An epigenetic panel of NEFH and HS3ST2 relates to overall survival in human ovarian cancer .
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE43265 | GEO | 2017/12/31
SECONDARY ACCESSION(S): PRJNA185174
REPOSITORIES: GEO
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Project description:Ovarian cancer is the most lethal gynecological malignancy in the western world. Despite recent efforts to characterize ovarian cancer using molecular profiling, few targeted treatment options are currently available. Here, we examined genetic variants, fusion transcripts, SNP genotyping, and gene expression patterns for early-stage (I, II) ovarian carcinomas (n=96) in relation to clinicopathological characteristics and clinical outcome, thereby identifying novel genetic features of ovarian carcinomas. Furthermore, mutation frequencies of specific genetic variants and/or their gene expression patterns were associated with histotype and overall survival, e.g. SLC28A2 (mucinous ovarian carcinoma histotype), ARCN1 (low expression in 0-2 year survival group), and tumor suppressor MTUS1 (mutation status and overall survival). The long non-coding RNA MALAT1 was identified as a highly promiscuous fusion transcript in ovarian carcinoma. Moreover, gene expression deregulation for 23 genes was associated with tumor aggressiveness. Taken together, the novel biomarkers identified here may improve ovarian carcinoma subclassification and patient stratification according to histotype and overall survival.
2018-10-04 | GSE101107 | GEO
Project description:Ovarian cancer is the most lethal gynecological malignancy in the western world. Despite recent efforts to characterize ovarian cancer using molecular profiling, few targeted treatment options are currently available. Here, we examined genetic variants, fusion transcripts, SNP genotyping, and gene expression patterns for early-stage (I, II) ovarian carcinomas (n=96) in relation to clinicopathological characteristics and clinical outcome, thereby identifying novel genetic features of ovarian carcinomas. Furthermore, mutation frequencies of specific genetic variants and/or their gene expression patterns were associated with histotype and overall survival, e.g. SLC28A2 (mucinous ovarian carcinoma histotype), ARCN1 (low expression in 0-2 year survival group), and tumor suppressor MTUS1 (mutation status and overall survival). The long non-coding RNA MALAT1 was identified as a highly promiscuous fusion transcript in ovarian carcinoma. Moreover, gene expression deregulation for 23 genes was associated with tumor aggressiveness. Taken together, the novel biomarkers identified here may improve ovarian carcinoma subclassification and patient stratification according to histotype and overall survival.
2018-10-04 | GSE101108 | GEO
Project description:An epigenetic panel of NEFH and HS3ST2 relates to overall survival in human ovarian cancer .
| PRJNA185174 | ENA
Project description:A gene expression prognostic signature for overall survival in patients with high-grade serous ovarian cancer
| PRJNA547637 | ENA
Project description:Purpose: The majority of patients with epithelial ovarian cancer (EOC) is diagnosed at advanced stage and has a poor prognosis. A proportion of these patients though will fare well, with a prognosis similar to patients with early stage disease while others die very quickly. Clinicopathological prognostic factors do not allow precise identification of these subgroups. Thus we have validated a molecular subclassification as prognostic factor in EOC. Experimental Design: One hundred ninety-four patients with EOC stage II to IV were characterized by whole-genome expression profiling of tumor tissues and classified using a published 112 gene-set, derived from a FIGO stage directed supervised classification approach. Results: The 194 tumor samples were classified into two subclasses of 95 (subclass 1) and 99 (subclass 2) tumors, grouping all 9 FIGO II tumors in subclass 1 (p=0.001). Subclass 2 (54% of advanced stage tumors) correlated significantly with peritoneal carcinomatosis and non-optimal debulking. Patients with subclass 2 tumors had a worse progression free survival (HR 1.67, p=0.005) by univariate analysis, but it was not an independent factor in multiple analysis. However, overall survival was impaired both, univariate (HR 3.68, p<0.001) and in models corrected for relevant clinicopathologic parameters (HR 3.13, p<0.001). Significance analysis of microarrays revealed 2,115 genes differentially expressed in both subclasses (FDR 5%). Conclusion: In this validation study we showed that in advanced-stage epithelial ovarian cancer two approximately equally large molecular subtypes exist, independent from classical clinocopathological parameters presenting with highly different whole genome expression profiles and an impressively different overall survival. Purpose: The majority of patients with epithelial ovarian cancer (EOC) is diagnosed at advanced stage and has a poor prognosis. A proportion of these patients though will fare well, with a prognosis similar to patients with early stage disease while others die very quickly. Clinicopathological prognostic factors do not allow precise identification of these subgroups. Thus we have validated a molecular subclassification as prognostic factor in EOC. Experimental Design: One hundred ninety-four patients with EOC stage II to IV were characterized by whole-genome expression profiling of tumor tissues and classified using a published 112 gene-set, derived from a FIGO stage directed supervised classification approach. Results: The 194 tumor samples were classified into two subclasses of 95 (subclass 1) and 99 (subclass 2) tumors, grouping all 9 FIGO II tumors in subclass 1 (p=0.001). Subclass 2 (54% of advanced stage tumors) correlated significantly with peritoneal carcinomatosis and non-optimal debulking. Patients with subclass 2 tumors had a worse progression free survival (HR 1.67, p=0.005) by univariate analysis, but it was not an independent factor in multiple analysis. However, overall survival was impaired both, univariate (HR 3.68, p<0.001) and in models corrected for relevant clinicopathologic parameters (HR 3.13, p<0.001). Significance analysis of microarrays revealed 2,115 genes differentially expressed in both subclasses (FDR 5%). Conclusion: In this validation study we showed that in advanced-stage epithelial ovarian cancer two approximately equally large molecular subtypes exist, independent from classical clinocopathological parameters presenting with highly different whole genome expression profiles and an impressively different overall survival. Targeted therapies in second line treatment gain more and more importance in managing recurrent or progressive carcinomas, particularly in ovarian cancer, a cancer entity characterized by a very high recurrence rate. One step ahead, it is necessary to define new therapeutic targets and to select patients who might benefit from these therapies already in first line settings. A robust molecular subclassification could provide both, an adequate patient selection and potential new targets. Notably, the validation of such a subclassification is of outstanding importance to obtain a reliable basis for a specific clinical decision and a rational for the expensive development of new targeted therapies. This work provides a comprehensive basis for both. The expression values of 204 epithelial ovarian cancer tissues are determined and used for the validation of a subclassification approach (Cancer Sci. 2009 Aug;100(8):1421-8.)
2014-01-01 | E-GEOD-49997 | biostudies-arrayexpress
Project description:Transcriptomic and genomic profiling of early-stage ovarian carcinomas associated with histotype and overall survival
| PRJNA393720 | ENA
Project description:Purpose: The majority of patients with epithelial ovarian cancer (EOC) is diagnosed at advanced stage and has a poor prognosis. A proportion of these patients though will fare well, with a prognosis similar to patients with early stage disease while others die very quickly. Clinicopathological prognostic factors do not allow precise identification of these subgroups. Thus we have validated a molecular subclassification as prognostic factor in EOC. Experimental Design: One hundred ninety-four patients with EOC stage II to IV were characterized by whole-genome expression profiling of tumor tissues and classified using a published 112 gene-set, derived from a FIGO stage directed supervised classification approach. Results: The 194 tumor samples were classified into two subclasses of 95 (subclass 1) and 99 (subclass 2) tumors, grouping all 9 FIGO II tumors in subclass 1 (p=0.001). Subclass 2 (54% of advanced stage tumors) correlated significantly with peritoneal carcinomatosis and non-optimal debulking. Patients with subclass 2 tumors had a worse progression free survival (HR 1.67, p=0.005) by univariate analysis, but it was not an independent factor in multiple analysis. However, overall survival was impaired both, univariate (HR 3.68, p<0.001) and in models corrected for relevant clinicopathologic parameters (HR 3.13, p<0.001). Significance analysis of microarrays revealed 2,115 genes differentially expressed in both subclasses (FDR 5%). Conclusion: In this validation study we showed that in advanced-stage epithelial ovarian cancer two approximately equally large molecular subtypes exist, independent from classical clinocopathological parameters presenting with highly different whole genome expression profiles and an impressively different overall survival. Purpose: The majority of patients with epithelial ovarian cancer (EOC) is diagnosed at advanced stage and has a poor prognosis. A proportion of these patients though will fare well, with a prognosis similar to patients with early stage disease while others die very quickly. Clinicopathological prognostic factors do not allow precise identification of these subgroups. Thus we have validated a molecular subclassification as prognostic factor in EOC. Experimental Design: One hundred ninety-four patients with EOC stage II to IV were characterized by whole-genome expression profiling of tumor tissues and classified using a published 112 gene-set, derived from a FIGO stage directed supervised classification approach. Results: The 194 tumor samples were classified into two subclasses of 95 (subclass 1) and 99 (subclass 2) tumors, grouping all 9 FIGO II tumors in subclass 1 (p=0.001). Subclass 2 (54% of advanced stage tumors) correlated significantly with peritoneal carcinomatosis and non-optimal debulking. Patients with subclass 2 tumors had a worse progression free survival (HR 1.67, p=0.005) by univariate analysis, but it was not an independent factor in multiple analysis. However, overall survival was impaired both, univariate (HR 3.68, p<0.001) and in models corrected for relevant clinicopathologic parameters (HR 3.13, p<0.001). Significance analysis of microarrays revealed 2,115 genes differentially expressed in both subclasses (FDR 5%). Conclusion: In this validation study we showed that in advanced-stage epithelial ovarian cancer two approximately equally large molecular subtypes exist, independent from classical clinocopathological parameters presenting with highly different whole genome expression profiles and an impressively different overall survival. Targeted therapies in second line treatment gain more and more importance in managing recurrent or progressive carcinomas, particularly in ovarian cancer, a cancer entity characterized by a very high recurrence rate. One step ahead, it is necessary to define new therapeutic targets and to select patients who might benefit from these therapies already in first line settings. A robust molecular subclassification could provide both, an adequate patient selection and potential new targets. Notably, the validation of such a subclassification is of outstanding importance to obtain a reliable basis for a specific clinical decision and a rational for the expensive development of new targeted therapies. This work provides a comprehensive basis for both.
2014-01-01 | GSE49997 | GEO
Project description:To elucidate the mechanisms of rapid progression of serous ovarian cancer, gene expression profiles from forty-three ovarian cancer tissues comprising eight early stage and thirty-five advanced stage tissues were performed using oligonucleotide microarrays of 18,716 genes. By non-negative matrix factorization analysis using 178 genes, which were extracted as stage-specific genes, 35 advanced-stage cases were classified into two subclasses with superior (n = 17) and poor (n = 18) outcome evaluated by progression-free survival (logrank test, p = 0.03). Of the 178 stage-specific genes, 112 genes were identified as showing different expression between the two subclasses. Of the 48 genes selected for biological function by Gene Ontology analysis or Ingenuity Pathway Analysis, 5 genes (ZEB2, CDH1, LTBP2, COL16A1 and ACTA2) were extracted as candidates for prognostic factors associated with progression-free survival. The relationship between high ZEB2 or low CDH1 expression and shorter progression-free survival was validated by real-time RT-PCR experiments of 37 independent advanced-stage cancer samples. ZEB2 expression was negatively correlated with CDH1 expression in advanced-stage samples, whereas ZEB2 knockdown in ovarian adenocarcinoma SKOV3 cells resulted in an increase in CDH1 expression. Multivariate analysis showed that high ZEB2 expression was independently associated with poor prognosis. Furthermore, the prognostic effect of E-cadherin encoded by CDH1 was verified using immunohistochemical analysis of an independent advanced-stage cancer samples set (n = 74). These findings suggest that the expressions of epithelial-mesenchymal transition-related genes such as ZEB2 and CDH1 may play important roles in the invasion process of advanced-stage serous ovarian cancer. Forty-three serous ovarian cancer samples were analyzed. Ten normal peritoneum samples were used as controls.
2009-07-19 | E-GEOD-12470 | biostudies-arrayexpress
Project description:We performed a time-course microarray experiment to define the transcriptional response to carboplatin in vitro, and to correlate this with clinical outcome in epithelial ovarian cancer (EOC). RNA was isolated from carboplatin and control-treated 36M2 ovarian cancer cells at several time points, followed by oligonucleotide microarray hybridization. Carboplatin induced changes in gene expression were assessed at the single gene as well as at the pathway level. Clinical validation was performed in publicly available microarray datasets using disease free and overall survival endpoints. Time-course and pathway analyses identified 317 genes and 40 pathways (designated time-course and pathway signatures) deregulated following carboplatin exposure. Both types of signatures were validated in two separate platinum-treated ovarian and NSCLC cell lines using published microarray data. Expression of time-course and pathway signature genes distinguished between patients with unfavorable and favorable survival in two independent ovarian cancer datasets. Among the pathways most highly induced by carboplatin in vitro, the NRF2, NF-kB, and cytokine and inflammatory response pathways were also found to be upregulated prior to chemotherapy exposure in poor prognosis tumors. Experiment Overall Design: we treated the 36M2 cell line with carboplatin 100μM or vehicle-control for 24hrs and cells were harvested and processed for RNA isolation at 24, 30 and 36hrs after treatment.
2009-01-14 | E-GEOD-13525 | biostudies-arrayexpress