Latent class analysis-derived classification improves the cancer-specific death stratification of molecular subtyping in colorectal cancer.

ABSTRACT: The molecular subtypes of colorectal cancer (CRC) represent a comprehensive dissection of CRC heterogeneity. However, molecular feature-based classification systems have limitations in accurately prognosticating stratification due to the inability to distinguish cancer-specific deaths. This study aims to establish a classification system that bridges clinical characteristics, cause-specific deaths, and molecular features. We adopted latent class analysis (LCA) on 491,107 first primary CRC patients from the Surveillance, Epidemiology, and End Results (SEER) database to reveal hidden profiles of CRC. The LCA-derived classification scheme was further applied to The Cancer Genome Atlas (TCGA) to assess its effectiveness in improving the accurate stratification of molecular-based subtypes of CR

SUBMITTER: Zhou W 

PROVIDER: S-EPMC10290127 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature