High-throughput proteomics profiling-derived signature associated with chemotherapy response and survival for stage II/III colorectal cancer.

ABSTRACT: Adjuvant chemotherapy (ACT) is usually used to reduce the risk of disease relapse and improve survival for stage II/III colorectal cancer (CRC). However, only a subset of patients could benefit from ACT. Thus, there is an urgent need to identify improved biomarkers to predict survival and stratify patients to refine the selection of ACT. We used high-throughput proteomics to analyze tumor and adjacent normal tissues of stage II/III CRC patients with /without relapse to identify potential markers for predicting prognosis and benefit from ACT. The machine learning approach was applied to identify relapse-specific markers. Then the artificial intelligence (AI)-assisted multiplex IHC was performed to validate the prognostic value of the relapse-specific markers and construct a proteomic-derive

SUBMITTER: Ye SB 

PROVIDER: S-EPMC10232411 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature