Crafting a Personalized Prognostic Model for Malignant Prostate Cancer Patients Using Risk Gene Signatures Discovered through TCGA-PRAD Mining, Machine Learning, and Single-Cell RNA-Sequencing

Crafting a Personalized Prognostic Model for Malignant Prostate Cancer Patients Using Risk Gene Signatures Discovered through TCGA-PRAD Mining, Machine Learning, and Single-Cell RNA-Sequencing

Background: Prostate cancer is a significant clinical issue, particularly for high Gleason score (GS) malignancy patients. Our study aimed to engineer and validate a risk model based on the profiles of high-GS PCa patients for early identification and the prediction of prognosis. Methods: We conduct...

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Bibliographic Details
Main Authors: Feng Lyu, Xianshu Gao, Mingwei Ma, Mu Xie, Shiyu Shang, Xueying Ren, Mingzhu Liu, Jiayan Chen
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Diagnostics
Subjects:
prostate cancer
prognostic model
immunotherapy
machine learning
single-cell RNA-sequencing
Online Access:https://www.mdpi.com/2075-4418/13/12/1997

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