Gene-Mutation-Based Algorithm for Prediction of Treatment Response in Colorectal Cancer Patients.

ABSTRACT:

Purpose

Despite the high mortality of metastatic colorectal cancer (mCRC), no new biomarker tools are available for predicting treatment response. We developed gene-mutation-based algorithms as a biomarker classifier to predict treatment response with better precision than the current predictive factors.

Methods

Random forest machine learning (ML) was applied to identify the candidate algorithms using the MSK Cohort (n = 471) as a training set and validated in the TCGA Cohort (n = 221). Logistic regression, progression-free survival (PFS), and univariate/multivariate Cox proportional hazard analyses were performed and the performance of the candidate algorithms was compared with the established risk parameters.

Results

A novel 7-Gene Algorithm based on mutation profil

SUBMITTER: Johnson H 

PROVIDER: S-EPMC9030299 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature