Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer
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...
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Online Access: | https://doi.org/10.1002/cam4.2692 |
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doaj-d21c0a21656c4cce8b9e73a3e529787b2020-11-24T23:34:02ZengWileyCancer Medicine2045-76342020-02-01931242125310.1002/cam4.2692Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancerCe Wu0Linxiu He1Qian Wei2Qian Li3Longyang Jiang4Lan Zhao5Chunyan Wang6Jianping Li7Minjie Wei8Department of Pharmacology School of Pharmacy China Medical University Shenyang City ChinaDepartment of Pharmacology School of Pharmacy China Medical University Shenyang City ChinaDepartment of Pharmacology School of Pharmacy China Medical University Shenyang City ChinaLiaoning Cancer Hospital and Institute Cancer Hospital of China Medical University Shenyang City ChinaDepartment of Pharmacology School of Pharmacy China Medical University Shenyang City ChinaDepartment of Pharmacology School of Pharmacy China Medical University Shenyang City ChinaLiaoning Cancer Hospital and Institute Cancer Hospital of China Medical University Shenyang City ChinaDepartment of Pharmacology School of Pharmacy China Medical University Shenyang City ChinaDepartment of Pharmacology School of Pharmacy China Medical University Shenyang City ChinaAbstract 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.https://doi.org/10.1002/cam4.2692bioinformaticshigh‐grade serous ovarian cancerplatinum resistanceprognosis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ce Wu Linxiu He Qian Wei Qian Li Longyang Jiang Lan Zhao Chunyan Wang Jianping Li Minjie Wei |
spellingShingle |
Ce Wu Linxiu He Qian Wei Qian Li Longyang Jiang Lan Zhao Chunyan Wang Jianping Li Minjie Wei Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer Cancer Medicine bioinformatics high‐grade serous ovarian cancer platinum resistance prognosis |
author_facet |
Ce Wu Linxiu He Qian Wei Qian Li Longyang Jiang Lan Zhao Chunyan Wang Jianping Li Minjie Wei |
author_sort |
Ce Wu |
title |
Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer |
title_short |
Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer |
title_full |
Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer |
title_fullStr |
Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer |
title_full_unstemmed |
Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer |
title_sort |
bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer |
publisher |
Wiley |
series |
Cancer Medicine |
issn |
2045-7634 |
publishDate |
2020-02-01 |
description |
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 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. |
topic |
bioinformatics high‐grade serous ovarian cancer platinum resistance prognosis |
url |
https://doi.org/10.1002/cam4.2692 |
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