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Large-scale integrated analysis of ovarian cancer tumors and cell lines identifies an individualized gene expression signature for predicting response to platinum-based chemotherapy
Sun, Jie1; Bao, Siqi1; Xu, Dandan2; Zhang, Yan1; Su, Jianzhong1; Liu, Jiaqi3; Hao, Dapeng4; Zhou, Meng1
2019-09-01
Source PublicationCell Death and Disease
Volume10Issue:9
Abstract

Heterogeneity in chemotherapeutic response is directly associated with prognosis and disease recurrence in patients with ovarian cancer (OvCa). Despite the significant clinical need, a credible gene signature for predicting response to platinum-based chemotherapy and for guiding the selection of personalized chemotherapy regimens has not yet been identified. The present study used an integrated approach involving both OvCa tumors and cell lines to identify an individualized gene expression signature, denoted as IndividCRS, consisting of 16 robust chemotherapy-responsive genes for predicting intrinsic or acquired chemotherapy response in the meta-discovery dataset. The robust performance of this signature was subsequently validated in 25 independent tumor datasets comprising 2215 patients and one independent cell line dataset, across different technical platforms. The IndividCRS was significantly correlated with the response to platinum therapy and predicted the improved outcome. Moreover, the IndividCRS correlated with homologous recombination deficiency (HRD) and was also capable of discriminating HR-deficient tumors with or without platinum-sensitivity for guiding HRD-targeted clinical trials. Our results reveal the universality and simplicity of the IndividCRS as a promising individualized genomic tool to rapidly monitor response to chemotherapy and predict the outcome of patients with OvCa.

DOI10.1038/s41419-019-1874-9
URLView the original
Language英語English
WOS IDWOS:000488849400004
Scopus ID2-s2.0-85072054886
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Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.School of Ophthalmology & Optometry and Eye Hospital, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, 325027, China
2.Faculty of Sciences, Department of Biology, Harbin University, Harbin, 150081, China
3.Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
4.Faculty of Health Sciences, University of Macau, 999078, Macao
Recommended Citation
GB/T 7714
Sun, Jie,Bao, Siqi,Xu, Dandan,et al. Large-scale integrated analysis of ovarian cancer tumors and cell lines identifies an individualized gene expression signature for predicting response to platinum-based chemotherapy[J]. Cell Death and Disease, 2019, 10(9).
APA Sun, Jie., Bao, Siqi., Xu, Dandan., Zhang, Yan., Su, Jianzhong., Liu, Jiaqi., Hao, Dapeng., & Zhou, Meng (2019). Large-scale integrated analysis of ovarian cancer tumors and cell lines identifies an individualized gene expression signature for predicting response to platinum-based chemotherapy. Cell Death and Disease, 10(9).
MLA Sun, Jie,et al."Large-scale integrated analysis of ovarian cancer tumors and cell lines identifies an individualized gene expression signature for predicting response to platinum-based chemotherapy".Cell Death and Disease 10.9(2019).
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