Unknown,Transcriptomics,Genomics,Proteomics

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A Gene Signature Predicting for Survival in Suboptimally Debulked Patients with Ovarian Cancer

ABSTRACT: To identify a prognostic gene signature accounting for the distinct clinical outcomes in ovarian cancer patients Despite the existence of morphologically indistinguishable disease, patients with advanced ovarian tumors display a broad range of survival end points. We hypothesize that gene expression profiling can identify a prognostic signature accounting for these distinct clinical outcomes. To resolve survival-associated loci, gene expression profiling was completed for an extensive set of 185(90 optimal/95 suboptimal) primary ovarian tumors using the Affymetrix human U133A microarray. Cox regression analysis identified probe sets associated with survival in optimally and suboptimally debulked tumor sets at a P value of <0.01. Leave-one-out cross-validation was applied to each tumor cohort and confirmed by a permutation test. External validation was conducted by applying the gene signature to a publicly available array database of expression profiles of advanced stage suboptimally debulked tumors. The prognostic signature successfully classified the tumors according to survival for suboptimally (P = 0.0179) but not optimally debulked (P = 0.144) patients. The suboptimal gene signature was validated using the independent set of tumors (odds ratio, 8.75; P = 0.0146). To elucidate signaling events amenable to therapeutic intervention in suboptimally debulked patients, pathway analysis was completed for the top 57 survival-associated probe sets. For suboptimally debulked patients, confirmation of the predictive gene signature supports the existence of a clinically relevant predictor, as well as the possibility of novel therapeutic opportunities. Ultimately, the prognostic classifier defined for suboptimally debulked tumors may aid in the classification and enhancement of patient outcome for this high-risk population. Gene expression profiling was completed for an extensive set of 185 primary ovarian tumors and 10 normal ovarian surface epithelium using the Affymetrix human U133A microarray

ORGANISM(S): Homo sapiens

SUBMITTER: Michael Birrer

PROVIDER: E-GEOD-26712 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Tumor specimens were collected from women with ovarian tumors at primary surgery in a study covering most of Denmark called the MALOVA-study (MALignant OVArian cancer study). This multidisciplinary study on ovarian cancer covers epidemiology (life style factors), biochemistry, and molecular biology with the purpose of identifying risk factors and prognostic factors for EOC. The study has been approved by the Scientific Ethic Committees in the study area (KF01-384/95). Sample collection went on from 1994 to 1999, and the study is described in details in other articles(20;21;24;30). Histopathological classification of the ovarian tumors was based on the typing criteria of the WHO. Pathology reports and tissue were collected from the participating hospitals. One pathologist specialized in ovarian tumors, reviewed the tissue specimens without knowledge of the primary diagnoses. Subsequently, the reviewed diagnosis was compared to the original diagnosis and agreement on invasiveness was present in 98 % of the cases. The histopathological type was refined in 14% of the cases. FIGO stages were obtained from clinical records and were reviewed by two gynecologists, both specialized in OC. Reviewed data were used for further analysis. Furthermore all other relevant hospital files were collected, and data concerning, debulking status, CA-125 level prior to operation, amount and type of chemotherapy and cause of death (if dead) were registered. Patients were scored as ÂradicalÂ (optimally debulked) if no macroscopic residual tumor nodules were left, and as Ânon-radicalÂ (sub-optimally debulked) if macroscopic nodules were left. All fresh tumor samples included in this study were intended to be snap frozen within 20 minutes after the tumor was removed, but exact transportation time is not known. All samples have been stored at -80ÂºC. We selected samples from the largest and most common histological subtype, the serous ovarian cancers, all stages. The tumor sample material consisted of 70 stage III/IV tumors and 19 stage I/II tumors. Further patient information can be obtained from the submitters on request.

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A Gene Signature Predicting for Survival in Suboptimally Debulked Patients with Ovarian Cancer

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