Unique Gene Expression Profile Based on Pathologic Response in Epithelial Ovarian Cancer

2005 ◽  
Vol 23 (31) ◽  
pp. 7911-7918 ◽  
Author(s):  
Dimitrios Spentzos ◽  
Douglas A. Levine ◽  
Shakirahmed Kolia ◽  
Hasan Otu ◽  
Jeff Boyd ◽  
...  

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.

2010 ◽  
Vol 28 (22) ◽  
pp. 3555-3561 ◽  
Author(s):  
Panagiotis A. Konstantinopoulos ◽  
Dimitrios Spentzos ◽  
Beth Y. Karlan ◽  
Toshiyasu Taniguchi ◽  
Elena Fountzilas ◽  
...  

Purpose To define a gene expression profile of BRCAness that correlates with chemotherapy response and outcome in epithelial ovarian cancer (EOC). Methods A publicly available microarray data set including 61 patients with EOC with either sporadic disease or BRCA½ germline mutations was used for development of the BRCAness profile. Correlation with platinum responsiveness was assessed in platinum-sensitive and platinum-resistant tumor biopsy specimens from six patients with BRCA germline mutations. Association with poly-ADP ribose polymerase (PARP) inhibitor responsiveness and with radiation-induced RAD51 foci formation (a surrogate of homologous recombination) was assessed in Capan-1 cell line clones. The BRCAness profile was validated in 70 patients enriched for sporadic disease to assess its association with outcome. Results The BRCAness profile accurately predicted platinum responsiveness and mutation status in eight of 10 patient-derived tumor specimens and between PARP-inhibitor sensitivity and resistance in four of four Capan-1 clones. When applied to the 70 patients with sporadic disease, patients with the BRCA-like (BL) profile had improved disease-free survival (34 months v 15 months; log-rank P = .013) and overall survival (72 months v 41 months; log-rank P = .006) compared with patients with a non–BRCA-like (NBL) profile, respectively. The BRCAness profile maintained independent prognostic value in multivariate analysis, which controlled for other known clinical prognostic factors. Conclusion The BRCAness profile correlates with responsiveness to platinum and PARP inhibitors and identifies a subset of sporadic patients with improved outcome. Additional evaluation of this profile as a predictive tool in patients with sporadic EOC is warranted.


Medicine ◽  
2016 ◽  
Vol 95 (46) ◽  
pp. e5296 ◽  
Author(s):  
Fang Cao ◽  
Liping Chen ◽  
Manhua Liu ◽  
Weiwei Lin ◽  
Jinlong Ji ◽  
...  

2018 ◽  
Vol 29 ◽  
pp. viii50
Author(s):  
E. Høgdall ◽  
C.K. Høgdall ◽  
P.-T. Vo ◽  
W. Zhou ◽  
L. Huang ◽  
...  

2020 ◽  
Vol 158 (1) ◽  
pp. 178-187
Author(s):  
Fangfang Song ◽  
Lian Li ◽  
Baifeng Zhang ◽  
Yanrui Zhao ◽  
Hong Zheng ◽  
...  

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