利用定量转录组学增强HER2低表达乳腺癌的检测

Enhancing HER2-low breast cancer detection with quantitative transcriptomics.

作者信息

Misiakou Maria-Anna, Jensen Maj-Britt, Talman Maj-Lis, Ejlertsen Bent, Rossing Maria

机构信息

Center for Genomic Medicine, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.

Danish Breast Cancer Group, Copenhagen, Denmark.

出版信息

NPJ Breast Cancer. 2025 Sep 1;11(1):98. doi: 10.1038/s41523-025-00817-9.

DOI:10.1038/s41523-025-00817-9

PMID:40890218

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12402487/

Abstract

Accurate identification of HER2-low breast cancers remains challenging using standard IHC. We analyzed 3182 breast tumors using transcriptomics, revealing detectable ERBB2 mRNA in 86% of IHC 0 cases. Pathological complete response was most prevalent in anti-HER2-treated patients with highest ERBB2 expression. Our results demonstrate that transcriptomics can sensitively detect HER2 expression and stratify patients beyond IHC classification, supporting its use as a complementary biomarker for guiding anti-HER2 therapy decisions.

摘要

使用标准免疫组化（IHC）准确识别HER2低表达乳腺癌仍然具有挑战性。我们使用转录组学分析了3182例乳腺肿瘤，发现在86%的IHC 0病例中可检测到ERBB2 mRNA。病理完全缓解在ERBB2表达最高的抗HER2治疗患者中最为常见。我们的结果表明，转录组学可以灵敏地检测HER2表达，并对患者进行超出IHC分类的分层，支持将其用作指导抗HER2治疗决策的补充生物标志物。