Machine learning developed a CD8+ exhausted T cells signature for predicting prognosis, immune infiltration and drug sensitivity in ovarian cancer

Machine learning developed a CD8+ exhausted T cells signature for predicting prognosis, immune infiltration and drug sensitivity in ovarian cancer

Abstract CD8+ exhausted T cells (CD8+ Tex) played a vital role in the progression and therapeutic response of cancer. However, few studies have fully clarified the characters of CD8+ Tex related genes in ovarian cancer (OC). The CD8+ Tex related prognostic signature (TRPS) was constructed with integ...

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Bibliographic Details
Main Authors: Rujun Chen, Yicai Zheng, Chen Fei, Jun Ye, He Fei
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Scientific Reports
Subjects:
CD8+ Tex
Machine learning
Ovarian cancer
Prognostic signature
Immunotherapy
Online Access:https://doi.org/10.1038/s41598-024-55919-4

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