1. Integrative network analysis identifies an immune-based prognostic signature as the determinant for the mesenchymal subtype in epithelial ovarian cancer
- Author
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Xiaoyan Lu, Mingyan Sheng, Peng Shu, Xingguo Zhang, Ni Shanshan, B. A. Ashok Reddy, and Haofei Tong
- Subjects
Adult ,Oncology ,China ,medicine.medical_specialty ,Epithelial-Mesenchymal Transition ,Drug resistance ,Carcinoma, Ovarian Epithelial ,03 medical and health sciences ,0302 clinical medicine ,Immune system ,Internal medicine ,Humans ,Medicine ,Epithelial ovarian cancer ,030212 general & internal medicine ,Prospective cohort study ,Aged ,Retrospective Studies ,Aged, 80 and over ,Prognostic signature ,business.industry ,Gene Expression Profiling ,Mesenchymal stem cell ,General Medicine ,Middle Aged ,Prognosis ,medicine.disease ,Phenotype ,Gene Expression Regulation, Neoplastic ,030220 oncology & carcinogenesis ,Female ,business ,Ovarian cancer - Abstract
BACKGROUND Epithelial ovarian cancer (EOC) has been classified into four molecular subtypes, of which the mesenchymal subtype has the poorest survival. Our goal is to develop an immune-based prognostic signature by incorporating molecular subtypes for EOC patients. METHODS The gene expression profiles of EOC samples were collected from seven public datasets as well as an internal retrospective validation cohort, containing 1192 EOC patients. Network analysis was applied to integrate the mesenchymal modalities and immune signature to establish an immune-based prognostic signature for EOC (IPSEOC). The signature was trained and validated in eight independent datasets. RESULTS Seven immune genes were identified as key regulators of the mesenchymal subtype and were used to construct the IPSEOC. The IPSEOC significantly divided patients into high- and low-risk groups in discovery (OS: P
- Published
- 2020
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