Gene panel predicts neoadjuvant chemoimmunotherapy response and benefit from immunotherapy in HER2-negative breast cancer.

ABSTRACT:

Background

It is encountering the dilemma of lacking precise biomarkers to predict the response to neoadjuvant chemoimmunotherapy (NACI) and determine whether patients should use immune checkpoint inhibitors (ICIs) in early breast cancer (BC). We aimed to develop a gene signature to predict NACI response for BC patients and identify individuals suitable for adding ICIs.

Patients and methods

Two I-SPY2 cohorts and one West China Hospital cohort of patients treated with NACI were included. Machine learning algorithms were used to identify key genes. Principal component analysis was used to calculate the ImPredict (IP) score. The interaction effects between biomarkers and treatment regimens were examined based on the logistic regression analysis. The relationship between the IP

SUBMITTER: Lu X 

PROVIDER: S-EPMC11337705 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature