Methods for determining basal fitness of mesenchymal stromal cells for use in treating an MSC-treatable disease

Abstract

The present disclosure provides methods for determining basal fitness of mesenchymal stromal cells (MSCs) using microRNA profiles from the MSCs. Also provided are methods of treating MSC-treatable diseases with MSCs with basal fitness identified by the methods disclosed herein. Further provided are methods of determining quantitative values for the microRNA profiles for assessing the basal fitness of a sample from a particular donor.

Description

METHODS FOR DETERMINING BASAL FITNESS OF MESENCHYMAL STROMAL CELLS FOR USE IN TREATING AN MSC-TREATABLE DISEASERelated Applications

[0001] This application claims the benefit of US provisional application 63 / 619,946, filed on January 11 , 2024, herein incorporated by reference.Incorporation of Sequence Listing

[0002] A computer readable form of the Sequence Listing “10723- P73094PC00_SequenceListing.txt” (61 ,593 bytes), filed herewith by electronic submission and created on January 10, 2025, is herein incorporated by reference.Field

[0003] The present disclosure relates to methods for determining basal fitness of mesenchymal stromal cells (MSCs) using microRNA profiles from the MSCs.Background

[0004] Knee osteoarthritis (OA) is a complex and heterogeneous joint disease estimated to affect 16% of adults over 40 years of age worldwide (1 ). Pathophysiological mechanisms of OA are not fully understood, but include abnormal mechanical loading, metabolic, and inflammatory factors (2, 3). Increasingly, the role of inflammation is recognized as a major contributing factor to OA symptomology and disease progression, with the joint synovium (consisting primarily of fibroblasts and macrophages) releasing pro-inflammatory factors that propagate the cartilage degradative cascade and contribute to patient symptoms (4, 5). In particular, monocytes / macrophages (MOs, indicating a mixed population containing both monocytes and macrophages) have been shown to represent the most abundant leukocyte population within the knee OA synovial fluid, and it has been shown that levels of the CD14+CD16+ (intermediate) MO subpopulation correlated to more severe patient-reported outcome measures (PROMs), indicating a key role of MO in OA disease pathology and symptomology (6).

[0005] Currently, there are no disease-modifying drugs available for OA, and patients rely on unsatisfactory symptom modification before resorting to total joint replacement at end stages of the disease (7). Culture-expanded mesenchymal stromal cells (MSCs), including those derived from bone marrow (MSC(M)), have emerged as a promising therapy for OA due to their multimodal mechanisms of action, which includechondroprotective / cartilage reparative, anti-fibrotic, and immunomodulatory functions (8- 10). However, despite hundreds of clinical trials, mixed reports on clinical efficacy and insufficient characterization of MSC potency have continued to hamper the field, resulting in very few MSC products with regulatory and market endorsement (31). In this vein, the International Society for Cell & Gene Therapy (ISCT) has emphasized a need for well- defined critical quality attributes (CQAs) that are sensitive, quantitative, relevant to mechanism of action, and validated for the specific disease indication (72, 13). This has been further emphasized by the recent US Food and Drug Administration (FDA) rejection of a MSC product, due in part to insufficient evidence for MSC mechanisms of action and clinically correlative CQAs (14).

[0006] In the context of OA, numerous preclinical studies have indicated MSCs act through immunomodulatory mechanisms (reviewed in (9, 15)). The inventors previously provided the first clinical evidence in support of immunomodulatory mechanism of action for autologous MSC(M), demonstrating significantly reduced levels of inflammatory cytokines and CD14+CD16+(intermediate) MO subpopulations within synovial fluid of OA patients at 3 months relative to baseline (11). Furthermore, panels of immunomodulatory genes and secreted factors measured in vitro were reported to be correlated to OA patient PROM improvements and may therefore serve as candidate CQAs that inform basal immunomodulatory fitness of MSCs (11 , 16).Summary

[0007] MicroRNAs (miRs) have emerged as an important mediator of MSC mechanisms of action (18). The value of miRs as CQAs for defining basal fitness of MSCs was unknown. The present inventors explored the relationship between microRNA (miR) levels in mesenchymal stromal (MSCs) and clinical outcomes following treatment with these cells, against a backdrop of donor heterogeneity. Using bone marrow-derived MSCs (MSC(M)), a statistical approach was employed to identify miRs that are correlated with clinical efficacy.

[0008] Accordingly, provided herein is a method of determining basal fitness of a sample of mesenchymal stromal cells (MSCs) comprising: determining a sample microRNA (miR) profile, the sample miR profile comprising the levels of at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69; anddetermining the level of similarity of said sample miR profile to one or more reference profiles, wherein (i) a high level of similarity of the sample miR profile to a basal fitness specific reference profile; (ii) a low level of similarity to a non-basal fitness specific reference profile; and / or (iii) a higher level of similarity to a basal fitness specific reference profile than to a non-basal fitness specific reference profile, indicates the cells have basal fitness.

[0009] In an embodiment, the miR profiles are analyzed using combinatorial or multivariate dimension reduction statistical or mathematical methods. The combinatorial or multivariate dimension reduction statistical or mathematical methods optionally comprise clustering analyses, machine learning analysis methods, or desirability analysis to enable comparisons between multivariate miR profiles with dimension-reduced empirical values.

[0010] In an embodiment, a higher level of similarity to the basal fitness specific reference profile than to the non-basal fitness specific reference profile is indicated by a higher correlation value computed between the sample profile and the basal fitness specific reference profile than an equivalent correlation value computed between the sample profile and the non-basal fitness specific reference profile, optionally wherein the correlation value is a correlation coefficient.

[0011] In some embodiments, the correlation coefficient is a linear correlation coefficient, optionally a Pearson correlation coefficient, or a monotonic correlation coefficient, optionally a Spearman’s correlation coefficient. In some embodiments, a high level of similarity to the reference profile is indicated by a Pearson correlation coefficient or a Spearman’s correlation coefficient between the sample profile and the reference profile having an absolute value between 0.5 to 1 , optionally between 0.75 to 1 , and a low level of similarity to the reference profile is indicated by a correlation coefficient between the sample profile and the reference profile having an absolute value between 0 to 0.5, optionally between 0 to 0.25.

[0012] Also provided herein is a method of determining quantitative values for a set of miRs for assessing basal fitness of a sample of mesenchymal stromal cells (MSCs), the method comprising:a) measuring levels of the set of microRNAs (miRs) for the sample, wherein the set of miRs comprises at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69; b) obtaining the basal fitness status of the sample; and c) conducting a regression analysis between each miR of a) with the basal fitness of b); determining minimum and maximum data values of each miR of the sample and using multivariate dimension reduction statistical or mathematical methods to assign minimization or maximization functions to indicate whether higher or lower values are desirable based on the directionality of correlation respectively.

[0013] In an embodiment, the method optionally further comprises d) assigning a weighting to each miR for desirability analysis based on the R2values from the regression analysis; and e) assigning a score from zero to one using desirability analysis to each sample based on the range of data values; wherein zero is undesirable and one is highly desirable to obtain a set of values for MSCs for each donor.

[0014] In an embodiment, the basal fitness status of the sample in step b) is obtained from a clinical sample for which the basal fitness or efficacy of the MSCs was previously evaluated clinically.

[0015] In another embodiment, the obtaining of the basal fitness status of the sample in step b) comprises:I) determining at least one patient-reported outcome measure (PROM) score from an assessment of an MSC-treatable disease from a subject with the MSC- treatable disease pre-treatment with the sample;II) determining the at least one PROM score from the assessment of the MSC- treatable disease from the subject post treatment with the sample;III) comparing the at least one PROM score in I) and II); andIV) assigning a basal fitness score to the sample based on the size of the improvement in the at least one PROM score post-treatment compared to pretreatment, wherein an improvement in the at least one PROM score posttreatment is indicative that the basal fitness score of the sample is high, and wherein no improvement or a worsening in the at least one PROM score posttreatment is indicative that the basal fitness score of the sample is low.

[0016] In an embodiment, step II) is performed 12 to 24 months post treatment with the sample.

[0017] In an embodiment, the MSC-treatable disease comprises osteoarthritis (OA), lupus, scleroderma, rheumatoid arthritis, graft versus host disease, stroke, inflammatory bowel disease, or cardiac disease.

[0018] In another embodiment, the MSC-treatable disease comprises OA.

[0019] In yet another embodiment, the OA comprises knee OA, and the assessment of the MSC-treatable disease comprises an assessment of knee OA.

[0020] In an embodiment, the assessment of knee OA comprises Knee injury and Osteoarthritis Outcome Score (KOOS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Visual Analogue Scale (VAS), Short Form 36 (SF-36) or Short Form 12 (SF-12), Tegner Lysholm Knee Score, Knee Society Clinical Rating System, Lequesne Index for Knee Osteoarthritis, Oxford Knee Score (OKS) and / or International Knee Documentation Committee (IKDC) Questionnaire.

[0021] In another embodiment, the assessment of knee osteoarthritis comprises KOOS, and the PROM score comprises KOOS Pain, KOOS Symptoms, function in daily living (ADL), function in Sport and Recreation (Sports / Rec), knee-related quality of life (QOL), or Overall KOOS, or combinations thereof.

[0022] Also provided herein is a method of determining basal fitness of a sample of mesenchymal stromal cells (MSCs) comprising a) determining a sample microRNA (miR) profile, the sample miR profile comprising the levels of at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69; and b) ranking the miR profile of a) based on a comparison of minimum and maximum values determined by the method disclosed herein for the same particular donor to determine the basal fitness.

[0023] In an embodiment, each miR of the at least one miR comprises a nucleic acid sequence selected from SEQ ID NOs: 1-33.

[0024] In another embodiment, each miR of the at least one miR comprises a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37.

[0025] In another embodiment, each miR of the at least one miR comprises a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32.

[0026] In yet another embodiment, each miR of the at least one miR comprises a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18- 20, 26, and 35.

[0027] In a further embodiment, the miR sample profile comprises the levels of 69 miRs, wherein the 69 miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 1-69.

[0028] In some embodiments, the MSCs are derived from adipose tissue, bone marrow, dental pulp, synovium, placenta, umbilical cord, or induced pluripotent stem cells.

[0029] In an embodiment, the MSCs are derived from bone marrow.

[0030] In another embodiment, the MSCs are derived from adipose tissue.

[0031] In yet another example, the MSCs are derived from induced pluripotent stem cells.

[0032] These and other features and advantages of the present disclosure will become apparent from the following detailed description taken together with the accompanying drawings. It should be understood, however, that the detailed description and specific examples, while indicating preferred implementations of the present disclosure, are given by way of illustration only, since various changes and modifications within the spirit and scope of the disclosure will become apparent to those of skill in the art from this detailed description.Brief Description of the Drawings

[0033] For a better understanding of the various embodiments described herein, and to show more clearly how these various embodiments may be carried into effect, reference will be made, by way of example, to the accompanying drawings which show at least one example embodiment, and which are now described. The drawings are not intended to limit the scope of the teachings described herein.

[0034] FIG. 1 shows a principal component analysis of microRNA (miR) expression profiles in synovial fluid-treated and untreated samples in an exampleembodiment of the disclosure. MSC(M) samples cluster by donor and responder status rather than by synovial fluid treatment.

[0035] FIGs. 2A-C show that miR-sequencing reveals differential miR expression profiles in responders versus non-responders in an example embodiment of the disclosure. FIG. 2A) Heatmap displaying 33 significantly differentially expressed miRs in MSC(M) derived from Function Responders versus Non-Responders. FIG. 2B) Heatmap displaying 14 significantly differentially expressed miRs in MSC(M) derived from Function-Pain Responders versus Non-Responders. Intensity scale indicates Log2 foldchange relative to the mean of Non-Responder samples. FIG. 2C) Venn diagram indicating 10 overlapping miRs in the differential expression panels for Function-Pain Responders versus Non-Responders and Function Responders versus NonResponders. N=10 MSC(M) donors treated with or without synovial fluid.

[0036] FIG. 3 shows a qPCR evaluation of expression levels of miR candidates identified based on miR-sequencing in Function Responders versus Non-Responders in an example embodiment of the disclosure. Select miR candidates that were significantly differentially expressed based on miR-sequencing were measured by qPCR in MSC(M) treated with or without late-stage OA synovial fluid (SF). Significant differential expression was confirmed for one candidate (hsa-miR-140-3p; SEQ ID NO:3) that was upregulated in MSC(M) derived from Function Responders versus Non-Responders, matching the miR-sequencing results. N=10 MSC(M) donors, n=2 replicates / donor. Unpaired student’s t-test, *p<0.05. Horizontal lines: group mean; error bars: standard deviation.

[0037] FIG. 4 shows a qPCR evaluation of expression levels of miR candidates identified based on miR-sequencing in Function-Pain Responders versus NonResponders in an example embodiment of the disclosure. Select miR candidates that were significantly differentially expressed based on miR-sequencing were measured by qPCR in MSC(M) treated with or without late-stage OA synovial fluid (SF). Significant differential expression was confirmed for one candidate (hsa-miR-642a-5p; SEQ ID NO:8) that was downregulated in MSC(M) derived from Function-Pain Responders versus Non-Responders, matching the miR-sequencing results. N=10 MSC(M) donors, n=2 replicates / donor. Unpaired student’s t-test, *p<0.05. Horizontal lines: group mean; error bars: standard deviation.

[0038] FIGs. 5A-D show correlation analyses of changes in KOOS at 12- and 24- months relative to baseline with expression levels of microRNA candidates measured by qPCR in an example embodiment of the disclosure. FIGs. 5A and 5B) Correlations of hsa-miR-642a-5p (SEQ ID NO:8) validate associations with changes in KOOS at 12- (FIG. 5A) and 24-months (FIG. 5B) relative to baseline as identified through the machine learning analysis. FIGs. 5C and 5D) Analysis of hsa-miR-483-5p (SEQ ID NO:26) shows no significant correlations with changes in KOOS at 12- (FIG. 5C) and 24-months (FIG. 5D) relative to baseline. N=10 patients. Spearman’s correlation. ADL: function in daily living; KOOS: knee injury and osteoarthritis outcome score.

[0039] FIG. 6 shows expression of hsa-miR-15b-5p (SEQ ID NO: 4) in different MSC sources in an example embodiment of the disclosure. The microRNA was measured in three MSC(AT) donors (AT01 , AT06, and AT07), in iMSCs (two different culture conditions, + dox and -dox) and in a healthy BM-MSC donor.

[0040] FIG. 7 shows expression of hsa-miR-210-3p (SEQ ID NO: 18) in different MSC sources in an example embodiment of the disclosure. The microRNA was measured in three MSC(AT) donors (AT01 , AT06, and AT07), in iMSCs (two different culture conditions, + dox and -dox) and in a healthy BM-MSC donor.

[0041] Further aspects and features of the example embodiments described herein will appear from the following description taken together with the accompanying drawings.Detailed Description of the Disclosure

[0042] The following is a detailed description provided to aid those skilled in the art in practicing the present disclosure. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used in the description herein is for describing particular embodiments only and is not intended to be limiting of the disclosure.

[0043] Further, the definitions and embodiments described in particular sections are intended to be applicable to other embodiments herein described for which they are suitable as would be understood by a person skilled in the art. For example, in the following passages, different aspects of the disclosure are defined in more detail. Eachaspect so defined may be combined with any other aspect or aspects unless clearly indicated to the contrary. In particular, any feature described herein may be combined with any other feature or features described herein.I. Definitions

[0044] As used herein, the following terms may have meanings ascribed to them below, unless specified otherwise. However, it should be understood that other meanings that are known or understood by those having ordinary skill in the art are also possible, and within the scope of the present disclosure. In the case of conflict, the present specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting.

[0045] In understanding the scope of the present disclosure, the term "comprising" and its derivatives, as used herein, are intended to be open ended terms that specify the presence of the stated features, elements, components, groups, integers, and / or steps, but do not exclude the presence of other unstated features, elements, components, groups, integers and / or steps. The foregoing also applies to words having similar meanings such as the terms, "including", "having" and their derivatives.

[0046] The term “consisting” and its derivatives, as used herein, are intended to be closed ended terms that specify the presence of stated features, elements, components, groups, integers, and / or steps, and also exclude the presence of other unstated features, elements, components, groups, integers and / or steps. The term “consisting essentially of”, as used herein, is intended to specify the presence of the stated features, elements, components, groups, integers, and / or steps as well as those that do not materially affect the basic and novel characteristic(s) of features, elements, components, groups, integers, and / or steps.

[0047] Further, terms of degree such as "substantially", "about" and "approximately" as used herein mean a reasonable amount of deviation of the modified term such that the end result is not significantly changed. These terms of degree should be construed as including a deviation of at least ±5% of the modified term if this deviation would not negate the meaning of the word it modifies.

[0048] As used in this specification and the appended claims, the singular forms “a”, “an” and “the” include plural references unless the content clearly dictates otherwise.Thus, for example, a composition containing “a compound” includes a mixture of two or more compounds.

[0049] The phrase "and / or," as used herein in the specification and in the claims, should be understood to mean "either or both" of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with "and / or" should be construed in the same fashion, i.e., "one or more" of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the "and / or" clause, whether related or unrelated to those elements specifically identified.

[0050] As used herein, "or" should be understood to have the same meaning as "and / or" as defined above. For example, when separating items in a list, "or" or "and / or" shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as "only one of or "exactly one of' or, when used in the claims, "consisting of" will refer to the inclusion of exactly one element of a number or list of elements. In general, the term "or" as used herein shall only be interpreted as indicating exclusive alternatives (i.e., "one or the other but not both") when preceded by terms of exclusivity, such as "either," "one of," "only one of," or "exactly one of."

[0051] As used herein, the phrase "at least one," in reference to a list of one or more elements, should be understood to mean at least one element selected from anyone or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase "at least one" refers, whether related or unrelated to those elements specifically identified.

[0052] The recitation of numerical ranges by endpoints herein includes all numbers and fractions subsumed within that range (e.g. 1 to 5 includes 1 , 1.5, 2, 2.75, 3, 3.90, 4, and 5). It is also to be understood that all numbers and fractions thereof are presumed to be modified by the term "about."

[0053] It should also be understood that, in certain methods described herein that include more than one step or act, the order of the steps or acts of the method is not necessarily limited to the order in which the steps or acts of the method are recited unless the context indicates otherwise.

[0054] Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present disclosure, examples of methods and materials are now described.II. Methods and Uses

[0055] The present inventors have identified microRNAs that are indicative of mesenchymal stromal cell basal fitness.

[0056] Accordingly, in one aspect, the present disclosure provides a method of determining basal fitness of a sample of mesenchymal stromal cells (MSC) comprising: determining a sample microRNA (miR) profile, the sample miR profile comprising the levels of at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69; and determining the level of similarity of said sample miR profile to one or more reference profiles, wherein (i) a high level of similarity of the sample miR profile to a basal fitness specific reference profile; (ii) a low level of similarity to a non-basal fitness specific reference profile; and / or (iii) a higher level of similarity to a basal fitness specific reference profile than to a non-basal fitness specific reference profile indicates the cells have basal fitness.

[0057] Also provided herein is a method of selecting a mesenchymal stromal cell (MSC) for treating an MSC-treatable disease in a subject in need thereof, comprising: a) determining a sample microRNA (miR) profile from a sample of MSCs, the sample miR profile comprising the levels of at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69; b) determining the level of similarity of said sample miR profile to one or more reference profiles, wherein (i) a high level of similarity of the sample miR profile to a basal fitness specific reference profile; (ii) a low level of similarity to a non-basal fitness specific reference profile; and / or (iii) a higher level of similarity to a basalfitness specific reference profile than to a non-basal fitness specific reference profile indicates the MSC has basal fitness; and c) administering the MSC with basal fitness to the subject.

[0058] Further provided herein is a method of treating a mesenchymal stromal cell (MSC)-treatable disease in a subject in need thereof comprising administering an MSC to the subject, wherein the MSC has been previously identified as having basal fitness by a method herein disclosed.

[0059] In another embodiment, herein provided is a use of an MSC for treating an MSC-treatable disease in a subject in need thereof, wherein the MSC has been previously identified as having basal fitness by a method herein disclosed. In yet another embodiment, herein provided is a use of an MSC in the manufacture of a medicament for treating an MSC-treatable disease in a subject in need thereof, wherein the MSC has been previously identified as having basal fitness by a method herein disclosed. In a further embodiment, herein provided is an MSC for use in treating an MSC-treatable disease in a subject in need thereof, wherein the MSC has been previously identified as having basal fitness by a method herein disclosed.

[0060] The term “cell” as used herein refers to a single cell or a plurality of cells.

[0061] MSCs can be obtained from a variety of tissue sources, including without limitation, adipose tissue, bone marrow, dental pulp, synovium, placenta, induced pluripotent stem cells, and umbilical cord, for example umbilical cord blood and umbilical cord tissue (i.e., Wharton's jelly).

[0062] Accordingly, in one embodiment, the MSCs are derived from adipose tissue, bone marrow, dental pulp, synovium, placenta, umbilical cord, induced pluripotent stem cells or a combination thereof. In another embodiment, the MSCs are derived from adipose tissue. In another embodiment, the MSCs are derived from induced pluripotent stem cells. In another embodiment, the MSCs are derived from dental pulp. In another embodiment, the MSCs are derived from synovium. In yet another embodiment, the MSCs are derived from placenta. In a further embodiment, the MSCs are derived from umbilical cord.

[0063] In an embodiment, the MSCs are derived from bone marrow.

[0064] MSCs can be derived from any animal, including dogs, cats, horse, and humans.

[0065] In an embodiment, the MSCs are for veterinary use and are derived from dogs, cats, or horse. In another embodiment, the MSCs are for medical use and are derived from humans.

[0066] In an embodiment, the MSCs are derived from humans. In another embodiment, the MSCs are derived from dogs, cats or horse.

[0067] The term “subject”, also referred to as patient, as used herein includes all members of the animal kingdom including mammals, and suitably refers to humans.

[0068] In an embodiment, the subject is a human. In another embodiment, the subject is a dog, a cat, or a horse.

[0069] The term “administering” or “administration” as used herein refers to the placement of the MSCs as disclosed herein into a subject by a method or route which results in at least partial delivery to a desired site. The MSCs disclosed herein can be administered by any appropriate route which results in an effective treatment in the subject, and when the subject has knee osteoarthritis, can be by injection into the knee, for example by intraarticular injection. The MSCs an also be administered, for example, by intravenous administration or intraosseous administration.

[0070] The term “MSC-treatable disease” as used herein refers to any disease known in the art wherein treatment with basally fit MSCs can be clinically beneficial. The MSC-treatable disease can comprise an inflammatory disease, for example osteoarthritis, lupus, scleroderma, or rheumatoid arthritis. The MSC-treatable disease can also comprise graft versus host disease, stroke, inflammatory bowel disease or cardiac disease.

[0071] Accordingly, in an embodiment, the MSC-treatable disease comprises osteoarthritis, lupus, scleroderma, rheumatoid arthritis, graft versus host disease, stroke, inflammatory bowel disease, or cardiac disease.

[0072] In another embodiment, the MSC-treatable disease comprises lupus. In another embodiment, the MSC-treatable disease comprises scleroderma. In another embodiment, the MSC-treatable disease comprises rheumatoid arthritis. In another embodiment, the MSC-treatable disease comprises graft versus host disease. In anotherembodiment, the MSC-treatable disease comprises stroke. In yet another embodiment, the MSC-treatable disease comprises inflammatory bowel disease. In a further embodiment, the MSC-treatable disease comprises cardiac disease.

[0073] In an embodiment, the MSC-treatable disease comprises osteoarthritis.

[0074] In an embodiment, the osteoarthritis comprises knee osteoarthritis.

[0075] The term “knee osteoarthritis” or “knee OA” as used herein refers to osteoarthritis of the knee joint and can be characterized by radiographic changes to the cartilage and other tissues in this joint.

[0076] As used herein, the term “sample microRNA profile” or “sample miR profile” or “sample profile” refers to the levels of the identified miRs of a particular sample or data set.

[0077] The term “microRNA” or “miR” as used herein refers to a small noncoding single-stranded RNA molecule of about 20 to 25 nucleotides in length. The 5'-end of a miR comprises a so-called “seed sequence”, which along with the rest of the miR, can recognize at least partially complementary miR target sequences in target messenger RNAs (mRNAs) and, once bound, prevents translation of the polypeptide or protein encoded by the mRNA.

[0078] miR levels of each miR can be obtained by measuring miR expression, for example by qPCR or microarray, or by directly quantifying miR, for example by miR- sequencing.

[0079] In an embodiment, miR levels are determined by measuring miR count.

[0080] In an embodiment, the sample miR profile comprises the levels of at least two miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 - 69. In an embodiment, the sample miR profile comprises the levels of at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least six miRs, each miR comprising nucleic acid sequence selected from SEQ ID NOs: 1 -69. In anotherembodiment, the sample miR profile comprises the levels of at least seven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least eight miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least nine miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least ten miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least eleven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least twelve miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least fifteen miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least twenty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least twenty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least thirty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least thirty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least forty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least forty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least fifty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least fifty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the sample miR profile comprises the levels of at least sixty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In yet another embodiment, the sample miR profile comprises the levels of at least sixty-five miRs, each miR comprising a nucleic acid sequence according to SEQ ID NOs: 1 - 69. In a further embodiment, the sample miR profile comprises the levels of 69 miRs, wherein the 69 miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 1 -69.

[0081] The term “basal fitness” as used herein refers to MSCs with an ability to modulate immune responses, angiogenesis, and / or chondroprotection, or other forms of tissue remodeling, to a sufficient degree to be measurable, for example through reduced inflammation or inflammatory response, or by modulating monocyte / macrophage phenotype in vitro. Basal fitness of MSCs is measured in vitro prior to clinical administration of the cells, after which the biological activity of MSCs is further modulated by host cells and tissues (35). The basal fitness of MSCs may correlate to their clinical efficacy (36, 37).

[0082] In an embodiment, basal fitness is evaluated by measuring levels of MSC miRs in vitro prior to clinical administration of the MSCs and determining their correlations with an improvement in a patient-reported outcome measure (PROM) score following treatment with the MSCs compared to pre-treatment with the MSCs in a patient with an MSC-treatable disease, optionally knee osteoarthritis.

[0083] The term “patient-reported outcome measure score” or “PROM score” as used herein refers to any symptomatic variable associated with a clinical phenotype of an MSC-treatable disease. A PROM score can, for example, be derived from an assessment of osteoarthritis. The PROM score may, for example, be an absolute, relative, interval, or ordinal value.

[0084] In an embodiment, the PROM score is derived from an assessment of osteoarthritis. In another embodiment, the PROM score is derived from an assessment of knee osteoarthritis.

[0085] In some embodiments, the sample miR profile is compared to one or more reference profiles obtained from one or more donor samples.

[0086] The term “donor” as used herein refers to an individual from which tissue was obtained to derive MSCs.

[0087] The reference profile may be a reference value and / or may be derived from one or more samples, optionally from historical miR data from a pool of samples from the same donor. In an embodiment, the reference profile is a value that is continually updatedas further samples are collected and basal fitness is measured and correlated. It will be understood that the reference profile represents an average of the levels for the selected miRs orfeatures described herein. Average values may, for example, be the mean values or median values.

[0088] For example, a “basal fitness specific reference profile” may be generated by measuring the levels of the miRs for those samples known to have basal fitness. Similarly, a “non-basal fitness specific reference profile” may be generated by measuring the levels of the miRs for those samples known not to have basal fitness.

[0089] In an embodiment, a higher level of similarity to the basal fitness specific reference profile than to the non-basal fitness specific reference profile is indicated by a higher correlation value computed between the sample profile and the basal fitness specific reference profile than an equivalent correlation value computed between the sample profile and the non-basal fitness specific reference profile, optionally wherein the correlation value is a correlation coefficient.

[0090] Methods of determining the similarity between profiles are well known in the art. Methods of determining similarity may in some embodiments provide a non- quantitative measure of similarity, for example, using visual clustering. In other embodiments, similarity may be determined using methods which provide a quantitative measure of similarity.

[0091] In an embodiment, similarity may be measured by computing a “correlation coefficient”, which is a measure of the interdependence of random variables that ranges in value from -1 to +1 , indicating perfect negative correlation at -1 , absence of correlation at zero, and perfect positive correlation at +1. In an embodiment, the correlation coefficient may be a linear correlation coefficient, for example, a Pearson productmoment correlation coefficient.

[0092] A Pearson correlation coefficient (r) is calculated using the following formula:

[0093] In an embodiment, the correlation coefficient may be a monotonic correlation coefficient, for example, a Spearman’s rank correlation coefficient.

[0094] A Spearman’s rank correlation coefficient (p) is calculated using the following formula:where cov(R(X),R(Y)) is the covariance of rank variables and ORQQ and ORCO are their standard deviations.

[0095] In one embodiment, X and Y are the expression values of the miR measurements in a sample profile and a reference profile, respectively. In another embodiment, X and Y are the PROM scores or the basal fitness score in a sample profile and a reference profile, respectively.

[0096] In an embodiment, a correlation coefficient calculated between a sample miR profile and a reference profile indicates a high level of similarity to the reference profile when the correlation coefficient has an absolute value between 0.5 to 1 , optionally between 0.75 to 1 , and a low level of similarity to the reference profile when the correlation coefficient has an absolute value between 0 to 0.5, optionally between 0 to 0.25.

[0097] It will be appreciated that any “correlation value” which provides a quantitative scaling measure of similarity between profiles may be used to measure similarity.

[0098] A sample miR profile may be identified as having basal fitness, where the sample profile has high similarity to the basal fitness specific reference profile, low similarity to the non-basal fitness specific reference profile, or higher similarity to the basal fitness specific reference profile than to the non-basal fitness specific reference profile. Conversely, a sample profile may be identified as having non-basal fitness, where the sample miR profile has high similarity to the non-basal fitness specific reference profile, low similarity to the basal fitness specific reference profile, or higher similarity to the non-basal fitness specific reference profile than to the basal fitness specific reference profile.

[0099] For example, in an embodiment, a sample profile may be identified as having basal fitness based on calculation of a score, which generally is defined by the following formula: score(B) = r (B, basal fitness profile) - r (B, reference profile) where r is the Pearson correlation coefficient, and B is a vector of miR levels across the selected miR.

[0100] In another embodiment, a sample profile may be identified as having basal fitness based on calculation of a score, which generally is defined by the following formula: score(B) = rs (B, basal fitness profile) - rs (B, reference profile) where rs is the Spearman’s rank correlation coefficient and B is a vector of miR levels across the selected miR.

[0101] A sample profile with a positive basal fitness score is more similar to the basal fitness specific reference profile across the selected miR, and is therefore classified as “having basal fitness”; whereas a sample with a negative basal fitness score is more similar to the non-basal specific reference profile across the selected miR, and is classified as “not having basal fitness”.

[0102] In an embodiment, the miR profiles for basal fitness are analyzed using combinatorial or multivariate dimension reduction statistical or mathematical methods. In another embodiment, the combinatorial or multivariate dimension reduction statistical or mathematical methods comprise clustering analysis, machine learning analysis methods, or desirability analyses to enable comparisons between multivariate miR profiles with dimension-reduced empirical values.

[0103] In an embodiment, the clustering analysis is principal component analysis. Principal component analysis is applied as an unbiased tool to visualize similarity between the multivariate miR profiles of different groups (e.g. a basal fitness specific reference profile, a non-basal fitness specific reference profile, and a sample profile). In another embodiment, the clustering analysis is canonical correlation analysis. Canonical correlation analysis is applied as a supervised technique to test whether multivariate miR profiles of different groups are statistically distinct, and to provide information on their level of similarity.

[0104] Machine learning analysis methods can comprise least absolute shrinkage and selection operator (LASSO) regression, Partial Least Square Discriminant Analysis (PLSDA), Support Vector Machine Discriminant Analysis (SVMDA), or an PLSDA or an Artificial Neural Network (ANN) topology. Alternatively, other types of machine learning techniques might be used such as, but not limited to, Convolutional Neural Networks, and the Random Forrest method, for example.

[0105] Desirability analysis or desirability profiling is based on methods developed by Derringer and Suich, 1980 (32), incorporated herein by reference. In an embodiment, desirability analysis is applied to rank the basal fitness of a sample based on the combination of miRs measured to facilitate relative comparisons between sample or reference profiles.

[0106] Quantitative values can be determined for the miRs for determining basal fitness of a sample of MSCs. A set of miRs can be used to assess samples from different donors or samples processed by different parameters in order to identify donors or parameters that give rise to MSCs with basal fitness. This evaluation can be considered a training dataset for particular donors or parameters. Once values are obtained for a particular donor or parameter, such values can then be used to assess fitness of samples from the same donor or grown underthe same parameters, for example, as a pass orfail for manufacturing processes.

[0107] Accordingly, also provided herein is a method of determining quantitative values for a set of miRs for assessing basal fitness of a sample of mesenchymal stromal cells (MSCs), the method comprising: a) measuring levels of the set of microRNAs (miRs) for the sample, wherein the set of miRs comprises at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69; b) obtaining the basal fitness status of the sample; and c) conducting a regression analysis between each miR of a) with the basal fitness of b); determining minimum and maximum data values of each miR of the sample and using multivariate dimension reduction statistical or mathematical methods to assign minimization or maximization functions to indicate whether higher or lower values are desirable based on the directionality of correlation respectively.

[0108] In an embodiment, the set of miRs comprises at least two miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In an embodiment, the set of miRs comprises at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69. In another embodiment, the set of miRs comprises at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69. In another embodiment, the set of miRs comprises at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the set of miRs comprises at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the set of miRs comprises at least seven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69. In another embodiment, the set of miRs comprises at least eight miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69. In another embodiment, the set of miRs comprises at least nine miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69. In another embodiment, the set of miRs comprises at least ten miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the set of miRs comprises at least eleven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69. In another embodiment, the set of miRs comprises at least twelve miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69. In another embodiment, the set of miRs comprises at least fifteen miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69. In another embodiment, the set of miRs comprises at least twenty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the set of miRs comprises at least twenty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the set of miRs comprises at least thirty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69. In another embodiment, the set of miRs comprises at least thirty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69. In another embodiment, the set of miRs comprises at least forty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the set of miRs comprises at least forty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In another embodiment, the set of miRs comprises at least fifty miRs, each miR comprising a nucleicacid sequence selected from SEQ ID NOs: 1-69. In another embodiment, the set of miRs comprises at least fifty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69. In another embodiment, the set of miRs comprises at least sixty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In yet another embodiment, the set of miRs comprises at least sixty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -69. In a further embodiment, the set of miRs comprises 69 miRs, wherein the 69 miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 1-69.

[0109] Desirability analysis may be applied to analyze the profile of miRs and to assign empirical rankings for donors or processing parameters that result in desirable MSC basal fitness.

[0110] Accordingly, in an embodiment, the method further comprises d) assigning a weighting to each miR for desirability analysis based on the R2values from the regression analysis; and e) assigning a score from zero to one using desirability analysis to each sample based on the range of data values; wherein zero is undesirable and one is highly desirable to obtain a set of values for MSCs for each donor.

[0111] Testing the MSCs for basal fitness is not required where the basal fitness is already known. Accordingly, in an embodiment, the basal fitness status of the sample in step b) is obtained from a clinical sample for which the basal fitness or efficacy of the MSCs were previously evaluated clinically, for example where the clinical sample is from a clinical study or pre-clinical or other correlated read-outs.

[0112] Alternatively, obtaining the basal fitness status of the sample in step b) can be determined clinically, for example by treating a subject having an MSC-treatable disease with the sample of MSCs and evaluating the relationship between in vitro characteristics with the therapeutic effect of the MSCs. Accordingly, in an embodiment, the obtaining of the basal fitness status of the sample in step b) comprises:I) determining at least one patient-reported outcome measure (PROM) score from an assessment of an MSC-treatable disease from a subject with the MSC- treatable disease pre-treatment with the sample;II) determining the at least one PROM score from the assessment of the MSC- treatable disease from the subject post treatment with the sample;III) comparing the at least one PROM score in I) and II); andIV) assigning a basal fitness score to the sample based on the size of the improvement in the at least one PROM score post-treatment compared to pretreatment, wherein an improvement in the at least one PROM score posttreatment is indicative that the basal fitness score of the sample is high, and wherein no improvement or a worsening in the at least one PROM score posttreatment is indicative that the basal fitness score of the sample is low.

[0113] In an embodiment, the obtaining of the basal fitness status of the sample in step b) further comprises: l.i) treating the subject with the sample; wherein step l.i) is performed between steps I) and II).

[0114] Step II) can be performed at any suitable interval following the treatment with the sample, including 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, 1 week, 2 weeks, 3 weeks, 4 weeks, 1 month, 2 months, 3 months, 4 months, 5 months, 6 months, 8 months, 10 months, 12 months, 18 months, 24 months, 3 years, 4 years, 5 years, 6 years, 8 years, 10 years, or longer following treatment with the sample. Step II) can also be performed within a range of suitable times following the treatment with the sample, for example 1-36 months, 12-24 months, or 1-10 years, or any range therein.

[0115] Accordingly, in an embodiment, step II) is performed 12 to 24 months post treatment with the sample.

[0116] In an embodiment, the MSC-treatable disease comprises osteoarthritis, lupus, scleroderma, rheumatoid arthritis, graft versus host disease, stroke, inflammatory bowel disease, or cardiac disease.

[0117] In another embodiment, the MSC-treatable disease comprises lupus. In another embodiment, the MSC-treatable disease comprises scleroderma. In another embodiment, the MSC-treatable disease comprises rheumatoid arthritis. In another embodiment, the MSC-treatable disease comprises graft versus host disease. In another embodiment, the MSC-treatable disease comprises stroke. In yet another embodiment,the MSC-treatable disease comprises inflammatory bowel disease. In a further embodiment, the MSC-treatable disease comprises cardiac disease.

[0118] In an embodiment, the MSC-treatable disease comprises osteoarthritis.

[0119] In an embodiment, the osteoarthritis comprises knee osteoarthritis.

[0120] In an embodiment, the assessment of the MSC-treatable disease comprises an assessment of knee osteoarthritis. The assessment of knee osteoarthritis can comprise any method known in the art to assess knee osteoarthritis. In some embodiments, the assessment of knee osteoarthritis comprises Knee injury and Osteoarthritis Outcome Score (KOOS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Visual Analogue Scale (VAS), Short Form 36 (SF-36) or Short Form 12 (SF-12), Tegner Lysholm Knee Score, Knee Society Clinical Rating System, Lequesne Index for Knee Osteoarthritis, Oxford Knee Score (OKS) and / or International Knee Documentation Committee (IKDC) Questionnaire. In an embodiment, the assessment of knee osteoarthritis comprises KOOS. In another embodiment, the assessment of knee osteoarthritis comprises WOMAC. In another embodiment, the assessment of knee osteoarthritis comprises VAS. In another embodiment, the assessment of knee osteoarthritis comprises SF-36 or SD-12. In another embodiment, the assessment of knee osteoarthritis comprises Tegner Lysholm Knee Score. In another embodiment, the assessment of knee osteoarthritis comprises Knee Society Clinical Rating System. In another embodiment, the assessment of knee osteoarthritis comprises Lequesne Index for Knee Osteoarthritis. In another embodiment, the assessment of knee osteoarthritis comprises OKS. In another embodiment, the assessment of knee osteoarthritis comprises IKDC Questionnaire.

[0121] In an embodiment, the assessment of knee osteoarthritis comprises KOOS and the PROM score comprises KOOS Pain, KOOS Symptoms, function in daily living (ADL), function in Sport and Recreation (Sports / Rec), knee-related quality of life (QOL), or Overall KOOS, or combinations thereof.

[0122] The term “treating”, “treatment”, and the like, as used herein, and as is well understood in the art, refers to an approach for obtaining beneficial or desired results, including clinical results. Beneficial or desired clinical results include, but are not limited to alleviation or amelioration of one or more symptoms or conditions, arresting development of disease, diminishment of extent of disease, stabilized (i.e. not worsening)state of disease, preventing spread of disease, delay or slowing of disease progression, amelioration or palliation of the disease state, including regression of the disease, diminishment of the reoccurrence of disease, and remission (whether partial or total), whether detectable or undetectable. “Treating” and “treatment” may also refer to prolonging survival as compared to expected survival if not receiving treatment.

[0123] Once values are obtained for a particular donor, samples from the same donor can be evaluated. Accordingly, also provided herein is a method of determining basal fitness of a sample of mesenchymal stromal cells (MSC) comprising a) determining a sample microRNA (miR) profile, the sample miR profile comprising levels of at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69; and b) ranking the miR profile of a) based on a comparison of minimum and maximum values determined by a method disclosed herein for the same particular donor to determine the basal fitness.

[0124] The miRs used in any of the methods and kits described herein can be miRs that are upregulated or downregulated at baseline in samples that lead to a beneficial or desired result in a subject with an MSC-treatable disease, for example knee osteoarthritis, post treatment with the sample, compared to baseline in samples that do not lead to a beneficial or desired result in a subject with the MSC treatable disease post treatment with the sample.

[0125] For example, the inventors investigated 2656 miRs and identified 38 miRs (SEQ ID NOs: 1-38) that were differentially expressed in MSCs at baseline between responders and non-responders to treatment in subjects with knee osteoarthritis.

[0126] Accordingly, in an embodiment, the sample miR profile comprises the levels of at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the set of miRs comprises at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38.

[0127] In another embodiment, the sample miR profile comprises the levels of at least two miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the sample miR profile comprises the levels of at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ IDNOs: 1-38. In another embodiment, the sample miR profile comprises the levels of at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the sample miR profile comprises the levels of at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the sample miR profile comprises the levels of at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the sample miR profile comprises the levels of at least seven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the sample miR profile comprises the levels of at least eight miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In another embodiment, the sample miR profile comprises the levels of at least nine miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In another embodiment, the sample miR profile comprises the levels of at least ten miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In another embodiment, the sample miR profile comprises the levels of at least eleven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In another embodiment, the sample miR profile comprises the levels of at least twelve miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In another embodiment, the sample miR profile comprises the levels of at least fifteen miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In another embodiment, the sample miR profile comprises the levels of at least twenty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In another embodiment, the sample miR profile comprises the levels of at least twenty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In another embodiment, the sample miR profile comprises the levels of at least thirty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In yet another embodiment, the sample miR profile comprises the levels of at least thirty- five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 - 38. In a further embodiment, the sample miR profile comprises the levels of thirty-eight miRs, wherein the 38 miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 1-38.

[0128] In another embodiment, the set of miRs comprises at least two miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In anotherembodiment, the set of miRs comprises at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the set of miRs comprises at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the set of miRs comprises at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the set of miRs comprises at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In another embodiment, the set of miRs comprises at least seven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the set of miRs comprises at least eight miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the set of miRs comprises at least nine miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the set of miRs comprises at least ten miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In another embodiment, the set of miRs comprises at least eleven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the set of miRs comprises at least twelve miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the set of miRs comprises at least fifteen miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In another embodiment, the set of miRs comprises at least twenty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In another embodiment, the set of miRs comprises at least twenty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -38. In another embodiment, the set of miRs comprises at least thirty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In yet another embodiment, the set of miRs comprises at least thirty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-38. In a further embodiment, the set of miRs comprises thirty-eight miRs, wherein the 38 miRs comprise nucleic acid sequences according to SEQ ID NOs: 1-38.

[0129] Of the 38 differentially expressed miRs, the inventors identified 33 (SEQ ID NOs: 1-33) which were differentially expressed in MSCs between Function Responders and non-responders to treatment in subjects with knee osteoarthritis.

[0130] Accordingly, in another embodiment, sample miR profile comprises the level of at least one miR, each miR comprising a nucleic acid sequence selected fromSEQ ID NOs: 1-33. In another embodiment, the set of miRs comprises at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33.

[0131] In another embodiment, the sample miR profile comprises the levels of at least two miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the sample miR profile comprises the levels of at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the sample miR profile comprises the levels of at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the sample miR profile comprises the levels of at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the sample miR profile comprises the levels of at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the sample miR profile comprises the levels of at least seven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the sample miR profile comprises the levels of at least eight miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -33. In another embodiment, the sample miR profile comprises the levels of at least nine miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -33. In another embodiment, the sample miR profile comprises the levels of at least ten miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -33. In another embodiment, the sample miR profile comprises the levels of at least eleven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -33. In another embodiment, the sample miR profile comprises the levels of at least twelve miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -33. In another embodiment, the sample miR profile comprises the levels of at least fifteen miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -33. In another embodiment, the sample miR profile comprises the levels of at least twenty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 11 -33. In another embodiment, the sample miR profile comprises the levels of at least twenty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -33. In yet another embodiment, the sample miR profile comprises the levels of at least thirty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -33. In a further embodiment, the sample miR profile comprises the levels of thirty-three miRs,wherein the thirty-three miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 1-33.

[0132] In another embodiment, the set comprises at least two miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -33. In another embodiment, the set of miRs comprises at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the set of miRs comprises at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the set of miRs comprises at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the set of miRs comprises at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -33. In another embodiment, the set of miRs comprises at least seven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the set of miRs comprises at least eight miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the set of miRs comprises at least nine miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the set of miRs comprises at least ten miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1 -33. In another embodiment, the set of miRs comprises at least eleven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the set of miRs comprises at least twelve miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the set of miRs comprises at least fifteen miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In another embodiment, the set of miRs comprises at least twenty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 11 -33. In another embodiment, the set of miRs comprises at least twenty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In yet another embodiment, the set of miRs comprises at least thirty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-33. In a further embodiment, the set of miRs comprises thirty-three miRs, wherein the thirty-three miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 1-33.

[0133] Of the 38 differentially expressed miRs, the inventors identified several miRs that were differentially expressed in MSCs in Function-Pain Responders comparedto non-responders (SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37) to treatment in subjects with knee osteoarthritis.

[0134] Accordingly, in another embodiment, sample miR profile comprises the level of at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the sample miR profile comprises at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37.

[0135] In another embodiment, the sample miR profile comprises the levels of at least two miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the sample miR profile comprises the levels of at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the sample miR profile comprises the levels of at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the sample miR profile comprises the levels of at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the sample miR profile comprises the levels of at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the sample miR profile comprises the levels of at least seven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the sample miR profile comprises the levels of at least eight miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the sample miR profile comprises the levels of at least nine miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the sample miR profile comprises the levels of at least ten miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the sample miR profile comprises the levels of at least eleven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the sample miR profile comprises the levels of at least twelve miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In yet another embodiment, the sample miRprofile comprises the levels of at least thirteen miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In a further embodiment, the sample miR profile comprises the levels of fourteen miRs, wherein the fourteen miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37.

[0136] In another embodiment, the set of miRs comprises at least two miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the set of miRs comprises at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the set of miRs profile comprises at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the set of miRs comprises at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the set of miRs comprises at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the set of miRs comprises at least seven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the set of miRs comprises at least eight miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the set of miRs comprises at least nine miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the set of miRs comprises at least ten miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the set of miRs comprises at least eleven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In another embodiment, the set of miRs comprises at least twelve miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In yet another embodiment, the set of miRs comprises at least thirteen miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37. In a further embodiment, the set of miRs comprises fourteen miRs, wherein the fourteen miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37.

[0137] Of the 38 differentially expressed miRs, the inventors identified several miRs that were differentially expressed in MSCs in both Function Responders and Function-Pain responders compared to non-responders. (SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32) to treatment in subjects with knee osteoarthritis.

[0138] Accordingly, in yet another embodiment, sample miR profile comprises the level of at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In another embodiment, the set of miRs comprises at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32.

[0139] In another embodiment, the sample miR profile comprises the levels of at least two miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In another embodiment, the sample miR profile comprises the levels of at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In another embodiment, the sample miR profile comprises the levels of at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In another embodiment, the sample miR profile comprises the levels of at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In another embodiment, the sample miR profile comprises the levels of at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5- 8, 16, 18, 26, and 32. In another embodiment, the sample miR profile comprises the levels of at least seven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In another embodiment, the sample miR profile comprises the levels of at least eight miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In yet another embodiment, the sample miR profile comprises the levels of at least nine miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In a further embodiment, the sample miR profile comprises the levels of ten miRs, wherein the ten miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32.

[0140] In another embodiment, the set of miRs comprises at least two miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18,26, and 32. In another embodiment, the set of miRs comprises at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In another embodiment, the set of miRs comprises at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In another embodiment, the set of miRs comprises at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In another embodiment, the set of miRs comprises at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In another embodiment, the set of miRs comprises at least seven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In another embodiment, the set of miRs comprises at least eight miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In yet another embodiment, the set of miRs comprises at least nine miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32. In a further embodiment, the set of miRs comprises ten miRs, wherein the ten miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32.

[0141] The miRs used in any of the methods or kits described herein can also be miRs whose expression in MSCs are statistically associated with a PROM score, such that a change in one is correlated with a change in the other, optionally as determined by LASSO regression.

[0142] For example, the inventors investigated 2656 miRs and identified 38 (SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69) by LASSO regression whose expression in MSCs were statistically associated with a PROM score, such that a change in one was correlated with a change in the other.

[0143] Accordingly, in an embodiment, sample miR profile comprises the level of at least one miR, each miRs comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least one miR, each miRs comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69.

[0144] In another embodiment, the sample miR profile comprises the levels of at least two miRs, each miRs comprising a nucleic acid sequence selected from SEQ IDNOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least seven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least eight miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least nine miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least ten miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least eleven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least twelve miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least fifteen miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least twenty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least twenty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the sample miR profile comprises the levels of at least thirty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In yet another embodiment, the sample miRprofile comprises the levels of at least thirty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In a further embodiment, the sample miR profile comprises the levels of thirty-eight miRs, wherein the thirty-eight miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69.

[0145] In another embodiment, the set of miRs comprises at least two miRs, each miRs comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs profile comprises at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least seven miRs , each miR comprising a nucleic acid sequence selected from SEQ ID NOs:2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least eight miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least nine miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least ten miRs comprising, each miR a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least eleven miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs:2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least twelve miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs:2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least fifteen miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs:2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least twenty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs:2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least twenty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ IDNOs: 2, 8, 18-20, 26, 35, and 39-69. In another embodiment, the set of miRs comprises at least thirty miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In yet another embodiment, the set of miRs comprises at least thirty-five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69. In a further embodiment, the set of miRs comprises thirty-eight miRs, wherein the thirty-eight miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 2, 8, 18-20, 26, 35, and 39-69.

[0146] The miRs used in any of the methods or kits described herein can further be both: 1) upregulated or downregulated at baseline in samples that lead to a beneficial or desired result in a subject with an MSC-treatable disease, for example knee osteoarthritis, post treatment with the sample compared to baseline in samples that do not lead to a beneficial or desired result in a subject with the MSC treatable disease post treatment with the sample; and 2) be statistically associated with a PROM score, such that a change in one is correlated with a change in the other, optionally as determined by LASSO regression.

[0147] For example, the inventors identified 7 miRs (SEQ ID NOs: 2, 8, 18-20, 26, and 35) that were both 1) differentially expressed at baseline between responders and non-responders to treatment in subjects with knee osteoarthritis, and 2) statistically associated with a PROM score, such that a change in one was correlated with a change in the other as determined by LASSO regression.

[0148] Accordingly, in an embodiment, sample miR profile comprises the level of at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, and 35. In another embodiment, the set comprises at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18- 20, 26, and 35.

[0149] In another embodiment, the sample miR profile comprises the levels of at least two miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, and 35. In another embodiment, the sample miR profile comprises the levels of at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, and 35. In another embodiment, the sample miR profile comprises the levels of at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, and 35. In another embodiment,the sample miR profile comprises the levels of at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, and 35. In yet another embodiment, the sample miR profile comprises the levels of at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, and 35. In a further embodiment, the sample miR profile comprises the levels of seven miRs, wherein the seven miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 2, 8, 18-20, 26, and 35.

[0150] In another embodiment, the set of miRs comprises at least two miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, and 35. In another embodiment, the set of miRs comprises at least three miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, and 35. In another embodiment, the set of miRs comprises at least four miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, and 35. In another embodiment, the set of miRs comprises at least five miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, and 35. In yet another embodiment, the set of miRs comprises at least six miRs, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18-20, 26, and 35. In a further embodiment, the set of miRs comprises seven miRs, wherein the seven miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 2, 8, 18-20, 26, and 35.III. Kits

[0151] In another aspect, the present disclosure provides a kit for determining basal fitness of a sample of mesenchymal stromal cells (MSCs), the kit comprising a plurality of probes, wherein the plurality of probes comprises a probe specific for each miR in a set of miRs disclosed herein.

[0152] In an embodiment, the probe is a quantitative polymerase chain reaction (qPCR) probe. In another embodiment, the probe is a locked nucleic acid (LNA) probe.

[0153] Also provided is a kit for determining basal fitness of a sample of mesenchymal stromal cells (MSCs), the kit comprising a plurality of probes, wherein the plurality of probes comprises a pair of probes specific for each miR in a set of miRs disclosed herein.

[0154] In another embodiment, the pair of probes comprises a capture probe and a reporter probe, optionally a NanoString capture and reporter probe.

[0155] In an embodiment, the kit further comprises culturing medium.

[0156] In another embodiment, the culturing medium comprises Dulbecco's Modified Eagle Medium (DMEM) and fetal bovine serum (FBS).

[0157] In an embodiment, the kit further comprises a licensing agent.

[0158] The term “licensing”, as used herein refers to stimulation of MSCs with pro- inflammatory cytokines. Accordingly, a licensing agent is an agent comprising pro- inflammatory cytokines that is capable of stimulating MSCs.

[0159] In another embodiment, the licensing agent is synovial fluid derived from an osteoarthritis joint.

[0160] The following non-limiting Examples are illustrative of the present disclosure:Example 1 - Sequencing reveals specific microRNAs as putative critical quality attributes for MSC(M) in knee OA

[0161] Given that microRNAs (miRs) have emerged as an important mediator of MSC mechanisms of action {18), these may also serve as valuable CQAs for defining basal fitness of MSCs and were interrogated in this study. To probe unbiased differences in MSC(M) donors classified as responders and non-responders, miR-Seq was performed to identify miRs to serve as putative CQAs for MSC(M) in knee OA.Methods

[0162] Experimental design and patients

[0163] Patients were recruited to this nonrandomized, open-label, dose-escalation phase l / lla clinical trial with informed consent as reported previously 11) (ClinicalTrials.gov Identifier: NCT02351011 ). Ethics approval was granted by the UHN Research Ethics Board (REB 14-7909) and Health Canada. Eligibility criteria and patient demographic information were previously provided {11). Patients received a single intraarticular autologous MSC(M) injection at doses of 1 x 106, 10 x 106, and 50 x 106cells (N=4 patients / dose group). Clinical follow-up was performed over 24 months after MSC(M) injection. The Knee Injury and Osteoarthritis Outcome Score (KOOS) was applied as a patient-reported outcome measurement tool (22) and the scale was inverted such that higher scores indicate worse outcomes. Overall KOOS was calculated as anaverage of all responses to the KOOS questionnaire, and KOOS subscales included: 1) pain; 2) symptoms; 3) function in daily living (ADL); 4) sports and recreation function (Sports / Rec); and 5) quality of life (QOL). Both delta and percentage change KOOS values were calculated using scores collected at follow-up time points relative to baseline in order to capture absolute changes, as well as changes that account for baseline values, respectively. While delta values correspond to the magnitude of difference relative to baseline, they do not account for differences at baseline; percentage change values do control for baseline scores but can be inflated when baseline scores are low. Both are considered relevant measures of change according to international criteria for evaluating OA therapeutics (79) and are therefore included throughout this study. Delta and percentage change values were calculated such that positive values indicated improvement.

[0164] microRNA-sequencinq on MSC(M) samples

[0165] Biobanked MSC(M) were thawed and plated on 24-well plates at 50,000 cells / well and cultured for 72 h in proliferation medium. Cells were then washed with phosphate-buffered saline (PBS) and treated with low-glucose DMEM (Sigma) supplemented with or without synovial fluid. To treat cells with synovial fluid, synovial fluid samples were collected from unrelated late-stage OA patients (Kellgren-Lawrence (KL) grade lll-IV) outside of the clinical trial cohort (REB #14-7483), pooled from eight patients, and stored at 80°C until use, as previously described (26). For treated wells, DMEM was supplemented with 30% (v / v) synovial fluid. After 24 h, RNA extraction was performed on cell samples using a miRNeasy Mini Kit (Qiagen, Hilden, Germany) and stored at -30°C until analysis.

[0166] Libraries of cDNA were prepared using the QIAseq miRNA Library Kit (Qiagen) according to the manufacturer's instructions. The libraries were quantified using a DS-11 Spectrophotometer (DeNovix, Wilmington, USA) and assessed for quality using a high-sensitivity DNA chip on the Bioanalyzer (Agilent, Santa Clara, USA). Samples were sequenced using the NextSeq 550 system (Illumina, San Diego, USA) at the Centre for Arthritis Diagnostic and Therapeutic Innovation (Krembil Research Institute, Toronto, Canada) according to previously published methods (27). Sequencing data alignment and miR counts generation was performed as described previously (27).

[0167] Expression of select miR candidates identified from miR-Seq results were evaluated by qPCR using the same MSC(M) RNA samples used for miR-Seq. RNA samples were reverse-transcribed using the miRCURY LNA RT kit (Qiagen) and qPCR was performed using the miRCURY LNA miRNA PCR system and primers (Qiagen) on a QuantStudio 5 system (ThermoFisher). Results were normalized (negative dCT) relative to hsa-miR-24-3p as a reference miR that was stable in the present samples according to miR-Seq results.

[0168] Machine Learning

[0169] Machine learning models were built using a supervised least absolute shrinkage and selection operator (LASSO) regression-based model to identify miRs associated with patient-reported outcomes, as measured using KOOS. A model was created for each of the subscales of the KOOS patient-reported outcome tool as well as overall KOOS, and for each time point (12 month and 24 months). The LASSO regularization technique was used to eliminate, from contention as predictors, miRs that are unlikely to be associated with a KOOS subscale or overall KOOS.

[0170] These models were validated with five-fold cross-validation to reduce the risk of overfitting. Briefly, the dataset for each model was randomly divided into 5 discrete subsets (or “folds”). The model was trained on 4 folds of the data. A fold of the data was kept for validation within each iteration. Therefore, each model used the data obtained from the clinical follow-up and microRNA-sequencing described above in training and validation, which included 2656 miRs and 2 MSC(M) samples (synovial fluid-treated and untreated) from each patient. Each sample was treated as independent.

[0171] The outcome was modelled as the difference from baseline KOOS subscale / overall KOOS scores. Clinical follow-up data was available for all patients at both 12 months and 24 months. The outcome was defined using the following formula:

[0172] A = Baseline - Follow-up (i2 or 24-months)

[0173] The analyst was blinded to the miRs that could indicate associations. Associations were defined statistically for rejecting the null hypothesis at the alpha level of 0.05. The associations were detected from the statistical model. No additional parameters were used to include or exclude miRs from selection. The minimum lambdavalue was used to select the miRs for predictions in the form of regression coefficients. All the analyses were completed using the R GLMNET package.

[0174] These models identified miRs predictive of an association with at least one KOOS subscale or overall KOOS after the 5-fold cross-validation. Applying regularization in the machine learning models increases the likelihood that the identified miRs will have an association with the KOOS subscales and overall KOOS in future datasets, as the models “regularize” the associations and move them closer to the null to limit overfitting.

[0175] Statistical analyses

[0176] GraphPad Prism 6.0 (La Jolla, USA) and JMP Pro 17 (Cary, USA) software were used for statistical analyses and to create plots. Statistical tests are specified in the figure and table descriptions. Spearman’s correlation was selected as a non-parametric statistical test to investigate associations between KOOS changes (delta or percentage change) and other variables, given that variables within our dataset violated assumptions of normality and homoscedasticity. Spearman’s correlation offers further advantages including that it does not assume linear associations (instead, it assesses monotonic relationships), and that dependent / independent variables do not need to be specified. P values derived from Spearman’s correlation were not corrected for multiple comparisons given our exploratory analyses with a limited dataset, and that common methods for multiple comparison corrections rely on assumptions of normality. P values less than 0.05 were considered statistically significant.

[0177] For miR-Seq analysis, differential expression was performed using the DE- Seq2 algorithm developed by Love et al. (28). MiRs were considered significantly differentially expressed based on adjusted p values <0.05 and absolute fold-change >1 .5.Results

[0178] Patient responder status to intra-articular MSC(M) injection in knee osteoarthritis

[0179] Using patient-reported Knee injury and Osteoarthritis Outcome Score (KOOS) data the inventors reported in a previous study which followed patients to the study endpoint of 12 months (11), criteria from the Osteoarthritis Research Society International Standing Committee for Clinical Trials Response Criteria Initiative and theOutcome Measures in Rheumatology (OMERACT-OARSI) (19) were applied to determine responder status, with modifications. The OMERACT-OARSI criteria offers a rigorous classification system developed using data from large, powered placebo- controlled drug trials for hip and knee OA (19). These criteria categorize patients as responders according to the following: i) improvement in pain or in function >50% and absolute change > 20; OR, ii) improvement (>20% and absolute change > 10) in at least two of the following: a) pain, b) function, c) patient global assessment (not measured in the clinical trial). Given the limited sample size and lack of patient global assessment metric in the previous clinical trial, patients were categorized based on changes in KOOS function in daily living (using the ADL subscale corresponding to a function score) and KOOS Pain only, and thresholds were applied based on the OMERACT-OARSI criteria for function and pain scores of delta value >10 AND percentage change >20% to determine responder status (19). The KOOS instrument was selected for evaluating responder status, as it is a validated tool for measuring responses to interventions in OA with high test-retest reliability and improved sensitivity in pain and function scoring relative to the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scoring system (19-21). Using KOOS ADL and pain, the criteria applied for determining responders were more relaxed to accommodate for a smaller sample size and lack of patient global assessment scores, and it consisted of the following: i) Function-Pain Responders (patients exceeding thresholds in both ADL and Pain scores); ii) Function Responders (patients exceeding thresholds only in ADL scores), and iii) Pain Responders (patients exceeding thresholds only in Pain scores) (Table 1). Six Function- Pain Responders (3 / 6 Function-Pain Responder patients self-identified as women), seven Function Responders (including the six Function-Pain Responders; 4 / 7 Function Responder patients self-identified as women), and seven Pain Responders (including the six Function-Pain Responders; 4 / 7 Pain Responder patients self-identified as women) were identified. The remaining patients were classified as Non-Responders. While the sample size is limited, the binary responder / non-responder criteria are useful for the analyses applied in the present work to determine miRs influencing MSC(M) basal fitness.

[0180] Notably, while the present clinical trial was under-powered to evaluate dose responses, Function-Pain Responders were observed across all three MSC(M) doses applied in the trial, including the 1 x 106cell dose (2 / 4 patients), 10 x 106cell dose (1 / 4patients), and the 50 x 106cell dose (3 / 4 patients) (Table 1). One patient within the 10x106cell dose group responded in terms of KOOS Pain (but not ADL) and was classified as a Pain Responder / Non-Responder, while another patient within the 50 x 106cell dose group responded in terms of KOOS ADL (but not pain) and was classified as a Function Responder / Non-Responder. These data align with previous findings (11 , 33, 34) reporting higher doses of > 50x106cells afforded improved patient outcomes, as discussed in a recent review of MSC therapies for OA (10). However, varying levels of responses were observed across all dose groups, indicating that other factors influence patient responses to MSC(M) injection, including basal MSC(M) fitness which was investigated in detail within the present study.

[0181] miRs as putative Critical Quality Attributes (CQAs)

[0182] MiR-sequencing was performed to analyze the miRNome of biobanked MSC(M) from the previous knee OA clinical trial. Principal component (PC) analysis of the miRNome for MSC(M) samples that did or did not result in clinical response posttreatment demonstrated that samples clustered by donor and by responder / non- responder status rather than by synovial fluid treatment (FIG. 1), and there were no significant differentially expressed miRs when comparing synovial fluid-supplemented versus untreated MSC(M). Thus, both synovial fluid-supplemented and untreated samples were used to evaluate MSC(M) donor differences based on responder status. Notably, PC analysis also indicated that MSC(M) derived from patient ID #10 (labelled as a Function Responder) appeared to cluster with MSC(M) derived from Function-Pain Responders rather than Non-Responders based on the miRNome, while the miR profile of MSC(M) derived from patient ID #6 (labelled as a Pain Responder) appeared to cluster more closely with Non-Responders (FIG. 1).

[0183] To identify miRs as putative CQAs, differential expression analysis was performed to compare basal miR expression levels in MSC(M) donors classified as responders (Function-Pain, Function, or Pain Responders) versus Non-Responders. This analysis revealed 33 significantly differentially expressed miRs (adjusted p value<0.05, absolute fold change > ±1 .5) between MSC(M) donors classified as Function Responders vs. Non-Responders, with 11 miRs that were upregulated and 22 miRs that were downregulated in Function Responders (FIG. 2A, Table 3). Additionally, 14 miRs were significantly differentially expressed between MSC(M) donors classified asFunction-Pain Responders and Non-Responders, with 8 miRs that were upregulated and 6 miRs that were downregulated in Function-Pain Responders (FIG. 2B, Table 2). Within these panels of significantly differentially expressed miRs, 10 miRs (hsa-miR-483-5p, hsa-miR-4775, has-miR-140-3p, has-miR-19a-3p, hsa-miR-31-3p, has-miR-19b-3p, has- miR-642a-5p, hsa-miR-210-3p, has-miR-34a-5p, hsa-miR-338-5p) were common to both panels identified by comparing Function-Pain Responders to Non-Responders, and Function Responders to Non-Responders (FIG. 2C). Analysis of the miR profiles for MSC(M) derived from Pain Responders versus Non-Responders identified only one significantly differentially expressed miR that was unique from either of the differentially expressed miR panels obtained for Function-Pain Responders and Function Responders (Table 4). A summary of all 38 differentially expressed miRs and their nucleic acid sequences is provided in Table 5.

[0184] In addition to differential expression analysis, comparing MSC(M) derived from responders and non-responder donors, supervised machine learning analysis using LASSO regression was also performed to identify microRNAs associated with changes in KOOS subscales at 12- and 24-months relative to baseline (using delta change values only to fulfill normality assumptions of the model). This analysis identified a total of 38 microRNAs ( Table 6), including 7 microRNAs that overlapped with the panels of microRNAs identified through the differential expression analysis (namely hsa-miR-1307- 3p, hsa-miR-20a-3p, hsa-miR-210-3p, hsa-miR-338-3p, hsa-miR-4775, hsa-miR-483-5p, hsa-miR-642a-5p). miRs associated with changes in KOOS subscales at 12 and 24 months are shown in Table 7 and Table 8, respectively. Notably, several microRNAs were associated with improvements in multiple KOOS subscales. MicroRNAs for which upregulated expression was associated with improvements in multiple KOOS subscales at 12 months relative to baseline included: hsa-miR-127-3p (KOOS ADL, Overall KOOS), hsa-miR-483-5p (KOOS ADL, Pain, Overall KOOS), hsa-miR-548l (KOOS Symptom, Pain, QOL, Overall KOOS), and hsa-miR-766-3p (KOOS Symptom, Pain, ADL, Sports / Rec, Overall KOOS). MicroRNAs for which downregulated expression was associated with improvements in multiple KOOS subscales at 12 months relative to baseline included: hsa-miR-1973 (KOOS Pain, Overall KOOS), hsa-miR-210-3p (KOOS ADL, QOL, Overall KOOS), hsa-miR-4775 (KOOS Symptom, QOL, Overall KOOS), hsa- miR-642a-5p (KOOS Pain, ADL, Overall KOOS), hsa-miR-8485 (KOOS Pain, Overall KOOS). MicroRNAs were also identified as being associated with improvements inmultiple KOOS subscales at 24 months relative to baseline, including upregulated expression of hsa-miR-127-3p (KOOS Symptom, ADL, Overall KOOS), hsa-miR-483-5p (KOOS Symptom, Pain, ADL, Overall KOOS), hsa-miR-5010-5p (KOOS ADL, Overall KOOS), hsa-miR-598-3p (KOOS ADL, QOL, Overall KOOS), hsa-miR-766-3p (KOOS ADL, KOOS Sports / Rec, Overall KOOS), and downregulated expression of hsa-miR- 642a-5p (KOOS Pain, ADL, Overall KOOS) and hsa-miR-8485 (KOOS Pain, Overall KOOS).

[0185] Select miRs were measured by qPCR, which verified significant differential expression for one miR (hsa-miR-140-3p) out of 12 miRs measured by qPCR from the panel of 33 differentially expressed miRs in MSC(M) donors from Function Responders vs. Non-Responders (FIG. 3). Similarly, significant differential expression was verified for one miR, hsa-miR-642a-5p, out of five miRs measured from the panel of 14 differentially expressed miRs in MSC(M) donors from Function-Pain Responders versus NonResponders ( FIG. 4). These data indicate that more sensitive tools are needed to verify differential expression between responder and non-responder MSC(M), as miR-Seq demonstrated that many of the differentially expressed miRs were expressed at low levels (baseMean <100) and / or with fold-change values <2, which may be insufficiently detected by qPCR.

[0186] Two of the microRNAs measured in MSC(M) by qPCR (hsa-miR-642a-5p and hsa-miR-483-5p) were contained within the panels identified using the machine learning approach. Correlation analyses were performed to validate significant negative correlations between hsa-miR-642a-5p levels (measured by qPCR) with improvements (delta values) in KOOS Pain, ADL, and Overall KOOS at both 12 and 24-months relative to baseline (FIGs. 5A, 5B), thereby corroborating the results from the machine learning analysis. Correlation analyses between levels of hsa-miR-483-5p with changes in KOOS identified through the machine learning analysis showed weak non-significant positive correlations to KOOS improvements (delta values) at both 12- and 24-months relative to baseline (FIGs. 5C, 5D), further suggesting that more sensitive measurement tools may be needed for measuring this microRNA in MSC(M).

[0187] Taken together, these data provide insight into miRs that are differentially expressed in MSC(M) with higher basal fitness (based on clinical data), and they cantherefore serve as CQAs. These analyses further indicate greater similarity of basal miR profiles and fitness of MSC(M) that induce functional improvements in knee OA patients.Discussion

[0188] Unbiased miR-Seq was performed to analyze MSC(M) and probe potential CQAs, given that miRs are important epigenetic regulators of MSC fitness (23) and can mediate MSC mechanisms of action, including immunomodulatory, angiogenic, and chondroprotective effects (23-25). Analysis of the miRNome in these MSC(M) samples demonstrated panels of miRs that were significantly differentially expressed between MSC(M) derived from Function-Pain and / or Function Responders relative to NonResponders. Analysis of the miRNome further identified panels of miRs whose expression is associated with improvements in KOOS measures at 12- and 24- months post treatment, 7 of which overlapped with the miRs identified in the differential expression analysis. These analyses further confirmed greater similarity of MSC(M) derived from Function Responders based on the multivariate miR profiles that showed similar clustering based on this responder classification. Further, qPCR was used to validate differential expression for hsa-miR-642a-5p expression in MSC(M) donors from Function-Pain Responders and hsa-miR-140-3p in Function Responders compared to Non-Responders. These miRs have previously been shown to regulate TLR4 signaling in THP-1 cells

[0029] , and mediate immunosuppressive functions of Wharton's jelly-derived mesenchymal stem cells (MSC(WJ))

[0030] , respectively. The differentially expressed panels can serve as CQAs for identifying basally fit MSC(M) for treating knee OA and other MSC-treatable diseases.Example 2 - MicroRNAs and adipose-tissue derived MSCs (MSC(AT)) and induced pluripotent stem cells-derived MSCs (iMSCs)

[0189] Expression of a subset of the identified miRs in MSC(M) (Example 1 ) was measured in other MSC sources, including adipose-tissue derived MSCs (MSC(AT)) and induced pluripotent stem cells-derived MSCs (iMSCs).Methods

[0190] MSC culture:

[0191] Four MSC(AT) donors (passage 3-5) were cultured until 70-90% confluency in MesenCult-ACF Plus medium (STEMCELL Technologies). The cells were plated at 60,000 cells / well in 24-well plates and cultured for 24 h prior to harvest. ThemiR expression was benchmarked against historical in vitro assay data to measure the immunomodulatory (monocyte / macrophage polarization) fitness of the cells as previously described (Robb et al, 2022; CA Patent Application No. 3,204,310).

[0192] iMSCs from an immortalized line (StemRNA™ Human iPSC SK005.3, product code: RCRP010N) were externally sourced and cultured using the manufacturer’s protocols in StemXVivo medium (R&D Systems). iMSCs were plated at 60,000 cells / well in 24-well plates in MesenCult-ACF Plus medium (STEMCELL Technologies) with or without addition of doxycycline. The cells were cultured for 24 h prior to harvest.

[0193] MSC(M)s derived from healthy bone marrow were also investigated. The cells were expanded in DMEM supplemented with 10% fetal bovine serum, harvested, and plated at 60,000 cells / well in 24-well plates in MesenCult-ACF Plus medium (STEMCELL Technologies).

[0194] MicroRNA measurement:

[0195] After culture, MSCs from all wells were harvested for RNA extraction using the Qiazol miRNA extraction kit (Qiagen). A subset of miRs was measured using the nCounter platform (NanoString).Results

[0196] miR Hsa-miR-15b-5p (SEQ ID NO: 4: Figure 6)

[0197] This miR was shown in Example 1 to be downregulated in Function Responder vs Non-Responder MSC(M) from the OA clinical trial.

[0198] In MSC(AT), the expression was lowest in donor AT01 , which has the highest immunomodulatory fitness levels of the three MSC(AT) donors tested based on historical data (Robb et al, 2022; CA Patent Application No. 3,204,310). Given that hsa- miR-15b-3p was lower in MSC(M) that were more efficacious in the OA clinical trial, this finding in AT-MSCs corroborates the findings of Example 1 as it shows that MSCs with higher basal fitness levels have lower expression of this miR.

[0199] Expression of this miR was also detected in iMSCs. Its level of expression was dependent on the culture conditions, wherein the expression level with doxycycline is consistent with MSC(AT) expression.

[0200] The miR was also detectable in a healthy MSC(M) donor which showed lowest expression of the miR.

[0201] miR Hsa-miR-210-3p (SEQ ID NO: 18; Figure 7)

[0202] This miR was shown in Example 1 to be down regulated in Responder MSC(M) through differential expression analysis (significantly downregulated in Function Responder vs Non-Responder MSC(M) and in Function-Pain Responder vs Nonresponder MSC(M)), and through machine learning analysis.

[0203] Expression levels of the miR were low and close to the detection limit; however, the expression trended lowest in donor AT01 , which has the highest immunomodulatory fitness levels of the three MSC(AT) donors tested based on the historical data (Robb et al, 2022; Canadian Patent Application No. 3,204,310). Given that hsa-miR-210-3p was lower in MSC(M) that were more efficacious in the OA clinical trial, this finding in MSC(AT) corroborates the work in Example 1 as it shows that MSCs with higher basal fitness levels have lower expression of this microRNA.

[0204] Expression of this miR was also measured in iMSCs. Its level of expression was dependent on the culture conditions, wherein the expression level with doxycycline is consistent with MSC(AT) expression.

[0205] The miR was also detectable in a healthy MSC(M) donor which showed relatively higher expression of the miR.Summary

[0206] Additional data are here provided for two miRs in MSC tissue sources aside from MSC(M). The data corroborates Example 1 , which used MSC(M) samples from the OA clinical trial, as they show that lower levels of expression of these miRs were observed in MSC(AT) with higher baseline immunomodulatory fitness. The miRs can be measured in iMSCs, which is an MSC source that is of high interest to the field for clinical translation of MSC therapies.

[0207] While the present disclosure has been described with reference to examples, it is to be understood that the scope of the claims should not be limited by the embodiments set forth in the examples, but should be given the broadest interpretation consistent with the description as a whole.

[0208] All publications, patents and patent applications are herein incorporated by reference in their entirety to the same extent as if each individual publication, patent or patent application was specifically and individually indicated to be incorporated by reference in its entirety. Where a term in the present description is found to be defined differently in a document incorporated herein by reference, the definition provided herein is to serve as the definition for the term.Table 1. Patients classified as Function-Pain Responders, Function Responders, Pain Responders, or Non-Responders based on changes in KOOS ADL and Pain scores at 12 months relative to baseline.Table 2. Significantly differentially expressed microRNAs between MSC(M) derived from Function-Pain Responders versus Non-Responders.Table 3. Significantly differentially expressed microRNAs between MSC(M) derived from Function Responders versus Non-Responders.Table 4. Significantly differentially expressed microRNA between MSC(M) derived from Pain Responders versus Non-Responders.Table 5. miRs from Function Responders, Pain Responders, and / or Function-Pain Responders with basal significant differential expression compared to NonResponders, and their nucleic acid sequences.Table 6. miRs identified by machine learning as associated with changes in PROMs at 12 and 24 months relative to baseline, and their nucleic acid sequences.Table 7. MicroRNAs expressed by MSC(M) associated with improvements in KOOS at 12 months relative to baseline identified through machine learning analysis. The effect of a one-unit increase in the microRNA expression level on the change (delta value) in KOOS is listed for each microRNA, such that positive values indicate that higher expression of the microRNA is associated with KOOS improvements, while negative values indicate that lower expression of the microRNA is associated with KOOS improvements.Table 8. 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Claims

Claims:1 . A method of determining basal fitness of a sample of mesenchymal stromal cells (MSCs) comprising: determining a sample microRNA (miR) profile, the sample miR profile comprising the levels of at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69; and determining the level of similarity of said sample miR profile to one or more reference profiles, wherein (i) a high level of similarity of the sample miR profile to a basal fitness specific reference profile; (ii) a low level of similarity to a non-basal fitness specific reference profile; and / or (iii) a higher level of similarity to a basal fitness specific reference profile than to a non-basal fitness specific reference profile, indicates the cells have basal fitness.

2. The method of claim 1 , wherein the miR profiles are analyzed using combinatorial or multivariate dimension reduction statistical or mathematical methods.

3. The method of claim 2, wherein the combinatorial or multivariate dimension reduction statistical or mathematical methods comprise clustering analyses, machine learning analysis methods, or desirability analysis to enable comparisons between multivariate miR profiles with dimension-reduced empirical values.

4. The method of any one of claims 1 to 3, wherein a higher level of similarity to the basal fitness specific reference profile than to the non-basal fitness specific reference profile is indicated by a higher correlation value computed between the sample profile and the basal fitness specific reference profile than an equivalent correlation value computed between the sample profile and the non-basal fitness specific reference profile, optionally wherein the correlation value is a correlation coefficient.

5. The method of claim 4, wherein the correlation coefficient is a linear correlation coefficient, optionally a Pearson correlation coefficient, or a monotonic correlation coefficient, optionally a Spearman’s correlation coefficient.

6. The method of claim 5, wherein a high level of similarity to the reference profile is indicated by a Pearson correlation coefficient or a Spearman’s correlation coefficient between the sample profile and the reference profile having an absolute value between 0.5 to 1 , optionally between 0.75 to 1 , and a low level of similarity to the reference profile is indicated by a correlation coefficient between the sample profile and the reference profile having an absolute value between 0 to 0.5, optionally between 0 to 0.25.

7. A method of determining quantitative values for a set of miRs for assessing basal fitness of a sample of mesenchymal stromal cells (MSCs), the method comprising: a) measuring levels of the set of microRNAs (miRs) for the sample, wherein the set of miRs comprises at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69; b) obtaining the basal fitness status of the sample; and c) conducting a regression analysis between each miR of a) with the basal fitness of b); determining minimum and maximum data values of each miR of the sample and using multivariate dimension reduction statistical or mathematical methods to assign minimization or maximization functions to indicate whether higher or lower values are desirable based on the directionality of correlation respectively.

8. The method of claim 7, further comprising d) assigning a weighting to each miR for desirability analysis based on the R2values from the regression analysis; and e) assigning a score from zero to one using desirability analysis to each sample based on the range of data values; wherein zero is undesirable and one is highly desirable to obtain a set of values for MSCs for each donor.

9. The method of claim 7 or 8, wherein the basal fitness status of the sample in step b) is obtained from a clinical sample for which the basal fitness or efficacy of the MSCs was previously evaluated clinically.

10. The method of claim 7 or 8, wherein the obtaining of the basal fitness status of the sample in step b) comprises:I) determining at least one patient-reported outcome measure (PROM) score from an assessment of an MSC-treatable disease from a subject with the MSC- treatable disease pre-treatment with the sample;II) determining the at least one PROM score from the assessment of the MSC- treatable disease from the subject post treatment with the sample;III) comparing the at least one PROM score in I) and II); andIV) assigning a basal fitness score to the sample based on the size of the improvement in the at least one PROM score post-treatment compared to pretreatment, wherein an improvement in the at least one PROM score posttreatment is indicative that the basal fitness score of the sample is high, and wherein no improvement or a worsening in the at least one PROM score posttreatment is indicative that the basal fitness score of the sample is low.11 . The method of claim 10, wherein step 11) is performed 12 to 24 months post treatment with the sample.

12. The method of claim 10 or 11 , wherein the MSC-treatable disease comprises osteoarthritis (OA), lupus, scleroderma, rheumatoid arthritis, graft versus host disease, stroke, inflammatory bowel disease, or cardiac disease.

13. The method of claim 12, wherein the MSC-treatable disease comprises OA.

14. The method of claim 12 or 13, wherein the OA comprises knee OA, and wherein the assessment of the MSC-treatable disease comprises an assessment of knee OA.

15. The method of claim 14, wherein the assessment of knee OA comprises Knee injury and Osteoarthritis Outcome Score (KOOS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Visual Analogue Scale (VAS), Short Form 36 (SF-36) or Short Form 12 (SF-12), Tegner Lysholm Knee Score, Knee Society Clinical Rating System, Lequesne Index for Knee Osteoarthritis, Oxford Knee Score (OKS) and / or International Knee Documentation Committee (IKDC) Questionnaire.

16. The method of claim 15, wherein when the assessment of knee osteoarthritis comprises KOOS, the PROM score comprises KOOS Pain, KOOS Symptoms, functionin daily living (ADL), function in Sport and Recreation (Sports / Rec), knee-related quality of life (QOL), or Overall KOOS, or combinations thereof.

17. A method of determining basal fitness of a sample of mesenchymal stromal cells (MSCs) comprising a) determining a sample microRNA (miR) profile, the sample miR profile comprising levels of at least one miR, each miR comprising a nucleic acid sequence selected from SEQ ID NOs: 1-69; and b) ranking the miR profile of a) based on a comparison of minimum and maximum values determined by the method of any one of claims 7-17 for the same particular donor to determine the basal fitness.

18. The method of any one of claims 1 -17, wherein each of the at least one miR comprise a nucleic acid sequence selected from SEQ ID NOs: 1 -33.

19. The method of any one of claims 1 -17, wherein each of the at least one miR comprise a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, 32, and 34-37.

20. The method of any one of claims 1 -17, wherein each of the at least one miR comprise a nucleic acid sequence selected from SEQ ID NOs: 2, 3, 5-8, 16, 18, 26, and 32.

21. The method of any one of claims 1 -17, wherein each of the at least one miR comprise a nucleic acid sequence selected from SEQ ID NOs: 2, 8, 18- 20, 26, and 35.

22. The method of any one of claims 1 -17, wherein the sample miR profile comprises the levels of 69 miRs, wherein the 69 miRs comprise nucleic acid sequences as shown in SEQ ID NOs: 1-69.

23. The method of any one of claims 1 -22, wherein the MSCs are derived from adipose tissue, bone marrow, dental pulp, synovium, placenta, umbilical cord, or induced pluripotent stem cells.

24. The method of claim 23, wherein the MSCs are derived from bone marrow.

25. The method of claim 23, wherein the MSCs are derived from adipose tissue.

26. The method of claim 24, wherein the MSCs are derived from induced pluripotent stem cells.

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