Integration of machine learning and experimental validation to identify the prognostic signature related to diverse programmed cell deaths in breast cancer.

ABSTRACT:

Background

Programmed cell death (PCD) is closely related to the occurrence, development, and treatment of breast cancer. The aim of this study was to investigate the association between various programmed cell death patterns and the prognosis of breast cancer (BRCA) patients.

Methods

The levels of 19 different programmed cell deaths in breast cancer were assessed by ssGSEA analysis, and these PCD scores were summed to obtain the PCDS for each sample. The relationship of PCDS with immune as well as metabolism-related pathways was explored. PCD-associated subtypes were obtained by unsupervised consensus clustering analysis, and differentially expressed genes between subtypes were analyzed. The prognostic signature (PCDRS) were constructed by the best combination of 101 machin

SUBMITTER: Li L 

PROVIDER: S-EPMC11744720 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature