U.S. patent application number 15/671856 was filed with the patent office on 2018-03-29 for mirna fingerprint in the diagnosis of lung cancer.
The applicant listed for this patent is Comprehensive Biomarker Center GMBH. Invention is credited to Markus Beier, Anne Borries, Andreas Keller, Eckart Meese.
Application Number | 20180087111 15/671856 |
Document ID | / |
Family ID | 42470815 |
Filed Date | 2018-03-29 |
United States Patent
Application |
20180087111 |
Kind Code |
A1 |
Keller; Andreas ; et
al. |
March 29, 2018 |
MIRNA FINGERPRINT IN THE DIAGNOSIS OF LUNG CANCER
Abstract
The present invention provides novel methods for diagnosing
diseases based on the determination of specific miRNAs that have
altered expression levels in disease states compared to healthy
controls.
Inventors: |
Keller; Andreas;
(Puttlingen, DE) ; Meese; Eckart;
(Huetschenhausen, DE) ; Borries; Anne;
(Heidelberg, DE) ; Beier; Markus; (Weinheim,
DE) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Comprehensive Biomarker Center GMBH |
Heidelberg |
|
DE |
|
|
Family ID: |
42470815 |
Appl. No.: |
15/671856 |
Filed: |
August 8, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13376281 |
Jan 19, 2012 |
9758827 |
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PCT/EP10/57942 |
Jun 7, 2010 |
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15671856 |
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61184452 |
Jun 5, 2009 |
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61213971 |
Aug 3, 2009 |
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61287521 |
Dec 17, 2009 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
C12Q 1/6809 20130101;
G16B 40/00 20190201; C12Q 2600/112 20130101; C12Q 2600/178
20130101; C12Q 1/6883 20130101; C12Q 1/6886 20130101; G16B 25/00
20190201; C12Q 2600/106 20130101; C12Q 2600/158 20130101; C12Q
1/6809 20130101; C12Q 2525/207 20130101 |
International
Class: |
G06F 19/20 20110101
G06F019/20; G06F 19/24 20110101 G06F019/24 |
Claims
1.-24. (canceled)
25. A method for diagnosing lung cancer in a patient comprising the
steps of: (a) determining an expression profile of a predetermined
set of miRNAs in a blood sample from a patient, wherein the
predetermined set of miRNAs comprises one or more miRNAs selected
from the group consisting of hsa-miR-15a, hsa-miR-126, hsa-miR-195,
hsa-miR-26b, hsa-miR-19a, and hsa-miR-18a*, and (b) comparing said
expression profile to a reference expression profile, wherein the
comparison of said determined expression profile to said reference
expression profile allows for the diagnosis of lung cancer.
26. The method of claim 25, wherein said predetermined set of
miRNAs comprises or consists of. (i) hsa-miR-22, hsa-miR-15a, and
hsa-miR-98, (ii) hsa-let-7i, hsa-let-7d, hsa-miR-22, hsa-miR-15a,
and hsa-miR-98, (iii) hsa-miR-22, hsa-miR-15a, hsa-miR-98,
hsa-miR-19a, and hsa-miR-574-5p, (iv) hsa-miR-15a, hsa-miR-98,
hsa-miR-19a, hsa-miR-574-5p, and hsa-miR-324-3p, (v) hsa-miR-126,
hsa-miR-423-5p, hsa-let-7i, hsa-let-7d, hsa-miR-22, hsa-miR-15a,
hsa-miR-98, hsa-miR-19a, hsa-miR-574-5p, and hsa-miR-324-3p, (vi)
hsa-miR-15a, hsa-miR-98, hsa-miR-19a, hsa-miR-574-5p,
hsa-miR-324-3p, hsa-miR-20b, hsa-miR-25, hsa-miR-195, hsa-let-7e,
hsa-let-7c, and hsa-let-7f, (vii) hsa-let-7d, hsa-miR-15a,
hsa-miR-19a, hsa-miR-324-3p, and hsa-miR-25, (viii) hsa-miR-1909,
hsa-let-7c, and hsa-miR-15a, (ix) hsa-miR-15a, hsa-miR-93*, and
hsa-miR-30e, (x) hsa-miR-299-3p, hsa-miR-423-3p, hsa-miR-18a*,
hsa-miR-1909, hsa-let-7c, and hsa-miR-15a, (xi) hsa-miR-1909,
hsa-let-7c, hsa-miR-15a, hsa-miR-425, hsa-miR-93*, and hsa-miR-665,
(xii) hsa-miR-604, hsa-miR-22, hsa-let-7b, hsa-miR-299-3p,
hsa-miR-423-3p, hsa-miR-18a*, hsa-miR-1909, hsa-let-7c,
hsa-miR-15a, and hsa-miR-425, or (xiii) hsa-miR-18a*, hsa-miR-1909,
hsa-let-7c, hsa-miR-15a, hsa-miR-425, hsa-miR-93*, hsa-miR-665,
hsa-miR-30e, hsa-miR-339-3p, and hsa-miR-1307.
27. The method of claim 25, wherein the blood sample is blood cell
sample.
28. The method of claim 27, wherein the blood cell sample comprises
erythrocytes, leukocytes and thrombocytes.
29. The method of claim 25, wherein the expression profile of the
predetermined set of miRNAs is determined using reverse-transcribed
miRNAs.
30. The method of claim 25, wherein the determination of the
expression profile of the predetermined set of miRNAs comprises the
steps of: (i) extracting total RNA from said blood sample, (ii)
reverse-transcribing the total RNA into cDNA, and (iii) amplifying
the cDNA and thereby quantifying said miRNAs.
31. The method of claim 25, wherein the diagnosis comprises
determining type, grade, and/or stage of cancer.
32. The method of claim 25, wherein the diagnosis comprises
determining survival rate, responsiveness to drugs, and/or
monitoring the course of the disease or the therapy, e.g.
chemotherapy, staging of the disease, measuring the response of a
patient to therapeutic intervention, segmentation of patients
suffering from the disease, identifying of a patient who has a risk
to develop the disease, predicting/estimating the occurrence,
preferably the severity of the occurrence of the disease,
predicting the response of a patient with the disease to
therapeutic intervention.
33. The method of claim 25, wherein the lung cancer selected from
the group consisting of lung carcinoid, lung pleural mesothelioma
and lung squamous cell carcinoma, in particular non-small cell lung
carcinoma.
34. The method of claim 25, wherein the determination of an
expression profile in step (a) comprises nucleic acid
hybridization, nucleic acid amplification, polymerase extension,
sequencing, mass spectroscopy or any combinations thereof, wherein
the nucleic acid hybridization is particularly performed using a
solid-phase nucleic acid biochip array, in particular a microarray,
a bead-based assay, or in situ hybridization or wherein the nucleic
acid amplification method is real-time PCR (RT-PCR).
35. A kit for diagnosing lung cancer comprising: (a) means for
determining an expression profile of a predetermined set of miRNAs
in a blood sample from a patient, wherein the predetermined set of
miRNAs comprises one or more miRNAs selected from the group
consisting of hsa-miR-15a, hsa-miR-126, hsa-miR-195, hsa-miR-26b,
hsa-miR-19a, and hsa-miR-18a*, and (b) a reference expression
profile of said predetermined set of miRNAs in a blood sample from
a healthy subject.
36. The kit of claim 35, wherein said predetermined set of miRNAs
comprises, essentially consists of or consists of. (i) hsa-miR-22,
hsa-miR-15a, and hsa-miR-98, (ii) hsa-let-7i, hsa-let-7d,
hsa-miR-22, hsa-miR-15a, and hsa-miR-98, (iii) hsa-miR-22,
hsa-miR-15a, hsa-miR-98, hsa-miR-19a, and hsa-miR-574-5p, (iv)
hsa-miR-15a, hsa-miR-98, hsa-miR-19a, hsa-miR-574-5p, and
hsa-miR-324-3p, (v) hsa-miR-126, hsa-miR-423-5p, hsa-let-7i,
hsa-let-7d, hsa-miR-22, hsa-miR-15a, hsa-miR-98, hsa-miR-19a,
hsa-miR-574-5p, and hsa-miR-324-3p, (vi) hsa-miR-15a, hsa-miR-98,
hsa-miR-19a, hsa-miR-574-5p, hsa-miR-324-3p, hsa-miR-20b,
hsa-miR-25, hsa-miR-195, hsa-let-7e, hsa-let-7c, and hsa-let-7f,
(vii) hsa-let-7d, hsa-miR-15a, hsa-miR-19a, hsa-miR-324-3p, and
hsa-miR-25, (viii) hsa-miR-1909, hsa-let-7c, and hsa-miR-15a, (ix)
hsa-miR-15a, hsa-miR-93*, and hsa-miR-30e, (x) hsa-miR-299-3p,
hsa-miR-423-3p, hsa-miR-18a*, hsa-miR-1909, hsa-let-7c, and
hsa-miR-15a, (xi) hsa-miR-1909, hsa-let-7c, hsa-miR-15a,
hsa-miR-425, hsa-miR-93*, and hsa-miR-665, (xii) hsa-miR-604,
hsa-miR-22, hsa-let-7b, hsa-miR-299-3p, hsa-miR-423-3p,
hsa-miR-18a*, hsa-miR-1909, hsa-let-7c, hsa-miR-15a, and
hsa-miR-425, or (xiii) hsa-miR-18a*, hsa-miR-1909, hsa-let-7c,
hsa-miR-15a, hsa-miR-425, hsa-miR-93*, hsa-miR-665, hsa-miR-30e,
hsa-miR-339-3p, and hsa-miR-1307.
Description
BACKGROUND OF THE INVENTION
[0001] MicroRNAs (miRNA) are a recently discovered class of small
non-coding RNAs (17-14 nucleotides). Due to their function as
regulators of gene expression they play a critical role both in
physiological and in pathological processes, such as cancer (Calin
and Croce 2006; Esquela-Kerscher and Slack 2006; Zhang, Pan et al.
2007; Sassen, Miska et al. 2008).
[0002] There is increasing evidence that miRNAs are not only found
in tissues but also in human blood both as free circulating nucleic
acids (also called circulating miRNAs) and in mononuclear cells. A
recent proof-of-principle study demonstrated miRNA expression
pattern in pooled blood sera and pooled blood cells, both in
healthy individuals and in cancer patients including patients with
lung cancer (Chen, Ba et al. 2008). In addition, a remarkable
stability of miRNAs in human sera was recently demonstrated (Chen,
Ba et al. 2008; Gilad, Meiri et al. 2008). These findings make
miRNA a potential tool for diagnostics for various types of
diseases based on blood analysis.
[0003] Lung cancer is the leading cause of cancer death worldwide
(Jemal, Siegel et al. 2008). Its five-year survival rate is among
the lowest of all cancer types and is markedly correlated to the
stage at the time of diagnosis (Scott, Howington et al. 2007).
Using currently existing techniques, more than two-thirds of lung
cancers are diagnosed at late stages, when the relative survival
rate is low (Henschke and Yankelevitz 2008). This reality calls for
the search of new biomarkers that are able to catch lung cancer
while it is still small and locally defined.
[0004] Various markers have been proposed to indicate specific
types of disorders and in particular cancer. However, there is
still a need for more efficient and effective methods and
compositions for the diagnosis of diseases and in particular
cancer.
SUMMARY OF THE INVENTION
[0005] The present invention provides novel methods for diagnosing
diseases based on the determination of specific miRNAs that have
altered expression levels in disease states compared to healthy or
other relevant controls. The present invention particularly
provides novel methods for the diagnosis and/or prognosis and/or
monitoring of lung cancer or related diseases in human individuals
based on miRNA analysis from samples derived from blood.
[0006] Subject-matter of the invention is a method for diagnosing
lung cancer, comprising the steps [0007] (a) determining an
expression profile of a predetermined set of miRNAs in a biological
sample from a patient; and [0008] (b) comparing said expression
profile to a reference expression profile,
[0009] wherein the comparison of said determined expression profile
to said reference expression profile allows for the diagnosis of
lung cancer.
[0010] A "biological sample" in terms of the invention means a
sample of biological tissue or fluid. Examples of biological
samples are sections of tissues, blood, blood fractions, plasma,
serum, etc. A biological sample may be provided by removing a
sample of cells from a subject, but can also be provided by using a
previously isolated sample. For example, a tissue sample can be
removed from a subject suspected of having a disease by
conventional biopsy techniques. In a preferred embodiment, a blood
sample is taken from the subject. In one embodiment, the blood or
tissue sample is obtained from the subject prior to initiation of
radiotherapy, chemotherapy or other therapeutic treatment.
According to the invention, the biological sample preferably is a
blood, plasma, PBMC (peripheral blood mononuclear cell) or a serum
sample. Further, it is also preferred to use blood cells, e.g.
erythrocytes, leukocytes or thrombocytes.
[0011] A biological sample from a patient means a sample from a
subject suspected to be affected by a disease. As used herein, the
term "subject" refers to any mammal, including both human and other
mammals. Preferably, the methods of the present invention are
applied to human subjects.
[0012] In step (a) of the method of the invention, an expression
profile of a predetermined set of miRNAs is determined. The
determination may be carried out by any convenient means for
determining nucleic acids. For expression profiling, qualitative,
semi-quantitative and preferably quantitative detection methods can
be used. A variety of techniques are well known to those of skill
in the art. In particular, the determination may comprise nucleic
acid hybridization and/or nucleic acid amplification steps.
[0013] Nucleic acid hybridization may for example be performed
using a solid phase nucleic acid biochip array, in particular a
microarray, beads, or in situ hybridization. The miRNA microarray
technology affords the analysis of a complex biological sample for
all expressed miRNAs. Nucleotides with complementarity to the
corresponding miRNAs are spotted or synthesized on coated carriers.
E.g., miRNAs isolated from the sample of interest may be labelled,
e.g. fluorescently labelled, so that upon hybridization of the
miRNAs to the complementary sequences on the carrier the resulting
signal indicates the occurrence of a distinct miRNA. Preferably,
microarray methods are employed that do not require a labeling of
the miRNAs prior to hybridization (FIG. 3-4) and start directly
from total RNA input. On one miRNA microarray, preferably the whole
predetermined set of miRNAs can be analyzed. Examples of preferred
hybridization assays are shown in FIGS. 1-4. The design of
exemplary miRNA capture probes for use in hybridization assays is
depicted in FIGS. 5 and 6.
[0014] Further, real-time or quantitative real-time polymerase
chain reaction (RT-RCR or qRT-PCR) can be used to detect also low
abandoned miRNAs. Furthermore, bead-based assays, e.g. the Luminex
platform, are suitable.
[0015] Alternative methods for obtaining expression profiles may
also contain sequencing, next generation sequencing or mass
spectroscopy.
[0016] The predetermined set of miRNAs in step (a) of the method of
the invention depends on the disease to be diagnosed. The inventors
found out that single miRNA biomarkers lack sufficient accuracy,
specificity and sensitivity, and therefore it is preferred to
analyze more complex miRNA expression patterns, so-called miRNA
signatures. The predetermined set of miRNAs comprises one or more,
preferably a larger number of miRNAs (miRNA signatures) that are
differentially regulated in samples of a patient affected by a
particular disease compared to healthy or other relevant
controls.
[0017] The expression profile determined in step (a) is
subsequently compared to a reference expression profile in step
(b). The reference expression profile is the expression profile of
the same set of miRNAs in a biological sample originating from the
same source as the biological sample from a patient but obtained
from a healthy subject. Preferably, both the reference expression
profile and the expression profile of step (a) are determined in a
blood or serum sample including whole blood, plasma, serum or
fractions thereof, or in a sample of peripheral blood mononuclear
cells, of erythrocytes, leukocytes and/or thrombocytes. It is
understood that the reference expression profile is not necessarily
obtained from a single healthy subject but may be an average
expression profile of a plurality of healthy subjects. It is
preferred to use a reference expression profile obtained from a
person of the same gender, and a similar age as the patient. It is
also understood that the reference expression profile is not
necessarily determined for each test. Appropriate reference
profiles stored in databases may also be used. These stored
references profiles may, e.g., be derived from previous tests. The
reference expression profile may also be a mathematical function or
algorithm developed on the basis of a plurality of reference
expression profiles.
[0018] The method of the invention is suitable for diagnosing lung
cancer. The diagnosis may comprise determining type, rate and/or
stage of lung cancer. The course of the disease and the success of
therapy such as chemotherapy may be monitored. The method of the
invention provides a prognosis on the survivor rate and enables to
determine a patient's response to drugs.
[0019] The inventors succeeded in developing a generally applicable
approach to arrive at miRNA signatures that are correlated with a
particular disease. The general work flow is depicted in FIG. 9. In
more detail, the following steps are accomplished: [0020] 1. miRNAs
are extracted from a biological sample of a patient, preferably a
blood or serum sample or a sample comprising erythrocytes,
leukocytes or thrombocytes, using suitable kits/purification
methods [0021] 2. The respective samples are measured using
experimental techniques. These techniques include but are not
restricted to: [0022] Array based approaches [0023] Real time
quantitative polymerase chain reaction [0024] Bead-based assays
(e.g. Luminex) [0025] Sequencing [0026] Next Generation Sequencing
[0027] Mass Spectroscopy [0028] 3. Mathematical approaches are
applied to gather information on the value and the redundancy of
single biomarkers. These methods include, but are not restricted
to: [0029] basic mathematic approaches (e.g. Fold Quotients, Signal
to Noise ratios, Correlation) [0030] statistical methods as
hypothesis tests (e.g. t-test, Wilcoxon-Mann-Whitney test), the
Area under the Receiver operator Characteristics Curve [0031]
Information Theory approaches, (e.g. the Mutual Information,
Cross-entropy) [0032] Probability theory (e.g. joint and
conditional probabilities) [0033] Combinations and modifications of
the previously mentioned examples [0034] 4. The information
collected in 3) are used to estimate for each biomarker the
diagnostic content or value. Usually, however, this diagnostic
value is too small to get a highly accurate diagnosis with accuracy
rates, specificities and sensitivities beyond the 90% barrier.
[0035] Please note that the diagnostic content for our miRNAs can
be found in the attached figures. These figures include the miRNAs
with the sequences, the fold quotient, the mutual information and
the significance value as computed by a t-test. [0036] 5. Thus
statistical learning/machine learning/bioinformatics/computational
approaches are applied to define subsets of biomarkers that are
tailored for the detection of diseases. These techniques includes
but are not restricted to [0037] Wrapper subset selection
techniques (e.g. forward step-wise, backward step-wise,
combinatorial approaches, optimization approaches) [0038] Filter
subset selection methods (e.g. the methods mentioned in 3) [0039]
Principal Component Analysis [0040] Combinations and modifications
of such methods (e.g. hybrid approaches) [0041] 6. The diagnostic
content of each detected set can be estimated by mathematical
and/or computational techniques to define the diagnostic
information content of subsets. [0042] 7. The subsets, detected in
step 5, which may range from only a small number (at least two) to
all measured biomarkers is then used to carry out a diagnosis. To
this end, statistical learning/machine
learning/bioinformatics/computational approaches are applied that
include but are not restricted to any type of supervised or
unsupervised analysis: [0043] Classification techniques (e.g. naive
Bayes, Linear Discriminant Analysis, Quadratic Discriminant
Analysis Neural Nets, Tree based approaches, Support Vector
Machines, Nearest Neighbour Approaches) [0044] Regression
techniques (e.g. linear Regression, Multiple Regression, logistic
regression, probit regression, ordinal logistic regression ordinal
Probit-Regression, Poisson Regression, negative binomial
Regression, multinomial logistic Regression, truncated regression)
[0045] Clustering techniques (e.g. k-means clustering, hierarchical
clustering, PCA) [0046] Adaptations, extensions, and combinations
of the previously mentioned approaches
[0047] The inventors surprisingly found out that the described
approach yields in miRNA signatures that provide high diagnostic
accuracy, specificity and sensitivity in the determination of lung
cancer.
[0048] According to the invention, the disease to be determined is
lung cancer, e.g. lung carcinoid, lung pleural mesothelioma or lung
squamous cell carcinoma, in particular non-small cell lung
carcinoma.
[0049] The inventors succeeded in determining miRNAs that are
differentially regulated in samples from lung cancer patients as
compared to healthy controls. A complete overview of all miRNAs
that are found to be differentially regulated in blood samples of
lung cancer patients is provided in the tables shown in FIGS. 10A
and 10B. In the tables shown in FIGS. 10A and 10B, the miRNAs that
are found to be differentially regulated are sorted in the order of
their mutual information and in the order of their t-test
significance as described in more detail below. Mutual information
(MI) (Shannon, 1984) is an adequate measure to estimate the overall
diagnostic information content of single biomarkers (Keller, Ludwig
et al., 2006). According to the invention mutual information is
considered as the reduction in uncertainty about the class labels
"0" for controls and "1" for tumor samples due to the knowledge of
the miRNA expression. The higher the value of the MI of a miRNA,
the higher is the diagnostic content of the respective miRNA. The
computation of the MI of each miRNA is explained in the
experimental section below.
[0050] For example, the predetermined set of miRNAs representative
for lung cancer comprises at least 1, 7, 10, 15, 20, 25, 30, 35,
40, 50, 75, 100 of the miRNAs selected from the group consisting of
hsa-miR-126, hsa-miR-423-5p, hsa-let-7i, hsa-let-7d, hsa-miR-22,
hsa-miR-15a, hsa-miR-98, hsa-miR-19a, hsa-miR-574-5p,
hsa-miR-324-3p, hsa-miR-20b, hsa-miR-25, hsa-miR-195, hsa-let-7e,
hsa-let-7c, hsa-let-7f, hsa-let-7a, hsa-let-7g, hsa-miR-140-3p,
hsa-miR-339-5p, hsa-miR-361-5p, hsa-miR-1283, hsa-miR-18a*,
hsa-miR-26b, hsa-miR-604, hsa-miR-423-3p, hsa-miR-93*, hsa-miR-29a,
hsa-miR-1248, hsa-miR-210, hsa-miR-19b, hsa-miR-453, hsa-miR-126*,
hsa-miR-188-3p, hsa-miR-624*, hsa-miR-505*, hsa-miR-425,
hsa-miR-339-3p, hsa-miR-668, hsa-miR-363*, hsa-miR-15b*,
hsa-miR-29c*, hsa-miR-550*, hsa-miR-34c-3p, hsa-miR-20a,
hsa-miR-374a, hsa-miR-145*, hsa-miR-302b, hsa-miR-106a,
hsa-miR-30e, hsa-miR-223, hsa-miR-1269, hsa-let-7b, hsa-miR-542-3p,
hsa-miR-516b*, hsa-miR-451, hsa-miR-519c-3p, hsa-miR-1244,
hsa-miR-602, hsa-miR-361-3p, hsa-miR-19a*, hsa-miR-433,
hsa-miR-1200, hsa-miR-522, hsa-miR-520f, hsa-miR-519c-5p,
hsa-miR-192, hsa-miR-1245, hsa-miR-151-5p, hsa-miR-1288,
hsa-miR-503, hsa-miR-563, hsa-miR-663b, hsa-let-7d*,
hsa-miR-199a-5p, hsa-miR-720, hsa-miR-1246, hsa-miR-338-5p,
hsa-miR-297, hsa-miR-1261, hsa-miR-922, hsa-miR-185, hsa-miR-611,
hsa-miR-1272, hsa-miR-1299, hsa-miR-335*, hsa-miR-497,
hsa-miR-1207-3p, hsa-miR-16, hsa-miR-1, hsa-miR-1291,
hsa-miR-138-2*, hsa-miR-136, hsa-miR-548d-3p, hsa-miR-561,
hsa-miR-548h, hsa-miR-331-3p, hsa-miR-186*, hsa-miR-145,
hsa-miR-17, hsa-miR-30b, hsa-let-7f-1*, hsa-miR-1305,
hsa-miR-129-5p, hsa-miR-1204, hsa-miR-106b*, hsa-miR-619,
hsa-miR-34a*, hsa-miR-652, hsa-miR-1256, hsa-miR-20b*,
hsa-miR-424*, hsa-miR-517a, hsa-miR-1284, hsa-miR-199b-3p,
hsa-miR-599, hsa-miR-411, hsa-miR-23b, hsa-miR-1302, hsa-miR-449a,
hsa-miR-548f, hsa-miR-597, hsa-miR-603, hsa-miR-1247, hsa-miR-1539,
hsa-miR-1911, hsa-miR-325, hsa-miR-409-5p, hsa-miR-182,
hsa-miR-658, hsa-miR-215, hsa-miR-147b, hsa-miR-30d, hsa-miR-378*,
hsa-miR-221*, hsa-miR-34b, hsa-miR-593*, hsa-miR-552, hsa-miR-378,
hsa-miR-143*, hsa-miR-1266, hsa-miR-554, hsa-miR-631, hsa-miR-609,
hsa-miR-30c, hsa-miR-28-5p, hsa-miR-23a, hsa-miR-645, hsa-miR-647,
hsa-miR-302b*, hsa-miR-607, hsa-miR-1289, hsa-miR-1324,
hsa-miR-513a-3p, hsa-miR-939, hsa-miR-29b, hsa-miR-665,
hsa-miR-18a, hsa-miR-1224-5p, hsa-miR-10a*, hsa-miR-181a*,
hsa-miR-218-2*, hsa-miR-371-3p, hsa-miR-377, hsa-miR-140-5p,
hsa-miR-301a, hsa-miR-1277, hsa-miR-130a*, hsa-miR-1912,
hsa-miR-193b, hsa-miR-214*, hsa-miR-216b, hsa-miR-302f,
hsa-miR-522*, hsa-miR-548j, hsa-miR-568, hsa-miR-648, hsa-miR-662,
hsa-miR-222, hsa-miR-1287, hsa-miR-891b, hsa-miR-342-3p,
hsa-miR-512-3p, hsa-miR-623, hsa-miR-208b, hsa-miR-16-1*,
hsa-miR-551b, hsa-miR-146b-3p, hsa-miR-520b, hsa-miR-449b,
hsa-miR-520g, hsa-miR-24-2*, hsa-miR-518f, hsa-miR-649, hsa-miR-32,
hsa-miR-151-3p, hsa-miR-454, hsa-miR-101, hsa-miR-19b-1*,
hsa-miR-509-5p, hsa-miR-144, hsa-miR-508-5p, hsa-miR-569,
hsa-miR-636, hsa-miR-937, hsa-miR-346, hsa-miR-506, hsa-miR-379*,
hsa-miR-1184, hsa-miR-579, hsa-miR-23b*, hsa-miR-1262, hsa-miR-153,
hsa-miR-520e, hsa-miR-632, hsa-miR-106a*, hsa-miR-31*,
hsa-miR-33b*, hsa-miR-654-3p, hsa-miR-99b*, hsa-miR-1278,
hsa-miR-135b, hsa-let-7c*, hsa-miR-1468, hsa-miR-374b*,
hsa-miR-514, hsa-miR-590-3p, hsa-miR-606, hsa-miR-369-3p,
hsa-miR-488, hsa-miR-128, hsa-miR-362-5p, hsa-miR-671-5p,
hsa-miR-874, hsa-miR-1911*, hsa-miR-1292, hsa-miR-194, hsa-miR-15b,
hsa-miR-342-5p, hsa-miR-125b-2*, hsa-miR-1297, hsa-miR-933,
hsa-miR-493*, hsa-miR-105, hsa-miR-141, hsa-miR-181c*,
hsa-miR-193a-3p, hsa-miR-302c, hsa-miR-485-5p, hsa-miR-499-3p,
hsa-miR-545, hsa-miR-548b-5p, hsa-miR-549, hsa-miR-576-5p,
hsa-miR-577, hsa-miR-583, hsa-miR-587, hsa-miR-624, hsa-miR-646,
hsa-miR-655, hsa-miR-885-5p, hsa-miR-194*, hsa-miR-299-5p,
hsa-miR-337-3p, hsa-miR-493, hsa-miR-497*, hsa-miR-519a,
hsa-miR-99a*, hsa-miR-1280, hsa-miR-523*, hsa-miR-198, hsa-miR-934,
hsa-miR-30d*, hsa-miR-452*, hsa-miR-548b-3p, hsa-miR-586,
hsa-miR-92b, hsa-miR-517b, hsa-miR-548a-3p, hsa-miR-875-5p,
hsa-miR-431*, hsa-miR-384, hsa-miR-644, hsa-miR-1185,
hsa-miR-29b-2*, hsa-miR-489, hsa-miR-566, hsa-miR-1538,
hsa-miR-28-3p, hsa-let-7f-2*, hsa-miR-1322, hsa-miR-1827,
hsa-miR-192*, hsa-miR-302e, hsa-miR-411*, hsa-miR-424,
hsa-miR-582-3p, hsa-miR-629*, hsa-miR-491-3p, hsa-miR-519b-3p,
hsa-miR-1197, hsa-miR-127-5p, hsa-miR-1286, hsa-miR-132*,
hsa-miR-33b, hsa-miR-553, hsa-miR-620, hsa-miR-708, hsa-miR-892b,
hsa-miR-520h, hsa-miR-500*, hsa-miR-551b*, hsa-miR-186,
hsa-miR-558, hsa-miR-26a, hsa-miR-1263, hsa-miR-211, hsa-miR-1304,
hsa-miR-220b, hsa-miR-891a, hsa-miR-1253, hsa-miR-1205,
hsa-miR-137, hsa-miR-154*, hsa-miR-555, hsa-miR-887, hsa-miR-363,
hsa-miR-1537, hsa-miR-219-1-3p, hsa-miR-220a, hsa-miR-222*,
hsa-miR-323-3p, hsa-miR-376b, hsa-miR-490-5p, hsa-miR-523,
hsa-miR-302a*, hsa-miR-27b*, hsa-miR-591, hsa-miR-888,
hsa-miR-376a*, hsa-miR-618, hsa-miR-1182, hsa-miR-532-3p,
hsa-miR-181b, hsa-miR-521, hsa-miR-545*, hsa-miR-9*, hsa-miR-920,
hsa-miR-571, hsa-miR-635, hsa-miR-200b, hsa-miR-455-5p,
hsa-miR-876-3p, hsa-miR-373*, hsa-miR-146a*, hsa-miR-122*,
hsa-miR-450b-3p, hsa-miR-24, hsa-miR-484, hsa-miR-103-as,
hsa-miR-380, hsa-miR-513a-5p, hsa-miR-509-3-5p, hsa-miR-873,
hsa-miR-556-5p, hsa-miR-369-5p, hsa-miR-653, hsa-miR-767-3p,
hsa-miR-516a-3p, hsa-miR-520c-3p, hsa-miR-708*, hsa-miR-924,
hsa-miR-520d-5p, hsa-miR-512-5p, hsa-miR-374a*, hsa-miR-921,
hsa-miR-1206, hsa-miR-1259, hsa-miR-525-5p, hsa-miR-200a*,
hsa-miR-1293, hsa-miR-372, hsa-miR-548a-5p, hsa-miR-548k,
hsa-miR-1300, hsa-miR-1264, hsa-miR-551 a, hsa-miR-196b,
hsa-miR-32*, hsa-miR-33a, hsa-miR-548d-5p, hsa-miR-616,
hsa-miR-876-5p, hsa-miR-508-3p, hsa-miR-26a-2*, hsa-miR-187,
hsa-miR-199a-3p, hsa-miR-96*, hsa-miR-18b, hsa-miR-432*,
hsa-miR-509-3p, hsa-miR-1183, hsa-miR-626, hsa-miR-513b,
hsa-miR-617, hsa-miR-9, hsa-miR-519e, hsa-miR-204, hsa-miR-29c,
hsa-miR-1268, hsa-miR-122, hsa-miR-7-2*, hsa-miR-15a*,
hsa-miR-181d, hsa-miR-219-5p, hsa-miR-302d, hsa-miR-34a,
hsa-miR-410, hsa-miR-33a*, hsa-miR-502-3p, hsa-miR-379,
hsa-miR-498, hsa-miR-518d-5p, hsa-miR-556-3p, hsa-miR-502-5p,
hsa-miR-31, hsa-miR-100, hsa-miR-296-3p, hsa-miR-615-5p,
hsa-miR-21*, hsa-miR-657, hsa-miR-651, hsa-miR-765, hsa-miR-548m,
hsa-miR-219-2-3p, hsa-miR-501-3p, hsa-miR-302a, hsa-miR-202*,
hsa-miR-206, hsa-miR-520d-3p, hsa-miR-548i, hsa-miR-511,
hsa-miR-30a, hsa-miR-1224-3p, hsa-miR-525-3p, hsa-miR-1225-5p,
hsa-miR-223*, hsa-miR-615-3p, hsa-miR-570, hsa-miR-320a,
hsa-miR-770-5p, hsa-miR-582-5p, hsa-miR-590-5p, hsa-miR-659,
hsa-miR-1251, hsa-miR-664, hsa-miR-488*, hsa-miR-548g, hsa-miR-802,
hsa-miR-542-5p, hsa-miR-190, hsa-miR-218-1*, hsa-miR-367*,
hsa-miR-450a, hsa-miR-367, hsa-miR-124, hsa-miR-767-5p,
hsa-miR-200c, hsa-miR-572, hsa-miR-526a, hsa-miR-936, hsa-miR-548n,
hsa-miR-21, hsa-miR-182*, hsa-miR-34c-5p, hsa-miR-429,
hsa-miR-628-5p, hsa-miR-29a*, hsa-miR-370, hsa-let-7a*,
hsa-miR-101*, hsa-miR-559, hsa-miR-217, hsa-miR-519b-5p,
hsa-miR-30e*, hsa-miR-147, hsa-miR-487b, hsa-miR-888*, hsa-miR-205,
hsa-miR-1257, hsa-miR-7, hsa-miR-296-5p, hsa-miR-1255a,
hsa-miR-380*, hsa-miR-1275, hsa-miR-330-5p, hsa-miR-1243,
hsa-miR-136*, hsa-miR-141*, hsa-miR-517c, hsa-miR-621,
hsa-miR-1915*, hsa-miR-541, hsa-miR-543, hsa-miR-942,
hsa-miR-26a-1*, hsa-miR-567, hsa-miR-184, hsa-miR-376a,
hsa-miR-124*, hsa-miR-1254, hsa-miR-1207-5p, hsa-miR-580,
hsa-let-7b*, hsa-miR-539, hsa-miR-520a-3p, hsa-miR-585,
hsa-miR-675b, hsa-miR-943, hsa-miR-573, hsa-miR-93, hsa-miR-27a*,
hsa-miR-613, hsa-miR-220c, hsa-miR-524-3p, hsa-miR-500,
hsa-miR-1201, hsa-miR-20a*, hsa-miR-1914*, hsa-miR-425*,
hsa-miR-515-3p, hsa-miR-377*, hsa-miR-504, hsa-miR-548c-3p,
hsa-miR-1276, hsa-miR-138, hsa-miR-431, hsa-miR-494, hsa-miR-448,
hsa-miR-633, hsa-miR-487a, hsa-miR-149, hsa-miR-300, hsa-miR-1826,
hsa-miR-127-3p, hsa-miR-486-5p, hsa-miR-148a, hsa-miR-1294,
hsa-miR-548l, hsa-miR-142-5p, hsa-miR-889, hsa-miR-365,
hsa-miR-99b, hsa-miR-200b*, hsa-miR-200a, hsa-miR-518e,
hsa-miR-612, hsa-miR-183*, hsa-miR-148b, hsa-miR-103, hsa-miR-548o,
hsa-miR-1203, hsa-miR-135a*, hsa-miR-383, hsa-miR-1913,
hsa-miR-373, hsa-miR-371-5p, hsa-miR-298, hsa-miR-758, hsa-miR-412,
hsa-miR-518c, hsa-miR-589*, hsa-miR-643, hsa-miR-592, hsa-miR-892a,
hsa-miR-944, hsa-miR-576-3p, hsa-miR-581, hsa-miR-625*,
hsa-miR-1260, hsa-miR-1281, hsa-miR-337-5p, hsa-miR-133b,
hsa-miR-92a-2*, hsa-miR-100*, hsa-miR-589, hsa-miR-218,
hsa-miR-224, hsa-miR-16-2*, hsa-miR-301b, hsa-miR-190b,
hsa-miR-375, hsa-miR-548p, hsa-miR-185*, hsa-miR-519d, hsa-miR-605,
hsa-miR-877, hsa-miR-125a-3p, hsa-miR-744*, hsa-miR-520c-5p,
hsa-miR-148a*, hsa-miR-212, hsa-miR-505, hsa-miR-496, hsa-miR-1323,
hsa-miR-548e, hsa-miR-628-3p, hsa-miR-1914, hsa-miR-584,
hsa-miR-135b*, hsa-miR-1295, hsa-miR-95, hsa-miR-133a,
hsa-miR-485-3p, hsa-miR-541*, hsa-miR-374b, hsa-miR-329,
hsa-miR-483-5p, hsa-miR-885-3p, hsa-let-7i*, hsa-miR-935,
hsa-miR-130b, hsa-miR-1274a, hsa-miR-1226, hsa-miR-518e*,
hsa-miR-1225-3p, hsa-miR-923, hsa-miR-196a*, hsa-miR-1270,
hsa-miR-1271, hsa-miR-610, hsa-miR-574-3p, hsa-miR-1282,
hsa-miR-10b*, hsa-miR-216a, hsa-miR-144*, hsa-miR-23a*,
hsa-miR-499-5p, hsa-miR-183, hsa-miR-490-3p, hsa-miR-330-3p,
hsa-let-7g*, hsa-miR-483-3p, hsa-miR-214, hsa-miR-34b*,
hsa-miR-302d*, hsa-miR-382, hsa-miR-454*, hsa-miR-1202,
hsa-miR-202, hsa-miR-544, hsa-miR-593, hsa-miR-760, hsa-miR-940,
hsa-let-7e*, hsa-miR-1237, hsa-miR-18b*, hsa-miR-630,
hsa-miR-519e*, hsa-miR-452, hsa-miR-26b*, hsa-miR-516b,
hsa-miR-299-3p, hsa-miR-381, hsa-miR-340, hsa-miR-132,
hsa-miR-142-3p, hsa-miR-125b-1*, hsa-miR-30c-2*, hsa-miR-627,
hsa-miR-1908, hsa-miR-1267, hsa-miR-507, hsa-miR-188-5p,
hsa-miR-486-3p, hsa-miR-596, hsa-miR-193a-5p, hsa-miR-671-3p,
hsa-miR-24-1*, hsa-miR-19b-2*, hsa-miR-1308, hsa-miR-208a,
hsa-miR-135a, hsa-miR-331-5p, hsa-miR-181c, hsa-miR-640,
hsa-miR-1909, hsa-miR-629, hsa-miR-10a, hsa-miR-491-5p,
hsa-miR-492, hsa-miR-516a-5p, hsa-miR-510, hsa-miR-1915,
hsa-miR-518c*, hsa-miR-1273, hsa-miR-25*, hsa-miR-744, hsa-miR-550,
hsa-miR-890, hsa-miR-1303, hsa-miR-650, hsa-miR-1227, hsa-miR-595,
hsa-miR-1255b, hsa-miR-1252, hsa-miR-455-3p, hsa-miR-345,
hsa-miR-96, hsa-miR-1321, hsa-miR-513c, hsa-miR-548c-5p,
hsa-miR-663, hsa-miR-320c, hsa-miR-320b, hsa-miR-654-5p,
hsa-miR-326, hsa-miR-1825, hsa-miR-328, hsa-miR-146b-5p,
hsa-miR-886-3p, hsa-miR-1909*, hsa-miR-1469, hsa-miR-338-3p,
hsa-miR-886-5p, hsa-miR-601, hsa-miR-1298, hsa-miR-1910,
hsa-miR-1226*, hsa-miR-421, hsa-miR-1471, hsa-miR-150*,
hsa-miR-1229, hsa-miR-17*, hsa-miR-320d, hsa-miR-10b, hsa-miR-766,
hsa-miR-600, hsa-miR-641, hsa-miR-340*, hsa-miR-616*,
hsa-miR-520a-5p, hsa-miR-1179, hsa-miR-1178, hsa-miR-30b*,
hsa-miR-155*, hsa-miR-138-1*, hsa-miR-501-5p, hsa-miR-191,
hsa-miR-107, hsa-miR-639, hsa-miR-518d-3p, hsa-miR-106b,
hsa-miR-129-3p, hsa-miR-1306, hsa-miR-187*, hsa-miR-125b,
hsa-miR-642, hsa-miR-30a*, hsa-miR-139-5p, hsa-miR-1307,
hsa-miR-769-3p, hsa-miR-532-5p, hsa-miR-7-1*, hsa-miR-196a,
hsa-miR-1296, hsa-miR-191*, hsa-miR-221, hsa-miR-92a-1*,
hsa-miR-1285, hsa-miR-518f*, hsa-miR-1233, hsa-miR-1290,
hsa-miR-598, hsa-miR-769-5p, hsa-miR-614, hsa-miR-578,
hsa-miR-1301, hsa-miR-515-5p, hsa-miR-564, hsa-miR-634,
hsa-miR-518b, hsa-miR-941, hsa-miR-376c, hsa-miR-195*,
hsa-miR-518a-5p, hsa-miR-557, hsa-miR-1228*, hsa-miR-22*,
hsa-miR-1234, hsa-miR-149*, hsa-miR-30c-1*, hsa-miR-200c*,
hsa-miR-1181, hsa-miR-323-5p, hsa-miR-1231, hsa-miR-203,
hsa-miR-302c*, hsa-miR-99a, hsa-miR-146a, hsa-miR-656,
hsa-miR-526b*, hsa-miR-148b*, hsa-miR-181a, hsa-miR-622,
hsa-miR-125a-5p, hsa-miR-152, hsa-miR-197, hsa-miR-27b,
hsa-miR-1236, hsa-miR-495, hsa-miR-143, hsa-miR-362-3p,
hsa-miR-675, hsa-miR-1274b, hsa-miR-139-3p, hsa-miR-130b*,
hsa-miR-1228, hsa-miR-1180, hsa-miR-575, hsa-miR-134,
hsa-miR-875-3p, hsa-miR-92b*, hsa-miR-660, hsa-miR-526b,
hsa-miR-422a, hsa-miR-1250, hsa-miR-938, hsa-miR-608, hsa-miR-1279,
hsa-miR-1249, hsa-miR-661, hsa-miR-1208, hsa-miR-130a,
hsa-miR-450b-5p, hsa-miR-432, hsa-miR-409-3p, hsa-miR-527,
hsa-miR-877*, hsa-miR-1238, hsa-miR-517*, hsa-miR-193b*,
hsa-miR-524-5p, hsa-miR-1258, hsa-miR-154, hsa-miR-637,
hsa-miR-588, hsa-miR-155, hsa-miR-664*, hsa-miR-1470, hsa-miR-105*,
hsa-miR-324-5p, hsa-miR-129*, hsa-miR-625, hsa-miR-519a*,
hsa-miR-181a-2*, hsa-miR-199b-5p, hsa-miR-27a, hsa-miR-518a-3p,
hsa-miR-1265, hsa-miR-92a, hsa-miR-29b-1*, hsa-miR-150,
hsa-miR-335, hsa-miR-638.
[0051] The miRNAs that provide the highest mutual information in
samples from lung cancer patients compared to healthy controls are
hsa-miR-361-5p, hsa-miR-23b, hsa-miR-126, hsa-miR-527, hsa-miR-29a,
hsa-let-7i, hsa-miR-19a, hsa-miR-28-5p, hsa-miR-185*, hsa-miR-23a,
hsa-miR-1914*, hsa-miR-29c, hsa-miR-505*, hsa-let-7d, hsa-miR-378,
hsa-miR-29b, hsa-miR-604, hsa-miR-29b, hsa-let-7b, hsa-miR-299-3p,
hsa-miR-423-3p, hsa-miR-18a*, hsa-miR-1909, hsa-let-7c,
hsa-miR-15a, hsa-miR-425, hsa-miR-93*, hsa-miR-665, hsa-miR-30e,
hsa-miR-339-3p, hsa-miR-1307, hsa-miR-625*, hsa-miR-193a-5p,
hsa-miR-130b, hsa-miR-17*, hsa-miR-574-5p, hsa-miR-324-3p (group
(a)).
[0052] Further, the measured miRNA profiles of FIGS. 10A and 10B
were classified according to their significance in t-tests as
described in more detail in the experimental section. The miRNAs
that performed best according to the t-test results are
hsa-miR-126, hsa-miR-423-5p, hsa-let-7i, hsa-let-7d, hsa-miR-22,
hsa-miR-15a, hsa-miR-98, hsa-miR-19a, hsa-miR-574-5p,
hsa-miR-324-3p, hsa-miR-20b, hsa-miR-25, hsa-miR-195, hsa-let-7e,
hsa-let-7c, hsa-let-7f, hsa-let-7a, hsa-let-7g, hsa-miR-140-3p,
hsa-miR-339-5p, hsa-miR-361-5p, hsa-miR-1283, hsa-miR-18a*,
hsa-miR-26b, hsa-miR-604, hsa-miR-423-3p, hsa-miR-93* (group (b)).
A comparison of a subset of 15 of these miRNAs is depicted in FIG.
12.
[0053] The miRNAs given above that have been grouped in the order
of their performance in the t-tests or in the order of their
MI-values provide the highest diagnostic power. Thus, preferably
the predetermined set of miRNAs for the diagnosis of lung cancer
comprises one or more nucleic acids selected from the above groups
(a) and (b) of miRNAs. The predetermined set of miRNAs should
preferably comprise at least 7, preferably at least 10, 15, 20 or
24 of the indicated nucleic acids. Most preferably, all of the
above indicated miRNAs are included in the predetermined set of
miRNAs. It is particularly preferred to include the 24, 20, 15, 10
or at least 7 of the first mentioned miRNAs in the order of their
performance in the t-tests or of their MI-values. A comparison of
the results obtained by determining 4, 8, 10, 16, 20, 24, 28 or 40
miRNAs provided in FIG. 13A-G shows that the accuracy of the
diagnosis is improved, the more miRNAs are measured.
[0054] In a particularly preferred embodiment of the method of the
invention, the predetermined set of miRNAs includes the miRNAs
hsa-miR-126, hsa-miR-423-5p, hsa-let-7i, hsa-let-7d, hsa-miR-22,
hsa-miR-15a, hsa-miR-98, hsa-miR-19a, hsa-miR-574-5p,
hsa-miR-324-3p, hsa-miR-20b, hsa-miR-25, hsa-miR-195, hsa-let-7e,
hsa-let-7c, hsa-let-7f, hsa-let-7a, hsa-let-7g, hsa-miR-140-3p,
hsa-miR-339-5p, hsa-miR-361-5p, hsa-miR-1283, hsa-miR-18a* and
hsa-miR-26b.
[0055] In a further particularly preferred embodiment of the method
of the invention, the miRNAs are selected from the miRNAs shown in
FIG. 11A. The predetermined set of miRNAs should preferably
comprise at least 7, preferably at least 10, 15, 20 or 24 of the
indicated nucleic acids. It is particularly preferred to include
the 24, 20, 15, 10 or at least 7 of the first mentioned miRNAs
according to their order in the table in FIG. 11A.
[0056] In another embodiment, the predetermined set of miRNAs for
the diagnosis of lung cancer comprises at least one preferred
signature L1-251 as shown in FIG. 11B. It should be noted that
preferred diagnostic sets may also comprise one or more miRNAs of
the miRNAs disclosed in FIG. 11B and any combination of the miRNAs
together with one or more further diagnostically relevant miRNA
from FIG. 10A, 10B or 11A. Preferred predetermined sets of miRNA
molecules based on FIG. 11B comprise at least 3, 4, 5, 6, 7, 8, 9
or 10 miRNAs and up to 10, 15, or 20 or more miRNAs.
[0057] For the diagnosis of different types of diseases, such as
for a different type of cancer, a different predetermined set of
miRNAs should be determined in step (a) of the method of the
invention. The relevant miRNA signatures can be obtained according
to the workflow depicted in FIG. 9 and as explained above.
[0058] Another embodiment of the present invention is a kit for
diagnosing a disease, comprising means for determining an
expression profile of a predetermined set of miRNAs in a biological
sample, in particular in a blood, plasma, and/or serum sample
including whole blood, plasma, serum or fractions thereof, or in a
sample comprising peripheral blood mononuclear cells, erythrocytes,
leukocytes and/or thrombocytes. Preferably, one or more reference
expression profiles are also provided which show the expression
profile of the same set of miRNAs in the same type of biological
sample, in particular in a blood and/or serum sample, obtained from
one or more healthy subjects. A comparison to said reference
expression profile(s) allows for the diagnosis of the disease.
[0059] The kit is preferably a test kit for detecting a
predetermined set of miRNAs in sample by nucleic acid hybridisation
and optionally amplification such as PCR or RT-PCR. The kit
preferably comprises probes and/or primers for detecting a
predetermined set of miRNAs. Further, the kit may comprise enzymes
and reagents including reagents for cDNA synthesis from miRNAs
prior to realtime PCR.
[0060] A kit for diagnosing lung cancer preferably comprises means
for determining the expression profile of one or more miRNAs
selected from the group (a) consisting of hsa-miR-361-5p,
hsa-miR-23b, hsa-miR-126, hsa-miR-527, hsa-miR-29a, hsa-let-7i,
hsa-miR-19a, hsa-miR-28-5p, hsa-miR-185*, hsa-miR-23a,
hsa-miR-1914*, hsa-miR-29c, hsa-miR-505*, hsa-let-7d, hsa-miR-378,
hsa-miR-29b, hsa-miR-604, hsa-miR-29b, hsa-let-7b, hsa-miR-299-3p,
hsa-miR-423-3p, hsa-miR-18a*, hsa-miR-1909, hsa-let-7c,
hsa-miR-15a, hsa-miR-425, hsa-miR-93*, hsa-miR-665, hsa-miR-30e,
hsa-miR-339-3p, hsa-miR-1307, hsa-miR-625*, hsa-miR-193a-5p,
hsa-miR-130b, hsa-miR-17*, hsa-miR-574-5p and hsa-miR-324-3p.
[0061] According to another embodiment of the invention, the kit
for diagnosing lung cancer preferably comprises means for
determining the expression profile of one or more miRNAs selected
from the group (b) consisting of hsa-miR-126, hsa-miR-423-5p,
hsa-let-7i, hsa-let-7d, hsa-miR-22, hsa-miR-15a, hsa-miR-98,
hsa-miR-19a, hsa-miR-574-5p, hsa-miR-324-3p, hsa-miR-20b,
hsa-miR-25, hsa-miR-195, hsa-let-7e, hsa-let-7c, hsa-let-7f,
hsa-let-7a, hsa-let-7g, hsa-miR-140-3p, hsa-miR-339-5p,
hsa-miR-361-5p, hsa-miR-1283, hsa-miR-18a*, hsa-miR-26b,
hsa-miR-604, hsa-miR-423-3p and hsa-miR-93*.
[0062] In a preferred embodiment, the kit comprises means for
determining at least 7, preferably at least 10, 15, 20 or 24 of the
indicated groups of miRNAs. It is particularly preferred to include
means for determining the 24, 20, 15, 10 or at least 7 of the first
mentioned miRNAs in the order of their MI-values or their
performance in the t-tests as shown in the tables in FIGS. 10 and
11. Most preferably, means for determining all of the above
indicated miRNAs are included in the kit for diagnosing lung
cancer. The kit is particularly suitable for diagnosing lung cancer
in a blood, plasma and/or serum sample or in a sample comprising
peripheral erythrocytes, leukocytes and/or thrombocytes.
[0063] In a particularly preferred embodiment, the kit comprises
means for determining the miRNAs hsa-miR-126, hsa-miR-423-5p,
hsa-let-7i, hsa-let-7d, hsa-miR-22, hsa-miR-15a, hsa-miR-98,
hsa-miR-19a, hsa-miR-574-5p, hsa-miR-324-3p, hsa-miR-20b,
hsa-miR-25, hsa-miR-195, hsa-let-7e, hsa-let-7c, hsa-let-7f,
hsa-let-7a, hsa-let-7g, hsa-miR-140-3p, hsa-miR-339-5p,
hsa-miR-361-5p, hsa-miR-1283, hsa-miR-18a* and hsa-miR-26b.
[0064] The means for determining a predetermined set of miRNAs may
for example comprise a microarray comprising miRNA-specific
oligonucleotide probes. In a preferred embodiment, the microarray
comprises miRNA-specific oligonucleotide probes for one or more
miRNAs selected from the group consisting of (a) hsa-miR-361-5p,
hsa-miR-23b, hsa-miR-126, hsa-miR-527, hsa-miR-29a, hsa-let-7i,
hsa-miR-19a, hsa-miR-28-5p, hsa-miR-185*, hsa-miR-23a,
hsa-miR-1914*, hsa-miR-29c, hsa-miR-505*, hsa-let-7d, hsa-miR-378,
hsa-miR-29b, hsa-miR-604, hsa-miR-29b, hsa-let-7b, hsa-miR-299-3p,
hsa-miR-423-3p, hsa-miR-18a*, hsa-miR-1909, hsa-let-7c,
hsa-miR-15a, hsa-miR-425, hsa-miR-93*, hsa-miR-665, hsa-miR-30e,
hsa-miR-339-3p, hsa-miR-1307, hsa-miR-625*, hsa-miR-193a-5p,
hsa-miR-130b, hsa-miR-17*, hsa-miR-574-5p and hsa-miR-324-3p or (b)
hsa-miR-126, hsa-miR-423-5p, hsa-let-7i, hsa-let-7d, hsa-miR-22,
hsa-miR-15a, hsa-miR-98, hsa-miR-19a, hsa-miR-574-5p,
hsa-miR-324-3p, hsa-miR-20b, hsa-miR-25, hsa-miR-195, hsa-let-7e,
hsa-let-7c, hsa-let-7f, hsa-let-7a, hsa-let-7g, hsa-miR-140-3p,
hsa-miR-339-5p, hsa-miR-361-5p, hsa-miR-1283, hsa-miR-18a*,
hsa-miR-26b, hsa-miR-604, hsa-miR-423-3p and hsa-miR-93*. In a
preferred embodiment, the microarray comprises oligonucleotide
probes for determining at least 7, preferably at least 10, 15, 20
or 24 of the indicated groups (a) and (b) of miRNAs. It is
particularly preferred to include oligonucleotide probes for
determining the 24, 20, 15, 10 or at least 7 of the first mentioned
miRNAs in the order of their MI-values or their performance in the
t-tests as shown in the tables in FIGS. 10 and 11. Most preferably,
oligonucleotide probes for determining all of the above indicated
miRNAs of groups (a) or (b) are included in the microarray for
diagnosing lung cancer.
[0065] In a particularly preferred embodiment, the microarray
comprises oligonucleotide probes for determining the miRNAs
hsa-miR-126, hsa-miR-423-5p, hsa-let-7i, hsa-let-7d, hsa-miR-22,
hsa-miR-15a, hsa-miR-98, hsa-miR-19a, hsa-miR-574-5p,
hsa-miR-324-3p, hsa-miR-20b, hsa-miR-25, hsa-miR-195, hsa-let-7e,
hsa-let-7c, hsa-let-7f, hsa-let-7a, hsa-let-7g, hsa-miR-140-3p,
hsa-miR-339-5p, hsa-miR-361-5p, hsa-miR-1283, hsa-miR-18a* and
hsa-miR-26b.
[0066] The microarray can comprise oligonucleotide probes obtained
from known or predicted miRNA sequences. The array may contain
different oligonucleotide probes for each miRNA, for example one
containing the active mature sequence and another being specific
for the precursor of the miRNA. The array may also contain controls
such as one or more sequences differing from the human orthologs by
only a few bases, which can serve as controls for hybridization
stringency conditions. It is also possible to include viral miRNAs
or putative miRNAs as predicted from bioinformatic tools. Further,
it is possible to include appropriate controls for non-specific
hybridization on the microarray.
[0067] The invention also relates to sets of oligo- or
polynucleotides for diagnosing lung cancer comprising the sequences
of at least 5, preferably at least 7, 10, 15, 20 or all of the
indicated miRNAs, and/or the complement of such sequences. It is
particularly preferred to include oligo- or polynucleotides for
detecting of the most significant miRNAs, which are represented by
their order in the table depicted in FIG. 10A, 10B or 11A. In a
further embodiment, the set includes oligo- or polynucleotides for
detecting the miRNA sets based on FIG. 11B as described above. The
oligo- or polynucleotides preferably have a length of 10, 15 or 20
and up to 30, 40, 50, 100 or more nucleotides. The term "oligo- or
polynucleotides" includes single- or double-stranded molecules, RNA
molecules, DNA molecules or nucleic acid analogs such as PNA or
LNA.
[0068] Another embodiment of the present invention relates to a
method for the assessment of a clinical condition related to lung
cancer of a patient.
[0069] Recent developments have shown that there is a tendency
towards smaller sets of biomarkers for the detection of diseases.
However, for single biomarkers and small biomarker sets, there is
only a basic understanding whether these biomarkers are specific
for only the single diseases or whether they occur in any other
disease.
[0070] Therefore, the present inventors developed a novel class of
diagnostic tests improving the current test scenarios. The
inventors found out that a variety of diseases are correlated with
a specific expression profile of miRNAs. In case a patient is
affected by a particular disease, several miRNAs are present in
larger amounts compared to a healthy normal control, whereas the
amount of other miRNAs is decreased. Interestingly, the amount of
some miRNAs is deregulated, i.e. increased or decreased, in more
than one disease. The miRNA profile for a particular disease
therefore shows conformity with the miRNA profile of other diseases
in regard of individual miRNAs while other miRNAs show significant
differences. If the expression profile of a large variety of miRNAs
in a biological sample of a patient is measured, the comparison of
the expression profile with a variety of reference expression
profiles which are each characteristic for different diseases makes
it possible to obtain information about the clinical condition of a
certain patient and to determine, which disease(s) is/are present
in said patient.
[0071] A further subject matter of the invention is a method for
the assessment of a clinical condition related to lung cancer of a
patient comprising the steps [0072] (a) providing a sample from the
patient, [0073] (b) determining a predetermined set of miRNAs in
said sample to obtain a miRNA expression profile, [0074] (c)
comparing said miRNA expression profile with a plurality of miRNA
reference expression profiles characteristic for different
diseases, and [0075] (d) assessing the clinical condition of the
patient based on the comparison of step (c).
[0076] The inventors found out that the above method for the
assessment of a clinical condition makes it possible to carry out
an integrative diagnosis of a wide variety of diseases,
particularly including lung cancer. Comparing a miRNA profile
obtained from a biological sample of a patient whose clinical
condition is not known with a plurality of reference profiles
characteristic for different diseases enables the diagnosis of a
wide variety of diseases with high specificity and sensitivity.
[0077] A "biological sample" in terms of the invention means a
sample of biological tissue or fluid as described hereinabove.
Examples of biological samples are sections of tissues, blood,
blood fractions, plasma, serum, urine or samples from other
peripheral sources. Preferred biological samples are blood, plasma
and/or serum samples including blood fractions such as PBMC.
[0078] The set of miRNAs determined in step (d) preferably includes
a large number of different miRNAs. It is particularly preferred to
use at least 10, 20, 30, 50, preferably at least 100, 200, 500 or
1,000 miRNAs. Most preferably, all known miRNAs are included in the
set of miRNAs determined in step (b) Such a complex set of
miRNA-biomarkers enables a diagnosis with higher specificity and
sensitivity compared to single biomarkers or sets of only a few
dozens of such markers.
[0079] The determination of the set of miRNAs can be done as
described herein above. Preferably, the determination is done on an
experimental platform which shows a high degree of automation to
minimize experimental variations, measure results time- and
cost-efficiently, measures results highly reproducibly and be able
for measuring more than one sample at once in order to ensure a
high throughput.
[0080] Step (c) preferably includes a comparison of the miRNA
profile measured for a patient with a large number of different
reference profiles to provide information about the presence of as
many different diseases as possible. The reference expression
profiles may be laid down in a database, e.g. an internet database,
a centralized or a decentralized database. The reference profiles
do not necessarily have to include information about all miRNAs
included in step (b), which are determined in the sample of the
patient. It is, according to the invention, sufficient if the
reference profile provides information on those miRNAs which are
altered to a large extent compared to the condition of a healthy
individual in case of the presence of a disease. Alternatively, the
said relevant reference may be a mathematical function or
algorithm.
[0081] Preferably, an miRNA reference profile or the relevant
reference according to the invention provides information on miRNA
expression characteristic for a particular disease in the same type
of biological sample as used in step (b) for determining a
predetermined set of miRNAs in a sample from a patient. This means
that, if a patient with an unknown disease is to be classified with
the analysis of a blood sample, the comparison is preferably made
with miRNA reference expression profiles, which do also relate to
the miRNA expression pattern in a blood sample.
[0082] The reference profiles or the relevant reference
characteristic for particular diseases provide information on one
or more miRNAs, which are, in case of the disease, highly
deregulated, for example strongly increased or decreased, as
compared to a healthy condition. It is not necessary for the
reference profiles to provide information about all miRNAs included
in the set of biomarkers determined in step (b). However, the more
miRNAs are included in the reference profile or relevant reference,
the more precise the diagnosis will be. If, for example, a
reference profile for lung cancer is included, it is preferred to
include the characteristic miRNAs for lung cancer.
[0083] Another embodiment of this aspect of the invention is a kit
for the assessment of a clinical condition related to lung cancer
of a patient comprising
[0084] (a) means for determining a predetermined set of miRNAs in a
biological sample from a patient, and
[0085] (b) a plurality of miRNA reference expression profiles
characteristic for different diseases or a mathematical function
that allows for the diagnosis on the basis of the data derived from
the miRNA expression profiles of a patient.
[0086] The set of miRNAs to be determined in a biological sample
from a patient preferably includes a large number of different
miRNAs. It is particularly preferred to include all known miRNAs in
the set of miRNAs to be determined. In each case, said
predetermined set of miRNAs should include those miRNAs for which
information is provided in the reference profiles characteristic
for particular diseases. It is understood that only in case the set
of miRNAs determined in a biological sample from a patient
comprises those miRNAs included in the reference profile/reference
for a disease, a diagnosis regarding this particular disease can be
provided or otherwise the diagnosis may be less informative.
[0087] The assessment of a clinical condition of a patient
according to the invention is suitable for diagnosing any diseases
which are correlated with a characteristic miRNA profile.
Accordingly, the kit for the assessment of a clinical condition
preferably includes reference profiles/references for a plurality
of diseases that are correlated with a characteristic miRNA
profile. It is understood that all miRNAs that are significantly
deregulated in the disease states for which reference profiles are
provided should be included in the set of miRNAs to be determined
in a biological sample from a patient. If the kit for the
assessment of a clinical condition of a patient should provide
information regarding, e.g. lung cancer or multiple sclerosis, a
reference profile should be available providing information about
the significantly deregulated miRNAs compared to a normal or any
other relevant control individual or any other relevant control
individual(s). A kit for the assessment of a clinical condition
shall provide information on the presence of lung cancer, a
reference profile characteristic for lung cancer should be
included. Said reference profile preferably includes information on
those miRNAs that are most significantly deregulated in the case of
lung cancer. The relevant miRNAs are as disclosed hereinabove.
[0088] The invention will now be illustrated by the following
figures and the non-limiting experimental examples.
FIGURES
[0089] FIG. 1:
[0090] Scheme of a miRNA hybridization assay for use in the
invention. [0091] miRNA capture probes consist of 1 miRNA probe
sequence stretch that is linked to support via 3'-end or
alternatively by 5'-end (not depicted here) [0092] the miRNA probe
sequence stretches are complementary to miRNA target sequences
[0093] each miRNA capture probe can bind 1 miRNA target sequences
[0094] the miRNA target sequences are labeled prior to
hybridisation (e.g. by biotin labeling)
[0095] FIG. 2:
[0096] Scheme of an miRNA tandem hybridization assay for use in the
invention [0097] miRNA capture probes consist of 2 DNA-based miRNA
probe sequence stretches that are linked to each other by a spacer
element [0098] the miRNA probe sequence stretches are complementary
to miRNA target sequences [0099] each miRNA capture probe can bind
2 miRNA target sequences [0100] the spacer sequence consists of 0-8
nucleotides
[0101] the miRNA target sequences are labeled prior to
hybridisation (e.g. by biotin labeling)
[0102] FIG. 3:
[0103] miRNA RAKE-Assay for use in the invention (PT Nelson et al.,
Nature Methods, 2004, 1(2), 1) [0104] the miRNA capture probes
consist of one miRNA probe sequence stretch (green) and one
elongation element (orange) [0105] probes are oriented 5'-3',
presenting a free terminal 3'-OH [0106] the miRNA probe sequence
stretch (green) is complementary to miRNA target sequences (dark
green) [0107] the elongation sequences (orange) can be freely
chosen and is typically between 1-12 nucleotides long, preferably a
homomeric sequence [0108] each miRNA capture probe can bind 1 miRNA
target sequences [0109] the miRNA target sequences are NOT labeled
prior to hybridisation [0110] Labeling occurs after hybridisation
during elongation by polymerase extention reaction
[0111] Biochip is not reusable due to exonuclease treatment
[0112] FIG. 4: [0113] miRNA MPEA-Assay for use in the invention
(Vorwerk S. et al., Microfluidic-based enzymatic on-chip labeling
of miRNAs, N. Biotechnol. 2008; 25(2-3):142-9. Epub 2008 Aug. 20)
[0114] the miRNA capture probes consist of one miRNA probe sequence
stretch (green) and one elongation element (orange) [0115] probes
are oriented 3'.fwdarw.5', presenting a free terminal 5'-OH
[0116] the miRNA probe sequence stretch (green) is complementary to
miRNA target sequences (dark green) [0117] the elongation sequences
(orange) can be freely chosen and is typically between 1-12
nucleotides long, preferably a homomeric sequence [0118] each miRNA
capture probe can bind 1 miRNA target sequences [0119] the miRNA
target sequences are NOT labeled prior to hybridisation [0120]
Labeling occurs after hybridisation during elongation by polymerase
extention reaction [0121] Biochip is reusable after removal of
target/elongated target
[0122] FIG. 5:
[0123] miRNA capture probe design
[0124] Depicted is the design of a capture probe for the exemplary
miRNA human mature miRNA let-7a for use in the various types of
hybridization assays shown in FIGS. 1-4. SP=spacer element;
EL=elongation element
[0125] FIG. 6:
[0126] Spacer Element.
[0127] Capture probes for use in e.g. a tandem hybridization assay
as shown in FIG. 2 may comprise a spacer element SP. The spacer
element represents a nucleotide sequence with n=0-12 nucleotides
chosen on the basis of showing low complementarity to potential
target sequences, therefore resulting in no to low degree of
crosshybridization to target mixture. Preferably, n=0, i.e. there
is no spacer between the 2 miRNA probe sequence stretches.
[0128] FIG. 7:
[0129] Elongation element
[0130] A capture probe, e.g. for use in a RAKE or MPEA assay as
shown in FIGS. 3 and 4 may include an elongation element. The
elongation element comprises a nucleotide sequence with N=0-30
nucleotides chosen on the basis of showing low complementarity to
potential target sequences, therefore resulting in no to low degree
of crosshybridization to target mixture. Preferred is a homomeric
sequence stretch -N.sub.n- with n=1-30, N=A or C, or T, or G.
Especially preferred is a homomeric sequence stretch -Nn- with
n=1-12, N=A or C, or T, or G.
[0131] FIG. 8:
[0132] Pearson Correlation Coefficient depending on the number of
elongated nucleotides in capture probes in an MPEA assay.
[0133] FIG. 9:
[0134] Diagram describing the general approach for determining
miRNA signatures for use as biomarkers in disease diagnosis.
[0135] FIG. 10A:
[0136] Overview of all miRNAs that are found to be differentially
regulated in blood samples of lung cancer patients, grouped
according to their mutual information (MI).
[0137] FIG. 10B:
[0138] Overview of all miRNAs that are found to be differentially
regulated in blood samples of lung cancer patients, grouped
according to their results in t-tests.
[0139] FIG. 11A:
[0140] Overview of preferred miRNAs that are found to be
significantly (p<0.1) differentially regulated in blood samples
of lung cancer patients.
[0141] FIG. 11B:
[0142] Overview of preferred signatures of miRNAs for the diagnosis
of lung cancer.
[0143] FIG. 12:
[0144] Expression of some relevant miRNAs. The bar-chart shows for
15 deregulated miRNAs the median value of cancer samples and normal
samples. Here, blue bars correspond to cancer samples while red
bars to controls.
[0145] FIGS. 13A-13G:
[0146] Bar diagrams showing a classification of the accuracy,
specificity and sensitivity of the diagnosis of lung cancer based
on blood samples using different sizes of subsets of miRNAs. Blue
bars represent accuracy, specificity and sensitivity of the
diagnosis using the indicated biomarkers and red bars represent the
results of the same experiments of random classifications. The
relevant value is the population median (horizontal black lines
inside the bars).
[0147] FIG. 13A: 4 biomarkers: [0148] hsa-miR-126, hsa-miR-423-5p,
hsa-let-7i and hsa-let-7d;
[0149] FIG. 13B: 8 biomarkers: [0150] hsa-miR-126, hsa-miR-423-5p,
hsa-let-7i; hsa-let-7d, hsa-miR-22, hsa-miR-15a, hsa-miR-98, and
hsa-miR-19a;
[0151] FIG. 13C: 10 biomarkers: [0152] hsa-miR-126, hsa-miR-423-5p,
hsa-let-7i; hsa-let-7d, hsa-miR-22, hsa-miR-15a, hsa-miR-98,
hsa-miR-19a, hsa-miR-574-5p, and hsa-miR-324-3p;
[0153] FIG. 13D: 16 biomarkers: [0154] hsa-miR-126, hsa-miR-423-5p,
hsa-let-7i; hsa-let-7d, hsa-miR-22, hsa-miR-15a, hsa-miR-98,
hsa-miR-19a; hsa-miR-574-5p; hsa-miR-324-3p, hsa-miR-20b,
hsa-miR-25, hsa-miR-195, hsa-let-7e, hsa-let-7c, and
has-let-7f;
[0155] FIG. 13E: 20 biomarkers: [0156] hsa-miR-126, hsa-miR-423-5p,
hsa-let-7i; hsa-let-7d, hsa-miR-22, hsa-miR-15a, hsa-miR-98,
hsa-miR-19a; hsa-miR-574-5p; hsa-miR-324-3p, hsa-miR-20b,
hsa-miR-25, hsa-miR-195, hsa-let-7e, hsa-let-7c, hsa-let-7f;
hsa-let-7a, hsa-let-7g, hsa-miR-140-3p and hsa-miR-339-5p;
[0157] FIG. 13F: 28 biomarkers: [0158] hsa-miR-126, hsa-miR-423-5p,
hsa-let-7i; hsa-let-7d, hsa-miR-22, hsa-miR-15a, hsa-miR-98,
hsa-miR-19a; hsa-miR-574-5p; hsa-miR-324-3p, hsa-miR-20b,
hsa-miR-25, hsa-miR-195, hsa-let-7e, hsa-let-7c, hsa-let-7f;
hsa-let-7a, hsa-let-7g, hsa-miR-140-3p, hsa-miR-339-5p,
hsa-miR-361-5p, hsa-miR-1283, hsa-miR-18a*, hsa-miR-26b,
hsa-miR-604, hsa-miR-423-3p, hsa-miR-93*, and hsa-miR-29a;
[0159] FIG. 13G: 40 biomarkers: [0160] hsa-miR-126, hsa-miR-423-5p,
hsa-let-7i; hsa-let-7d, hsa-miR-22, hsa-miR-15a, hsa-miR-98,
hsa-miR-19a; hsa-miR-574-5p; hsa-miR-324-3p, hsa-miR-20b,
hsa-miR-25, hsa-miR-195, hsa-let-7e, hsa-let-7c, hsa-let-7f;
hsa-let-7a, hsa-let-7g, hsa-miR-140-3p, hsa-miR-339-5p,
hsa-miR-361-5p, hsa-miR-1283, hsa-miR-8a*, hsa-miR-26b,
hsa-miR-604, hsa-miR-423-3p, hsa-miR-93*, hsa-miR-29a,
hsa-miR-1248, hsa-miR-210, hsa-miR-19b, hsa-miR-453, hsa-miR-126*,
hsa-miR-188-3p, hsa-miR-624*, hsa-miR-505*, hsa-miR-425,
hsa-miR-339-3p, hsa-miR-668, and hsa-miR-363*.
[0161] FIG. 14:
[0162] Classification of cancer samples versus controls for two
individual miRNAs (miR-126 and miR-196). Blue bars correspond to
cancer samples, while red bars correspond to controls.
[0163] FIG. 15:
[0164] Scatterplot of fold quotients of rt-qPCR (x-axis) and
microarray experiments (y-axis).
[0165] FIG. 16:
[0166] The mutual information of all miRNAs that have higher
information content than the best permutation test (upper red
line). The middle red line denotes the 95% quantile of the 1000
permutation tests and the bottom red line the mean of the
permutation experiments, corresponding to the background MI.
[0167] FIG. 17:
[0168] Box plots of the classification accuracy, specificity and
sensitivity of the set of 24 best miRNAs (obtained with radial
basis function support vector machine). These miRNAs allow for the
discrimination between blood cells of lung cancer patients and
blood cells of controls with an accuracy of 95.4% [94.9%-95.9%], a
specificity of 98.1%[97.3%-98.8%], and a sensitivity of
92.5%[91.8%-92.5%]. The permutation tests showed significantly
decreased accuracy, specificity and sensitivity with 94.2%
[47.2%-51.3%], 56.9%[54.5%-59.3%] and 40.6%[37.9%-43.4%],
respectively, providing evidence that the obtained results are not
due to an overfit of the statistical model on the miRNA
fingerprints.
EXAMPLE 1
[0169] Lung Cancer
[0170] 1. Material and Methods
[0171] 1.1 Samples
[0172] Blood samples were obtained with patients' informed consent.
The patient samples stem from 17 patients with non-small cell lung
carcinoma and normal controls. Normal samples were obtained from 19
different volunteers. More detailed information of patients and
controls is given in Table 1.
TABLE-US-00001 TABLE 1 Detailed information on lung cancer patients
and healthy control subjects blood donors male female lung cancer
patients number 9 8 average age 67.4 60.6 squamous cell lung cancer
3 4 adenocarcinoma 6 1 adenosquamous carcinoma 0 1 broncholaveolar
carcinoma 0 1 typical carcinoid 0 1 healthy subjects number 7 12
average age 43.3 36.7 lung cancer patients number 9 8 average age
67.4 60.6 squamous cell lung cancer 3 4 adenocarcinoma 6 1
adenosquamous carcinoma 0 1 broncholaveolar carcinoma 0 1 typical
carcinoid 0 1 healthy subjects number 7 12 average age 43.3 36.7
lung cancer patients number 9 8 average age 67.4 60.6 squamous cell
lung cancer 3 4 adenocarcinoma 6 1 adenosquamous carcinoma 0 1
broncholaveolar carcinoma 0 1 typical carcinoid 0 1 healthy
subjects number 7 12 average age 43.3 36.7
[0173] 1.2 miRNA Microarray Screening
[0174] Blood of lung cancer patients and volunteers without known
disease was extracted in PAXgene Blood RNA tubes (BD, Franklin
Lakes, N.J. USA). For each blood donor, 5 ml of peripheral blood
were obtained. Total RNA was extracted from blood cells using the
miRNeasy Mini Kit (Qiagen GmbH, Hilden, Germany) and the RNA has
been stored at -70.degree. C. Samples were analyzed with the Geniom
Realtime Analyzer (GRTA, febit gmbh, Heidelberg, Germany) using the
Geniom Biochip miRNA homo sapiens. Each array contains 7 replicates
of 866 miRNAs and miRNA star sequences as annotated in the Sanger
mirBase 12.0 (Griffiths-Jones, Moxon et al. 2005; Griffiths-Jones,
Saini et al. 2008). Sample labelling with Biotin has been carried
out either by using the miRVANA.TM. miRNA Labelling Kit (Applied
Biosystems Inc, Foster City, Calif. USA) or by multifluidic-based
enzymatic on-chip labelling of miRNAs (MPEA (Vorwerk, Ganter et al.
2008), incorporated herein by reference).
[0175] Following hybridization for 16 hours at 42.degree. C. the
biochip was washed automatically and a program for signal
enhancement was processed with the GRTA. The resulting detection
pictures were evaluated using the Geniom Wizard Software. For each
array, the median signal intensity was extracted from the raw data
file such that for each miRNA seven intensity values have been
calculated corresponding to each replicate copy of mirBase on the
array. Following background correction, the seven replicate
intensity values of each miRNA were summarized by their median
value. To normalize the data across different arrays, quantile
normalization (Bolstad, Irizarry et al. 2003) was applied and all
further analyses were carried out using the normalized and
background subtracted intensity values.
[0176] 1.3 Statistical Analysis
[0177] After having verified the normal distribution of the
measured data, parametric t-tests (unpaired, two-tailed) were
carried out for each miRNA separately, to detect miRNAs that show a
different behavior in different groups of blood donors. The
resulting p-values were adjusted for multiple testing by
Benjamini-Hochberg (Hochberg 1988; Benjamini and Hochberg 1995)
adjustment. Moreover, the Mutual Information (MI) (Shannon 1984)
was computed as a measure to access the diagnostic value of single
miRNA biomarkers. To this end, all biomarkers were transformed to
z-scores and binned in three bins before the MI values of each
biomarker, and the information whether the marker has been measured
from a normal or lung cancer sample, was computed. In addition to
the single biomarker analysis classification of samples using miRNA
patterns was carried out using Support Vector Machines (SVM,
(Vapnik 2000)) as implemented in the R (Team 2008) e1071 package.
In detail, different kernel (linear, polynomial, sigmoid, radial
basis function) Support Vector Machines were evaluated, where the
cost parameter was sampled from 0.01 to 10 in decimal powers. The
measured miRNA profiles were classified using 100 repetitions of
standard 10-fold cross-validation. As a subset selection technique
a filter approach based on t-test was applied. In detail, the s
miRNAs with lowest p-values were computed on the training set in
each fold of the cross validation, where s was sampled from 1 to
866. The respective subset was used to train the SVM and to carry
out the prediction of the test samples. As result, the mean
accuracy, specificity, and sensitivity were calculated together
with the 95% Confidence Intervals (95% CI) for each subset size. To
check for overtraining permutation tests were applied. Here the
class labels were sampled randomly and classifications were carried
out using the permuted class labels. All statistical analyzes were
performed using R (Team 2008).
[0178] 2. Results
[0179] 2.1 miRNA Experiments
[0180] The expression of 866 miRNAs and miRNA star sequences was
analyzed in blood cells of 17 patients with NSCLC. As a control
blood cells of 19 volunteers without known disease were used (see
also Materials and Methods).
[0181] Following RNA isolation and labeling by miRVANA.TM. miRNA
Labeling Kit, the miRNA expression profiles were measured by the
Geniom Bioship miRNA homo sapiens in the GRTA (febit gmbh,
Heidelberg). Following intensity value computation and quantile
normalization of the miRNA profiles (Bolstad, Irizarry et al.
2003), a mean correlation value of 0.97 for technical replicates
was determined by using purchased total RNA from Ambion (four heart
and four liver replicates). For the biological replicates the
different tumor samples were compared between each other and the
different normal samples between each other. The biological
replicates showed a mean correlation of 0.87 and a variance of
0.009.
[0182] 2.2 Ruling Out the Influence of Age and Gender
[0183] To cross-check that age and gender do not have an influence
on our analysis, t-tests were computed for the normal samples. In
the case of males versus females there was no statistically
significant deregulated miRNA. The most significant miRNA,
hsa-miR-423, showed an adjusted significance level of 0.78.
[0184] To test for the influence of donor age the profiles obtained
from samples obtained from the oldest versus youngest patients were
compared by splitting the group in half based on age. Here, the
most significant miRNA, miR-890, obtained an adjusted p-value of
0.87. As for gender, there were no deregulated miRNAs, thus
providing evidence that age and gender do not have a substantial
influence on the miRNA profiles.
[0185] 2.3 Single Deregulated miRNAs
[0186] Hypothesis testing was applied to identify miRNAs
deregulated in the blood cells of lung cancer patients as compared
to the blood cells of the controls. Following verification of an
approximately normal distribution, two-tailed unpaired t-tests were
performed for each miRNA. The respective p-values were adjusted for
multiple testing by the Benjamini-Hochberg approach (Hochberg 1988;
Benjamini and Hochberg 1995). In total 27 miRNAs significantly
deregulated in blood cells of lung cancer patients as compared to
the controls were detected. A complete list of deregulated miRNAs
is given in the tables in FIGS. 10 and 11. The miRNAs that were
most significantly deregulated included hsa-miR-126 with a p-value
of 0.00003, hsa-let-7d with a p-value of 0.003, hsa-let-7i with a
p-value of 0.003, and hsa-miR-423 with a p-value of 0.001 (FIG. 1
and FIG. 2). Other members of the let-7 family that were also found
to be deregulated included hsa-let-7c, hsa-let-7e, hsa-let-7f,
hsa-let-7g and hsa-let-7a. Besides miR-423, all above mentioned
miRNAs were down-regulated in blood cells of lung cancer patients
compared to blood cells of healthy subjects indicating an overall
decreased miRNA repertoire.
[0187] To validate the findings, the miRNA profiling was repeated
using an enzymatic on-chip labeling technique termed MPEA
(Microfluidic-based enzymatic on-chip labeling of miRNAs). For this
control experiment, 4 out of the 17 lung cancer patients and 10 of
the controls were used. Hereby, 100 differentially regulated miRNAs
were detected. The miRNAs that were most significantly deregulated
include hsa-miR-1253 with a p-value of 0.001, hsa-miR-126 with a
p-value of 0.006, hsa-let-7d with a p-value of 0.006, and
hsa-let-7f with a p-value of 0.006. Of the previously identified 27
miRNAs 12 were detected to be significant in the second experiment,
while the remaining miRNAs showed increased p-values. The
correlation of fold changes was 0.62. Also other members of the
let-7 family were confirmed as deregulated in blood cells of lung
cancer patients. Furthermore, it was confirmed that the majority of
the deregulated miRNAs were down-regulated in patients' blood
samples. Here, 62% of the deregulated miRNAs showed decreased
intensity values in lung cancer samples.
[0188] As a further control experiment an expression analysis by
qRT-PCR was performed. As a test sample the fold changes of
has-miR-106b, miR-98, miR-140-3p, let-7d, mir-126, and miR-22 were
analyzed in blood cells of eight tumor patients and five controls.
The fold quotients detected by the Geniom Biochip experiments
agreed very well with the qRT-PCR experiments, as demonstrated by
an excellent R.sup.2 value of 0.994. The fold quotients are
presented as a scatterplot together with the R.sup.2 value and the
regression line in FIG. 16.
[0189] 2.4 Diagnostic Value of miRNA Biomarkers
[0190] Mutual Information (MI) (Shannon 1984) is an adequate
measure to estimate the overall diagnostic information content of
single biomarkers (Keller, Ludwig et al. 2006). In the present
study, Mutual Information is considered as the reduction in
uncertainty about the class labels `0` for controls and `1` for
tumor samples due to the knowledge of the miRNA expression. The
higher the value of the MI of a miRNA, the higher is the diagnostic
content of the respective miRNA.
[0191] The MI of each miRNA with the class labels was computed.
First, a permutation test was carried out to determine the
background noise of the miRNAs, e.g. the random information content
of each miRNA. 1000 miRNAs (with replacements) were randomly
selected and the class labels were sampled for each miRNA. These
permutation tests yielded a mean MI value of 0.029, a 95% quantile
of 0.096 and a value of 0.217 for the highest random MI. Second,
the MI values were calculated for the comparison between the miRNAs
in blood cells of tumor patients and controls. The overall
comparison of the 866 miRNAs yielded significantly increased MI
values with a two-tailed p-value of .ltoreq.10.sup.-10 as shown by
an unpaired Wilcoxon Mann-Whitney test (Wilcoxon 1945; Mann and
Wilcoxon 1947). The miRNA hsa-miR-361-5p showed the highest MI with
a value of 0.446. The miRNAs with the best significance values as
computed by the t-test, namely hsa-miR-126 and hsa-miR-98, were
also among the miRNAs showing the highest MI values. In total 37
miRNAs with MI values higher than the highest of 1000 permuted
miRNAs and 200 miRNAs with MI values higher than the 95% quantile
were detected (FIG. 16). A complete list of miRNAs, the respective
MI and the enrichment compared to the background MI is provided in
the table in FIG. 10.
[0192] 2.5 Evaluating Complex Fingerprints
[0193] Even single miRNAs with highest MI values are not sufficient
to differentiate between blood cells of tumor patients as compared
to controls with high specificity. For example, the has-miR-126
separates blood cells of tumor patients from blood cells of healthy
individuals with a specificity of 68%, only. In order to improve
the classification accuracy the predictive power of multiple miRNAs
was combined by using statistical learning techniques. In detail,
Support Vector Machines with different kernels (linear, polynomial,
sigmoid, radial basis function) were applied to the data and a
hypothesis test was carried out based subset selection as described
in Material and Methods. To gain statistical significance 100
repetitions of 10-fold cross validation were carried out. Likewise,
100 repetitions for the permutation tests were computed.
[0194] The best results were obtained with radial basis function
Support Vector Machines and a subset of 24 miRNAs. These miRNAs
allowed for the discrimination between blood cells of lung tumor
patients and blood cells of controls with an accuracy of 95.4%
[94.9%-95.9%], a specificity of 98.1% [97.3%-98.8%], and a
sensitivity of 92.5% [91.8%-92.5%]. The permutation tests showed
significantly decreased accuracy, specificity, and sensitivity with
49.2% [47.2%-51.3%], 56.9% [54.5%-59.3%] and 40.6% [37.9%-43.4%],
respectively (FIG. 5), providing evidence that the obtained results
are not due to an overfit of the statistical model on the miRNA
fingerprints.
[0195] 3. Discussion
[0196] While complex miRNA expression patterns have been reported
for a huge variety of human tumors, information there was only one
study analyzing miRNA expression in blood cells derived from tumor
patients. In the following the present miRNA expression profiling
is related to both the miRNA expression in blood cells and in
cancer cells of non-small cell lung cancer patients. A significant
down-regulation of has-miR-126 was found that was recently detected
in blood cells of healthy individuals, but not in blood cells of
lung cancer patients (Chen, Ba et al. 2008). Down-regulation of
has-miR-126 was also found in lung cancer tissue in this study.
Functional studies on has-miR-126 revealed this miRNA as a
regulator of the endothelial expression of vascular cell adhesion
molecule 1 (VCAM-1), which is an intercellular adhesion molecule
expressed by endothelial cells focuses on the identification of
miRNAs in serum of patients with cancer and other diseases or
healthy controls. Since most miRNAs are expressed in both, serum
and blood cells of healthy controls, most serum miRNAs are likely
derived from circulating blood cells. Since there was only a weak
correlation between the miRNA expression in serum and blood cell,
miRNA expression appears to be deregulated in either serum or blood
cells of cancer patients. The present experimental example focused
on the analysis of miRNA expression in blood cells of non-small
cell lung cancer patients and healthy controls. Significant
downregulation of has-miR-126 was found that was recently detected
in blood cells of healthy individuals, but not in blood cells of
lung cancer patients (Harris, YamakuchiChen, Ba et al. 2008).
Downregulation of has-miR-126 was also found in lung cancer tissue
(Yanaihara, Caplen et al. 2006). Functional studies on has-miR-126
revealed this miRNA as regulator of the endothelial expression of
vascular cell adhesion molecule 1 (VCAM-1), which is an
intercellular adhesion molecule expressed by endothelial cells
(Harris, Yamakuchi et al. 2008). hsa-miR-126 is also reported to be
an inhibitor of cell invasion in non-small cell lung cancer cell
lines, and down-regulation of this miRNA 126 might be a mechanism
of lung cancer cells to evade these inhibitory effects (Crawford,
Brawner et al. 2008). Members of the has-let-7 family that were
found down-regulated in the present invention were the first miRNAs
reported as de-regulated in lung cancer (Johnson, Grosshans et al.
2005). This down-regulation of the let-7 family in lung cancer was
confirmed by several independent studies (Takamizawa, Konishi et
al. 2004; Stahlhut Espinosa and Slack 2006; Tong 2006; Zhang, Wang
et al. 2007; Williams 2008). The present data are also in agreement
with a recent study showing the down-regulation of has-let-7a,
has-let-7d, has-let-7f, has-let-7g, and has-let-7i in blood cells
of lung cancer patients (Chen, Ba et al. 2008). Notably,
down-regulation of let-7 in lung cancer was strongly associated
with poor clinical outcome (Takamizawa, Konishi et al. 2004). The
let-7 family members negatively regulate oncogene RAS (Johnson,
Grosshans et al. 2005). The miRNA has-miR-22 that showed a high MI
value and up-regulation in the present study, was recently also
reported to be up-regulated in blood cells of lung cancer patients
(Chen, Ba et al. 2008). The miRNA has-miR-19a that also showed a
high MI value and up-regulation in the present study was reported
to be up-regulated in lung cancer tissue (Hayashita, Osada et al.
2005; Calin and Croce 2006). In contrast, has-miR-20a, which is
significantly down-regulated in the present experiments, was
reported as up-regulated in lung cancer tissue (Hayashita, Osada et
al. 2005; Calin and Croce 2006). The up-regulation of has-miR-20a
was found in small-cell lung cancer cell lines, the present study
investigated only NSCLC. In summary, there is a high degree of
consistency between miRNA expression found in the peripheral blood
cells of lung cancer patients and miRNA expression in lung cancer
tissue (Takamizawa, Konishi et al. 2004; Hayashita, Osada et al.
2005; Lu, Getz et al. 2005; Calin and Croce 2006; Stahlhut Espinosa
and Slack 2006; Tong 2006; Volinia, Calin et al. 2006; Yanaihara,
Caplen et al. 2006; Zhang, Wang et al. 2007; Williams 2008).
[0197] Some of the deregulated miRNAs identified in the present
invention are also reported as de-regulated in other cancer
entities, e.g. has-miR-346 in gastritic cancer, has-miR-145 in
bladder cancer, and has-miR-19a in hepatocellular carcinoma and
B-cell leukemia (Alvarez-Garcia and Miska 2005; He, Thomson et al.
2005; Feitelson and Lee 2007; Guo, Huang et al. 2008; Ichimi,
Enokida et al. 2009). In addition, miRNAs with high diagnostic
potential e.g. high MI value, were found that were not yet related
to cancer as for example has-miR-527 or has-mir-361-5p that were
both up-regulated in blood cells of lung cancer patients.
[0198] Besides the deregulation of single miRNAs, the overall
expression pattern of miRNAs in peripheral blood cells of lung
cancer patients were analyzed in comparison to the pattern in blood
cells of healthy controls. Recently, Chen et al. (Chen, Ba et al.
2008) reported a high correlation of 0.9205 between miRNA profiles
in serum and miRNA profiles in blood cells, both in healthy
individuals. The correlation of the miRNA profiles between serum
and blood cells in lung cancer patients were significantly lower
(0.4492). These results are indicative of deregulated miRNAs in
blood and/or serum of patients and are in agreement with the
present data that show the deregulation of miRNAs in the blood
cells of lung carcinoma patients. These deregulated miRNAs can be
used to differentiate patients with lung cancer from normal
controls with high specificity and sensitivity. This is the first
evidence for the diagnostic potential of miRNA expression profiles
in peripheral blood cells of cancer patients and healthy
individuals.
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Sequence CWU 1
1
866122RNAHomo sapiens 1ucguaccgugaguaauaaugcg 22223RNAHomo sapiens
2ugaggggcagagagcgagacuuu 23322RNAHomo sapiens
3ugagguaguaguuugugcuguu 22422RNAHomo sapiens
4agagguaguagguugcauaguu 22522RNAHomo sapiens
5aagcugccaguugaagaacugu 22622RNAHomo sapiens
6uagcagcacauaaugguuugug 22722RNAHomo sapiens
7ugagguaguaaguuguauuguu 22823RNAHomo sapiens
8ugugcaaaucuaugcaaaacuga 23923RNAHomo sapiens
9ugagugugugugugugagugugu 231020RNAHomo sapiens
10acugccccaggugcugcugg 201123RNAHomo sapiens
11caaagugcucauagugcagguag 231222RNAHomo sapiens
12cauugcacuugucucggucuga 221321RNAHomo sapiens
13uagcagcacagaaauauuggc 211422RNAHomo sapiens
14ugagguaggagguuguauaguu 221522RNAHomo sapiens
15ugagguaguagguuguaugguu 221622RNAHomo sapiens
16ugagguaguagauuguauaguu 221722RNAHomo sapiens
17ugagguaguagguuguauaguu 221822RNAHomo sapiens
18ugagguaguaguuuguacaguu 221921RNAHomo sapiens
19uaccacaggguagaaccacgg 212023RNAHomo sapiens
20ucccuguccuccaggagcucacg 232122RNAHomo sapiens
21uuaucagaaucuccagggguac 222222RNAHomo sapiens
22ucuacaaaggaaagcgcuuucu 222323RNAHomo sapiens
23acugcccuaagugcuccuucugg 232421RNAHomo sapiens
24uucaaguaauucaggauaggu 212519RNAHomo sapiens 25aggcugcggaauucaggac
192623RNAHomo sapiens 26agcucggucugaggccccucagu 232722RNAHomo
sapiens 27acugcugagcuagcacuucccg 222822RNAHomo sapiens
28uagcaccaucugaaaucgguua 222927RNAHomo sapiens
29accuucuuguauaagcacugugcuaaa 273022RNAHomo sapiens
30cugugcgugugacagcggcuga 223123RNAHomo sapiens
31ugugcaaauccaugcaaaacuga 233223RNAHomo sapiens
32agguuguccguggugaguucgca 233321RNAHomo sapiens
33cauuauuacuuuugguacgcg 213421RNAHomo sapiens
34cucccacaugcaggguuugca 213522RNAHomo sapiens
35uaguaccaguaccuuguguuca 223622RNAHomo sapiens
36gggagccaggaaguauugaugu 223723RNAHomo sapiens
37aaugacacgaucacucccguuga 233823RNAHomo sapiens
38ugagcgccucgacgacagagccg 233923RNAHomo sapiens
39ugucacucggcucggcccacuac 234022RNAHomo sapiens
40cggguggaucacgaugcaauuu 224122RNAHomo sapiens
41cgaaucauuauuugcugcucua 224222RNAHomo sapiens
42ugaccgauuucuccugguguuc 224322RNAHomo sapiens
43ugucuuacucccucaggcacau 224422RNAHomo sapiens
44aaucacuaaccacacggccagg 224523RNAHomo sapiens
45uaaagugcuuauagugcagguag 234622RNAHomo sapiens
46uuauaauacaaccugauaagug 224722RNAHomo sapiens
47ggauuccuggaaauacuguucu 224823RNAHomo sapiens
48uaagugcuuccauguuuuaguag 234923RNAHomo sapiens
49aaaagugcuuacagugcagguag 235022RNAHomo sapiens
50uguaaacauccuugacuggaag 225122RNAHomo sapiens
51ugucaguuugucaaauacccca 225222RNAHomo sapiens
52cuggacugagccgugcuacugg 225322RNAHomo sapiens
53ugagguaguagguugugugguu 225422RNAHomo sapiens
54ugugacagauugauaacugaaa 225518RNAHomo sapiens 55ugcuuccuuucagagggu
185622RNAHomo sapiens 56aaaccguuaccauuacugaguu 225722RNAHomo
sapiens 57aaagugcaucuuuuuagaggau 225826RNAHomo sapiens
58aaguaguugguuuguaugagaugguu 265923RNAHomo sapiens
59gacacgggcgacagcugcggccc 236023RNAHomo sapiens
60ucccccaggugugauucugauuu 236122RNAHomo sapiens
61aguuuugcauaguugcacuaca 226222RNAHomo sapiens
62aucaugaugggcuccucggugu 226322RNAHomo sapiens
63cuccugagccauucugagccuc 226422RNAHomo sapiens
64aaaaugguucccuuuagagugu 226522RNAHomo sapiens
65aagugcuuccuuuuagaggguu 226622RNAHomo sapiens
66cucuagagggaagcgcuuucug 226721RNAHomo sapiens
67cugaccuaugaauugacagcc 216821RNAHomo sapiens
68aagugaucuaaaggccuacau 216921RNAHomo sapiens
69ucgaggagcucacagucuagu 217021RNAHomo sapiens
70uggacugcccugaucuggaga 217123RNAHomo sapiens
71uagcagcgggaacaguucugcag 237219RNAHomo sapiens
72agguugacauacguuuccc 197322RNAHomo sapiens
73gguggcccggccgugccugagg 227422RNAHomo sapiens
74cuauacgaccugcugccuuucu 227523RNAHomo sapiens
75cccaguguucagacuaccuguuc 237617RNAHomo sapiens 76ucucgcuggggccucca
177719RNAHomo sapiens 77aauggauuuuuggagcagg 197822RNAHomo sapiens
78aacaauauccuggugcugagug 227921RNAHomo sapiens
79auguaugugugcaugugcaug 218019RNAHomo sapiens 80auggauaaggcuuuggcuu
198123RNAHomo sapiens 81gcagcagagaauaggacuacguc 238222RNAHomo
sapiens 82uggagagaaaggcaguuccuga 228323RNAHomo sapiens
83gcgaggaccccucggggucugac 238426RNAHomo sapiens
84gaugaugauggcagcaaauucugaaa 268522RNAHomo sapiens
85uucuggaauucugugugaggga 228622RNAHomo sapiens
86uuuuucauuauugcuccugacc 228721RNAHomo sapiens
87cagcagcacacugugguuugu 218818RNAHomo sapiens 88ucagcuggcccucauuuc
188922RNAHomo sapiens 89uagcagcacguaaauauuggcg 229022RNAHomo
sapiens 90uggaauguaaagaaguauguau 229124RNAHomo sapiens
91uggcccugacugaagaccagcagu 249222RNAHomo sapiens
92gcuauuucacgacaccaggguu 229323RNAHomo sapiens
93acuccauuuguuuugaugaugga 239422RNAHomo sapiens
94caaaaaccacaguuucuuuugc 229522RNAHomo sapiens
95caaaguuuaagauccuugaagu 229622RNAHomo sapiens
96aaaaguaaucgcgguuuuuguc 229721RNAHomo sapiens
97gccccugggccuauccuagaa 219822RNAHomo sapiens
98gcccaaaggugaauuuuuuggg 229923RNAHomo sapiens
99guccaguuuucccaggaaucccu 2310023RNAHomo sapiens
100caaagugcuuacagugcagguag 2310122RNAHomo sapiens
101uguaaacauccuacacucagcu 2210222RNAHomo sapiens
102cuauacaaucuauugccuuccc 2210322RNAHomo sapiens
103uuuucaacucuaaugggagaga 2210421RNAHomo sapiens
104cuuuuugcggucugggcuugc 2110521RNAHomo sapiens
105ucguggccuggucuccauuau 2110622RNAHomo sapiens
106ccgcacuguggguacuugcugc 2210724RNAHomo sapiens
107gaccuggacauguuugugcccagu 2410822RNAHomo sapiens
108caaucagcaaguauacugcccu 2210921RNAHomo sapiens
109aauggcgccacuaggguugug 2111022RNAHomo sapiens
110aggcauugacuucucacuagcu 2211122RNAHomo sapiens
111acuguaguaugggcacuuccag 2211221RNAHomo sapiens
112caaaacgugaggcgcugcuau 2111322RNAHomo sapiens
113aucgugcaucccuuuagagugu 2211422RNAHomo sapiens
114ucuauacagacccuggcuuuuc 2211522RNAHomo sapiens
115acaguagucugcacauugguua 2211620RNAHomo sapiens
116guugugucaguuuaucaaac 2011721RNAHomo sapiens
117uaguagaccguauagcguacg 2111821RNAHomo sapiens
118aucacauugccagggauuacc 2111921RNAHomo sapiens
119uugggacauacuuaugcuaaa 2112022RNAHomo sapiens
120uggcaguguauuguuagcuggu 2212119RNAHomo sapiens
121aaaaacuguaauuacuuuu 1912222RNAHomo sapiens
122ugugucacucgaugaccacugu 2212322RNAHomo sapiens
123cacacacugcaauuacuuuugc 2212422RNAHomo sapiens
124acccgucccguucguccccgga 2212521RNAHomo sapiens
125uccugcgcgucccagaugccc 2112623RNAHomo sapiens
126ugaguaccgccaugucuguuggg 2312723RNAHomo sapiens
127ccuaguagguguccaguaagugu 2312823RNAHomo sapiens
128agguuacccgagcaacuuugcau 2312924RNAHomo sapiens
129uuuggcaaugguagaacucacacu 2413025RNAHomo sapiens
130ggcggagggaaguagguccguuggu 2513121RNAHomo sapiens
131augaccuaugaauugacagac 2113222RNAHomo sapiens
132gugugcggaaaugcuucugcua 2213322RNAHomo sapiens
133uguaaacauccccgacuggaag 2213422RNAHomo sapiens
134cuccugacuccagguccugugu 2213522RNAHomo sapiens
135accuggcauacaauguagauuu 2213622RNAHomo sapiens
136caaucacuaacuccacugccau 2213725RNAHomo sapiens
137aggcaccagccaggcauugcucagc 2513821RNAHomo sapiens
138aacaggugacugguuagacaa 2113921RNAHomo sapiens
139acuggacuuggagucagaagg 2114022RNAHomo sapiens
140ggugcagugcugcaucucuggu 2214123RNAHomo sapiens
141ccucagggcuguagaacagggcu 2314221RNAHomo sapiens
142gcuaguccugacucagccagu 2114321RNAHomo sapiens
143agaccuggcccagaccucagc 2114420RNAHomo sapiens
144aggguguuucucucaucucu 2014523RNAHomo sapiens
145uguaaacauccuacacucucagc 2314622RNAHomo sapiens
146aaggagcucacagucuauugag 2214721RNAHomo sapiens
147aucacauugccagggauuucc 2114819RNAHomo sapiens
148ucuaggcugguacugcuga 1914921RNAHomo sapiens
149guggcugcacucacuuccuuc 2115022RNAHomo sapiens
150acuuuaacauggaagugcuuuc 2215121RNAHomo sapiens
151guucaaauccagaucuauaac 2115223RNAHomo sapiens
152uggaguccaggaaucugcauuuu 2315324RNAHomo sapiens
153ccagacagaauucuaugcacuuuc 2415423RNAHomo sapiens
154uaaauuucaccuuucugagaagg 2315524RNAHomo sapiens
155uggggagcugaggcucugggggug 2415623RNAHomo sapiens
156uagcaccauuugaaaucaguguu 2315720RNAHomo sapiens
157accaggaggcugaggccccu 2015823RNAHomo sapiens
158uaaggugcaucuagugcagauag 2315919RNAHomo sapiens
159gugaggacucgggaggugg 1916022RNAHomo sapiens
160caaauucguaucuaggggaaua 2216122RNAHomo sapiens
161accaucgaccguugauuguacc 2216222RNAHomo sapiens
162caugguucugucaagcaccgcg 2216323RNAHomo sapiens
163aagugccgccaucuuuugagugu 2316422RNAHomo sapiens
164aucacacaaaggcaacuuuugu 2216522RNAHomo sapiens
165cagugguuuuacccuaugguag 2216623RNAHomo sapiens
166cagugcaauaguauugucaaagc 2316722RNAHomo sapiens
167uacguagauauauauguauuuu 2216822RNAHomo sapiens
168uucacauugugcuacugucugc 2216922RNAHomo sapiens
169uacccagagcaugcagugugaa 2217022RNAHomo sapiens
170aacuggcccucaaagucccgcu 2217122RNAHomo sapiens
171ugccugucuacacuugcugugc 2217222RNAHomo sapiens
172aaaucucugcaggcaaauguga 2217317RNAHomo sapiens
173uaauugcuuccauguuu 1717422RNAHomo sapiens
174cucuagagggaagcgcuuucug 2217522RNAHomo sapiens
175aaaaguaauugcggucuuuggu 2217620RNAHomo sapiens
176auguauaaauguauacacac 2017719RNAHomo sapiens
177aagugugcagggcacuggu 1917821RNAHomo sapiens
178ucccacguuguggcccagcag 2117921RNAHomo sapiens
179agcuacaucuggcuacugggu 2118022RNAHomo sapiens
180ugcuggaucagugguucgaguc 2218122RNAHomo sapiens
181ugcaacuuaccugagucauuga 2218223RNAHomo sapiens
182ucucacacagaaaucgcacccgu 2318322RNAHomo sapiens
183aagugcugucauagcugagguc 2218423RNAHomo sapiens
184aucccuugcaggggcuguugggu 2318522RNAHomo sapiens
185auaagacgaacaaaagguuugu 2218622RNAHomo sapiens
186ccaguauuaacugugcugcuga 2218721RNAHomo sapiens
187gcgacccauacuugguuucag 2118822RNAHomo sapiens
188ugcccuguggacucaguucugg 2218921RNAHomo sapiens
189aaagugcuuccuuuuagaggg 2119022RNAHomo sapiens
190aggcaguguauuguuagcuggc 2219124RNAHomo sapiens
191acaaagugcuucccuuuagagugu 2419222RNAHomo sapiens
192ugccuacugagcugaaacacag 2219321RNAHomo sapiens
193gaaagcgcuucucuuuagagg 2119422RNAHomo sapiens
194aaaccuguguuguucaagaguc 2219522RNAHomo sapiens
195uauugcacauuacuaaguugca 2219621RNAHomo sapiens
196cuagacugaagcuccuugagg 2119723RNAHomo sapiens
197uagugcaauauugcuuauagggu 2319821RNAHomo sapiens
198uacaguacugugauaacugaa 2119923RNAHomo sapiens
199aguuuugcagguuugcauccagc 2320021RNAHomo sapiens
200uacugcagacaguggcaauca 2120120RNAHomo sapiens
201uacaguauagaugauguacu 2020223RNAHomo sapiens
202uacuccagagggcgucacucaug 2320321RNAHomo sapiens
203aguuaaugaauccuggaaagu 2120423RNAHomo sapiens
204ugugcuugcucgucccgcccgca 2320522RNAHomo sapiens
205auccgcgcucugacucucugcc 2220623RNAHomo sapiens
206ugucugcccgcaugccugccucu 2320721RNAHomo sapiens
207uaaggcacccuucugaguaga 2120822RNAHomo sapiens
208uauguaacaugguccacuaacu 2220923RNAHomo sapiens
209ccugcagcgacuugauggcuucc 2321023RNAHomo sapiens
210uucauuugguauaaaccgcgauu 2321122RNAHomo sapiens
211uggguuccuggcaugcugauuu 2221222RNAHomo sapiens
212augggugaauuuguagaaggau 2221322RNAHomo sapiens
213uugcauagucacaaaagugauc 2221421RNAHomo sapiens
214aaagugcuuccuuuuugaggg 2121519RNAHomo sapiens
215gugucugcuuccuguggga 1921622RNAHomo sapiens
216cugcaauguaagcacuucuuac 2221722RNAHomo sapiens
217ugcuaugccaacauauugccau 2221822RNAHomo sapiens
218cagugccucggcagugcagccc 2221922RNAHomo sapiens
219uaugucugcugaccaucaccuu 2222022RNAHomo sapiens
220caagcucgugucuguggguccg 2222122RNAHomo sapiens
221uaguacugugcauaucaucuau 2222223RNAHomo sapiens
222uauggcuuuucauuccuauguga 2322322RNAHomo sapiens
223uagaguuacacccugggaguua 2222421RNAHomo sapiens
224cuccguuugccuguuucgcug 2122522RNAHomo sapiens
225cuuagcagguuguauuaucauu 2222621RNAHomo sapiens
226auugacacuucugugaguaga 2122721RNAHomo sapiens
227uaauuuuauguauaagcuagu 2122821RNAHomo sapiens
228aaacuacugaaaaucaaagau 2122921RNAHomo sapiens
229aauaauacaugguugaucuuu 2123021RNAHomo sapiens
230uugaaaggcuauuucuugguc 2123121RNAHomo sapiens
231ucacagugaaccggucucuuu 2123224RNAHomo sapiens
232aauccuuggaaccuaggugugagu 2423323RNAHomo sapiens
233aggaagcccuggaggggcuggag 2323422RNAHomo sapiens
234cugcccuggcccgagggaccga 2223520RNAHomo sapiens
235caccaggcauuguggucucc 2023625RNAHomo sapiens
236ugggaacggguuccggcagacgcug 2523722RNAHomo sapiens
237uguaacagcaacuccaugugga 2223822RNAHomo sapiens
238uagcagcacaucaugguuuaca 2223921RNAHomo sapiens
239aggggugcuaucugugauuga 2124022RNAHomo sapiens
240ucacaagucaggcucuugggac 2224117RNAHomo sapiens
241uucaaguaauucaggug 1724222RNAHomo sapiens
242ugugcgcagggagaccucuccc 2224322RNAHomo sapiens
243uuguacaugguaggcuuucauu 2224423RNAHomo sapiens
244ucaaaugcucagacuccuguggu 2324522RNAHomo sapiens
245uaacacugucugguaaagaugg 2224622RNAHomo sapiens
246aaccaucgaccguugaguggac 2224722RNAHomo sapiens
247aacuggccuacaaagucccagu 2224823RNAHomo sapiens
248uaagugcuuccauguuucagugg 2324922RNAHomo sapiens
249agaggcuggccgugaugaauuc 2225022RNAHomo sapiens
250aacaucacagcaagucugugcu 2225122RNAHomo sapiens
251ucagcaaacauuuauugugugc 2225222RNAHomo sapiens
252aaaaguaauugugguuuuggcc 2225321RNAHomo sapiens
253ugacaacuauggaugagcucu 2125422RNAHomo sapiens
254auucuaauuucuccacgucuuu 2225521RNAHomo sapiens
255uagauaaaauauugguaccug 2125621RNAHomo sapiens
256caaagaggaaggucccauuac 2125721RNAHomo sapiens
257uuuccauaggugaugagucac 2125821RNAHomo sapiens
258cacaagguauugguauuaccu 2125919RNAHomo sapiens
259aagcagcugccucugaggc 1926022RNAHomo sapiens
260auaauacaugguuaaccucuuu 2226122RNAHomo sapiens
261uccauuacacuacccugccucu 2226222RNAHomo sapiens
262ccaguggggcugcuguuaucug 2226322RNAHomo sapiens
263ugguuuaccgucccacauacau 2226422RNAHomo sapiens
264cuccuauaugaugccuuucuuc 2226522RNAHomo sapiens
265ugaaggucuacugugugccagg 2226622RNAHomo sapiens
266caaaccacacugugguguuaga 2226722RNAHomo sapiens
267aaagugcauccuuuuagagugu 2226822RNAHomo sapiens
268caagcucgcuucuaugggucug 2226917RNAHomo sapiens
269ucccaccgcugccaccc 1727022RNAHomo sapiens
270cucuagagggaagcgcuuucug 2227122RNAHomo sapiens
271gguccagaggggagauagguuc 2227222RNAHomo sapiens
272ugucuacuacuggagacacugg 2227322RNAHomo sapiens
273cuuucagucagauguuugcugc 2227422RNAHomo sapiens
274cucaucugcaaagaaguaagug 2227522RNAHomo sapiens
275caagaaccucaguugcuuuugu 2227622RNAHomo sapiens
276uaugcauuguauuuuuaggucc 2227722RNAHomo sapiens
277uauugcacucgucccggccucc 2227822RNAHomo sapiens
278ucgugcaucccuuuagaguguu 2227922RNAHomo sapiens
279caaaacuggcaauuacuuuugc 2228022RNAHomo sapiens
280uauaccucaguuuuaucaggug 2228122RNAHomo sapiens
281caggucgucuugcagggcuucu 2228220RNAHomo sapiens
282auuccuagaaauuguucaua 2028319RNAHomo sapiens
283aguguggcuuucuuagagc 1928421RNAHomo sapiens
284agaggauacccuuuguauguu 2128522RNAHomo sapiens
285cugguuucacaugguggcuuag 2228622RNAHomo sapiens
286gugacaucacauauacggcagc 2228719RNAHomo sapiens
287gggcgccugugaucccaac 1928823RNAHomo sapiens
288cggcccgggcugcugcuguuccu 2328922RNAHomo sapiens
289cacuagauugugagcuccugga 2229022RNAHomo sapiens
290cuauacagucuacugucuuucc 2229119RNAHomo sapiens
291gaugaugcugcugaugcug 1929218RNAHomo sapiens 292ugaggcaguagauugaau
1829322RNAHomo sapiens 293cugccaauuccauaggucacag 2229417RNAHomo
sapiens 294uaagugcuuccaugcuu 1729522RNAHomo sapiens
295uauguaacacgguccacuaacc 2229622RNAHomo sapiens
296cagcagcaauucauguuuugaa 2229722RNAHomo sapiens
297uaacugguugaacaacugaacc 2229822RNAHomo sapiens
298guucucccaacguaagcccagc 2229922RNAHomo sapiens
299cuuaugcaagauucccuucuac 2230022RNAHomo sapiens
300aaagugcauccuuuuagagguu 2230121RNAHomo sapiens
301uaggacacauggucuacuucu 2130222RNAHomo sapiens
302cugaagcucagagggcucugau 2230321RNAHomo sapiens
303ugcaggaccaagaugagcccu 2130422RNAHomo sapiens
304accguggcuuucgauuguuacu 2230520RNAHomo sapiens
305gugcauugcuguugcauugc 2030621RNAHomo sapiens
306aaaacggugagauuuuguuuu 2130720RNAHomo sapiens
307auggagauagauauagaaau 2030823RNAHomo sapiens
308aaggagcuuacaaucuagcuggg 2330922RNAHomo sapiens
309cacuggcuccuuucuggguaga 2231022RNAHomo sapiens
310acaaagugcuucccuuuagagu 2231122RNAHomo sapiens
311augcaccugggcaaggauucug 2231222RNAHomo sapiens
312gaaaucaagcgugggugagacc 2231322RNAHomo sapiens
313caaagaauucuccuuuugggcu 2231419RNAHomo sapiens
314ugagcugcuguaccaaaau 1931522RNAHomo sapiens
315uucaaguaauccaggauaggcu 2231622RNAHomo sapiens
316augguacccuggcauacugagu 2231722RNAHomo sapiens
317uucccuuugucauccuucgccu 2231822RNAHomo sapiens
318uuugaggcuacagugagaugug 2231921RNAHomo sapiens
319ccaccaccgugucugacacuu 2132022RNAHomo sapiens
320ugcaacgaaccugagccacuga 2232121RNAHomo sapiens
321agagaagaagaucagccugca 2132220RNAHomo sapiens
322ucugcaggguuugcuuugag 2032323RNAHomo sapiens
323uuauugcuuaagaauacgcguag 2332422RNAHomo sapiens
324aaucauacacgguugaccuauu 2232521RNAHomo sapiens
325aggguaagcugaaccucugau 2132622RNAHomo sapiens
326gugaacgggcgccaucccgagg 2232722RNAHomo sapiens
327aauugcacgguauccaucugua 2232822RNAHomo sapiens
328aaaaccgucuaguuacaguugu 2232922RNAHomo sapiens
329agaguugagucuggacgucccg 2233021RNAHomo sapiens
330ccacaccguaucugacacuuu 2133122RNAHomo sapiens
331cucaguagccaguguagauccu 2233221RNAHomo sapiens
332cacauuacacggucgaccucu 2133322RNAHomo sapiens
333aucauagaggaaaauccauguu 2233420RNAHomo sapiens
334ccauggaucuccaggugggu 2033523RNAHomo sapiens
335gaacgcgcuucccuauagagggu 2333623RNAHomo sapiens
336acuuaaacguggauguacuugcu 2333722RNAHomo sapiens
337agagcuuagcugauuggugaac 2233820RNAHomo sapiens
338agaccauggguucucauugu 2033921RNAHomo sapiens
339uacucaaaaagcugucaguca 2134022RNAHomo sapiens
340guagauucuccuucuaugagua 2234123RNAHomo sapiens
341aaacucuacuuguccuucugagu 2334223RNAHomo sapiens
342gagggucuugggagggaugugac 2334322RNAHomo sapiens
343ccucccacacccaaggcuugca 2234423RNAHomo sapiens
344aacauucauugcugucggugggu 2334522RNAHomo sapiens
345aacgcacuucccuuuagagugu 2234622RNAHomo sapiens
346ucaguaaauguuuauuagauga 2234722RNAHomo sapiens
347auaaagcuagauaaccgaaagu 2234820RNAHomo sapiens
348ggggagcuguggaagcagua 2034921RNAHomo sapiens
349ugaguuggccaucugagugag 2135023RNAHomo sapiens
350acuugggcacugaaacaaugucc 2335122RNAHomo sapiens
351uaauacugccugguaaugauga 2235222RNAHomo sapiens
352uaugugccuuuggacuacaucg 2235322RNAHomo sapiens
353uggugguuuacaaaguaauuca 2235422RNAHomo sapiens
354acucaaaaugggggcgcuuucc 2235522RNAHomo sapiens
355ccucugaaauucaguucuucag 2235622RNAHomo sapiens
356aacgccauuaucacacuaaaua 2235722RNAHomo sapiens
357uugggaucauuuugcauccaua 2235822RNAHomo sapiens
358uggcucaguucagcaggaacag 2235922RNAHomo sapiens
359ucaggcucaguccccucccgau 2236023RNAHomo sapiens
360ucauagcccuguacaaugcugcu 2336122RNAHomo sapiens
361uauguaauaugguccacaucuu 2236218RNAHomo sapiens
362uucacagggaggugucau 1836322RNAHomo sapiens
363uacugcagacguggcaaucaug 2236421RNAHomo sapiens
364gcaggaacuugugagucuccu 2136522RNAHomo sapiens
365gaugagcucauuguaauaugag 2236622RNAHomo sapiens
366agaucgaccguguuauauucgc 2236721RNAHomo sapiens
367guguugaaacaaucucuacug 2136823RNAHomo sapiens
368ucugcucauaccccaugguuucu 2336918RNAHomo sapiens
369ugcuuccuuucagagggu 1837022RNAHomo sapiens
370aaagugcuuccuuuuagagggu 2237122RNAHomo sapiens
371caacuagacugugagcuucuag 2237220RNAHomo sapiens
372agagucuugugaugucuugc 2037320RNAHomo sapiens
373cuacaaagggaagcccuuuc 2037423RNAHomo sapiens
374cacucagccuugagggcacuuuc 2337522RNAHomo sapiens
375cuuaucagauuguauuguaauu 2237625RNAHomo sapiens
376cuagugagggacagaaccaggauuc 2537721RNAHomo sapiens
377uguucauguagauguuuaagc
2137821RNAHomo sapiens 378auauaugaugacuuagcuuuu 2137921RNAHomo
sapiens 379cuccagagggaugcacuuucu 2138022RNAHomo sapiens
380caucuuaccggacagugcugga 2238122RNAHomo sapiens
381uggguggucuggagauuugugc 2238223RNAHomo sapiens
382aaagugcugcgacauuugagcgu 2338322RNAHomo sapiens
383aaaaguaauugcgaguuuuacc 2238422RNAHomo sapiens
384aaaaguacuugcggauuuugcu 2238518RNAHomo sapiens
385uugagaaggaggcugcug 1838623RNAHomo sapiens
386caagucuuauuugagcaccuguu 2338721RNAHomo sapiens
387gcgacccacucuugguuucca 2138822RNAHomo sapiens
388uagguaguuuccuguuguuggg 2238922RNAHomo sapiens
389caauuuagugugugugauauuu 2239021RNAHomo sapiens
390gugcauuguaguugcauugca 2139122RNAHomo sapiens
391aaaaguaauugugguuuuugcc 2239222RNAHomo sapiens
392agucauuggaggguuugagcag 2239322RNAHomo sapiens
393uggauuucuuugugaaucacca 2239423RNAHomo sapiens
394ugauuguagccuuuuggaguaga 2339522RNAHomo sapiens
395ccuauucuugauuacuuguuuc 2239622RNAHomo sapiens
396ucgugucuuguguugcagccgg 2239722RNAHomo sapiens
397acaguagucugcacauugguua 2239822RNAHomo sapiens
398aaucaugugcagugccaauaug 2239923RNAHomo sapiens
399uaaggugcaucuagugcaguuag 2340021RNAHomo sapiens
400cuggauggcuccuccaugucu 2140122RNAHomo sapiens
401ugauugguacgucuguggguag 2240227RNAHomo sapiens
402cacuguaggugauggugagagugggca 2740319RNAHomo sapiens
403agcugucugaaaaugucuu 1940422RNAHomo sapiens
404uucacaaggaggugucauuuau 2240522RNAHomo sapiens
405agacuucccauuugaagguggc 2240623RNAHomo sapiens
406ucuuugguuaucuagcuguauga 2340722RNAHomo sapiens
407aagugccuccuuuuagaguguu 2240822RNAHomo sapiens
408uucccuuugucauccuaugccu 2240922RNAHomo sapiens
409uagcaccauuugaaaucgguua 2241018RNAHomo sapiens
410cgggcguggugguggggg 1841122RNAHomo sapiens
411uggagugugacaaugguguuug 2241222RNAHomo sapiens
412caacaaaucccagucuaccuaa 2241322RNAHomo sapiens
413caggccauauugugcugccuca 2241423RNAHomo sapiens
414aacauucauuguugucggugggu 2341521RNAHomo sapiens
415ugauuguccaaacgcaauucu 2141623RNAHomo sapiens
416uaagugcuuccauguuugagugu 2341722RNAHomo sapiens
417uggcagugucuuagcugguugu 2241821RNAHomo sapiens
418aauauaacacagauggccugu 2141922RNAHomo sapiens
419caauguuuccacagugcaucac 2242022RNAHomo sapiens
420aaugcaccugggcaaggauuca 2242121RNAHomo sapiens
421ugguagacuauggaacguagg 2142223RNAHomo sapiens
422uuucaagccagggggcguuuuuc 2342322RNAHomo sapiens
423cucuagagggaagcacuuucug 2242422RNAHomo sapiens
424auauuaccauuagcucaucuuu 2242521RNAHomo sapiens
425auccuugcuaucugggugcua 2142621RNAHomo sapiens
426aggcaagaugcuggcauagcu 2142722RNAHomo sapiens
427aacccguagauccgaacuugug 2242822RNAHomo sapiens
428gaggguuggguggaggcucucc 2242922RNAHomo sapiens
429ggggguccccggugcucggauc 2243021RNAHomo sapiens
430caacaccagucgaugggcugu 2143123RNAHomo sapiens
431ggcagguucucacccucucuagg 2343222RNAHomo sapiens
432uuuaggauaagcuugacuuuug 2243321RNAHomo sapiens
433uggaggagaaggaaggugaug 2143421RNAHomo sapiens
434caaagguauuugugguuuuug 2143522RNAHomo sapiens
435agaauuguggcuggacaucugu 2243622RNAHomo sapiens
436aaugcacccgggcaaggauucu 2243723RNAHomo sapiens
437uaagugcuuccauguuuugguga 2343822RNAHomo sapiens
438uuccuaugcauauacuucuuug 2243922RNAHomo sapiens
439uggaauguaaggaagugugugg 2244022RNAHomo sapiens
440aaagugcuucucuuuggugggu 2244122RNAHomo sapiens
441aaaaguaauugcggauuuugcc 2244221RNAHomo sapiens
442gugucuuuugcucugcaguca 2144322RNAHomo sapiens
443uguaaacauccucgacuggaag 2244421RNAHomo sapiens
444ccccaccuccucucuccucag 2144522RNAHomo sapiens
445gaaggcgcuucccuuuagagcg 2244622RNAHomo sapiens
446guggguacggcccagugggggg 2244722RNAHomo sapiens
447cguguauuugacaagcugaguu 2244822RNAHomo sapiens
448uccgagccugggucucccucuu 2244922RNAHomo sapiens
449cgaaaacagcaauuaccuuugc 2245022RNAHomo sapiens
450aaaagcuggguugagagggcga 2245123RNAHomo sapiens
451uccaguaccacgugucagggcca 2345223RNAHomo sapiens
452uuacaguuguucaaccaguuacu 2345322RNAHomo sapiens
453gagcuuauucauaaaagugcag 2245422RNAHomo sapiens
454cuugguucagggagggucccca 2245521RNAHomo sapiens
455acucuagcugccaaaggcgcu 2145623RNAHomo sapiens
456uauucauuuauccccagccuaca 2345721RNAHomo sapiens
457cccagauaauggcacucucaa 2145822RNAHomo sapiens
458aaaacuguaauuacuuuuguac 2245923RNAHomo sapiens
459caguaacaaagauucauccuugu 2346023RNAHomo sapiens
460ucggggaucaucaugucacgaga 2346122RNAHomo sapiens
461ugauauguuugauauauuaggu 2246222RNAHomo sapiens
462augguuccgucaagcaccaugg 2246322RNAHomo sapiens
463acuguugcuaauaugcaacucu 2246422RNAHomo sapiens
464uuuugcgauguguuccuaauau 2246522RNAHomo sapiens
465aauugcacuuuagcaaugguga 2246620RNAHomo sapiens
466uaaggcacgcggugaaugcc 2046723RNAHomo sapiens
467ugcaccaugguugucugagcaug 2346823RNAHomo sapiens
468uaauacugccggguaaugaugga 2346920RNAHomo sapiens
469guccgcucggcgguggccca 2047022RNAHomo sapiens
470cucuagagggaagcacuuucug 2247122RNAHomo sapiens
471acaguagagggaggaaucgcag 2247222RNAHomo sapiens
472caaaaguaauuguggauuuugu 2247322RNAHomo sapiens
473uagcuuaucagacugauguuga 2247421RNAHomo sapiens
474ugguucuagacuugccaacua 2147523RNAHomo sapiens
475aggcaguguaguuagcugauugc 2347622RNAHomo sapiens
476uaauacugucugguaaaaccgu 2247722RNAHomo sapiens
477augcugacauauuuacuagagg 2247822RNAHomo sapiens
478acugauuucuuuugguguucag 2247922RNAHomo sapiens
479gccugcugggguggaaccuggu 2248021RNAHomo sapiens
480cuauacaaucuacugucuuuc 2148122RNAHomo sapiens
481caguuaucacagugcugaugcu 2248221RNAHomo sapiens
482uaaaguaaauaugcaccaaaa 2148323RNAHomo sapiens
483uacugcaucaggaacugauugga 2348422RNAHomo sapiens
484cucuagagggaagcgcuuucug 2248522RNAHomo sapiens
485cuuucagucggauguuuacagc 2248620RNAHomo sapiens
486guguguggaaaugcuucugc 2048722RNAHomo sapiens
487aaucguacagggucauccacuu 2248822RNAHomo sapiens
488gacugacaccucuuugggugaa 2248922RNAHomo sapiens
489uccuucauuccaccggagucug 2249021RNAHomo sapiens
490agugaaugauggguucugacc 2149123RNAHomo sapiens
491uggaagacuagugauuuuguugu 2349221RNAHomo sapiens
492agggcccccccucaauccugu 2149323RNAHomo sapiens
493aggaugagcaaagaaaguagauu 2349422RNAHomo sapiens
494ugguugaccauagaacaugcgc 2249517RNAHomo sapiens
495gugggggagaggcuguc 1749622RNAHomo sapiens
496ucucugggccugugucuuaggc 2249722RNAHomo sapiens
497aacuggaucaauuauaggagug 2249822RNAHomo sapiens
498caucaucgucucaaaugagucu 2249922RNAHomo sapiens
499caucuuccaguacaguguugga 2250022RNAHomo sapiens
500aucgugcauccuuuuagagugu 2250121RNAHomo sapiens
501ggcuagcaacagcgcuuaccu 2150222RNAHomo sapiens
502accuugccuugcugcccgggcc 2250322RNAHomo sapiens
503uggugggcacagaaucuggacu 2250422RNAHomo sapiens
504aaacauucgcggugcacuucuu 2250522RNAHomo sapiens
505ucuucucuguuuuggccaugug 2250622RNAHomo sapiens
506ccuauucuugguuacuugcacg 2250723RNAHomo sapiens
507aguauguucuuccaggacagaac 2350822RNAHomo sapiens
508uggacggagaacugauaagggu 2250921RNAHomo sapiens
509aucauagaggaaaauccacgu 2151022RNAHomo sapiens
510cguguucacagcggaccuugau 2251124RNAHomo sapiens
511agccuggaagcuggagccugcagu 2451221RNAHomo sapiens
512uggcagggaggcugggagggg 2151322RNAHomo sapiens
513uugagaaugaugaaucauuagg 2251422RNAHomo sapiens
514cuauacaaccuacugccuuccc 2251522RNAHomo sapiens
515ggagaaauuauccuuggugugu 2251622RNAHomo sapiens
516aaagugcuucccuuuggacugu 2251719RNAHomo sapiens
517ugggcguaucuguaugcua 1951820RNAHomo sapiens
518cuguaugcccucaccgcuca 2051921RNAHomo sapiens
519cugacuguugccguccuccag 2152024RNAHomo sapiens
520cugaagugauguguaacugaucag 2452123RNAHomo sapiens
521caaagugcuguucgugcagguag 2352222RNAHomo sapiens
522agggcuuagcugcuugugagca 2252320RNAHomo sapiens
523aggaauguuccuucuuugcc 2052422RNAHomo sapiens
524acacagggcuguugugaagacu 2252521RNAHomo sapiens
525gaaggcgcuucccuuuggagu 2152623RNAHomo sapiens
526uaauccuugcuaccugggugaga 2352724RNAHomo sapiens
527agccugauuaaacacaugcucuga 2452822RNAHomo sapiens
528acugcauuaugagcacuuaaag 2252922RNAHomo sapiens
529ggaggggucccgcacugggagg 2253022RNAHomo sapiens
530aucgggaaugucguguccgccc 2253122RNAHomo sapiens
531gagugccuucuuuuggagcguu 2253222RNAHomo sapiens
532agagguugcccuuggugaauuc 2253322RNAHomo sapiens
533agacccuggucugcacucuauc 2253422RNAHomo sapiens
534caaaaaucucaauuacuuuugc 2253520RNAHomo sapiens
535uaaagagcccuguggagaca 2053623RNAHomo sapiens
536agcugguguugugaaucaggccg 2353721RNAHomo sapiens
537ugucuugcaggccgucaugca 2153822RNAHomo sapiens
538ugaaacauacacgggaaaccuc 2253922RNAHomo sapiens
539uugcauauguaggaugucccau 2254023RNAHomo sapiens
540cuaauaguaucuaccacaauaaa 2354122RNAHomo sapiens
541aaucauacagggacauccaguu 2254223RNAHomo sapiens
542ucuggcuccgugucuucacuccc 2354322RNAHomo sapiens
543uauacaagggcagacucucucu 2254427RNAHomo sapiens
544auugaucaucgacacuucgaacgcaau 2754522RNAHomo sapiens
545ucggauccgucugagcuuggcu 2254622RNAHomo sapiens
546uccuguacugagcugccccgag 2254722RNAHomo sapiens
547ucagugcacuacagaacuuugu 2254822RNAHomo sapiens
548ugugagguuggcauuguugucu 2254922RNAHomo sapiens
549aaaaguauuugcggguuuuguc 2255021RNAHomo sapiens
550cauaaaguagaaagcacuacu 2155121RNAHomo sapiens
551uuaauaucggacaaccauugu 2155222RNAHomo sapiens
552uaaugccccuaaaaauccuuau 2255322RNAHomo sapiens
553cacccguagaaccgaccuugcg 2255422RNAHomo sapiens
554caucuuacugggcagcauugga 2255522RNAHomo sapiens
555uaacacugucugguaacgaugu 2255621RNAHomo sapiens
556aaagcgcuucccuucagagug 2155725RNAHomo sapiens
557gcugggcagggcuucugagcuccuu 2555822RNAHomo sapiens
558gugaauuaccgaagggccauaa 2255922RNAHomo sapiens
559ucagugcaucacagaacuuugu 2256023RNAHomo sapiens
560agcagcauuguacagggcuauga 2356122RNAHomo sapiens
561ccaaaacugcaguuacuuuugc 2256221RNAHomo sapiens
562cccggagccaggaugcagcuc 2156322RNAHomo sapiens
563uauagggauuggagccguggcg 2256422RNAHomo sapiens
564agaucagaaggugauuguggcu 2256522RNAHomo sapiens
565ucugcccccuccgcugcugcca
2256623RNAHomo sapiens 566gaagugcuucgauuuuggggugu 2356720RNAHomo
sapiens 567acucaaacugugggggcacu 2056824RNAHomo sapiens
568agcagaagcagggagguucuccca 2456922RNAHomo sapiens
569uuugugaccugguccacuaacc 2257023RNAHomo sapiens
570acuucaccugguccacuagccgu 2357123RNAHomo sapiens
571caaagcgcuucucuuuagagugu 2357224RNAHomo sapiens
572ucagaacaaaugccgguucccaga 2457322RNAHomo sapiens
573acuuguaugcuagcucagguag 2257422RNAHomo sapiens
574uugugucaauaugcgaugaugu 2257521RNAHomo sapiens
575cacuguguccuuucugcguag 2157622RNAHomo sapiens
576aaauuauuguacaucggaugag 2257722RNAHomo sapiens
577aagauguggaaaaauuggaauc 2257821RNAHomo sapiens
578ucuuguguucucuagaucagu 2157922RNAHomo sapiens
579gacuauagaacuuucccccuca 2258018RNAHomo sapiens
580aucccaccucugccacca 1858117RNAHomo sapiens 581ucgccuccuccucuccc
1758221RNAHomo sapiens 582gaacggcuucauacaggaguu 2158322RNAHomo
sapiens 583uuugguccccuucaaccagcua 2258422RNAHomo sapiens
584ggguggggauuuguugcauuac 2258522RNAHomo sapiens
585caagcuuguaucuauagguaug 2258622RNAHomo sapiens
586ugagaaccacgucugcucugag 2258721RNAHomo sapiens
587uugugcuugaucuaaccaugu 2158821RNAHomo sapiens
588caagucacuagugguuccguu 2158922RNAHomo sapiens
589ccaauauuacugugcugcuuua 2259023RNAHomo sapiens
590cagugcaaugauauugucaaagc 2359121RNAHomo sapiens
591ugauauguuugauauuggguu 2159222RNAHomo sapiens
592uuuguucguucggcucgcguga 2259322RNAHomo sapiens
593uagcaaaaacugcaguuacuuu 2259422RNAHomo sapiens
594aggggcuggcuuuccucugguc 2259522RNAHomo sapiens
595caaagugccucccuuuagagug 2259623RNAHomo sapiens
596uaaaucccauggugccuucuccu 2359720RNAHomo sapiens
597guagaggagauggcgcaggg 2059822RNAHomo sapiens
598acaggugagguucuugggagcc 2259922RNAHomo sapiens
599cuguugccacuaaccucaaccu 2260022RNAHomo sapiens
600cucuagagggaagcacuuucug 2260122RNAHomo sapiens
601aaaguucugagacacuccgacu 2260221RNAHomo sapiens
602uaacagucuccagucacggcc 2160322RNAHomo sapiens
603cgucaacacuugcugguuuccu 2260422RNAHomo sapiens
604ugaguauuacauggccaaucuc 2260522RNAHomo sapiens
605ucaaaacugaggggcauuuucu 2260622RNAHomo sapiens
606aaaaacugagacuacuuuugca 2260721RNAHomo sapiens
607ucuaguaagaguggcagucga 2160822RNAHomo sapiens
608cccugugcccggcccacuucug 2260922RNAHomo sapiens
609uuaugguuugccugggacugag 2261022RNAHomo sapiens
610auguagggcuaaaagccauggg 2261121RNAHomo sapiens
611uuaggccgcagaucuggguga 2161222RNAHomo sapiens
612uucaacggguauuuauugagca 2261322RNAHomo sapiens
613uuugguccccuucaaccagcug 2261422RNAHomo sapiens
614gucauacacggcucuccucucu 2261525RNAHomo sapiens
615aaaggauucugcugucggucccacu 2561622RNAHomo sapiens
616auauaauacaaccugcuaagug 2261722RNAHomo sapiens
617aacacaccugguuaaccucuuu 2261822RNAHomo sapiens
618aagacgggaggaaagaagggag 2261922RNAHomo sapiens
619aggcagcgggguguaguggaua 2262022RNAHomo sapiens
620cugcgcaagcuacugccuugcu 2262123RNAHomo sapiens
621ccaguuaccgcuuccgcuaccgc 2362222RNAHomo sapiens
622cagugcaaugaugaaagggcau 2262318RNAHomo sapiens
623gucccuguucaggcgcca 1862422RNAHomo sapiens
624ucaccagcccuguguucccuag 2262522RNAHomo sapiens
625cucuagagggaagcgcuuucug 2262622RNAHomo sapiens
626ugagccccugugccgcccccag 2262721RNAHomo sapiens
627gucagcggaggaaaagaaacu 2162822RNAHomo sapiens
628cggcaacaagaaacugccugag 2262923RNAHomo sapiens
629cuggagauauggaagagcugugu 2363022RNAHomo sapiens
630cuuggcaccuagcaagcacuca 2263121RNAHomo sapiens
631ugagcuaaaugugugcuggga 2163222RNAHomo sapiens
632cacgcucaugcacacacccaca 2263320RNAHomo sapiens
633ucguuugccuuuuucugcuu 2063422RNAHomo sapiens
634acagauucgauucuaggggaau 2263522RNAHomo sapiens
635uaaucucagcuggcaacuguga 2263622RNAHomo sapiens
636ggauaucaucauauacuguaag 2263722RNAHomo sapiens
637gggguuccuggggaugggauuu 2263821RNAHomo sapiens
638uuaagacuugcagugauguuu 2163922RNAHomo sapiens
639uauggcacugguagaauucacu 2264022RNAHomo sapiens
640caaccuggaggacuccaugcug 2264123RNAHomo sapiens
641gcaaagcacacggccugcagaga 2364221RNAHomo sapiens
642cuguacaggccacugccuugc 2164321RNAHomo sapiens
643ucacuccucuccucccgucuu 2164422RNAHomo sapiens
644acagcaggcacagacaggcagu 2264523RNAHomo sapiens
645uaggcagugucauuagcugauug 2364622RNAHomo sapiens
646acuuuaacauggaggcacuugc 2264722RNAHomo sapiens
647gaaguuguucgugguggauucg 2264822RNAHomo sapiens
648acccuaucaauauugucucugc 2264921RNAHomo sapiens
649gugccagcugcagugggggag 2165020RNAHomo sapiens
650agagguauagggcaugggaa 2065122RNAHomo sapiens
651auucugcauuuuuagcaaguuc 2265219RNAHomo sapiens
652ugucucugcugggguuucu 1965320RNAHomo sapiens
653cggcucugggucugugggga 2065421RNAHomo sapiens
654aaggcagggcccccgcucccc 2165522RNAHomo sapiens
655cuauacggccuccuagcuuucc 2265621RNAHomo sapiens
656uccuucugcuccgucccccag 2165722RNAHomo sapiens
657ugcccuaaaugccccuucuggc 2265822RNAHomo sapiens
658aguauucuguaccagggaaggu 2265922RNAHomo sapiens
659uucuccaaaagggagcacuuuc 2266022RNAHomo sapiens
660aacuguuugcagaggaaacuga 2266122RNAHomo sapiens
661ccuguucuccauuacuuggcuc 2266222RNAHomo sapiens
662aucuggagguaagaagcacuuu 2266322RNAHomo sapiens
663uaugugggaugguaaaccgcuu 2266422RNAHomo sapiens
664uauacaagggcaagcucucugu 2266522RNAHomo sapiens
665uuauaaagcaaugagacugauu 2266622RNAHomo sapiens
666uaacagucuacagccauggucg 2266723RNAHomo sapiens
667uguaguguuuccuacuuuaugga 2366822RNAHomo sapiens
668acggguuaggcucuugggagcu 2266922RNAHomo sapiens
669cugggagaaggcuguuuacucu 2267022RNAHomo sapiens
670gugagucucuaagaaaagagga 2267121RNAHomo sapiens
671cggcggggacggcgauugguc 2167221RNAHomo sapiens
672ccuguugaaguguaaucccca 2167321RNAHomo sapiens
673uuuugcaccuuuuggagugaa 2167421RNAHomo sapiens
674caucccuugcaugguggaggg 2167521RNAHomo sapiens
675cggggcagcucaguacaggau 2167621RNAHomo sapiens
676aagccugcccggcuccucggg 2167722RNAHomo sapiens
677ugggucuuugcgggcgagauga 2267821RNAHomo sapiens
678uccgguucucagggcuccacc 2167922RNAHomo sapiens
679ugccuacugagcugauaucagu 2268022RNAHomo sapiens
680aguuuugcagguuugcauuuca 2268118RNAHomo sapiens
681gcaugggugguucagugg 1868222RNAHomo sapiens
682auaagacgagcaaaaagcuugu 2268323RNAHomo sapiens
683uauggcuuuuuauuccuauguga 2368422RNAHomo sapiens
684cuagguauggucccagggaucc 2268522RNAHomo sapiens
685aacauucaaccugucggugagu 2268621RNAHomo sapiens
686augauccaggaaccugccucu 2168722RNAHomo sapiens
687cgcaggggccgggugcucaccg 2268821RNAHomo sapiens
688uggguuuacguugggagaacu 2168923RNAHomo sapiens
689uacccuguagauccgaauuugug 2369022RNAHomo sapiens
690aguggggaacccuuccaugagg 2269123RNAHomo sapiens
691aggaccugcgggacaagauucuu 2369223RNAHomo sapiens
692uucucgaggaaagaagcacuuuc 2369322RNAHomo sapiens
693uacucaggagaguggcaaucac 2269420RNAHomo sapiens
694ccccagggcgacgcggcggg 2069523RNAHomo sapiens
695ucucuggagggaagcacuuucug 2369625RNAHomo sapiens
696gggcgacaaagcaagacucuuucuu 2569721RNAHomo sapiens
697aggcggagacuugggcaauug 2169822RNAHomo sapiens
698ugcggggcuagggcuaacagca 2269923RNAHomo sapiens
699agugccugagggaguaagagccc 2370021RNAHomo sapiens
700uacuuggaaaggcaucaguug 2170122RNAHomo sapiens
701uuuagagacggggucuugcucu 2270221RNAHomo sapiens
702aggaggcagcgcucucaggac 2170320RNAHomo sapiens
703cgugccacccuuuuccccag 2070421RNAHomo sapiens
704gaagugugccguggugugucu 2170522RNAHomo sapiens
705cggaugagcaaagaaagugguu 2270622RNAHomo sapiens
706agaaggaaauugaauucauuua 2270721RNAHomo sapiens
707gcaguccaugggcauauacac 2170822RNAHomo sapiens
708gcugacuccuaguccagggcuc 2270923RNAHomo sapiens
709uuuggcacuagcacauuuuugcu 2371018RNAHomo sapiens
710cagggaggugaaugugau 1871122RNAHomo sapiens
711uucucaaggaggugucguuuau 2271222RNAHomo sapiens
712aaaaguaauugcgguuuuugcc 2271322RNAHomo sapiens
713aggcggggcgccgcgggaccgc 2271420RNAHomo sapiens
714aaaagcuggguugagagggu 2071522RNAHomo sapiens
715aaaagcuggguugagagggcaa 2271622RNAHomo sapiens
716uggugggccgcagaacaugugc 2271720RNAHomo sapiens
717ccucugggcccuuccuccag 2071818RNAHomo sapiens
718uccagugcccuccucucc 1871922RNAHomo sapiens
719cuggcccucucugcccuuccgu 2272022RNAHomo sapiens
720ugagaacugaauuccauaggcu 2272121RNAHomo sapiens
721cgcgggugcuuacugacccuu 2172221RNAHomo sapiens
722ugagugccggugccugcccug 2172322RNAHomo sapiens
723cucggcgcggggcgcgggcucc 2272422RNAHomo sapiens
724uccagcaucagugauuuuguug 2272523RNAHomo sapiens
725cgggucggaguuagcucaagcgg 2372622RNAHomo sapiens
726uggucuaggauuguuggaggag 2272722RNAHomo sapiens
727uucauucggcuguccagaugua 2272821RNAHomo sapiens
728ccaguccugugccugccgccu 2172926RNAHomo sapiens
729gugagggcaugcaggccuggaugggg 2673023RNAHomo sapiens
730aucaacagacauuaauugggcgc 2373122RNAHomo sapiens
731gcccgcguguggagccaggugu 2273222RNAHomo sapiens
732cugguacaggccugggggacag 2273323RNAHomo sapiens
733cucucaccacugcccucccacag 2373422RNAHomo sapiens
734acugcagugaaggcacuuguag 2273519RNAHomo sapiens
735aaaagcuggguugagagga 1973623RNAHomo sapiens
736uacccuguagaaccgaauuugug 2373722RNAHomo sapiens
737acuccagccccacagccucagc 2273823RNAHomo sapiens
738acuuacagacaagagccuugcuc 2373924RNAHomo sapiens
739aaagacauaggauagagucaccuc 2474022RNAHomo sapiens
740uccgucucaguuacuuuauagc 2274122RNAHomo sapiens
741acucaaaacccuucagugacuu 2274221RNAHomo sapiens
742cuccagagggaaguacuuucu 2174321RNAHomo sapiens
743aagcauucuuucauugguugg 2174421RNAHomo sapiens
744uugcucacuguucuucccuag 2174522RNAHomo sapiens
745cugggagguggauguuuacuuc 2274622RNAHomo sapiens
746cuccuacauauuagcauuaaca 2274722RNAHomo sapiens
747gcuacuucacaacaccagggcc 2274822RNAHomo sapiens
748aauccuuugucccugggugaga 2274923RNAHomo sapiens
749caacggaaucccaaaagcagcug 2375023RNAHomo sapiens
750agcagcauuguacagggcuauca 2375123RNAHomo sapiens
751aucgcugcgguugcgagcgcugu 2375221RNAHomo sapiens
752caaagcgcuucccuuuggagc 2175321RNAHomo sapiens
753uaaagugcugacagugcagau
2175422RNAHomo sapiens 754aagcccuuaccccaaaaagcau 2275518RNAHomo
sapiens 755acguuggcucugguggug 1875622RNAHomo sapiens
756ggcuacaacacaggacccgggc 2275722RNAHomo sapiens
757ucccugagacccuaacuuguga 2275822RNAHomo sapiens
758gucccucuccaaaugugucuug 2275922RNAHomo sapiens
759cuuucagucggauguuugcagc 2276022RNAHomo sapiens
760ucuacagugcacgugucuccag 2276122RNAHomo sapiens
761acucggcguggcgucggucgug 2276223RNAHomo sapiens
762cugggaucuccggggucuugguu 2376322RNAHomo sapiens
763caugccuugaguguaggaccgu 2276422RNAHomo sapiens
764caacaaaucacagucugccaua 2276522RNAHomo sapiens
765uagguaguuucauguuguuggg 2276622RNAHomo sapiens
766uuagggcccuggcuccaucucc 2276722RNAHomo sapiens
767gcugcgcuuggauuucgucccc 2276823RNAHomo sapiens
768agcuacauugucugcuggguuuc 2376923RNAHomo sapiens
769agguugggaucgguugcaaugcu 2377022RNAHomo sapiens
770ucugggcaacaaagugagaccu 2277122RNAHomo sapiens
771cucuagagggaagcacuuucuc 2277220RNAHomo sapiens
772ugagcccuguccucccgcag 2077319RNAHomo sapiens
773uggauuuuuggaucaggga 1977422RNAHomo sapiens
774uacgucaucguugucaucguca 2277522RNAHomo sapiens
775ugagaccucuggguucugagcu 2277623RNAHomo sapiens
776gaacgccuguucuugccaggugg 2377721RNAHomo sapiens
777cuucuugugcucuaggauugu 2177824RNAHomo sapiens
778uugcagcugccugggagugacuuc 2477924RNAHomo sapiens
779uucuccaaaagaaagcacuuucug 2478019RNAHomo sapiens
780aggcacggugucagcaggc 1978122RNAHomo sapiens
781aaccagcaccccaacuuuggac 2278222RNAHomo sapiens
782caaagcgcuccccuuuagaggu 2278323RNAHomo sapiens
783cacccggcugugugcacaugugc 2378421RNAHomo sapiens
784aacauagaggaaauuccacgu 2178522RNAHomo sapiens
785ccaauauuggcugugcugcucc 2278620RNAHomo sapiens
786cugcaaagggaagcccuuuc 2078723RNAHomo sapiens
787guuugcacgggugggccuugucu 2378821RNAHomo sapiens
788gugggcgggggcaggugugug 2178922RNAHomo sapiens
789aguucuucaguggcaagcuuua 2279022RNAHomo sapiens
790ucggccugaccacccaccccac 2279121RNAHomo sapiens
791agggagggacgggggcugugc 2179222RNAHomo sapiens
792cugggagaggguuguuuacucc 2279322RNAHomo sapiens
793cgucuuacccagcaguguuugg 2279421RNAHomo sapiens
794ccgucgccgccacccgagccg 2179522RNAHomo sapiens
795aggugguccguggcgcguucgc 2279620RNAHomo sapiens
796gugucugggcggacagcugc 2079722RNAHomo sapiens
797gugaaauguuuaggaccacuag 2279822RNAHomo sapiens
798uuuaacauggggguaccugcug 2279922RNAHomo sapiens
799aacccguagauccgaucuugug 2280022RNAHomo sapiens
800ugagaacugaauuccauggguu 2280121RNAHomo sapiens
801aauauuauacagucaaccucu 2180222RNAHomo sapiens
802gaaagugcuuccuuuuagaggc 2280322RNAHomo sapiens
803aaguucuguuauacacucaggc 2280423RNAHomo sapiens
804aacauucaacgcugucggugagu 2380521RNAHomo sapiens
805acagucugcugagguuggagc 2180624RNAHomo sapiens
806ucccugagacccuuuaaccuguga 2480721RNAHomo sapiens
807ucagugcaugacagaacuugg 2180822RNAHomo sapiens
808uucaccaccuucuccacccagc 2280921RNAHomo sapiens
809uucacaguggcuaaguucugc 2181022RNAHomo sapiens
810ccucuuccccuugucucuccag 2281122RNAHomo sapiens
811aaacaaacauggugcacuucuu 2281221RNAHomo sapiens
812ugagaugaagcacuguagcuc 2181322RNAHomo sapiens
813aacacaccuauucaaggauuca 2281423RNAHomo sapiens
814uggugcggagagggcccacagug 2381517RNAHomo sapiens
815ucccuguucgggcgcca 1781622RNAHomo sapiens
816ggagacgcggcccuguuggagu 2281721RNAHomo sapiens
817acucuuucccuguugcacuac 2181820RNAHomo sapiens
818ucacaccugccucgcccccc 2081922RNAHomo sapiens
819uuuccggcucgcgugggugugu 2282019RNAHomo sapiens
820gagccaguuggacaggagc 1982122RNAHomo sapiens
821ugugacugguugaccagagggg 2282221RNAHomo sapiens
822ccuggaaacacugagguugug 2182322RNAHomo sapiens
823agggacgggacgcggugcagug 2282422RNAHomo sapiens
824uacccauugcauaucggaguug 2282523RNAHomo sapiens
825cucuugagggaagcacuuucugu 2382622RNAHomo sapiens
826acuggacuuagggucagaaggc 2282721RNAHomo sapiens
827acggugcuggauguggccuuu 2182822RNAHomo sapiens
828ugcccuuaaaggugaacccagu 2282925RNAHomo sapiens
829aggggugguguugggacagcuccgu 2583017RNAHomo sapiens
830ucauauugcuucuuucu 1783122RNAHomo sapiens
831acgcccuucccccccuucuuca 2283224RNAHomo sapiens
832ugccugggucucuggccugcgcgu 2483320RNAHomo sapiens
833ucacuguucagacaggcgga 2083422RNAHomo sapiens
834cagugcaauguuaaaagggcau 2283522RNAHomo sapiens
835uuuugcaauauguuccugaaua 2283623RNAHomo sapiens
836ucuuggaguaggucauugggugg 2383722RNAHomo sapiens
837gaauguugcucggugaaccccu 2283820RNAHomo sapiens
838cugcaaagggaagcccuuuc 2083921RNAHomo sapiens
839uccucuucucccuccucccag 2184020RNAHomo sapiens
840cuuccucgucugucugcccc 2084122RNAHomo sapiens
841ccucuagauggaagcacugucu 2284222RNAHomo sapiens
842cgggguuuugagggcgagauga 2284322RNAHomo sapiens
843cuacaaagggaagcacuuucuc 2284421RNAHomo sapiens
844aguuaggauuaggucguggaa 2184522RNAHomo sapiens
845uagguuauccguguugccuucg 2284624RNAHomo sapiens
846acugggggcuuucgggcucugcgu 2484721RNAHomo sapiens
847uuggccacaauggguuagaac 2184823RNAHomo sapiens
848uuaaugcuaaucgugauaggggu 2384924RNAHomo sapiens
849acuggcuagggaaaaugauuggau 2485021RNAHomo sapiens
850gcccuccgcccgugcaccccg 2185122RNAHomo sapiens
851acggauguuugagcaugugcua 2285223RNAHomo sapiens
852cgcauccccuagggcauuggugu 2385322RNAHomo sapiens
853aagcccuuaccccaaaaaguau 2285421RNAHomo sapiens
854agggggaaaguucuauagucc 2185522RNAHomo sapiens
855cucuagagggaagcgcuuucug 2285622RNAHomo sapiens
856accacugaccguugacuguacc 2285723RNAHomo sapiens
857cccaguguuuagacuaucuguuc 2385821RNAHomo sapiens
858uucacaguggcuaaguuccgc 2185922RNAHomo sapiens
859gaaagcgcuucccuuugcugga 2286022RNAHomo sapiens
860caggauguggucaaguguuguu 2286122RNAHomo sapiens
861uauugcacuugucccggccugu 2286224RNAHomo sapiens
862gcugguuucauauggugguuuaga 2486322RNAHomo sapiens
863ucucccaacccuuguaccagug 2286423RNAHomo sapiens
864ucaagagcaauaacgaaaaaugu 2386525RNAHomo sapiens
865agggaucgcgggcggguggcggccu 2586622DNAHomo sapiens
866aactatacaacctactacctca 22
* * * * *