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...
Main Authors: | Ce Wu, Linxiu He, Qian Wei, Qian Li, Longyang Jiang, Lan Zhao, Chunyan Wang, Jianping Li, Minjie Wei |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2020-02-01
|
Series: | Cancer Medicine |
Subjects: | |
Online Access: | https://doi.org/10.1002/cam4.2692 |
Similar Items
-
Development of Machine Learning Models to Predict Platinum Sensitivity of High-Grade Serous Ovarian Carcinoma
by: Suhyun Hwangbo, et al.
Published: (2021-04-01) -
Kallistatin inhibits tumour progression and platinum resistance in high-grade serous ovarian cancer
by: Huan Wu, et al.
Published: (2019-12-01) -
Targeting Aurora A Kinase (AAK) in Platinum-Resistant High Grade Serous Ovarian Cancer
by: Ram N. Ganapathi, et al.
Published: (2020-08-01) -
Tumor genomic, transcriptomic, and immune profiling characterizes differential response to first‐line platinum chemotherapy in high grade serous ovarian cancer
by: Johanne I. Weberpals, et al.
Published: (2021-05-01) -
Identification of Chemoresistance-Associated Key Genes and Pathways in High-Grade Serous Ovarian Cancer by Bioinformatics Analyses
by: Wu Y, et al.
Published: (2020-06-01)