Molecular classification of geriatric breast cancer displays distinct senescent subgroups of prognostic significance.

ABSTRACT: Breast cancer in the elderly presents distinct biological characteristics and clinical treatment responses compared with cancer in younger patients. Comprehensive Geriatric Assessment is recommended for evaluating treatment efficacy in elderly cancer patients based on physiological classification. However, research on molecular classification in older cancer patients remains insufficient. In this study, we identified two subgroups with distinct senescent clusters among geriatric breast cancer patients through multi-omics analysis. Using various machine learning algorithms, we developed a comprehensive scoring model called "Sene_Signature," which more accurately distinguished elderly breast cancer patients compared with existing methods and better predicted their prognosis. The Sene_Signatu

SUBMITTER: Wu X 

PROVIDER: S-EPMC11408383 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature