MARKERS FOR DIAGNOSING MULTIPLE SCLEROSIS AND PREDICTING RESPONSIVENESS TO INTERFERON TREATMENT

FIELD OF THE INVENTION

The present invention relates to markers and methods for diagnosing multiple sclerosis in a subject. The present invention further relates to a gene expression profile for the prediction of responsiveness to interferon treatment of subjects in need of interferon treatment, including but not limited to, subjects having multiple sclerosis. BACKGROUND OF THE INVENTION

Multiple Sclerosis (MS) is a chronic autoimmune demyelinating disease of the central nervous system. It is characterized by inflammation, demyelination and axonal degeneration. More than 2 million individuals are affected by the disease worldwide. The disease has a heterogeneous nature, which is reflected by variability in clinical course, timing of relapses and rate of disability progression.

Currently, there is no specific test for diagnosing MS and the diagnosis relies on recognition of the clinical history of the subject. The diagnosis can be supported by MRI of the brain and spinal cord, analysis of the cerebrospinal fluid, and evoked potential studies of the visual and somatosensory pathways. In addition, systemic or infectious etiologies with similar presentation must be excluded.

The McDonald criteria was introduced in 2001, and revised in 2005 (Polman et al., 2006, Ann Neurol. ;59(4):727-8), as guidelines to facilitate early and accurate diagnosis of multiple sclerosis (MS). Diagnostic classifications are reduced to a) having MS, b) not having MS, or c) having possible MS. Advantages to the Criteria include the capability of making a definitive diagnosis of MS either after a monosymptomatic presentation or in the context of a primary progressive course. However, the diagnostic classification scheme and MRI criteria remain complicated and tedious, and this complexity limits their use in everyday practice. Furthermore, the specificity of these criteria is relatively low, emphasizing the importance of clinical judgment in excluding other diagnoses. In addition, studies have observed that standard MS disease-modifying medications can benefit patients who do not yet fulfill these diagnostic criteria.

MS is the leading cause of neurological disability in young adults. No curative therapy is available and most of the individuals with MS will progress in disability and deteriorate clinically with time. The available therapies for MS are mostly effective during the earlier - relapsing- stage of the disease.

There are currently six FDA approved drugs for MS, three of them are interferons. It is highly important to start with an effective therapy as early as possible in order to prevent neurological disability.

Interferon β (IFN ) is the mainstay therapy used to prevent deterioration in MS. There are three commercial preparations of IFN available for clinical use: Betaferon, Avonex and Rebif. However, INF treatment may cause significant adverse effects including injection site reactions, flu-like symptoms, leukopenia, hepatic function disturbances and depression. Two- thirds of treated patients experience at least one of these side effects. Moreover, the clinical response rate to IFN is estimated to be around 30- 50%. The response rate varies between patients, ranging from full response (responders) to complete lack of response (non- responders), however clear criteria for such classification are still lacking. Clinical, neuro- radiological and immunological surrogate indicators of response to IFN are currently missing.

A correlation between the expression of various genes, especially in the IFN signal transduction pathway, and outcome of IFN treatment, has been observed. Although distinct patterns of expression of a few genes have been associated with the response status, no direct linkage has been proved.

International Patent Application Publication No. WO 10/076788 provides methods of predicting responsiveness to interferon treatment and treating hepatitis C infection.

Van Baarsen et al. (PLoS One; Apr 2;3(4):el927, 2008) disclosed that the expression levels of a set of 15 IFN response genes in the peripheral blood of MS patients prior to treatment could serve a role as biomarker for the differential clinical response to IFN .

There remains a need for improved diagnostic methods and kits useful in diagnosing

MS in a subject. Further, there remains an unmet medical need for providing methods capable of efficiently, objectively and expeditiously predicting responsiveness to interferon treatment in subjects afflicted with MS. SUMMARY OF THE INVENTION

The present invention provides methods and kits for prediction/determination of responsiveness to interferon (IFN) treatment. In particular embodiments, the present invention provides a gene expression profile for the prediction of responsiveness to interferon treatment in subjects with MS. The present invention further provides methods of treating a subject in need of treatment comprising predicting the responsiveness of the subject to interferon treatment and selecting a treatment regimen based on said prediction. In some embodiments, the methods and kits are gender-specific. In some embodiments, the gene expression profiles enable to differentiate between responder subjects and non- responder subjects. In some embodiments, such differentiation is in particular significant in differentiating between male responders and non-responders.

The present invention further provides methods and kits for diagnosing multiple sclerosis (MS) in a subject, antigen probe arrays for practicing such a diagnosis, and antigen probe sets for generating such arrays. In some embodiments, the methods and kits provided herein are gender specific, i.e. they may be used to provide a statistically significant result for male and/or female. In some embodiments,

It is herein disclosed, for the first time, that a specific gene expression profile significantly differentiates between interferon beta (IFN ) responder patients and IFN non- responder patients. While the expression of numerous inflammatory-related genes was tested, only specific genes showed remarkable differential expression pattern between responders (i.e., subjects who respond to IFN treatment) and non-responders. In some embodiments, the differential expression is gender-specific, i.e. the differentiation is significant in male and not in female.

The present invention is also based, in part, on the unexpected results obtained when testing Janus kinase 1 (JAK1) expression levels. As exemplified herein below, JAK1 expression is significantly differentiated between responders and non-responders as well as between MS patients and healthy controls. In some embodiments, JAK1 expression is significantly differentiated in a gender specific pattern. In some embodiments, JAK1 expression is higher in responders as compared to non-responders.

According to one aspect, the present invention provides a method of predicting responsiveness of a subject to interferon (IFN) treatment, comprising determining the expression level of a plurality of genes selected from the group consisting of: JAK1, CCR7, EEF1G, IFNAR2, MAP4K2, RPL19, SKI, ZEB 1 and ZAP70, or a subset thereof, in a sample obtained from the subject, wherein a significant difference between the expression level of the plurality of genes in said sample compared to a control value is indicative of the responsiveness of said subject to IFN treatment. According to some embodiments, the present invention provides a method of predicting/identifying responsiveness of a male subject to interferon (IFN) treatment, comprising determining the expression level of a plurality of genes selected from JAK1, IFNAR2, SKI, or a subset thereof, in a sample obtained from the subject, wherein a significant difference between the expression level of the plurality of genes in said sample compared to a control value is indicative of the responsiveness of said male subject to IFN treatment.

According to some embodiments, there is provided a method of predicting responsiveness of a male subject to interferon (IFN) treatment, comprising determining the expression level of a plurality of genes comprising JAK1 , IFNAR2, SKI, or a subset thereof, in a sample obtained from the subject, wherein a significant difference between the expression level of the plurality of genes in said sample compared to a control value is indicative of the responsiveness of said male subject to IFN treatment.

According to some embodiments, the present invention provides a method of predicting responsiveness of a male subject to interferon (IFN) treatment, comprising determining the expression level of genes comprising JAK1, IFNAR2 and SKI, in a sample obtained from the subject, wherein a significant difference between the expression level of the plurality of genes in said sample compared to a control value is indicative of the responsiveness of said male subject to IFN treatment.

In particular embodiments of the methods and kits of the invention, said interferon is interferon-beta (IFN ). In another embodiment, said interferon is interferon- alpha (IFNa).

According to some embodiments, the plurality of genes comprises at least 2 genes, at least 3 genes, at least 4 genes, at least 5 genes, at least 6 genes, at least 7 genes or at least 8 genes selected from the group consisting of: JAK1, CCR7, EEF1G, IFNAR2, MAP4K2, RPL19, SKI, ZEB 1 and ZAP70. According to another embodiment, the plurality of genes comprises JAK1 and at least 1 gene, at least 2 genes, at least 3 genes, at least 4 genes, at least 5 genes, at least 6 genes, at least 7 genes selected from the group consisting of: CCR7, EEF1G, IFNAR2, MAP4K2, RPL19, SKI, ZEB1 and ZAP70.

According to another embodiment, the plurality of genes comprises: ALAS1, CD247, CD44, CD5, CMKLR1, CXCR4, IL18R1, IL18RAP, IL2RB, STAT4, STAT5A, TGFB l and TRAFl, or a subset thereof. According to another embodiment, the plurality of genes comprises no more than 30 genes. According to another embodiment, the plurality of genes comprises CCR7 and ZEB 1 and further comprises: ABCB1, CCR6, CD247, CD5, IL18R1, IRAK2, KLRB 1, MUC1, STAT4, CMKLRl and PLA2G2A.

According to another embodiment, the present invention provides a method of predicting responsiveness of a subject to interferon treatment, the method comprising determining the expression level of a plurality of genes selected from the group consisting of: CCR7, ZEB 1, ABCB1, CCR6, CD247, CD5, IL18R1, IRAK2, KLRB1, MUC1, STAT4, CMKLRl and PLA2G2A, or a subset thereof, in a sample obtained from the subject, wherein a significant difference between the expression level of the plurality of genes in said sample compared to a control value is indicative of the responsiveness of said subject to IFN treatment. Each possibility represents a separate embodiment of the present invention.

According to another embodiment, an increased expression level of at least one gene selected from said plurality of genes, compared to the control value, indicates that said subject is responsive to IFN treatment. According to another embodiment, a reduced expression level of at least one gene selected from said plurality of genes compared to the control value indicates that said subject is non-responsive to IFN treatment.

According to some embodiments, the method comprises determining the expression pattern of the sample obtained from the subject and comparing the expression pattern of the sample to a control expression pattern, wherein a significant difference between the expression pattern of the sample obtained from the subject compared to a control expression pattern is indicative of the responsiveness of said subject to IFN treatment. In some embodiments, the subject is a male subject.

In particular embodiments, the subject is afflicted with multiple sclerosis (MS). In another embodiment, the subject is afflicted with a subtype of MS selected from: relapsing remitting MS (RRMS), primary progressive multiple sclerosis (PPMS) and secondary progressive multiple sclerosis (SPMS). Each possibility is a separate embodiment.

According to another embodiment, the sample is a fluid sample. According to some embodiments, the fluid sample is selected from a blood, plasma, CSF or serum sample.

According to another aspect, the present invention provides a method of treating a subject in need of IFN treatment, the method comprises:

(a) predicting the responsiveness of the subject to IFN treatment according to a method of the invention; and

(b) selecting a treatment regimen based on the prediction of step (a); thereby treating said subject in need of IFN treatment.

According to some embodiments, there is provided a method of identifying responsiveness of a subject to interferon treatment, the method comprising determining in a sample obtained from the subject an increased expression level of a plurality of genes comprising JAK1, IFNAR2, SKI, or combinations thereof, compared to a control value, wherein the subject is a male subject afflicted with Multiple Sclerosis (MS).

According to some embodiments, there is provided a method of predicting/identifying responsiveness of a subject to interferon treatment, the method comprising determining in a sample obtained from the subject an expression level of a plurality of genes comprising JAK1 and at least one gene selected from the group consisting of: CCR7, EEF1G, IFNAR2, MAP4K2, RPL19, SKI, ZEB1 and ZAP70, wherein the subject is a male subject afflicted with Multiple Sclerosis (MS). In some embodiments, an increased expression level of at least one gene selected from said plurality of genes, compared to the control value, indicates that said subject is responsive to IFN treatment. In some embodiments, a reduced expression level of at least one gene selected from said plurality of genes compared to the control value indicates that said subject is non-responsive to IFN treatment. In some embodiments, the method comprising determining the expression pattern of the sample obtained from the subject and comparing the expression pattern of the sample to a control expression pattern, wherein a significant difference between the expression pattern of the sample obtained from the subject compared to a control expression pattern is indicative of the responsiveness of said subject to IFN treatment.

According to some embodiments, there is provided a method of identifying responsiveness of a subject to interferon treatment, the method comprising determining in a sample obtained from the subject an increased expression level of a plurality of genes comprising JAK1, and at least one gene selected from the group consisting of: CCR7, EEF1G, IFNAR2, MAP4K2, RPL19, SKI, ZEB 1 and ZAP70, compared to a control value, wherein the subject is a male subject afflicted with Multiple Sclerosis (MS).

According to another aspect, the present invention provides a method of diagnosing MS in a subject, the method comprising determining the expression level of JAK1 in a sample obtained from the subject, wherein a significant difference between the expression levels of JAK1 in said sample compared to a control value is an indication that the subject is afflicted with MS. According to some embodiments, a decreased expression level of JAK1 compared to the control value indicates that said subject is afflicted with MS. In some embodiments, the subject is a male subject.

According to another embodiment, the method further comprises determining the expression level of at least one gene selected from CXCR4, EEFIG, MAP4K4 and CD44 in a sample obtained from the subject, wherein a significant difference between the expression level of JAKl and/or at least one gene in said sample compared to a control value is an indication that the subject is afflicted with MS.

According to another aspect, the present invention provides kits suitable for use in predicting the responsiveness of a subject to IFN treatment, the kit comprising means for determining the expression level of a plurality of genes selected from the group consisting of: JAKl, CCR7, EEFIG, IFNAR2, MAP4K2, RPL19, SKI, ZEBl and ZAP70, ALAS1, CD247, CD44, CD5, CMKLR1, CXCR4, IL18R1, IL18RAP, IL2RB, STAT4, STAT5A, TGFB 1 and TRAF1, or a subset thereof. In one embodiment, the subset of gene comprises JAKl, CCR7, EEFIG, IFNAR2, MAP4K2, RPL19, SKI, ZEBl and ZAP70. According to some embodiments, the kit further comprises means for determining the expression level of a plurality of genes selected from the group consisting of: CCR7, ZEBl, ABCB 1, CCR6, CD247, CD5, IL18R1, IRAK2, KLRB 1, MUC1, STAT4, CMKLR1 and PLA2G2A, or a subset thereof. Each possibility represents a separate embodiment of the present invention.

According to another embodiment, the present invention provides a kit suitable for use in predicting the responsiveness of a subject to IFN treatment, the kit comprising means for determining the expression level of a plurality of genes selected from the group consisting of: JAKl, CCR7, EEFIG, IFNAR2, MAP4K2, RPL19, SKI, ZEB l, ZAP70, ALAS1, CD247, CD44, CD5, CMKLR1, CXCR4, IL18R1, IL18RAP, IL2RB, STAT4, STAT5A, TGFB 1, TRAF1, ABCB 1, CCR6, IRAK2, KLRB 1, MUC1 and PLA2G2A or a subset thereof. Each possibility represents a separate embodiment of the present invention.

According to another aspect, the present invention provides kits suitable for diagnosing MS in a subject, the kit comprising means for determining the expression level of a plurality of genes comprising or selected from the group consisting of: JAKl, CXCR4, EEFIG, MAP4K4 and CD44.

According to another aspect, the present invention provides kits suitable for diagnosing MS in a subject, the kit comprising means for determining the expression level of a plurality of genes comprising or selected from the group consisting of: JAKl, IFNAR2 and SKI. Further embodiments and the full scope of applicability of the present invention will become apparent from the detailed description given hereinafter. However, it should be understood that the detailed description and specific examples, while indicating preferred embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 is a heatmap of a gene cluster of 80 genes (p<=0.05) depicting differential expression in the non-responder and responder groups.

Figure 2 is a heatmap of a gene cluster of 80 genes (p<=0.05) depicting differential expression in the non-responder and responder groups in men.

Figure 3 is a heatmap of TGFB 1, ALAS1, CMKLR1, IL18RAP, IL2RB, IL18R1, MAP4K2, TRAF1, ZEB 1, CCR7, SKI, STAT5A , JAK1, STAT4, ZAP70, IFNAR2, CD5, CD44, CD247, CXCR4, EEFIG and RPL19 genes (p<=0.01) depicting differential expression in the non-responder and responder groups.

Figure 4 is a heatmap of TGFB 1, ALAS1, CMKLR1, IL18RAP, IL2RB, IL18R1, MAP4K2, TRAF1, ZEB 1, CCR7, SKI, STAT5A , JAK1, STAT4, ZAP70, IFNAR2, CD5, CD44, CD247, CXCR4, EEFIG and RPL19 genes (p<=0.01) depicting differential expression in the non-responder and responder groups in men.

Figure 5 is a heatmap of MAP4K2, ZEB1, SKI, JAK1, ZAP70, IFNAR2, EEFIG and RPL19 genes (p<=0.005) depicting differential expression in the non-responder and responder groups.

Figure 6 is a heatmap of MAP4K2, ZEB1, SKI, JAK1, ZAP70, IFNAR2, EEFIG and RPL19 genes (p<=0.005) depicting differential expression in the non-responder and responder groups in men.

Figure 7 is a graph depicting JAK1 differential expression observed in responder (R), non-responder (NR) and control groups.

Figure 8 is a graph depicting JAK1 expression correlation with multiple sclerosis disease severity scale (EDSS).

DETAILED DESCRIPTION OF THE INVENTION The invention is directed, in some embodiments, to prediction of responsiveness to interferon treatment. In particular embodiments, the invention is directed to a gene expression profile for the prediction of responsiveness to interferon treatment in subjects with multiple sclerosis (MS). The present invention is further directed to a method of treating a subject in need of interferon treatment comprising predicting the responsiveness of the subject to interferon treatment and selecting a treatment regimen based on said prediction. In some embodiments, the subject is a male subject.

Table 1 lists the differentiating genes as well as their full name and gene ID

CD44 CD44 molecule (Indian blood group) NM_000610.3

CD5 CD5 molecule NM_014207.2

CMKLRl chemokine-like receptor 1 NM_004072.1

CXCR4 chemokine (C-X-C motif) receptor 4 NM_003467.2

IL18R1 interleukin 18 receptor 1 NM_003855.2

IL18RAP interleukin 18 receptor accessory protein NM_003853.2

IL2RB interleukin 2 receptor, beta NM_000878.2

STAT4 signal transducer and activator of transcription 4 NM_003151.2

STAT5A signal transducer and activator of transcription 5A NM_003152.2

TGFB 1 transforming growth factor, beta 1 NM_000660.3

TRAF1 TNF receptor-associated factor 1 NM_005658.3

Homo sapiens ATP -binding cassette, sub-family B

ABCB1 NM_000927.4

(MDR/TAP), member 1

CCR6 Homo sapiens chemokine (C-C motif) receptor 6 NM_004367.5

Interleukin- 1 receptor-associated kinase 2

IRAK2 NM_001570.3

Killer cell lectin-like receptor subfamily B, member 1

KLRB1 NM_002258.2

MUC1 Cell surface associated Mucin 1 NM_001204296.1

Phospholipase A2, group IIA

PLA2G2A NM_000300.3 According to some embodiments, the present invention provides a method of predicting responsiveness of a subject to interferon treatment, the method comprising comparing the expression levels of a plurality of genes selected from the group comprising or consisting of: JAKl, CCR7, EEF1G, IFNAR2, MAP4K2, RPL19, SKI, ZEB1, ZAP70, ALAS1, CD247, CD44, CD5, CMKLRl, CXCR4, IL18R1, IL18RAP, IL2RB, STAT4, STAT5A, TGFB1 and TRAF1, or a subset thereof, in a sample obtained from the subject, to a control value (e.g., a reference expression value) of said plurality of genes, thereby predicting the responsiveness of the subject to interferon treatment.

According to another aspect, the present invention provides a method of predicting responsiveness of a subject to interferon beta (ΙΕΝβ) treatment, the method comprising determining the expression levels of a plurality of genes in a sample obtained from the subject, the plurality of genes may be selected from the group comprising or consisting of: JAKl, CCR7, EEF1G, IFNAR2, MAP4K2, RPL19, SKI, ZEB 1, ZAP70, ALAS1, CD247, CD44, CD5, CMKLRl, CXCR4, IL18R1, IL18RAP, IL2RB, STAT4, STAT5A, TGFB 1 and TRAF1, or a subset thereof, thereby determining the expression pattern of the sample, wherein a significant difference between the expression pattern of the sample obtained from the subject compared to a control expression pattern is indicative of the responsiveness of said subject to ΙΕΝβ treatment.

According to some embodiments, the plurality of genes comprises at least three genes. According to some embodiments, the plurality of genes comprises at least four genes. According to some embodiments, the plurality of genes comprises at least five genes. According to some embodiments, the plurality of genes comprises at least six genes. According to some embodiments, the plurality of genes comprises at least seven genes. According to some embodiments, the plurality of genes comprises at least eight genes. According to some embodiments, the plurality of genes comprises at least nine genes. According to some embodiments, the plurality of genes comprises at least ten genes.

According to additional embodiments, the plurality of genes of the methods for predicting responsiveness of a subject to ΙΕΝβ treatment may include any subset or combination of the genes selected from the group consisting of: ABCB1, ABCF1, ALAS1, ATG16L1, BCL3, CASPl, CASP8, CCR6, CCR7, CD247, CD28, CD36, CD40LG, CD44, CD5, CD6, CD7, CD8A, CD99, CMKLRl, CUL9, CX3CR1, CXCR4 ,EEF1G, FYN, GFIl, GP1BB, ICAM1, IFI35 ,IFNAR2, IFNGR1, IL10RA, IL11RA, IL18R1, IL18RAP, IL1RL1, IL22RA2, IL2RB, IL4R, ILF3, IRAKI, IRAK2, JAKl, KLRBl, LITAF, MAP4K2, MAPK14, MAPKAPK2, MUCl, NFATCl, NFKB2, PDCDl, POLR2A, PPIA, PRDMl, PTGER4, PTK2, RELA, RELB, RPL19, RUNXl, SH2D1A, SKI, SLAMFl, SMAD3, SRC, STAT3, STAT4, STAT5A, TBKl, TGFB l, TGFBR2, TNFAIP3, TNFRSF13C, TNFRSF9, TNFSF8, TRAF1, TRAF3, TUBB and ZEBl.

According to some embodiments, the plurality of genes comprises or consists or at least one of JAK1, IFNAR2 and/or SKI. Each possibility is a separate embodiment.

According to some embodiments, the plurality of genes comprises or consists of one or more of JAK1, IFNAR2 and/or SKI. Each possibility is a separate embodiment.

According to some embodiments, the plurality of genes is selected from JAK1, IFNAR2, SKI, or subsets thereof. Each possibility is a separate embodiment.

According to some embodiments, the plurality of genes comprises no more than 25 genes, no more than 30 genes, no more than 35 genes, no more than 40 genes, no more than 45 genes, no more than 50 genes, no more than 55 genes, no more than 60 genes, no more than 65 genes, no more than 70 genes, no more than 75 genes, no more than 80 genes, no more than 85 genes, no more than 90 genes, no more than 95 or alternatively no more than 100 genes.

According to another embodiment, the sample obtained from the subject is a fluid sample. According to specific embodiments, the fluid sample is selected from blood, plasma, cerebrospinal fluid (CSF) or serum. According to another embodiment, the fluid sample is selected from blood, plasma or serum. According to another embodiment, said sample comprises peripheral blood mononuclear cells (PBMC).

According to some embodiments, the methods are performed ex-vivo. According to some embodiments, the methods are performed ex-vivo on a sample obtained from the subject.

According to some embodiments of the methods of the invention, said significant difference comprises a reduced expression level of at least one gene compared to the control value. According to additional embodiments, said significant difference comprises an increased expression level of at least one gene compared to the control value. According to yet another embodiment, said significant difference comprises an increased expression level of at least one gene and a reduced expression level of at least one gene compared to the control value.

According to additional embodiments of the methods of the invention, the control value is selected from the group consisting of a value obtained from a sample from at least one individual, a panel of control samples from a set of individuals, and a stored set of data from control individuals.

With respect to the methods for predicting responsiveness to IFN treatment the control value may be obtained from at least one interferon responder subject or, in some embodiments, from at least one interferon non-responder subject. According to another embodiment, the control values are measured in the subject or in a control sample obtained from said subject at an earlier time point. In a specific embodiment, the control sample is obtained from said subject prior to IFN treatment. In yet another specific embodiment, the control sample is obtained prior to first treatment of said subject with IFN.

According to another embodiment, the sample is obtained at least once prior to IFN treatment. According to specific embodiments, said prior to IFN treatment denotes prior to the first IFN treatment of said subject. According to another embodiment, said sample is obtained not more than about two hours before IFN treatment. According to another embodiment, the sample is obtained at least once after IFN treatment. According to another embodiment, the sample is obtained not more than 4, 3 or 2 hours following IFN treatment.

According to another embodiment, the sample is obtained at least once prior to IFN treatment and at least once following IFN treatment. According to a particular embodiment, a significant difference between the expression level of the plurality of genes in said sample compared to a control value obtained from said subject at an earlier time point is indicative of the responsiveness of said subject to IFN treatment.

With respect to the methods for diagnosing MS, the control value is typically obtained from healthy control (i.e., not afflicted with MS or any other inflammatory or autoimmune disease).

A "significant difference" between the sample and control expression level refers, in different embodiments, to a statistically significant difference, or in other embodiments to a significant difference as recognized by a skilled artisan. A significantly smaller or larger increase in expression level refers, in different embodiments, to a statistically significant difference, or to a significant difference as recognized by a skilled artisan. "Responders versus non-responders" as used herein refers, in different embodiments, to a value corresponding to at least one samples obtained from a responder individual versus a value corresponding to at least one samples obtained from a responder individual, or a stored set of data from said individuals. Advantageously, the methods of the invention may employ the use of learning and pattern recognition analyzers, clustering algorithms and the like, in order to discriminate between expression patterns of control subjects to subject being responsive to interferon treatment. As such, this term specifically includes a difference measured by, for example, determining the expression levels of the genes of the invention in a test sample, and comparing the resulting expression pattern to the expression pattern of negative and/or positive control samples using such algorithms and/or analyzers. The difference may also be measured by comparing the reactivity pattern of the test sample to a predetermined classification rule obtained in such manner.

Thus, in another embodiment, a significant difference between the expression pattern of a test sample compared to an expression pattern of a control sample, wherein the difference is computed using a learning and pattern recognition algorithm, indicates that the responsiveness of the subject to IFN treatment. For example, the algorithm may include, without limitation, supervised or non-supervised classifiers including statistical algorithms including, but not limited to, principal component analysis (PC A), partial least squares (PLS), multiple linear regression (MLR), principal component regression (PCR), discriminant function analysis (DFA) including linear discriminant analysis (LDA), and cluster analysis including nearest neighbor, artificial neural networks, coupled two-way clustering algorithms, multi-layer perceptrons (MLP), generalized regression neural network (GRNN), fuzzy inference systems (FIS), self-organizing map (SOM), genetic algorithms (GAS), neuro-fuzzy systems (NFS), adaptive resonance theory (ART). In an exemplary embodiment, said algorithm is linear discriminant analysis (LDA).

The term "subject" as used herein refers to a mammal, preferably a human. In yet another particular embodiment, the subject (e.g., with respect to the method for IFN treatment prediction) is a male subject. According to some embodiments of the invention, the subject is diagnosed with a pathology (disease, disorder or condition) which requires interferon treatment such as an autoimmune disease (e.g., MS), a viral infection (e.g., hepatitis C virus (HCV) infection) or cancer. In some embodiments, a subject is a male. In some embodiments, the subject is a female.

As used herein the phrase "predicting responsiveness of a subject to interferon treatment" refers to determining the likelihood that the subject will respond to interferon treatment, e.g., the success or failure of interferon treatment. As used herein the term "interferon" or "IFN" which is interchangeably used herein, refers to a synthetic, recombinant or purified interferon, and encompasses interferon type I (in human include IFN-a (GenBank Accession No. NM_024013 and NP_076918), interferon alpha 2a (GenBank Accession No. NM_000605 and NP_000596), IFN-β (GenBank Accession No. NM_002176 and NP_002167), interferon beta la (AVONEX (Biogen Idee); REBIF (EMD Serono)) or interferon beta lb (BETASERON) and IFN-co (GenBank Accession No. NM_002177 and NP_002168), which bind to the cell surface receptor complex IFN-a receptor (IFNAR) consisting of IFNAR1 and IFNAR2 chains; interferon type II (in human is IFN-γ (GenBank Accession No. NM_000619 and NP_000610), which binds to the IFNGR receptor; and interferon type III, which bind to a receptor complex consisting of IL10R2 (also called CRF2-4) and IFNLR1 (also called CRF2-12).

As used herein the phrase "interferon treatment" refers to administration of interferon into a subject in need thereof. It should be noted that administration of interferon may comprise a single or multiple dosages, as well as a continuous administration, depending on the pathology to be treated and the subject receiving the treatment. As used herein the term "interferon beta treatment" refers to administration of interferon beta into a subject in need thereof. It should be noted that administration of interferon beta may comprise a single or multiple dosages, as well as a continuous administration, depending on the pathology to be treated and the subject receiving the treatment.

Various modes of interferon administration are known in the art. These include, but are not limited to, injection (e.g., using a subcutaneous, intramuscular, intravenous, or intradermal injection), intranasal administration and oral administration.

According to some embodiments of the invention, interferon treatment is provided to the subject in doses matching his weight, at a frequency of once a week, for a period of up to 48 weeks.

Interferon is used in the treatment of various pathologies such as autoimmune disorders (e.g., multiple sclerosis using e.g., interferon beta-la and/or interferon beta-lb), various cancers (e.g., hematological malignancy, leukemia and lymphomas including hairy cell leukemia, chronic myeloid leukemia, nodular lymphoma, cutaneous T-cell lymphoma, recurrent melanomas, using e.g., recombinant IFN-a2b), and viral infections (e.g., hepatitis C virus infection, hepatitis B virus infection, viral respiratory diseases such as cold and flu).

The term "response" to IFN treatment refers to an improvement in at least one relevant clinical parameter as compared to an untreated subject (or a panel of subjects) diagnosed with the same pathology (e.g., the same type, stage, degree and/or classification of the pathology), or as compared to the clinical parameters of the same subject prior to interferon treatment. For example, a successful interferon treatment in multiple sclerosis patients can result in slowing disease progression and activity in relapsing-remitting multiple sclerosis and reducing attacks in secondary progressive multiple sclerosis.

In some embodiments, the response assessment may be focused on extreme clinical phenotypes to maximize the ability to detect differences. In some embodiments, responders may be defined as subjects who had no relapses and no change in the EDSS over a determined period. In some embodiments, Non-responders may be defined as subjected who experienced at least 2 relapses or an increase in EDSS of at least 1 point during a determined period.

The term "sample" as used herein means a sample of biological tissue or fluid or an excretion sample that comprises nucleic acids. Such samples include, but are not limited to, tissue or fluid isolated from subjects. Biological samples may also include sections of tissues such as biopsy and autopsy samples, frozen sections, blood, plasma, serum, sputum, stool and mucus. A biological sample may be provided by removing a sample of cells from an animal, but can also be accomplished by using previously isolated cells (e.g., isolated by another person, at another time, and/or for another purpose), or by performing the methods described herein in vivo. Archival tissues, such as those having treatment or outcome history, may also be used. As used herein, a "sample" or "biological sample" refers to a sample of biological tissue, fluid or excretion that comprises nucleic acids (e.g., RNA). It should be noted that a "biological sample obtained from the subject" may also optionally comprise a sample that has not been physically removed from the subject. In some embodiments the sample obtained from the subject is a body fluid or excretion sample including but not limited to seminal plasma, blood, serum, urine, prostatic fluid, seminal fluid, semen, the external secretions of the skin, respiratory, intestinal, and genitourinary tracts, tears, cerebrospinal fluid, sputum, saliva, milk, peritoneal fluid, pleural fluid, peritoneal fluid, cyst fluid, lavage of body cavities, broncho alveolar lavage, lavage of the reproductive system and/or lavage of any other organ of the body or system in the body, and stool.

Numerous well known tissue or fluid collection methods can be utilized to collect the biological sample from the subject in order to determine the expression level of the biomarkers of the invention in said sample of said subject. Examples include, but are not limited to, blood sampling, urine sampling, stool sampling, sputum sampling, aspiration of pleural or peritoneal fluids, fine needle biopsy, needle biopsy, core needle biopsy and surgical biopsy, and lavage. Regardless of the procedure employed, once a biopsy/sample is obtained the level of the biomarkers can be determined and a diagnosis can thus be made. Tissue samples are optionally homogenized by standard techniques e.g. sonication, mechanical disruption or chemical lysis. Tissue section preparation for surgical pathology can be frozen and prepared using standard techniques. In situ hybridization assays on tissue sections are performed in fixed cells and/or tissues.

As used herein, the terms "nucleic acid" and "polynucleotide" are used interchangeably, and include polymeric forms of nucleotides of any length, either deoxyribonucleotides or ribonucleotides, or analogs thereof. The following are non- limiting examples of polynucleotides: a gene or gene fragment, exons, introns, messenger RNA (mRNA), microRNA transfer RNA (tRNA), ribosomal RNA (rRNA), ribozymes, cDNA, recombinant polynucleotides, branched polynucleotides, plasmids, vectors, isolated DNA of any sequence, isolated RNA of any sequence, nucleic acid probes, and primers. A polynucleotide may comprise modified nucleotides, such as methylated nucleotides and nucleotide analogs. The sequence of nucleotides may be interrupted by non-nucleotide components. A polynucleotide may be further modified after polymerization, such as by conjugation with a labeling component. The term also includes both double- and single- stranded molecules.

As used herein, the phrase "level of expression" refers to the degree of gene expression and/or gene product activity in a specific cell. For example, up-regulation or down-regulation of various genes can affect the level of the gene product (i.e., RNA and/or protein) in a specific cell. In some embodiments, the level of expression is increased. In some embodiments, the level of expression is reduced.

Typically, determining the expression levels of the genes of the invention may comprise detection of the expression or expression levels of specific polynucleotides via any means known in the art, and as described herein. In some embodiments, the methods of the invention are preformed by employing at least one nucleotide probe or at least one primer, preferably a primer pair. Typically, the nucleotide probe or primer is suitable for detecting the expression or expression levels of a specific gene of the present invention.

According to certain embodiments, determining the expression levels comprises determining the ribonucleic acid (RNA) expression levels of said plurality of biomarkers. According to some embodiment, the methods of the invention may further optionally include amplifying (e.g., using a primer pair) the plurality of genes of the invention. According to typical embodiments, amplifying the plurality of genes is performed by polymerase chain reaction (PCR). According to another embodiment, the PCR is reverse transcriptase PCR (RT-PCR). According to another embodiment, the PCR is real-time PCR. According to another embodiment, the PCR is a quantitative real-time PCR (qRT-PCR).

According to some embodiments, detecting the RNA expression levels of the genes in a biological sample comprises hybridizing at least one probe capable of recognizing a biomarker of the present invention with nucleic acid isolated from the biological sample, and detecting a hybridization complex; wherein the level of the hybridization complex correlates with the level of said biomarker in the biological sample. According to additional embodiments, determining the RNA levels is performed using in situ hybridization (ISH). According to another embodiment, determining the RNA levels is performed using fluorescent in situ hybridization (FISH).

Hybridization assays

Detection of a nucleic acid of interest, or its expression levels, in a biological sample

(e.g., RNA) may optionally be effected by hybridization-based assays using an oligonucleotide probe. Traditional hybridization assays include PCR, reverse-transcriptase PCR, real-time PCR, RNase protection, in-situ hybridization, primer extension, dot or slot blots (RNA), and Northern blots (i.e., for RNA detection). More recently, PNAs have been described (Nielsen et al. 1999, Current Opin. Biotechnol. 10:71-75). Other detection methods include kits containing probes on a dipstick setup and the like.

The term "probe" refers to a labeled or unlabeled oligonucleotide capable of selectively hybridizing to a target or template nucleic acid under suitable conditions. Typically, a probe is sufficiently complementary to a specific target sequence contained in a nucleic acid sample to form a stable hybridization duplex with the target sequence under a selected hybridization condition, such as, but not limited to, a stringent hybridization condition. A hybridization assay carried out using the probe under sufficiently stringent hybridization conditions permits the selective detection of a specific target sequence. For use in a hybridization assay for the discrimination of single nucleotide differences in sequence, the hybridizing region is typically from about 8 to about 100 nucleotides in length. Although the hybridizing region generally refers to the entire oligonucleotide, the probe may include additional nucleotide sequences that function, for example, as linker binding sites to provide a site for attaching the probe sequence to a solid support or the like, as sites for hybridization of other oligonucleotides, as restriction enzymes sites or binding sites for other nucleic acid binding enzymes, etc. In certain embodiments, a probe of the invention is included in a nucleic acid that comprises one or more labels (e.g., a reporter dye, a quencher moiety, etc.), such as a 5'-nuclease probe, a FRET probe, a molecular beacon, or the like, which can also be utilized to detect hybridization between the probe and target nucleic acids in a sample. In some embodiments, the hybridizing region of the probe is completely complementary to the target sequence. However, in general, complete complementarity is not necessary (i.e., nucleic acids can be partially complementary to one another); stable duplexes may contain mismatched bases or unmatched bases. Modification of the stringent conditions may be necessary to permit a stable hybridization duplex with one or more base pair mismatches or unmatched bases. Sambrook et al., Molecular Cloning: A Laboratory Manual, 3rd Ed., Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y. (2001), which is incorporated by reference, provides guidance for suitable modification. Stability of the target/probe duplex depends on a number of variables including length of the oligonucleotide, base composition and sequence of the oligonucleotide, temperature, and ionic conditions. One of skill in the art will recognize that, in general, the exact complement of a given probe is similarly useful as a probe. One of skill in the art will also recognize that, in certain embodiments, probe nucleic acids can also be used as primer nucleic acids. Exemplary probe nucleic acids include 5'-nuclease probes, molecular beacons, among many others known to persons of skill in the art.

As used herein, "hybridization" refers to a reaction in which at least one polynucleotide reacts to form a complex that is stabilized via hydrogen bonding between the bases of the nucleotide residues. The hydrogen bonding may occur by Watson-Crick base pairing, in any other sequence-specific manner. A hybridization reaction may constitute a step in a more extensive process, such as the initiation of a PCR reaction.

Hybridization reactions can be performed under conditions of different stringency. Under stringent conditions, nucleic acid molecules at least 60%, 65%, 70%, 75% identical to each other remain hybridized to each other. A non-limiting example of highly stringent hybridization conditions is hybridization in 6 * sodium chloride/sodium citrate (SSC) at approximately 450C, followed by one or more washes in 0.2* SSC and 0.1% SDS at 5O ⁰ C, at 55°C, or at about 6O ⁰ C or more. When hybridization occurs in an antiparallel configuration between two single- stranded polynucleotides, those polynucleotides are described as complementary.

Hybridization based assays which allow the detection of a biomarker of interest in a biological sample rely on the use of probe(s) which can be 10, 15, 20, or 30 to 100 nucleotides long optionally from 10 to 50, or from 40 to 50 nucleotides long.

Thus, the polynucleotides of the biomarkers of the invention, according to at least some embodiments, are optionally hybridizable with any of the herein described nucleic acid sequences under moderate to stringent hybridization conditions.

The detection of hybrid duplexes can be carried out by a number of methods. Typically, hybridization duplexes are separated from unhybridized nucleic acids and the labels bound to the duplexes are then detected. Such labels refer to radioactive, fluorescent, biological or enzymatic tags or labels of standard use in the art. A label can be conjugated to either the oligonucleotide probes or the nucleic acids derived from the biological sample.

Probes can be labeled according to numerous well known methods. Non-limiting examples of detectable markers include ligands, fluorophores, chemiluminescent agents, enzymes, and antibodies. Other detectable markers for use with probes, which can enable an increase in sensitivity of the method of the invention, include biotin and radio-nucleotides. It will become evident to the person of ordinary skill that the choice of a particular label dictates the manner in which it is bound to the probe.

For example, oligonucleotides according to at least some embodiments of the present invention can be labeled subsequent to synthesis, by incorporating biotinylated dNTPs or rNTP, or some similar means (e.g., photo-cross-linking a psoralen derivative of biotin to RNAs), followed by addition of labeled streptavidin (e.g., phycoerythrin-conjugated streptavidin) or the equivalent. Alternatively, when fluorescently-labeled oligonucleotide probes are used, fluorescein, lissamine, phycoerythrin, rhodamine (Perkin Elmer Cetus), Cy2, Cy3, Cy3.5, Cy5, Cy5.5, Cy7, FluorX (Amersham) and others (e.g., Kricka et al. (1992), Academic Press San Diego, Calif) can be attached to the oligonucleotides. Preferably, detection of the biomarkers of the invention is achieved by using TaqMan assays, preferably by using combined reporter and quencher molecules (Roche Molecular Systems inc.).

Although the present invention is not specifically dependent on the use of a label for the detection of a particular nucleic acid sequence, such a label might be beneficial, by increasing the sensitivity of the detection. Furthermore, it enables automation. Probes can be labeled according to numerous well known methods.

As commonly known, radioactive nucleotides can be incorporated into probes of the invention by several methods. Non-limiting examples of radioactive labels include 3H, 14C, 32P, and 35S.

Those skilled in the art will appreciate that wash steps may be employed to wash away excess target polynucleotide or probe as well as unbound conjugate. Further, standard heterogeneous assay formats are suitable for detecting the hybrids using the labels present on the oligonucleotide primers and probes.

It will be appreciated that a variety of controls may be usefully employed to improve accuracy of hybridization assays. For instance, samples may be hybridized to an irrelevant probe and treated with RNAse A prior to hybridization, to assess false hybridization.

Probes of the invention can be utilized with naturally occurring sugar-phosphate backbones as well as modified backbones including phosphorothioates, dithionates, alkyl phosphonates and a-nucleotides and the like. Probes of the invention can be constructed of either ribonucleic acid (RNA) or deoxyribonucleic acid (DNA).

An additional NAT test known in the art is Fluorescence In Situ Hybridization (FISH). FISH uses fluorescent single-stranded DNA or RNA probes which are complementary to the nucleotide sequences that are under examination (genes, chromosomes or RNA). These probes hybridize with the complementary nucleotide and allow the identification of the chromosomal location of genomic sequences of DNA or RNA.

Detection of a nucleic acid of interest in a biological sample may also optionally be effected by NAT-based assays, which involve nucleic acid amplification technology, such as PCR for example (or variations thereof such as real-time PCR for example).

As used herein, a "primer" defines an oligonucleotide which is capable of annealing to (hybridizing with) a target sequence, thereby creating a double stranded region which can serve as an initiation point for DNA synthesis under suitable conditions. Although other primer nucleic acid lengths are optionally utilized, they typically comprise hybridizing regions that range from about 8 to about 100 nucleotides in length. Short primer nucleic acids generally utilize cooler temperatures to form sufficiently stable hybrid complexes with template nucleic acids. A primer nucleic acid that is at least partially complementary to a subsequence of a template nucleic acid is typically sufficient to hybridize with the template for extension to occur. A primer nucleic acid can be labeled (e.g., a SCORPION primer, etc.), if desired, by incorporating a label detectable by, e.g., spectroscopic, photochemical, biochemical, immunochemical, chemical, or other techniques. To illustrate, useful labels include radioisotopes, fluorescent dyes, electron-dense reagents, enzymes (as commonly used in ELISAs), biotin, or haptens and proteins for which antisera or monoclonal antibodies are available. Many of these and other labels are described further herein and/or otherwise known in the art. One of skill in the art will recognize that, in certain embodiments, primer nucleic acids can also be used as probe nucleic acids.

Amplification of a selected, or target, nucleic acid sequence may be carried out by a number of suitable methods (e.g., Kwoh et al., 1990, Am. Biotechnol. Lab. 8: 14). Numerous amplification techniques have been described and can be readily adapted to suit particular needs of a person of ordinary skill. Non-limiting examples of amplification techniques include polymerase chain reaction (PCR), ligase chain reaction (LCR), strand displacement amplification (SDA), transcription-based amplification, the q3 replicase system and NASBA (Kwoh et al., 1989, Proc. Natl. Acad. Sci. USA 86, 1173-1177; Lizardi et al, 1988, BioTechnology 6:1197-1202; Malek et al, 1994, Methods Mol. Biol, 28:253-260; and Sambrook et al., 1989, supra).

The terminology "amplification pair" (or "primer pair") refers herein to a pair of oligonucleotides according to at least some embodiments of the present invention, which are selected to be used together in amplifying a selected nucleic acid sequence by one of a number of types of amplification processes, preferably a polymerase chain reaction. Other types of amplification processes include ligase chain reaction, strand displacement amplification, or nucleic acid sequence-based amplification, as explained in greater detail below. As commonly known in the art, the oligos are designed to bind to a complementary sequence under selected conditions.

In one particular embodiment, amplification of a nucleic acid sample from a patient is amplified under conditions which favor the amplification of the most abundant differentially expressed nucleic acid. In one embodiment, RT-PCR is carried out on an RNA sample from a patient under conditions which favor the amplification of the most abundant RNA. In another embodiment, the amplification of the differentially expressed nucleic acids is carried out simultaneously. It will be realized by a person skilled in the art that such methods could be adapted for the detection of differentially expressed proteins instead of differentially expressed nucleic acid sequences.

In particular embodiments, TagMan® microRNA assay may be used for evaluating the expression levels of the microRNAs panel of the invention. Non limiting examples for evaluating the expression level of the microRNAs of the invention are TagMan® microRNA assay ID 001533 for evaluating miR566, assay ID 000186 for evaluating miR96, assay ID 002269 for evaluating miR183, assay ID 000493 for evaluating miR194, assay ID 001502 for evaluating miR200a, assay ID 002251 for evaluating miR200b, assay ID 002300 for evaluating miR200c, assay ID 000507 evaluating miR203, and assay ID 001024 for evaluating miR429.

The nucleic acid (e.g., RNA) for practicing the present invention may be obtained according to well known methods.

Oligonucleotide primers according to at least some embodiments of the present invention may be of any suitable length, depending on the particular assay format and the particular needs and targeted genomes employed. Optionally, the oligonucleotide primers are at least 12 nucleotides in length, preferably between 15 and 24 molecules, and they may be adapted to be especially suited to a chosen nucleic acid amplification system. As commonly known in the art, the oligonucleotide primers can be designed by taking into consideration the melting point of hybridization thereof with its targeted sequence (Sambrook et al., 1989, Molecular Cloning -A Laboratory Manual, 2nd Edition, CSH Laboratories; Ausubel et al., 1989, in Current Protocols in Molecular Biology, John Wiley & Sons Inc., N.Y.).

The polymerase chain reaction and other nucleic acid amplification reactions are well known in the art. The pair of oligonucleotides according to this aspect of the present invention are preferably selected to have compatible melting temperatures (Tm), e.g., melting temperatures which differ by less than that 7 °C, preferably less than 5 °C, more preferably less than 4 °C, most preferably less than 3 °C, ideally between 3 °C and 0 °C.

Polymerase Chain Reaction (PCR)

The polymerase chain reaction (PCR), as described in U.S. Pat. Nos. 4,683,195 and 4,683,202 to Mullis and Mullis et al., is a method of increasing the concentration of a segment of target sequence in a mixture of genomic DNA without cloning or purification. This technology provides one approach to the problems of low target sequence concentration. PCR can be used to directly increase the concentration of the target to an easily detectable level. This process for amplifying the target sequence involves the introduction of a molar excess of two oligonucleotide primers which are complementary to their respective strands of the double- stranded target sequence to the DNA mixture containing the desired target sequence. The mixture is denatured and then allowed to hybridize. Following hybridization, the primers are extended with polymerase so as to form complementary strands. The steps of denaturation, hybridization (annealing), and polymerase extension (elongation) can be repeated as often as needed, in order to obtain relatively high concentrations of a segment of the desired target sequence.

The length of the segment of the desired target sequence is determined by the relative positions of the primers with respect to each other, and, therefore, this length is a controllable parameter. Because the desired segments of the target sequence become the dominant sequences (in terms of concentration) in the mixture, they are said to be "PCR-amplified". The following examples are presented in order to more fully illustrate some embodiments of the invention. They should, in no way be construed, however, as limiting the broad scope of the invention.

EXAMPLES

Methods:

Patients

Diagnosis and Follow Up

Diagnosis is based on established clinical and, when necessary, laboratory criteria. The presence of gadolinium-enhancing lesions on Magnetic Resonance Imaging (MRI) indicates current sites of presumed inflammatory demyelination (active lesions). Cerebrospinal fluid (CSF) analysis shows increased intrathecal synthesis of immunoglobulins of restricted specificity with moderate lymphocytic pleocytosis in approximately 80% of MS patients.

The Expanded Disability Status Scale (EDSS) was established in order to rate the degree of disability according to the various clinical symptoms (see Table 2). At present, EDSS is the gold standard for rating disease disability in clinical routine. Further tools to assess disease activity and severity are the clinical relapse rate and contrast-enhancing MRI scans.

Table 2: Kurtzke Expanded Disability Status Scale (EDSS)

Ambulatory without aid or rest for about 200 m; disability severe enough to impair0

full daily activities (work a full day without special provisions)

Ambulatory without aid or rest for about 100 m; disability severe enough to preclude5

full daily activities

Intermittent or unilateral constant assistance (cane, crutch, brace) required to walk0

about 100 m with or without resting

Constant bilateral assistance (canes, crutches and braces) required to walk about5

20 m without resting

Unable to walk beyond approximately 5 m even with aid, essentially restricted to0 wheelchair; wheels self in standard wheelchair and transfers alone; up and about in wheelchair some 12 hours a day

Unable to take more than a few steps; restricted to wheelchair; may need aid in5 transfer; wheels self but cannot carry on in standard wheelchair a full day; may require motorized wheelchair

Essentially restricted to bed or chair or perambulated in wheelchair, but may be out0 of bed itself much of the day; retains many selfcare functions; generally has effective use of arms

Essentially restricted to bed much of day; has some effective use of arms retains5

some selfcare functions

0 Confined to bed; can still communicate and eat

5 Totally helpless bed patient; unable to communicate effectively or eat/swallow

.0 Death due to MS

Inclusion Criteria

The patients suffer from clinically definite RRMS about to start IFN β therapy. (The patients about to start IFN β therapy serve as a baseline for standardization as well as reference for prospective studies)

Patients who have had at least 2 documented relapses over the 2 years prior to treatment onset.

Patients with at least 8 months of follow up clinical data

All patients have to sign an informed consent.

Exclusion criteria 1. Patients treated with other immunosuppressive medications during a period of 6 months prior to the inclusion.

2. Patients unable to sign an informed consent.

3. Patients with other systemic autoimmune diseases.

4. Female patients during pregnancy or having delivered during the last 3 months prior to the inclusion.

Response assessment

The patients who had no relapses and no change in the EDSS over a one year follow up period, were defined as Responders and those who had no decrease in the relapse rate during the one year treatment period or had an increase in EDSS of at least 1 point, were defined as Non-responders. Disability data was collected at 3 month intervals. EDSS was defined at each visit by experienced neurologists from the MS center. A relapse was defined as a new symptom or worsening of a preexisting symptom attributable to MS activity, confirmed by neurological examination. MRI served as a surrogate marker for detection of sub clinical disease activity and the response to IFN β treatment.

Isolation of PBMC

For each patient, 8 cc of blood has been collected in EDTA tubes (a total of 2 tubes). The peripheral blood mononuclear cells (PBMC) were purified from the fresh peripheral blood specimens employing a density step gradient (Ficolle-Hypaque density gradient centrifugation, Pharmacia LKB Biotechnology, Piscataway, NJ): The PBMCs were trapped at the interface of the aqueous layer and the Ficoll following a 20 minute centrifugation step. Then they were recovered from the interface and washed twice with PBS (Phosphate Buffered Saline). Samples were frozen in 1000 μΐ of Tri-reagent.

RNA Extraction

RNA was extracted from PBMCs using Tri-reagent (Sigma):

1. The PBMC samples were defrosted and homogenized. 200 μΐ of Chloroform (Bio- Lab LTD.) was added to each sample.

2. The samples were centrifuged in 4°C at a speed of 18000 cycles per minute. Three phases were formed: The lowest, which contained the red phenol, the middle, which contained DNA and proteins (cellular particles) and the upper, which contained the RNA.

The upper phase was separated and frozen for 5 minutes in liquid nitrogen after addition of 0.5 ml of Ethanol 100% (Bio-Lab LTD.).

RNA was precipitated by two centrifugations at 18000 cycles per minute together with 1 ml of 70% Ethanol.

RNA was dried in room air and dissolved in 40 μΐ of nuclease free water (Bio Labs LTD.).

In order to dispose of remains of genomic DNA, which could later disrupt with the results, the RNA was subjected to DNAse treatment (RQ1 Promega) according to manufacturer instructions.

The Integrity of the RNA Was Confirmed by Gel Electrophoresis: The gel consisted of 50 ml of 1 % TAE (Tris base, Acetic acid and EDTA) Buffer (Biological Industries, Beit Haemek) with 0.5 g of Agarose (Cambrex) and 5μ1 of Ethidium Bromide (Gene Choice).

Concentration and quality of the RNA was measured using a spectrophotometer - Nanodrop 2000c (Thermo Fisher Scientific Inc.) with an optical density of OD260 nm. cDNA Preparation

cDNA was prepared using High Capacity cDNA Reverse Transcription Kit (Applied Biosystems) with 500ng of total RNA and random hexamers according to the manufacturer's protocol. Real Time RT PCR

Gene amplification was carried out using Taqman Probes of the relevant genes. The PCR reaction included Ιμΐ of cDNA, 0.75μ1 of each Taqman probe and 7.5μ1 of TaqMan Gene expression Master mix in a total volume of 15 μΐ.

Gene amplification was carried out using ABI 7000 Sequence Detection System (Applied Biosystems) in 96 well plates. Amplification included 2 steps:

(1) 10 min at 95 °C (enzyme activation)

(2) 40 cycles of: 15 seconds at 95°C (denaturation) and 1 min at 60°C (annealing and extension). The results were normalized to the endogenous gene CDK1. All experiments were repeated for at least 3 times in triplicate.

Analysis of Real Time PCR Data

Real time PCR is used to amplify and simultaneously quantify a targeted cDNA molecule. In this study we used the TaqMan probes technique. In this method, the level of fluorescence rises logarithmically within each cycle until it reaches a plateau. The cycle in which the fluorescentic signal passes the threshold is called Cycle Threshold (CT). The threshold is automatically set within the exponential phase of the fluorescence emission by the Real time PCR software.

Calculations were based on Relative Quantification (2 ^A ACt method). CDK1 was chosen as endogenous control gene, because its expression is steady regardless of treatment or patient.

Calculation was applied by the following formula:

The ACT (Difference in Cycle threshold) was calculated by applying the equation: CT (tested gene) - CT (endogenous control; CDK1).

Next, the equation 2 ^{" (ACT)} was applied.

Nanostring nCounter® technology

RNA was extract from PBMCs isolated from blood that was withdrawn from naive patients or from treated patients on treatment before the next INF injection.

The RNA was subjected to nCounter® Kit which include either selected genes and endogenous controls genes based on our preliminary results, or a comprehensive set of 526 human genes known to be differentially expressed in immunology (nCounter code set panel). This allowed profiling of gene expression of the different groups.

The nanostring technology is well known in the art. In detail, this technology may be practiced as follows: A multiplexed probe library is made with two sequence-specific probes for each gene of interest. The first probe, a capture probe, contains a 35- to 50-base sequence complementary to a particular target mRNA plus a short common sequence coupled to an affinity tag such as biotin. The second probe, the reporter probe, contains a second 35- to 50- base sequence complementary to the target mRNA, which is coupled to a color-coded tag that provides the detection signal. The tag consists of a single-stranded DNA molecule, the backbone, annealed to a series of complementary in vitro transcribed RNA segments each labeled with a specific fluorophore. The linear order of these differently colored RNA segments creates a unique code for each gene of interest.

Unique pairs of capture and reporter probes are constructed to detect transcripts for each gene of interest. All probes are mixed together with total RNA in a single hybridization reaction that proceeds in solution. Hybridization results in the formation of tripartite structures, each comprised of a target mRNA bound to its specific reporter and capture probes. Unhybridized reporter and capture probes are removed by affinity purification, and the remaining complexes are washed across a surface that is coated with the appropriate capture reagent (e.g., streptavidin). After capture on the surface, an applied electric field extends and orients each complex in the solution in the same direction. The complexes are then immobilized in an elongated state and imaged. Each target molecule of interest is identified by the color code generated by the ordered fluorescent segments present on the reporter probe. The level of expression is measured by counting the number of codes for each mRNA.

Data Processing

The data was analyzed with the 2 following complementary approaches: discovery of associations among attribute groups using the Linear Correlation Discovery (LCD) process (Benis, A. and Courtine, M., 2011, Volume 696, Part 4, pp.327-334; Chiang et al, 2005, Data and Knowledge Engineering 53(3), 311-337) andheatmaps (Eisen, M. et al., 1995, Proc Natl Acad Sci USA 95, 14863-14868). The LCD and the heatmaps were built using R and its package gplots.

In this analysis, non-parametric statistic was used in order to overcome the lack of knowledge related to the bioclinical attributes distributions and to the gene expressions.

The Spearman's rank correlation coefficient value (rho) was computed for all the pair of bioclinical data and gene expression data. In order to overcome the limitation related to the heterogeneous set of individuals included into the research protocols, for each bioclinical attribute, "rho" was computed for subsets of others bio-clinical attributes. With this approach, 28875 relationships have been generated.

As an example for the Responder, "rho" was computed for men and women separately. As another example, for "women", "rho" was computed for patient having an EDSS lower to the EDSS median for the overall population. Even if FDR (Benjamini and Hochberg, 1995, Journal of the Royal Statistical Society 57, 289-300; also known as "q" Storey, J. 2002, Journal of the Royal Statistical Society: Series B (Statistical Methodology) 64(3), 479-498) values are not significant (q>0.05) it was considered as correlations having a high absolute value (and a low p-value (p<0.05)) which can be analyzed with some benefits by the biologists. Typically, (Efron, 2007, Journal of the American Statistical Association 102, 93-103), a high correlation value is sufficient in order to consider that a relationship / link between 2 attributes exist.

The analysis of the bioclinical data collected was conducted as a first step by the LCD process which is useful for determining the direction and strength of a relationship between the measured expression of each one of the 526 immune-related human genes and each one of the bioclinical parameters available for each included patient. Correlations with P >0.005 were selected in order to build heatmaps allowing the visual identification of patients with similar gene expression in a number of genes. The gene expression patterns were also examined according to different demographical (i.e., gender, age, class) and bioclinical (e.g treatments, disease status, EDSS) parameters. p<0.05 was considered as significant.

Pathway analysis was performed using QIAGEN's Ingenuity Pathway Analysis.

EXAMPLE 1 - The expression level of a gene cluster predicts the response of MS patients to interferon treatment The First dataset included 30 subjects (9 men and 21 women), aged between 21 and

55 year-old (average age 36+11), being diagnosed for multiple sclerosis between 2 and 21 years ago (average main disease duration of 7.7+5), and with an average expanded disability status scale (EDSS) of 3+1.1. 11 patients were treated with IFNp lb (Betaferon) and 19 were treated with IFNpia (12 with Avonex and 7 with Rebif). 16 patients were clinically classified as responders (with a good response to interferon) and 14 were classified as non-responders.

In order to allow a user-friendly visual analysis of the heatmap a Wilcoxon signed- rank test (non-parametric version of the t-test) has been run for each bio-clinical parameter and for each gene for the Responders / Non-Responders groups.

Analysis of the data obtained by the array-based gene expression of samples extracted from responders and non-responders revealed a significant correlation (Wilcoxon signed rank test, p <0.05) between expression of 80 genes and ΙΕΝβ treatment response. A group of 80 (15.1%) genes with p<=0.05 was observed: ABCB 1, ABCF1, ALAS1, ATG16L1, BCL3, CASP1, CASP8, CCR6, CCR7, CD247, CD28, CD36, CD40LG, CD44, CD5, CD6, CD7, CD8A, CD99, CMKLR1, CUL9, CX3CR1, CXCR4 ,EEF1G, FYN, GFI1, GP1BB, ICAM1, IFI35 FNAR2, IFNGR1, IL10RA, IL11RA, IL18R1, IL18RAP, IL1RL1, IL22RA2, IL2RB, IL4R, ILF3, IRAKI, IRAK2, JAKl, KLRB1, LITAF, MAP4K2, MAPK14, MAPKAPK2, MUC1, NFATC1, NFKB2, PDCD1, POLR2A, PPIA, PRDM1, PTGER4, PTK2, RELA, RELB, RPL19, RUNX1, SH2D1A, SKI, SLAMF1, SMAD3, SRC, STAT3, STAT4, STAT5A, TBK1, TGFB 1, TGFBR2, TNFAIP3, TNFRSF13C, TNFRSF9, TNFSF8, TRAF1, TRAF3, TUBB and ZEBl.

As seen in Figure 1, the above gene cluster demonstrated a significant differential expression between responders and non-responders. Figure 2 shows a more significant differential expression of the above gene cluster between responders and non-responders observed in male.

Further, as seen in Figure 3 a gene cluster of 22 genes with p<=0.01 was observed: ALAS1, CCR7, CD247, CD44, CD5, CMKLR1, CXCR4, EEF1G, IFNAR2, IL18R1, IL18RAP, IL2RB, JAKl, MAP4K2, RPL19, SKI, STAT4, STAT5A, TGFB 1, TRAF1, ZEB 1 and ZAP70. Figure 4 shows a remarkably significant differential expression of the gene cluster between responders and non-responders in men.

Moreover, a gene cluster of 8 genes with a more stringent cutoff of p<=0.005 was observed: JAKl, EEF1G, IFNAR2, MAP4K2, RPL19, SKI, ZEB l and ZAP70 (Figure 5). Figure 6 shows a remarkably significant differential expression of the gene cluster between responders and non-responders in men.

When Ingenuty pathway analysis was used, it was found that four genes (ZAP70, IFNAR2, ZEBl and JAKl) out of the 8 discriminating genes belong to the pathway of T lymphocyte differentiation.

Validation cohort

In order to validate the above results, the gene cluster was tested on another group of 47 patients, including 21 treated patients (10 females and 11 males), average age 41+10, with mean disease duration of 8.6+6.3 years (average +sd) and EDSS of 2.6+1.9 (average +sd). 1 patient was treated with IFNp ib (Betaferon), 20 with IFNp ia (19 with Avonex and 1 with Rebif). The validation cohort also included 26 untreated patients (18 females and 8 males), average age 35+7, with mean disease duration of 5+3.2 years (average +sd) and EDSS of 3.2+2.2 (average +sd). In the validation cohort,

In the validation cohort, analysis revealed that 3 of the 8 genes, namely, JAKl, IFNAR2 and SKI were able to discriminate highly significantly (p=0.01, p=0.028, p=0.045, respectively) between treated male responders and non-responders (Table 3, below). In general, the expression of these genes was upregulated in the responders.

Altogether, the final analysis included 77 individuals which included 31 sick female on treatment (blood was withdraw before the next injection), 18 sick females women, naive to the treatment (untreated), 20 sick males on treatment (blood was withdraw before the next injection), 8 men naive to treatment and 5 healthy controls.

Table 3 summarizes the T-test values of the comparisons of all tested groups. In addition to analyzing the differential expression between responders and non-responders, the differential expression between patients and healthy controls was also analyzed. This comparison generated a group of 5 genes (CD44, CXCR4, EEFIG, JAKl and MAP4K4) that were significantly differentially expressed in MS patients as compared to healthy controls (the significant results are highlighted).

Table 3: summary of the t-test values of all the compared groups.

Genes Female on Female Male on Male Patients Vs treatment baseline treatment baseline healthy controls

79 patients, 5

17R, 15NR 11R, 7NR 12R, 7NR 3R, 5NR

healthy controls

ALAS1 0.409 0.572 0.045 0.432 0.165

CCL23 0.714 0.402 0.108 0.771 0.224

CD274 0.581 0.335 0.094 0.716 0.120

CD44 0.788 0.102 0.075 0.012 0.040

CD5 0.680 0.100 0.125 0.694 0.229

CD7 0.220 0.428 0.092 0.671 0.201

CMKLR1 0.834 0.981 0.449 0.810 0.691

CXCR4 0.595 0.248 0.139 0.195 0.000

EEFIG 0.545 0.162 0.218 0.418 0.026

HLA-A 0.681 0.704 0.088 0.437 0.428

IFI16 0.646 0.052 0.421 0.764 0.565

IFNAR2 0.492 0.028 0.028 0.010 0.885

JAKl 0.869 0.156 0.001 0.256 0.001

MAP4K4 0.359 0.963 0.221 0.297 0.035

PTPN6 0.194 0.291 0.583 0.988 0.839

RPL19 0.882 0.194 0.087 0.098 0.104

SKI 0.619 0.156 0.045 0.426 0.299 STAT4 0.703 0.112 0.024 0.581 0.935

STAT5A 0.750 0.298 0.018 0.237 0.129

TGFB1 0.537 0.911 0.106 0.776 0.399

TRAF1 0.689 0.573 0.002 0.473 0.187

Accordingly, the LCD allows to discover 473 potentially interesting correlations having lrhol>=0.66, 6192 correlations having p<=0.05 wherein, 456 correlations having lrhol>=0.66 and p<=0.05.

The Wilcoxon test was further used to analyze the data received from all the above mentioned treated and non-treated patients (including those used for the validation experiment). The analysis discovered the following cluster of 15 genes found to differentiate (p<0.1) between interferon responder and non-responder patients: ABCB1, CCR6, CCR7, CD247, CD5, CMKLR1, IL18R1, IL18RAP, IRAK2, KLRB 1, MUC1, STAT4, ZEB 1, CMKLR1 and PLA2G2A. Out of the abovementioned 15 genes, the following genes are known to be expressed by Mucosal Associated Invariant T (MAIT) cells which are known in the art to play a role in Multiple Sclerosis: CCR6, ABCB1, CD247, CD5, IL18R1, IL18RAP and KLRB1.

As known in the art, human MAIT cells represent approximately 10% of mature CD8 or CD4-CD8- (DN) T cells in adults, express the semi-invariant T-cell receptor (TCR; iVa7.2-J(x33) and may be selected by the MHC class lb molecule, MR1 on hematopoietic cells. In humans, MAIT cells are defined as CD161hiIL-18Ra+Va7.2+y5-CD3+ lymphocytes. Either CD161 or IL-18Ra expression at the cell surface, together with the Va7.2 segment, allows for the unequivocal identification of MAIT cells in both peripheral blood and tissues. EXAMPLE 2 - JAK1 expression differentiates responders and non-responders as well as

MS patients and healthy individuals

Figure 7 shows that JAK1 expression can differentiate between responders (R) and non-responders (NR) as well as between MS patients and healthy individuals (C).

Figure 8 shows that JAK1 expression correlates with Multiple sclerosis disease severity scale (EDSS).

Although the invention has been described in conjunction with specific embodiments thereof, it is evident that many alternatives, modifications, and variations will be apparent to those skilled in the art. Accordingly, it is intended to embrace all such alternatives, modifications, and variations that fall within the spirit and broad scope of the appended claims.