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PMID: 41898428 已发表 · epublish 英语

Gene Expression Profiles Associated with Molecular Subtypes and Pathological Response to Neoadjuvant Treatment in Surgical Breast Cancer.

International journal of molecular sciences ·第 27 卷 ·第 6 期 ·2026-03-11

Baulies S, Molina-Vila MA, Tresserra F, Rodríguez I, Hurni Y, Giménez-Capitán A, Cabrera S, Fábregas R

摘要

Chemotherapy has significantly improved survival in breast cancer and, in the neoadjuvant setting, contributes to tumor downstaging and increased rates of breast-conserving surgery while enabling in vivo assessment of tumor biology and chemosensitivity. Pathological complete response (pCR) is a key endpoint associated with favorable outcomes; however, tumor heterogeneity highlights the need for reliable predictive biomarkers. This study evaluated the mRNA expression of 13 candidate genes in relation to molecular subtypes and pathological response to neoadjuvant chemotherapy (NAC) to identify potential predictive and prognostic markers. Pretreatment core biopsies from 92 patients receiving NAC were analyzed by quantitative RT-PCR. Molecular subtypes were determined by immunohistochemistry (ER, PR, HER2, Ki67), and pathological response was classified using the Miller-Payne scale as good (MP 4/5) or poor (MP 1-3). Multivariate logistic regression assessed associations between gene expression, subtype, and pCR. Hormone receptor-positive tumors showed significantly higher expression of AXL, FGFR1, RAP80, GAS6, BTRCP, and ZNF217. Significant associations with pCR were observed for AXL, FGFR1, YAP, and BRCA1. Low AXL and BRCA1 expression levels were independently associated with pCR. In addition, their combined low expression was associated most strongly with breast pCR in this cohort. These findings should be interpreted as exploratory and require validation in independent cohorts.

关键词
breast cancer subtypes gene expression profiling neoadjuvant chemotherapy pathological response predictive molecular markers
文献信息
期刊
International journal of molecular sciences
期刊简称
Int J Mol Sci
ISSN
1422-0067
发表日期
2026-03-11
语言
英语
国家/地区
Switzerland
NLM ID
101092791
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