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6. Additional file 1 of Molecular subtypes based on cuproptosis-related genes and tumor microenvironment infiltration characterization in ovarian cancer

Author

Zhang, Jingjing, Lu, Miao, Xu, Haoya, Ren, Fang, and Zhu, Liancheng

Abstract

Additional file 1: Figure S1. The Kaplan-Meier plots of 9 prognostic CRGs in ovarian cancer. Figure S2. Unsupervised clustering of cuproptosis-related genes and Consensus matrix heatmaps for k = 2,4-9, as well as the consensus cumulative distribution function (CDF) curve for 2-9 curves. Figure S3. External validation for unsupervised clustering of cuproptosis-related genes in GSE32062. a Unsupervised clustering of cuproptosis-related genes in GSE32062, showing the consensus matrix heatmaps for k = 2-5; b Kaplan–Meier curves for overall survival of 260 OC patients (GSE32062) with three cuproptosis subtypes, the significant differences were observed among the three subtypes (log-rank test, p =0.0329). Figure S4. Forest plot of 48 prognostic genes after uniCox analysis of the DEGs (all P

Published
2022
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10. methylation-driven genes prognostic signature and the immune microenvironment in epithelial ovarian cancer.

Author

Tan, Mingzi, Wang, Shengtan, Li, Feifei, Xu, Haoya, Gao, Jian, and Zhu, Liancheng

Subjects
OVARIAN epithelial cancer, OVARIAN cancer, DISEASE risk factors, OVARIAN diseases, THERAPEUTICS, TUMOR suppressor genes, GENES, CANCER patients, OVARIAN reserve
Abstract

Aberrant gene methylation has been implicated in the development and progression of tumors. In this study, we aimed to identity methylation-driven genes involved in epithelial ovarian cancer (EOC) to establish a prognostic signature for patients with EOC. We identified and verified 6 MDGs that are closely related to the prognosis of ovarian cancer. A prognostic risk score model and nomogram for predicting the prognosis of ovarian cancer were constructed based on the six MDGs. It can also effectively reflect the immune environment and immunotherapy response of ovarian cancer. These MDGs have great significance to the implementation of individualized treatment and disease monitoring of ovarian cancer patients. [ABSTRACT FROM AUTHOR]

Published
2022
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