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Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer
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 sp...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6997076/ https://www.ncbi.nlm.nih.gov/pubmed/31856408 http://dx.doi.org/10.1002/cam4.2692 |
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author | Wu, Ce He, Linxiu Wei, Qian Li, Qian Jiang, Longyang Zhao, Lan Wang, Chunyan Li, Jianping Wei, Minjie |
author_facet | Wu, Ce He, Linxiu Wei, Qian Li, Qian Jiang, Longyang Zhao, Lan Wang, Chunyan Li, Jianping Wei, Minjie |
author_sort | Wu, Ce |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6997076 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-69970762020-02-05 Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer Wu, Ce He, Linxiu Wei, Qian Li, Qian Jiang, Longyang Zhao, Lan Wang, Chunyan Li, Jianping Wei, Minjie Cancer Med Cancer Prevention 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. John Wiley and Sons Inc. 2019-12-19 /pmc/articles/PMC6997076/ /pubmed/31856408 http://dx.doi.org/10.1002/cam4.2692 Text en © 2019 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Cancer Prevention Wu, Ce He, Linxiu Wei, Qian Li, Qian Jiang, Longyang Zhao, Lan Wang, Chunyan Li, Jianping Wei, Minjie Bioinformatic profiling identifies a platinum‐resistant–related risk signature for ovarian cancer |
title | 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_short | 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 |
topic | Cancer Prevention |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6997076/ https://www.ncbi.nlm.nih.gov/pubmed/31856408 http://dx.doi.org/10.1002/cam4.2692 |
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