4.7 Article

Unique gene expression profile based on pathologic response in epithelial ovarian cancer

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JOURNAL OF CLINICAL ONCOLOGY
卷 23, 期 31, 页码 7911-7918

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AMER SOC CLINICAL ONCOLOGY
DOI: 10.1200/JCO.2005.02.9363

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  1. NCI NIH HHS [1R21CA107352, R01 CA85467, P50 CA105009, U01 CA88175] Funding Source: Medline
  2. NIDDK NIH HHS [U24 DK58739] Funding Source: Medline

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Purpose We investigated whether tumor tissue obtained at diagnosis expresses a specific gene profile that is predictive of findings at second-look surgery in patients with epithelial ovarian cancer (EOC). Patients and Methods Tumor tissue obtained at the time of diagnosis was profiled with oligonucleotide microarrays. Class prediction analysis was performed in a training set of 24 patients who had undergone a second-look procedure. The resultant predictive signature was then tested on an independent validation set comprised of 36 patients. Results A 93-gene signature referred to as the Chemotherapy Response Profile (CRP) was identified through its association with pathologic complete response. When applied to a separate validation set, the CRP distinguished between patients with unfavorable versus favorable overall survival (median 41 months v not yet reached, respectively, log-rank P = .007), with a median follow-up of 52 months. The signature maintained independent prognostic value in multivariate analysis, controlling for other known prognostic factors such as age, stage, grade, and debulking status. There was no genetic overlap between the CRP and our previously described Ovarian Cancer Prognostic Profile (OCPP), which demonstrated similar prognostic value. The combination of the CRP and OCPP yielded better prognostic discrimination then either profile alone. Genes present in the CRP include BAX a proapoptotic protein previously associated with chemotherapy response in ovarian cancer. Conclusion Identification of a gene expression profile based on pathologic response in EOC provides independent prognostic information and offers potential insights into the mechanism of drug resistance. Efforts to identify a more tailored profile using selected genes from both the CRP and OCPP are underway.

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