
identified (herein below also MiRNA) as a new class of circulating
bio-markers which by their nature seem to be very stable and highly
specific tissue (Chen X, Cell Res, 2008). MiRNAs are small
non-coding RNA molecules (length 19-25 nucleotides) having a
regulatory function which are able to modulate the expression of
several target genes involved in various molecular mechanisms,
among which those involved in transformation processes.
[0017] The development of high-throughput technologies has enabled
the study of overall expression of the profiles of miRNA in cancer
(microRNAome) (Cummins J M et al., Proc Natl Acad Sci USA, 2006),
revealing that there exist hundreds of miRNA whose expression is
deregulated in tumours (Croce C M, Visone R, A J P, 2009;
WO2009/070653, The Ohio State University Research Foundation).
[0018] Apart from the tissue specificity, miRNA possess a high
degree of stability, ease of detection and association with known
clinical-pathological parameters (Lu Jet al., Nature, 2005).
[0019] Tests have also been carried out to determine whether miRNAs
are stable, detectable and quantifiable not only in the tissues
(both deep-frozen and fixed in formalin or paraffin) but also in
the bodily fluids. The results of this research have demonstrated
that miRNAs are also present in the blood circulation (whole blood,
serum and plasma), where they are found in stable form protected by
endogenous RNAsi. Circulating miRNAs are detectable and
quantifiable and the studies which have taken their levels in
oncological patients' biological fluids under examination have
reported that some of them present deregulated levels with respect
to healthy individuals (Heneghan H M et al., Ann Surg, 2010;
Mitchell P S et al., Proc Natl Acad Sci USA, 2008; Chen X, Cell
Res, 2008).
[0020] Recent publications report the profile of miRNAs circulating
in the serum and plasma of patients having pulmonary tumour (Hu Z,
Clin Oncol, 2010; Silva J, Eur Respir J, 2010 Shen J, Lab Invest,
2010).
[0021] Notwithstanding the presence of diagnostic imaging systems
and the studies relating to microRNAs, there is still the need to
identify procedures which are able to identify, with a certain
degree of anticipation, individuals at risk of developing pulmonary
cancer and possibly able to predict the development of the forms of
cancer, in particular pulmonary tumour, that are more aggressive
and lethal. There is also a need to improve the degree of
reliability of diagnostic techniques at present available.
SUMMARY OF THE INVENTION
[0022] In this situation, the aim of the present invention is to
obviate one or more of the limitations in the known procedures and
products.
[0023] Thus it is an aim of the invention to provide procedures for
early determination of individuals who present a risk of developing
a tumour, in particular a pulmonary tumour.
[0024] A further aim of the invention is to make available
procedures which assist in the diagnosis of tumour, in particular
pulmonary tumours, in human subjects.
[0025] A further aim of the invention is to make available
procedures which can be easily set up in laboratories, by analyzing
biological samples collected from an individual.
[0026] A further aim of the invention is to provide procedures
which enable satisfactory results to be obtained using samples of
blood, serum or plasma.
[0027] A further aim of the invention is to define diagnostic kits
and/or apparatus usable in the above-cited procedures in order to
identify human subjects who are at risk of contracting a tumour
and/or for assisting in the diagnosis of tumours present in human
subjects.
[0028] A further aim of the invention is to provide pharmaceutical
compounds and/or treatments which can be used to treat an
individual in whom the presence of a pulmonary tumour has been
diagnosed.
[0029] A final aim of the invention is to provide pharmaceutical
compounds and/or treatments for reducing and/or eliminating the
risk of developing a pulmonary tumour.
[0030] One or more of the set aims are substantially attained by a
method and/or a kit and/or a compound and/or an apparatus in
accordance with one or more of the accompanying claims.
[0031] Aspects of the invention are described herein below.
[0032] A first aspect concerns a procedure for identifying
individuals at risk of a pulmonary tumour, the procedure comprising
steps of: measuring, in at least a sample of biological fluid
previously collected from a subject, a value of the level of
expression of a plurality of microRNA molecules; determining when
the measured values of the level of expression deviate with respect
to a predetermined and respective control criterion.
[0033] The microRNA or miRNA molecules are thus used for
identifying individuals at risk or in a stage in which the tumour
has not yet manifested.
[0034] In a second aspect in accordance with the first aspect the
step of determining comprises determining the level of expression
of at least six miRNA from the miRNA listed in Tables Ia, Ic, Ha or
He in a biological sample from a subject, and comparing the level
of expression of said miRNA from said sample from said subject to
the level of expression of said miRNA from a control biological
sample. For example determining may comprise determining--in a
biological sample from a subject--the level of expression of the
six miRNA listed in Table Ib or Id or the level of expression of
the six miRNA listed in Table IIb or IId, and comparing the level
of expression of said six miRNA from said sample from said subject
to the level of expression of said miRNA from a control biological
sample, wherein a change or deviation in the level of expression of
said at least six miRNA in said biological sample from said control
biological sample identifies a subject at risk of manifesting a
tumor (Table 1b or Id miRNA are used) or an aggressive tumor (Table
IIb or lid miRNA are used).
[0035] In a third aspect in accordance with the first aspect the
step of determining comprises substeps of calculating a plurality
of ratios or real differences determined by performing the ratio or
respectively the difference between the measured values of the
levels of expression of a predetermined number of pairs of the
microRNA molecules, comparing each of the real ratios or
differences with a respective control value, determining the real
ratios or differences which deviate from the respective ratio value
or control difference.
[0036] In a fourth aspect in accordance with the third aspect, a
step is also included of determining a number or percentage of real
ratios or differences which deviate from the respective control
value and defining as an individual at risk an individual for whom
at least a predetermined number or a predetermined percentage of
the real ratios or differences deviates with respect to the
respective ratio value or control difference.
[0037] In a fifth aspect, in accordance with any one of the
preceding aspects, for each of the calculated ratios, a respective
control ratio is associated represented by the ratio of the
expression values for the microRNAs in a control sample relating to
a biological fluid of the same type. The control ratio is in
reality either a known value, or a determined value as a mean of
measured values in a sufficiently large population of individuals,
or a value relating to a fluid sample collected from a healthy
individual.
[0038] In a sixth aspect, in accordance with any one of the
preceding aspects, the procedure comprises the step of correlating
the deviation of a predetermined number or a predetermined
percentage of expression levels (i.e. real ratios or differences)
with respect to the corresponding control criteria in the presence
or absence of risk that the individual clinically presents a
pulmonary tumour in a predetermined time.
[0039] In a seventh aspect according to the preceding aspect the
predetermined time is comprised between one and three years, more
optionally is comprised between 12 and 28 months. In other words
the method of the invention is able to significantly anticipate the
determination of the risk of contracting a tumour with respect to
traditional techniques (such as spiral CT) which have to wait for
the disease to manifest at the level of lacerations or nodules of
various mm.
[0040] In an eighth aspect in accordance with any one of the
preceding aspects the procedure comprises a step of correlating the
deviation of a predetermined number or a predetermined percentage
of expression level with respect to the corresponding control
criteria to the presence or absence of risk which the individual
manifests clinically an aggressive pulmonary tumour in a
predetermined time.
[0041] In a ninth aspect, according to the preceding aspect, the
predetermined time is comprised between one and three years, more
optionally between 12 and 28 months. In other words the method of
the invention is able to significantly anticipate the determination
of the risk of contracting an aggressive tumour with respect to the
traditional techniques (such as spiral CT) which have to wait for
the disease to manifest at the level of lacerations or nodules or
various mm.
[0042] In a tenth aspect, in accordance with any one of the
preceding aspects, calculating the plurality of real ratios or
differences comprises using the expression values of a
predetermined number or a predetermined percentage of the miRNAs of
Table Ia, Ic, IIa and/or of Table IIc, optionally using the
expression values of the miRNAs of Table Ib, Id, IIb and/or of
Table IId.
[0043] In an eleventh aspect in accordance with any one of aspects
6.sup.th, 7.sup.th or 10.sup.th, calculating the plurality of real
ratios or differences comprises using the expression values of a
predetermined number or a predetermined percentage of the miRNAs of
Table Ia or Ic.
[0044] In a twelfth aspect, according to any one of aspects
8.sup.th, 9.sup.th or 10.sup.th, calculating the plurality of real
ratios or differences comprises using the expression values of a
predetermined number or a predetermined percentage of the miRNA of
Table IIa or IIc.
[0045] In a thirteenth aspect according to any one of the preceding
aspects, calculating the plurality of real ratios comprises
determining a predetermined number or a predetermined percentage of
ratios among the values of the expression levels, the ratios being
selected from the group comprising ratios between values of
expression levels of pairs of microRNA as in Table IIIa or IIIc,
optionally in which at least 20% are determined, more optionally at
least 50% and still more optionally all the ratios of Table IIIa or
IIIc.
[0046] In a fourteenth aspect in accordance with the preceding
claim, determining a predetermined number or a predetermined
percentage of ratios comprises calculating at least 20% of the real
ratios of Table IIIa or IIIc and in which it comprises a step of
defining as an individual at risk of pulmonary tumour, optionally
in a period comprised between one and three years from a collection
of the sample of biological fluid, an individual for whom at least
30%, optionally at least 50% of the real ratios calculated deviates
with respect to the respective control ratio value.
[0047] In a fifteenth aspect in accordance with any one of aspects
13 or 14, in which the ratios are those of Table IIIb or IIId.
[0048] In a sixteenth aspect in accordance with any one of the
preceding aspects, calculating the plurality of real ratios
comprises determining a predetermined number or a predetermined
percentage of ratios among the values of the expression levels, the
ratios being selected from the group comprising ratios between
values of expression levels of pairs of microRNAs as in Table IVa
or IVc, optionally in which at least 30% are determined, more
optionally at least 50%, and still more optionally all the ratios
of Table IVa or IVc.
[0049] In a seventeenth aspect according to the preceding aspect,
determining a predetermined number or a predetermined percentage of
ratios comprises calculating at least 30% of the real ratios as in
Table IVa or IVc, and wherein the procedure comprises a step of
defining as an individual at risk of aggressive pulmonary tumour,
optionally in a period comprised between one and three years from
collecting a sample of biological fluid, an individual for whom at
least 50%, optionally at least 75% of the real ratios calculated
deviates with respect to the respective control ratio value.
[0050] In an eighteenth aspect according to any one of aspects 16
or 17, the ratios are those of Table IVb or IVd.
[0051] In a nineteenth aspect of any one of the preceding aspects,
the steps of the procedure are conducted in vitro.
[0052] In a twentieth aspect in accordance with any one of the
preceding aspects, the biological fluid is one selected from a
group comprising: whole blood, a fraction of blood, plasma,
serum.
[0053] In a twenty-first aspect in accordance with any one of the
preceding aspects the pulmonary tumour is one selected from the
group comprising: small-cell lung cancer (SCLC), non small-cell
lung cancer (NSCLC), pulmonary adenocarcinoma (ADC),
bronchio-alveolar carcinoma (BAC), squamous-cell lung carcinoma
(SCC), large-cell carcinoma (LC).
[0054] In a twenty-second aspect according to any one of the
preceding aspects, the sample of biological fluid originates from a
smoker individual who, at the moment of the collection of the
sample, does not present a pulmonary tumour if subjected to imaging
diagnostic methods, in particular the smoker individual not
presenting nodules of dimensions of greater than 5 mm if subjected
to a spiral CT scan.
[0055] A twenty-third aspect concerns a medical kit for determining
biomolecular markers present in a sample of human biological fluid,
the kit comprising a platform having a plurality of sites, each of
which is destined to receive a respective discrete quantity of the
sample of biological fluid, each of the sites comprising a reagent
capable of bonding with at least a respective microRNA of Table Ia,
Ic, IIa and/or Table IIc, optionally wherein each of the sites
comprises a reagent capable of bonding with at least a respective
microRNA of Table Ib, Id, IIb and/or Table IId.
[0056] In a twenty-fourth aspect in accordance with the preceding
aspect, the reagent includes at least a reagent selected from among
the group comprising: a polynucleotide comprising a nucleotide
sequence of at least one of the microRNAs as in Table Ia, Ic, Ha
and/or Table IIc, optionally as in Table Ib, Id, IIb and/or Table
IId; a polynucleotide comprising a nucleotide sequence which is
complementary to a sequence of at least one of the microRNAs as in
Table Ia, Ic, IIa and/or Table IIc, optionally as in Table Ib, Id,
IIb and/or Table IId; a molecular probe configured such as to
recognize a sequence of at least one of the microRNAs as in Table
Ia, Ic, IIa and/or Table IIc, optionally as in Table Ib, Id, IIb
and/or Table IId.
[0057] A twenty-fifth aspect concerns a medical apparatus
comprising: a unit defining a seating for receiving one or more of
the kits of aspects 23.sup.rd or 24.sup.th; means for determining a
value of the level of expression of the microRNAs as in Table Ia,
Ic, IIa and/or Table IIc; means for calculating the values of the
real ratios from among the values of levels of expression of pairs
of microRNAs, the ratios being selected from those in Table IIa,
IIc, IVa and/or Table IVd, optionally those ratios of Table Ib,
IId, IVb and/or those of Table IVd.
[0058] In a twenty-sixth aspect according to the preceding aspect,
the means for determining the value of the expression level
comprise one of the techniques selected from the group:
Quantitative Real-time PCR, Microfluidic cards, Microarrays,
RT-PCR, quantitative or semi-quantitative, Northern blot, Solution
Hybridization, or Sequencing.
[0059] A twenty-eighth aspect comprises an in vitro procedure for
identifying individuals at risk of tumour and/or for determining a
presence of and/or an aggressiveness of a tumour in an individual,
the process comprising steps of: measuring, in at least a sample of
biological fluid previously collected from a subject, a value of a
level of expression of a plurality of microRNA molecules;
calculating a plurality of real ratios determined by calculating a
ratio between the measured values of the levels of expression of a
predetermined number of pairs of the microRNA molecules; comparing
each of the real ratios with a respective control value.
[0060] In a twenty-ninth aspect in accordance with the
twenty-eighth aspect, the process comprises determining a number or
percentage of real ratios which deviate from the respective control
value, defining, as an individual presenting a form of tumour, an
individual for whom at least a predetermined number or a
predetermined percentage of the real ratios deviates with respect
to the respective control ratio value.
[0061] In a thirtieth aspect in accordance with the twenty-ninth, a
respective control ratio is associated to each of the calculated
ratios, represented by a ratio of the values of expression for the
microRNAs in a control sample relative to a biological fluid of a
same type.
[0062] In a thirty-first aspect, in accordance with the thirtieth
or the twenty-ninth, calculating the plurality of real ratios
comprises using the values of expression of a predetermined number
of the miRNAs as in Table Ia, Ic, IIa and/or Table IIc and/or Table
Va, Vc, VIa and/or Table VIc.
[0063] In a thirty-second aspect in accordance with any one of
aspects from the 29.sup.th to 31.sup.st, calculating the plurality
of real ratios comprises determining a predetermined number or a
predetermined percentage of ratios from among the values of the
levels of expression, the ratios being selected from among the
group comprising ratios as in Table IIIa, IIIc, IVa, and/or Table
IVc and/or in Table VIIa, VIIc, VIIIa and/or in Table VIIIc.
[0064] In a thirty-third aspect in accordance with the
thirty-second, determining a predetermined number or a
predetermined percentage of ratios comprises calculating at least
20% of the real ratios of Table VIIa or VIIc and comprises a step
of defining as an individual presenting a pulmonary tumour an
individual for whom at least 30% of the predetermined number of
real ratios as in Table VIIa or VIIc which have been calculated
deviate with respect to the control value.
[0065] In a thirty-fourth aspect in accordance with the
thirty-third or the thirty-second, determining a predetermined
number or a predetermined percentage of ratios comprises
calculating at least 20% of the real ratios of Table VIIIa or VIIIc
and comprises a step of defining as an individual presenting an
aggressive pulmonary tumour an individual in whom 50%, optionally
at least 60%, of the real ratios which have been calculated deviate
with respect to the respective control value.
[0066] In a thirty-fifth aspect, in accordance with the
thirty-fourth or the thirty-third or the thirty-second, determining
the predetermined number or a predetermined percentage of ratios
comprises calculating at least 20% of the real ratios of Table IIa
or IIc and comprises a step of defining as an individual at risk of
a pulmonary tumour, optionally in a period comprised between one
and three years from a collection of the sample of biological
fluid, an individual for whom at least 30%, optionally at least
50%, of the real ratios calculated deviate with respect to the
respective control ratio value.
[0067] In a thirty-sixth aspect in accordance with the
thirty-fifth, the thirty-fourth or the thirty-third or the
thirty-second, determining the predetermined number or a
predetermined percentage of ratios comprises calculating at least
30% of the real ratios of Table IVa or IVc and comprises a step of
defining as an individual at risk of an aggressive pulmonary
tumour, optionally in a period comprised between one and three
years from a collection of the sample of biological fluid, an
individual for whom at least 50%, optionally at least 75%, of the
real ratios calculated deviate with respect to the respective
control ratio value.
[0068] In a thirty-seventh aspect in accordance with the any one of
the aspects from the 28.sup.th to the 32.sup.nd, determining a
predetermined number or a predetermined percentage of ratios
comprises calculating the real ratios of Table VIIb or VIId and
wherein the procedure comprises a step of defining as an individual
presenting a pulmonary tumor an individual for whom at least 80% of
the real ratios as in Table VIIb or VIId which have been calculated
deviate with respect to the control value.
[0069] In a thirty-eighth aspect in accordance with the any one of
the aspects from the 28.sup.th to the 32.sup.nd, determining a
predetermined number or a predetermined percentage of ratios
comprises calculating the real ratios of Table VIIIb or VIIId and
wherein the procedure comprises a step of defining as an individual
presenting an aggressive pulmonary tumor an individual for whom at
least 80% of the real ratios as in Table VIIIb or VIIId which have
been calculated deviate with respect to the control value.
[0070] In a thirty-ninth aspect in accordance with the any one of
the aspects from the 28.sup.th to the 32.sup.nd, determining a
predetermined number or a predetermined percentage of ratios
comprises calculating the real ratios of Table IIIb or IIId and
wherein the procedure comprises a step of defining as individual at
risk of a pulmonary tumour, optionally in a period comprised
between one and three years from a collection of the sample of
biological fluid, an individual for whom at least 80% of the real
ratios as in Table IIIb or IIId which have been calculated deviate
with respect to the control value.
[0071] In a fortieth aspect in accordance with the any one of the
aspects from the 28.sup.th to the 32.sup.nd, determining a
predetermined number or a predetermined percentage of ratios
comprises calculating the real ratios of Table IVb or IVd and
wherein the procedure comprises a step of defining as individual at
risk of an aggressive pulmonary tumour, optionally in a period
comprised between one and three years from a collection of the
sample of biological fluid, an individual for whom at least 80% of
the real ratios as in Table IVb or IVd which have been calculated
deviate with respect to the control value.
[0072] In a forty-first aspect in accordance with any one of the
preceding aspects from the 28.sup.th to 40.sup.th, the biological
fluid is one selected from among a group comprising: whole blood, a
fraction of blood, plasma, serum; saliva or bronchial
condensate.
[0073] In a forty-second aspect in accordance with any one of the
preceding aspects from the 28.sup.th to 41.sup.st, the tumour is a
pulmonary tumour selected from among a group comprising: small-cell
lung cancer (SCLC), non small-cell lung cancer (NSCLC), pulmonary
adenocarcinoma (ADC), bronchio-alveolar carcinoma (BAC),
squamous-cell lung carcinoma (SCC), large-cell carcinoma (LC).
[0074] In a forty-third aspect, in accordance with any one of the
preceding aspects from the 28.sup.th to 42.sup.nd, the sample of
biological fluid originates from a smoker individual who, at the
moment of the collection of the sample, presents a pulmonary tumour
if subjected to imaging diagnostic methods, in particular the
smoker individual presenting nodules of dimensions of greater than
5 mm if subjected to a spiral CT scan.
[0075] In a forty-fourth aspect, a medical kit is provided for
determining bio-molecular markers present in a sample of human
biological fluid, the kit comprising: a platform, for example a
support for receiving fluid samples, having a plurality of sites,
each of which is destined to receive a respective discrete quantity
of the sample of biological fluid, each of the sites comprising a
reagent capable of bonding with at least a respective microRNA of
Table Ia, Ic, IIa and/or Table IIc and/or Table Va, Vc, VIa and/or
Table VIc, optionally a reagent capable of bonding with at least a
respective microRNA as in Table Ib, Id, IIb and/or Table IId,
and/or Table Vb, Vd, VIb and/or Table VId.
[0076] In a forty-fifth aspect in accordance with the preceding
aspect, the reagent includes at least a reagent selected from among
a group comprising:
[0077] a polynucleotide comprising a nucleotide sequence of at
least one of the microRNAs as in Table Ia, Ic, IIa and/or Table IIc
and/or Table Va, Vc, VIa and/or Table VIc, or a nucleotide sequence
of at least one of the microRNAs as in Table Ib, Id, IIb and/or
Table IId, and/or Table Vb, Vd, VIb and/or Table VId;
[0078] a polynucleotide comprising a nucleotide sequence which is
complementary to a sequence of at least one of the microRNAs as in
Table Ia, Ic, IIa and/or Table IIc and/or Table Va, Vc, VIa and/or
Table VIc, optionally comprising a nucleotide sequence which is
complementary to a sequence of at least one of the microRNAs as in
Table Ib, Id, IIb and/or Table IId, and/or Table Vb, Vd, VIb and/or
Table VId;
[0079] a molecular probe configured such as to recognize a sequence
of at least one of the microRNAs as in Table Ia, Ic, IIa and/or
Table IIc and/or Table Va, Vc, VIa and/or Table VIc, optionally a
sequence of at least one of the microRNAs as in Table Ib, Id, IIb
and/or Table IId, and/or Table Vb, Vd, VIb and/or Table VId.
[0080] In a forty-sixth aspect a medical apparatus is provided,
comprising: a unit defining a seating for receiving one or more of
the kits of the preceding claim, means for determining a value of
the level of expression of the microRNAs as in Tables Ia, Ic, IIa
and/or Table IIc and/or Table Va, Vc, VIa and/or Table VIc,
optionally the value of the level of expression of the microRNA as
in Tables Ib, Id, IIb and/or Table IId, and/or Table Vb, Vd, VIb
and/or Table VId; means for calculating the values of the real
ratios from among the values of levels of expression of pairs of
microRNAs, the ratios being selected from those in Tables IIIa,
IIIc, IVa and/or Table IVc and/or Table VIIa, VIII, VIIIa and/or
Table VIIIc, optionally from those in Tables IIb, IIId, IVb and/or
Table IVd and/or Table VIIb, VIId, VIIIb and/or Table VIIId.
[0081] In a forty-third aspect in accordance with the preceding
aspect, the means for determining the value of the level of
expression comprise one from among the techniques selected from a
group as follows: Quantitative Real-time PCR, Microfluidic cards,
Microarrays, RT-PCR, quantitative or semi-quantitative, Northern
blot, Solution Hybridization, or Sequencing.
[0082] In a forty-eighth aspect a method is comprised for treating
an individual in whom a presence of a pulmonary tumour has been
diagnosed or in whom a risk of developing a pulmonary tumour has
been identified, respectively for treatment of the pulmonary tumour
or for reducing and/or eliminating the risk of developing a
pulmonary tumour, the method comprising following steps: measuring
a level of expression of at least an miRNA listed in Table Ia, Ic,
IIa and/or Table IIc and/or Table Va, Vc, VIa and/or Table VIc
present in a sample of biological fluid previously taken from the
individual, determining the miRNAs having measured values of a
level of expression which deviate with respect to a predetermined
and respective control criterion; altering the level of expression
of the miRNAs for which the levels of expression deviate with
respect to the respective control criterion.
[0083] In a forty-ninth aspect the step of measuring comprises
measuring a level of expression of at least a miRNA listed in Table
Ib, Id, IIb and/or Table IId, and/or Table Vb, Vd, VIb and/or Table
VId present in a sample of biological fluid previously taken from
the individual.
[0084] In a fiftieth aspect in accordance with the preceding aspect
the step of altering the level of expression of the miRNAs
comprises: administering to the individual an effective quantity of
at least one of the miRNAs listed in Table Ia, Ic, IIa and/or Table
IIc and/or Table Va, Vc, VIa and/or Table VIc, or of one of more of
the miRNA listed in Table Ib, Id, IIb and/or Table IId, and/or
Table Vb, Vd, VIb and/or Table VId, if the level of expression
measured of the miRNA or the miRNAs is lower than a respective
control level of expression
[0085] In a fifty-first aspect according to the 49th or 50th
aspect, the step of altering the level of expression of the miRNAs
comprises administering to the individual an effective quantity of
at least a compound for inhibiting the expression of at least one
of the miRNAs listed in Table Ia, Ic, IIa and/or Table IIc and/or
Table Va, Vc, VIa and/or Table VIc, or listed in Table Ib, Id, IIb
and/or Table IId, and/or Table Vb, Vd, VIb and/or Table VId, if the
measured level of expression of one or more of the miRNA or miRNAs
is higher than the control level of expression.
[0086] In a fifty-second aspect, in accordance with the 50.sup.th
aspect, the method comprises restoring the values of levels of
expression to a control level of expression for the miRNAs which
are under-expressed with respect to the respective control level of
expression.
[0087] In a fifty-third aspect in accordance with any one of
aspects from the 48.sup.th to the 52.sup.nd, the method comprises
administering a therapeutically effective quantity of a compound
comprising at least one of the miRNAs of Table Ia, Ic, IIa and/or
Table IIc and/or Table Va, Vc, VIa and/or Table VIc, optionally at
least one of the miRNA listed in Table Ib, Id, IIb and/or Table
IId, and/or Table Vb, Vd, VIb and/or Table VId, chemically
synthesized (miRNA mimetics) or recombinant.
[0088] In a fifty-fourth aspect according to any one of aspects
from 51.sup.st to 53.sup.rd, the method comprises reducing the
values of the level of expression to the control level of
expression for miRNAs which are over-expressed with respect to the
respective control level of expression.
[0089] In a fifty-fifth aspect in accordance with any one of the
aspects from 48.sup.th to 54.sup.th, the method comprises
administering a therapeutically effective quantity of a compound
comprising at least an inhibitor of a microRNA of Table Ia, Ic, IIa
and/or Table IIc and/or Table Va, Vc, VIa and/or Table VIc or Table
Ib, Id, IIb and/or Table IId, and/or Table Vb, Vd, VIb and/or Table
VId.
[0090] In fifty-sixth aspect in accordance with the preceding
aspect, the inhibitor comprises double-filament RNA.
[0091] In a fifty-seventh aspect according to the preceding aspect
the method comprises short interfering RNA (siRNA), antisense
nucleic acids (anti-miRNA oligonucleotides (AMOs), molecules of
enzymatic RNA (ribozymes).
[0092] In a fifty-eight aspect according to any one of aspects from
the 55.sup.th to the 57.sup.th, the inhibitor is directed to a
specific product of microRNA and interferes with the expression,
for example by means of inhibition of a translation or induction of
degradation, of a target gene of the microRNA.
[0093] In a fifty-ninth aspect in accordance with any one of the
preceding aspects, the step of determining the miRNAs having
measured values of the levels of expression which deviate with
respect to the respective control criterion comprises: calculating
a plurality of real ratios determined by performing a ratio between
the measured values of the levels of expression of a predetermined
number of pairs of the microRNA molecules, the ratios being
selected from a group comprising the ratios as in Table IIa, IIIc,
IVa and/or Table IVc and/or Table VIIa, VIII, VIIIa and/or Table
VIIIc, optionally the ratios being selected from a group comprising
the ratios as in and/or Table IIIb, IIId, IVb and/or Table IVd
and/or Table VIIb, VIId, VIIIb and/or Table VIIId, determining the
real ratios which deviate from the respective control values,
identifying the miRNAs involved in the real ratios which deviate
from the respective control value.
[0094] A sixtieth aspect concerns a pharmaceutical compound for
treating an individual in whom has been diagnosed a pulmonary
tumour or in whom a risk of developing a pulmonary tumour has been
identified, respectively for treatment of the pulmonary tumour or
for reducing and/or eliminating the risk of developing a pulmonary
tumour, the compound comprising: at least one, optionally at least
six, of the miRNAs listed in Table Ia, Ic, IIa and/or Table IIc
and/or Table Va, Vc, VIa and/or Table VIc, and/or at least an
inhibitor of the expression of at least one, optionally at least
six, of the miRNAs listed in Table Ia, Ic, IIa and/or Table IIc
and/or Table Va, Vc, VIa and/or Table VIc.
[0095] In a sixty-first aspect, according to the preceding aspect,
the compound comprises a therapeutically effective quantity of at
least one of the miRNAs listed in Table Ia, Ic, IIa and/or Table
IIc and/or Table Va, Vc, VIa and/or Table VIc.
[0096] A sixty-second aspect concerns a pharmaceutical compound for
treating an individual in whom has been diagnosed a pulmonary
tumour or in whom a risk of developing a pulmonary tumour has been
identified, respectively for treatment of the pulmonary tumour or
for reducing and/or eliminating the risk of developing a pulmonary
tumour, the compound comprising: at least one, optionally at least
six, of the miRNAs listed in Table Ib, Id, IIb and/or Table IId,
and/or Table Vb, Vd, VIb and/or Table VId, and/or at least an
inhibitor of the expression of at least one, optionally of at least
six, of the miRNAs listed in Table Ib, Id, IIb and/or Table Hd,
and/or Table Vb, Vd, VIb and/or Table VId.
[0097] In a sixty-third aspect, according to the preceding aspect,
the compound comprises a therapeutically effective quantity of at
least one, optionally of at least six, of the miRNAs listed in
Table Ib, Id, Ith and/or Table IId, and/or Table Vb, Vd, VIb and/or
Table VId.
[0098] In a sixty-fourth aspect in accordance with any one of
aspects from the 60.sup.th to the 63.sup.rd, the quantity is able,
for the miRNAs that are under-expressed with respect to the
respective control level of expression, to restore the values of
the level of expression to the respective control level of
expression.
[0099] In a sixty-fifth aspect in accordance with any one of
aspects from the 60.sup.th to the 64.sup.th, the therapeutically
effective quantity comprises miRNA of Table Ia, Ic, IIa and/or
Table IIc and/or Table Va, Vc, VIa and/or Table VIc, optionally the
therapeutically effective quantity comprises the miRNA of Table Ib,
Id, Ith and/or Table IId, and/or Table Vb, Vd, VIb and/or Table
VId, chemically synthesized or recombinant.
[0100] In a sixty-sixth aspect in accordance with any one of
aspects from the 60.sup.th to the 64.sup.th, the compound comprises
a therapeutically effective quantity of the inhibitor of the
expression of at least one of the miRNAs listed in Table Ia, Ic,
IIa and/or Table IIc and/or Table Va, Vc, VIa and/or Table Vic,
optionally all those listed in Table Ib, Id, IIb and/or Table IId,
and/or Table Vb, Vd, VIb and/or Table VId, the quantity being able,
for the over-expressed miRNAs with respect to the respective
control level of expression, to reduce the values of the level of
expression to the respective control level of expression.
[0101] In a sixty-seventh aspect in accordance with the preceding
aspect, the inhibitor comprises double-filament RNA, optionally
short interfering RNA (siRNA), and/or antisense nucleic acids,
and/or enzymatic RNA molecules (ribozymes).
[0102] In a sixty-eighth aspect in accordance with one of the
preceding two aspects, the inhibitor is directed to a specific
product of microRNA and interferes with the expression (by means of
inhibition of translation or induction of degradation) of a target
gene of the microRNA.
[0103] In a sixty-ninth aspect, a pharmaceutical compound is
provided according to any one of claims from the 60.sup.th to the
68.sup.th, for preparation of a medicament usable in one of the
therapeutic methods of any one of aspects from the 48.sup.th to
59.sup.th.
[0104] In a seventieth aspect in accordance with the preceding
aspect the therapeutic method is a method for treating an
individual in whom a presence of a pulmonary tumour has been
diagnosed.
[0105] In a seventy-first aspect in accordance with the
sixty-ninth, the therapeutic method is a method for treating an
individual in whom a risk of developing a pulmonary tumour has been
identified, in order to reduce and/or eliminate the risk of
developing the pulmonary tumour.
[0106] In a seventy-second aspect, in accordance with any one of
the preceding aspects, as a variant of the invention and
alternatively to the real ratios (in the method, the medical kit
and the apparatus) real differences are determined by performing
the difference between the measured values of the expression levels
of a predetermined number of pairs of the molecules of microRNA. In
this case each of the differences is compared with a respective
control value in order to determine the differences which deviate
from the respective control value.
[0107] All the preceding aspects are equally applied by replacing
the real ratios with real differences between the pairs of miRNA as
in the appended tables.
[0108] Unless otherwise defined, all technical and scientific terms
used herein have the same meaning as commonly understood by one of
ordinary skill in the art to which this invention belongs. In the
specification, the singular forms also include the plural unless
the context clearly dictates otherwise. Although methods and
materials similar or equivalent to those described herein can be
used in the practice or testing of the present invention, suitable
methods and materials are described below. All publications, patent
applications, patents, and other references mentioned herein are
incorporated by reference. The references cited herein are not
admitted to be prior art to the claimed invention. In the case of
conflict, the present specification, including definitions, will
control. In addition, the materials, methods, and examples are
illustrative only and are not intended to be limiting.
[0109] Other features and advantages of the invention will be
apparent from the following detailed description and claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0110] FIG. 1 is a schematic showing the clinical-pathological
characteristics of patients from training and validation sets
selected for miRNA expression analysis in plasma samples.
[0111] FIG. 2 is a graph showing a Kaplan-Meier survival curve of
patients with or without the signature of risk of aggressive
disease.
[0112] FIG. 3 is a graph showing a Kaplan-Meier survival curve of
patients with or without the signatures for presence of aggressive
disease.
[0113] FIG. 4 is a series of ratios and graphs showing miRNA
expression analyses in plasma samples collected before the onset
and at the time of disease. The signatures of miRNA ratios and
their direction in the analyses are listed in the tables. Panel A
shows miRNA signature of risk to develop lung cancer. Panel B shows
miRNA signature of lung cancer diagnosis. The ROC curves of samples
belonging to the validation set are shown. Panel C shows
Kaplan-Meier survival curves of patients with miRNA signatures of
risk of aggressive disease (RAD) in plasma samples collected 1-2 y
before CT-detection of lung cancer. Panel D shows Kaplan-Meier
survival curves of patients with miRNA signatures of presence of
aggressive disease (PAD) in plasma samples collected at the time of
CT-detected lung cancer. The RAD- or PAD-positive patients show a
significantly worse survival rate than RAD- or PAD-negative
patients (P=0.0006 and P=0.0001, respectively).
[0114] FIG. 5 is two graphs showing the risk of manifesting a
pulmonary tumor (validation set). Left Panel shows the ROC curve
when using the 15 miRNAs of Table Ito create the 30 ratios of Table
III. Right Panel shows the ROC curve when using the 6 miRNAs of
Table Ib to create the 9 ratios of Table IIb.
[0115] FIG. 6 is two graphs showing the risk of manifesting an
aggressive pulmonary tumor (validation set). Left panel shows the
ROC curve when using the 16 miRNAs of Table II to create the 28
ratios of Table IV. Right panel shows the ROC curve when using the
6 miRNAs of Table IIb to create the 9 ratios of Table IVb.
[0116] FIG. 7 is two graphs showing the risk of manifesting an
aggressive pulmonary tumor (validation set). Left panel shows the
ROC curve when using the 18 miRNAs of Table V to create the 36
ratios of Table VII. Right panel shows the ROC curve when using the
6 miRNAs of Table Vb to create the 9 ratios of Table VIIb.
[0117] FIG. 8 is two graphs showing the risk of manifesting an
aggressive pulmonary tumor (validation set). Left panel shows the
ROC curve when using the 10 miRNAs of Table VI to create the 16
ratios of Table VIII. Right panel shows the ROC curve when using
the 6 miRNAs of Table VIb to create the 9 ratios of Table
VIIIb.
[0118] FIG. 9 is a graph showing the expression levels of
mir-486-5p and mir-660 in 20 paired tumor and normal lung tissue of
the same patients.
[0119] FIG. 10 is a graph showing the results of a proliferation
assay performed on A549-GFP cells transfected with the miRNA mimic
mir-486-5p and mir-660.
[0120] FIG. 11 is a graph showing the results of a migration assay
performed on A549-GFP cells transfected with the miRNA mimic
mir-486-5p and mir-660.
[0121] FIG. 12 is two graph showing Kaplan-Meier estimates of
observed 5-y survival in CT-screening INT-IEO trial. Panel A shows
data arranged according to the extent of disease: 92% for stage I
(95% CI: 70.0-97.8) and 7% for stage II-IV (95% CI: 0.5-27.5,
P<0.001). Panel B shows data arranged according to the year of
CT-detection: 77% for lung cancers detected in the first 2 y of the
study (95% CI: 53.7-89.8) and 36% for lung cancers diagnosed from
third to fifth years (95% CI: 13.7-58.7, P=0.005).
[0122] FIG. 13 is an illustration showing clustering analysis on 24
normal lung tissue samples using miRNAs differentially expressed
between patients with tumors detected in the first 2 y and those of
later years of screening. Clinical status of the patient (0=alive,
1=dead), tumor stage, and year of tumor detection are reported in
columns A, B, and C, respectively.
[0123] FIG. 14A is a diagram showing sample collection and analysis
in the training set. FIG. 14B is a diagram showing sample
collection and analysis in the validation set. FIG. 14C is a
diagram showing sample collection and analysis in an enlarged data
set.
[0124] FIG. 15 is a series of graphs showing consistency of miRNA
expression measurement in plasma samples by quantitative real-time
PCR considering only the 100 miRNAs selected for class comparison
analysis. Panel A shows that technical duplicates were performed
for two patient samples (341 and 380) and for a control pool (M2).
The graphical representation was performed plotting the first miRNA
values obtained on abscissa (duplicate A) and the values obtained
in the second evaluation in ordinate (duplicate B). The linear
regression value shows a good reproducibility of measurements.
Panel B shows the correlation between two different control pools.
Panel C is a graphical representation of average values of all
Pearson correlation coefficients between control pools, technical
duplicates, and between all patient samples (before and at time of
disease.
[0125] FIG. 16A is graph showing the number of miRNA and ratio of
miRNA for a signature of risk. FIG. 16B is graph showing the number
of miRNA and ratio of miRNA for a signature of aggressive risk.
FIG. 16C is graph showing the number of miRNA and ratio of miRNA
for a signature of diagnosis. FIG. 16D is graph showing the number
of miRNA and ratio of miRNA for a signature of aggressive
disease.
[0126] FIG. 17 is a flow-chart illustrating the use of miRNA and
the ratio of miRNA from a patient in the signatures of risk,
aggressive risk, diagnosis and aggressive disease.
DETAILED DESCRIPTION OF THE INVENTION
[0127] The present invention provides methods comprising
determining the level of expression of at least two miRNA, or at
least six miRNA, from the miRNA listed in Tables Ia, Ic, IIa, IIc,
Va, Vc, VIa, or VIc in a biological sample from a subject, and
comparing the level of expression of said miRNA from said sample
from said subject to the level of expression of said miRNA from a
control biological sample.
[0128] The present invention provides methods comprising
determining the level of expression of at least two miRNA, or at
least six miRNA, listed in Table Ib or Id in a biological sample
from a subject, and comparing the level of expression of said miRNA
from said sample from said subject to the level of expression of
said miRNA from a control biological sample, wherein a change or
deviation in the level of expression of said at least two miRNA in
said biological sample from said control biological sample
identifies a subject at risk of manifesting a tumor. Preferably,
the miRNA can be the miRNA listed in Table Ie. Preferably, the
tumor cannot be detected by CT spiral scan.
[0129] The present invention provides methods comprising
determining the level of expression of at least two miRNA, or at
least six miRNA, listed in Table IIb or IId in a biological sample
from a subject, and comparing the level of expression of said miRNA
from said sample from said subject to the level of expression of
said miRNA from a control biological sample, wherein a change or
deviation in the level of expression of said at least two miRNA in
said biological sample from said control biological sample
identifies a subject at risk of manifesting an aggressive tumor.
Preferably, the miRNA can be the miRNA listed in Tables IIe, IIf or
IIg.
[0130] The present invention provides methods comprising
determining the level of expression of at least two miRNA, or at
least six miRNA, listed in Table Vb or Vd in a biological sample
from a subject, and comparing the level of expression of said miRNA
from said sample from said subject to the level of expression of
said miRNA from a control biological sample, wherein a change or
deviation in the level of expression of said at least two miRNA in
said biological sample from said control biological sample
determines the presence of a tumor in said subject. Preferably, the
miRNA can be the miRNA listed in Tables Ve or Vf. Preferably, the
determination of the presence of said tumor confirms detection by
CT spiral scan.
[0131] The present invention provides methods comprising
determining the level of expression of at least two miRNA, or at
least six miRNA, listed in Table VIb or VId in a biological sample
from a subject, and comparing the level of expression of said miRNA
from said sample from said subject to the level of expression of
said miRNA from a control biological sample, wherein a change or
deviation in the level of expression of said at least two miRNA in
said biological sample from said control biological sample
determines the presence of an aggressive tumor in said subject.
Preferably, the miRNA can be the miRNA listed in Tables VIe or VIf.
Preferably, the determination provides a prognosis of disease-free
survival following surgical intervention.
[0132] The methods of the present invention can further comprise
calculating a plurality of real quotients by determining a ratio
between the level of expression of at least one pair of miRNA from
at least two miRNA, or at least six miRNA, listed in Tables Ia, Ic,
IIa, IIc, Va, Vc, VIa, or VIc; comparing each of the real quotients
with a respective control value; and determining the real quotients
which deviate from the respective control quotient value.
[0133] The methods of the present invention can further comprise
calculating a plurality of real quotients by determining a ratio
between the level of expression of at least one pair of miRNA from
at least two miRNA, or at least six miRNA, listed in Tables Ib, Id,
IIb, IId, Vb, Vd, VIb or VId; comparing each of the real quotients
with a respective control value; and determining the real quotients
which deviate from the respective control quotient value.
Preferably, the miRNA can be the miRNA listed in Table Ie, IIe,
IIf, IIg, Ve, Vf, VIe or VIf.
[0134] The methods of the present invention can further comprise
determining a number or percentage of real quotients which deviate
from the respective control value.
[0135] The methods of the present invention can further comprise
defining as an individual at risk an individual for whom at least a
predetermined number or a predetermined percentage of the real
quotients deviates with respect to the respective control quotient
value.
[0136] For each of the calculated quotients a respective control
quotient is associated, represented by a ratio of the levels of
expression for the miRNA in a control biological sample relative to
a biological sample of a same type.
[0137] The methods of the present invention can further comprise
correlating the deviation of a predetermined number or a
predetermined percentage of levels of expression with respect to
the corresponding control criteria to a presence or absence of risk
that the individual might clinically present with a tumor in a
predetermined time.
[0138] The individual might clinically present an aggressive tumor
in a predetermined time. The predetermined time is between one and
three years. Preferably, the predetermined time is within 28
months.
[0139] Calculating the plurality of real quotients comprises using
the expression level of at least two miRNA, or at least six miRNA,
listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc. Calculating
the plurality of real quotients comprises determining a
predetermined number or a predetermined percentage of quotients
from among the levels of expression, wherein the quotients are
selected from at least one of the quotients, at least two of the
quotients, at least six of the quotients, as listed in Tables IIa,
IIc, IVa, IVc, VIIa, VIIc, VIIIa, or VIIIc. At least 20%, 30%, 50%
or 100% of the real quotients listed in Tables IIIa, IIIc, IVa,
IVc, VIIa, VIIc, VIIIa, or VIIIc can be determined The quotients
can be selected from the quotients as listed in Tables IIIb, IIId,
IVb, IVd, VIIb, VIId, VIIIb, or VIIId.
[0140] The methods of the present invention can further comprise
defining as an individual at risk of a tumor, an individual for
whom at least 20%, 30%, 50% or 100% of the real quotients
calculated deviate with respect to the respective control quotient
value. The individual is at risk of a tumor between one to three
years from a collection of the biological sample. The tumor can be
an aggressive tumor.
[0141] The methods of the present invention can further comprise
defining as an individual presenting a tumor, an individual for
whom at least 20%, 30%, 50%, 60% or 100% of the real quotients
calculated deviate with respect to the respective control quotient
value. The tumor can be an aggressive tumor.
[0142] The tumor is a pulmonary tumor. The pulmonary tumor can be
small-cell lung cancer (SCLC), non small-cell lung cancer (NSCLC),
pulmonary adenocarcinoma (ADC), bronchio-alveolar carcinoma (BAC),
squamous-cell lung carcinoma (SCC) or large-cell carcinoma
(LC).
[0143] The biological sample is a biological fluid. The biological
fluid can be whole blood, a fraction of blood, plasma or serum. The
biological sample originates from a smoker individual who, at the
moment of the collection of the sample, does not present a
pulmonary tumor if subjected to imaging diagnostic methods, in
particular the smoker individual not presenting nodules of
dimensions of greater than 5 mm if subjected to a spiral CT
scan.
[0144] The control biological sample is a biological sample from a
disease-free subject. The control biological sample is a biological
sample obtained from said subject at a previous time. The control
biological sample is obtained from said subject up to three years
preceding diagnosis. The control biological sample is a biological
sample obtained from a different tissue from said subject.
[0145] As used herein, an "individual", "subject", "patient" or
"subject in need thereof" is an individual having an risk of
developing a tumor or an aggressive tumor or one who may have or
may be afflicted with a tumor or aggressive tumor. These terms may
be utilized interchangeably. Preferably, the individual is a
mammal. The mammal can be e.g., any mammal, e.g., a human, primate,
bird, mouse, rat, fowl, dog, cat, cow, horse, goat, camel, sheep or
a pig. Preferably, the mammal is a human.
[0146] As used herein, MicroRNA or miRNA is small, non-coding, RNA
molecules (length 19-25 nucleotides). In particular, reference is
made to miRNA present in biological samples of human tissue, for
example whole blood, plasma, serum, saliva or bronchial
condensate.
[0147] Signature of Risk
[0148] The present invention provides methods including:
determining the level of expression of the six miRNA listed in
Table Ib or Id in a biological sample from a subject, and comparing
the level of expression of said miRNA from said sample from said
subject to the level of expression of said miRNA from a control
biological sample, wherein a change or deviation in the level of
expression of said at least six miRNA in said biological sample
from said control biological sample identifies a subject at risk of
manifesting a tumor. Preferably, the tumor cannot be detected by CT
spiral scan.
[0149] The method can further include: calculating a plurality of
real quotients by determining a ratio between the level of
expression of at least one pair of miRNA from at least six miRNA
listed in Table Ib or Id; comparing each of the real quotients with
a respective control value; and determining the real quotients
which deviate from the respective control quotient value.
[0150] The present invention provides miRNAs, in particular those
of appended Table Ia or Ic, as molecular biomarkers for the
evaluation of the risk of manifesting pulmonary tumours within 1-3
years from the sample collection of biological fluid. The present
invention also provides that the ratios among the miRNA expression
values are ideal molecular biomarkers for investigation into the
evaluation of the risk of contracting a pulmonary tumour within 1-3
years from the sample collection of biological fluid, such as whole
blood, serum, plasma, saliva or bronchial condensate.
[0151] As used herein, an individual at risk of tumour (aggressive
or not according to the case studies): an individual who in the
time of reference (1-3 years) following the collection of the
biological sample has a risk of over 80% of developing a tumour,
for example a pulmonary tumour, detectable using techniques such as
spiral CT.
[0152] Using the expression levels of the miRNAs listed in Table Ia
or Ic, the ratios were identified among the values measured of the
expression levels relative to the pairs of microRNA listed in Table
IIIa or IIIc. These ratios can be used for the evaluation of the
risk of contracting pulmonary tumour within 1-3 years from the
collection of the sample of biological fluid, giving extremely
reliable prediction results.
[0153] In more detail, by calculating a sufficient number of real
ratios selected from among those in Table IIIa or Inc, for example
at least 20% of them, and optionally at least 50%, it is possible
to observe the progress with respect to control ratios. An
individual is defined at high risk of pulmonary tumour, which might
be detectable by spiral CT, in a period comprised between one and
three years from the collection of the sample of biological fluid,
for whom at least 30% of real ratios calculated deviates with
respect to the respective value of the control ratio.
TABLE-US-00001 TABLE Ia One set of miRNAs used for evaluation of
the risk of manifesting a pulmonary tumour (within 1-3 years from
collecting the sample of biological fluid). miRNA hsa-miR-451
hsa-miR-320 hsa-miR-660 hsa-miR-92a hsa-miR-106a hsa-miR-140-5p
hsa-miR-15b hsa-miR-17 hsa-miR-197 hsa-miR-19b hsa-miR-221
hsa-miR-28-3p hsa-miR-30b hsa-miR-30c hsa-miR-145
[0154] Comparing the miRNAs listed in Table Ia in pre-disease
patient samples v. disease free samples (control) results showed a
sensitivity of 83.3 (training sensitivity of 85.0; validation
sensitivity of 81.3) and a specificity of 95.5 (training
specificity of 85.7; validation specificity of 100.0).
TABLE-US-00002 TABLE Ib One set of preferred miRNAs used for
evaluation of the risk of manifesting a pulmonary tumour (within
1-3 years from collecting the sample of biological fluid). miRNA
hsa-miR-451 hsa-miR-320 hsa-miR-660 hsa-miR-197 hsa-miR-30b
hsa-miR-30c
[0155] Comparing the preferred miRNAs listed in Table Ib in
pre-disease patient samples v. disease free samples (control)
results showed a sensitivity of 80.6 (training sensitivity of 80.0;
validation sensitivity of 81.3) and a specificity of 95.5 (training
specificity of 85.7; validation specificity of 100.0).
TABLE-US-00003 TABLE Ic Another set of miRNAs used for evaluation
of the risk of manifesting a pulmonary tumour (within 1-3 years
from collecting the sample of biological fluid). miRNA hsa-miR-660
hsa-miR-451 hsa-miR-197 hsa-miR-17 hsa-miR-15b hsa-miR-106a
hsa-miR-16 hsa-miR-92a hsa-miR-19b hsa-miR-101 hsa-miR-133a
hsa-miR-28-3p hsa-miR-320 hsa-miR-126 hsa-miR-142-3p
hsa-miR-140-3p
TABLE-US-00004 TABLE Id Another set of preferred miRNAs used for
evaluation of the risk of manifesting a pulmonary tumour (within
1-3 years from collecting the sample of biological fluid). miRNA
hsa-miR-660 hsa-miR-451 hsa-miR-197 hsa-miR-17 hsa-miR-15b
hsa-miR-106a
TABLE-US-00005 TABLE Ie Another set of preferred miRNAs used for
evaluation of the risk of manifesting a pulmonary tumour (within
1-3 years from collecting the sample of biological fluid). miRNA
hsa-miR-660 hsa-miR-197
TABLE-US-00006 TABLE IIIa ratios among measured values of
expression of pairs of miRNAs used for evaluating a risk of
manifesting a pulmonary tumour (within 1-3 years from collecting
the sample of biological fluid). miRNA Pairs Q1 =
hsa-miR-30c/hsa-miR-660 Q2 = hsa-miR-30b/hsa-miR-660 Q3 =
hsa-miR-197/hsa-miR-660 Q4 = hsa-miR-17/hsa-miR-660 Q5 =
hsa-miR-28-3p/hsa-miR-660 Q6 = hsa-miR-106a/hsa-miR-660 Q7 =
hsa-miR-15b/hsa-miR-660 Q8 = hsa-miR-30c/hsa-miR-451 Q9 =
hsa-miR-30b/hsa-miR-451 Q10 = hsa-miR-197/hsa-miR-451 Q11 =
hsa-miR-145/hsa-miR-660 Q12 = hsa-miR-19b/hsa-miR-660 Q13 =
hsa-miR-17/hsa-miR-451 Q14 = hsa-miR-28-3p/hsa-miR-451 Q15 =
hsa-miR-106a/hsa-miR-451 Q16 = hsa-miR-30c/hsa-miR-320 Q17 =
hsa-miR-30b/hsa-miR-320 Q18 = hsa-miR-197/hsa-miR-320 Q19 =
hsa-miR-15b/hsa-miR-451 Q20 = hsa-miR-28-3p/hsa-miR-320 Q21 =
hsa-miR-197/hsa-miR-92a Q22 = hsa-miR-30b/hsa-miR-92a Q23 =
hsa-miR-30c/hsa-miR-92a Q24 = hsa-miR-140-5p/hsa-miR-660 Q25 =
hsa-miR-221/hsa-miR-660 Q26 = hsa-miR-19b/hsa-miR-451 Q27 =
hsa-miR-145/hsa-miR-451 Q28 = hsa-miR-17/hsa-miR-320 Q29 =
hsa-miR-106a/hsa-miR-320 Q30 = hsa-miR-15b/hsa-miR-320
TABLE-US-00007 TABLE IIIb ratios among measured values of
expression of preferred pairs of microRNAs used for evaluating a
risk of manifesting a pulmonary tumour (within 1-3 years from
collecting the sample of biological fluid). miRNA Pairs
hsa-miR-30b/hsa-miR-320 hsa-miR-30b/hsa-miR-451
hsa-miR-30b/hsa-miR-660 hsa-miR-197/hsa-miR-451
hsa-miR-197/hsa-miR-660 hsa-miR-197/hsa-miR-320
hsa-miR-30c/hsa-miR-451 hsa-miR-30c/hsa-miR-660
hsa-miR-30c/hsa-miR-320
[0156] In connection with the risk of manifesting a pulmonary
tumor, FIG. 5 shows (on the left hand side) the ROC curve when
using the 15 miRNAs of Table Ia to create the 30 ratios of Table
IIa and (on the right end side) the ROC curve when using the 6
miRNAs of Table Ib to create the 9 ratios of Table IIIb.
TABLE-US-00008 TABLE IIIc Another set of ratios among measured
values of expression of pairs of miRNAs used for evaluating a risk
of manifesting a pulmonary tumour (within 1-3 years from collecting
the sample of biological fluid). miRNA Pairs < or > 3 y
storage cut-off Q1 = hsa-miR-197/hsa-miR-660 > 3.44 Q2 =
hsa-miR-197/hsa-miR-92a > -1.72 Q3 = hsa-miR-17/hsa-miR-660 >
8.63 Q4 = hsa-miR-17/hsa-miR-92a > 3.60 Q5 =
hsa-miR-197/hsa-miR-451 > -2.45 Q6 = hsa-miR-17/hsa-miR-451 >
2.77 Q7 = hsa-miR-19b/hsa-miR-660 > 7.85 Q8 =
hsa-miR-197/hsa-miR-19b > -3.96 Q9 = hsa-miR-19b/hsa-miR-451
> 1.90 Q10 = hsa-miR-106a/hsa-miR-660 > 8.71 Q11 =
hsa-miR-106a/hsa-miR-451 > 2.87 Q12 = hsa-miR-106a/hsa-miR-92a
> 3.73 Q13 = hsa-miR-101/hsa-miR-97 < -4.59 Q14 =
hsa-miR-101/hsa-miR-17 < -9.73 Q15 = hsa-miR-133a/hsa-miR-660
> -0.11 Q16 = hsa-miR-133a/hsa-miR-451 > -5.49 Q17 =
hsa-miR-101/hsa-miR-133a < -1.34 Q18 = hsa-miR-16/hsa-miR-660
> 8.78 Q19 = hsa-miR-16/hsa-miR-451 > 2.38 Q20 =
hsa-miR-140-3p/hsa-miR-660 > -0.31 Q21 =
hsa-miR-101/hsa-miR-140-3p < -0.11 Q22 = hsa-miR-15b/hsa-miR-451
> -1.40 Q23 = hsa-miR-15b/hsa-miR-660 > 4.77 Q24 =
hsa-miR-142-3p/hsa-miR-15b < 2.71 Q25 = hsa-miR-126/hsa-miR-660
> 8.08 Q26 = hsa-miR-28-3p/hsa-miR-660 > 3.18 Q27 =
hsa-miR-320/hsa-miR-660 > 6.39
[0157] Reducing the number of microRNAs and ratios (from the
27.sup.th to the 1.sup.st), the shorter signatures were tested on
the validation set, analyzing their power using the mean percent of
correct classification among 6 different methods of class
prediction analysis:, Compound Covariate Predictor, Diagonal Linear
Discriminant Analysis, 1-Nearest Neighbor, 3-Nearest Neighbors,
Nearest Centroid and Support Vector Machines. The results are shown
in FIG. 16a.
TABLE-US-00009 TABLE IIId Another set of ratios among measured
values of expression of preferred pairs of microRNAs used for
evaluating a risk of manifesting a pulmonary tumour (within 1-3
years from collecting the sample of biological fluid). miRNA Pairs
hsa-miR-197/hsa-miR-660 hsa-miR-197/hsa-miR-92a
hsa-miR-17/hsa-miR-660 hsa-miR-17/hsa-miR-92a
hsa-miR-197/hsa-miR-451 hsa-miR-17/hsa-miR-451
hsa-miR-19b/hsa-miR-660 hsa-miR-197/hsa-miR-19b
hsa-miR-19b/hsa-miR-451
[0158] As used herein, miRNA ratios are real ratios determined by
performing a ratio among the measured values of the expression
levels of predetermined pairs of molecules of microRNA.
[0159] Signature of Risk of Aggressive Disease
[0160] The present invention provides methods including:
determining the level of expression of the six miRNA listed in
Table IIb or IId in a biological sample from a subject, and
comparing the level of expression of said miRNA from said sample
from said subject to the level of expression of said miRNA from a
control biological sample, wherein a change or deviation in the
level of expression of said at least six miRNA in said biological
sample from said control biological sample identifies a subject at
risk of manifesting an aggressive tumor. Preferably, the tumor
cannot be detected by CT spiral scan.
[0161] The method can further include: calculating a plurality of
real quotients by determining a ratio between the level of
expression of at least one pair of miRNA from at least six miRNA
listed in Table IIb or IId; comparing each of the real quotients
with a respective control value; and determining the real quotients
which deviate from the respective control quotient value.
[0162] The present invention provides the miRNAs, in particular
those of appended Table IIa or IIc, as biomarkers for evaluation of
the risk of contracting aggressive pulmonary tumour within 1-3
years from the sample collection of biological fluid. Further, in
this case too, the ratios between the miRNA expression values were
specifically identified as ideal molecular biomarkers to be
investigated for the evaluation of the risk of contracting an
aggressive pulmonary tumour within 1-3 years from the sample
biological fluid collection, which might be whole blood, serum,
plasma, saliva or bronchial condensate.
[0163] Further, by using the miRNA expression levels of Table IIa
or IIc, the ratios were identified between measure values of
expression levels relative to pairs of microRNAs of Table IVa or
IVc for evaluation of the risk of contracting an aggressive
pulmonary tumour within 1-3 years from the sample collection of
biological fluid. In more detail, by calculating a sufficient
number of real ratios selected from among the ratios of Table IVa
or IVc, for example at least 30%, and optionally at least 50%, the
progression of the ratios with respect to control ratios can be
studied.
[0164] An individual is defined as at risk of contracting an
aggressive pulmonary tumour in a period comprised between one and
three years from the collection of the sample of biological fluid,
if in that individual at least 50%, optionally at least 75%, of the
real ratios calculated deviate with respect to the respective
control ratio value.
[0165] As used herein, an aggressive tumour is a tumour, for
example a pulmonary tumour, with a lethal prognosis or capable of
causing death in 90% of patients within five years from diagnosis
of the disease.
[0166] The use of miRNA ratios also enables reliably predicting the
development of pulmonary tumour, in particular of the more
aggressive form, in high-risk individuals (more than 50 years of
age and heavy smokers) up to two years before the disease is at a
visible stage with the better imaging techniques at present
available (spiral CT). Note also that the method using the
calculation of the ratios, or miRNA ratios, described above can be
actuated with a simple collection of a blood sample and is
therefore entirely non-invasive, and allows the analysis to be
performed rapidly and economically.
TABLE-US-00010 TABLE IIa microRNAs used for evaluation of the risk
of manifesting an aggressive pulmonary tumour (within 1-3 years
from collecting the sample of biological fluid). miRNA hsa-miR-660
hsa-miR-140-5p hsa-miR-486-5p hsa-miR-197 hsa-miR-221 hsa-miR-451
hsa-miR-28-3p hsa-miR-148a hsa-miR-19b hsa-miR-15b hsa-miR-30c
hsa-miR-30b hsa-miR-101 hsa-miR-21 hsa-miR-140-3p
hsa-miR-142-3p
[0167] Comparing the miRNAs listed in Table IIa in pre-disease
patient samples of aggressive lung cancer v. pre-disease samples of
indolent lung cancer and disease free samples (control) results
showed a sensitivity of 94.5 (training sensitivity of 90.9;
validation sensitivity of 100.0) and a specificity of 97.6
(training specificity of 100.0; validation specificity of
96.0).
TABLE-US-00011 TABLE IIb preferred microRNAs used for evaluation of
the risk of manifesting an aggressive pulmonary tumour (within 1-3
years from collecting the sample of biological fluid). miRNA
hsa-miR-660 hsa-miR-486-5p hsa-miR-221 hsa-miR-28-3p hsa-miR-148a
hsa-miR-19b
[0168] Comparing the miRNAs listed in Table IIb in pre-disease
patient samples of aggressive lung cancer v. pre-disease samples of
indolent lung cancer and disease free samples (control) results
showed a sensitivity of 94.5 (training sensitivity of 90.9;
validation sensitivity of 100.0) and a specificity of 95.0
(training specificity of 100.0; validation specificity of
92.0).
TABLE-US-00012 TABLE IIc Another set of microRNAs used for
evaluation of the risk of manifesting an aggressive pulmonary
tumour (within 1-3 years from collecting the sample of biological
fluid). miRNA hsa-miR-21 hsa-miR-451 hsa-miR-197 hsa-miR-17
hsa-miR-15b hsa-miR-106a hsa-miR-16 hsa-miR-92a hsa-miR-19b
hsa-miR-101 hsa-miR-145 hsa-miR-28-3p hsa-miR-30c hsa-miR-320
hsa-miR-126 hsa-miR-221 hsa-miR-148a hsa-miR-30b hsa-miR-140-3p
TABLE-US-00013 TABLE IId Another set of preferred microRNAs used
for evaluation of the risk of manifesting an aggressive pulmonary
tumour (within 1-3 years from collecting the sample of biological
fluid). miRNA hsa-miR-21 hsa-miR-451 hsa-miR-197 hsa-miR-17
hsa-miR-15b hsa-miR-106a
TABLE-US-00014 TABLE IIe Another set of preferred microRNAs used
for evaluation of the risk of manifesting an aggressive pulmonary
tumour (within 1-3 years from collecting the sample of biological
fluid). miRNA hsa-miR-197 hsa-miR-451
TABLE-US-00015 TABLE IIf Another set of preferred microRNAs used
for evaluation of the risk of manifesting an aggressive pulmonary
tumour (within 1-3 years from collecting the sample of biological
fluid). miRNA hsa-miR-197 hsa-miR-101
TABLE-US-00016 TABLE IIg Another set of preferred microRNAs used
for evaluation of the risk of manifesting an aggressive pulmonary
tumour (within 1-3 years from collecting the sample of biological
fluid). miRNA hsa-miR-197 hsa-miR-28-3p hsa-miR-451 hsa-miR-101
TABLE-US-00017 TABLE IVa ratios among measured values of expression
of pairs of microRNAs used for determining a risk of manifesting an
aggressive pulmonary tumour (within 1-3 years from collecting the
sample of biological fluid). miRNA Pairs Q1 =
hsa-miR-221/hsa-miR-660 Q2 = hsa-miR-221/hsa-miR-486-5p Q3 =
hsa-miR-221/hsa-miR-451 Q4 = hsa-miR-140-3p/hsa-miR-221 Q5 =
hsa-miR-21/hsa-miR-221 Q6 = hsa-miR-101/hsa-miR-221 Q7 =
hsa-miR-197/hsa-miR-660 Q8 = hsa-miR-197/hsa-miR-486-5p Q9 =
hsa-miR-140-5p/hsa-miR-660 Q10 = hsa-miR-140-5p/hsa-miR-486-5p Q11
= hsa-miR-140-5p/hsa-miR-19b Q12 = hsa-miR-142-3p/hsa-miR-660 Q13 =
hsa-miR-148a/hsa-miR-660 Q14 = hsa-miR-148a/hsa-miR-486-5p Q15 =
hsa-miR-148a/hsa-miR-19b Q16 = hsa-miR-148a/hsa-miR-451 Q17 =
hsa-miR-15b/hsa-miR-660 Q18 = hsa-miR-15b/hsa-miR-486-5p Q19 =
hsa-miR-15b/hsa-miR-19b Q20 = hsa-miR-19b/hsa-miR-221 Q21 =
hsa-miR-19b/hsa-miR-30c Q22 = hsa-miR-28-3p/hsa-miR-660 Q23 =
hsa-miR-28-3p/hsa-miR-486-5p Q24 = hsa-miR-30b/hsa-miR-660 Q25 =
hsa-miR-30b/hsa-miR-486-5p Q26 = hsa-miR-30c/hsa-miR-660 Q27 =
hsa-miR-30c/hsa-miR-486-5p Q28 = hsa-miR-19b/hsa-miR-28-3p
TABLE-US-00018 TABLE IVb ratios among measured values of expression
of preferred pairs of microRNAs used for determining a risk of
manifesting an aggressive pulmonary tumour (within 1-3 years from
collecting the sample of biological fluid). miRNA Pairs
hsa-miR-221/hsa-miR-660 hsa-miR-28-3p/hsa-miR-660
hsa-miR-19b/hsa-miR-221 hsa-miR-19b/hsa-miR-28-3p
hsa-miR-148a/hsa-miR-19b hsa-miR-148a/hsa-miR-486-5p
hsa-miR-28-3p/hsa-miR-486-5p hsa-miR-221/hsa-miR-486-5p
hsa-miR-148a/hsa-miR-660
[0169] In connection with the risk of manifesting an aggressive
pulmonary tumor, FIG. 6 shows (on the left hand side) the ROC curve
when using the 16 miRNAs of Table IIa to create the 28 ratios of
Table IVa and (on the right end side) the ROC curve when using the
6 miRNAs of Table IIb to create the 9 ratios of Table IVb.
TABLE-US-00019 TABLE IVc Another set of ratios among measured
values of expression of pairs of microRNAs used for determining a
risk of manifesting an aggressive pulmonary tumour (within 1-3
years from collecting the sample of biological fluid). miRNA Pairs
< or > 3y storage cut-off Q1 = hsa-miR-101/hsa-miR-197 <
-4.51 Q2 = hsa-miR-197/hsa-miR-451 > -2.07 Q3 =
hsa-miR-101/hsa-miR-28-3p < -4.42 Q4 = hsa-miR-28-3p/hsa-miR-451
> -2.36 Q5 = hsa-miR-197/hsa-miR-21 > -0.38 Q6 =
hsa-miR-21/hsa-miR-28-3p < 0.78 Q7 = hsa-miR-101/hsa-miR-106a
< -9.85 Q8 = hsa-miR-106a/hsa-miR-451 > 3.14 Q9 =
hsa-miR-106a/hsa-miR-21 > 4.81 Q10 = hsa-miR-16/hsa-miR-28-3p
< 4.72 Q11 = hsa-miR-16/hsa-miR-197 < 4.56 Q12 =
hsa-miR-106a/hsa-miR-16 > 0.66 Q13 = hsa-miR-101/hsa-miR-17 <
-9.74 Q14 = hsa-miR-17/hsa-miR-451 > 3.04 Q15 =
hsa-miR-17/hsa-miR-21 > 4.67 Q16 = hsa-miR-16/hsa-miR-17 <
-0.56 Q17 = hsa-miR-28-3p/hsa-miR-92a > -1.6 Q18 =
hsa-miR-197/hsa-miR-92a > -1.36 Q19 = hsa-miR-197/hsa-miR-30c
> -1.51 Q20 = hsa-miR-28-3p/hsa-miR-30c > -1.79 Q21 =
hsa-miR-320/hsa-miR-92a > 1.42 Q22 = hsa-miR-320/hsa-miR-451
> 0.66 Q23 = hsa-miR-221/hsa-miR-451 > -0.2 Q24 =
hsa-miR-21/hsa-miR-221 < -1.33 Q25 = hsa-miR-145/hsa-miR-197
< -0.96 Q26 = hsa-miR-145/hsa-miR-28-3p < -0.69 Q27 =
hsa-miR-28-3p/hsa-miR-30b > -3.47 Q28 = hsa-miR-197/hsa-miR-30b
> -3.2 Q29 = hsa-miR-19b/hsa-miR-451 > 2.19 Q30 =
hsa-miR-126/hsa-miR-451 > 2.24 Q31 = hsa-miR-15b/hsa-miR-451
> -1.2 Q32 = hsa-miR-148a/hsa-miR-197 < -3.38 Q33 =
hsa-miR-140-3p/hsa-miR-451 > -6.81
[0170] Reducing the number of microRNAs and ratios (from the
33.sup.rd to the 1.sup.st), the shorter signatures were tested on
the validation set, analyzing their power using the mean percent of
correct classification among 6 different methods of class
prediction analysis:, Compound Covariate Predictor, Diagonal Linear
Discriminant Analysis, 1-Nearest Neighbor, 3-Nearest Neighbors,
Nearest Centroid and Support Vector Machines. The results are shown
in FIG. 16b.
TABLE-US-00020 TABLE IVd Another set of ratios among measured
values of expression of preferred pairs of microRNAs used for
determining a risk of manifesting an aggressive pulmonary tumour
(within 1-3 years from collecting the sample of biological fluid).
miRNA Pairs hsa-miR-101/hsa-miR-197 hsa-miR-197/hsa-miR-451
hsa-miR-101/hsa-miR-28-3p hsa-miR-28-3p/hsa-miR-451
hsa-miR-197/hsa-miR-21 hsa-miR-21/hsa-miR-28-3p
hsa-miR-101/hsa-miR-106a hsa-miR-106a/hsa-miR-451
hsa-miR-106a/hsa-miR-21
[0171] Signature of Diagnosis
[0172] The present invention provides a method including:
determining the level of expression of the six miRNA listed in
Table Vb or Vd in a biological sample from a subject, and comparing
the level of expression of said miRNA from said sample from said
subject to the level of expression of said miRNA from a control
biological sample, wherein a change or deviation in the level of
expression of said at least six miRNA in said biological sample
from said control biological sample determines the presence of a
tumor in said subject. Preferably, determination of the presence of
said tumor confirms detection by CT spiral scan.
[0173] The method can further include: calculating a plurality of
real quotients by determining a ratio between the level of
expression of at least one pair of miRNA from at least six miRNA
listed in Table Vb or Vd; comparing each of the real quotients with
a respective control value; and determining the real quotients
which deviate from the respective control quotient value.
[0174] The present invention provides miRNAs, and in particular
those listed in Table Va or Vc, have a role as biomolecular markers
for determining the actual presence of a pulmonary tumour in an
individual, for diagnostic purposes.
[0175] The present invention also provides the ratios between
expression level values of miRNA pairs are valid biomarkers with a
diagnostic and prognostic function. In detail, the miRNAs of Table
Va or Vc were used for determining the ratios of Table VIIa or VIIc
which represent ratios between measured values of expression levels
of relative microRNA pairs and which are used to determine the
actual presence (diagnosis) of a pulmonary tumour in an individual.
In more detail, by calculating at least 20% of the real ratios of
Table VIIa or VIIc it is possible to define the individual presents
a pulmonary tumour if at least 30% of the real ratios (as in Table
VIIa or VIIc) calculated deviate from the respective control
value.
TABLE-US-00021 TABLE Va microRNAs used for determining the actual
presence of a pulmonary tumour in an individual. miRNA hsa-miR-106a
hsa-miR-140-3p hsa-miR-17 hsa-miR-660 hsa-miR-15b hsa-miR-92a
hsa-miR-451 hsa-miR-19b hsa-miR-28-3p hsa-miR-133a hsa-miR-101
hsa-miR-197 hsa-miR-145 hsa-miR-320 hsa-miR-21 hsa-miR-30b
hsa-miR-126 hsa-miR-140-5p
[0176] Comparing the miRNAs listed in Table Va in the plasma of
patients at surgery v. disease free samples (control) results
showed a sensitivity of 80.5 (training sensitivity of 84.2;
validation sensitivity of 76.5) and a specificity of 95.5 (training
specificity of 100.0; validation specificity of 93.3).
TABLE-US-00022 TABLE Vb preferred microRNAs used for determining
the actual presence of a pulmonary tumour in an individual. miRNA
hsa-miR-106a hsa-miR-17 hsa-miR-660 hsa-miR-92a hsa-miR-451
hsa-miR-197
[0177] Comparing the miRNAs listed in Table Vb in the plasma of
patients at surgery v. disease free samples (control) results
showed a sensitivity of 77.8 (training sensitivity of 84.2;
validation sensitivity of 70.6) and a specificity of 90.9 (training
specificity of 85.7; validation specificity of 93.3).
TABLE-US-00023 TABLE Vc Another set of microRNAs used for
determining the actual presence of a pulmonary tumour in an
individual. miRNA hsa-miR-660 hsa-miR-197 hsa-miR-17 hsa-miR-106a
hsa-miR-142-3p hsa-miR-92a hsa-miR-19b hsa-miR-101 hsa-miR-145
hsa-miR-28-3p hsa-miR-320 hsa-miR-126 hsa-miR-140-5p
hsa-miR-148
TABLE-US-00024 TABLE Vd Another set of preferred microRNAs used for
determining the actual presence of a pulmonary tumour in an
individual. miRNA hsa-miR-660 hsa-miR-197 hsa-miR-17 hsa-miR-106a
hsa-miR-142-3p hsa-miR-92a
TABLE-US-00025 TABLE Ve Another set of preferred microRNAs used for
determining the actual presence of a pulmonary tumour in an
individual. miRNA hsa-miR-660 hsa-miR-197
TABLE-US-00026 TABLE Vf Another set of preferred microRNAs used for
determining the actual presence of a pulmonary tumour in an
individual. miRNA hsa-miR-197 hsa-miR-106a hsa-miR-660
hsa-miR-92a
TABLE-US-00027 TABLE VIIa ratios among measured values of
expression of pairs of microRNAs used for determining an actual
presence of pulmonary tumour in an individual. miRNA Pairs Q1 =
hsa-miR-17/hsa-miR-451 Q2 = hsa-miR-106a/hsa-miR-451 Q3 =
hsa-miR-133a/hsa-miR-451 Q4 = hsa-miR-17/hsa-miR-660 Q5 =
hsa-miR-106a/hsa-miR-660 Q6 = hsa-miR-197/hsa-miR-451 Q7 =
hsa-miR-133a/hsa-miR-660 Q8 = hsa-miR-145/hsa-miR-451 Q9 =
hsa-miR-28-3p/hsa-miR-451 Q10 = hsa-miR-17/hsa-miR-92a Q11 =
hsa-miR-106a/hsa-miR-92a Q12 = hsa-miR-197/hsa-miR-660 Q13 =
hsa-miR-133a/hsa-miR-92a Q14 = hsa-miR-145/hsa-miR-660 Q15 =
hsa-miR-28-3p/hsa-miR-660 Q16 = hsa-miR-15b/hsa-miR-451 Q17 =
hsa-miR-19b/hsa-miR-451 Q18 = hsa-miR-30b/hsa-miR-451 Q19 =
hsa-miR-17/hsa-miR-320 Q20 = hsa-miR-106a/hsa-miR-320 Q21 =
hsa-miR-17/hsa-miR-21 Q22 = hsa-miR-106a/hsa-miR-21 Q23 =
hsa-miR-197/hsa-miR-92a Q24 = hsa-miR-101/hsa-miR-106a Q25 =
hsa-miR-133a/hsa-miR-320 Q26 = hsa-miR-101/hsa-miR-17 Q27 =
hsa-miR-145/hsa-miR-92a Q28 = hsa-miR-28-3p/hsa-miR-92a Q29 =
hsa-miR-106a/hsa-miR-140-3p Q30 = hsa-miR-15b/hsa-miR-660 Q31 =
hsa-miR-19b/hsa-miR-660 Q32 = hsa-miR-30b/hsa-miR-660 Q33 =
hsa-miR-126/hsa-miR-451 Q34 = hsa-miR-140-5p/hsa-miR-451 Q35 =
hsa-miR-133a/hsa-miR-21 Q36 = hsa-miR-140-3p/hsa-miR-17
TABLE-US-00028 TABLE VIIb ratios among measured values of
expression of preferred pairs of microRNAs used for determining an
actual presence of pulmonary tumour in an individual. miRNA Pairs
hsa-miR-106a/hsa-miR-660 hsa-miR-106a/hsa-miR-92a
hsa-miR-106a/hsa-miR-451 hsa-miR-17/hsa-miR-451
hsa-miR-17/hsa-miR-660 hsa-miR-17/hsa-miR-92a
hsa-miR-197/hsa-miR-451 hsa-miR-197/hsa-miR-92a
hsa-miR-197/hsa-miR-660
[0178] In connection with the determination of the actual presence
of a pulmonary tumour in an individual, FIG. 7 shows (on the left
hand side) the ROC curve when using the 18 miRNAs of Table Va to
create the 36 ratios of Table VIIa and (on the right end side) the
ROC curve when using the 6 miRNAs of Table Vb to create the 9
ratios of Table VIIb.
TABLE-US-00029 TABLE VIIc Another set of ratios among measured
values of expression of pairs of microRNAs used for determining an
actual presence of pulmonary tumour in an individual. miRNA Pairs
< or > 3y storage cut-off Q1 = hsa-miR-197/hsa-miR-660 >
3.58 Q2 = hsa-miR-197/hsa-miR-92a > -1.5 Q3 =
hsa-miR-106a/hsa-miR-92a > 3.73 Q4 = hsa-miR-106a/hsa-miR-660
> 8.87 Q5 = hsa-miR-106a/hsa-miR-197 < 4.97 Q6 =
hsa-miR-142-3p/hsa-miR-197 < 3.73 Q7 =
hsa-miR-140-5p/hsa-miR-197 < -0.03 Q8 =
hsa-miR-142-3p/hsa-miR-28-3p < 4.19 Q9 =
hsa-miR-140-5p/hsa-miR-28-3p < 0.33 Q10 =
hsa-miR-28-3p/hsa-miR-660 > 3.18 Q11 = hsa-miR-28-3p/hsa-miR-92a
> -1.79 Q12 = hsa-miR-17/hsa-miR-660 > 8.63 Q13 =
hsa-miR-17/hsa-miR-92a > 3.6 Q14 = hsa-miR-142-3p/hsa-miR-145
< 3.94 Q15 = hsa-miR-145/hsa-miR-660 > 3.76 Q16 =
hsa-miR-145/hsa-miR-92a > -1.35 Q17 = hsa-miR-197/hsa-miR-320
> -2.45 Q18 = hsa-miR-106a/hsa-miR-320 > 2.79 Q19 =
hsa-miR-17/hsa-miR-320 > 2.64 Q20 = hsa-miR-148a/hsa-miR-92a
> -4.41 Q21 = hsa-miR-148a/hsa-miR-660 > 0.76 Q22 =
hsa-miR-19b/hsa-miR-660 > 7.95 Q23 = hsa-miR-19b/hsa-miR-92a
> 2.75 Q24 = hsa-miR-101/hsa-miR-660 > -0.08 Q25 =
hsa-miR-101/hsa-miR-92a > -5.18 Q26 = hsa-miR-126/hsa-miR-660
> 8.08 Q27 = hsa-miR-126/hsa-miR-92a > 3.05
[0179] Reducing the number of microRNAs and ratios (from the
27.sup.th to the 1.sup.st), the shorter signatures were tested on
the validation set, analyzing their power using the mean percent of
correct classification among 6 different methods of class
prediction analysis:, Compound Covariate Predictor, Diagonal Linear
Discriminant Analysis, 1-Nearest Neighbor, 3-Nearest Neighbors,
Nearest Centroid and Support Vector Machines. The results are shown
in FIG. 16c.
TABLE-US-00030 TABLE VIId Another set of ratios among measured
values of expression of preferred pairs of microRNAs used for
determining an actual presence of pulmonary tumour in an
individual. miRNA Pairs hsa-miR-197/hsa-miR-660
hsa-miR-197/hsa-miR-92a hsa-miR-106a/hsa-miR-92a
hsa-miR-106a/hsa-miR-660 hsa-miR-106a/hsa-miR-197
hsa-miR-142-3p/hsa-miR-197 hsa-miR-140-5p/hsa-miR-197
hsa-miR-142-3p/hsa-miR-28-3p hsa-miR-140-5p/hsa-miR-28-3p
hsa-miR-28-3p/hsa-miR-660 hsa-miR-28-3p/hsa-miR-92a
[0180] Signature of Presence of Aggressive Disease
[0181] The present invention provides a method including:
determining the level of expression of the six miRNA listed in
Table VIb or VId in a biological sample from a subject, and
comparing the level of expression of said miRNA from said sample
from said subject to the level of expression of said miRNA from a
control biological sample, wherein a change or deviation in the
level of expression of said at least six miRNA in said biological
sample from said control biological sample determines the presence
of an aggressive tumor in said subject. Preferably, the
determination provides a prognosis of disease-free survival
following surgical intervention.
[0182] The method can further include: calculating a plurality of
real quotients by determining a ratio between the level of
expression of at least one pair of miRNA from at least six miRNA
listed in Table VIb or VId; comparing each of the real quotients
with a respective control value; and determining the real quotients
which deviate from the respective control quotient value.
[0183] The present invention provides miRNAs, and in particular
those listed in Table VIa or VIc, that can be used as biomolecular
markers for determining the actual presence of an aggressive
pulmonary tumour in an individual (prognosis). The present
invention demonstrates in particular the ratios between values of
expression levels of miRNA pairs are valid biomarkers with a
diagnostic and prognostic function even in the case of an
aggressive tumour.
[0184] In detail, the miRNAs of Table VIa and VIc were used to
determine the ratios of Table VIIIa and VIIIc where there is a list
of ratios between the measured values of the expression levels
relative to microRNA pairs of Table VIa and VIc used for
determining the actual presence of an aggressive pulmonary tumour
in an individual. In detail, by detecting at least 20% of the real
ratios of Table VIIIa and VIIIc, it is possible to define an
individual having an aggressive pulmonary tumour as one in whom at
least 60% of the real ratios that have been calculated deviate with
respect to the respective control value.
[0185] Thus the use of the described procedure can help also to
resolve the problem of overdiagnosis and overtreatment in patients
who are not at risk.
[0186] In greater detail, in a context of surveillance of the
disease using spiral CT, the use of a test based on this method
might enable selection of only a sub-group of patients at high risk
of developing the disease to be subsequently kept under a more
strict control. Further, the ability of the test to predict the
patients who will develop a more aggressive disease, frequently not
diagnosed by the CT scan, enables directing these individuals
directly to specific pharmacological programmes (including giving
up smoking) and/or the use of more specific diagnostic examinations
based on the metabolic-biological characteristics such as PET with
various tracers or body MRI, or a different local treatment such as
stereotaxic radiotherapy, or other treatments besides. The use of
miRNA ratios is an easily-applicable method with a potential
current clinical use and which avoids the use of more profound and
complex analysis.
TABLE-US-00031 TABLE VIa microRNAs used for determining the actual
presence of an aggressive pulmonary tumour in an individual. miRNA
hsa-miR-142-3p hsa-miR-148a hsa-miR-15b hsa-miR-21 hsa-miR-221
hsa-miR-660 hsa-miR-19b hsa-miR-486-5p hsa-miR-30b hsa-miR-16
[0187] Comparing the miRNAs listed in Table VIa in patient samples
of aggressive lung cancer v. pre-disease samples of indolent lung
cancer and disease free samples (control) results showed a
sensitivity of 86.7 (training sensitivity of 80.0; validation
sensitivity of 100.0) and a specificity of 93.2 (training
specificity of 94.0; validation specificity of 92.6).
TABLE-US-00032 TABLE VIb preferred microRNAs used for determining
the actual presence of an aggressive pulmonary tumour in an
individual. miRNA hsa-miR-142-3p hsa-miR-21 hsa-miR-221 hsa-miR-660
hsa-miR-19b hsa-miR-486-5p
[0188] Comparing the miRNAs listed in Table VIb in patient samples
of aggressive lung cancer v. pre-disease samples of indolent lung
cancer and disease free samples (control) results showed a
sensitivity of 80.0 (training sensitivity of 80.0; validation
sensitivity of 80.0) and a specificity of 93.2 (training
specificity of 94.0; validation specificity of 92.6).
TABLE-US-00033 TABLE VIc Another set of microRNAs used for
determining the actual presence of an aggressive pulmonary tumour
in an individual. miRNA hsa-miR-660 hsa-miR-197 hsa-miR-17
hsa-miR-106a hsa-miR-142-3p hsa-miR-92a hsa-miR-19b hsa-miR-101
hsa-miR-145 hsa-miR-28-3p hsa-miR-451 hsa-miR-126 hsa-miR-140-5p
hsa-miR-148a hsa-miR-486-5p hsa-miR-21 hsa-miR-16 hsa-miR-30b
hsa-miR-30c hsa-miR-15b
TABLE-US-00034 TABLE VId Another set of preferred microRNAs used
for determining the actual presence of an aggressive pulmonary
tumour in an individual. miRNA hsa-miR-660 hsa-miR-197 hsa-miR-17
hsa-miR-106a hsa-miR-142-3p hsa-miR-92a
TABLE-US-00035 TABLE VIe Another set of preferred microRNAs used
for determining the actual presence of an aggressive pulmonary
tumour in an individual. miRNA hsa-miR-451 hsa-miR-197
TABLE-US-00036 TABLE VIf Another set of preferred microRNAs used
for determining the actual presence of an aggressive pulmonary
tumour in an individual. miRNA hsa-miR-197 hsa-miR-486-5p
hsa-miR-451
TABLE-US-00037 TABLE VIIIa ratios among measured values of
expression of pairs of microRNAs used for determining an actual
presence of aggressive pulmonary tumour in an individual. miRNA
Pairs Q1 = hsa-miR-142-3p/hsa-miR-486-5p Q2 =
hsa-miR-21/hsa-miR-486-5p Q3 = hsa-miR-221/hsa-miR-486-5p Q4 =
hsa-miR-19b/hsa-miR-21 Q5 = hsa-miR-19b/hsa-miR-221 Q6 =
hsa-miR-142-3p/hsa-miR-19b Q7 = hsa-miR-148a/hsa-miR-486-5p Q8 =
hsa-miR-15b/hsa-miR-486-5p Q9 = hsa-miR-30b/hsa-miR-486-5p Q10 =
hsa-miR-142-3p/hsa-miR-660 Q11 = hsa-miR-221/hsa-miR-660 Q12 =
hsa-miR-148a/hsa-miR-19b Q13 = hsa-miR-15b/hsa-miR-19b Q14 =
hsa-miR-19b/hsa-miR-30b Q15 = hsa-miR-16/hsa-miR-486-5p Q16 =
hsa-miR-21/hsa-miR-660
TABLE-US-00038 TABLE VIIIb ratios among measured values of
expression of preferred pairs of microRNAs used for determining an
actual presence of aggressive pulmonary tumour in an individual.
miRNA Pairs Q1 = hsa-miR-hsa-miR-142-3p/hsa-miR-660
hsa-miR-142-3p/hsa-miR-19b hsa-miR-21/hsa-miR-660
hsa-miR-221/hsa-miR-660 hsa-miR-19b/hsa-miR-21
hsa-miR-19b/hsa-miR-221 hsa-miR-142-3p/hsa-miR-486-5p
hsa-miR-221/hsa-miR-486-5p hsa-miR-21/hsa-miR-486-5p
[0189] In connection with the determination of the actual presence
of an aggressive pulmonary tumour in an individual, FIG. 8 shows
(on the left hand side) the ROC curve when using the 10 miRNAs of
Table VIa to create the 16 ratios of Table VIIIa and (on the right
end side) the ROC curve when using the 6 miRNAs of Table VIb to
create the 9 ratios of Table VIIIb.
TABLE-US-00039 TABLE VIIIc Another set of ratios among measured
values of expression of pairs of microRNAs used for determining an
actual presence of aggressive pulmonary tumour in an individual.
miRNA Pairs < or > 3y storage cut-off Q1 =
hsa-miR-197/hsa-miR-451 > -1.76 Q2 = hsa-miR-197/hsa-miR-486-5p
> -1.65 Q3 = hsa-miR-106a/hsa-miR-197 < 4.9 Q4 =
hsa-miR-106a/hsa-miR-486-5p > 3.59 Q5 = hsa-miR-106a/hsa-miR-451
> 3.14 Q6 = hsa-miR-17/hsa-miR-197 < 4.79 Q7 =
hsa-miR-17/hsa-miR-486-5p > 3.49 Q8 = hsa-miR-17/hsa-miR-451
> 3.21 Q9 = hsa-miR-126/hsa-miR-197 < 4.17 Q10 =
hsa-miR-126/hsa-miR-486-5p > 2.75 Q11 = hsa-miR-126/hsa-miR-451
> 2.58 Q12 = hsa-miR-197/hsa-miR-660 > 4.59 Q13 =
hsa-miR-126/hsa-miR-660 > 8.46 Q14 = hsa-miR-28-3p/hsa-miR-660
> 3.53 Q15 = hsa-miR-28-3p/hsa-miR-486-5p > -2.41 Q16 =
hsa-miR-28-3p/hsa-miR-451 > -2.36 Q17 = hsa-miR-197/hsa-miR-19b
> -3.97 Q18 = hsa-miR-19b/hsa-miR-486-5p > 2.41 Q19 =
hsa-miR-19b/hsa-miR-660 > 8.42 Q20 = hsa-miR-19b/hsa-miR-451
> 2.19 Q21 = hsa-miR-140-5p/hsa-miR-197 < -0.52 Q22 =
hsa-miR-140-5p/hsa-miR-28-3p < 0.28 Q23 = hsa-miR-16/hsa-miR-197
< 4.48 Q24 = hsa-miR-197/hsa-miR-92a > -1.14 Q25 =
hsa-miR-101/hsa-miR-197 < -4.51 Q26 = hsa-miR-145/hsa-miR-451
> -2 Q27 = hsa-miR-148a/hsa-miR-451 > -4.77 Q28 =
hsa-miR-142-3p/hsa-miR-197 < 3 Q29 = hsa-miR-30b/hsa-miR-451
> 1.2 Q30 = hsa-miR-15b/hsa-miR-451 > -1.2 Q31 =
hsa-miR-30c/hsa-miR-451 > -0.3 Q32 = hsa-miR-197/hsa-miR-21 >
-0.21
[0190] Reducing the number of microRNAs and ratios (from the
32.sup.nd to the 1.sup.st), the shorter signatures were tested on
the validation set, analyzing their power using the mean percent of
correct classification among 6 different methods of class
prediction analysis: Compound Covariate Predictor, Diagonal Linear
Discriminant Analysis, 1-Nearest Neighbor, 3-Nearest Neighbors,
Nearest Centroid and Support Vector Machines. The results are shown
in FIG. 16d.
TABLE-US-00040 TABLE VIIId Another set of ratios among measured
values of expression of preferred pairs of microRNAs used for
determining an actual presence of aggressive pulmonary tumour in an
individual. miRNA Pairs hsa-miR-197/hsa-miR-451
hsa-miR-197/hsa-miR-486-5p hsa-miR-106a/hsa-miR-197
hsa-miR-106a/hsa-miR-486-5p hsa-miR-106a/hsa-miR-451
hsa-miR-17/hsa-miR-197 hsa-miR-17/hsa-miR-486-5p
hsa-miR-17/hsa-miR-451 hsa-miR-126/hsa-miR-197
hsa-miR-126/hsa-miR-486-5p hsa-miR-126/hsa-miR-451
[0191] Once the miRNA profile of the subject is obtained, it is
necessary to determine for each ratio if the value exceed a
predetermined cut-off value. The results from the training and
validation set show that for the signatures of risk and diagnosis,
described above in Tables 111c and VIIc, respectively, at least 30%
(e.g., about 10 out of 27) of the ratios must exceed the cut-off to
consider the subject positive for the test. For the two signatures
of aggressiveness, described above in Tables IVc and VIIIc,
respectively, at least 50% (e.g., 17 out of 33 and 17 out of 32) of
the ratios must exceed the cut-off to consider the patient positive
for the signature of aggressive risk and presence of aggressive
disease, respectively. When reducing the number of miRNAs composing
the signature the percentage of positive ratios must be the same.
The cut-off values were obtained with the validation set from
samples stored for almost 3 years, and the values are shown in
Tables 111c, IVc, VIIc and VIIIc.
[0192] If a subject is determined to be positive to more than one
signature, the most critical one is considered in this order: risk,
diagnosis (both low risk), risk of aggressive disease, presence of
aggressive disease (both high risk). A flow chart is shown in FIG.
17.
[0193] Compositions and Methods of Treatment
[0194] The method can further comprise altering the level of
expression of at least one miRNA, at least two miRNA or at least
six miRNA, for which the level of expression changes or deviates,
thereby reducing or eliminating the risk of developing a tumor in
said subject. The method can further comprise altering the level of
expression of at least one miRNA, at least two miRNA or at least
six miRNA, for which the level of expression changes or deviates,
thereby reducing or eliminating the risk of developing an
aggressive tumor in said subject. The method can further comprise
altering the level of expression of at least one miRNA, at least
two miRNA or at least six miRNA, for which the level of expression
changes or deviates, thereby treating a tumor in said subject. The
method can further comprise altering the level of expression of at
least one miRNA, at least two miRNA or at least six miRNA, for
which the level of expression changes or deviates, thereby treating
an aggressive tumor in said subject.
[0195] Preferably, altering the level of expression of said of at
least one miRNA, at least two miRNA or at least six miRNA,
comprises administering to said subject a therapeutically effective
amount of at least one miRNA, at least two miRNA or at least six
miRNA, listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, or a
chemically synthesized miRNA mimetic or recombinant thereof, if the
level of expression of said of at least one miRNA, at least two
miRNA or at least six miRNA, is lower than the control level of
expression or administering to said subject a therapeutically
effective amount of a compound capable of inhibiting the expression
of at least one miRNA, at least two miRNA or at least six miRNA,
listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, if the
level of expression of said of at least one miRNA, at least two
miRNA or at least six miRNA, is higher than the control level of
expression.
[0196] The method can comprise increasing the level of expression
of said at least one miRNA, at least two miRNA or at least six
miRNA, which is under-expressed with respect to the control level
of expression. The method can comprise administering a
therapeutically effective amount of a composition comprising at
least one miRNA, at least two miRNA or at least six miRNA listed in
Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, or a chemically
synthesized miRNA mimetic or recombinant thereof. The method can
comprise administering a therapeutically effective amount of a
composition comprising at least one miRNA, at least two miRNA or at
least six miRNA listed in Tables Ib, Id, IIb, IId, Vb, Vd, VIb or
VId, or a chemically synthesized miRNA mimetic or recombinant
thereof. The method can comprise decreasing the level of expression
of said at least one miRNA, at least two miRNA or at least six
miRNA, which is over-expressed with respect to the control level of
expression. The method can comprise administering a therapeutically
effective amount of a composition comprising an inhibitor of at
least one miRNA, at least two miRNA or at least six miRNA listed in
Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc. The method can
comprise administering a therapeutically effective amount of a
composition comprising an inhibitor of at least one miRNA, at least
two miRNA or at least six miRNA listed in Tables Ib, Id, IIb, IId,
Vb, Vd, VIb or VId. The inhibitor can comprise double-filament RNA,
short interfering RNA (siRNA), antisense nucleic acids, anti-miRNA
oligonucleotides (AMOs), molecules of enzymatic RNA, or
ribozymes.
[0197] The present invention also provides pharmaceutical compound
comprising at least one miRNA, at least two miRNA or at least six
miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc,
chemically synthesized miRNA mimetic or recombinant thereof, or an
inhibitor of the expression of at least one miRNA, at least two
miRNA or at least six miRNA listed in Tables Ia, Ic, IIa, IIc, Va,
Vc, VIa, or VIc and a pharmaceutically acceptable carrier.
[0198] The present invention also provides pharmaceutical compound
comprising at least one miRNA, at least two miRNA or at least six
miRNA listed in Tables Ib, Id, IIb, IId, Vb, Vd, VIb or VId,
chemically synthesized miRNA mimetic or recombinant thereof, or an
inhibitor of the expression of at least one miRNA, at least two
miRNA or at least six miRNA listed in Tables Ib, Id, IIb, IId, Vb,
Vd, VIb or VId and a pharmaceutically acceptable carrier.
Preferably, the miRNA are the miRNA listed in Tables Ie, IIe, IIf,
IIg, Ve, Vf, VIe or VIf.
[0199] The present invention provides a method for treating an
individual in whom the presence of a pulmonary tumour has been
diagnosed or in whom a risk of developing a pulmonary tumour has
been diagnosed, respectively for the treatment of the pulmonary
tumour or in order to reduce and/or eliminate the risk of
developing a pulmonary tumour.
[0200] The method comprises the following steps of measuring an
expression level of at least one miRNA, at least two miRNA or at
least six miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or
VIc, present in a sample of biological fluid previously collected
from an individual, and then determining the miRNAs having values
measured for the expression level which deviate with respect to a
predetermined and respective control criterion. The evaluation of
the deviation with respect to a control criterion can use the
procedures of the miRNA ratios described above for the various
cases.
[0201] Once the overexpressed or underexpressed miRNAs have been
determined, the method comprises altering the expression level of
the miRNAs whose levels of expression deviate with respect to the
respective control criterion.
[0202] For example, in order to alter the expression level of the
miRNAs the individual can be administered with a pharmaceutical
compound having an effective quantity of at least one miRNA, at
least two miRNA or at least six miRNA of the miRNAs listed in
Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc if the expression
level measured of the miRNA, or miRNAs, is lower than a respective
control expression level.
[0203] Alternatively, or in addition to the above, it is also
possible to administer the individual with a pharmaceutical
compound having an effective quantity of at least a compound for
inhibiting the expression of at least one miRNA, at least two miRNA
or at least six miRNA listed in Tables Ia, Ic, IIa, IIc, Va, Vc,
VIa, or VIc if and for those miRNAs whose measured expression level
is above the control expression level.
[0204] In this way the values of the expression level can be reset
to the control expression level for the underexpressed miRNAs with
respect to the respective control level of expression and/or it is
possible to reduce the expression level for the overexpressed
miRNAs.
[0205] With the aim of resetting the level of the underexpressed
miRNAs a therapeutically effective quantity of a compound can be
administered which comprises at least one miRNA, at least two miRNA
or at least six miRNA of the miRNAs of Tables Ia, Ic, IIa, IIc, Va,
Vc, VIa, or VIc, chemically synthesized (miRNA mimetics) or
recombinant.
[0206] With the aim of reducing the expression level values to the
control expression level for the overexpressed miRNAs with respect
to the respective control expression level, a therapeutically
effective quantity of a compound can be administered which
comprises at least one miRNA, at least two miRNA or at least six
miRNA inhibitor of a microRNA of Tables Ia, Ic, IIa, IIc, Va, Vc,
VIa, or VIc. The inhibitor comprises, for example, one or more of
the following: double-filament RNA, optionally short interfering
RNA (siRNA), antisense nucleic acids (anti-miRNA oligonucleotides
(AMOs), molecules of enzymatic RNA (ribozymes). The inhibitor is
directed to a specific product of microRNA and interferes with the
expression (by inhibition of the translation or induction of the
degradation) of a target gene of the microRNA.
[0207] The administering of the above compounds (synthetic
microRNAs or mimetic miRNAs and inhibitors of microRNA) can for
example can be done by means of viral systems or nanoparticles
containing microRNA or microRNA inhibitor) linked covalently with
lipids or encapsulated liposomes.
[0208] The compounds can be administered by any means known in the
art, including but not limited to, intranasal instillation,
inhalation (aerosol), systemic administration (injection or
infusion), direct inoculation in the tumour (where present and
visible), intrapleuric administration, endopleuric administration
or a combination thereof.
[0209] In terms of dosage, continuous and prolonged dosage can be
performed over time. As miRNA molecules are "naturally" present in
the organism, no relevant toxicity will obtain.
[0210] Biomarker Apparatuses and Kits
[0211] The present invention provides an article comprising a
support having a plurality of sites, wherein each site is capable
of receiving a quantity of a biological sample, wherein each of the
sites comprises at least one reagent capable of binding with at
least one miRNA, at least two miRNA or at least six miRNA, listed
in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.
[0212] The reagent can be selected from group consisting of a
polynucleotide comprising a nucleotide sequence of at least one
miRNA, at least two miRNA, or at least six miRNA, from the miRNA
listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc; a
polynucleotide comprising a nucleotide sequence which is
complementary to a sequence of at least one miRNA, at least two
miRNA, or at least six miRNA, from the miRNA listed in Tables Ia,
Ic, IIa, IIc, Va, Vc, VIa, or VIc; and a molecular probe configured
such as to recognize a sequence of at least one miRNA, at least two
miRNA, or at least six miRNA, from the miRNA listed in Tables Ia,
Ic, IIa, IIc, Va, Vc, VIa, or VIc.
[0213] The present invention also provides an article comprising a
support having a plurality of sites, wherein each site is capable
of receiving a quantity of a biological sample, wherein each of the
sites comprises at least one reagent capable of binding with at
least one miRNA, at least two miRNA or at least six miRNA, listed
in Tables Ib, Id, IIb, IId, Vb, Vd, VIb, or VId. Preferably, the
miRNA can be the miRNA listed in Table Ie, IIe, IIf, IIg, Ve, Vf,
VIe or VIf.
[0214] The present invention also provides an apparatus comprising
at least one unit capable of receiving at least one of the articles
of the present invention; means for determining the level of
expression of at least one miRNA, at least two miRNA or at least
six miRNA, listed in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc,
and means for calculating the real quotients from among the levels
of expression of at least one pair, at least two pairs, or at least
six pairs, of miRNA from the pairs of miRNA listed in Tables IIIa,
IIIc, IVa, IVc, VIIa, VIII, VIIIa, or VIIIc.
[0215] The means for determining the value of the level of
expression can be selected from the group consisting of
Quantitative Real-time PCR, Microfluidic cards, Microarrays,
RT-PCR, quantitative or semi-quantitative, Northern blot, Solution
Hybridization, and Sequencing.
[0216] The present invention provides medical kits useful for
effectively and simply applying the methods described above, for
determining the risk of contracting a tumour or for tumour
diagnosis, for example by using a sample of blood removed from an
individual.
[0217] In its general form the kit comprises a platform having a
plurality of sites, each of which is destined to receive a
respective discrete quantity of the sample of biological fluid (for
example whole blood, serum, plasma, saliva or bronchial
condensate). In the structural sense the platform can be a support
for a micro-fluidic card with the miRNA of interest with
channellings for the distribution to the respective sites of a
predetermined number of samples of biological fluid. Each site
comprises a reagent capable of bonding with at least one miRNA, at
least two miRNA or at least six miRNA of the microRNAs of Tables
Ia, Ic, IIa or IIc for determining the risk of contracting a tumour
or a reagent capable of bonding with at least one miRNA, at least
two miRNA or at least six miRNA of the microRNAs of Tables Va, Vc,
VIa or VIc for tumour diagnosis, in such a way as to enable
detectability with the apparatus described herein below.
[0218] For example it can include at least one selected from a
group comprising: a polynucleotide comprising a nucleotide sequence
of at least one miRNA, at least two miRNA or at least six miRNA of
the microRNAs as in Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc, a
polynucleotide comprising a nucleotide sequence which is
complementary to a sequence of at least one miRNA, at least two
miRNA or at least six miRNA of the microRNAs as in Tables Ia, Ic,
IIa, IIc, Va, Vc, VIa, or VIc, a molecular probe configured such as
to recognize a sequence of at least one miRNA, at least two miRNA
or at least six miRNA of the microRNAs as in Tables Ia, Ic, IIa,
IIc, Va, Vc, VIa, or VIc.
[0219] The described medical kit can also be used with a medical
apparatus comprising a unit defining a seating for receiving one or
more kits and means for determining the value of the expression of
the microRNAs of Tables Ia, Ic, IIa, IIc, Va, Vc, VIa, or VIc.
Determining the value of the expression level can be performed by
any means known in the art, including but not limited to,
Quantitative Real-time PCR, Microfluidic cards, Microarrays,
Quantitative or semi-quantitative RT-PCR, Northern blot, Solution
Hybridization, Sequencing or combinations thereof.
[0220] The apparatus can also exhibit means for calculating the
values of the real ratios among values of expression levels of
pairs of microRNAs as in Tables IIIa, IIIc, IVa, IVc, VIIa, VIII,
VIIIa, or VIIIc. These means can comprise a programme and a
processing unit in which the programme contains instructions which
when carried out by the processor enable a calculation of the
ratios. Alternatively an analog circuit can be provided which is
able to perform the calculations.
[0221] miRNA
[0222] Overall, 24 miRNAs compose the signature of risk (R),
signature of aggressive disease (AR), signature of diagnosis (D)
and signature of presence of aggressive disease (AD). Table IX
recites those 24 miRNAs and how often they appear as part of a
ratio for each signature.
TABLE-US-00041 TABLE IX miRNA R AR D AD hsa-miR-16 2 4 0 1
hsa-miR-17 4 4 3 3 hsa-miR-21 0 5 0 1 hsa-miR-101 4 4 2 1
hsa-miR-126 1 1 2 4 hsa-miR-145 0 2 3 1 hsa-miR-197 5 9 6 13
hsa-miR-221 0 2 0 0 hsa-miR-320 1 2 3 0 hsa-miR-451 7 10 0 11
hsa-miR-660 11 0 9 4 hsa-miR-106a 3 4 4 3 hsa-miR-133a 3 0 0 0
hsa-miR-140-3p 2 1 0 0 hsa-miR-140-5p 0 0 2 2 hsa-miR-142-3p 1 0 3
1 hsa-miR-148a 0 1 2 1 hsa-miR-15b 3 1 0 1 hsa-miR-19b 3 1 2 4
hsa-miR-28-3p 1 8 4 4 hsa-miR-30b 0 2 0 1 hsa-miR-30c 0 2 0 1
hsa-miR-486-5p 0 0 0 6 hsa-miR-92a 3 3 9 1
[0223] The present invention provides apparatuses and kits for
detecting at least one, at least two, at least three, at least
four, at least six or all twenty-four of the miRNA of Table IX. The
present invention provides apparatuses and kits for activating or
stimulating the activity of or the expression of at least one, at
least two, at least three, at least four, at least six or all
twenty-four of the miRNA of Table IX. The present invention
provides apparatuses and kits for decreasing or inhibiting the
activity of or the expression of at least one, at least two, at
least three, at least four, at least six or all twenty-four of the
miRNA of Table IX. The present invention also provides
pharmaceutical compositions for activating or stimulating the
activity of or the expression of at least one, at least two, at
least three, at least four, at least six or all twenty-four of the
miRNA of Table IX. The present invention also provides
pharmaceutical compositions for decreasing or inhibiting the
activity of or the expression of at least one, at least two, at
least three, at least four, at least six or all twenty-four of the
miRNA of Table IX.
[0224] Table X provides a summary of the miRNA for use in all
aspects of the present invention.
TABLE-US-00042 TABLE X miRNA Name Sequence hsa-miR-7-2
CUGGAUACAGAGUGGACCGGCUGGCCCCAUCUGGAAGACUAGUGA (pre-miR)
UUUUGUUGUUGUCUUACUGCGCUCAACAACAAAUCCCAGUCUACC UAAUGGUGCCAGCCAUCGCA
(SEQ ID NO: 1) hsa-miR-7-2-5p UGGAAGACUAGUGAUUUUGUUGU (mature miR
5' arm) (SEQ ID NO: 2) hsa-miR-7-2-3p CAACAAAUCCCAGUCUACCUAA
(mature miR 3' arm) (SEQ ID NO: 3) hsa-miR-15b
UUGAGGCCUUAAAGUACUGUAGCAGCACAUCAUGGUUUACAUGCU (pre-miR)
ACAGUCAAGAUGCGAAUCAUUAUUUGCUGCUCUAGAAAUUUAAGG AAAUUCAU (SEQ ID NO:
4) hsa-miR-15b-5p UAGCAGCACAUCAUGGUUUACA (mature miR 5'arm) (SEQ ID
NO: 5) hsa-miR-15b-3p CGAAUCAUUAUUUGCUGCUCUA (mature miR 3'arm)
(SEQ ID NO: 6) hsa-miR-16-1
GUCAGCAGUGCCUUAGCAGCACGUAAAUAUUGGCGUUAAGAUUCU (pre-miR from Chr.13)
AAAAUUAUCUCCAGUAUUAACUGUGCUGCUGAAGUAAGGUUGAC (SEQ ID NO: 7)
hsa-miR-16-2 GUUCCACUCUAGCAGCACGUAAAUAUUGGCGUAGUGAAAUAUAUA (pre-miR
from Chr.3) UUAAACACCAAUAUUACUGUGCUGCUUUAGUGUGAC (SEQ ID NO: 8)
hsa-miR-16-5p UAGCAGCACGUAAAUAUUGGCG (mature miR 5' arm) (SEQ ID
NO: 9) hsa-miR-16-3p CCAAUAUUACUGUGCUGCUUUA (mature miR 3'arm) (SEQ
ID NO: 10) hsa-miR-17 GUCAGAAUAAUGUCAAAGUGCUUACAGUGCAGGUAGUGAUAUGUG
(pre-miR) CAUCUACUGCAGUGAAGGCACUUGUAGCAUUAUGGUGAC (SEQ ID NO: 11)
hsa-miR-17-5p CAAAGUGCUUACAGUGCAGGUAG (mature miR 5'arm) (SEQ ID
NO: 12) hsa-miR-17-3p ACUGCAGUGAAGGCACUUGUAG (mature miR 3'arm)
(SEQ ID NO: 13) hsa-miR-19b-1
CACUGUUCUAUGGUUAGUUUUGCAGGUUUGCAUCCAGCUGUGUGA (pre-miR from Chr.
13) UAUUCUGCUGUGCAAAUCCAUGCAAAACUGACUGUGGUAGUG (SEQ ID NO: 14)
hsa-miR-19b-1-5p AGUUUUGCAGGUUUGCAUCCAGC (mature miR 5'arm from
Chr. 13) (SEQ ID NO: 15) hsa-miR-19b-2
ACAUUGCUACUUACAAUUAGUUUUGCAGGUUUGCAUUUCAGCGUA (pre-miR from Chr. X)
UAUAUGUAUAUGUGGCUGUGCAAAUCCAUGCAAAACUGAUUGUGA UAAUGU (SEQ ID NO:
16) hsa-miR-19b-2-5p AGUUUUGCAGGUUUGCAUUUCA (mature miR 5' arm from
Chr. X) (SEQ ID NO: 17) hsa-miR-19b-3p UGUGCAAAUCCAUGCAAAACUGA
(mature miR 3' arm from Chr. 13 (SEQ ID NO: 18) or X) hsa-miR-21
UGUCGGGUAGCUUAUCAGACUGAUGUUGACUGUUGAAUCUCAUGG (pre-miR)
CAACACCAGUCGAUGGGCUGUCUGACA (SEQ ID NO: 19) hsa-miR-21-5p
UAGCUUAUCAGACUGAUGUUGA (mature miR 5' arm) (SEQ ID NO: 20)
hsa-miR-21-3p CAACACCAGUCGAUGGGCUGU (mature miR 3' arm) (SEQ ID NO:
21) hsa-miR-28 GGUCCUUGCCCUCAAGGAGCUCACAGUCUAUUGAGUUACCUUUCU
(pre-miR) GACUUUCCCACUAGAUUGUGAGCUCCUGGAGGGCAGGCACU (SEQ ID NO: 22)
hsa-miR-28-5p AAGGAGCUCACAGUCUAUUGAG (mature miR 5' arm) (SEQ ID
NO: 23) hsa-miR-28-3p CACUAGAUUGUGAGCUCCUGGA (mature miR 3' arm)
(SEQ ID NO: 24) hsa-miR-30a
GCGACUGUAAACAUCCUCGACUGGAAGCUGUGAAGCCACAGAUGG (pre-miR)
GCUUUCAGUCGGAUGUUUGCAGCUGC (SEQ ID NO: 25) hsa-miR-30a-5p
UGUAAACAUCCUCGACUGGAAG (mature miR 5' arm) (SEQ ID NO: 26)
hsa-miR-30a-3p CUUUCAGUCGGAUGUUUGCAGC (mature miR 3' arm) (SEQ ID
NO: 27) hsa-miR-30b ACCAAGUUUCAGUUCAUGUAAACAUCCUACACUCAGCUGUAAUAC
(pre-miR) AUGGAUUGGCUGGGAGGUGGAUGUUUACUUCAGCUGACUUGGA (SEQ ID NO:
28) hsa-miR-30b-5p UGUAAACAUCCUACACUCAGCU (mature miR 5' arm) (SEQ
ID NO: 29) hsa-miR-30b-3p CUGGGAGGUGGAUGUUUACUUC (mature miR 3'
arm) (SEQ ID NO: 30) hsa-miR-30c-1
ACCAUGCUGUAGUGUGUGUAAACAUCCUACACUCUCAGCUGUGAG (pre-miR from Chr. 1)
CUCAAGGUGGCUGGGAGAGGGUUGUUUACUCCUUCUGCCAUGGA (SEQ ID NO: 31)
hsa-miR-30c-1-3p CUGGGAGAGGGUUGUUUACUCC (mature miR 3' arm from
Chr. 1) (SEQ ID NO: 32) hsa-miR-30c-2
AGAUACUGUAAACAUCCUACACUCUCAGCUGUGGAAAGUAAGAAA (pre-miR from Chr. 6)
GCUGGGAGAAGGCUGUUUACUCUUUCU (SEQ ID NO: 33) hsa-miR-30c-5p
UGUAAACAUCCUACACUCUCAGC (mature miR 5' arm from (SEQ ID NO: 34)
Chr. 1 or 6) hsa-miR-30c-2-3p CUGGGAGAAGGCUGUUUACUCU (mature miR 3'
arm from Chr. 6) (SEQ ID NO: 35) hsa-miR-30d
GUUGUUGUAAACAUCCCCGACUGGAAGCUGUAAGACACAGCUAAG (pre-miR)
CUUUCAGUCAGAUGUUUGCUGCUAC (SEQ ID NO: 36) hsa-miR-30d-5p
UGUAAACAUCCCCGACUGGAAG (mature miR 5' arm) (SEQ ID NO: 37)
hsa-miR-30d-3p CUUUCAGUCAGAUGUUUGCUGC (mature miR 3' arm) (SEQ ID
NO: 38) hsa-miR-34b GUGCUCGGUUUGUAGGCAGUGUCAUUAGCUGAUUGUACUGUGGUG
(pre-miR) GUUACAAUCACUAACUCCACUGCCAUCAAAACAAGGCAC (SEQ ID NO: 39)
hsa-miR-34b-5p UAGGCAGUGUCAUUAGCUGAUUG (mature miR 5' arm) (SEQ ID
NO: 40) hsa-miR-34b-3p CAAUCACUAACUCCACUGCCAU (mature miR 3' arm)
(SEQ ID NO: 41) hsa-mirR-92a-1
CUUUCUACACAGGUUGGGAUCGGUUGCAAUGCUGUGUUUCUGUAU (pre-miR from Chr.
13) GGUAUUGCACUUGUCCCGGCCUGUUGAGUUUGG (SEQ ID NO: 42)
hsa-miR-92a-1-5p AGGUUGGGAUCGGUUGCAAUGCU (mature miR 5' arm from
Chr. 13) (SEQ ID NO: 43) hsa-miR-92a-3p UAUUGCACUUGUCCCGGCCUGU
(mature miR 3' arm from Chr. 13 (SEQ ID NO: 44) or X) hsa-miR-92a-2
UCAUCCCUGGGUGGGGAUUUGUUGCAUUACUUGUGUUCUAUAUAA (pre-miR from Chr. X)
AGUAUUGCACUUGUCCCGGCCUGUGGAAGA (SEQ ID NO: 45) hsa-miR-92a-2-5p
GGGUGGGGAUUUGUUGCAUUAC (mature miR 5' arm from Chr. X) (SEQ ID NO:
46) hsa-miR-101-1 UGCCCUGGCUCAGUUAUCACAGUGCUGAUGCUGUCUAUUCUAAAG
(pre-miR from Chr. 1) GUACAGUACUGUGAUAACUGAAGGAUGGCA (SEQ ID NO:
47) hsa-miR-101-5p CAGUUAUCACAGUGCUGAUGCU (mature miR 5' arm from
(SEQ ID NO: 48) Chr. 1 or 9) hsa-miR-101-1-3p UACAGUACUGUGAUAACUGAA
(mature miR 3' arm from Chr. 1) (SEQ ID NO: 49) hsa-miR-101-2
ACUGUCCUUUUUCGGUUAUCAUGGUACCGAUGCUGUAUAUCUGAA (pre-miR from Chr. 9)
AGGUACAGUACUGUGAUAACUGAAGAAUGGUGGU (SEQ ID NO: 50) hsa-miR-101-2-3p
UACAGUACUGUGAUAACUGAA (mature miR 3' arm from Chr. 9) (SEQ ID NO:
51) hsa-miR-106a CCUUGGCCAUGUAAAAGUGCUUACAGUGCAGGUAGCUUUUUGAGA
(pre-miR) UCUACUGCAAUGUAAGCACUUCUUACAUUACCAUGG (SEQ ID NO: 52)
hsa-miR-106a-5p AAAAGUGCUUACAGUGCAGGUAG (mature miR 5' arm) (SEQ ID
NO: 53) hsa-miR 106a-3p CUGCAAUGUAAGCACUUCUUAC (mature miR 3' arm)
(SEQ ID NO: 54) hsa-miR-126
CGCUGGCGACGGGACAUUAUUACUUUUGGUACGCGCUGUGACACU (pre-miR)
UCAAACUCGUACCGUGAGUAAUAAUGCGCCGUCCACGGCA (SEQ ID NO: 55)
hsa-miR-126-5p CAUUAUUACUUUUGGUACGCG (mature miR 5' arm) (SEQ ID
NO: 56) hsa-miR-126-3p (mature miR 3' UCGUACCGUGAGUAAUAAUGCG arm)
(SEQ ID NO: 57) hsa-miR-133a-1
ACAAUGCUUUGCUAGAGCUGGUAAAAUGGAACCAAAUCGCCUCUU (pre-miR from Chr.
18) CAAUGGAUUUGGUCCCCUUCAACCAGCUGUAGCUAUGCAUUGA (SEQ ID NO: 58)
hsa-miR 133a-2 GGGAGCCAAAUGCUUUGCUAGAGCUGGUAAAAUGGAACCAAAUCG
(pre-miR from Chr. 20)
ACUGUCCAAUGGAUUUGGUCCCCUUCAACCAGCUGUAGCUGUGCA UUGAUGGCGCCG (SEQ ID
NO: 59) hsa-miR-133a UUUGGUCCCCUUCAACCAGCUG (mature miR 3' arm from
(SEQ ID NO: 60) Chr. 18 or 20) hsa-miR-140
UGUGUCUCUCUCUGUGUCCUGCCAGUGGUUUUACCCUAUGGUAGG (pre-miR)
UUACGUCAUGCUGUUCUACCACAGGGUAGAACCACGGACAGGAUA CCGGGGCACC (SEQ ID
NO: 61) hsa-miR-140-5p CAGUGGUUUUACCCUAUGGUAG (mature miR 5' arm)
(SEQ ID NO: 62) hsa-miR-140-3p UACCACAGGGUAGAACCACGG (mature miR 3'
arm) (SEQ ID NO: 63) hsa-miR-142
GACAGUGCAGUCACCCAUAAAGUAGAAAGCACUACUAACAGCACU (pre-miR)
GGAGGGUGUAGUGUUUCCUACUUUAUGGAUGAGUGUACUGUG (SEQ ID NO: 64)
hsa-miR-142-5p CAUAAAGUAGAAAGCACUACU (mature miR 5' arm) (SEQ ID
NO: 65) hsa-miR-142-3p UGUAGUGUUUCCUACUUUAUGGA (mature miR 3' arm)
(SEQ ID NO: 66) hsa-miR-144
UGGGGCCCUGGCUGGGAUAUCAUCAUAUACUGUAAGUUUGCGAUG (pre-miR)
AGACACUACAGUAUAGAUGAUGUACUAGUCCGGGCACCCCC (SEQ ID NO: 67)
hsa-miR-144-5p GGAUAUCAUCAUAUACUGUAAG (mature miR 5' arm) (SEQ ID
NO: 68) hsa-miR-144-3p UACAGUAUAGAUGAUGUACU (mature miR 3' arm)
(SEQ ID NO: 69) hsa-miR-145
CACCUUGUCCUCACGGUCCAGUUUUCCCAGGAAUCCCUUAGAUGC (pre-miR)
UAAGAUGGGGAUUCCUGGAAAUACUGUUCUUGAGGUCAUGGUU (SEQ ID NO: 70)
hsa-miR-145-5p GUCCAGUUUUCCCAGGAAUCCCU (mature miR 5' arm) (SEQ ID
NO: 71) hsa-miR-145-3p GGAUUCCUGGAAAUACUGUUCU (mature miR 3'arm)
(SEQ ID NO: 72) hsa-miR-148a
GAGGCAAAGUUCUGAGACACUCCGACUCUGAGUAUGAUAGAAGUC (pre-miR)
AGUGCACUACAGAACUUUGUCUC (SEQ ID NO: 73) hsa-miR-148a-5p
AAAGUUCUGAGACACUCCGACU (mature miR 5' arm) (SEQ ID NO: 74)
hsa-miR-148a-3p UCAGUGCACUACAGAACUUUGU (mature miR 3' arm) (SEQ ID
NO: 75) hsa-miR-197 GGCUGUGCCGGGUAGAGAGGGCAGUGGGAGGUAAGAGCUCUUCAC
(pre-miR) CCUUCACCACCUUCUCCACCCAGCAUGGCC (SEQ ID NO: 76)
hsa-miR-197-5p CGGGUAGAGAGGGCAGUGGGAGG (mature miR 5' arm) (SEQ ID
NO: 77) hsa-miR-197-3p UUCACCACCUUCUCCACCCAGC (mature miR 3' arm)
(SEQ ID NO: 78) hsa-miR-200b
CCAGCUCGGGCAGCCGUGGCCAUCUUACUGGGCAGCAUUGGAUGG (pre miR)
AGUCAGGUCUCUAAUACUGCCUGGUAAUGAUGACGGCGGAGCCCU GCACG (SEQ ID NO: 79)
hsa-miR-200b-5p CAUCUUACUGGGCAGCAUUGGA (mature miR 5' arm) (SEQ ID
NO: 80) hsa-miR-200b-3p UAAUACUGCCUGGUAAUGAUGA (mature miR 3' arm)
(SEQ ID NO: 81) hsa-miR-205
AAAGAUCCUCAGACAAUCCAUGUGCUUCUCUUGUCCUUCAUUCCA (pre-miR)
CCGGAGUCUGUCUCAUACCCAACCAGAUUUCAGUGGAGUGAAGUU CAGGAGGCAUGGAGCUGACA
(SEQ ID NO: 82) hsa-miR-205-5p UCCUUCAUUCCACCGGAGUCUG (mature miR
5' arm) (SEQ ID NO: 83) hsa-miR-205-3p GAUUUCAGUGGAGUGAAGUUC
(mature miR 3' arm) (SEQ ID NO: 84) hsa-miR-210
ACCCGGCAGUGCCUCCAGGCGCAGGGCAGCCCCUGCCCACCGCAC (pre-miR)
ACUGCGCUGCCCCAGACCCACUGUGCGUGUGACAGCGGCUGAUCU GUGCCUGGGCAGCGCGACCC
(SEQ ID NO: 85) hsa-miR-210 CUGUGCGUGUGACAGCGGCUGA (mature miR)
(SEQ ID NO: 86) hsa-miR-219-1
CCGCCCCGGGCCGCGGCUCCUGAUUGUCCAAACGCAAUUCUCGAG (pre-miR)
UCUAUGGCUCCGGCCGAGAGUUGAGUCUGGACGUCCCGAGCCGCC GCCCCCAAACCUCGAGCGGG
(SEQ ID NO: 87) hsa-miR-219-1-5p UGAUUGUCCAAACGCAAUUCU (mature miR
5' arm) (SEQ ID NO: 88) hsa-miR-219-1-3p AGAGUUGAGUCUGGACGUCCCG
(mature miR 3' arm) (SEQ ID NO: 89) hsa-miR-221
UGAACAUCCAGGUCUGGGGCAUGAACCUGGCAUACAAUGUAGAUU (pre-miR)
UCUGUGUUCGUUAGGCAACAGCUACAUUGUCUGCUGGGUUUCAGG CUACCUGGAAACAUGUUCUC
(SEQ ID NO: 90) hsa-miR-221-5p ACCUGGCAUACAAUGUAGAUUU (mature miR
5' arm) (SEQ ID NO: 91) hsa-miR-221-3p AGCUACAUUGUCUGCUGGGUUUC
(mature miR 3' arm) (SEQ ID NO: 92) hsa-miR-320a
GCUUCGCUCCCCUCCGCCUUCUCUUCCCGGUUCUUCCCGGAGUCG (pre-miR)
GGAAAAGCUGGGUUGAGAGGGCGAAAAAGGAUGAGGU (SEQ ID NO: 93) hsa-miR-320a
AAAAGCUGGGUUGAGAGGGCAA (mature miR) (SEQ ID NO: 94) hsa-miR-320b-1
AAUUAAUCCCUCUCUUUCUAGUUCUUCCUAGAGUGAGGAAAAGCU (pre-miR from Chr. 1:
117214371- GGGUUGAGAGGGCAAACAAAUUAACUAAUUAAUU 117214449) (SEQ ID
NO: 95) hsa-miR-320b-2
UGUUAUUUUUUGUCUUCUACCUAAGAAUUCUGUCUCUUAGGCUUU (pre-miR from Chr. 1:
224444706- CUCUUCCCAGAUUUCCCAAAGUUGGGAAAAGCUGGGUUGAGAGGG 224444843)
CAAAAGGAAAAAAAAAGAAUUCUGUCUCUGACAUAAUUAGAUAGG GAA (SEQ ID NO: 96)
hsa-miR-320b AAAAGCUGGGUUGAGAGGGCAA (mature miR from Chr. 1) (SEQ
ID NO: 97) hsa-miR-320c-1
UUUGCAUUAAAAAUGAGGCCUUCUCUUCCCAGUUCUUCCCAGAGU (pre-miR from Chr.
18: 19263471- CAGGAAAAGCUGGGUUGAGAGGGUAGAAAAAAAAUGAUGUAGG 19263558)
(SEQ ID NO: 98) hsa-miR-320c-2
CUUCUCUUUCCAGUUCUUCCCAGAAUUGGGAAAAGCUGGGUUGAG (pre-miR from Chr.
18-21901650- AGGGU 21901699) (SEQ ID NO: 99) hsa-miR-320-c
AAAAGCUGGGUUGAGAGGGU (mature miR from either Chr 18 (SEQ ID NO:
100) loci) hsa-miR-320d-1
UUCUCGUCCCAGUUCUUCCCAAAGUUGAGAAAAGCUGGGUUGAGA (pre-miR from Chr.
13) GGA (SEQ ID NO: 101) hsa-miR-320d-2
UUCUCUUCCCAGUUCUUCUUGGAGUCAGGAAAAGCUGGGUUGAGA (pre-miR from Chr. X)
GGA (SEQ ID NO: 102) hsa-miR-320d AAAAGCUGGGUUGAGAGGA (mature miR
from Chr. 13 or X) (SEQ ID NO: 103) hsa-miR-320e
GCCUUCUCUUCCCAGUUCUUCCUGGAGUCGGGGAAAAGCUGGGUU (pre-miR) GAGAAGGU
(SEQ ID NO: 104) hsa-miR-320e AAAGCUGGGUUGAGAAGG (mature miR) (SEQ
ID NO: 105) hsa-miR-324
CUGACUAUGCCUCCCCGCAUCCCCUAGGGCAUUGGUGUAAAGCUG (pre-miR)
GAGACCCACUGCCCCAGGUGCUGCUGGGGGUUGUAGUC (SEQ ID NO: 106) hsa-miR-324
CGCAUCCCCUAGGGCAUUGGUGU (mature miR 5' arm) (SEQ ID NO: 107)
hsa-miR-324 ACUGCCCCAGGUGCUGCUGG (mature miR 3' arm) (SEQ ID NO:
108) hsa-miR-429 CGCCGGCCGAUGGGCGUCUUACCAGACAUGGUUAGACCUGGCCCU
(pre-miR) CUGUCUAAUACUGUCUGGUAAAACCGUCCAUCCGCUGC (SEQ ID NO: 109)
hsa-miR-429 UAAUACUGUCUGGUAAAACCGU (mature miR) (SEQ ID NO: 110)
hsa-miR-451a CUUGGGAAUGGCAAGGAAACCGUUACCAUUACUGAGUUUAGUAAU
(pre-miR) GGUAAUGGUUCUCUUGCUAUACCCAGA (SEQ ID NO: 111) hsa-miR-451a
AAACCGUUACCAUUACUGAGUU (mature miR) (SEQ ID NO: 112) hsa-miR-451b
UGGGUAUAGCAAGAGAACCAUUACCAUUACUAAACUCAGUAAUGG (pre-miR)
UAACGGUUUCCUUGCCAUUCCCA (SEQ ID NO: 113) hsa-miR-451b
UAGCAAGAGAACCAUUACCAUU (mature miR) (SEQ ID NO: 114) hsa-miR-486
GCAUCCUGUACUGAGCUGCCCCGAGGCCCUUCAUGCUGCCCAGCU (pre-miRNA)
CGGGGCAGCUCAGUACAGGAUAC (SEQ ID NO: 115) hsa-miR-486-5p
UCCUGUACUGAGCUGCCCCGAG (mature miR 5' arm) (SEQ ID NO: 116)
hsa-miR-486-3p CGGGGCAGCUCAGUACAGGAU (mature miR 3' arm) (SEQ ID
NO: 117) hsa-miR-518e UCUCAGGCUGUGACCCUCUAGAGGGAAGCGCUUUCUGUUGGCUAA
(pre-miR) AAGAAAAGAAAGCGCUUCCCUUCAGAGUGUUAACGCUUUGAGA (SEQ ID NO:
118) hsa-miR-518e 5p CUCUAGAGGGAAGCGCUUUCUG (mature miR 5' arm)
(SEQ ID NO: 119) hsa-miR-518e-3p AAAGCGCUUCCCUUCAGAGUG (mature miR
3' arm) (SEQ ID NO: 120) hsa-miR-660
CUGCUCCUUCUCCCAUACCCAUUGCAUAUCGGAGUUGUGAAUUCU (pre-miR)
CAAAACACCUCCUGUGUGCAUGGAUUACAGGAGGGUGAGCCUUGU CAUCGUG (SEQ ID NO:
121) hsa-miR-660-5p UACCCAUUGCAUAUCGGAGUUG (mature miR 5' arm) (SEQ
ID NO: 122) hsa-miR-660-3p ACCUCCUGUGUGCAUGGAUUA (mature miR 3'
arm) (SEQ ID NO: 123)
[0225] Other features and advantages of the present invention are
apparent from the different examples. The provided examples
illustrate different components and methodology useful in
practicing the present invention. The examples do not limit the
claimed invention. Based on the present disclosure the skilled
artisan can identify and employ other components and methodology
useful for practicing the present invention.
EXAMPLES
Example 1
Studies, Materials & Methods
[0226] The present invention investigated the expression profile of
miRNA in the plasma of individuals enrolled in screening protocols
using spiral CT. This investigation was done with the aim of
verifying the capability of miRNAs as a new class of biomolecular
markers for: prediction of the risk of developing a tumour, in
particular a pulmonary tumour, and diagnosis of the tumour, in
particular pulmonary tumour, and thus as a prognostic aid for
discriminating patients with indolent or aggressive pulmonary
lesions.
[0227] Plasma samples taken from smoker individuals were used,
where the individuals were over 50 years old, in a time parameter
of between one and two years before detection with CT spiral of the
presence of a pulmonary tumour in the same individuals. Also used
were samples of plasma collected at the moment of the appearance of
the disease (detected using spiral CT). The plasma samples were
obtained from patients who had developed a pulmonary tumour with
various characteristics in terms of clinical aggressiveness
(indolent nodules or advanced and metastatic tumours) as well as
from individuals who remained free of disease for the whole
duration of the screening.
[0228] In a first stage of the research, identification was made of
the microRNAs that were present in the plasma using microfluidic
cards, model: TaqMan.RTM. of Applied Biosystems. Out of 378
microRNA analysed, 100 were present stably in the plasma of healthy
smoker individuals used as the control group. Thus, with a large
amount of starting data, there is a general agreement on the
possibility of normalizing the expression levels of the single
microRNAs on the mean of the expression levels of the 100 microRNAs
for each individual (Mestdagh P et al. Genome Biol, 2009). The data
obtained using this type of normalization were compared to those
obtained by normalizing on potential microRNA housekeeping (for
example mir-16, mammU6, RNU44 or RNU48).
[0229] The inventors then thought of no longer using the values of
the expression levels of the single microRNAs, but instead the
ratios among pairs thereof. The value of the cycle threshold (Ct)
obtained by qReal-Time PCR with the SDS 2.2.2.RTM. software
(Applied Biosystems) was transformed into the corresponding
expression value (2.sup.-Ct). Then the ratio between the value of
the expression level of each pair of microRNAs possible was
calculated, obtaining 4950 total ratios: the 4950 total ratios were
given by the formula 100*99/2 as the ratio between two miRNAs and
the reciprocal contain the same data. Finally the variation of
these ratios (called "miRNA ratios") in the plasma of the various
classes of patients was analysed in order to identify plasma
biomarkers.
[0230] The results showed that the microRNAs present in the
greatest amount in the ratios discriminating among the classes of
patients are the same as those which emerge from the analyses
performed by normalizing on the mean value of the expression levels
of the 100 microRNAs for each individual, thus validating the
method based on the miRNA ratios for quantifying the involved
microRNAs.
[0231] In greater detail, with the aim of identifying biomarkers in
the plasma which are able to predict the appearance of the
pulmonary tumour, the inventors studied the expression profile of
microRNAs circulating in collected samples up to two years
preceding the diagnosis of the disease and at the moment of surgery
in patients of two independent clinical trials, as mentioned above,
for early diagnosis of pulmonary tumour in high-risk individuals
(age >50 years and smokers) using spiral CT. In the first
training set, made up of 40 samples of plasma from 19 patients and
27 samples of plasma from healthy control individuals in 5
different pools, the miRNA expression levels were analysed using
TaqMan MicroRNA Assays (Applied Biosystems) with the aim of
identifying the significantly-different miRNA ratios (p<0.05)
between samples of plasma collected pre-disease, at the moment of
surgery and from healthy individuals.
[0232] The specificity and sensitivity of the signatures of
microRNAs thus obtained were compared with the validation set
composed, as described above, of 32 plasma samples of 22 patients
and 54 plasma samples of healthy control individuals, grouped in 10
different pools.
[0233] For the generalization of the signatures used for predicting
the aggressiveness of the disease, the inventors grouped the two
cohorts (training set and validation set) with the aim of obtaining
a sufficient number for the statistical analysis. The cases with
unfavorable prognosis were first compared to the respective
controls and the signatures thus obtained were tested to evaluate
their effective capacity to discriminate the patients having poor
prognosis from those having good prognosis.
[0234] As already mentioned, the signatures of the microRNAs
identified in the various analyses were validated on two
independent sets constituted by high-risk individuals (smokers of
more than 50 years of age) enrolled in two different clinical
trials for early identification of pulmonary tumour using low-dose
spiral CT: a first set, or training set, made up of 40 samples of
plasma from 19 patients and 27 samples of plasma from healthy
control individuals grouped in 5 different pools and a second set
or validation set (i.e. in a second set of individuals) made up of
32 samples of plasma from 22 patients and 54 samples of plasma from
healthy control individuals, grouped in 10 different pools.
[0235] FIG. 1 summarizes the pathological clinical characteristics
of the training set and the validation set selected for the
analysis of the expression levels of the miRNAs in the plasma
samples.
[0236] To determine the microRNA profile in the plasma samples the
total RNA was extracted from 200 .mu.l of plasma using the
mirVana.TM. PARIS.TM. Kit (Ambion), eluting in 50 .mu.l of elution
buffer.
[0237] The expression levels were determined using q-Real Time PCR
starting from 3 .mu.l of elute first using the Megaplex.TM. Pools
Protocol on a microfluidic card, type A (Applied Biosystems), then
the Multiplex.TM. Pools Protocol (Applied Biosystems).
[0238] All the data was extrapolated using the Sequence Detection
System software (SDS 2.2.2.RTM. Applied Biosystems), setting the
threshold manually at 0.2 and the baseline between 3 and 18 cycles
(on a total of 40).
[0239] Apart from the standard equipment for molecular biology, use
was made of Real-time quantitative PCR 7900-HT (Applied Biosystems)
and GeneAmp.COPYRGT. 9700 Sequence Detection System (Applied
Biosystems).
[0240] Identification of a Signature Based on MiRNAs Able to
Identify Individuals at Risk of Developing Pulmonary Tumour
[0241] The samples of plasma collected 1-2 years before from
patients in whom a tumour was later diagnosed using spiral CT were
analysed and compared with the control pool, constituted by healthy
individuals.
[0242] A signature was therefore identified in the training
comprising 14 miRNA ratios made up of 14 microRNAs capable of
correctly discriminating 18 out of 20 pre-disease samples from
individuals who then will develop the disease (90% sensitivity),
while only one control pool was positive for this signature (80%
specificity). In the validation set the sensitivity was 80%, while
the specificity was 90% (AUC-ROC=0.85, p<0.001).
[0243] The miRNA ratios of the first example were then listed and
are reported also in FIG. 4A.
[0244] Q.sub.1=hsa-mirR-106a/hsa-mirR-451
[0245] Q.sub.2=hsa-mirR-140-5p/hsa-mirR-320
[0246] Q.sub.3=hsa-mirR-140-5p/hsa-mirR-451
[0247] Q.sub.4=hsa-mirR-140-5p/hsa-mirR-660
[0248] Q.sub.5=hsa-mirR-140-5p/hsa-mirR-92a
[0249] Q.sub.6=hsa-mirR-15b/hsa-mirR-92a
[0250] Q.sub.7=hsa-mirR-17/hsa-mirR-451
[0251] Q.sub.8=hsa-mirR-197/hsa-mirR-451
[0252] Q.sub.9=hsa-mirR-19b/hsa-mirR-660
[0253] Q.sub.10=hsa-mirR-221/hsa-mirR-660
[0254] Q.sub.11=hsa-mirR-28-3p/hsa-mirR-660
[0255] Q.sub.12=hsa-mirR-30b/hsa-mirR-92a
[0256] Q.sub.13=hsa-mirR-30c/hsa-mirR-451
[0257] Q.sub.14=hsa-mirR-30c/hsa-mirR-660
[0258] The predictive capacity of this signature was validated in
samples collected up to 28 months before the diagnosis of disease
with spiral CT and the microRNAs most frequently deregulated were:
mir-660, mir-140-5p, mir-451, mir-28-3p, mir-30c and mir-92.
[0259] Identification of the Signature Based on the MiRNAs Able to
have Diagnostic Value
[0260] Plasma samples collected at the moment of surgery or on
identification of the disease by spiral CT were compared with the
control pools. In the training set, a panel of 16 miRNA ratios,
made up of 13 microRNAs, correctly classify 16 out of 19 patients
with a sensitivity of 84% and a specificity of 80%. In the
validation set sensitivity is 75% and the specificity is 100%
(AUC-ROC=0.88, p<0.0001).
[0261] A lower sensitivity in the validation set can be correlated
to the presence of a greater number of small indolent nodules, of
which two patients are part, whose blood samples were mis-matched
both by the risk signature in the pre-disease samples, and by the
signature in the samples taken in the presence of disease.
[0262] The miRNA ratios of the second example are listed herein
below and are also reported in FIG. 4B.
[0263] Q.sub.1=hsa-mirR-106a/hsa-mirR-140-3p
[0264] Q.sub.2=hsa-mirR-106a/hsa-mirR-30c
[0265] Q.sub.3=hsa-mirR-106a/hsa-mirR-486-5p
[0266] Q.sub.4=hsa-mirR-140-3p/hsa-mirR-17
[0267] Q.sub.5=hsa-mirR-140-5p/hsa-mirR-660
[0268] Q.sub.6=hsa-mirR-15b/hsa-mirR-660
[0269] Q.sub.7=hsa-mirR-15b/hsa-mirR-92a
[0270] Q.sub.8=hsa-mirR-17/hsa-mirR-30c
[0271] Q.sub.9=hsa-mirR-17/hsa-mirR-451
[0272] Q.sub.10=hsa-mirR-17/hsa-mirR-486-5p
[0273] Q.sub.11=hsa-mirR-19b/hsa-mirR-451
[0274] Q.sub.12=hsa-mirR-19b/hsa-mirR-660
[0275] Q.sub.13=hsa-mirR-19b/hsa-mirR-92a
[0276] Q.sub.14=hsa-mirR-21/hsa-mirR-92a
[0277] Q.sub.15=hsa-mirR-28-3p/hsa-mirR-660
[0278] Q.sub.16=hsa-mirR-28-3p/hsa-mirR-92a
[0279] This diagnostic signature was then used to verify the
presence of disease in the plasma samples collected before
identification of the disease by spiral CT. In the training set, 11
out of 20 (55%) of the cases are classified as being in presence of
disease and, very interestingly, of these 11, 10 are either
pessimistic diagnosis cases or belonging to patients in whom the
tumour was identified in the later years of the screening, or where
more aggressive tumours with worse prognoses were identified.
[0280] Very similar results were obtained in the validation set,
since in 10 out of 15 (66.6%) pre-disease samples the signature of
the presence of disease was presented. There are only 4 miRNA
ratios in common between the risk signatures and the diagnosis
signatures; also partially different are the microRNAs involved:
mir-17, mir-660, mir-92a, mir-106a, mir-19b are the most
deregulated microRNAs at the moment of the diagnosis of pulmonary
tumour.
[0281] Identification of a Signature Based on the MiRNAs for Risk
of Development of Aggressive Pulmonary Tumour
[0282] The microRNA profiles of the pre-disease samples with
unfavorable prognosis were identified and 10 miRNA ratios
identified that were able to recognize 5 out of 5 patients in the
first set, 4 out of 5 in the validation set and with a specificity
in both of 100%. Note that mir-221, mir-660, mir-486-5p, mir-28-3p,
mir-197, mir-106a, mir-451, mir-140-5p and mir-16 are the
deregulated microRNAs.
[0283] The miRNA ratios of this third example are listed below and
are also reported in FIG. 4C.
[0284] Q.sub.1=hsa-mirR-106a/hsa-mirR-660
[0285] Q.sub.2=hsa-mirR-140-5p/hsa-mirR-486-5p
[0286] Q.sub.3=hsa-mirR-16/hsa-mirR-197
[0287] Q.sub.4=hsa-mirR-197/hsa-mirR-486-5p
[0288] Q.sub.5=hsa-mirR-197/hsa-mirR-660
[0289] Q.sub.6=hsa-mirR-221/hsa-mirR-451
[0290] Q.sub.7=hsa-mirR-221/hsa-mirR-660
[0291] Q.sub.8=hsa-mirR-28-3p/hsa-mirR-451
[0292] Q.sub.9=hsa-mirR-28-3p/hsa-mirR-486-5p
[0293] Q.sub.10=hsa-mirR-28-3p/hsa-mirR-660
[0294] This signature was then tested on the pre-disease samples of
the patients having a good prognosis in the training set and in the
validation set. The signature classifies, respectively in the two
sets, 33.3% and 45% of the samples; FIG. 2 illustrates a
Kaplan-Meier survival curve of patients with or without the
signature of risk of aggressive disease; the curve with the
aggressive signature is represented in a continuous line and
identified by RAD+ (risk of aggressive disease +) while the curve
without the signature of risk of aggressive disease is represented
by a discontinuous line and identified by RAD- (risk of aggressive
disease -) in plasma samples collected 1-2 years before
identification of the disease by spiral CT.
[0295] Of interest is the fact that the majority of the identified
samples belong to individuals who developed the tumour between the
III and the V year of screening, independently of the degree of the
tumour. This supports the previous observation on the tumoral and
normal samples of lung tissue, where a different profile of
microRNA was present respectively in the tumoral and normal tissue
of the same patients. It is worthy of note that among the patients
having a tumour diagnosed in the second year of screening (all
tumours at stage Ia and Ib), only one case with stage Ib exhibited
the signature of aggressive risk.
[0296] Identification of a Signature Based on MiRNAs for Prognosis
of Patients Identified by Spiral CT
[0297] The samples from patients having a pessimistic prognosis,
collected at the moment of the diagnosis of the disease, were
analysed, revealing a signature of 10 miRNA ratios, all containing
mir-486-5p, which identifies 7 out of 8 patients with a pessimistic
prognosis in the training set, 2 out of 3 of the validation set and
no control pool in either data set.
[0298] The miRNA ratios of this fourth example are listed below and
are also reported in FIG. 4D.
[0299] Q.sub.1=hsa-mirR-106a/hsa-mirR-486-5p
[0300] Q.sub.2=hsa-mirR-126/hsa-mirR-486-5p
[0301] Q.sub.3=hsa-mirR-142-3p/hsa-mirR-486-5p
[0302] Q.sub.4=hsa-mirR-148a/hsa-mirR-486-5p
[0303] Q.sub.5=hsa-mirR-15b/hsa-mirR-486-5p
[0304] Q.sub.6=hsa-mirR-17/hsa-mirR-486-5p
[0305] Q.sub.7=hsa-mirR-197/hsa-mirR-486-5p
[0306] Q.sub.8=hsa-mirR-21/hsa-mirR-486-5p
[0307] Q.sub.9=hsa-mirR-221/hsa-mirR-486-5p
[0308] Q.sub.10=hsa-mirR-28-3p/hsa-mirR-486-5p
[0309] Further, only 2 out of 11 and 2 out of 13 patients having a
good prognosis, respectively in the first and second set, are
positive for this signature. FIG. 3 reports a Kaplan-Meier survival
curve of patients with or without the signatures for presence of
aggressive disease (respectively identified with the continuous
line of PAD+, which stands for the presence of aggressive disease+,
and with the broken line of PAD-, standing for the presence of
aggressive disease -) in plasma samples collected at the moment of
identification of the disease by spiral CT.
[0310] Further, this signature was used to classify the pre-disease
samples in both data sets. Half of the patients with pessimistic
prognosis also present this aggressiveness signature, while for
those with good prognosis of the 6 positives for this signature, 5
are tumours identified after the third year of screening.
[0311] Note that mir-486-5p, compared with mir-21, mir-126,
mir-15b, mir-148a, mir-142-3p, mir-17, mir-197, mir-221, mir-28-3p
and mir-106a, is always under-expressed in the plasma of patients
with a pessimistic prognosis.
[0312] From the above-reported results, the inventors deduced that
the microRNAs present in the plasma are useful for identifying the
presence of the pulmonary tumour even 1-2 years before detection by
spiral CT and further for predicting the development of types of
more aggressive pulmonary cancer, indicating the possibility of
selecting individuals at high risk on the basis of profiles of
circulating microRNA.
Example 2
miRNA Treatment
[0313] The instant example demonstrates modifying the level of two
microRNAs of our plasma signatures in a lung cancer cell line
(A549). Mir-486 and mir-660 were down-modulated in plasma samples
of patients with lung cancer and in particular in those who have
developed the aggressive form of the disease. In FIG. 9 microRNA
levels were measured by qReal-Time PCR in 20 paired tumor and
normal lung tissue of the same patients enrolled in the
CT-screening trial used as validation set. Row Ct data were
normalized on the housekeeping miRNA RNU6B (DCt). The final
expression values were obtained with the formula: 2 (-DCt of the
tumor tissue)/2 (-DCt of the normal lung). Values
>1.fwdarw.upregulated in tumor tissue.
Values<1.fwdarw.downregulated in tumor tissue. The results in
FIG. 9 show that these two miRNA were downregulated in the tumor
tissue compared with the normal lung tissue.
[0314] In FIG. 10 mirVana.TM. miRNA Mimic (Applied biosystem) were
used to transfect lung cancer cell line expressing constitutively
the Green Fluorescence Protein (A549-GFP), accordingly with the
Lipofectamine2000 standard protocol (Invitrogen). 24 h hours after
transfection, cells were plated in multiwell plate to assess the
proliferation capacity. Real time measurements of the GFP signal
were measured every 24 h with a fluorescent multiplate reader
(Tecan M1000) using the wavelengths of the GFP. In FIG. 10, 549-GFP
transfected with the miRNA mimic mir-486-5p and mir-660 showed a
reduced proliferative capacity compared to the wild type and the
miRNA mimic scrambled (ctrl-) cell lines.
[0315] In FIG. 11, 549-GFP cells were transfected with miRNA mimics
as reported before. 24 h hour after transfection cell were plated
in Falcon.TM. FluoroBlok.TM. Cell Culture Inserts 8.0 .mu.m (BD
biosciences) placed in a 24-wells plate. Cell migration capacity
was assess measuring GFP signal using the bottom reading tool of
the Tecan M1000, in this way it was possible to read just the
signal of the cells passed through the membrane of the insert. Real
time migration was followed for 4 days. In FIG. 11, 549-GFP
transfected with the miRNA mimic mir-486-5p and mir-660 showed a
reduced migration capacity compared to the wild type and the miRNA
mimic scrambled (ctrl-) cell lines.
[0316] Thus, the results show that if these two miRNA were restored
in the cancer cell line the proliferation (FIG. 10) and the
migration (FIG. 11) capability of cancer cells were significantly
reduced. These preliminary results support the idea of using these
miRNAs for a putative therapeutic approach.
Example 3
Lung Cancer Detection and Survival
[0317] INT-IEO cohort (training set). Lung cancer was diagnosed in
38 subjects, 22 in the first 2 y and 16 from the 3rd to 5th y of
screening, including one interval cancer at 4th y. The frequency of
stage I was 63% (77% in first 2 y vs. 44% in the last 3 y), and
adenocarcinoma was 71% (95% in first 2 y vs. 63% in the last 3 y;
Table XI).
TABLE-US-00043 TABLE XI CT Year Characteristic 1-2 3-5 Total Lung
Cancer 22 16 38 Resected 21 (95) 12 (75) 33* (87) Stage I 17 (77) 7
(44) 24 (63) Stage II-IV 5 (23) 9 (56) 14 (37) Adeno 17 (95) 10
(63) 27 (71) *28 tumor tissue and 24 normal lung samples were
available for miRNA expression analysis. The number in parenthesis
is the percent of all detected lung cancers.
[0318] Median follow-up time for the 38 lung cancer cases was 75
mo, with 60% 5-y overall survival (95% C.I.: 43-74%). Five-y
overall survival was 92% for stage 1 and 7% for stages II-IV
(P<0.001; FIG. 12A). When the year of detection was considered,
5-y overall survival was 77% for cancers diagnosed in the first 2 y
compared with 36% for those detected from 3rd to 5th y of screening
(P=0.005; FIG. 12B), indicating that incident cancers represent a
more aggressive disease. Year of detection and tumor stage were
significantly associated (.chi..sup.2 test, P=0.034). In the subset
of CT year 1-2/stage I, 5-y survival was 94% (95% C.I.: 65.0-99.1).
In the whole group of stage I, after exclusion of one death from
second primary lung cancer and one from end-stage chronic
obstructive pulmonary disorder (COPD), 5-y survival was 100%.
[0319] Multicentric Italian Lung Detection (MILD) cohort
(validation set). At the end of 4th year of screening in the MILD
trial, lung cancer was diagnosed in 53 subjects, 24 in the first 2
y, and 23 in the 3rd and 4th year. Six interval cancers were
diagnosed: one in the 1st y, two in the 2nd y, and three in the 3rd
y. Early stage disease (Ia-Ib) was diagnosed in 28 (53%) patients,
and adenocarcinoma was diagnosed in 30 (57%) of patients. Because
this trial is ongoing, no interim analysis was performed so far.
However, even if the median follow-up time of 23 mo is relatively
short, we could divide the 53 patients in two groups of reasonable
size: 14 patients with poor prognosis (dead or alive with incurable
disease) and 39 patients with good prognosis (alive without
disease).
[0320] miRNA Expression Profiling in Tumor and Normal Lung
[0321] miRNA profiles of 28 tumors and 24 paired normal lung
tissues were analyzed using a miRNA microarray platform. Validation
of the differentially expressed miRNAs was done using qRT-PCR.
[0322] By class comparison and class prediction analyses (using
both paired and unpaired algorithms), expression of 56 miRNAs was
significantly different at the nominal 0.001 level of the
univariate test. The top 10 deregulated miRNAs that discriminate
CT-detected lung cancer from normal lung tissue were: mir-7,
mir-21, mir-200b, mir-210, mir-219-1, miR-324 (up-regulated),
mir-126, mir-451, mir-30a, and mir-486 (down-regulated; Table
XII).
TABLE-US-00044 TABLE XII Tumor vs. miRNAs deregulated Normal
Tissues (p < 0.001) Direction Fold Change mir-7-2-prec Up 1.3
mir-126 Down 0.4 mir-200b Up 1.3 mir-210 Up 3.0 mir-219-1 Up 1.6
mir-21 Up 2.9 mir-324-5p Up 1.3 mir-451 Down 0.5 mir-486-5p Down
0.5 mir-30a Down 0.6
[0323] This list included alterations previously identified in
symptomatic lung cancer patients (e.g., mir-21 and the mir-200
family, known to be involved in pathways such as survival,
apoptosis, epithelial-mesenchymal transition) and some unidentified
changes (e.g., down-regulation of miR-486 and miR-451).
[0324] To validate the results obtained with microarray
hybridization, the levels of the two most regulated miRNAs (mir-21
and mir-486) were evaluated in tumor and normal samples by qRT-PCR,
which confirmed the previous observation.
[0325] mIRNA Expression in Tissues is Associated with
Clinical-Pathological Features
[0326] Possible association of miRNA expression profiles with
clinical-pathological characteristics of the patients was then
investigated (Table XIII). Two miRNAs (mir-205 and mir-21)
significantly discriminated adenocarcinoma from squamous cell
carcinoma histotypes (P.ltoreq.0.001). Mir-518e and mir-144 were
down-regulated in tumors with a faster growth rate, and higher
levels of mir-429, member of the mir-200 family, correlated with a
worse disease-free survival (DFS).
TABLE-US-00045 TABLE XIII Clinical- Pathological Tumor Tissue
Normal Tissue Charac- Direc- Direc- teristics miRNA tion P value
miRNA tion P value Histotype mir-205 Down <0.001 (ADC v. SCC or
others) mir-21- Up <0.001 pre Growth Rate mir-518e Up <0.001
mir- Up <0.001 Diameter 30d* (.gtoreq.50% vs. >50%) mir-144-
Up <0.001 pre Disease-free mir-429 Down 0.003 mir-34b Up 0.001
Survival (Alive vs. Dead or Relapse)
[0327] The miRNA expression profile of tumors detected in the first
2 y of the screening was significantly different from the profile
of tumors appearing after the 2nd y, with differential expression
of eight miRNAs (mir-128, mir-129, mir-369-3p, mir-193, mir-339-3p,
mir-185, mir-346, and mir-340). These results indicate that these
groups of tumors display different miRNA profiles associated with
distinct aggressive features, where the incident tumors grow
faster.
[0328] miRNA expression analysis on normal lung tissues also
discriminated subjects identified in the first 2 y from those of
later years of screening (miR-126*, mir-126, let-7c, mir-222,
mir-30e, mir-1-2, mir-29b-1, mir-30d-prec, mir-15a, mir-16; FIG.
13). Significant associations were found between miRNAs expression
in normal lung and reduction of forced expiratory volume (FEV;
mir-379 and mir-29-1*), faster tumor growth (mir-30d*), DFS of the
patients (mir-34b; Table XIII). The results obtained by microarray
hybridization were independently validated by qRT-PCR.
[0329] Although there was no significant difference in smoking
habits (packs-per-year, time from smoking cessation), patients
detected in years 3-5 showed a higher proportion of severe COPD
(GOLD criteria.gtoreq.2, 33% vs. 5%; .chi..sup.2 test, P=0.02).
[0330] These findings indicate that specific miRNA signatures in
normal lung microenvironment are associated with tumor
aggressiveness and clinical history of the patients.
[0331] Pathways Enrichment Analysis
[0332] For the miRNA signature discriminating tumor from normal
samples, pathway enrichment analysis was performed using
DIANA-mirPath software on the gene targets predicted by microT-4.0,
Pic-Tar, and TargetScan-5. This analysis showed that many of the
predicted miRNA targets are involved in critical pathway affected
in cancer such as survival, apoptosis, epithelial-mesenchymal
transition, and proliferation (XIV).
TABLE-US-00046 TABLE XIV KEGG Pathway (P < 0.001) No. of Genes
MAPK Signaling Pathway 159 Regulation of Actin Cytoskeleton 133
Focal Adhesion 130 Wnt Signaling Pathway 102 Axon Guidance 93
Insulin Signaling Pathway 92 TGF-Beta Signaling Pathway 69 ErbB
Signaling Pathway 64 Adherens Junction 62 Ribosome 3
[0333] mIRNA Expression Profiling in Plasma Samples: Study
Design
[0334] Validated circulating biomarkers in plasma/serum could
potentially represent the gold standard for a noninvasive routine
clinical application. We reasoned that ideal miRNA biomarkers
should be identified before the onset of the tumors and be able to
predict aggressive versus indolent disease development.
[0335] To determine whether specific miRNA signatures are already
detectable in plasma samples collected before the detection of the
disease, we performed high-throughput miRNA expression profiles of
plasma samples using TaqMan microfluidic cards (Applied
Biosystems). We first analyzed plasma samples collected >1 y
before disease development and at the time of disease detection
(positive CT/surgery) in the training set (CT-screening trial
INT-IEO). We generated miRNA signatures that were then validated in
plasma samples (also predisease and at disease detection) of a
validation set (CT-screening MILD cohort). The
clinical-pathological characteristics of training and validation
sets are shown in FIG. 1. As control groups, we tested 15 pools of
plasma samples (5-7 individuals per pool, 81 individuals in total)
collected from disease-free subjects (negative spiral-CT) from both
trials, with age, sex, and smoking habits distribution similar to
those of cases.
[0336] Using microfluidic cards, 113 miRNAs were found to be always
expressed in all plasma samples, and a subset of 100 miRNAs was
found to be consistently expressed in the 15 control pools, with a
good reproducibility among biological duplicates (FIG. 15). These
100 miRNAs were then used to identify circulating biomarkers of
risk, diagnosis, and prognosis in plasma samples collected before
or in presence of CT-detected disease.
[0337] miRNA Ratios as Bioinformatics Tools for miRNA Analysis
[0338] Because the normalization of miRNA data in plasma samples is
still a controversial issue, the ratios between the expression
values of all miRNAs consistently expressed in plasma were
computed. Each value of a single miRNA was compared with the values
of all of the other 99 miRNAs, and 4,950 ratios were obtained and
subsequently used to analyze differences between classes of samples
resulting in the definition of ratios with clinical relevance. When
using microfluidic cards, there is general agreement on the
normalization of single miRNA expression using the mean values of
expression of all miRNAs of each card (13). To validate the
robustness of the miRNA ratios method, we compared the results
obtained independently by the two methods in the microfluidic
cards. The results showed that the miRNAs mostly deregulated in
multiple ratios were the same as those detected using the
normalization on the mean expression value, thus confirming the
robustness of the ratios method.
[0339] The use of miRNA ratios seems to be an easily applicable
method with potential for general clinical use that avoids the need
for large scale, high-throughput analyses and was therefore used to
develop clinically useful signatures based on circulating
biomarkers.
[0340] Identification of Diagnostic and Prognostic Circulating
miRNA Profiles in Plasma Samples Collected Before and at the Time
of Disease Detection
[0341] Class comparison analysis was initially performed in the
training set to identify a group of miRNA ratios showing
statistically significant differences between prediagnostic,
diagnostic, and disease-free plasma (P<0.05). These ratios were
then technically validated, in a subset of samples, by TaqMan
MicroRNA assays.
[0342] To assess the consistency of miRNA ratios within the control
pools, we compared the value of each ratio in two control pools
with the mean value resulting from the analysis of the individual
samples composing the pools. We found that the values were
consistent.
[0343] However, because some ratios showed a high individual
variability in the control subjects, possibly leading to a high
number of false positives, we considered for further analyses only
those ratios with minimal intrapool variability.
[0344] The signatures obtained were then used to calculate
specificity and sensitivity in an independent validation set.
[0345] Because the range of miRNA expression levels in the two
datasets was consistently different, possibly due to a storage
effect (14), the patients in each dataset were compared with the
respective control groups.
[0346] For the generation of the signatures predicting clinical
outcome (both before and in presence of CT-detected disease),
because of the small number of events, we grouped the two datasets.
Cases with bad outcome were compared with the respective control
pools, and the signatures obtained were then tested for their power
to discriminate patients with bad (dead and alive with disease) or
good (disease free) prognosis in the whole cohort.
[0347] mIRNA Signature Identifies Individuals at Risk to Develop
Lung Cancer
[0348] To investigate whether there are molecular markers
predicting development of lung cancer, samples collected from
patients 1 and/or 2 y before detection of the disease by CT were
analyzed and compared with the control pools of heavy-smoking
individuals (FIG. 14A-14C).
[0349] A signature of 16 ratios composed by 15 miRNAs could
discriminate correctly 18 of 20 samples from subjects developing
lung cancer in the training set (90% sensitivity) and resulted
positive in only 1 of the 5 control pools (80% specificity). In the
validation set, this signature identified 12 of 15 samples
collected before lung cancer detection by spiral-CT, with
sensitivity of 80% and specificity of 90% (AUC-ROC=0.85,
P<0.0001; FIG. 4A). The predictive value of this signature was
evaluated to be useful up to 28 mo before the disease, and mir-660,
mir-140-5p, mir-451, mir-28-3p, mir-30c, and mir-92a are the most
frequently deregulated miRNAs.
[0350] mIRNA Signature with Diagnostic Value
[0351] Plasma samples collected at surgery or at time of disease
detection by spiral CT were compared with pools of disease-free
individuals to identify a miRNA profile associated with lung cancer
diagnosis. In the training set, a panel of 16 ratios involving 13
different miRNAs classified 16 of 19 patients, with a sensitivity
of 84% and a specificity of 80%. In the validation set plasma
samples, 12 of 16 patients were correctly discriminated, with a
sensitivity of 75% and a specificity of 100% (AUC-ROC=0.88,
P<0.0001; FIG. 4B).
[0352] The lower sensitivity observed may be related to the
presence of a higher number of small, early-stage nodules with
indolent behavior in this series and the inclusion of two patients
misclassified by both the signature of diagnosis and risk.
[0353] The diagnostic signature was then used for class prediction
of predisease plasma samples in the same series. In the training
set, 11 of 20 (55%) cases were classified as individuals with
disease and, very interestingly, 10 of these 11 cases were
characterized by poor prognosis (dead or alive with disease) or
belonged to the group of patients identified from 3rd to 5th y of
screening. In the validation set, similar results were obtained,
with presence of the disease signature already in 10 of 15 (66.6%)
predisease plasma samples. Moreover, looking at the three
predisease samples of interval cancer cases (patients who developed
lung cancer few months after a negative CT result), only 1 patient
was classified by the risk signature. Instead, 2 cases (including
the 1 identified by risk signature) already displayed the
diagnostic signature 8-9 mo before disease detection. The interval
cancer case not recognized by any signatures had a stage 1a tumor
with good outcome, suggesting the presence of a low-risk
nodule.
[0354] Only 4 ratios were shared by the signatures of risk and of
diagnosis, and the miRNAs involved were partially different.
mir-17, mir-660, mir-92a, mir-106a, and mir-19b were the most
frequently deregulated at the time of lung cancer diagnosis.
[0355] Overall, these findings strengthen the observation that
circulating miRNA in plasma is detectable well before clinical
disease detection by spiral CT, indicating the possibility to
select high-risk groups on the basis of miRNA profiling.
[0356] mIRNA Signature of Risk to Develop Aggressive Lung
Cancer
[0357] We analyzed the miRNA expression profiles in predisease
plasma samples of individuals with poor clinical outcome to define
a signature of miRNAs identifying individuals at high risk to
develop an aggressive disease.
[0358] A signature of 10 ratios, composed of 9 different miRNAs,
identified 5 of 5 patients with poor prognosis (dead or with
progressive disease) in this first set (100% sensitivity and 100%
specificity). In the validation set, 4 of 5 patients with poor
prognosis were correctly classified, including a patient with poor
prognosis who developed an interval cancer. The sensitivity of this
signature in the validation set was 80% with 100% specificity.
[0359] mir-221, mir-660, mir-486-5p, mir-28-3p, mir-197, mir-106a,
mir-451, mir-140-5p, and mir-16 are the miRNAs deregulated in the
signature of aggressive disease.
[0360] The signature was then used for class prediction of
predisease plasma samples of patients with good prognosis in
training and validation sets. The signature identified 5 of 15
(33.3%) patients in the training set and 5 of 11 (45%) patients in
the validation set (FIG. 4C). Interestingly, in both the datasets,
most of these classified samples belonged to patients whose tumor
was detected after the 3rd y of screening. This finding supports
our previous observation on tissue samples where a distinct miRNA
profile was identified in tumor and normal tissues of the same
patients. Noticeably, among the patients with tumor diagnosed in
the 2nd y of screening (all stage 1a and 1b tumors), only one case
with stage 1b tumor had the risk signature of aggressive
disease.
[0361] These results suggest that miRNA profiles in predisease
plasma samples are able to predict the development of tumors with
worse prognosis and might even be helpful in pinpointing those
early stage tumors at high risk of aggressive evolution.
[0362] mIRNA Expression in Plasma Samples at Time of Disease
Detection and Prognosis
[0363] Then we looked at the association between miRNA expression
and prognosis in plasma samples collected at the time of lung
cancer diagnosis by generating a signature composed by 10 ratios,
all containing mir-486-5p. This signature identified 7 of 8
patients with bad prognosis in the training set (88% sensitivity
and 100% specificity). The signature of aggressive disease was
observed also in 2 of 10 samples with good prognosis, one of these
having a stage 1b tumor. In the validation set, only 3 plasma
samples collected in presence of disease of patients with poor
prognosis were available, and 2 of these had the profile of
aggressive disease. The third case was misclassified by all of the
analyses performed in all plasma samples collected during screening
evaluations (FIG. 4D).
[0364] Again, this signature was used for class prediction of
predisease plasma samples of patients in the training and
validation sets. Half of the predisease samples of patients with
bad prognosis were positive for both the signatures of aggressive
disease, whereas the predisease samples of patients with good
prognosis that showed the signature of aggressive disease belonged
mainly (5 of 6) to patients with tumors detected after the 3rd y of
screening. It is noteworthy that, although individuals in the
training set have an extended follow-up and 5-y overall survival
data are available, the shorter median follow-up observation time
(14 mo) for patients in validation set might affect the strength of
the prognostic signatures.
[0365] mir-486-5p, compared with mir-21, mir-126, mir-15b,
mir-148a, mir-142-3p, mir-17, mir-197, mir-221, mir-28-3p, and
mir-106a, appears to be always down-regulated in plasma of patients
with bad outcome.
[0366] Analysis
[0367] The investigation of biological and molecular features of
indolent and aggressive lung cancer is critical to identify
specific risk markers for lung cancer development, to achieve the
earliest possible prediction and intervention and, potentially, to
define novel therapeutic targets.
[0368] In this study, we have focused on the role of miRNAs as
biomarkers of lung disease by taking advantage of the availability
of both tissue samples (tumor and normal lung) and multiple plasma
samples, collected before and at the time of disease detection,
from patients enrolled in two different spiral-CT screening trials
with extended follow-up. These patients developed tumors displaying
variable aggressive behavior during the course of the trials.
[0369] Although previous studies reported miRNA expression profiles
predicting recurrence and prognosis only in lung tumor samples
collected at the time of surgery for symptomatic lung cancer, our
study provides unique results on miRNA signatures able to identify
the presence of aggressive lung cancer not only in tumor, but also
in normal lung tissues and in plasma samples of patients. Moreover,
miRNAs deregulated in plasma samples collected before clinical
appearance of disease were powerful molecular predictors of
high-risk disease development.
[0370] In tumor samples, we confirmed up-regulation of known miRNAs
such as mir-21, a miRNA with proproliferative and anti-apoptotic
function that is reported to target PTEN, and described
down-regulation of two miRNAs (mir-486 and mir-451) that are
involved in maintenance of self-renewal capacity of
bronchio-alveolar stem cells. Association analyses revealed that
expression of mir-205 and mir-21 are markers linked to squamous
cell carcinoma (SCC) and adenocarcinoma (ADC) histology,
respectively, confirming previous studies on the validity of
studying miRNA expression in support of histopathological diagnosis
for a precise classification of tumor histology. Interestingly,
miRNAs that were deregulated in the more aggressive tumors
identified in later years of screening are involved in adhesion and
invasion pathways: miR-339 was reported to negatively regulate
intercellular cell adhesion molecule (ICAM)-1, and mir-128a has
been involved in TGF.beta. pathway promotion of tumor cell invasion
and metastasis. This miRNA specifically targets FOXO1A, a
transcription factor involved in AKT signaling and apoptosis
inhibition.
[0371] The finding of miRNA expression profiles associated with
aggressive disease and poor survival in normal lung tissues of the
patients strengthens the existing evidence on the critical
influence of the normal lung microenvironment on tumor development
and, in the present study, on tumor aggressiveness. It is possible
to speculate that these markers might represent molecular signs of
a "soil" that, after extensive damage caused by smoking, becomes
permissive, or even promoting, for cancer development. Several
miRNAs deregulated in normal lung tissue of the patients undergoing
surgery are involved in major pathways linked to cancer. In
particular, miR-126 is known to promote angiogenesis by repressing
the inhibitors of VEGF signaling spred1 and pik3r2, and let-7 is
involved in proinflammatory programs. In addition, AKT signaling is
the major pathway influenced by miR-222, miR-30 regulates
connective tissue growth factor, and mir-29b modulates
anti-apoptotic and prometastatic matrix molecules by repressing
Mc1-1. It is also interesting to note the down-regulation of
mir-34b in patients with worse DFS, because mir-34b is a well known
target of p53, which cooperates to control cell proliferation and
adhesion-independent growth. The observation of a possible
prognostic role of several miRNAs in normal lung opens up the
possibility of innovative therapeutic strategies targeting the host
rather than the tumor itself.
[0372] Because circulating miRNAs in plasma could be more
tissue-specific than tumor-specific, we decided to perform a
high-throughput miRNA expression in plasma profiling using
microfluidic cards. We then developed multiplex real-time PCR
assays to validate, as single PCR assays, those miRNA signatures
significantly associated with clinical characteristics of the
patients. We have optimized simple and highly reproducible miRNA
assays and formulated a suitable algorithm for qRT-PCR data
validation in plasma using miRNA reciprocal ratios. Our findings
suggest that the assessment of a number of miRNAs in plasma by
qRT-PCR assays is a potentially useful and clinically applicable
procedure to improve lung cancer management.
[0373] miRNAs deregulated in tissue specimens were rarely detected
in plasma samples, further strengthening the high
tissue-specificity of miRNAs and suggesting a predictive role of
plasma miRNAs independent from tissue specimens. We observed that a
partially different set of miRNAs were deregulated in plasma before
and at the time of disease. This finding might be explained by the
consideration that genes and pathways necessary in the earlier
phases of disease development are different from those required for
the maintenance and the progression of the tumor.
[0374] Overall, the 21 miRNAs composing the signatures of risk,
diagnosis, and prognosis in plasma belong to major pathways:
cellular aging (mir-19b, mir-17, mir-106), bronchioalveolar and
hematopoietic stem cells renewal (mir-486, mir-106a, 142-3p), tumor
recurrence in stage I NSCLC (mir-27b; mir-106a; mir-19b; mir-15b
mir-16, mi-21), and lung cancer aggressiveness (mir-221, mir-222).
In particular mir-17, mir-92a, mir-19b, and mir-106a are oncomirs
belonging to the same family responsible for increased
proliferation, repression of apoptosis and induction of
angiogenesis. mir-197 regulates expression of the tumor suppressor
gene FUS1, whose expression is lost in a large proportion of lung
tumors. mir-28-3p is located in a chromosomal region that is
frequently amplified in lung cancer (3q28). mir-221 blocks PTEN
expression leading to activation of the AKT pathway, and is
suggested to play an important role in cell growth and invasiveness
by targeting the PTEN/AKT pathway. Alterations of these pathways
represent well established and meaningful risk factors in lung
cancer. Finally, in a recent publication regarding circulating
miRNAs, mir-21, mir-126, and mir-486-5p were also identified as
potential blood-based biomarkers with diagnostic value in NSCLC
patients.
[0375] The identification of miRNA signatures in plasma samples
collected 1-2 y before disease that predict cancer development and
prognosis is potentially useful in the selection of high-risk
individuals who need to undergo spiral-CT surveillance. It is
noteworthy that specific miRNA signatures in predisease plasma
samples are able to predict and discriminate the development of the
more aggressive, early metastatic tumors that are frequently
undetectable by yearly spiral-CT. This information could be
certainly helpful to prompt these individuals in pharmacological
smoking cessation programs and possibly to propose more specific
imaging for detection of occult metastatic disease (e.g., PET,
whole-body MRI), as well as nontoxic treatments such as enrollment
in prophylactic vaccination programs. Furthermore, the signature of
a potentially aggressive disease could also help in the clinical
management of the frequent early-stage nodules detected during
CT-screening trials improving diagnostic algorithms.
[0376] Considering the noninvasive characteristics of plasma
sampling and the reproducible and easy detection of miRNA markers,
plasma-based miRNA biomarkers can be used in clinical practice and
may help to avoid overdiagnosis and overtreatment of low-risk
disease and late detection of high-risk and early metastatic
disease (Boeri et al., Proc Natl Acad Sci USA. 108(9):3713-8,
2011)
[0377] Materials and Methods
[0378] CT Screening Protocols. In the INT/IEO screening cohort of
1,035 high-risk heavy smokers, the median age was 58 y (range
50-84), 739 (71%) were men, average tobacco consumption was 26
cigarettes daily for 37 y (median pack/years=40), and 14% were
former smokers.
[0379] The following clinical parameters were evaluated: age, sex,
pack/years index, forced expiratory ventilation in 1 s (FEV1%), CT
year, pathological stage of detected cancers, histology, size,
growth rate, standard uptake value (SUV) of PET. The .chi..sup.2
test was used to examine the associations between predictor
variables. Overall survival (OS) curves of lung cancer patients
were estimated with the Kaplan-Meier method and compared with the
log-rank test, using time from lung cancer onset until death or by
censoring at the last follow-up date. Statistical analyses were
carried out using SAS (SAS Institute Inc., Cary, N.C.) and R
software. Two-sided P values <0.05 were considered statistically
significant.
[0380] The second trial was a prospective randomized trial named
Multicentric Italian Lung Detection trial (MILD) launched in 2005
(MILD trial, validation set). Current or former smokers, at least
50 years old and without history of cancer within the prior 5 y,
were randomized in two study groups: a control group undergoing a
program of primary prevention with pulmonary function test
evaluation and an early-detection group where periodic spiral-CT
was associated with primary prevention and pulmonary function test
evaluation. The early-detection group was further randomized in two
arms: yearly low-dose spiral CT vs. spiral CT every 2 y. A total of
2,352 subjects were randomized in one of the two CT screening
arms.
[0381] During enrollment and annual recall of all volunteers in
both trials, whole blood was collected in EDTA vacuum tubes and
plasma immediately separated by two centrifugation steps at 1,258
relative centrifugal force.times.g at 4.degree. C. and stored in a
biological bank, supported by a database recording all clinical and
epidemiological information. Tissue samples from lung tumors and
matching normal lung tissue (sampled at distance from the cancer
lesion) were also collected when available from patients undergoing
surgical resections. Tissue and plasma specimens were obtained
according to the Internal Review and the Ethics Boards of the
Istituto Nazionale Tumori of Milan.
[0382] miRNA Microarray Analysis in Tissue Samples
[0383] For expression analyses, we first used a set of 28
snap-frozen spiral-CT detected lung primary tumors and 24 paired
normal lung tissues, collected during the INT/IEO trial. miRNA
labeling and hybridization was performed using 5 .mu.g of total
TRIzol (Invitrogen) extracted RNA. The miRNA microarray (Ohio State
University Comprehensive Cancer Center, version 2.0) used contained
probes for 460 mature miRNAs spotted in quadruplicate (235 Homo
sapiens, 222 Mus musculus, and three Arabidopsis thaliana) with
annotated active sites selected for oligonucleotide design.
Hybridization signals were detected with streptavidin-Alexa-647
conjugate, and scanned images (Perkin-Elmer ScanArray XL5K Scanner)
were quantified using the GeneSpring software version 7.2 (Silicon
Genetics, Redwood City, Calif.).
[0384] Statistical and Bioinformatics Analyses on Tissue
Samples
[0385] On the microarray chips, after background subtraction and
data transformation (to convert any negative value to 0.01), the
average value of the four spots was normalized using a per-chip
50th percentile method that normalizes each chip on its median.
[0386] Class Comparison and Class Prediction Analyses. Statistical
analyses were performed using BRB ArrayTools 3.8.1 software
developed by Dr. Richard Simon at the National Cancer Institute.
MicroRNA differentially expressed between two classes were
considered significant at the nominal 0.001-0.003 level of the
univariate test based on 10,000 random permutations and were used
for class prediction analyses with the multiple methods tool.
[0387] miRNA Profiling in Plasma Samples
[0388] miRNA expression profiling was performed in 40 plasma
samples, collected 12-28 mo before and at time of the disease
detection, from 19 patients in the training set and in 34 plasma
samples from 22 patients from the validation set. Using mirVana
PARISKit (Ambion), total RNA was extracted from 200-.mu.l plasma
samples, and miRNA expression was determined using the Megaplex
Pools Protocol on microfluidic card type A (Applied Biosystems).
The control groups were represented by 15 pools of 5-7 plasma
samples each from disease-free individuals enrolled in the same
trials and matched to the patients by sex, age, and smoking habit.
For each micro-fluidic card (sample), the Ct of every miRNA was
determined using the program SDS 2.2.2 (Applied Biosystems) and
setting a threshold of 0.2 and a manual baseline from 3 to 18
cycles.
[0389] Quantitative Real-Time PCR. Tissues
[0390] Starting from 20 ng of total RNA in the reverse
transcription (RT) step, TaqMan MicroRNA Assays (Applied
Biosystems) were used for quantitative real-time PCR following
their standard procedures. Relative quantification was performed
using the .DELTA..DELTA.Ct method using as housekeeping the miRNA
RNU-6B.
[0391] Plasma samples. Starting from 3 n1 of the same plasma
free-circulating RNA used for the Megaplex Pools Protocol (Applied
Biosystems), selected miRNAs were validated with the Multiplex
Pools Protocol (Applied Biosystems).
[0392] Results
[0393] FIG. 15 shows the consistency of miRNA expression
measurement in plasma samples by quantitative real-time PCR
considering only the 100 miRNAs selected for class comparison
analysis. (A) Technical duplicates were performed for two patient
samples (341 and 380) and for a control pool (M2). The graphical
representation was performed plotting the first miRNA values
obtained on abscissa (duplicate A) and the values obtained in the
second evaluation in ordinate (duplicate B). The linear regression
value shows a good reproducibility of measurements. (B) Correlation
between two different control pools. (C) Graphical representation
of average values of all Pearson correlation coefficients between
control pools, technical duplicates, and between all patient
samples (before and at time of disease).
Sequence CWU 1
1
1231110RNAHomo sapiens 1cuggauacag aguggaccgg cuggccccau cuggaagacu
agugauuuug uuguugucuu 60acugcgcuca acaacaaauc ccagucuacc uaauggugcc
agccaucgca 110223RNAHomo sapiens 2uggaagacua gugauuuugu ugu
23322RNAHomo sapiens 3caacaaaucc cagucuaccu aa 22498RNAHomo sapiens
4uugaggccuu aaaguacugu agcagcacau caugguuuac augcuacagu caagaugcga
60aucauuauuu gcugcucuag aaauuuaagg aaauucau 98522RNAHomo sapiens
5uagcagcaca ucaugguuua ca 22622RNAHomo sapiens 6cgaaucauua
uuugcugcuc ua 22789RNAHomo sapiens 7gucagcagug ccuuagcagc
acguaaauau uggcguuaag auucuaaaau uaucuccagu 60auuaacugug cugcugaagu
aagguugac 89881RNAHomo sapiens 8guuccacucu agcagcacgu aaauauuggc
guagugaaau auauauuaaa caccaauauu 60acugugcugc uuuaguguga c
81922RNAHomo sapiens 9uagcagcacg uaaauauugg cg 221022RNAHomo
sapiens 10ccaauauuac ugugcugcuu ua 221184RNAHomo sapiens
11gucagaauaa ugucaaagug cuuacagugc agguagugau augugcaucu acugcaguga
60aggcacuugu agcauuaugg ugac 841223RNAHomo sapiens 12caaagugcuu
acagugcagg uag 231322RNAHomo sapiens 13acugcaguga aggcacuugu ag
221487RNAHomo sapiens 14cacuguucua ugguuaguuu ugcagguuug cauccagcug
ugugauauuc ugcugugcaa 60auccaugcaa aacugacugu gguagug 871523RNAHomo
sapiens 15aguuuugcag guuugcaucc agc 231696RNAHomo sapiens
16acauugcuac uuacaauuag uuuugcaggu uugcauuuca gcguauauau guauaugugg
60cugugcaaau ccaugcaaaa cugauuguga uaaugu 961722RNAHomo sapiens
17aguuuugcag guuugcauuu ca 221823RNAHomo sapiens 18ugugcaaauc
caugcaaaac uga 231972RNAHomo sapiens 19ugucggguag cuuaucagac
ugauguugac uguugaaucu cauggcaaca ccagucgaug 60ggcugucuga ca
722022RNAHomo sapiens 20uagcuuauca gacugauguu ga 222121RNAHomo
sapiens 21caacaccagu cgaugggcug u 212286RNAHomo sapiens
22gguccuugcc cucaaggagc ucacagucua uugaguuacc uuucugacuu ucccacuaga
60uugugagcuc cuggagggca ggcacu 862322RNAHomo sapiens 23aaggagcuca
cagucuauug ag 222422RNAHomo sapiens 24cacuagauug ugagcuccug ga
222571RNAHomo sapiens 25gcgacuguaa acauccucga cuggaagcug ugaagccaca
gaugggcuuu cagucggaug 60uuugcagcug c 712622RNAHomo sapiens
26uguaaacauc cucgacugga ag 222722RNAHomo sapiens 27cuuucagucg
gauguuugca gc 222888RNAHomo sapiens 28accaaguuuc aguucaugua
aacauccuac acucagcugu aauacaugga uuggcuggga 60gguggauguu uacuucagcu
gacuugga 882922RNAHomo sapiens 29uguaaacauc cuacacucag cu
223022RNAHomo sapiens 30cugggaggug gauguuuacu uc 223189RNAHomo
sapiens 31accaugcugu agugugugua aacauccuac acucucagcu gugagcucaa
gguggcuggg 60agaggguugu uuacuccuuc ugccaugga 893222RNAHomo sapiens
32cugggagagg guuguuuacu cc 223372RNAHomo sapiens 33agauacugua
aacauccuac acucucagcu guggaaagua agaaagcugg gagaaggcug 60uuuacucuuu
cu 723423RNAHomo sapiens 34uguaaacauc cuacacucuc agc 233522RNAHomo
sapiens 35cugggagaag gcuguuuacu cu 223670RNAHomo sapiens
36guuguuguaa acauccccga cuggaagcug uaagacacag cuaagcuuuc agucagaugu
60uugcugcuac 703722RNAHomo sapiens 37uguaaacauc cccgacugga ag
223822RNAHomo sapiens 38cuuucaguca gauguuugcu gc 223984RNAHomo
sapiens 39gugcucgguu uguaggcagu gucauuagcu gauuguacug uggugguuac
aaucacuaac 60uccacugcca ucaaaacaag gcac 844023RNAHomo sapiens
40uaggcagugu cauuagcuga uug 234122RNAHomo sapiens 41caaucacuaa
cuccacugcc au 224278RNAHomo sapiens 42cuuucuacac agguugggau
cgguugcaau gcuguguuuc uguaugguau ugcacuuguc 60ccggccuguu gaguuugg
784323RNAHomo sapiens 43agguugggau cgguugcaau gcu 234422RNAHomo
sapiens 44uauugcacuu gucccggccu gu 224575RNAHomo sapiens
45ucaucccugg guggggauuu guugcauuac uuguguucua uauaaaguau ugcacuuguc
60ccggccugug gaaga 754622RNAHomo sapiens 46ggguggggau uuguugcauu ac
224775RNAHomo sapiens 47ugcccuggcu caguuaucac agugcugaug cugucuauuc
uaaagguaca guacugugau 60aacugaagga uggca 754822RNAHomo sapiens
48caguuaucac agugcugaug cu 224921RNAHomo sapiens 49uacaguacug
ugauaacuga a 215079RNAHomo sapiens 50acuguccuuu uucgguuauc
augguaccga ugcuguauau cugaaaggua caguacugug 60auaacugaag aaugguggu
795121RNAHomo sapiens 51uacaguacug ugauaacuga a 215281RNAHomo
sapiens 52ccuuggccau guaaaagugc uuacagugca gguagcuuuu ugagaucuac
ugcaauguaa 60gcacuucuua cauuaccaug g 815323RNAHomo sapiens
53aaaagugcuu acagugcagg uag 235422RNAHomo sapiens 54cugcaaugua
agcacuucuu ac 225585RNAHomo sapiens 55cgcuggcgac gggacauuau
uacuuuuggu acgcgcugug acacuucaaa cucguaccgu 60gaguaauaau gcgccgucca
cggca 855621RNAHomo sapiens 56cauuauuacu uuugguacgc g 215722RNAHomo
sapiens 57ucguaccgug aguaauaaug cg 225888RNAHomo sapiens
58acaaugcuuu gcuagagcug guaaaaugga accaaaucgc cucuucaaug gauuuggucc
60ccuucaacca gcuguagcua ugcauuga 8859102RNAHomo sapiens
59gggagccaaa ugcuuugcua gagcugguaa aauggaacca aaucgacugu ccaauggauu
60ugguccccuu caaccagcug uagcugugca uugauggcgc cg 1026022RNAHomo
sapiens 60uuuggucccc uucaaccagc ug 2261100RNAHomo sapiens
61ugugucucuc ucuguguccu gccagugguu uuacccuaug guagguuacg ucaugcuguu
60cuaccacagg guagaaccac ggacaggaua ccggggcacc 1006222RNAHomo
sapiens 62cagugguuuu acccuauggu ag 226321RNAHomo sapiens
63uaccacaggg uagaaccacg g 216487RNAHomo sapiens 64gacagugcag
ucacccauaa aguagaaagc acuacuaaca gcacuggagg guguaguguu 60uccuacuuua
uggaugagug uacugug 876521RNAHomo sapiens 65cauaaaguag aaagcacuac u
216623RNAHomo sapiens 66uguaguguuu ccuacuuuau gga 236786RNAHomo
sapiens 67uggggcccug gcugggauau caucauauac uguaaguuug cgaugagaca
cuacaguaua 60gaugauguac uaguccgggc accccc 866822RNAHomo sapiens
68ggauaucauc auauacugua ag 226920RNAHomo sapiens 69uacaguauag
augauguacu 207088RNAHomo sapiens 70caccuugucc ucacggucca guuuucccag
gaaucccuua gaugcuaaga uggggauucc 60uggaaauacu guucuugagg ucaugguu
887123RNAHomo sapiens 71guccaguuuu cccaggaauc ccu 237222RNAHomo
sapiens 72ggauuccugg aaauacuguu cu 227368RNAHomo sapiens
73gaggcaaagu ucugagacac uccgacucug aguaugauag aagucagugc acuacagaac
60uuugucuc 687422RNAHomo sapiens 74aaaguucuga gacacuccga cu
227522RNAHomo sapiens 75ucagugcacu acagaacuuu gu 227675RNAHomo
sapiens 76ggcugugccg gguagagagg gcagugggag guaagagcuc uucacccuuc
accaccuucu 60ccacccagca uggcc 757723RNAHomo sapiens 77cggguagaga
gggcaguggg agg 237822RNAHomo sapiens 78uucaccaccu ucuccaccca gc
227995RNAHomo sapiens 79ccagcucggg cagccguggc caucuuacug ggcagcauug
gauggaguca ggucucuaau 60acugccuggu aaugaugacg gcggagcccu gcacg
958022RNAHomo sapiens 80caucuuacug ggcagcauug ga 228122RNAHomo
sapiens 81uaauacugcc ugguaaugau ga 2282110RNAHomo sapiens
82aaagauccuc agacaaucca ugugcuucuc uuguccuuca uuccaccgga gucugucuca
60uacccaacca gauuucagug gagugaaguu caggaggcau ggagcugaca
1108322RNAHomo sapiens 83uccuucauuc caccggaguc ug 228421RNAHomo
sapiens 84gauuucagug gagugaaguu c 2185110RNAHomo sapiens
85acccggcagu gccuccaggc gcagggcagc cccugcccac cgcacacugc gcugccccag
60acccacugug cgugugacag cggcugaucu gugccugggc agcgcgaccc
1108622RNAHomo sapiens 86cugugcgugu gacagcggcu ga 2287110RNAHomo
sapiens 87ccgccccggg ccgcggcucc ugauugucca aacgcaauuc ucgagucuau
ggcuccggcc 60gagaguugag ucuggacguc ccgagccgcc gcccccaaac cucgagcggg
1108821RNAHomo sapiens 88ugauugucca aacgcaauuc u 218922RNAHomo
sapiens 89agaguugagu cuggacgucc cg 2290110RNAHomo sapiens
90ugaacaucca ggucuggggc augaaccugg cauacaaugu agauuucugu guucguuagg
60caacagcuac auugucugcu ggguuucagg cuaccuggaa acauguucuc
1109122RNAHomo sapiens 91accuggcaua caauguagau uu 229223RNAHomo
sapiens 92agcuacauug ucugcugggu uuc 239382RNAHomo sapiens
93gcuucgcucc ccuccgccuu cucuucccgg uucuucccgg agucgggaaa agcuggguug
60agagggcgaa aaaggaugag gu 829422RNAHomo sapiens 94aaaagcuggg
uugagagggc ga 229579RNAHomo sapiens 95aauuaauccc ucucuuucua
guucuuccua gagugaggaa aagcuggguu gagagggcaa 60acaaauuaac uaauuaauu
7996138RNAHomo sapiens 96uguuauuuuu ugucuucuac cuaagaauuc
ugucucuuag gcuuucucuu cccagauuuc 60ccaaaguugg gaaaagcugg guugagaggg
caaaaggaaa aaaaaagaau ucugucucug 120acauaauuag auagggaa
1389722RNAHomo sapiens 97aaaagcuggg uugagagggc aa 229888RNAHomo
sapiens 98uuugcauuaa aaaugaggcc uucucuuccc aguucuuccc agagucagga
aaagcugggu 60ugagagggua gaaaaaaaau gauguagg 889950RNAHomo sapiens
99cuucucuuuc caguucuucc cagaauuggg aaaagcuggg uugagagggu
5010020RNAHomo sapiens 100aaaagcuggg uugagagggu 2010148RNAHomo
sapiens 101uucucguccc aguucuuccc aaaguugaga aaagcugggu ugagagga
4810248RNAHomo sapiens 102uucucuuccc aguucuucuu ggagucagga
aaagcugggu ugagagga 4810319RNAHomo sapiens 103aaaagcuggg uugagagga
1910453RNAHomo sapiens 104gccuucucuu cccaguucuu ccuggagucg
gggaaaagcu ggguugagaa ggu 5310518RNAHomo sapiens 105aaagcugggu
ugagaagg 1810683RNAHomo sapiens 106cugacuaugc cuccccgcau ccccuagggc
auugguguaa agcuggagac ccacugcccc 60aggugcugcu ggggguugua guc
8310723RNAHomo sapiens 107cgcauccccu agggcauugg ugu 2310820RNAHomo
sapiens 108acugccccag gugcugcugg 2010983RNAHomo sapiens
109cgccggccga ugggcgucuu accagacaug guuagaccug gcccucuguc
uaauacuguc 60ugguaaaacc guccauccgc ugc 8311022RNAHomo sapiens
110uaauacuguc ugguaaaacc gu 2211172RNAHomo sapiens 111cuugggaaug
gcaaggaaac cguuaccauu acugaguuua guaaugguaa ugguucucuu 60gcuauaccca
ga 7211222RNAHomo sapiens 112aaaccguuac cauuacugag uu
2211368RNAHomo sapiens 113uggguauagc aagagaacca uuaccauuac
uaaacucagu aaugguaacg guuuccuugc 60cauuccca 6811422RNAHomo sapiens
114uagcaagaga accauuacca uu 2211568RNAHomo sapiens 115gcauccugua
cugagcugcc ccgaggcccu ucaugcugcc cagcucgggg cagcucagua 60caggauac
6811622RNAHomo sapiens 116uccuguacug agcugccccg ag 2211721RNAHomo
sapiens 117cggggcagcu caguacagga u 2111888RNAHomo sapiens
118ucucaggcug ugacccucua gagggaagcg cuuucuguug gcuaaaagaa
aagaaagcgc 60uucccuucag aguguuaacg cuuugaga 8811922RNAHomo sapiens
119cucuagaggg aagcgcuuuc ug 2212021RNAHomo sapiens 120aaagcgcuuc
ccuucagagu g 2112197RNAHomo sapiens 121cugcuccuuc ucccauaccc
auugcauauc ggaguuguga auucucaaaa caccuccugu 60gugcauggau uacaggaggg
ugagccuugu caucgug 9712222RNAHomo sapiens 122uacccauugc auaucggagu
ug 2212321RNAHomo sapiens 123accuccugug ugcauggauu a 21
* * * * *