Stem cell subpopulations with differential GSTT1 expression or genotype

Abstract

A method for providing a sub-population of stem cell or plurality of stem cells by determining or modulating GSTT1 expression level or genotype is disclosed together with uses of the stem cells.

Claims

1. A method for selecting a stem cell donor, the method comprising: (a) determining the genotype for GSTT1 in a DNA-containing sample isolated from an individual, and selecting as the stem cell donor an individual determined to have a GSTT1 genotype which is known, and/or which would be predicted, to result in decreased expression of GSTT1 relative to individuals homozygous for wildtype; or (b) determining the level of GSTT1 expression by a stem cell or plurality of stem cells in a sample isolated from an individual, and comparing the determined level of GSTT1 expression to a reference value for the level of GSTT1 expression for that stem cell type, and selecting as the stem cell donor an individual determined to have a stem cell or plurality of stem cells having decreased GSTT1 expression relative to the reference value, the method further comprising separating and/or isolating a stem cell or plurality of stem cells from the individual selected as a stem cell donor, wherein the stem cell or plurality of stem cells separated and/or isolated from the individual selected as the stem cell donor is a mesenchymal stem cell (MSC) or plurality of MSCs obtained from the bone marrow of the individual selected as a stem cell donor.

2. The method according to claim 1, wherein the stem cell or plurality of stem cells additionally possess one or more of the following characteristics as compared to a reference population of stem cells: (i) enhanced colony forming capacity; (ii) reduced cell size; (iii) increased telomere length and/or a reduced rate of telomere shortening; (iv) increased expression of STRO-1, SSEA-4, CD146 and/or PDGFRβ; (v) increased secretion of FGF-2, VEGF, SDF-1α, fractalkine, PDGF-BB and/or MIP-1α; (vi) enhanced suppression of T cells; (vii) decreased expression of ALP, RUNX2 and/or BSP-II; and (viii) increased expression of TWIST-1 and DERMO-1.

3. The method according to claim 1, wherein determining the genotype for GSTT1 in a DNA-containing sample isolated from an individual comprises detecting the presence of a wildtype GSTT1 allele, a GSTT1 allele which is known and/or which would be predicted to result in decreased expression of GSTT1 relative to the wildtype GSTT1 allele, and/or a GSTT1 null allele.

4. The method according to claim 3, wherein the method of detecting the presence of a wildtype GSTT1 allele, a GSTT1 allele which is known and/or which would be predicted to result in decreased expression of GSTT1 relative to the wildtype GSTT1 allele, and/or a GSTT1 null allele comprises contacting the DNA-containing sample with one or more oligonucleotide primers suitable for use to detect the presence of a wildtype GSTT1 allele, a GSTT1 allele which is known and/or which would be predicted to result in decreased expression of GSTT1 relative to the wildtype GSTT1 allele and/or a GSTT1 null allele.

5. The method according to claim 4, wherein the one or more oligonucleotide primers comprise one of more of 5′-TCTTTTGCATAGAGACCATGACCAG-3′ (SEQ ID NO:12), 5′-CTCCCTACTCCAGTAACTCCCGACT-3′ (SEQ ID NO:13), 5′-GAAGCCCAAGAATGGGTGTGTGTG-3′ (SEQ ID NO:14) and 5′-TGTCCCCATGGCCTCCAACATT-3′ (SEQ ID NO:15).

Description

BRIEF DESCRIPTION OF THE FIGURES

(1) Embodiments and experiments illustrating the principles of the invention will now be discussed with reference to the accompanying figures in which:

(2) FIGS. 1A and 1B.

(3) (FIG. 1A) Classification of the GST superfamily based on sequence homology and structure. (FIG. 1B) GST enzymes catalyze the conjugation of glutathione to xenobiotics.

(4) FIG. 2.

(5) Frequency of GSTT1 homozygous deletion across several populations.

(6) FIG. 3.

(7) Continuous monitoring of cell proliferation for fast and slow growing MSC lines. The number of viable cells in a culture well was assessed (Cell Index) over 5 days (time shown in hours) on the xCELLigence system. Results are shown for 2 independent cell lines representing each group, with 3 technical replicates of each. Line starting below and then crossing over and remaining above the other line=fast-growing; the other line=slow-growing.

(8) FIGS. 4A-4D.

(9) (FIG. 4A) Normalized microarray beadchip signal. All the slow growers (B, D and F) express GSTT1 at a modest level, while two of the fast growers (A and C) have negligible expression. (FIG. 4B) Genotyping of GSTT1. BM-MSC lines A and C are nulls (GSTT1−/−) and the remaining are positive (B, D, E, F: GSTT1+/−; 10R, 11R: GSTT1+/+). (FIG. 4C) Expression analysis by qRT-PCR. GSTT1 level is correlated with copy number of alleles. (FIG. 4D) Protein expression analysis. The expression was consistent with the ‘trimodal effect’.

(10) FIGS. 5A and 5B.

(11) Evaluation of DNA damage by comet assay. Lysis and electrophoresis were performed on cells embedded in low melting point agarose on microscope slides. (FIG. 5A) Comet images after comet assay. DAPI-stained nuclei of slow and fast growers have similar extent of tail length. (FIG. 5B) Quantification of DNA lesion by olive tail moment detected inconsiderable damage in both groups.

(12) FIGS. 6A and 6B.

(13) Evaluation of DNA damage after oxidative stress by comet assay. Embedded cells were treated with 10 μM hydrogen peroxide for 20 min before lysis and hOGG1 treatment, followed by electrophoresis. Controls: untreated, mutagen only and enzyme only. (FIG. 6A) Comet images after comet assay. The tail length increases upon hydrogen peroxide and enzyme treatments, but comparable tail lengths between the fast and slow growers. (FIG. 6B) Olive tail measurement of DNA damage. No difference detected between the groups under the various treatments.

(14) FIGS. 7A and 7B.

(15) GSTT1 expression analysis across passages by qRT-PCR (FIG. 7A) and western blot (FIG. 7B). Expression of GSTT1 increases with passage.

(16) FIGS. 8A-8D.

(17) (FIG. 8A) GSTT1 knockdown efficiency. Lentiviral infection of slow growers with shRNA for GSTT1 results in decline of mRNA level by 70% compared to nonsilencing control. (FIG. 8B) Viable cell count. 80% increase in cell number seen in the knockdown in comparison to control. (FIG. 8C) EdU labeling assay. Analysis by flow cytometry after 18 h incubation of cells with 10 μM EdU and reaction with copper sulfate and 647-azide reaction. Significant increase in the population of dividing cells with the knockdown. (FIG. 8D) Real-time proliferation measurement on the xCELLigence system. Knockdown has shorter doubling time.

(18) FIGS. 9A-9C.

(19) Clonogenic potential assessment by CFU-F assay. 150 cells plated in 10 cm format were maintained in culture for 2 weeks, fixed and stained with Geimsa. (FIG. 9A) Giemsa-stained plates. Knockdown has larger and higher number of colonies than control. (FIG. 9B) Quantification of CFU-F frequency. Higher frequency of CFU-F detected with knockdown. (FIG. 9C) Measurement of colony size. Knockdown has an increase in colony size.

(20) FIGS. 10A-10D.

(21) (FIG. 10A) GSTT1 overexpression analysis. Transfection of expression vector in fast growers (null) found GSTT1 level increasing by about 50 000 fold of control at 3 days post-transfection. (FIG. 10B) Viable cell count. 40% decrease in cell number in the overexpression system compared to control. (FIG. 10C) EdU labeling assay. Flow cytometric analysis following labeling show decline in the number of dividing cells with overexpression. (FIG. 10D) xCELLigence system run. Increase in growth rate with overexpression.

(22) FIGS. 11A-11F.

(23) Characterisation of BMMNCs isolated from donors A-F. (FIG. 11A) microscopy of BMMCs isolated from donors. (FIG. 11B) Bar chart showing CFU-F efficiency and colony size. (FIG. 11C) Left panel: bar chart showing proportions of ‘small’ cells. Right panel: scatterplot showing. (D) Graph and bar charts showing cell numbers through passages. (E, F) Graph and bar chart showing telomere length through passages (FIG. 11E) and R.sup.2 value [correlation coefficient] (FIG. 11F).

(24) FIG. 12.

(25) Scatterplot showing surface phenotypic profiles of hMSCs. A panel of twenty-four CD markers were checked for their expression on hMSCs. Cells from all the donors satisfied the minimal criteria set by the ICST by demonstrating >95% expression for CD103, CD73, and CD90, and, <2% expression for haematopoietic markers. The dotted reference line corresponds to 2%. The cells showed variability in the expression of growth factor receptors and additional hMSC-related markers such as CD146, STRO-1, and SSEA-4.

(26) FIG. 13.

(27) Bar chart showing cytokines and growth factors produced by hMSCs from donors A-F.

(28) FIG. 14.

(29) Bar chart showing production of growth factors by hMSCs from donors A-F.

(30) FIGS. 15A-15B.

(31) Analysis of ability of MSC to inhibit T-cell proliferation (FIG. 15A) Bar chart showing dose-dependent suppression of T cell proliferation under antibody stimulation by hMSCs. (FIG. 15B) Table summarising the results. *P<0.05.

(32) FIGS. 16A-16C.

(33) Gene expression by fast-growing and slow-growing hMSCs (FIG. 16A) Bar charts showing TWIST-1 and DERMO-1 expression by fast-growing and slow-growing hMSCs. (FIG. 16B) Representation of differentially expressed genes. (FIG. 16C) Plots showing expression of RUNX2, ALP, BSP-II, SOX9, COL2, CEBPα and PPARγ by fast-growing and slow-growing hMSCs isolated from donors A-F. *P<0.05

(34) FIGS. 17A-17C.

(35) Multilineage differentiation ability by fast-growing and slow-growing hMSCs isolated from donors A-F. (FIG. 17A) Plots showing expression of RUNX2, BSP-II, ALP, COL2A1, SOX9 CEBPα and PPARγ by fast-growing and slow-growing hMSCs isolated from donors A-F. (FIG. 17B) Images showing von Kossa, Alizarin red, Alician blue and Oil red O staining of cells isolated from donors A-F. (FIG. 17C) Plots showing quantification of stainings of (B). *P<0.05, **P<0.01.

(36) FIGS. 18A-18E.

(37) Ectopic bone formation by hMSC isolated from donors A-F in mice in vivo (FIG. 18A). (FIG. 18B) Images, x-rays and 3D μCT images of bone formed by hMSC isolated from donors A-F (FIG. 18C) Bar charts and (FIG. 18D) box plot showing bone volume formed by hMSC isolated from donors A-F; *P=0.002, ANOVA (post-test, Fisher LSD). (FIG. 18E) Bar chart showing bone volume formed by fast- and slow-growing hMSC; *P=<0.001 (t-test).

(38) FIGS. 19A-19B.

(39) (FIG. 19A) Immunohistochemical analysis of sections harvested from in vivo implants of hMSC fast-growing and slow-growing hMSCs isolated from donors A-F. (FIG. 19B) Histological analysis. Representative images on a scale of least (left) to highest (right) bone formation. For each donor, first three panels=H&E staining, last three panels=Rallis trichrome staining. Lighter staining=fibrous tissue, darker staining=bone tissue.

(40) FIG. 20.

(41) Photographs showing colonies of hMSCs formed when plating bone marrow mononuclear cells from donors A-F.

(42) FIG. 21.

(43) Representative schematic of CFDA-SE assay. T cells and hMSCs from a representative fast-growing donor (donor A) or representative slow-growing donor (donor F) were co-cultured in varying proportions of T cell: MSC. The percentage of T cells proliferating can be derived from the CFSE-read out (read by the FITC channel) where peaks show successive cell divisions. The scatter plots (SSC vs FITC) indicate the percentage of cells positive for FITC. Differences in the size of the proliferating T cell colonies are visualized by the T cell micrographs of individual wells of a 96-well plate. Positive controls (no hMSCs) and negative control (no antibody) are also included.

(44) FIG. 22.

(45) Scanned images of 6-well plates showing differences between the staining intensity of induction (top wells) and control cultures (bottom wells) stained by the von Kossa method and with Alizarin Red to detect mineralization during osteogenesis, and Oil red O to detect lipid formation during adipogenesis. Sections of pellets stained with Alcian blue showing differences in glycosaminoglycan formation during chondrogenesis.

(46) FIG. 23.

(47) Schematic diagram showing the genomic location of GSTT1 and the deletion responsible for the null allele (reproduced from Teixeira et al., (2013) Tuberculosis—Current Issues in Diagnosis and Management; Chapter 6: Tuberculosis Pharmacogenetics: State of the Art). The null allele of GSTT1 results from a 50 kbp deletion that encompasses the entire gene on chromosome 22. The null genotype is common (20-58%) in human populations.

(48) FIG. 24.

(49) Schematic diagram of the assay for the detection of the deleted and wildtype GSTT1 alleles. In the presence of GSTT1, the GSTT1_Deletion primer set will not amplify a product since the distance between the forward and reverse primer is too long for amplification, and only the GSTT1_Gene primer set will generate a product. Amplification by the GSTT1_Deletion will only occur in the absence of the gene.

EXAMPLES

Example 1—GSTT1 is a Prognostic Biomarker of Function Mesenchymal Stem Cells for Bone Regeneration

(50) The gene encoding Glutathione-S-transferase isoform T1 (GSTT1) is commonly deleted in the human population. The present inventors have found that the GSTT1 genotype significantly affects the proliferation and bone-forming potential of BM-MSC derived from patients. In particular, the null allele of GSTT1 renders BM-MSC with greater proliferation in vitro and improved bone forming activity, relative to BM-MSC that retain a functional allele of GSTT1.

(51) This finding is clinically applicable as it provides a means to pre-screen and select donors based on their genotype thus improving the efficacy of bone repair with BM-MSC transplantation.

(52) 1.1 Variation in Proliferation Rate Between Fast and Slow Growers

(53) Bone marrow-derived mesenchymal stem cells (BM-MSC) from several donors have been were characterised according to proliferation rate either as ‘fast-growers’ or ‘slow-growers’.

(54) Genome-wide expression analysis by microarray was performed to find transcriptome-level differences between the two groups. The goal was to determine if there are inherent molecular variations, and also find genetic differences that contribute to the phenotypic differences. Gene ontology of the resulting data shows several biological processes linked to cell cycle to be upregulated in the fast growers, while differentiation/development associated processes were down compared to slow growers, which correlates with the phenotype.

(55) Assessment of proliferation rate on the xCELLigence system showed the variance in growth rate in real time between the fast and slow growers (FIG. 3). The cell doubling times of fast growers on average was 35 h, while it was more than double at 75 h for slow growers. This corroborates the difference in proliferation between the two groups observed by the other growth assays (Samsonraj et al., manuscript in preparation).

(56) 1.2 Slow Growers Express GSTT1 and Most Fast Growers Lack it

(57) Characterization for proliferation and clonogenic potential for the donor derived lines found BM-MSC from donors A, C and E to be fast growers, while those from donor B, D, F and 10R and 11R were slow growers. Microarray analysis of the BM-MSC lines showed GSTT1 as the most differentially expressed gene between the two groups with the slow growers highly expressing the gene in comparison to fast growers (FIG. 4A).

(58) Genotyping for GSTT1 revealed two of the three fast growers (A and C) to have homozygous deletions of the gene, while the slow growers were positive, either as heterozygotes (B, D and F) or homozygous positives (10R and 11R) (FIG. 4B). RNA and protein expression analysis by qRT-PCR and western blot respectively showed the lack of expression of GSTT1 by the lines A and C, and expression by the other lines, consistent with the genotyping result (FIGS. 4C and 4D). The homozygote positives also had a higher expression of the gene than the heterozygotes, agreeing with the trimodal effect seen with copy number of alleles.

(59) 1.3 No DNA Damage Difference Between Fast and Slow Growers

(60) Aberrations in DNA repair mechanism are often associated with accelerated proliferation due to faulty cell cycle checkpoints. This may lead to accumulation of DNA damage which can be studied through assays that detect DNA lesions such as comet assay (also known as single cell electrophoresis assay). The fast and slow growers were studied using this method to check their extent of DNA damage to ensure the proliferation difference was not due to the malfunctioning of the DNA damage surveillance mechanism. The comet tails were mostly undamaged for both groups, and the comet tails, if any, were very slight (FIG. 5A). Quantification of the comets also showed almost negligible level of DNA damage for the groups (FIG. 5B), confirming normal intact state of the DNA. The cell cycle control of DNA repair/damage seems in check for the fast growers.

(61) 1.4 Similar Oxidative Stress Response of Fast and Slow Growers

(62) The GST superfamily of enzymes plays a major role in oxidative stress response since it removes reactive oxygen species (ROS) by glutathione conjugation. No convincing data is available for the effect of GSTT1 loss on oxidative stress response. To assess whether the GSTT1 genotype affects oxidative stress response, the fast and slow growers were treated with hydrogen peroxide, followed by hOGG1 (DNA glycosylase) treatment which cleaves at oxidized purines before being analyzed by comet assay. For both groups, the hydrogen peroxide and enzyme treated samples had significantly higher level of oxidized DNA damage than the untreated control (FIG. 6). Furthermore, the extent of DNA lesion was comparable between the groups, indicating no variation in the stress response despite the difference in genotype. So, the loss of GSTT1 does not affect the removal of oxidative factors, indicating that the presence of the other GST enzymes is sufficient to cope with the stress.

(63) 1.5 GSTT1 Expression Increases with Passage

(64) Genes associated with cell cycle are commonly modulated with prolonged passaging, an effect believed to mimic aging. It is known that GSTT1 increases with aging, although it is unknown why this happens. MSC can be maintained in culture at optimal state up to passage 8, beyond which their proliferation slows down and they show signs of senescence. In order to investigate the effect of passaging on GSTT1, slow-growers were maintained in culture, and passaged when 70% confluent. At certain passages, cells were harvested for expression analysis by qRT-PCR and western blot. Both methods found the expression level of GSTT1 to increase with passage (FIG. 7), suggesting its role in cell cycle regulation. Similar expression is seen between p5 and p8, but beyond p10 the expression consistently increased. By p15, the mRNA level was 2.5 fold higher than that of early passages.

(65) 1.6 GSTT1 Knockdown Increases Proliferation and Clonogenic Potential

(66) In order to assess whether it is the GSTT1 genotype that contributes to the enhanced proliferation observed with the fast growers (GSTT1 null) relative to slow-growers (GSTT1 positive), GSTT1 stable knockdown was performed and proliferative potential was studied. GSTT1 expression was suppressed up to 0.30 (SD±0.14) fold of that of nonsilencing control (FIG. 8A).

(67) For both treatments, cells seeded at the same density were stained with trypan blue and quantified at 5 days post-seeding. The viable cell count was significantly higher for the knockdown by approximately 80% (SD±28.28%) with respect to nonsilencing (FIG. 8B). The percentage of dividing cells in the span of 24 h was also higher as measured by the incorporation of 5-ethynyl-2′-deoxyuridine (EdU) (FIG. 8C). Real-time monitoring of proliferation by the xCELLigence system also confirmed the accelerated proliferation of the knockdown. The proliferate rate of the knockdown is about 34 h, which is close to 10 h difference of the doubling time of the nonsilencing at 43 h (FIG. 8D). Overall, the proliferation assays show an increase of growth rate with a decline in GSTT1. Infection of GSTT1 null BM-MSC line with the lentivirus packaged with shRNA did not affect their proliferation as assessed by the various techniques (data not shown), indicating specificity of the shRNA for GSTT1.

(68) Clonogenic potential was also measured to determine whether the self-renewal of the BM-MSC is affected by the knockdown of GSTT1 expression. The clonogenic potential of MSC is defined by colony-forming-units-fibroblasts (CFU-F). The knockdown and nonsilencing control were plated a low density and maintained for 2 weeks before they were fixed and counterstained by Giemsa.

(69) Visual inspection showed a larger number of colonies formed by the knockdown which were also bigger than the control (FIG. 9A). Quantification of the results found an average of 7% increase in the frequency of CFU-F (FIG. 9B) and an increase in the colony size by approximately 1 mm (FIG. 9C). The data shows an improved clonogenic potential with lower GSTT1 expression, indicating its influence on self-renewal property of BM-MSC.

(70) 1.7 Overexpression of GSTT1 Decreases Proliferation

(71) GSTT1 expression seems to be inversely correlated to proliferation in BM-MSC. To investigate if the overexpression of the gene will lead will have the opposite effect as the knockdown, the gene was transiently overexpressed in the fast growers that are GSTT1 null. Within 3 days of transfection, the expression level was close to 50 000 fold compared to the empty vector transfected cells (FIG. 10A). The proliferation assessments were performed between 1 to 2 weeks post-transfection.

(72) Viable cell count using trypan blue at day 5 post-seeding at a certain density showed the population of overexpression transgenic cells had a reduced percentage of cells at 60% (SD±3.79) with respect to the empty vector transfected cells (FIG. 10B). EdU labeling of dividing cells over the period of 24 h also found a decline in the proportion of mitotic cells by about 8% (FIG. 10C). Real-time measurement of growth rate was consistent with the other proliferation assays. The overexpression cell lines had a longer doubling time of 63 h, in comparison to the 53 h of the control. Overall, the overexpression of GSTT1 slowed the growth of the cells. The data confirms the involvement of GSTT1 in cell proliferation, with inverse relation to proliferation.

(73) 1.8 Conclusions

(74) Microarray data on slow-growing and fast-growing BM-MSC identify GSTT1 is most differentially expressed between the two groups. The slow-growers expressed GSTT1, while the fast-growers had negligible expression. Genotyping for GSTT1 confirmed the slow-growers possessed a functional alelle and the fast-growers were null for GSTT1.

(75) The fast-growers (GSTT1 null) generated more bone mass in our ectopic animal study. Thus, we show that the GSTT1 genotype predicts bone formation from BM-MSC isolated from patients.

(76) The finding that GSTT1 genotype influences proliferation and differentiation of BM-MSC is in agreement with previous studies showing that oxidative stress induces an increase in GSTT1 expression possibly through the p38 signaling pathway, suggesting its involvement in cell cycle control. The expression studies prove association of GSTT1 with proliferation, and also show that the loss of GSTT1 does not affect oxidative stress response, which is important for the normal physiology of the cell.

Example 2—Correlation of hMSC Behaviour In Vitro with Efficacy In Vivo

(77) 2.1 Introduction

(78) The present inventors establish a set of benchmarks for the selection of hMSCs with high efficacy. The confirm that in vitro differentiation potential is not of itself a reliable indicator of stem cell potency, and sought to reassess the minimum criteria to better define an hMSC, and to directly benchmark them to in vivo efficacy. They found that, in addition to the markers defined by the ISCT (2006), Stro-1, CD146, CD140b best correlated with the ability to form bone in vivo. It was also found that cells expressing these extra markers also displayed faster population doubling times, a smaller cell phenotype, and a secretome comparatively rich in FGF2, VEGF165 and PDGF-BB. The present inventors thereby identify a combination which constitutes a stem cell signature that is highly predictive of successful in vivo outcomes.

(79) 2.2 Isolation and Culture of Human Bone Marrow-Derived Mesenchymal Stem Cells

(80) Human MSCs (Lonza, Walkersville, MD) were isolated from bone marrow mononuclear cells (BMMNCs) (Table 1) by plating down the mononuclear cell fractions in maintenance media comprising of Dulbecco's Modified Eagles medium (DMEM-low glucose, 1000 mg/I) supplemented with 10% fetal calf serum (FCS; Hyclone), 2 mM L-glutamine, 50 U/ml penicillin, and 50 U/ml streptomycin (Sigma-Aldrich), as described previously (Rider et al, 2008). Cells from passage 4 were used for all experiments unless otherwise stated. Cells from individual donors were characterized and treated as a separate hMSC population throughout. For the CFU-F assays, BMMNCs were plated at 0.5-3.0×10.sup.6 cells/T75 flask, allowed to adhere and form colonies, and stained with 0.5% crystal violet (Sigma-Aldrich, USA) after 14 days. Visible colonies were then enumerated only when they were greater than or equal to 50 cells in number and were not in contact with another colony.

(81) TABLE-US-00003 TABLE 1 Donor information Donor ID Sex Age Race Source Donor A Male 21 Hispanic Lonza, Walkersville Inc., MD Donor B Male 20 Caucasian Lonza, Walkersville Inc., MD Donor C Male 20 Hispanic Lonza, Walkersville Inc., MD Donor D Male 26 Caucasian Lonza, Walkersville Inc., MD Donor E Male 20 Black Lonza, Walkersville Inc., MD Donor F Male 23 Caucasian Lonza, Walkersville Inc., MD

(82) 2.3 Donor Variability in Colony Formation, Cell-Size, Growth and Telomere Lengths

(83) 2.3.1 Cell-Size Analysis

(84) Single cell suspensions of hMSCs were stained with Annexin V, washed and resuspended in MACS buffer (2 mM EDTA, 0.5% BSA in PBS, pH 7.2) before analysis with a FACSArray™ Bioanalyzer. After gating out the Annexin V− cells, a quadrant gate was applied to the live population and the fraction of very low FSC/SSC events estimated to obtain the relative percentage of small-sized cells.

(85) All donor BMMNCs adhered quickly to tissue culture plastic and gave rise to colonies that readily expanded in culture (FIG. 11A). Comparison between the donors revealed significant differences in CFU-F efficiency and size of the colonies. Donors A, C, and E showed relatively higher colony formation efficiency (7.4±1.7) than donors B, D, and F (3.2±1.1) (FIG. 11B). No differences in morphology were observed at earlier passage numbers (FIG. 11A), although at later passages, hMSCs from donors with high CFU-F efficiency showed smaller, compact, spindle shaped morphology, whereas hMSCs from donors with low CFU-F efficiency appeared larger, and more elongated (data not shown). All donors, by virtue of plastic-adherence and colony formation, thus satisfied the ISCT criteria for identification as mesenchymal stem cells.

(86) Cell size was analysed. In addition to the abundant spindle-shaped and large flattened cells, the heterogeneous populations also contained small, round cells that could be identified as rapidly self-renewing (RS) (Colter et al., 2001 Proceedings of the National Academy of Sciences of the United States of America 98:7841-7845; Sekiya et al., 2002 Stem Cells 20:530-541; Smith et al., 2004 Stem Cells 22:823-831), characterizable by flow cytometry as low forward scatter (FSC.sup.lo) and low side scatter (SSC.sup.lo) of light. Donors A, C, E, which the higher colony-forming ability, consisted of, on average, 74.4% smaller-sized cells (identified as FSC.sup.lo/SSC.sup.lo in quadrant 1, FIG. 11C), whereas donors B, D, F, with lower colony-forming ability, consisted of only 66.4% small cells. Thus there was a positive correlation between CFU-F efficiency and the proportion of smaller cells present (FIG. 11B, 11C).

(87) 2.3.2 Cumulative Growth and Telomere Length Analysis

(88) To compare hMSC growth between donors, cells were seeded at 5,000 cells/cm.sup.2 and cultured under maintenance conditions. At 70-80% confluency, cells were enzymatically removed by 0.125% trypsin/Versene and viable cells counted using the Guava ViaCount® Assay with Guava EasyCyte™ Plus Sytem/CytoSoft™ software (Millipore™) Cells were re-plated at the same density and progressively sub-cultured to estimate cumulative cell numbers and population doublings over 13-15 passages or until senescence. Genomic DNA at different passages was isolated and telomere length analysis performed. Using human embryonic stem cells (hES3, ES International, Singapore) as the reference, telomere lengths of hMSCs were determined relative to the reference cell line and expressed in units of relative telomere lengths (RTLs) as described previously (Samsonraj et al., 2013 Gene). The hMSC sample DNA (12 ng/reaction) and reference DNA (across the various dilutions) were used as templates in SYBR Green-based real time PCR set-up with specific telomere (Tel) and 36B4 (single copy gene) primers.

(89) Growth is a key metric of MSC quality because the ability to self-renew is a defining trait. MSCs are known to undergo phenotypic changes with long-term expansion, eventually losing proliferative capacity. Cell growth was monitored for extended periods (8-10 weeks) in culture. Cumulative cell numbers and the extent of population doubling assayed over several passages revealed significant differences in proliferative potential. Donor C displayed the maximum growth, with donor F showing the minimum (FIG. 11D). On average, cells from (fast-growing) donors A, C, and E achieved 33% more cumulative cell numbers than (slow-growing) donors B, D, and F (P<0.05). These donors also showed a greater efficiency for colony formation (FIG. 11B) with higher percentages of smaller cells (FIG. 11C), signifying a correlation between cell growth, colony formation, and size. Taken together these results allowed us to group donors A, C, and E as fast-growing hMSCs and B, D, and F as slow-growing hMSCs. Real-time assessment of proliferation rates demonstrated that fast-growing cells have shorter population doubling times (˜35 h) than slow-growing cells (˜75 h), so confirming the growth differences between the two groups as observed in long-term expansion (FIG. 20).

(90) As telomeres are tightly linked to cell divisions, the telomere status of these cells was checked. Analysis from initial seeding (P1) until senescence (P13-P15) at seven different passages showed progressive decreases in the relative lengths as the cells underwent divisions. The rate of telomere shortening occurred in a linear fashion, as indicated by the negative slope of the curves (FIG. 11E), albeit at different rates, as shown by the straight line gradients and the R.sup.2 value (correlation coefficient) (FIG. 11F). Regression plots of donors A, C, and E showed substantially lower regression (R.sup.2) values than donors B, D, and F suggesting that fast-growing hMSCs reduced their telomeres at rates less than that of slow-growing hMSCs (FIG. 11F). In addition, slow-growing hMSCs reached senescence after 13 passages whereas the fast-growing hMSCs underwent cell divisions until 15 passages.

(91) Given that the age of the donors (between 20-30Y) was within a narrow limit, taken together our results confirm that donors whose cells gave rise to more colonies possessed higher proportions of small-sized cells with increased growth rates and relatively longer telomeres.

(92) 2.4 Immunophenotypic Characterization by Flow Cytometry

(93) Flow cytometry was performed to compare surface immunophenotypic profiles of hMSCs. Single-cell suspensions were stained with phycoerythrin (PE)- or fluorescein isothiocyanate (FITC)-conjugated anti-human CD105, CD73, CD90, CD45, CD34, CD49a, CD29, EGF-R, IGF-IRα (CD221), NGF-R (CD271), PDGF-Rα and β (CD140a and CD140b), CD11b, HLA-DR, CD19, CD14, CD106, CD146, SSEA-4, STRO-1 antibodies or isotype-matched controls IgG1, IgG1κ, IgG2a κ, IgG2b κ, IgM(p) and IgG3, and analyzed on BD FACSArray™ Bioanalyzer and FlowJo software. All antibodies were purchased from BD Biosciences except IgM (μ) (Caltag laboratories) and STRO-1 (kindly provided by Prof Stan Gronthos, Institute of Medical and Veterinary Sciences, University of Adelaide, Australia).

(94) 2.4.1 Immunophenotypic Profiles of hMSCs

(95) The next step was to verify the presence of CD markers. A set of 27 markers including those described by the ISCT as definitive for MSCs was analysed (Dominici et al., 2006 Cytotherapy 8: 315-317). Culture-expanded hMSCs from all the donors were uniformly and strongly positive for CD105, CD73, and CD90 (greater than 95%) and negative for the hematopoietic markers CD45, CD34, CD11b, CD14, CD38, CD19, CD31 and HLA-DR (FIG. 12). Donor variability was seen in the expression of markers that have been recently proposed to identify MSCs. Growth factor receptors such as EGFR, IGFR, PDGFRα/β had variable expression as evident by the spread of data in the profile. Other recently described markers such cell adhesion molecules CD106, CD146, CD166 were also differentially expressed, although with little correlation with growth. PDGFRα levels, which correlate with osteogenic potential (Tokunaga et al., JBMR 2008), were higher in slow-growing hMSCs. Notably, fast-growing hMSCs had significantly higher expression of STRO-1, SSEA-4, CD146, and PDGFRβ P<0.05, t-test). From our profiling, it is evident that the ISCT criteria is inadequate and MSC identification should include checking the levels of STRO-1, SSEA-4, CD146, and PDGFRβ

(96) 2.5 Quantitative Multiplex Detection of Cytokines

(97) Media conditioned by cells seeded at 3,000 cells/cm.sup.2 in maintenance media were collected after 4 days. To release matrix bound proteins, cell layers were treated with 2M NaCl in 20 mM HEPES (pH 7.4) for 5-10 sec. Conditioned media and salt wash were analyzed separately using Millipore's MILLIPLEX® MAP—Human Cytokine/Chemokine kit (Cat. No. MPXHCYTO-60K) for simultaneous quantification of fourteen different growth factors, according to the manufacturer's instructions. Results are presented as concentrations of total growth factors, in picograms/ml normalized to cell numbers, which included factors secreted into media and factors that were matrix-bound.

(98) 2.5.1 Cytokine Secretion Profiles of hMSCs

(99) Levels of cytokines and growth factors produced by hMSCs were assayed as an indicator of possible in vivo efficacy. Significant donor variability was observed for majority of the growth factors. Fibroblast growth factor-2 (FGF-2) was the most highly secreted factor (500-6000 pg/ml) (FIG. 13), followed by MCP-1 which is known to play important roles in both cell migration and angiogenesis. PDGF-BB, a central connector between cellular components and contributors of the osteoblast differentiation program (Caplan and Correa, 2011), was at levels significantly greater than those of PDGF-AA. Overall, when grouping the factors based on growth it is notable that the amounts of FGF-2, VEGF, SDF-1α, fractalkine, PDGF-BB, and MIP-1α were significantly higher in fast growing hMSCs (FIG. 14). It is notable that key factors involved in wound healing such as mitogenic factor FGF-2, pro-angiogenic molecule VEGF, chemokines SDF-1α and fractalkine, pro-inflammatory chemokine MIP-1α, and PDGF-BB—a potent angiogenic, mitogenic and chemotactic factor—are upregulated in fast-growing cells. Our results highlight the importance of assaying the levels of these growth factors which could be central to predicting in vivo efficacy of hMSCs, and thus serve as key parameters that facilitate MSC selection for potential clinical use.

(100) 2.6 Immunosuppression of Activated T-Cells

(101) Peripheral blood mononuclear cells (PBMCs) from whole adult blood were obtained using Ficoll-Paque PLUS (GE Healthcare). CD4+ T-cells were isolated from PBMCs using EasySep negative selection human CD4+ T cell enrichment kit (Stem Cell Technologies, Canada) and labeled with carboxy-fluorescein diacetate succinimidyl ester (CFSE; Vybrant® CFDA SE cell tracer kit). CD4+ CFSE+ cells (0.5-1×10.sup.5) were stimulated by anti-CD3 and anti-CD28 MACSiBeads (Miltenyi Biotec, Germany) at a ratio of four beads per T cell, to which hMSCs were added at different T cell:MSC ratios and incubated at 37° C. Proliferation of CD4+ CFSE+ cells was measured after 7 days by flow cytometry and the percentage inhibition of T cell proliferation by hMSCs was determined.

(102) 2.6.1 Immunosuppressive Ability of hMSCs

(103) To test the ability of MSCs to secrete immunomodulatory factors capable of suppressing ongoing immune responses by virtue of an inhibition of T-cell proliferation in either mixed-lymphocyte culture or under mitogenic stimulation, cells from one representative from both the fast-growing (donor A), and slow-growing (donor F) pools were examined (FIG. 21; Table 2). Analysis of cell divisions via flow cytometry showed that T cell proliferation under antibody stimulation was suppressed by hMSCs in a dose-dependent manner (FIG. 15). At a T cell:MSC ratio of 32:1, no suppression was observed, and the percentage of cells proliferating under such conditions were equal to that of the ‘no hMSC’ control group. Inhibition was the highest at the 1 T cell: 2 hMSC ratio, with the proliferation percentage comparable to T cell growth without antibody stimulation. The fast-growing hMSCs consistently showed significantly greater suppression of T cells (*P<0.05). Notably, fast-growing hMSCs consistently showed significantly higher suppression of T cells (*P<0.05). This functional assay of immunosuppression highlights the supremacy of fast-growing cells in being efficacious for therapy.

(104) Table 2.

(105) Dose-dependent suppression of T cell proliferation. T cells and hMSC were co-cultured in varying proportions. A ratio of $:1 (T cell:hMSC) resulting in 50% suppression of T cell proliferation.

(106) TABLE-US-00004 Proliferation of T cells in co-culture with hMSCs (%) T cell:hMSC Fast-growing Slow-growing ratio (Donor A) (Donor F) 1:2 5.42 4.96 1:1 7.49 18.1 2:1 21.34 34.51 4:1 47.92 58.53 8:1 68.4 73.77 16:1  79.3 82.41 32:1  85.26 83.45

(107) 2.7 Gene Expression Studies

(108) 2.7.1 Quantitative Real Time Polymerase Chain Reaction (PCR):

(109) Total RNA was isolated using the Nucleospin RNA II kit (Macherey Nagel, Bethlehem, PA) according to the manufacturer's instructions and quantified by NanoDrop™ 1000 (Thermo Fisher Scientific Inc.). After conversion to cDNA (Superscript VILO, Invitrogen Corporation, CA), expression of mesodermal genes TWIST-1 and DERMO-1, osteogenic markers RUNX2, ALP and BSP-II, adipogenic markers PPARγ and CEBPα and chondrogenic genes COL2A1 and SOX9 was assessed using the TaqMan® Gene Expression assay on an Applied Biosystems 7500 Fast Real Time PCR System (Table 3). C.sub.T values were normalized to β-actin and results plotted as relative expression units (REU).

(110) TABLE-US-00005 TABLE 3 TaqMan® Gene Expression assays for real-time PCR Gene Amplicon Symbol Target gene Context sequence Assay ID length RUNX2 runt-related TCGGGAACCCAGA Hs00231692_m1 116 transcription AGGCACAGACAG factor 2 ALP alkaline TACAAGCACTCCC Hs01029144_m1 79 phosphatase, ACTTCATCTGGA liver/bone/ kidney BSP II integrin- TCCAGTTCAGGGC Hs00173720_m1 95 (IBSP) binding AGTAGTGACTCA sialoprotein PPARy peroxisome TCTCATAATGCCAT Hs01115513_m1 90 proliferator- CAGGTTTGGGC activated receptor gamma CEBPα CCAAT/enhancer TCGTGCCTTGTCAT Hs00269972_s1 77 binding TTTATTTGGAG protein (C/EBP), alpha TWIST-1 twist homolog GCCGGAGACCTAG Hs00361186_m1 115 1 ATGTCATTGTTT DERMO-1 twist homolog ACGTGCGCGAGCG Hs02379973_s1 154 2 CCAGCGCACCCA COL2A1 collagen, TGGTCTTGGTGGA Hs00264051_m1 124 type II, α1 AACTTTGCTGCC

(111) 2.7.2 Microarray and Gene Ontology Analysis:

(112) RNA extracted at P5 was amplified for microarray using a TotalPrep RNA amplification kit according to the manufacturer's instructions (Ambion Inc., USA). The resulting purified biotin-labeled complementary RNA (cRNA) was normalized and hybridized onto a HumanHT-12 version 4 beadchip (Illumina Inc., USA) using its direct hybridization assay facility. The chip was then washed, blocked and Cy3-streptavidin bound to the hybridized cRNA. An Illumina BeadArray Reader using the Illumina BeadScan software was used to image the chip and the image data was converted into expression profile by GenomeStudio (Illumina Inc., USA). Background was subtracted and the data was submitted to GeneSpring (Agilent, USA). The replicates were averaged and a pairwise analysis was done followed by Student's-test unpaired statistical analysis with p<0.05 and fold change ≥1.5. Two donor samples representing each group with two technical replicates were analyzed. The gene lists generated were uploaded using Entrez gene ID onto DAVID for functional annotation clustering by GOTERM_BP_FAT with medium classification stringency. Only biological processes with p≤0.05 were considered.

(113) 2.7.3 Gene Expression Analysis

(114) The phenotypic differences between the fast- and slow-growing cells may be due to systematic differences in gene expression. To identify such persistent differences at the transcriptome level, qPCR was done to check the levels of mesoderm-related markers Twist-1 and Dermo-1. Fast-growing hMSCs demonstrated higher transcript levels of these markers. Upon identifying such differences, a global gene expression analysis by microarray was performed on the two groups. A fold change cut-off of 1.5 and p-value <0.05 delineated a small set of transcripts differentially expressed between the two groups, with 74 significantly enriched in the fast-growers and 149 in the slow-growers (FIG. 16B). The limited size of the gene sets indicate that the two groups are largely similar, and that the trait variation could be attributed these genes.

(115) Gene ontology (GO) analysis by DAVID functional annotation clustering was performed on the gene lists generated to identify biological processes enriched in the fast and slow groups. Genes regulating cell adhesion, the cytoskeleton and organelles were significantly upregulated (p-value s 0.05) in the fast group (Table 4), with the latter indicative of a faster rate of turnover. Adhesion to the extracellular matrix and neighboring cells correlates with cell cycle progression (2,3). Genes enriched in the slow-growing cells tend to be cell morphogenetic and to do with development of mesenchyme-derived organs (Table 4).

(116) Table 4.

(117) Gene ontology (GO) analysis. GO analysis was performed using DAVID functional annotation terms (subset: GOTERM_BP_FAT) on the sets of genes enriched in fast-growing (Table 4A) and slow-growing hMSCs (Table 4B). Descendant GO terms are represented by the parent term.

(118) TABLE-US-00006 TABLE 4A Biological processes enriched in fast growers. GO ID GO Description p-value Genes GO:0051493 Regulation of 0.008 BRCA1, SKA3, cytoskeleton PDGFA, SCIN organization GO:0033043 Regulation of 0.028 BRCA1, SKA3, organelle PDGFA, SCIN organization GO:0007155 Cell adhesion 0.051 TEK, CDH4, OPCML, OMD, PCDH19, THRA

(119) TABLE-US-00007 TABLE 4B Biological processes enriched in slow growers. GO ID GO Term p-value Genes GO:0009991 Response to 0.002 ALPL, BMP2, LEPR, extracellular LIPG, MGP, RBP4, stimulus SLC22A3 GO:0001763 Morphogenesis of 0.010 BMP2, ERMN, EYA1, a branching MGP structure GO:0001501 Skeletal 0.012 ALPL, BMP2, CYTL1, system EYA1, MGP, OSR2, development RBP4 GO:0000902 Cell 0.020 KAL1, S100A4, ANK1, morphogenesis BMP2, DCLK1, HGF, NRXN3 GO:0042445 Hormone 0.026 CPE, DHRS9, metabolic process HSD17B6, RBP4 GO:0001656 Metanepharos 0.028 BMP2, EYA1, ITGA8 development GO:0001655 Urogenital 0.028 BMP2, EYA1, ITGA8, system development RBP4 GO:0060485 Mesenchyme 0.039 S100A4, BMP2, HGF development GO:0009611 Response 0.039 BMP2, ENTPD1, SCG2, to wounding SERPINA1, SERPINA3, SERPINB2, TFPI, TNFAIP6 GO:0022604 Regulation of 0.044 ERMN, PALM, PALMD, cell morphogenesis RHOJ

(120) In order to investigate the upregulation/downregulation of genes involved in MSC differentiation, transcript levels of the markers were assayed under non-induced conditions by qPCR. Individual donors demonstrated variability in the baseline expression of these genes, however no significant differences in the tri-lineage differentiation markers were observed between the two groups.

(121) 2.8 In Vitro Multilineage Differentiation

(122) Evaluation of the differentiation potential of hMSCs for the osteogenic, adipogenic, and chondrogenic lineages was performed as described previously (Rider et al, 2008). Average intensities of stained plates/wells were analyzed using Quantity One® software (Bio-Rad Laboratories), and recorded and expressed as relative intensity units, that is, fold-increase of intensity in treatment wells compared to their respective control wells. In these measurements, a darker stain implies higher density value.

(123) 2.8.1 Multilineage Differentiation Ability

(124) To assess the multipotency of the hMSCs, the cells were induced to differentiate down the osteogenic, adipogenic, and chondrogenic lineages by culturing them with defined media components and culture conditions (FIG. 22). All the donor hMSCs satisfied the minimal criteria to be designated as ‘mesenchymal stem cells’, as they could all both self-renew and differentiate, albeit with differing capacities. Fast-growing cells which had the highest proportion of potential precursors as evident from the TWIST and DERMO levels displayed variability associated with the expression of RUNX2, ALP, and CEBPα. High-expressing Twist-1 and Dermo-1 hMSCs were found to exhibit the most proliferative potential; thus higher expression of TWIST correlates with both decreased capacity for osteogenic differentiation and increased capacity for self renewal (FIG. 17A). Looking at a comparison of the means differences are observed, with no other significant effects noted. As the deposition of matrix is a more functional readout, the staining of the cell layers was analysed. Significant differences in calcium deposition under induced conditions between the fast and slow-growing cells was observed (FIGS. 17B,17C). It is notable that the ALP mRNA levels were correspondingly higher in slow-growing cells. This indicates that there is a possibility that these cells are already primed to differentiate down the osteogenic lineage. Certainly, for the bone lineage, the gene expression levels are tightly clustered among the fast-growing donors. Genes involved in adipogenesis showed upregulation of PPARγ and CEBPα in adipogenic cultures. Significant differences were not observed at the transcript levels but in the normalized staining intensity between the two groups of hMSCs (P<0.05) (FIG. 17C). In general, there was less variability among the fast-growing donors under osteogenic and chondrogenic differentiation. Under chondrogenic conditions, no differences were observed between the two groups.

(125) Given that the differences may not be biologically relevant, it is notable that all the donors demonstrate tri-lineage differentiation potential. As our study focuses on identifying clinical correlates, our results on differentiation provided a fulsome assessment of a set of criteria for MSC identification. At this stage, this cannot be taken as sufficient evidence that fast-growing cells are better cells for differentiation, albeit their slight different efficiencies. Nevertheless, all individual donors demonstrated tri-lineage differentiation potential and have thus satisfied the ISCT criteria for the identification of MSCs.

(126) 2.9 Ectopic Bone Formation Assay

(127) Ex-vivo passage 4 cells were expanded and ˜3-5×10.sup.6 seeded onto MasterGraft Matrix scaffolds (Medtronic, Inc. USA) before their implantation into subcutaneous pockets of 8 week-old immunodeficient mice (NIH-bg-nu-xid, Harlan Sprague-Dawley) as described previously (Zannentino et al, 2010). Surgeries were performed according to specifications of an ethics-approved small animal protocol (IACUC: #110651). X-rays were taken immediately post-transplantation and at 8 weeks using Shimadzu MobileArt MUX-101 Standard (Shimadzu Corporation, Japan) and a DÜRR MEDICAL—CR 35 VET Image Plate Scanner. Micro-CT was performed on the animals at weeks 4 and 8 using a SkyScan CT-Analyser, and datasets were reconstructed and analyzed by CTAn (SkyScan) and Mimics software to compute bone volume by applying appropriate threshold settings. Implants were recovered from the animals after 8 weeks, de-calcified, embedded in paraffin, and stained with hematoxylin/eosin and Rallis Trichrome. Immunohistochemistry was done by incubating tissue sections with appropriate concentrations of primary antibodies to mouse osteocalcin (M188, 1:100, Takara Bio Inc.), human osteocalcin (ab76690, 1:50, Abcam), mouse collagen I (NBP1-77458, 1:200, Novus Biologicals) or the same concentration of mouse IgG (MG100, Caltag Lab, USA; as negative controls) in blocking buffer overnight at 4° C. Sections were washed and incubated with rat-absorbed biotin-labeled anti-mouse IgG (Vector Lab Inc, USA) for 1 h, followed by the addition of avidin-biotin-peroxidase complex (ABC) solution (Immunopure ABC preoxidase staining kit, Vector Lab. Inc) for 1 h. Peroxidase activity was detected using 3,3-diaminobenzidiine-tetrahydrochloride (DAB; DAKO, USA). Sections were washed, mounted and examined under a Zeiss Axiolmager (Z1) upright microscope.

(128) 2.9.1 In Vivo Ectopic Bone Forming Efficacy of hMSCs

(129) The in vitro characterization of hMSCs was followed by a functional in vivo assay. Amongst the most important assays for MSC efficacy is the ability to form bone after implantation at ectopic sites. MSCs from all donors demonstrated a capacity to form bone, albeit with significant variability in extent. Compiled analyses of the implants show that fast-growing hMSCs exhibited a two- to three-fold greater ability to form ectopic bone than the slow-growing, as quantified by μCT (FIGS. 18A-18E). Sections of implants stained with H&E and Rallis Trichrome showed the morphology, the extent of bone formation and fibrous tissue as indicated by the color gradient bar (FIG. 19B). Sections of the harvested implants were stained with species-specific antibodies against osteocalcin in order to determine whether the bone formed was of human or mouse origin. This enabled determination of whether transplanted hMSCs had differentiated into human osteoblasts to form bone at ectopic sites, or if they had supported host tissue to form bone. Immunohistochemical analysis revealed the presence of human osteocalcin at levels greater than mouse osteocalcin (FIG. 19A) Osteoblast-like cells observed to be depositing bone in the pores of the scaffold were of human origin as indicated by the staining for human osteocalcin. Donors A, C, and E triggered greater amounts of osteocalcin deposition than donors B, D, and F, correlating with the μCT analysis. Scaffolds with no hMSCs also revealed some bone deposition, in keeping with the osteoconductive property of the carrier. Mouse collagen was predominant in all the implants, with fast-growing hMSCs showing higher collagen 1 deposition than slow-growing cells.

(130) All hMSC populations studied were able to display bone forming ability in vivo, albeit at different levels. Correlating in vitro parameters with the above in vivo results, hMSCs were found to exhibit increased proliferative potential, longer telomeres, and higher secretion levels of growth factors were more potent in forming bone at ectopic sites.

(131) 2.10 Conclusions

(132) The correlation of in vitro and in vivo attributes of human bone-marrow derived mesenchymal stem cells revealed that cells from donors with high CFU-F efficiency are on average smaller in size, show increased growth, and have longer telomeres compared to slow-growing cells; biomarkers of multipotency (CD profiling) are similarly high in donors with a higher proportion of small-sized hMSCs; secretion of trophic factors FGF-2, VEGF, PDGF-BB, SDF-1α, fractalkine, is elevated in hMSCs showing enhanced proliferative potential, and that bone formation at a subcutaneous ectopic site is positively correlated with the transplantation of hMSCs in culture having higher secretion levels of trophic factors, higher proliferative potential, and relatively longer telomeres. Monitoring the benchmarks of FGF-2 levels, telomere length and growth rate described in this study should enable the selection of potent cells for therapy, saving time and resources involved in hMSC transplantation. Selection of hMSCs that show higher efficiency for the above characteristics should heighten in vivo efficacy. These findings lay the foundation for developing future strategies to direct and enhance the growth and developmental of culture expanded MSC for tissue engineering applications by enabling the selection of best-in-class hMSCs.

(133) By correlating in vitro findings with the in vivo, the present inventors conclude that hMSCs with faster doubling times, a higher proportion of rapidly self-renewing cells with longer telomeres, and greater secretion levels of certain key growth factors, particularly FGF-2, VEGF, PDGF-BB, and SDF-1α, are more efficacious in vivo for the formation of new bone at ectopic sites. Somewhat paradoxically, fast-growing hMSCs that yielded the greater new bone formation displayed the least mineralization capacity in vitro. The enrichment of proliferation-associated and maturation-related processes in the fast and slow growers respectively suggests a physiological basis that may underpin their phenotypic divergence. As the BM-MSCs were derived and propagated from donors according to standardized procedures, with as minimal handling variation as possible, differences in the physiology of the cells might be due to this underlying transcriptome variation.

(134) To date, no systematic correlation between the properties of hMSCs in vitro and their effects on treatment in vivo has been demonstrated, primarily because there is no universally accepted in vitro method for predicting the therapeutic capacity of MSCs (REF). A key study by Janicki et al. (2011), in attempts to provide clinically-relevant potency assays, demonstrated that the doubling time of hMSCs correlates well with in vivo bone formation; here the present inventors have greatly extended that concept to other in vitro parameters factors that correlate with ectopic tissue formation, including assays for mitogenic and cytokine factor secretion. Retrospectively analysis of the CFU-F efficiency of donors yielding fast-growing hMSCs, confirmed that hMSCs able to complete more than 15 cumulative population doublings within seven passages possessing a superior ability to induce bone formation in vivo.

(135) It had been previously reported that rapidly self-renewing cells express higher levels of CXCR4 and CX3R1 for SDF-1α and fractalkine respectively (Lee et al., 2006), receptors implicated in haematopoiesis, vasculogenesis, and the efficient trafficking of immune cells, which were also observed. Rapidly self-renewing progenitor cells with increased expression of chemokine receptors are also known to engraft better into murine neurospheres (REF). The greater twist-1 and dermo-1 expression in the fast-growing hMSCs, genes known to be crucial for mesenchymal stem cell growth and development, also tend to corroborate the functional studies done by Isenmann et al. (2009), who demonstrated that such MSCs had a decreased capacity for osteogenic/chondrogenic differentiation and an enhanced tendency to undergo adipogenesis.

(136) 2.10.1 Correlating In Vitro hMSC Characteristics with In Vivo Efficacy

(137) It is not known why hMSC growth is a predictor of outcome in the ectopic model, where osteoinductive growth factors, mechanical stimuli and a supporting bone-environment must also be in play. Perhaps high anabolism is needed to create an active, blood-rich microenvironment at the site of transplantation. Helledie et al. (2012) showed that hMSCs with longer telomeres survived longer when transplanted into critical-sized bone defects in nude rats.

(138) In vitro, there were significant differences in the expression of osteogenic genes between fast- and slow-growing hMSCs. The slow-growing hMSCs showed better mineralization in vitro upon osteogenic induction, but were poor performers in vivo. This suggests that the high proliferation rate of a large fraction of MSCs within a population out-competed the possible advantage yielded by the fraction of cells that may already have started to become osteoblasts. The deposition of bone in the scaffold pores suggests that the capacity to deposit a mineralised matrix is spatially controlled, and that the most adaptable hMSC to achieve this may be the faster proliferating, rather than slow-growing, pre-differentiated cells. That the standard in vitro osteogenic assay yields a poor prognosis is in accord with a previous study from our group, and with work others showing that ex vivo matrix mineralisation assays lack specificity, and show little or no concordance with true bone formation (Watson, 2004; Rai et al., 2010).

(139) Fast-growing hMSCs consisted of a higher proportion of small-sized cells from within the heterogeneous population, with high clonogenicity and multipotentiality. This correlation is interesting as it connects three aspects of hMSC behaviour: secretion of trophic factors, proportion of RS cell subpopulations, and bone forming-efficacy.

(140) Among the many growth factors regulating bone metabolism, FGF-2 is recognized as a particularly potent mitogen for mesenchymal cells. It is produced by cells within the osteoblastic lineage, accumulates in bone matrix, and acts as an autocrine/paracrine factor for bone cells (REF). FGF-2 stimulation of osteoblast differentiation and bone formation is mediated in part by modulation of the Wnt pathway (Kasten et al., 2008; Fei et al., 2011). The exogenous application of FGF-2 has stimulatory effects on bone formation by facilitating BMP-2-induced ectopic bone formation, through alteration of the expression of BMPRs on the surface of bone-forming progenitor cells, an effect now thought to be the major pharmacological action of FGF-2 in vivo (Nakamura et al., 2005), and a plausible reason why hMSCs are better at giving rise to ectopic bone formation than pre-differentiated osteoblasts (FIG. 15B). VEGF belongs to the PDGF superfamily of growth factors, and is a key regulator of angiogenesis, a process crucial for all tissue healing (Zentilin et al., 2006; Schipani et al., 2009). VEGF also acts as a strong mitogenic stimulus for endothelial cells (Han et al., 2009), and osteoblasts (Hiltunen et al., 2003), as well as MSCs (Huang et al., 2010). The present inventors also demonstrate that VEGF was secreted by hMSCs; it is possible that the fast-growing cells produced superior bone in part because of their superior ability to stimulate of endothelial cell recruitment, as supported by the histology. Angiogenesis involves the recruitment of capillary-forming endothelial cells, that are in turn stimulated by pro-angiogenic factors to induce the further migration and proliferation of neovascularising cells (Abboud, 1993). As bone healing is closely associated with angiogenesis, the increases in levels of VEGF and MCP-1 correlate well with earlier reports (Zisa et al., 2009).

(141) Despite the immense amount of work done over the last decade, MSCs are still relatively poorly understood, heterogenous cell mixtures with unpredictable properties. As pointed out by Mendicino et al. 2014 in their recent review, there is bewildering diversity in how sponsors have defined, manufactured, and described MSCs in their regulatory submissions to the US FDA, not only in terms of tissue sourcing, but also methods of in vitro propagation, cell surface marker expression and product manufacturing. They confirmed from their survey of FDA submissions that seven cell surface markers are routinely utilized for MSC-based product IND submissions (CD105, CD73, CD90, CD45, CD34, CD14, and HLA class II), which is consistent with the marker set specified by the ISCT in their 2006 position paper (Dominici et al., 2006 Cytotherapy 8: 315-317). However, it is clear that this marker set is far from definitive, and encompasses a vast majority of cells without true, “stem-like” qualities; it has recently been shown that special conditions are required in culture, including specific HS content, to maintain and even increase the fraction of bone marrow-derived adherent cells that are capable of true self-renewal (Helledie et al., 2012). Thus it is still an open question which particular set of markers truly describes this heterogeneous cell class.

(142) MSC bioactivity may also be dependent on cues in the microenvironment, clinical indication, and route of administration. The most-targeted clinical indications for MSCs are cardiovascular, neurological, orthopaedic and metabolic disease, in particular diabetes. Nearly a quarter looking to ameliorate immune-mediated disease, particularly Graft versus Host Disease. Multiple routes of administration have been employed, including intravenous, direct injection (mostly cardiac) and topical application (REF). Proof-of-concept animal studies variably seek to monitor such complex aspects of cell behaviour as phenotype, proliferative ability, distribution, and survival post-administration, and even combinations thereof, despite the lack of convincing means to assess exactly how the cells are exerting their biological activity.

(143) It seems clear that more work of the kind described here will be needed to better understand the phenotypic stability and impact of subpopulations on MSC-based therapies. This may be even more true for non-bone marrow-derived MSC-based therapies, where even less information is available. Markers predictive of therapeutic benefit can be expected to yield multiplicative effects for the clinical translation of MSC-based products.

Example 3—Development of Techniques Based on GSTT1

(144) 3.1 Developing a Biomarker Kit—Designing a Test for GSTT1 Genotype for Use in Clinical Settings

(145) An affordable PCR diagnostic kit will be designed to detect the 2 major GSTT1 alleles, wildtype and the GSTT1 deletion allele.

(146) The simplest, fastest and cheapest means will be to adopt a diagnostic test to the TaqMan RT-PCR platform, which is widely used in the diagnostics community. RT-PCR primers will be designed for both alleles that will work well in this TaqMan format. For commercialization considerations, the kit will be optimized for use with peripheral blood drawn from prospective donors.

(147) The kit will be versatile and able to start with DNA extracted from the non-adherent cells from bone marrow preparations typically discarded during the isolation of MSC. Primers and probes will be selected that have suitable properties (e.g. annealing temperature) for use with the TaqMan platform.

(148) 10-20 primer pair combinations will be designed using an optimised primer design algorithm, and tested for ability to detect GSTT1 alleles. The best pairs will then be tested pair wise to identify a suitable matched set for use in multiplex format for the detection of GSTT1 alleles in a single reaction.

(149) A simple DNA-based kit has been designed, which allows screening of patients or prospective donors for the presence or absence of GSTT1 before making a decision on whether or not to harvest stem cells.

(150) Various tissues can be utilized to detect the presence or absence of GSTT1 such as buccal swabs, blood and skin punches. The kit will be used primarily to test cells harvested from buccal swabs of consenting donors. Depending on tissue availability, other tissue materials will also be considered as an alternative to buccal swabs.

(151) Genomic DNA (gDNA) will be extracted from samples using standard extraction procedures. Primers designed by Buchard et al. for detecting the copy number of the GSTT1 gene will be utilized to probe the gDNA samples (FIG. 24)—see Buchard et al. et al., J Mol Diagn, (2007) 9(5): 612-617:

(152) TABLE-US-00008 Primer set Forward Primer Reverse Primer GSTT1_Gene 5′-TCTTTTGCATAGAGACCATGACCAG-3′ 5′-CTCCCTACTCCAGTAACTCCCGACT-3′ GSTT1_Deletion 5′-GAAGCCCAAGAATGGGTGTGTGTG-3′ 5′-TGTCCCCATGGCCTCCAACATT-3′

(153) The “GSTT1_Deletion” primer set, hybridizes to specific sequences adjacent to the homologous regions flanking both GSTT1 (FIG. 24). When the GSTT1 gene is deleted, these primers will amplify a ˜3 Kb product, as the deletion brings the hybridization sites for the primers into close enough proximity for PCR amplification. The “GSTT1_gene” primer set is specific to a segment of the GSTT1 sequence, and will amplify a 1 Kb product when the gene is present (i.e. not deleted): GSTT1+/+: 1 kb band only GSTT1+/−: 1 kb band and 3 kb band GSTT1+/+: 3 kb band only

(154) In a multiplex PCR assay, the primer enable us the genotype of the donors to be determined. Therefore, the copy number of GSTT1 in patients and donors can be identified, enabling pre-selection of individuals null for the biomarker for stem cell isolation. This could save time and resources in generating quality stem cells for cell-based therapies. The application of these selectively isolated stem cells can also have better efficacy for such clinical purposes.

(155) 3.2 Assessing Stem Cell Quality In Vitro

(156) Stem cell donors will be screened for GSTT1 genotype, and GSTT1 genotype will be correlated with stem cell phenotype.

(157) a. Bone Marrow Aspiration:

(158) Bone marrow aspirates (30 ml) will be obtained from iliac crests of ten normal healthy adult donors (n=10) under local anaesthesia, using a Jamshidi needle under, after informed consent and following standard protocols.

(159) b. Isolation of MSCs:

(160) Bone marrow aspirate will be layered on Ficoll and centrifuged at 2000 rpm for 20 min. The mononuclear cell fraction will be aseptically transferred to tissue culture plates and incubated at 37° C., 5% CO.sub.2 until colonies of adherent cells are formed. The nonadherent cell population will be collected, and DNA isolated for the verification of the GSTT1 status using the biomarker kit according to 3.1. c. MSC characterization: Isolated MSCs from the multiple donors will be characterized individually by the following methods;

(161) (i) Colony Efficiency—

(162) CFU-Fs will be assayed by plating the different MSC preparations (0.5-2 million bone marrow mononuclear cells per T75 flask), and culturing them for 14 days. Colonies with more than 50 cells (not in contact with other colonies) will be scored.

(163) (ii) Proliferation—

(164) Cumulative cell numbers up to passage 10 will be determined by ViaCount assay using the Guava PCA-96 Base System as per the manufacturer's instructions (Millipore).

(165) (iii) Cell-Surface Antigen Marker Expression—

(166) Cells will be lifted using TrypLE™ and washed. Approximately, 1×10.sup.5 cells will be incubated with antibodies (CD73, CD90, CD105, STRO-1, SSEA-4, CD-19, CD34, CD45, CD14, and HLA-DR) and analyzed on a BD FACSArray Bioanalyzer. All samples will be measured in triplicates.

(167) (iv) Multilineage Differentiation—

(168) MSCs will be phenotypically assessed for their ability to either deposit a bone-like matrix, form fat-laden droplets or secrete glycosaminoglycans when stimulated with osteogenic, adipogenic or chondrogenic supplements. In parallel cultures, total RNA will be isolated and the levels of mRNA transcripts for TWIST-1, DERMO-1, together with other major osteogenic, adipogenic and chondrogenic biomarkers normalized to β-ACTIN.

(169) (v) Telomere Length—

(170) Chromosomal DNA will be isolated and then precipitated, washed, dried and quantified. DNA (12.5 ng) will be used for amplification of telomeric repeats by real time quantitative PCR (RQ-PCR), in triplicate. Relative expression of telomeric repeats will be estimated from standard curves (Ct vs. log quantity) made from chromosomal DNA isolated from the human embryonic stem cell line BG01V (Invitrogen).

(171) 3.3 Assessment of Stem Cell Quality In Vivo in an Ectopic Bone Formation Model

(172) Bone-healing potential of MSCs characterised as in 3.2 will be correlated with GSTT1 genotype in a clinically-relevant murine an ectopic bone formation model.

(173) Ectopic Bone Formation Assay

(174) TABLE-US-00009 TABLE 5 Experimental groups for ectopic bone formation assay Experimental Groupds (6 implants/group) Method Dose of MSCs 1 MasterGraft Matrix (vehicle 0 only) 2-11 MasterGraft Matrix + MSC 3 × 10.sup.6 (Donor 10) cultured in basal media

(175) (i) Animal Species:

(176) Immunodeficient 8 week-old female beige mice (NIH-bg-nu-xid) will be used as recipients for subcutaneous transplants.

(177) (ii) Cell and Scaffold Preparation:

(178) Ex vivo expanded, passage 4 MSCs (under maintenance conditions) from donors will be lifted by 0.125% trypsin/versene and resuspended in maintenance medium before seeding onto the MastertGraft® Matrix scaffold (Medtronic, Inc. USA). The MastertGraft® Matrix scaffold is a collagen sponge containing 15% HA/80% β-TCP ceramic particles. The scaffold will be cut into cubes of dimensions 3×3×3 mm (27 mm.sup.3) using surgical scalpels, under sterile conditions. Approximately 3-5 million osteoblasts will be seeded on to the cut scaffolds and incubated for 1 h at 37° C. prior to implantation. The scaffold and cells will be held together with a fibrin clot, generated with 15 μl of mouse thrombin (100 U/ml in 2% CaCl.sub.2; Sigma-Aldrich®, USA) and 15 μl of mouse fibrinogen (30 mg/ml in PBS; Sigma-Aldrich®, USA).

(179) (iii) Surgery:

(180) Operations will be performed according to specifications of an ethics-approved small animal protocol IACUC: #110651 (pending renewal). Mid-longitudinal skin incisions of 0.5 cm will made on the dorsal surface of each mouse, and subcutaneous pockets formed by blunt dissection. A single implant will be placed into each pocket with two implants per animal. Incisions will be closed with surgical staples. Each transplant and the corresponding control transplant, will be implanted under the same conditions (n=6).

(181) (iv) Methods of Analysis:

(182) The extent of new bone formation will be analyzed by X-rays, micro-CT, and histology. X-rays will be taken on the day of surgery immediately after transplantation and after 8 weeks.

(183) Micro-CT will be performed on the animals at weeks 4 and 8 using a SkyScan μCT-Analyser. Reconstructed images will be analyzed using Mimics software to compute the total bone volume by applying appropriate threshold settings set for each component. For histological analyses, sections of 5 μm thickness will be cut from the middle and either end of each 3-4 mm implant using a rotary microtome (Leica Microsystems, Germany). The paraffin sections will be placed on positively charged microscope slides, dried, stained with H&E and Rallis Trichrome, and finally examined under Zeiss Axiolmager (Z1) upright microscope. For immunohistochemistry analysis, tissue sections will be incubated with appropriate concentrations of primary antibodies to mouse osteocalcin, human osteocalcin, mouse collagen I or the same concentration of mouse IgG. Sections will be incubated with rat absorbed biotinlabeled anti-mouse IgG (Vector Lab Inc, USA), incubated with avidin-biotin-peroxidase complex (ABC) solution (Immunopure ABC preoxidase staining kit, Vector Lab. Inc) for 1 h. Peroxidase activity will be detected using 3,3-diaminobenzidiine-tetrahydrochloride (DAB; DAKO, USA).

(184) TABLE-US-00010 TABLE 6 Experimental plan X-ray MIcroCT Histology Experimental Group (0, 4, 8 weeks) (4, 8 weeks) (8 weeks) MasterGraft Matrix 6 of 6 6 of 6 6 of 6 (vehicle implants implants implants only) imaged imaged stained MasterGraft Matrix + 60 of 60 60 of 60 60 of 60 MSC (Donor 10) implants implants implants cultured in imaged imaged stained basal media

(185) 3.4 Assessment of Strategies for Modulating GSTT1 and Determining Effect on Stem Cell Quality

(186) The effects of modulating GSTT1 levels on in vitro MSCs via siRNA and small molecule inhibitors will be investigated.

(187) Given their importance, GSTs have become active targets for drug discovery, particularly for cancer and inflammatory diseases. Preliminary data indicates that the expression of GSTT1 directly impacts the proliferation rates of MSCs. Small molecule inhibitors of GSTT1 will be identified, MSCs will be treated with the inhibitors prior to transplantation, and whether it is possible to bestow bone-forming ability on GSTT1 wild-type cells will be assessed.

(188) GST inhibitors will be obtained from commercial sources and tested in vitro on GSTT1-expressing MSCs for their effects on proliferation. A series of established assays will be used, which will reveal differential activities within GSTT1+ and GSTT1−/− MSCs, including clonogenic potential (colony-forming activity), cell proliferation (the xCELLigence system), and growth rates (EdU labelling). Selected GSTT1 inhibitors will then be tested for their influence on MSC cytokine expression profiles, immunophenotype, and multipotency in vitro.

(189) It is also possible to target its downstream signaling pathways of GSTT1. Preliminary data indicate that p38 MAPK regulates GSTT1 expression (data not shown). The p38 MAPK may therefore be a key regulator of MSC proliferation, and bone-forming activity. Selective targeting of this pathway to enhance the regenerative potential of MSC may therefore be possible. Which cytokines are influenced by GSTT1 will be investigated, as will the mechanism of action, using molecular and pharmacological tools. GSTT1 will be over-expressed in null cells, and changes in cytokine expression will be investigated. Similarly, GSTT1 expression will be knocked-down by shRNA in wildtype MSCs, and subsequent changes in growth, signal transduction, phenotype and cytokine production will be investigated. Such perturbation studies will inform understanding of cytokine expression, and provide the means to explore underlying signaling pathways operating in the presence/absence of GSTT1.

(190) Statistical Justification for the Sample Size and the Means by which Data Will be Analyzed and Interpreted.

(191) Cell-Based Assays—

(192) All experiments will be performed with three independent repeats. The mean values and standard deviations will be computed. Analysis of variance (ANOVA) will be utilised to assess the level of significant difference between the experimental groups, followed by Tukey post hoc testing where appropriate. All statistical analysis will be performed using SPSS V 12.0 software (SPSS, Inc. Chicago, USA). The difference will be considered significant if p≤0.05.