Identification of autophagy related genes predicting response of trastuzumab resistance in breast cancer patients

Abstract

AbstractBackground The emergence of trastuzumab resistance is the barrier to effective clinical outcomes for HER2 + Breast Cancer (BC). However, the relationship between the expression of autophagy related genes in HER2 + BC and their correlation with prognosis remains unclear. This study aims to identify the potential predictive markers through bioinformatics analysis and experiment validation. Methods Gene expression profile dataset GSE29431 was obtained from GEO database. Autophagy related differentially expressed genes (ARGs) of HER2 + BC were identified by R software. Multiple bioinformatics analyses were conducted to identify functional hub genes. The prognostic significance of these hub genes was validated, and the correlations between ARGs, clinicopathological parameters, and patient prognosis were analyzed using The Cancer Genome Atlas (TCGA) cohort. Results A total of 73 ARGs were identified between 41 HER2 + BC patients and 12 normal samples. Functional analysis, including Gene Ontology (GO), protein-protein interaction (PPI), and Kyoto Encyclopedia of Genes and Genomes (KEGG), revealed important functional genes related to macroautophagy, late endosome formation, and ubiquitin-like metabolism, which were identified as autophagy-related hub genes. Additionally, PPP1R15A, VAMP7, PTK6, CASP3 demonstrated strong predictive power in the TCGA cohort through prognostic correlation analysis (p < 0.05). The results of qRT-PCR and immunohistochemistry demonstrated increased expression of VAMP7 and PTK6 in BC patients with trastuzumab resistance, further confirming their prognostic significance in a trastuzumab adjuvant treatment cohort using our clinical data. Conclusions Patients with high expression of VAMP7 and PTK6 exhibit poor efficacy and prognosis in HER2 + BC, particularly in the context of trastuzumab neoadjuvant chemotherapy.