U.S. patent application number 17/340534 was filed with the patent office on 2022-03-31 for methods for predicting acute severe colitis treatment response.
The applicant listed for this patent is Assistance Publique-Hopitaux de Paris (APHP), CHU de Bordeaux, INSERM (Institut National de la Sante et de la Recherche Medicale, Universite de Bordeaux, Universite de Paris, Universite Paris XIII Paris-Nord. Invention is credited to Yoram BOUHNIK, David LAHARIE, Ian MORILLA, Eric OGIER-DENIS, Xavier TRETON, Mathieu UZZAN, Gilles WAINRIB.
Application Number | 20220098665 17/340534 |
Document ID | / |
Family ID | |
Filed Date | 2022-03-31 |
United States Patent
Application |
20220098665 |
Kind Code |
A1 |
OGIER-DENIS; Eric ; et
al. |
March 31, 2022 |
METHODS FOR PREDICTING ACUTE SEVERE COLITIS TREATMENT RESPONSE
Abstract
The present invention relates to methods for predicting acute
severe colitis treatment response. Currently, there is no biomarker
of drag response. The present invention provides the first
prediction tool for responses to first- and second-line treatments
in acute severe ulcerative colitis. Putative mRNA targets of
dysregulated microRNAs were identified from patient biopsies. One
classifier of fifteen colonic microRNAs plus five biological values
at admission were identified with a prediction accuracy of 96.6%
for discriminating responders from non-responders to steroids.
Using a similar method, 6 and 4 mucosal microRNA-based algorithms
were identified to classify responders from non-responders to
infliximab and cyclosporine. In particular, the present invention
relates to methods for predicting acute severe colitis treatment
response by measuring the expression levels of several miRNAs
selected front the group consisting of hp_hsa-mir-3934,
hp_hsa-mir-100, hsa-miR-718, hp_hsa-mir-193b, hsa-miR-3150a-5p,
hp_hsa-mir-1260b, hsa-miR-938, hsa-miR-518b and hsa-miR-1468.
Inventors: |
OGIER-DENIS; Eric; (Paris,
FR) ; TRETON; Xavier; (Paris, FR) ; BOUHNIK;
Yoram; (Paris, FR) ; MORILLA; Ian;
(Villetaneuse, FR) ; LAHARIE; David; (Bordeaux,
FR) ; WAINRIB; Gilles; (Paris Cedex 05, FR) ;
UZZAN; Mathieu; (Paris, FR) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
INSERM (Institut National de la Sante et de la Recherche
Medicale
Universite de Paris
Assistance Publique-Hopitaux de Paris (APHP)
Universite de Bordeaux
CHU de Bordeaux
Universite Paris XIII Paris-Nord |
Paris
Paris
Paris
Bordeaux
Talence
Villetaneuse |
|
FR
FR
FR
FR
FR
FR |
|
|
Appl. No.: |
17/340534 |
Filed: |
June 7, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16309699 |
Dec 13, 2018 |
11060147 |
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PCT/EP2017/064496 |
Jun 14, 2017 |
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17340534 |
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International
Class: |
C12Q 1/6883 20060101
C12Q001/6883; G16B 40/00 20060101 G16B040/00; C07K 16/24 20060101
C07K016/24 |
Foreign Application Data
Date |
Code |
Application Number |
Jun 14, 2016 |
EP |
16305715.1 |
Claims
1. A method of determining whether a subject suffering from acute
severe colitis (ASC) will be a responder or a non-responder to an
anti-TNF.alpha. drug, comprising the steps of i) measuring in a
mucosal tissue sample obtained from said subject before or during
the first days of anti-TNF.alpha. drug administration the
expression level of at least one miRNA selected from the group
consisting of hsa-miR-4423-3p, hsa-miR-3128, hsa-miR-3152-3p,
hp_hsa-mir-193b, hsa-miR-938 and hp_hsa-mir-100, ii) comparing the
expression level measured at step i) with a reference value, and
iii) detecting differences in the expression level between the
mucosal tissue sample and the reference value is indicative that
said subject will be a responder or a non-responder.
2. The method of claim 1 wherein the anti-TNF.alpha. drug is
infliximab
3. A method of determining whether a subject suffering from acute
severe colitis (ASC) will be a responder or a non-responder to an
anti-TNF.alpha. drug, comprising the steps of i) measuring in a
mucosal tissue sample obtained from said subject before or during
the first days of anti-TNF.alpha. drug administration the
expression level of the miRNAs selected from the group consisting
of hp_hsa-mir-100, hsa-miR-938 and hsa-miR-518b ii) comparing the
expression level measured at step i) with a reference value, and
iii) detecting differences in the expression level between the
mucosal tissue sample and the reference value is indicative that
said subject will be a responder or a non-responder.
4. The method of claim 3 wherein the anti-TNF.alpha. drug is
infliximab
Description
FIELD OF THE INVENTION
[0001] The present invention relates to methods for predicting
acute severe colitis treatment response.
BACKGROUND OF THE INVENTION
[0002] Ulcerative colitis (UC) is a lifelong, idiopathic chronic
inflammatory disorder affecting the colorectal mucosa[1].
Approximately 15 to 25% of UC patients have had at least one
episode of acute severe UC (ASUC). Such an episode is a life
threatening condition and requires surgery, as it exposes patients
to serious complications, including sepsis, toxic mega colon,
colonic perforation, digestive bleeding and thromboembolic
accidents [2, 3]. In patients who do not require emergency
colectomy, intravenous (IV) corticosteroids are recommended as the
first line of treatment [4]. However, 40% of patients will fail to
respond to IV steroids [5, 6] and will require a salvage colectomy
or second line treatment with cyclosporine (CsA) [7] or infliximab
(IFX) [8] with good efficiency and safety [9]. In patients
refractory to either of these two agents, an emergency colectomy is
recommended instead of third-line medical therapy, as delayed
surgery is associated with an increased mortality rate, estimated
to be between 2 and 3%[10]. Thus, the treatment of ASUC requires an
early assessment of the response to each medical treatment.
However, physicians' decisions regarding treatment are currently
based on the patient's evolution and a few clinical or biological
parameters, such as Oxford criteria or Ho index, having low
accuracy[11]. Then, relevant and early predictors of drug efficacy
remain to be discovered. MicroRNAs (miRNAs) are short (21-25
nucleotides), non-coding RNA molecules that are most commonly
transcribed by RNA III and processed by proteins, such as Drosha
and Dicer[12]. MiRNAs have recently emerged as important mediators
of immune development and response, suggesting their potential
efficacy as biomarkers for diagnosis, determining prognosis and/or
predicting treatment response in various diseases[13, 14]. In
inflammatory bowel disease (IBD), such as UC, several studies have
identified mucosal or blood miRNA signatures in both active and
inactive patients[15], but no signatures have been identified yet
for predicting drug response.
SUMMARY OF THE INVENTION
[0003] The present invention relates to methods for predicting
acute severe colitis treatment response. In particular, the present
invention is defined by the claims.
DETAILED DESCRIPTION OF THE INVENTION
[0004] Acute severe ulcerative colitis (ASUC) is a severe condition
managed with intravenous steroids and infliximab or cyclosporine in
the case of steroid resistance. If medical treatment fails, salvage
colectomy would be delayed, which is associated with increased
mortality. Currently, there is no biomarker of drug response; the
aim was to identify predictors of responses to first- and
second-line treatments in ASUC. Forty-seven patients with ASUC from
two tertiary French units who were well characterized for their
response to steroids, cyclosporine and infliximab were
retrospectively included. The clinical and biological parameters
were reviewed at admission. Fixed colonic biopsies taken before or
within the first 3 days of treatment were used for microRNA
expression profiling by microarray. Random forest-based
classification algorithms were used to derive candidate biomarkers
for discriminating responders from non-responders to each treatment
and were calibrated through a leave-one-out cross validation.
Putative mRNA targets of dysregulated microRNAs were identified.
One classifier of 15 colonic microRNAs plus 5 biological values
(haemoglobin, hematocrit, albumin, CRP, and transferrin expression
levels) at admission were identified with a prediction accuracy of
96.6% (AUC=0.96) for discriminating responders from non-responders
to steroids. Using a similar method, 6 and 4 mucosal microRNA-based
algorithms were identified to classify responders from
non-responders to infliximab (90%-AUC=0.86) and cyclosporine
(83%-AUC=0.81), respectively. microRNA-related mRNA target analysis
highlighted potential mucosal alterations associated with the drug
response profile in ASUC. This study identified new predictors of
responses to the first and second lines of treatment in patients
with ASUC. The present invention thus provides a method for
predicting drug response of subjects suffering from acute severe
colitis (ASC). In particular, the present invention provides
methods for predicting responses to a corticosteroid, an
anti-TNF.alpha. drug and cyclosporine.
[0005] As used herein, the term "acute severe colitis" or "ASC"
refers to acute severe colitis, a potentially lethal complication
of ulcerative colitis (UC), an idiopathic, chronic inflammatory
disorder affecting the colonic mucosa (K51-K52 such as revised in
the World Health Organisation Classification). The term "acute
severe colitis" also refers to acute severe ulcerative colitis. The
acute severe colitis activity can be measured according to the
standards recognized in the art. The acute severe colitis activity
may be measured by clinical and physical examination, Lichtiger
score and histological grading.
[0006] As used herein, the term "ASC treatment" refers to the
typical medical regimen of acute severe colitis that includes a
first line administration of a corticosteroid and a second line
administration with an anti-TNF.alpha. drug (infliximab) and/or an
immunosuppressive drug (cyclosporine).
[0007] As used herein, the term "corticosteroids" has its general
meaning in the art and refers the first line ASC treatment or first
line ASC therapy. The term "corticosteroids" refers to first line
administration of corticosteroids, the class of active ingredients
having a hydrogenated cyclopentoperhydrophenanthrene ring system
endowed with anti-inflammatory activity. Corticosteroid drugs
typically include cortisone, hydrocortisone, methylprednisolone,
prednisone, prednisolone, betamethesone, beclomethasone
dipropionate, budesonide, dexamethasone sodium phosphate,
flunisolide, fluticasone propionate, triamcinolone acetonide,
betamethasone, fluocinolone, fluocinonide, betamethasone
dipropionate, betamethasone valerate, desonide, desoximetasone,
fluocinolone, triamcinolone, triamcinolone acetonide, clobetasol
propionate and dexamethasone.
[0008] As used herein, the term "anti-TNF.alpha. drug" is intended
to encompass agents including proteins, antibodies, antibody
fragments, fusion proteins (e.g., Ig fusion proteins or Fc fusion
proteins), multivalent binding proteins (e.g., DVD Ig), small
molecule TNF.alpha. antagonists and similar naturally- or
non-naturally-occurring molecules, and/or recombinant and/or
engineered forms thereof, that, directly or indirectly, inhibit
TNF.alpha. activity, such as by inhibiting interaction of
TNF.alpha. with a cell surface receptor for TNF.alpha., inhibiting
TNF.alpha. protein production, inhibiting TNF.alpha. gene
expression, inhibiting TNF.alpha. secretion from cells, inhibiting
TNF.alpha. receptor signalling or any other means resulting in
decreased TNF.alpha. activity in a subject. The term
"anti-TNF.alpha. drug" preferably includes agents which interfere
with TNF.alpha. activity. Examples of anti-TNF.alpha. drugs
include, without limitation, infliximab (REMICADE.TM., Johnson and
Johnson), human anti-TNF monoclonal antibody adalimumab
(D2E7/HUMIRA.TM., Abbott Laboratories), etanercept (ENBREL.TM.,
Amgen), certolizumab pegol (CIMZIA.RTM., UCB, Inc.), golimumab
(SIMPON1.RTM.; CNTO 148), CDP 571 (Celltech), CDP 870 (Celltech),
as well as other compounds which inhibit TNF.alpha. activity, such
that when administered to a subject in which TNF.alpha. activity is
detrimental, the disorder (i.e. acute severe colitis) could be
treated.
[0009] As used herein, the term "cyclosporine" has its general
meaning in the art and refers to an immunosuppressive drug.
Cyclosporine (also named "cyclosporine A" or "CyA" was the
cornerstone of rescue medical therapy for steroid-refractory acute
severe colitis until the advent of anti-TNF agents. CyA is a
competitive calcinuerin inhibitor with potent immunosuppressive
properties.
[0010] As used herein, the term "responder" refers to an acute
severe colitis (ASC) subject that will respond to ASC treatment. In
a further aspect, the term "responder" refers to an acute severe
colitis (ASC) subject that will respond to first line ASC treatment
with corticosteroids. In a further aspect, the term "responder"
refers to an acute severe colitis (ASC) subject that will respond
to second line ASC treatment with anti-TNF.alpha. drug. In a
further aspect, the term "responder" refers to an acute severe
colitis (ASC) subject that will respond to second line ASC
treatment with cyclosporine. In a further aspect, the term
"responder" refers to an acute severe colitis (ASC) subject that
will respond to second line ASC treatment with anti-TNF.alpha. drug
and cyclosporine. The acute severe colitis activity can be measured
according to the standards recognized in the art. The acute severe
colitis activity may be measured by clinical and physical
examination, Lichtiger score, histological grading and
progression-free survival or overall survival. A "responder" or
"responsive" subject to an acute severe colitis (ASC) treatment
refers to a subject who shows or will show a clinically significant
relief in the disease when treated with acute severe colitis (ASC)
treatment.
[0011] The first object of the present invention ("object n.degree.
1") relates to a method of determining whether a subject suffering
from acute severe colitis (ASC) will be a responder or a
non-responder to a corticosteroid, comprising the steps of i)
measuring in a mucosal tissue sample obtained from said subject
before or during the first day of corticosteroid administration the
expression level of at least one miRNA selected from the group
consisting of hp_hsa-mir-3934, hp_hsa-mir-3667, hp_hsa-mir-100,
hsa-miR-603, hsa-miR-718, hsa-miR-4259, hp_hsa-mir-193b,
hsa-miR-3150a-5p, hp_hsa-mir-1260b, hsa-miR-938, hsa-miR-3128,
hsa-miR-4423-3p, hsa-miR-518b, hsa-miR-1468 and hsa-miR-3152-3p,
ii) comparing the expression level measured at step i) with a
reference value, and iii) detecting differences in the expression
level between the mucosal tissue sample and the reference value is
indicative that said subject will be a responder or a
non-responder.
[0012] In some embodiments, the expression level of 1, 2, 3, 4, 5,
6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 miRNA selected from the group
consisting of hp_hsa-mir-3934, hp_hsa-mir-3667, hp_hsa-mir-100,
hsa-miR-603, hsa-miR-718, hsa-miR-4259, hp_hsa-mir-193b,
hsa-miR-3150a-5p, hp_hsa-mir-1260b, hsa-miR-938, hsa-miR-3128,
hsa-miR-4423-3p, hsa-miR-518b, hsa-miR-1468 and hsa-miR-3152-3p is
determined. In some embodiments, the expression levels of
hp_hsa-mir-3934, hp_hsa-mir-3667, hp_hsa-mir-100, hsa-miR-603,
hsa-miR-718, hsa-miR-4259, hp_hsa-mir-193b, hsa-miR-3150a-5p,
hp_hsa-mir-1260b, hsa-miR-938, hsa-miR-3128, hsa-miR-4423-3p,
hsa-miR-518b, hsa-miR-1468 and hsa-miR-3152-3p are measured.
[0013] In some embodiments, the expressions levels of 9 miRNA are
measured. Said 9 miRNA are hp_hsa-mir-3934, hp_hsa-mir-100,
hsa-miR-718, hp_hsa-mir-193b, hsa-miR-3150a-5p, hp_hsa-mir-1260b,
hsa-miR-938, hsa-miR-518b and hsa-miR-1468.
[0014] The second object of the present invention ("object
n.degree. 2") relates to a method of determining whether a subject
suffering from acute severe colitis (ASC) will be a responder or a
non-responder to an anti-TNF.alpha. drug, comprising the steps of
(i) measuring in a mucosal tissue sample obtained from said subject
before or during the first days of anti-TNF.alpha. drug
administration the expression level of at least one miRNA selected
from the group consisting of hsa-miR-4423-3p, hsa-miR-3128,
hsa-miR-3152-3p, hp_hsa-mir-193b, hsa-miR-938 and hphsa-mir-100,
(ii) comparing the expression level measured at step i) with a
reference value, and (iii) detecting differences in the expression
level between the mucosal tissue sample and the reference value is
indicative that said subject will be a responder or a
non-responder.
[0015] In some embodiments, the expression level of 1, 2, 3, 4, 5
or 6 miRNA selected from the group consisting of hsa-miR-4423-3p,
hsa-miR-3128, hsa-miR-3152-3p, hp_hsa-mir-193b, hsa-miR-938 and
hp_hsa-mir-100 is determined. In some embodiments, the expression
levels of hsa-miR-4423-3p, hsa-miR-3128, hsa-miR-3152-3p,
hp_hsa-mir-193b, hsa-miR-938 and hp_hsa-mir-100 are determined.
[0016] In some embodiments, the expressions levels of 3 miRNA are
measured. Said 3 miRNA are hp_hsa-mir-100, hsa-miR-938 and
hsa-miR-518b.
[0017] The third object of the present invention ("object n.degree.
3") relates to a method of determining whether a subject suffering
from acute severe colitis (ASC) will be a responder or a
non-responder to cyclosporine, comprising the steps of i) measuring
in a mucosal tissue sample obtained from said subject before or
during the first days of cyclosporine administration the expression
level of at least one miRNA selected from the group consisting of
has-miR-4423-3p, has-miR-938, has-miR-518b and has-miR-100, ii)
comparing the expression level measured at step i) with a reference
value, and iii) detecting differences in the expression level
between the mucosal tissue sample and the reference value is
indicative that said subject will be a responder or a
non-responder.
[0018] In some embodiments, the expression level of 1, 2, 3 or 4
miRNA selected from the group consisting of hsa-miR-4423-3p,
hsa-miR-938, hsa-miR-518b and hsa-miR-100 is determined. In some
embodiments, the expression levels of hsa-miR-4423-3p, hsa-miR-938,
hsa-miR-518b and hsa-miR-100 are measured.
[0019] In some embodiments, the expressions levels of 3 miRNA are
measured. Said 3 miRNA are hp_hsa-mir-100, hsa-miR-938 and
hp_hsa-mir-193b.
[0020] The fourth object of the present invention ("object
n.degree. 4") relates to a method of determining whether a subject
suffering from acute severe colitis (ASC) will be a responder or a
non-responder to a corticosteroid, anti-TNF.alpha. drug and
cyclosporinc by performing the methods of object 1, 2 and 3 as
above described. In some embodiments, the methods of determining
whether a subject suffering from acute severe colitis (ASC) will be
a responder or a non-responder to a corticosteroid, anti-TNF.alpha.
drug and cyclosporine are performed sequentially or
concomitantly.
[0021] In some embodiments, the expressions levels of 9 miRNA are
measured. Said 9 miRNA are hp_hsa-mir-3934, hp_hsa-mir-100,
hsa-miR-718, hp_hsa-mir-193b, hsa-miR-3150a-5p, hp_hsa-mir-1260b,
hsa-miR-938, hsa-miR-518b and hsa-miR-1468.
[0022] In some embodiments, the method of the invention comprises a
step consisting of comparing the expression level of the miRNA with
a reference value, wherein detecting differences in the expression
level of the miRNA between the mucosal tissue sample and the
reference value is indicative that said subject will be a responder
or a non-responder.
[0023] A reference value is determined for each miRNA. Typically,
the reference value can be a threshold value or a cut-off value.
Typically, a "threshold value" or "cut-off value" can be determined
experimentally, empirically, or theoretically. A threshold value
can also be arbitrarily selected based upon the existing
experimental and/or clinical conditions, as would be recognized by
a person of ordinary skill in the art. The threshold value has to
be determined in order to obtain the optimal sensitivity and
specificity according to the function of the test and the
benefit/risk balance (clinical consequences of false positive and
false negative). Typically, the optimal sensitivity and specificity
(and so the threshold value) can be determined using a Receiver
Operating Characteristic (ROC) curve based on experimental data.
Preferably, the person skilled in the art may compare the miRNAs
expression levels (obtained according to the method of the
invention with a defined threshold value). In one embodiment of the
present invention, the threshold value is derived from the miRNA
expression level (or ratio, or score) determined in a mucosal
tissue sample derived from one or more subjects who are responders
to a corticosteroid, anti-TNF.alpha. drug or cyclosporine. In one
embodiment of the present invention, the threshold value may also
be derived from the miRNA expression level (or ratio, or score)
determined in a mucosal tissue sample derived from one or more
subjects who are non-responders to a corticosteroid,
anti-TNF.alpha. drug or cyclosporine. Furthermore, retrospective
measurement of the miRNA expression levels (or ratio, or scores) in
properly banked historical subject samples may be used in
establishing these threshold values.
[0024] In some embodiments, the reference value may be determined
by carrying out a method comprising the steps of a) providing a
collection of mucosal tissue samples obtained from subjects before
or during the first days of the corticosteroid treatment, b)
providing, for each sample provided at step a), information
relating to the actual clinical outcome (response or no response);
c) providing a series of arbitrary quantification values; d)
determining the level of the miRNA for each sample contained in the
collection provided at step a); e) classifying said samples in two
groups for one specific arbitrary quantification value provided at
step c), respectively: (i) a first group comprising samples that
exhibit a quantification value for the level that is lower than the
said arbitrary quantification value contained in the said series of
quantification values; (ii) a second group comprising samples that
exhibit a quantification value for said level that is higher than
the said arbitrary quantification value contained in the said
series of quantification values; whereby two groups of samples are
obtained for the said specific quantification value, wherein the
samples of each group are separately enumerated; calculating the
statistical significance between (i) the quantification value
obtained at step e) and (ii) the actual clinical outcome of the
subjects (i.e. response or non-response) from which samples
contained in the first and second groups defined at step f) derive;
g) reiterating steps f) and g) until every arbitrary quantification
value provided at step d) is tested; and h) setting the said
reference value as consisting of the arbitrary quantification value
for which the highest statistical significance (most significant)
has been calculated at step g).
[0025] For example, the level of the miRNA has been assessed for
100 samples of 100 subjects. The 100 samples are ranked according
to the level of the miRNA. Sample 1 has the highest level and
sample 100 has the lowest level. A first grouping provides two
subsets: on one side sample
[0026] Nr 1 and on the other side the 99 other samples. The next
grouping provides on one side samples 1 and 2 and on the other side
the 98 remaining samples etc., until the last grouping: on one side
samples 1 to 99 and on the other side sample Nr 100. According to
the information relating to the actual clinical outcome for the
corresponding subjects, the p value between both subsets was
calculated. The reference value is then selected such as the
discrimination based on the criterion of the minimum p value is the
strongest. In other terms, the level of the miRNA corresponding to
the boundary between both subsets for which the p value is minimum
is considered as the reference value. It should be noted that the
reference value is not necessarily the median value of levels of
the miRNA. The setting of a single "cut-off" value thus allows
discrimination between responder or non-responder. Practically,
high statistical significance values (e.g. low P values) are
generally obtained for a range of successive arbitrary
quantification values, and not only for a single arbitrary
quantification value. Thus, in one alternative embodiment of the
invention, instead of using a definite reference value, a range of
values is provided. Therefore, a minimal statistical significance
value (minimal threshold of significance, e.g. maximal threshold P
value) is arbitrarily set and a range of a plurality of arbitrary
quantification values for which the statistical significance value
calculated at step g) is higher (more significant, e.g. lower P
value) are retained, so that a range of quantification values is
provided. This range of quantification values includes a "cut-off"
value as described above. For example, on a hypothetical scale of 1
to 10, if the ideal cut-off value (the value with the highest
statistical significance) is 5, a suitable (exemplary) range may be
from 4-6. Therefore, a subject may be assessed by comparing values
obtained by measuring the level of the miRNA, where values greater
than 5 reveal that the subject will be a responder (or
alternatively a non-responder) and values less than 5 reveal that
the subject will be a non-responder (or alternatively a responder).
In another embodiment, a subject may be assessed by comparing
values obtained by measuring the level of the miRNA and comparing
the values on a scale, where values above the range of 4-6 indicate
that the subject will be a responder (or alternatively a
non-responder) and values below the range of 4-6 indicate that the
subject will be a non-responder (or alternatively a non-responder),
with values falling within the range of 4-6 indicating an
intermediate response.
[0027] In some embodiments, a score which is a composite of the
expression levels of the different miRNAs may also be determined
and compared to a reference value wherein a difference between said
score and said reference value is indicative whether said subject
is a responder or a non-responder to corticosteroid, anti-TNFu drug
or cyclosporine treatment.
[0028] In some embodiments, the method of the invention comprises
the step of determining the subject response using a classification
algorithm selected from Linear Discriminant Analysis (LDA),
Topological Data Analysis (TDA), Neural Networks and Random Forests
algorithm (RF) such as described in the Example. In some
embodiments, the method of the invention comprises the step of
determining the subject response using a classification algorithm
wherein the classification algorithm is Deep learning
classification. As used herein, the term "classification algorithm"
has its general meaning in the art and refers to classification and
regression tree methods and multivariate classification well known
in the art such as described in U.S. Pat. No. 8,126,690;
WO2008/156617. As used herein, the term "Random Forests algorithm"
or "RF" has its general meaning in the art and refers to
classification algorithm such as described in U.S. Pat. No.
8,126,690; WO2008/156617. Random Forest is a decision-tree-based
classifier that is constructed using an algorithm originally
developed by Leo Breiman (Breiman L, "Random forests," Machine
Learning 2001, 45:5-32). The classifier uses a large number of
individual decision trees and decides the class by choosing the
mode of the classes as determined by the individual trees. The
individual trees are constructed using the following algorithm: (1)
Assume that the number of cases in the training set is N, and that
the number of variables in the classifier is M; (2) Select the
number of input variables that will be used to determine the
decision at a node of the tree; this number, m should be much less
than M; (3) Choose a training set by choosing N samples from the
training set with replacement; (4) For each node of the tree
randomly select m of the M variables on which to base the decision
at that node; (5) Calculate the best split based on these m
variables in the training set. In some embodiments, the score is
generated by a computer program.
[0029] In some embodiments, a higher expression level of at least
one miRNA selected from the group consisting of hsa-miR-4423-3p,
hsa-miR-3128, hsa-miR-3152-3p and hsa-miR-603 and a lower
expression level of at least one miRNA selected from the group
consisting of hsa-miR-718,hsa-miR-4259, hp_hsa-mir-193b,
hp_hsa-mir-3934, hp_hsa-mir-3667, hp_hsa-mir-1260b, hsa-miR-938,
hsa-miR-3150a-5p, hp_hsa-mir-100, hsa-miR-518b and hsa-miR-1468 are
indicative that the subject will be a responder to corticosteroid
treatment, and accordingly a lower expression level of at least one
miRNA selected from the group consisting of hsa-miR-4423-3p,
hsa-miR-3128, hsa-miR-3152-3p and hsa-miR-603 and a higher
expression level of at least one miRNA selected from the group
consisting of hsa-miR-718, hsa-miR-4259, hp_hsa-mir-193b,
hp_hsa-mir-3934, hp_hsa-mir-3667, hp_hsa-mir-1260b, hsa-miR-938,
hsa-miR-3150a-5p, hp_hsa-mir-100, hsa-miR-518b and hsa-miR-1468 are
indicative that the subject will be a non-responder to
corticosteroid treatment.
[0030] In some embodiments, the reference value may correspond to
the expression level determined in a mucosal tissue sample derived
from one or more subjects who are responders to corticosteroid
treatment. Accordingly, when the expression level determined for at
least one miRNA selected from the group consisting of
hsa-miR-4423-3p, hsa-miR-3128, hsa-miR-3152-3p and hsa-miR-603 is
equal or higher than the corresponding reference value and/or the
expression level of at least one miRNA selected from the group
consisting of hsa-miR-718, hsa-miR-4259, hp_hsa-mir-193b,
hp_hsa-mir-3934, hp_hsa-mir-3667, hp hsa-mir-1260b, hsa-miR-938,
hsa-miR-3150a-5p, hp_hsa-mir-100, hsa-miR-518b and hsa-miR-1468 is
equal or lower than the corresponding reference value, it is
concluded that the subject will be a responder to corticosteroid
treatment, and accordingly, when the expression level determined
for at least one miRNA selected from the group consisting of
hsa-miR-4423-3p, hsa-miR-3128, hsa-miR-3152-3p and hsa-miR-603 is
lower than the corresponding reference value and/or the expression
level of at least one miRNA selected from the group consisting of
hsa-miR-718, hsa-miR-4259, hp_hsa-mir-193b, hp_hsa-mir-3934,
hp_hsa-mir-3667, hp_hsa-mir-1260b, hsa-miR-938, hsa-miR-3150a-5p,
hp_hsa-mir-100, hsa-miR-518b and hsa-miR-1468 is higher than the
corresponding reference value, its concluded that the subject will
be a non-responder to corticosteroid treatment.
[0031] In some embodiments, the reference value may correspond to
the expression level determined in a mucosal tissue sample derived
from one or more subjects who are non-responders to corticosteroid
treatment. Accordingly, when the expression level determined for at
least one miRNA selected from the group consisting of
hsa-miR-4423-3p, hsa-miR-3128, hsa-miR-3152-3p and hsa-miR-603 is
higher than the corresponding reference value and/or the expression
level of at least one miRNA selected from the group consisting of
hsa-miR-718, hsa-miR-4259, hp_hsa-mir-193b, hp_hsa-mir-3934,
hp_hsa-mir-3667, hp_hsa-mir-1260b, hsa-miR-938, hsa-miR-3150a-5p,
hp_hsa-mir-100, hsa-miR-518b and hsa-miR-1468 is lower than the
corresponding reference value, it is concluded that the subject
will be a responder to corticosteroid treatment, and accordingly,
when the expression level determined for at least one miRNA
selected from the group consisting of hsa-miR-4423-3p,
hsa-miR-3128, hsa-miR-3152-3p and hsa-miR-603 is equal or lower
than the corresponding reference value and/or the expression level
of at least one miRNA selected from the group consisting of
hsa-miR-718, hsa-miR-4259, hp_hsa-mir-193b, hp_hsa-mir-3934,
hp_hsa-mir-3667, hp_hsa-mir-1260b, hsa-miR-938, hsa-miR-3150a-5p,
hp_hsa-mir-100, hsa-miR-518b and hsa-miR-1468 is equal or higher
than the corresponding reference value, its concluded that the
subject will be a non-responder to corticosteroid treatment.
[0032] In some embodiments, a higher expression level of at least
one miRNA selected from the group consisting of hsa-miR-4423-3p,
hsa-miR-3128 and hsa-miR-3152-3p and a lower expression level of at
least one miRNA selected from the group consisting of
hp_hsa-mir-193b, hsa-miR-938 and hp_hsa-mir-100 are indicative that
the subject will be a responder to anti-TNF.alpha. drug treatment,
and accordingly a lower expression level of at least one miRNA
selected from the group consisting of hsa-miR-4423-3p, hsa-miR-3128
and hsa-miR-3152-3p and a higher expression level of at least one
miRNA selected from the group consisting of hp_hsa-mir-193b,
hsa-miR-938 and hp_hsa-mir-100 are indicative that the subject will
be a non-responder to anti-TNF.alpha. drug treatment.
[0033] In some embodiments, the reference value may correspond to
the expression level determined in a mucosal tissue sample derived
from one or more subjects who are responders to anti-TNF.alpha.
drug treatment. Accordingly, when the expression level determined
for at least one miRNA selected from the group consisting of
hsa-miR-4423-3p, hsa-miR-3128, and hsa-miR-3152-3p is equal or
higher than the corresponding reference value and/or the expression
level of at least one miRNA selected from the group consisting of
hp_hsa-mir-193b, hsa-miR-938 and hp_hsa-mir-100 is equal or lower
than the corresponding reference value, it is concluded that the
subject will be a responder to anti-TNF.alpha. drug treatment, and
accordingly, when the expression level determined for at least one
miRNA selected from the group consisting of hsa-miR-4423-3p,
hsa-miR-3128, and hsa-miR-3152-3p is lower than the corresponding
reference value and/or the expression level of at least one miRNA
selected from the group consisting of hp_hsa-mir-193b, hsa-miR-938
and hp_hsa-mir-100 is higher than the corresponding reference
value, its concluded that the subject will be a non-responder to
anti-TNF.alpha. drug treatment.
[0034] In some embodiments, the reference value may correspond to
the expression level determined in a mucosal tissue sample derived
from one or more subjects who are non-responders to anti-TNF.alpha.
drug treatment. Accordingly, when the expression level determined
for at least one miRNA selected from the group consisting of
hsa-miR-4423-3p, hsa-miR-3128, and hsa-miR-3152-3p is higher than
the corresponding reference value and/or the expression level of at
least one miRNA selected from the group consisting of
hp_hsa-mir-193b, hsa-miR-938 and hp_hsa-mir-100 is lower than the
corresponding reference value, it is concluded that the subject
will be a responder to anti-TNF.alpha. drug treatment, and
accordingly, when the expression level determined for at least one
miRNA selected from the group consisting of hsa-miR-4423-3p,
hsa-miR-3128, and hsa-miR-3152-3p is equal or lower than the
corresponding reference value and/or the expression level of at
least one miRNA selected from the group consisting of
hp_hsa-mir-193b, hsa-miR-938 and hp_hsa-mir-100 is equal or higher
than the corresponding reference value, its concluded that the
subject will be a non-responder to anti-TNF.alpha. drug
treatment.
[0035] In some embodiments, a higher expression level of
miR-4423-3p and a lower expression level of at least one miRNA
selected from the group consisting of hsa-miR-938, hsa-miR-518b and
hsa-miR-100 are indicative that the subject will be a responder to
cyclosporine treatment, and accordingly lower expression level of
miR-4423-3p and higher expression level of at least one miRNA
selected from the group consisting of hsa-miR-938, hsa-miR-518b and
hsa-miR-100 are indicative that the subject will be a non-responder
to cyclosporine treatment.
[0036] In some embodiments, the reference value may correspond to
the expression level determined in a mucosal tissue sample derived
from one or more subjects who are responders to cyclosporine
treatment. Accordingly, when the expression level determined for
miR-4423-3p is equal or higher than the corresponding reference
value and/or the expression level of at least one miRNA selected
from the group consisting of hsa-miR-938, hsa-miR-518b and
hsa-miR-100 is equal or lower than the corresponding reference
value, it is concluded that the subject will be a responder to
cyclosporine treatment, and accordingly, when the expression level
determined for hsa-miR-4423-3p is lower than the corresponding
reference value and/or the expression level of at least one miRNA
selected from the group consisting of hsa-miR-938, hsa-miR-518b and
hsa-miR-100 is higher than the corresponding reference value, its
concluded that the subject will be a non-responder to cyclosporine
treatment.
[0037] In some embodiments, the reference value may correspond to
the expression level determined in a mucosal tissue sample derived
from one or more subjects who are non-responders to cyclosporine
treatment. Accordingly, when the expression level determined for
has-hsa-miR-4423-3p is higher than the corresponding reference
value and/or the expression level of at least one miRNA selected
from the group consisting of hsa-miR-938, hsa-miR-518b and
hsa-miR-100 is lower than the corresponding reference value, it is
concluded that the subject will be a responder to cyclosporine
treatment, and accordingly, when the expression level determined
for hsa-miR-4423-3p is equal or lower than the corresponding
reference value and/or the expression level of at least one miRNA
selected from the group consisting of hsa-miR-938, hsa-miR-518b and
hsa-miR-100 is equal or higher than the corresponding reference
value, its concluded that the subject will be a non-responder to
cyclosporine treatment.
[0038] In some embodiments, the methods of the invention further
comprises measuring at least one biological value selected from the
group consisting of leukocyte, hematite, basophil and lymphocyte
count, hematocrit, haemoglobin, glucose, ferritin, albumin, iron,
C-reactive protein (CRP) and transferrin.
[0039] As used herein, the term "mucosal tissue sample" means any
sample derived from the colon of the subject, which comprise
mucosal cells. Said mucosal tissue sample may be obtained before or
during the first day of the first line treatment with
corticosteroids. Said mucosal tissue sample is obtained for the
purpose of in vitro evaluation. In a particular embodiment the
mucosal tissue sample results from an endoscopic biopsy performed
in the colon of the subject. Said endoscopic biopsy may be taken
from various areas of the colon. In another particular embodiment,
the mucosal tissue sample may be isolated from inflamed mucosa of
the subject's colon.
[0040] As used herein, the term "miR" has its general meaning in
the art and refers to the miRNA sequence publicly available from
the data base http://microrna.sanger.ac.uk/sequences/ under the
miRBase Accession number. The miRNAs pertaining to the invention
are known per se, and are listed in the below Table A.
TABLE-US-00001 TABLE A list of the miRNAs biomarkers according to
the invention miRNA miRBase Accession number hp_hsa-mir-3934
MI0016590 hp_hsa-mir-3667 MI0016068 hp_hsa-mir-100 MI0000102
hsa-miR-603 MI0003616 hsa-miR-718 MI0012489 hsa-miR-4259 MI0015858
hp_hsa-mir-193b MI0003137 hsa-miR-3150a-5p MIMAT9619206
hp_hsa-mir-1260b MI0014197 hsa-miR-938 MI0005760 hsa-miR-3128
MI0014145 hsa-miR-4423-3p MIMAT0018936 hsa-miR-518b MI0003156
hsa-miR-1468 MI0003782 hsa-miR-3152-3p MIMAT0015025 hsa-miR-3128
M10014145 hplisa-mir-193b MI0003137 hsa-miR-4423-3p
MIMAT0018936
Table A: List of the miRNAs Biomarkers According to the
Invention
[0041] According to the invention, measuring the expression level
of the miRNA selected from the group consisting of miRNAs of Table
A of the invention in the mucosal tissue sample obtained from the
subject can be performed by a variety of techniques. For example
the nucleic acid contained in the samples (mucosal tissue prepared
from the subject) is first extracted according to standard methods,
for example using lytic enzymes or chemical solutions or extracted
by nucleic-acid-binding resins following the manufacturer's
instructions. Conventional methods and reagents for isolating RNA
from a mucosal tissue sample comprise High Pure miRNA Isolation Kit
(Roche), Trizol (Invitrogen), Guanidinium
thiocyanate-phenol-chloroform extraction, PureLink.TM. miRNA
isolation kit (Invitrogen), PureLink Micro-to-Midi Total RNA
Purification System (invitrogen), RNeasy kit (Qiagen), miRNeasy kit
(Qiagen), Oligotex kit (Qiagen), phenol extraction,
phenol-chloroform extraction, TCA/acetone precipitation, ethanol
precipitation, Column purification, Silica gel membrane
purification, PureYield.TM. RNA Midiprep (Promega), PolyATtract
System 1000 (Promega), Maxwell.RTM. 16 System (Promega), SV Total
RNA Isolation (Promega), geneMAG-RNA/DNA kit (Chemicell), TRI
Reagent (Ambion), RNAqueous Kit (Ambion), ToTALLY RNA.TM. Kit
(Ambion), Poly(A)Purist.TM. Kit (Ambion) and any other methods,
commercially available or not, known to the skilled person. The
expression level of one or more miRNA in the mucosal tissue sample
may be determined by any suitable method. Any reliable method for
measuring the level or amount of miRNA in a sample may be used.
Generally, miRNA can be detected and quantified from a mucosal
tissue sample (including fractions thereof), such as samples of
isolated RNA by various methods known for mRNA, including, for
example, amplification-based methods (e.g., Polymerase Chain
Reaction (PCR), Real-Time Polymerase Chain Reaction (RT-PCR),
Quantitative Polymerase Chain Reaction (qPCR), rolling circle
amplification, etc.), hybridization-based methods (e.g.,
hybridization arrays (e.g., microarrays), NanoString analysis,
Northern Blot analysis, branched DNA (bDNA) signal amplification,
in situ hybridization, etc.), and sequencing-based methods (e.g.,
next-generation sequencing methods, for example, using the illumina
or IonTorrent platforms). Other exemplary techniques include
ribonuclease protection assay (RPA) and mass spectroscopy.
[0042] In some embodiments, RNA is converted to DNA (cDNA) prior to
analysis. cDNA can be generated by reverse transcription of
isolated miRNA using conventional techniques. miRNA reverse
transcription kits are known and commercially available. Examples
of suitable kits include, but are not limited to the mirVana
TaqMan.RTM. miRNA transcription kit (Ambion, Austin, Tex.), and the
TaqMan.RTM. miRNA transcription kit (Applied Biosystems, Foster
City, Calif.). Universal primers, or specific primers, including
miRNA-specific stem-loop primers, are known and commercially
available, for example, from Applied Biosystems. In some
embodiments, miRNA is amplified prior to measurement. In some
embodiments, the expression level of miRNA is measured during the
amplification process. In some embodiments, the expression level of
miRNA is not amplified prior to measurement. Some exemplary methods
suitable for determining the expression level of miRNA in a sample
are described in greater hereinafter. These methods are provided by
way of illustration only, and it will be apparent to a skilled
person that other suitable methods may likewise be used.
[0043] Many amplification-based methods exist for detecting the
expression level of miRNA nucleic acid sequences, including, but
not limited to, PCR, RT-PCR, qPCR, and rolling circle
amplification. Other amplification-based techniques include, for
example, ligase chain reaction (LCR), multiplex ligatable probe
amplification, in vitro transcription (IVT), strand displacement
amplification (SDA), transcription-mediated amplification (TMA),
nucleic acid sequence based amplification (NASBA), RNA (Eberwine)
amplification, and other methods that are known to persons skilled
in the art. A typical PCR reaction includes multiple steps, or
cycles, that selectively amplify target nucleic acid species: a
denaturing step, in which a target nucleic acid is denatured; an
annealing step, in which a set of PCR primers (i.e., forward and
reverse primers) anneal to complementary DNA strands, and an
elongation step, in which a thermostable DNA polymerase elongates
the primers. By repeating these steps multiple times, a DNA
fragment is amplified to produce an amplicon, corresponding to the
target sequence. Typical PCR reactions include 20 or more cycles of
denaturation, annealing, and elongation. In many cases, the
annealing and elongation steps can be performed concurrently, in
which case the cycle contains only two steps. A reverse
transcription reaction (which produces a cDNA sequence having
complementarity to a miRNA) may be performed prior to PCR
amplification. Reverse transcription reactions include the use of,
e.g., a RNA-based DNA polymerase (reverse transcriptase) and a
primer. Kits for quantitative real time PCR of miRNA are known, and
are commercially available. Examples of suitable kits include, but
are not limited to, the TaqMan.RTM. miRNA Assay (Applied
Biosystems) and the mirVana.TM. qRT-PCR miRNA detection kit
(Ambion). The miRNA can be ligated to a single stranded
oligonucleotide containing universal primer sequences, a
polyadenylated sequence, or adaptor sequence prior to reverse
transcriptase and amplified using a primer complementary to the
universal primer sequence, poly(T) primer, or primer comprising a
sequence that is complementary to the adaptor sequence. In some
embodiments, custom qRT-PCR assays can be developed for
determination of miRNA levels. Custom qRT-PCR assays to measure
miRNAs in a sample can be developed using, for example, methods
that involve an extended reverse transcription primer and locked
nucleic acid modified PCR. Custom miRNA assays can be tested by
running the assay on a dilution series of chemically synthesized
miRNA corresponding to the target sequence. This permits
determination of the limit of detection and linear range of
quantitation of each assay. Furthermore, when used as a standard
curve, these data permit an estimate of the absolute abundance of
miRNAs measured in the samples. Amplification curves may optionally
be checked to verify that Ct values are assessed in the linear
range of each amplification plot. Typically, the linear range spans
several orders of magnitude. For each candidate miRNA assayed, a
chemically synthesized version of the miRNA can be obtained and
analyzed in a dilution series to determine the limit of sensitivity
of the assay, and the linear range of quantitation. Relative
expression levels may be determined, for example, according to the
2(-.DELTA..DELTA. C(T)) Method, as described by Livak et ah,
Analysis of relative gene expression data using real-time
quantitative PCR and the 2(-.DELTA..DELTA. C(T)) Method. Methods
(2001) Dec;25(4):402-8.
[0044] In some embodiments, two or more miRNAs are amplified in a
single reaction volume. For example, multiplex q-PCR, such as
qRT-PCR, enables simultaneous amplification and quantification of
at least two miRNAs of interest in one reaction volume by using
more than one pair of primers and/or more than one probe. The
primer pairs comprise at least one amplification primer that
specifically binds each miRNA, and the probes are labeled such that
they are distinguishable from one another, thus allowing
simultaneous quantification of multiple miRNAs.
[0045] Rolling circle amplification is a DNA-polymerase driven
reaction that can replicate circularized oligonucleotide probes
with either linear or geometric kinetics under isothermal
conditions (see, for example, Lizardi et al., Nat. Gen. (1998)
19(3):225-232; Gusev et al, Am. J. Pathol. (2001) 159(1):63-69;
Nallur et al, Nucleic Acids Res. (2001) 29(23):E118). In the
presence of two primers, one hybridizing to the (+) strand of DNA,
and the other hybridizing to the (-) strand, a complex pattern of
strand displacement results in the generation of over 109 copies of
each DNA molecule in 90 minutes or less. Tandemly linked copies of
a closed circle DNA molecule may be formed by using a single
primer. The process can also be performed using a matrix-associated
DNA. The template used for rolling circle amplification may be
reverse transcribed. This method can be used as a highly sensitive
indicator of miRNA sequence and expression level at very low miRNA
concentrations (see, for example, Cheng et al., Angew Chem. Int.
Ed. Engl. (2009) 48(18):3268-72; Neubacher et al, Chembiochem.
(2009) 10(8): 1289-91).
[0046] miRNA quantification may be performed by using stem-loop
primers for reverse transcription (RT) followed by a real-time
TaqMan.RTM. probe. Typically, said method comprises a first step
wherein the stem-loop primers are annealed to miRNA targets and
extended in the presence of reverse transcriptase. Then
miRNA-specific forward primer, TaqMan.RTM. probe, and reverse
primer are used for PCR reactions. Quantitation of miRNAs is
estimated based on measured CT values. Many miRNA quantification
assays are commercially available from Qiagen (S. A. Courtaboeuf,
France), Exiqon (Vedbaek, Denmark) or Applied Biosystems (Foster
City, USA).
[0047] Expression levels of miRNAs may be expressed as absolute
expression levels or normalized expression levels. Typically,
expression levels are normalized by correcting the absolute
expression level of miRNAs by comparing its expression to the
expression of a mRNA that is not a relevant marker for determining
whether a subject suffering from acute severe colitis (ASC) will be
a responder or a non-responder to a corticosteroid, anti-TNF.alpha.
drug and cyclosporine, e.g., a housekeeping mRNA that is
constitutively expressed. Suitable mRNAs for normalization include
housekeeping mRNAs such as the U6, U24, U48 and S18. This
normalization allows the comparison of the expression level in one
sample, e.g., a subject sample, to another sample, or between
samples from different sources. In a particular embodiment,
expression levels are normalized by correcting the absolute
expression level of miRNAs by comparing its expression to the
expression of a reference mRNA.
[0048] Nucleic acids exhibiting sequence complementarity or
homology to the miRNAs of interest herein find utility as
hybridization probes or amplification primers. It is understood
that such nucleic acids need not be identical, but are typically at
least about 80% identical to the homologous region of comparable
size, more preferably 85% identical and even more preferably 90-95%
identical. In certain embodiments, it will be advantageous to use
nucleic acids in combination with appropriate means, such as a
detectable label, for detecting hybridization. A wide variety of
appropriate indicators are known in the art including, fluorescent,
radioactive, enzymatic or other ligands (e.g. avidinibiotin).
[0049] The probes and primers are "specific" to the miRNAs they
hybridize to, i.e. they preferably hybridize under high stringency
hybridization conditions (corresponding to the highest melting
temperature Tm, e.g., 50% formamide, 5.times. or 6.times. SCC. SCC
is a 0.15 M NaCl, 0.015 M Na-citrate).
[0050] miRNA may be detected using hybridization-based methods,
including but not limited to hybridization arrays (e.g.,
microarrays), NanoString analysis, Northern Blot analysis, branched
DNA (bDNA) signal amplification, and in situ hybridization.
[0051] Microarrays can be used to measure the expression levels of
large numbers of miRNAs simultaneously. Microarrays can be
fabricated using a variety of technologies, including printing with
fine-pointed pins onto glass slides, photolithography using
pre-made masks, photolithography using dynamic micromirror devices,
inkjet printing, or electrochemistry on microelectrode arrays. Also
useful are microfluidic TaqMan Low-Density Arrays, which are based
on an array of microfluidic qRT-PCR reactions, as well as related
microfluidic qRT-PCR based methods. In one example of microarray
detection, various oligonucleotides (e.g., 200+5'-amino-modified-C6
oligos) corresponding to human sense miRNA sequences are spotted on
three-dimensional CodeLink slides (GE Health/Amersham Biosciences)
at a final concentration of about 20 .mu.M and processed according
to manufacturer's recommendations. First strand cDNA synthesized
from 20 .mu.g TRIzol-purified total RNA is labeled with
biotinylated ddUTP using the Enzo BioArray end labeling kit (Enzo
Life Sciences Inc.). Hybridization, staining, and washing can be
performed according to a modified Affymetrix Antisense genome array
protocol. Axon B-4000 scanner and Gene-Pix Pro 4.0 software or
other suitable software can be used to scan images. Non-positive
spots after background subtraction, and outliers detected by the
ESD procedure, are removed. The resulting signal intensity values
are normalized to per-chip median values and then used to obtain
geometric means and standard errors for each miRNA. Each miRNA
signal can be transformed to log base 2, and a one-sample t test
can be conducted. Independent hybridizations for each sample can be
performed on chips with each miRNA spotted multiple times to
increase the robustness of the data.
[0052] Microarrays can be used for the expression profiling of
miRNAs. For example, RNA can be extracted from the sample and,
optionally, the miRNAs are size- selected from total RNA.
Oligonucleotide linkers can be attached to the 5' and 3' ends of
the miRNAs and the resulting ligation products are used as
templates for an RT-PCR reaction. The sense strand PCR primer can
have a fluorophore attached to its 5' end, thereby labeling the
sense strand of the PCR product.
[0053] The PCR product is denatured and then hybridized to the
microarray. A PCR product, referred to as the target nucleic acid
that is complementary to the corresponding miRNA capture probe
sequence on the array will hybridize, via base pairing, to the spot
at which the capture probes are affixed. The spot will then
fluoresce when excited using a microarray laser scanner. The
fluorescence intensity of each spot is then evaluated in terms of
the number of copies of a particular miRNA, using a number of
positive and negative controls and array data normalization
methods, which will result in assessment of the level of expression
of a particular miRNA. Total RNA containing the miRNA extracted
from the sample can also be used directly without size-selection of
the miRNAs. For example, the RNA can be 3' end labeled using T4 RNA
ligase and a fluorophore-labeled short RNA linker.
Fluorophore-labeled miRNAs complementary to the corresponding miRNA
capture probe sequences on the array hybridize, via base pairing,
to the spot at which the capture probes are affixed. The
fluorescence intensity of each spot is then evaluated in terms of
the number of copies of a particular miRNA, using a number of
positive and negative controls and array data normalization
methods, which will result in assessment of the level of expression
of a particular miRNA. Several types of microarrays can be employed
including, but not limited to, spotted oligonucleotide microarrays,
pre-fabricated oligonucleotide microarrays or spotted long
oligonucleotide arrays.
[0054] Accordingly, the nucleic acid probes include one or more
labels, for example to permit detection of a target nucleic acid
molecule using the disclosed probes. In various applications, such
as in situ hybridization procedures, a nucleic acid probe includes
a label (e.g., a detectable label). A "detectable label" is a
molecule or material that can be used to produce a detectable
signal that indicates the presence or concentration of the probe
(particularly the bound or hybridized probe) in a sample. Thus, a
labeled nucleic acid molecule provides an indicator of the presence
or concentration of a target nucleic acid sequence (e.g., genomic
target nucleic acid sequence) (to which the labeled uniquely
specific nucleic acid molecule is bound or hybridized) in a sample.
A label associated with one or more nucleic acid molecules (such as
a probe generated by the disclosed methods) can be detected either
directly or indirectly. A label can be detected by any known or yet
to be discovered mechanism including absorption, emission and/or
scattering of a photon (including radio frequency, microwave
frequency, infrared frequency, visible frequency and ultra-violet
frequency photons). Detectable labels include colored, fluorescent,
phosphorescent and luminescent molecules and materials, catalysts
(such as enzymes) that convert one substance into another substance
to provide a detectable difference (such as by converting a
colorless substance into a colored substance or vice versa, or by
producing a precipitate or increasing sample turbidity), haptens
that can be detected by antibody binding interactions, and
paramagnetic and magnetic molecules or materials.
[0055] Particular examples of detectable labels include fluorescent
molecules (or fluorochromes). Numerous fluorochromes are known to
those of skill in the art, and can be selected, for example from
Life Technologies (formerly Invitrogen), e.g., see, The Handbook-A
Guide to Fluorescent Probes and Labeling Technologies). Examples of
particular fluorophores that can be attached (for example,
chemically conjugated) to a nucleic acid molecule (such as a
uniquely specific binding region) are provided in U.S. Pat. No.
5,866, 366 to Nazarenko et al., such as
4-acetamido-4'-isothiocyanatostilbene-2,2' disulfonic acid,
acridine and derivatives such as acridine and acridine
isothiocyanate, 5-(2'-aminoethyl) aminonaphthalene-1-sulfonic acid
(EDANS), 4-amino-N-[3 vinylsulfonyl)phenyl]naphthalimide-3,5
disulfonate (Lucifer Yellow VS), N-(4-anilino-1-naphthyl)maleimide,
Brilliant Yellow, coumarin and derivatives such as coumarin,
7-amino-4-methylcoumarin (AMC, Coumarin 120),
7-amino-4-trifluoromethylcoumarin (Coumarin 151); cyanosine;
4',6-diaminidino-2-phenylindole (DAPI);
5',5''dibromopyrogallol-sulfonephthalein (Bromopyrogallol Red);
7-diethylamino-3-(4'-isothiocyanatophenyl)-4-methylcoumarin;
diethylenetriamine pentaacetate;
4,4'-diisothiocyanatodihydro-stilbene-2,2'-disulfonic acid;
4,4'-diisothiocyanatostilbene-2,2'-disulfonic acid;
5-[dimethylamino] naphthalene-1-sulfonyl chloride (DNS, dansyl
chloride); 4-(4'-dimethylaminophenylazo)benzoic acid (DABCYL);
4-dimethylaminophenylazophenyl-4'-isothiocyanate (DABITC); eosin
and derivatives such as eosin and eosin isothiocyanate; erythrosin
and derivatives such as erythrosin B and erythrosin isothiocyanate;
ethidium; fluorescein and derivatives such as 5-carboxyfluorescein
(FAM), Dichlorotriazinylamino fluorescein (DTAF),
2'7'dimethoxy-4'5'-dichloro-6-carboxyfluorescein (JOE),
fluorescein, fluorescein isothiocyanate (FITC), and QFITC Q(RITC);
2'7'-difluorofluorescein (OREGON GREEN.RTM.); fluorescamine; IR144;
IR1446; Malachite Green isothiocyanate; 4-methylumbelliferone;
ortho cresolphthalein; nitrotyrosine; pararosaniline; Phenol Red;
B-phycoerythrin; o-phthaldialdehyde; pyrene and derivatives such as
pyrene, pyrene butyrate and succinimidyl 1-pyrene butyrate;
Reactive Red 4 (Cibacron Brilliant Red 3B-A); rhodamine and
derivatives such as 6-carboxy-X-rhodamine (ROX), 6-carboxyrhodamine
(R6G), lissamine rhodamine B sulfonyl chloride, rhodamine (Rhod),
rhodamine B, rhodamine 123, rhodamine X isothiocyanate, rhodamine
green, sulforhodamine B, sulforhodamine 101 and sulfonyl chloride
derivative of sulforhodamine 101 (Texas Red);
N,N,N',N'-tetramethyl-6-carboxyrhodamine (TAMRA); tetramethyl
rhodamine; tetramethyl rhodamine isothiocyanate (TRITC);
riboflavin; rosolic acid and terbium chelate derivatives. Other
suitable fluorophores include thiol-reactive europium chelates
which emit at approximately 617 mn (Heyduk and Heyduk, Analyt.
Biochem. 248:216-27, 1997; J. Biol. Chem. 274:3315-22, 1999), as
well as GFP, Lissamine.TM., diethylaminocoumarin, fluorescein
chlorotriazinyl, naphthofluorescein, 4,7-dichlororhodamine and
xanthene (as described in U.S. Pat. No. 5,800,996 to Lee et al.)
and derivatives thereof. Other fluorophores known to those skilled
in the art can also be used, for example those available from Life
Technologies (Invitrogen; Molecular Probes (Eugene, Oreg.)) and
including the ALEXA FLUOR.RTM. series of dyes (for example, as
described in U.S. Pat. Nos. 5,696,157, 6,130,101 and 6,716,979),
the BODIPY series of dyes (dipyrrometheneboron difluoride dyes, for
example as described in U.S. Pat. Nos. 4,774,339, 5,187,288,
5,248,782, 5,274,113, 5,338,854, 5,451,663 and 5,433,896), Cascade
Blue (an amine reactive derivative of the sulfonated pyrene
described in U.S. Pat. No. 5,132,432) and Marina Blue (U.S. Pat.
No. 5,830,912).
[0056] In addition to the fluorochromes described above, a
fluorescent label can be a fluorescent nanoparticle, such as a
semiconductor nanocrystal, e.g., a QUANTUM DOT.TM. (obtained, for
example, from Life Technologies (QuantumDot Corp, Invitrogen
Nanocrystal Technologies, Eugene, Oreg.); see also, U.S. Pat. Nos.
6,815,064; 6,682,596; and 6,649,138). Semiconductor nanocrystals
are microscopic particles having size-dependent optical and/or
electrical properties. When semiconductor nanocrystals are
illuminated with a primary energy source, a secondary emission of
energy occurs of a frequency that corresponds to the bandgap of the
semiconductor material used in the semiconductor nanocrystal. This
emission can he detected as colored light of a specific wavelength
or fluorescence. Semiconductor nanocrystals with different spectral
characteristics are described in e.g., U.S. Pat. No. 6,602,671.
Semiconductor nanocrystals that can he coupled to a variety of
biological molecules (including dNTPs and/or nucleic acids) or
substrates by techniques described in, for example, Bruchez et al.,
Science 281 :20132016, 1998; Chan et al., Science 281:2016-2018,
1998; and U.S. Pat. No. 6,274,323. Formation of semiconductor
nanocrystals of various compositions are disclosed in, e.g., U.S.
Pat. Nos. 6,927,069; 6,914,256; 6,855,202; 6,709,929; 6,689,338;
6,500,622; 6,306,736; 6,225,198; 6,207,392; 6,114,038; 6,048,616;
5,990,479; 5,690,807; 5,571,018; 5,505,928; 5,262,357 and in U.S.
Patent Publication No. 2003/0165951 as well as PCT Publication No.
99/26299 (published May 27, 1999). Separate populations of
semiconductor nanocrystals can he produced that are identifiable
based on their different spectral characteristics. For example,
semiconductor nanocrystals can he produced that emit light of
different colors based on their composition, size or size and
composition. For example, quantum dots that emit light at different
wavelengths based on size (565 nm, 655 nm, 705 nm, or 800 nm
emission wavelengths), which are suitable as fluorescent labels in
the probes disclosed herein are available from Life Technologies
(Carlsbad, Calif.).
[0057] RT-PCR is typically carried out in a thermal cycler with the
capacity to illuminate each sample with a beam of light of a
specified wavelength and detect the fluorescence emitted by the
excited fluorophore. The thermal cycler is also able to rapidly
heat and chill samples, thereby taking advantage of the
physicochemical properties of the nucleic acids and thermal
polymerase. The majority of the thermocyclers on the market now
offer similar characteristics. Typically, thermocyclers involve a
format of glass capillaries, plastics tubes, 96-well plates or
384-well plates. The thermocylcer also involves software
analysis.
[0058] miRNAs can also be detected without amplification using the
nCounter Analysis System (NanoString Technologies, Seattle, Wash.).
This technology employs two nucleic acid-based probes that
hybridize in solution (e.g., a reporter probe and a capture probe).
After hybridization, excess probes are removed, and probe/target
complexes are analyzed in accordance with the manufacturer's
protocol. nCounter miRNA assay kits are available from NanoString
Technologies, which are capable of distinguishing between highly
similar miRNAs with great specificity. The basis of the nCounter
Analysis system is the unique code assigned to each nucleic acid
target to be assayed (International Patent Application Publication
No. WO 08/124847, U.S. Pat. No. 8,415,102 and Geiss et al. Nature
Biotechnology. 2008. 26(3): 317-325; the contents of which are each
incorporated herein by reference in their entireties). The code is
composed of an ordered series of colored fluorescent spots which
create a unique barcode for each target to be assayed. A pair of
probes is designed for each oligonucleotide target, a biotinylated
capture probe and a reporter probe carrying the fluorescent
barcode. This system is also referred to, herein, as the
nanoreporter code system. Specific reporter and capture probes are
synthesized for each target. The reporter probe can comprise at a
least a first label attachment region to which are attached one or
more label monomers that emit light constituting a first signal; at
least a second label attachment region, which is non-over-lapping
with the first label attachment region, to which are attached one
or more label monomers that emit light constituting a second
signal; and a first target-specific sequence. Preferably, each
sequence specific reporter probe comprises a target specific
sequence capable of hybridizing to no more than one gene and
optionally comprises at least three, or at least four label
attachment regions, said attachment regions comprising one or more
label monomers that emit light, constituting at least a third
signal, or at least a fourth signal, respectively. The capture
probe can comprise a second target-specific sequence; and a first
affinity tag. In some embodiments, the capture probe can also
comprise one or more label attachment regions. Preferably, the
first target-specific sequence of the reporter probe and the second
target-specific sequence of the capture probe hybridize to
different regions of the same gene to be detected. Reporter and
capture probes are all pooled into a single hybridization mixture,
the "probe library". The relative abundance of each target is
measured in a single multiplexed hybridization reaction. The method
comprises contacting the sample with a probe library, such that the
presence of the target in the sample creates a probe pair--target
complex. The complex is then purified. More specifically, the
sample is combined with the probe library, and hybridization occurs
in solution. After hybridization, the tripartite hybridized
complexes (probe pairs and target) are purified in a two-step
procedure using magnetic beads linked to oligonucleotides
complementary to universal sequences present on the capture and
reporter probes. This dual purification process allows the
hybridization reaction to be driven to completion with a large
excess of target-specific probes, as they are ultimately removed,
and, thus, do not interfere with binding and imaging of the sample.
All post hybridization steps are handled robotically on a custom
liquid-handling robot (Prep Station, NanoString Technologies).
Purified reactions are typically deposited by the Prep Station into
individual flow cells of a sample cartridge, bound to a
streptavidin-coated surface via the capture probe, clectrophoresed
to elongate the reporter probes, and immobilized. After processing,
the sample cartridge is transferred to a fully automated imaging
and data collection device (Digital Analyzer, NanoString
Technologies). The expression level of a target is measured by
imaging each sample and counting the number of times the code for
that target is detected. For each sample, typically 600
fields-of-view (FOV) are imaged (1376.times.1024 pixels)
representing approximately 10 mm2 of the binding surface. Typical
imaging density is 100-1200 counted reporters per field of view
depending on the degree of multiplexing, the amount of sample
input, and overall target abundance. Data is output in simple
spreadsheet format listing the number of counts per target, per
sample. This system can be used along with nanoreporters.
Additional disclosure regarding nanoreporters can be found in
International Publication No. WO 07/076129 and WO07/076132, and US
Patent Publication No. 2010/0015607 and 2010/0261026, the contents
of which are incorporated herein in their entireties. Further, the
term nucleic acid probes and nanoreporters can include the
rationally designed (e.g. synthetic sequences) described in
International Publication No. WO 2010/019826 and US Patent
Publication No. 2010/0047924, incorporated herein by reference in
its entirety.
[0059] Mass spectroscopy can be used to quantify miRNA using RNase
mapping. Isolated RNAs can be enzymatically digested with RNA
endonucleases (RNases) having high specificity (e.g., RNase T1,
which cleaves at the 3'-side of all unmodified guanosine residues)
prior to their analysis by MS or tandem MS (MS/MS) approaches. The
first approach developed utilized the on-line chromatographic
separation of endonuclease digests by reversed phase HPLC coupled
directly to ESTMS. The presence of post-transcriptional
modifications can be revealed by mass shifts from those expected
based upon the RNA sequence. Ions of anomalous mass/charge values
can then be isolated for tandem MS sequencing to locate the
sequence placement of the post-transcriptionally modified
nucleoside. Matrix-assisted laser desorption/ionization mass
spectrometry (MALDI-MS) has also been used as an analytical
approach for obtaining information about post-transcriptionally
modified nucleosides. MALDI-based approaches can be differentiated
from EST-based approaches by the separation step. In MALDI-MS, the
mass spectrometer is used to separate the miRNA. To analyze a
limited quantity of intact miRNAs, a system of capillary LC coupled
with nanoESl-MS can be employed, by using a linear ion
trap-orbitrap hybrid mass spectrometer (LTQ Orbitrap XL, Thermo
Fisher Scientific) or a tandem-quadrupole time-of-flight mass
spectrometer (QSTAR.RTM. XL, Applied Biosystems) equipped with a
custom-made nanospray ion source, a Nanovolume Valve (Valeo
Instruments), and a splitless nano HPLC system (DiNa, KYA
Technologies). Analyte/TEAA is loaded onto a nano-LC trap column,
desalted, and then concentrated. Intact miRNAs are eluted from the
trap column and directly injected into a C1 8 capillary column, and
chromatographed by RP-HPLC using a gradient of solvents of
increasing polarity. The chromatographic eluent is sprayed from a
sprayer tip attached to the capillary column, using an ionization
voltage that allows ions to be scanned in the negative polarity
mode.
[0060] Additional methods for miRNA detection and measurement
include, for example, strand invasion assay (Third Wave
Technologies, Inc.), surface plasmon resonance (SPR), cDNA, MTDNA
(metallic DNA; Advance Technologies, Saskatoon, SK), and
single-molecule methods such as the one developed by US Genomics.
Multiple miRNAs can be detected in a microarray format using a
novel approach that combines a surface enzyme reaction with
nanoparticle-amplified SPR imaging (SPRI). The surface reaction of
poly(A) polymerase creates poly(A) tails on miRNAs hybridized onto
locked nucleic acid (LNA) microarrays. DNA-modified nanoparticles
are then adsorbed onto the poly(A) tails and detected with SPRI.
This ultrasensitive nanoparticle-amplified SPRI methodology can be
used for miRNA profiling at attamole levels. miRNAs can also be
detected using branched DNA (bDNA) signal amplification (see, for
example, Urdea, Nature Biotechnology (1994), 12:926-928). miRNA
assays based on bDNA signal amplification are commercially
available. One such assay is the QuantiGene.RTM. 2.0 miRNA Assay
(Affymetrix, Santa Clara, Calif.). Northern Blot and in situ
hybridization may also be used to detect miRNAs. Suitable methods
for performing Northern Blot and in situ hybridization are known in
the art. Advanced sequencing methods can likewise be used as
available. For example, miRNAs can be detected using Illumina.RTM.
Next Generation Sequencing (e.g. Sequencing-By-Synthesis or TruSeq
methods, using, for example, the HiSeq, HiScan, GenomeAnalyzer, or
MiSeq systems (Illumina, Inc., San Diego, Calif.)). miRNAs can also
be detected using Ion Torrent Sequencing (Ion Torrent Systems,
Inc., Gulliford, Conn.), or other suitable methods of semiconductor
sequencing.
[0061] A further object relates to a kit for performing the methods
of the present invention, wherein said kit comprises means for
measuring the expression level of at least one miRNA selected from
miRNAs of Table A that is indicative of subject responder to
corticosteroid, anti-TNF.alpha. drug or cyclosporine treatment.
Typically the kit may include primers, probes macroarrays or
microarrays as above described. For example, the kit may comprise a
set of miRNA probes as above defined, usually made of DNA, and
optionally pre-labelled. Alternatively, probes may be unlabelled
and the ingredients for labelling may be included in the kit in
separate containers. The kit may further comprise hybridization
reagents or other suitably packaged reagents and materials needed
for the particular hybridization protocol, including solid-phase
matrices, if applicable, and standards. Alternatively the kit of
the invention may comprise amplification primers (e.g. stem-loop
primers) that may be pre-labelled or may contain an affinity
purification or attachment moiety. The kit may further comprise
amplification reagents and also other suitably packaged reagents
and materials needed for the particular amplification protocol.
[0062] The methods of the invention thus allow to define a subgroup
of subjects who will be responders or non-responders to
corticosteroid, anti-TNF.alpha. drug or cyclosporine treatment.
[0063] Accordingly a further object the present invention relates
to a method of treating acute severe colitis (ASC) by a
corticosteroid in a subject in need thereof comprising the steps of
a) determining whether the subject will be a responder or a
non-responder to a corticosteroid by performing the method
according to object n.degree. 1, and b) administering the
corticosteroid, if said subject has been considered as a responder
in step a).
[0064] A further object of the present invention relates to a
method of treating acute severe colitis (ASC) by an anti-TNF.alpha.
drug in a subject in need thereof comprising the steps of a)
determining whether the subject will be a responder or a
non-responder to anti-TNF.alpha. drug by performing the method
according to object n.degree. 2, and b) administering the
anti-TNF.alpha. drug, if said subject has been considered as a
responder in step a).
[0065] A further object of the present invention relates to a
method of treating acute severe colitis (ASC) by cyclosporine in a
subject in need thereof comprising the steps of a) determining
whether the subject will be a responder or a non-responder to
cyclosporine by performing the method according object n.degree. 3,
and b) administering the cyclosporine, if said subject has been
considered as a responder in step a).
[0066] A further object of the present invention relates to a
method of treating acute severe colitis (ASC) by a corticosteroid,
an anti-TNF.alpha. drug, cyclosporine or colectomy in a subject in
need thereof comprising the steps of a) determining whether the
subject will be a responder or a non-responder to a corticosteroid,
anti-TNF.alpha. drug, and cyclosporine by performing the method
according object n.degree. 4, and b) administering the
corticosteroid, if said subject has been considered as a responder
to the corticosteroid in step a), c) administering the
anti-TNF.alpha. drug, if said subject has been considered as a
non-responder to the corticosteroid and as a responder to
anti-TNF.alpha. drug in step a), d) administering cyclosporine, if
said subject has been considered as a non-responder to the
corticosteroid and as a responder to cyclosporine in step a), and
c) performing a colectomy, if said subject has been considered as a
non-responder to the corticosteroid, anti-TNF.alpha. drug and
cyclosporine in step a).
[0067] As used herein, the term "colectomy" refers to surgical
resection of any extent of the large intestine (colon). Herein,
colectomy includes, but is not limited to right hemicolectomy, left
hemicolectomy, extended hemicolectomy, transverse colectomy,
sigmoidectomy, proctosigmoidectomy, Hartmann operation,
"double-barrel" or Mikulicz colostomy, total colectomy (also known
as Lane's Operation), total procto-colectomy and subtotal
colectomy.
[0068] In some embodiments, the method of the invention comprises
the step of administering the anti-TNF.alpha. drug and
cyclosporine, if the subject has been considered as a non-responder
to the corticosteroid, as a responder to the anti-TNF.alpha. drug
and as a responder to cyclosporine by performing the method
according to the invention.
[0069] The invention will be further illustrated by the following
Example. However, this example should not be interpreted in any way
as limiting the scope of the present invention.
EXAMPLE
Material & Methods
Patients:
[0070] Patients were selected from two French tertiary centres:
Beaujon Hospital (Assistance Publique des Hopitaux de Paris) and
Haut-Lev que (CHU de Bordeaux) Hospital. The institutional review
boards of both centres approved this study, and all patients were
informed. The selection of patients was retrospectively made from
clinical files and pathological databases. The inclusion criteria
were the following: older than 18 years of age, well-established UC
diagnosis according to ECCO criteria[16], admission for an ASUC
episode based on a Lichtiger index above 10 points at
admission[17], and flexible recto-sigmoidoscopy with colonic
biopsies performed within 5 days following admission. Colonic
biopsies were taken at admission or during the first days of IV
steroid treatment before the assessment of the clinical response to
this treatment at days 3 to 5. The exclusion criteria were the
following: having Crohn's disease, absence of biopsies at entry or
insufficient RNA amount (less than 5 ng/.mu.l), and follow-up
duration of less than 3 months after admission for ASUC. Patients
were recruited from January 2007 to October 2014, including 11
patients previously included in the CYSIF study, which compared CsA
to IFX as second-line medical therapy for steroid refractory ASUC
[9]. In both centres, patients received IV steroids (at least 0.8
mg/kg/d of methylprednisolone) as the first-line therapy. In
patients with an insufficient response after 3 to 5 days,
second-line treatment with CsA or IFX was started in patients who
did not require a colectomy according to clinical need and
experienced physician advice. CsA was started at 2 mg/kg/day and
was subsequently adapted according to blood concentrations to
obtain levels of 150 to 250 ng/mL. IFX was infused at the usual
dose of 5 mg/kg at weeks 0, 2, and 6 and was continued as
maintenance therapy. Thiopurine was offered to all patients
responding to steroids, IFX or CsA. For each treatment, the
treatment response definitions used were those from the CYSIF
trial. Treatment failure was defined by one or more of the
following conditions: absence of a clinical response at day 7,
defined by a Lichtiger index above 10 points; relapse before month
3, defined by a Lichtiger index of greater than 10 or of more than
3 points on three consecutive days; need for a new systemic UC
therapy; or colectomy or death within 3 months of starting
treatment. Conversely, treatment success was defined by a Lichtiger
index of less than 10 points without any failure criteria on at
least 2 consecutive days within the first week of treatment.
RNA Extraction
[0071] Biopsies analysed in the study were all taken from inflamed
mucosa of the sigmoid colon. Total RNA was extracted from
formaldehyde fixed and paraffin embedded (FFPE) tissue (seven 10-nm
sections cut with a microtome from FFPE tissue blocks) using a
RecoverAll.TM. Total Nucleic Acid kit (Ambion.RTM., life
technologies.TM.). The FFPE samples were deparaffinized using a
series of xylene and ethanol washes and then subjected to a
rigorous protease digestion. Nucleic acids were purified using a
rapid glass-fibre filter methodology, which includes an on-filter
DNAse treatment, and then eluted into water. The purity and amount
of total RNA extracted were assessed with a spectrophotometer
(Nanodrop.TM. Spectrophotometer). All samples had a 260/280 ratio
above 1.6.
microRNA Assessment
[0072] The expression level of human pre- and mature miRNAs was
assessed using GeneChip.RTM. miRNA4.0 Arrays (Affymetrix, Santa
Clara, USA) with 100% coverage of the mirBASE v20 listed microRNAs.
An amount of 70 ng of total RNA was biotin labelled using the
FlashTag Biotin HSR RNA labelling kit (Affymetrix). Briefly, we
started with poly(A) tailing followed by ligation of the
biotinylated signal molecule to the target RNAs in the sample.
After overnight hybridization, chips were washed on a fluidic
station FS450 following specific protocols (Affymetrix) and scanned
using the GCS3000 7G. The scanned images were then analysed with
Expression Console software (Affymetrix) to obtain raw data (CEL
files) and metrics for Quality Controls. The observations of some
of these metrics and the study of the distribution of raw data
showed no outliers. Then, the hybridization data (CEL files) were
normalized by a miRNA QC tool and filtered by flags (absent or
present). The raw array data was analysed by an unpaired
t-test.
Differential microRNA Signature Expression Analysis
[0073] To measure the similarity between steroid and CsA/IFX
responders and non-responders for the 3,391-miRNA expression
profiles, we modelled data using general linear models adopted from
the R package `Limma`[19]. At this stage, neither the "responders"
nor "non-responders" labels were considered for the construction of
the matrix. The first set of 24 miRNA candidates was chosen from
the top-ranking candidates based on the false discovery rate
(fdr<0.05). Subsequently, annotated heatmaps were produced using
the R package `Heatplus` [20]. Additionally, we developed a blended
strategy to characterize predictive biomarkers, integrating patient
features based on inferences from patient data, i.e., miRNA
expression levels plus biological indicators. This approach is
built on two complementary actions: (1) refining the previous set
of features integrating a non-supervised enquiry for knowledge
related to particular miRNAs and (2) integrating a list of key
medically relevant clinical indicators.
Prediction Analysis
Classification Algorithms and Cross Validation Methods
[0074] The biological profile obtained from initial biopsies was
used to predict the response to first- and second-line ASUC medical
treatments. The classification of samples from responders or
non-responders was assessed through an assorted set of methods,
including Linear Discriminant Analysis (LDA), Topological Data
Analysis (TDA, [21]) Neural Networks or the Random Forest algorithm
(RF). However, a tailored deep learning model (DL, [** at the
bottom]) outperformed the other methods and showed more statistical
robustness in the two cohort studies. Regarding method validation,
the Leave-One-Out cross-validation (LOO, [23]) approach was used on
each sample. In these computations, we iteratively accounted for
two performance functions: (1) the Sum Squared Error performance
function (SSE), and (2) a classification score consisting of the
following formula: [.SIGMA..sub.error/(sample size)].times.100.
Whereas the classification score is used as a rough estimate of the
statistical power for the RF classification method, we leveraged
SSE to calculate the coefficient of variation (CV) in our
prediction algorithm. Notice that CV is concerned with the model
fit in terms of the relative sizes of the squared residuals (SSE)
and outcome values.
Analysis of Prediction Accuracy
[0075] The performance of each DL drug classification was analysed
by means of its receiver operating characteristic (ROC) curve. We
also wanted to validate our feature selection method using a
cross-procedure similar to that described in the previous section.
Thus, when a patient was removed from the list of candidates during
the LOO cross-validation, the feature selection method was run
without the patient, and we ranked the 15 and the 9 miRNAs produced
by this process in both the discovery and the validation cohorts
respectively. Therefore, when making a prediction on an
out-of-sample patient, we did not use his data during the feature
selection process nor during the training of the classification
algorithm.
Target Prediction and Pathway Analysis
[0076] To determine how the putative regulatory targets of the
selected differentially expressed miRNAs alter biological pathways,
a mapping of our predictive biomarker candidates was applied
against four different databases in two different groups, namely:
(1) KEGG and Reactome ([24,25]) against Targetscan[26] and
miRBase[27]; (2) mirPath[28] against microT-CDS[29] and
TarBase[30]. A hypergeometric test mathematically evaluated each
gene set enrichment related to deregulated functions or pathways.
Similar to the target analysis of the selected miRNAs, we evaluated
the mature miRNAs and regions of the miRNAs in the target genes in
a particular KEGG or Reactome Gene Ontology (GO)[31] category or
pathway.
Results:
Patients
[0077] Forty-seven patients with ASUC have been included. For 10
patients, ASUC was their first occurrence of UC. All patients
presented severe clinical and biological signs of colitis, with a
mean Lichtiger index of 13.4 points and a mean C-reactive protein
(CRP) level of 60.3 mg/l. All of the patients had Mayo endoscopic
subscore of 3, including 11 with deep ulcerations. Briefly, 14
patients responded to the first line of IV steroids, and most were
further treated with thiopurines. Thirty-three patients were
resistant to steroids and required a second or third line of
treatment. Among these 33 patients, 24 received IFX, 15 received
CsA, and 6 received both drugs. Thus, 12 patients responded and 12
failed to respond to IFX. Additionally, 9 patients responded and 6
patients failed to respond to CsA. In steroid non-responders, 10
patients underwent a colectomy during follow-up.
MicroRNA Expression Profile
Discovery Cohort
[0078] We measured the expression of 3,391 human microRNAs in
colonic biopsies fixed in FFPE from 47 patients admitted for an
episode of ASUC. The FFPE colonic biopsies were obtained from the
inflamed mucosa of 35 patients before the IV steroid treatment.
Twelve patients had colonic biopsies within the first 3 days of the
IV steroid course. Unsupervised clustering analysis showed 24
initial miRNA candidates, clearly separating steroid responders
from non-responders. We further applied an integrative method for
feature selection to reduce the signature. A set of 15 miRNAs was
selected: hp_hsa-mir-3934, hp_hsa-mir-3667, hp_hsa-mir-100,
hsa-miR-603, hsa-miR-718, hsa-miR-4259, hp_hsa-mir-193b,
hsa-miR-3150a-5p, hp_hsa-mir-1260b, hsa-miR-938, hsa-miR-3128,
hsa-miR-4423-3p, hsa-miR-518b, hsa-miR-1468 and hsa-miR-3152-3p. In
the steroid-non-responders group, we evaluated the value of using
miRNAs to discriminate between second-line therapy responders and
non-responders whose biopsies were obtained before (or during) the
first line of steroid treatment. Following the previous selection
methodology, we identified 6 (hsa-miR-4423-3p, hsa-miR-3128,
hsa-miR-3152-3p, hp_hsa-mir-193b, hsa-miR-938) and 4 miRNAs
(hsa-miR-4423-3p, hsa-miR-938, hsa-miR-518b and hsa-miR-100)
associated with response to IFX and CsA, respectively. The miRNAs
that were differentially expressed in second-line treatment
responders vs non-responders were included in the set of 15 miRNAs
associated with steroid response.
Validation Cohort
[0079] We measured by qPCR analysis the expression of the 15
selected human miRNAs in colonic biopsies fixed in FFPE from 29
additional patients with similar inclusion criteria recruited
secondarily. 9 out of the 15 miRNAs were expressed and remained as
candidates: hp_hsa-mir-3934, hp hsa-mir-100, hsa-miR-718,
hp_hsa-mir-193b, hsa-miR-3150a-5p, hp_hsa-mir-1260b, hsa-miR-938,
hsa-miR-518b and hsa-miR-1468. Next, we evaluated these 9 miRNAs
candidates in the discrimination between steroids responders and
non-responders to the validation cohort (data not shown). 3 miRNAs
were associated with response to IFX and CsA (data not shown).
Deep Learning Classification
[0080] Several classification methods were applied (see suppl.
Table 1) to develop a miRNA classifier for steroid, IFX and CsA,
responders versus non-responders. Among them, we selected the deep
learninu (DL) method, whose performance was the best both for the
discovery and the validation cohorts (FIG. 3). This selection was
made based on the raw and CV scores (see methods) before the LOO
validation. In turn, DL performing multi-classification with 2
categorical features, 14 numerical levels and expecting to have 33
input neurons yielded the best results, as shown in Table S1. Upon
the use of feature selection, as described in the Methods section,
the classifiers for the discovery cohort were the 15-miRNA steroid
response, 6-miRNA IFX response and 4-miRNA CsA response and 9-miRNA
steroid response, 3-miRNA IFX response and 3-miRNA CsA for the
validation cohort. At this stage, the intrinsic risk of
overfitting, as we picked 15-9, 6-3 or 4-3 miRNAs out of 3,391, is
worth noting. For that reason.
[0081] we developed a feature selection strategy based only on
unsupervised biological enquiries and integrated this feature
selection strateey into the LOO cross-validation strategy
afterwards. Furthermore. the classifiers were combined with some
biological data (see further below), achieving classification
success levels of .about.94%, .about.90% and .about.83% between
responders and non-responders to steroids, IFX and CsA in the
discovery cohort. And .about.90%, .about.84% and .about.80% between
responders and non-responders to steroids, IFX and CsA in the
validation cohort.
Adding Biological Data to Improve Classification Value
Stability
[0082] To improve the stratification strategy, we added values from
biological sample types collected at the same time as the biopsy to
the miRNA signature in a semi-supervised fashion. Sample types
included leukocytes, haematites, haematocrit, haemoglobin, glucose,
ferritin, transferrin, albumin, iron, basophil and lymphocyte
counts and C-reactive protein (CRP) levels. Importantly, prognostic
values for the steroid response were improved by combining the
selected miRNAs and a non-linear transformation of 5 clinically
relevant biological parameters (haemoglobin, haematocrit, albumin,
CRP, and transferrin levels). Hence, the DL stratification
algorithm steroid response prediction performance (see FIG. 4 and
table 2) increased to an .about.97%/.about.93% level of success for
the discovery cohort and the validation cohort respectively.
However, no combination of biological values allowed us to improve
the IFX and CsA response classifiers.
Cross Validation
[0083] The parameter leveraged to mathematically validate our
predictors was the CV, which was used as an exponent of the
goodness exhibited by our strategy and a raw score of
classification. Thus, from this score, a thorough analysis of each
DL drug classification was performed according to their associated
ROC curves (FIG. 4), i.e., AUC.sub.steroids=0.92-0.96/0.83-0.91
(without or with biological indicators inclusion) for the discovery
and validation cohorts, AUC.sub.IFX=0.86 and AUC.sub.CsA=0.81. The
CV values for the steroid, IFX and CsA, classifier performances
were 0.03-0.01 (without/with biological indicators), 0.05 and 0.08
(see Table 2). The benchmarking of the unsupervised feature
selection method showed similar prognostic values in each run (data
not shown).
Discussion:
[0084] To our knowledge, the present study is one of the first to
establish a mlRNA-based biomarker for precision medicine in IBD.
The identification of predictors of clinical outcomes is a major
challenge in ASUC treatment. Several scores have been established
to predict pejorative clinical outcomes after starting steroid
treatment for ASUC. Travis et al. determined that on day 3 of
intravenous treatment, the treatment for patients with more than
eight stools on that day, or a stool frequency between three and
eight with a CRP above 45 mg/l, would fail [18]. Seo et al.
[0085] proposed a composite activity index (60.times.blood
stool+13.times.bowel movements+0.5.times.erythrocyte sedimentation
rate-4.times.haemoglobin-15.times.albumin+200) [19]. In the pilot
study, remission occurred in all patients with ASUC, as indicated
by an index below 180 points 2 weeks after therapy, whereas
approximately 65% of patients with an index above 180 points
subsequently required a colectomy[20]. A recent study from the IBD
UK audit analysed the value of the Travis and the Ho indexes to
predict steroid failure in a retrospective cohort of 420 patients
with ASUC[11]. High-risk patients in Travis and the Ho groups, when
compared to lower risk groups, were more likely to fail steroid
therapy: 64.5% vs. 38.7% ((P<0.0001) for Travis and 66.2% vs.
46.7% vs. 36.6% (P <0.0001) for Ho[11]. These results highlight
the limited value of these indexes to stratify responders vs
non-responders to steroids.
[0086] More recently, biological indicators have been correlated
with ASUC clinical outcomes. Ho et al. showed that faecal
calprotectin was significantly higher in patients who required a
colectomy [21]. In a paediatric cohort of ASUC, an elevated faecal
M2-pyruvate kinase level was associated with steroid response [22].
However, the Pediatric UC Activity Index, a simple clinical index,
performed better than the faecal markers in predicting outcomes
following a course of intravenous steroids in ASUC.
[0087] Despite many efforts, there are currently no accurate
predictors of responses to treatments in ASUC. In a paediatric
cohort of 79 patients with ASUC, the interleukine-6 (IL-6) plasma
level at day 3 of an IV steroid course was significantly different
between responders and non-responders [23]. However, in
multivariate analysis, IL-6 was not associated with the steroid
response, suggesting an association with disease activity rather
than with steroid pathway failure [23]. The G2677T/A polymorphism
(TT genotype) of the multidrug resistance gene (MDR1) was
associated with the risk of CsA failure in a cohort of 154 patients
with steroid resistant episodes of ASUC [24]. However, this genetic
marker was neither validated nor used in daily practice. Mucosal
expression of TNF-alpha was inversely associated with endoscopic
and clinical responses to IFX in UC [25]. The same group also
determined that high expression levels of IL-17A and IFN-.gamma.
were significantly associated with remission after three IFX
infusions (OR=5.4, p=0.013 and OR=5.5, p=0.011, respectively) [26].
More recently, faecal loss of IFX was associated with IFX failure
in ASUC and severe colonic Crohn's disease [27].
[0088] A simple score predicting standard drug responses is still
lacking in treating patients with ASUC. For this reason, miRNAs
were considered to be relevant candidates. Dysregulation of a
specific subset of miRNAs has been identified in several studies
performed on inflammatory or quiescent colonic mucosa of patients
with UC[28]. An abnormal expression of several miRNAs was similarly
identified in several independent studies. These miRNAs were mostly
identified in inflammatory colonic mucosa, suggesting their
participation in dysregulated inflammatory processes (miR-21-5p,
miR-155-5p, miR-146a-5p, miR-31-5p, etc.). Interestingly, in other
diseases, mostly cancers, some miRNAs have been studied for their
potential prognostic values. To our knowledge, microRNA-based
prognostic biomarkers have still not been established for IBD
management.
[0089] To build this prediction algorithm, we established a
retrospective, bicentric, well-defined cohort of patients with UC
who were admitted for an episode of ASUC. Treatment procedures,
evaluations and definitions of responses or relapses were strictly
defined according to the CYSIF randomized trial criterion[9]. Even
the different clinical outcomes and drug response profiles of the
patients included were characterized retrospectively. The
predictive nature of the algorithm results from the fact that the
biochemical and molecular signatures were obtained before or during
the first days of initial treatment. Twelve patients had their
biopsies taken during the first line of IV steroids. Their
signatures of the 15 selected miRNAs were not affected in
comparison with those naive IV steroids patients (data not
shown).
[0090] Overall, this predictive algorithm utilizes a mathematical
approach that goes beyond a simple miRNA signature. It uses a
stratification tool using the DL layer of neurons decision method
whereby multiple comparisons are made between the individual data
of a patient (mucosal expression of 15-9 microRNAs, plus five
biological values for steroids) and those of a matrix of patients
who are well characterized for their responses to defined
treatments. Thus, for each patient tested in the algorithm, one
obtains a probability of their response to IV steroids, IFX and CsA
by learning a non-linear equation that properly captures the set of
solutions of a system composed by 9 miRNAs expression in qPCR and 5
biological indicators whose qualitative behaviour resembles in norm
the treatment output. Our approach, in addition to identifying a
limited set of response drivers, enables the improvement of the
performance ranges of classification methods, such as the classic
logistic regression from outreaches, of .about.80% to .about.93%
(.about.97% with biological data), even when the entire set of
miRNAs is taken into consideration. Unlike other similar studies
recently published [29], our method addressed a small number of
patients. To face this limit, the novelty of the proposed
predictive algorithm is not only built on a signature of mucosal
miRNAs but on a versatile method with: (1) a purely unsupervised
feature selection phase to minimize over-fitting issues, (2) a
classification task using random forests algorithm, and (3) the
addition of biological data to improve efficiency. In particular,
we do not rely on differential expression or random forest
variables for selecting the best miRNAs, as in Li et al. [29].
Instead, our selection approach relies on a combination of
unsupervised feature selection by hierarchical clustering and
integrative data analysis by matching the identified miRNAs with
existing biological knowledge. This integration with external
knowledge enhances the performance of unsupervised feature
selection in the context of a small number of patients. As far as
the classification task is concerned, we leverage the random forest
algorithm (not the centroid algorithm used in [29]), which was
calibrated with a leave-one-out cross-validation due to the limited
number of patients. Of note, the 5 biological data types were
helpful in predicting responses to steroids, but not second line
treatment responses, as these data were collected at admission.
[0091] Interestingly, the presence of deep ulcerations on
pre-therapeutic endoscopy assessment was not associated with the
prediction of the drug response profile, and this item was not
retained in the final DL predictive algorithm.
[0092] In summary, our study provides the first prediction tool for
responses to first- and second-line treatments in ASUC. Our results
are encouraging for the development of predictive medicine in UC,
even if they must be validated prospectively.
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