Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer. (19th December 2019)
- Record Type:
- Journal Article
- Title:
- Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer. (19th December 2019)
- Main Title:
- Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer
- Authors:
- Wu, Ce
He, Linxiu
Wei, Qian
Li, Qian
Jiang, Longyang
Zhao, Lan
Wang, Chunyan
Li, Jianping
Wei, Minjie - Abstract:
- Abstract: Most high‐grade serous ovarian cancer (HGSOC) patients develop resistance to platinum‐based chemotherapy and recur. Many biomarkers related to the survival and prognosis of drug‐resistant patients have been delved by mining databases; however, the prediction effect of single‐gene biomarker is not specific and sensitive enough. The present study aimed to develop a novel prognostic gene signature of platinum‐based resistance for patients with HGSOC. The gene expression profiles were obtained from Gene Expression Omnibus and The Cancer Genome Atlas database. A total of 269 differentially expressed genes (DEGs) associated with platinum resistance were identified ( P < .05, fold change >1.5). Functional analysis revealed that these DEGs were mainly involved in apoptosis process, PI3K‐Akt pathway. Furthermore, we established a set of seven‐gene signature that was significantly associated with overall survival (OS) in the test series. Compared with the low‐risk score group, patients with a high‐risk score suffered poorer OS ( P < .001). The area under the curve (AUC) was found to be 0.710, which means the risk score had a certain accuracy on predicting OS in HGSOC (AUC > 0.7). Surprisingly, the risk score was identified as an independent prognostic indicator for HGSOC ( P < .001). Subgroup analyses suggested that the risk score had a greater prognostic value for patients with grade 3‐4, stage III‐IV, venous invasion and objective response. In conclusion, we developed aAbstract: Most high‐grade serous ovarian cancer (HGSOC) patients develop resistance to platinum‐based chemotherapy and recur. Many biomarkers related to the survival and prognosis of drug‐resistant patients have been delved by mining databases; however, the prediction effect of single‐gene biomarker is not specific and sensitive enough. The present study aimed to develop a novel prognostic gene signature of platinum‐based resistance for patients with HGSOC. The gene expression profiles were obtained from Gene Expression Omnibus and The Cancer Genome Atlas database. A total of 269 differentially expressed genes (DEGs) associated with platinum resistance were identified ( P < .05, fold change >1.5). Functional analysis revealed that these DEGs were mainly involved in apoptosis process, PI3K‐Akt pathway. Furthermore, we established a set of seven‐gene signature that was significantly associated with overall survival (OS) in the test series. Compared with the low‐risk score group, patients with a high‐risk score suffered poorer OS ( P < .001). The area under the curve (AUC) was found to be 0.710, which means the risk score had a certain accuracy on predicting OS in HGSOC (AUC > 0.7). Surprisingly, the risk score was identified as an independent prognostic indicator for HGSOC ( P < .001). Subgroup analyses suggested that the risk score had a greater prognostic value for patients with grade 3‐4, stage III‐IV, venous invasion and objective response. In conclusion, we developed a seven‐gene signature relating to platinum resistance, which can predict survival for HGSOC and provide novel insights into understanding of platinum resistance mechanisms and identification of HGSOC patients with poor prognosis. Abstract : The present study aimed to develop a novel prognostic gene signature of platinum‐based resistance for patients with HGSOC. We developed a seven‐gene signature relating to platinum‐resistance, which can predict survival for HGSOC and provide novel insights into understanding of platinum‐resistance mechanisms and identification of HGSOC patients with poor prognosis. … (more)
- Is Part Of:
- Cancer medicine. Volume 9:Number 3(2020)
- Journal:
- Cancer medicine
- Issue:
- Volume 9:Number 3(2020)
- Issue Display:
- Volume 9, Issue 3 (2020)
- Year:
- 2020
- Volume:
- 9
- Issue:
- 3
- Issue Sort Value:
- 2020-0009-0003-0000
- Page Start:
- 1242
- Page End:
- 1253
- Publication Date:
- 2019-12-19
- Subjects:
- bioinformatics -- high‐grade serous ovarian cancer -- platinum resistance -- prognosis
616.994005 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2045-7634 ↗ - DOI:
- 10.1002/cam4.2692 ↗
- Languages:
- English
- ISSNs:
- 2045-7634
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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- 12695.xml