Machine learning prediction of HER2-low expression in breast cancers based on hematoxylin-eosin-stained slides.

ABSTRACT:

Background

Treatment with HER2-targeted therapies is recommended for HER2-positive breast cancer patients with HER2 gene amplification or protein overexpression. Interestingly, recent clinical trials of novel HER2-targeted therapies demonstrated promising efficacy in HER2-low breast cancers, raising the prospect of including a HER2-low category (immunohistochemistry, IHC) score of 1 + or 2 + with non-amplified in-situ hybridization for HER2-targeted treatments, which necessitated the accurate detection and evaluation of HER2 expression in tumors. Traditionally, HER2 protein levels are routinely assessed by IHC in clinical practice, which not only requires significant time consumption and financial investment but is also technically challenging for many basic hospitals in developing

SUBMITTER: Du J 

PROVIDER: S-EPMC12008878 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature