VISTA Deficiency Attenuates Antibody-induced Arthritis and Alters Macrophage Gene Expression in Response to Simulated Immune Complexes

In addition to activated T cells, the immune checkpoint inhibitor “V domain-containing Ig suppressor of T-cell activation” (VISTA) is expressed by myeloid cell types, including macrophages and neutrophils. The importance of VISTA expression by myeloid cells to antibody-induced arthritis and its potential for relevance in human disease was evaluated. Methods: VISTA was immunolocalized in normal and arthritic human synovial tissue sections and synovial tissue lysates were subjected to western blot analysis. The collagen antibody-induced arthritis model (CAIA) was performed with DBA/1 J mice treated with antibodies against VISTA and with VISTA-deficient mice (V-KO). Total mRNA from arthritic joints, spleens, and cultured macrophages was analyzed with NanoString arrays. Cytokines secreted by splenic inflammatory macrophages were determined. In-vitro chemotaxis and signal transduction assays were performed with cultured macrophages. Results: VISTA protein was localized to synovial membrane cells, neutrophils, and scattered cells in lymphocyte-rich foci and was detected by western blot analysis in normal synovium and synovium from rheumatoid arthritis patients. Deficiency of VISTA or treatment of mice with anti-VISTA monoclonal antibodies attenuated CAIA. Joint damage and MMP-3 expression were significantly reduced in V-KO mice. Surface expression of C5a receptor was reduced on monocytes, neutrophils, and cultured macrophages from V-KO. Upon Fc receptor engagement in vitro, gene expression by V-KO macrophages was altered profoundly compared to WT, including a significant induction of IL-1 receptor antagonist (IL1rn). Conclusions: VISTA expression supports immune-complex inflammation in CAIA and VISTA is expressed in human synovium. VISTA supports optimal responses to C5a and modulates macrophage responses to immune complexes

Epigenetic regulation of CD133 and tumorigenicity of CD133 positive and negative endometrial cancer cells

<p>Abstract</p> <p>Background</p> <p>Recent data provide significant evidence to support the hypothesis that there are sub-populations of cells within solid tumors that have an increased tumor initiating potential relative to the total tumor population. CD133, a cell surface marker expressed on primitive cells of neural, hematopoietic, endothelial and epithelial lineages has been identified as a marker for tumor initiating cells in solid tumors of the brain, colon, pancreas, ovary and endometrium. Our objectives were to assess the relative level of CD133 expressing cells in primary human endometrial tumors, confirm their tumorigenic potential, and determine whether CD133 expression was epigenetically modified.</p> <p>Methods</p> <p>We assessed CD133 expression in primary human endometrial tumors by flow cytometry and analyzed the relative tumorigenicity of CD133+ and CD133- cells in an <it>in vivo </it>NOD/SCID mouse model. We assessed potential changes in CD133 expression over the course of serial transplantation by immunofluorescence and flow cytometry. We further examined CD133 promoter methylation and expression in normal endometrium and malignant tumors.</p> <p>Results</p> <p>As determined by flow cytometric analysis, the percentage of CD133+ cells in primary human endometrial cancer samples ranged from 5.7% to 27.4%. In addition, we confirmed the tumor initiating potential of CD133+ and CD133^-cell fractions in NOD/SCID mice. Interestingly, the percentage of CD133+ cells in human endometrial tumor xenografts, as evidenced by immunofluorescence, increased with serial transplantation although this trend was not consistently detected by flow cytometry. We also determined that the relative levels of CD133 increased in endometrial cancer cell lines following treatment with 5-aza-2'-deoxycytidine suggesting a role for methylation in the regulation of CD133. To support this finding, we demonstrated that regions of the CD133 promoter were hypomethylated in malignant endometrial tissue relative to benign control endometrial tissue. Lastly, we determined that methylation of the CD133 promoter decreases over serial transplantation of an endometrial tumor xenograft.</p> <p>Conclusions</p> <p>These findings support the hypotheses that CD133 expression in endometrial cancer may be epigenetically regulated and that cell fractions enriched for CD133+ cells may well contribute to endometrial cancer tumorigenicity, pathology and recurrence.</p

VISTA Deficiency Attenuates Antibody-induced Arthritis and Alters Macrophage Gene Expression in Response to Simulated Immune Complexes

In addition to activated T cells, the immune checkpoint inhibitor “V domain-containing Ig suppressor of T-cell activation” (VISTA) is expressed by myeloid cell types, including macrophages and neutrophils. The importance of VISTA expression by myeloid cells to antibody-induced arthritis and its potential for relevance in human disease was evaluated. Methods: VISTA was immunolocalized in normal and arthritic human synovial tissue sections and synovial tissue lysates were subjected to western blot analysis. The collagen antibody-induced arthritis model (CAIA) was performed with DBA/1 J mice treated with antibodies against VISTA and with VISTA-deficient mice (V-KO). Total mRNA from arthritic joints, spleens, and cultured macrophages was analyzed with NanoString arrays. Cytokines secreted by splenic inflammatory macrophages were determined. In-vitro chemotaxis and signal transduction assays were performed with cultured macrophages. Results: VISTA protein was localized to synovial membrane cells, neutrophils, and scattered cells in lymphocyte-rich foci and was detected by western blot analysis in normal synovium and synovium from rheumatoid arthritis patients. Deficiency of VISTA or treatment of mice with anti-VISTA monoclonal antibodies attenuated CAIA. Joint damage and MMP-3 expression were significantly reduced in V-KO mice. Surface expression of C5a receptor was reduced on monocytes, neutrophils, and cultured macrophages from V-KO. Upon Fc receptor engagement in vitro, gene expression by V-KO macrophages was altered profoundly compared to WT, including a significant induction of IL-1 receptor antagonist (IL1rn). Conclusions: VISTA expression supports immune-complex inflammation in CAIA and VISTA is expressed in human synovium. VISTA supports optimal responses to C5a and modulates macrophage responses to immune complexes

Characterization of twenty-five ovarian tumour cell lines that phenocopy primary tumours

Currently available human tumour cell line panels consist of a small number of lines in each lineage that generally fail to retain the phenotype of the original patient tumour. Here we develop a cell culture medium that enables us to routinely establish cell lines from diverse subtypes of human ovarian cancers with >95% efficiency. Importantly, the 25 new ovarian tumour cell lines described here retain the genomic landscape, histopathology and molecular features of the original tumours. Furthermore, the molecular profile and drug response of these cell lines correlate with distinct groups of primary tumours with different outcomes. Thus, tumour cell lines derived using this methodology represent a significantly improved platform to study human tumour pathophysiology and response to therapy

Genome Wide DNA Copy Number Analysis of Serous Type Ovarian Carcinomas Identifies Genetic Markers Predictive of Clinical Outcome

Ovarian cancer is the fifth leading cause of cancer death in women. Ovarian cancers display a high degree of complex genetic alterations involving many oncogenes and tumor suppressor genes. Analysis of the association between genetic alterations and clinical endpoints such as survival will lead to improved patient management via genetic stratification of patients into clinically relevant subgroups. In this study, we aim to define subgroups of high-grade serous ovarian carcinomas that differ with respect to prognosis and overall survival. Genome-wide DNA copy number alterations (CNAs) were measured in 72 clinically annotated, high-grade serous tumors using high-resolution oligonucleotide arrays. Two clinically annotated, independent cohorts were used for validation. Unsupervised hierarchical clustering of copy number data derived from the 72 patient cohort resulted in two clusters with significant difference in progression free survival (PFS) and a marginal difference in overall survival (OS). GISTIC analysis of the two clusters identified altered regions unique to each cluster. Supervised clustering of two independent large cohorts of high-grade serous tumors using the classification scheme derived from the two initial clusters validated our results and identified 8 genomic regions that are distinctly different among the subgroups. These 8 regions map to 8p21.3, 8p23.2, 12p12.1, 17p11.2, 17p12, 19q12, 20q11.21 and 20q13.12; and harbor potential oncogenes and tumor suppressor genes that are likely to be involved in the pathogenesis of ovarian carcinoma. We have identified a set of genetic alterations that could be used for stratification of high-grade serous tumors into clinically relevant treatment subgroups

Genome wide DNA copy number analysis of serous type ovarian carcinomas identifies genetic markers predictive of clinical outcome.

Ovarian cancer is the fifth leading cause of cancer death in women. Ovarian cancers display a high degree of complex genetic alterations involving many oncogenes and tumor suppressor genes. Analysis of the association between genetic alterations and clinical endpoints such as survival will lead to improved patient management via genetic stratification of patients into clinically relevant subgroups. In this study, we aim to define subgroups of high-grade serous ovarian carcinomas that differ with respect to prognosis and overall survival. Genome-wide DNA copy number alterations (CNAs) were measured in 72 clinically annotated, high-grade serous tumors using high-resolution oligonucleotide arrays. Two clinically annotated, independent cohorts were used for validation. Unsupervised hierarchical clustering of copy number data derived from the 72 patient cohort resulted in two clusters with significant difference in progression free survival (PFS) and a marginal difference in overall survival (OS). GISTIC analysis of the two clusters identified altered regions unique to each cluster. Supervised clustering of two independent large cohorts of high-grade serous tumors using the classification scheme derived from the two initial clusters validated our results and identified 8 genomic regions that are distinctly different among the subgroups. These 8 regions map to 8p21.3, 8p23.2, 12p12.1, 17p11.2, 17p12, 19q12, 20q11.21 and 20q13.12; and harbor potential oncogenes and tumor suppressor genes that are likely to be involved in the pathogenesis of ovarian carcinoma. We have identified a set of genetic alterations that could be used for stratification of high-grade serous tumors into clinically relevant treatment subgroups

Characterization of twenty-five ovarian tumour cell lines that phenocopy primary tumours

Currently available human tumour cell line panels consist of a small number of lines in each lineage that generally fail to retain the phenotype of the original patient tumour. Here we develop a cell culture medium that enables us to routinely establish cell lines from diverse subtypes of human ovarian cancers with >95% efficiency. Importantly, the 25 new ovarian tumour cell lines described here retain the genomic landscape, histopathology and molecular features of the original tumours. Furthermore, the molecular profile and drug response of these cell lines correlate with distinct groups of primary tumours with different outcomes. Thus, tumour cell lines derived using this methodology represent a significantly improved platform to study human tumour pathophysiology and response to therapy

A–E.

<p>Representative aCGH profiles of 5 ovarian carcinomas. Log2 ratios (y axis) are plotted along the chromosomes (x axis). Each tumor showing many CNAs including gain and loss of entire chromosome and/or chromosome arms, interstitial deletions, and high-level amplifications (indicated in red arrows). Some tumors had more than 10 high-level amplifications. <b>F.</b> Genomic profiles of 72 primary ovarian carcinomas generated by oligonucleotide array CGH. Each column in the left panel represents a tumor sample and rows represent losses and gains of DNA sequences along the length of chromosomes 1 through X as determined by the segmentation analysis of normalized log2 ratios. The color scale ranges from blue (loss) through white (two copies) to red (gain). The right panel indicates the frequencies of gain and loss of oligonucleotide probes on a probe-by-probe basis for all autosomes and the X chromosome. The color scale ranges from white (no changes) to blue (frequent changes). Amplification of 3q26.2 and 8q24.12 including the <i>EVI1</i> and <i>MYC</i> oncogenes and deletion of 16q24.2 and 22q13.33 were the most frequent alterations observed in 75% and 78% of the ovarian carcinomas respectively. <b>G.</b> Overall frequency of CNAs in 72 high-grade serous ovarian carcinomas. <b>H and I.</b> GISTIC analysis of copy number gains (<b>H</b>) and losses (<b>I</b>) in ovarian carcinomas. The statistical significance of the aberrations identified by GISTIC are displayed as false discovery rate q values to account for multiple hypothesis testing (q values; green line is 0.25 cut-off for significance). Scores for each alteration are plotted along the x-axis and the genomic positions are plotted along the y-axis; dotted lines indicate the centromeres. <b>H</b>) GISTIC revealed twenty broad and focal regions of gain (copy number threshold = log2 ratio ≥0.4). <b>I</b>) Loss of both broad and focal regions were identified by GISTIC (copy number threshold = log2 ratio≤0.4 for broad and ≤0.1 for focal events). Twenty broad and focal regions of losses, including seven focal events, were identified in the background of broad regions. Candidate genes for some broad and focal events are noted. Green stars indicate known or presumed copy number polymorphisms.</p

Unsupervised hierarchical clustering of CNAs identifies distinct patient subgroups.

<p><b>A</b>) Unsupervised hierarchical clustering of raw log2 ratios derived from 72 serous type ovarian cancers. Copy number values are color coded as follows: blue (loss), white (normal) and magenta (gain). The pattern of dendrogram suggests two major genomic subgroups within the grade 3 tumors. <b>B</b>) PFS Kaplan-Meier plot for the two subgroups. <b>C</b>) Comparison of clinical characteristics between the patient subgroups. Histology: red = serous; Grade: orange = grade 2, yellow = grade 3; Stage: red = Ic, blue = II, green = IIc, yellow = IIIa, orange = IIIb, brown = IIIc, pink = IV, dark gray = IVa; Status: red = evidence of disease, blue = no evidence of disease; Outcome: green = complete remission, orange = progression, yellow = partial remission, brown = lost to follow up, pink = benign; 6 month progression: red = yes, blue = no, green = P (progression); Recurrence: brown = yes, orange = persistent disease, yellow = no; Platinum response: red = sensitive, black = resistant; Drug: blue = yes, light blue = no; Ascites: red = yes, black = no; Chemo: orange = yes, brown = no; Radiation: red = yes, black = no; General: white = n/a and/or blank.</p

Patient characterisitics.

<p>Patient characterisitics.</p