Affiliation:
1. Oncology Biomarker Research Group, Institute of Molecular Life Sciences, Hungarian Research Network, Magyar Tudósok Körútja 2, 1117 Budapest, Hungary
2. National Laboratory for Drug Research and Development, Magyar Tudósok Körútja 2, 1117 Budapest, Hungary
3. Department of Bioinformatics, Semmelweis University, 1094 Budapest, Hungary
Abstract
Approximately 30% of early-stage breast cancer (BC) patients experience recurrence after systemic chemotherapy; thus, understanding therapy resistance is crucial in developing more successful treatments. Here, we investigated the mechanisms underlying resistance to combined anthracycline–taxane treatment by comparing gene expression patterns with subsequent therapeutic responses. We established a cohort of 634 anthracycline–taxane-treated patients with pathological complete response (PCR) and a separate cohort of 187 patients with relapse-free survival (RFS) data, each having transcriptome-level expression data of 10,017 unique genes. Patients were categorized as responders and non-responders based on their PCR and RFS status, and the expression for each gene was compared between the two groups using a Mann–Whitney U-test. Statistical significance was set at p < 0.05, with fold change (FC) > 1.44. Altogether, 224 overexpressed genes were identified in the tumor samples derived from the patients without PCR; among these, the gene sets associated with xenobiotic metabolism (e.g., CYP3A4, CYP2A6) exhibited significant enrichment. The genes ORAI3 and BCAM differentiated non-responders from responders with the highest AUC values (AUC > 0.75, p < 0.0001). We identified 51 upregulated genes in the tumor samples derived from the patients with relapse within 60 months, participating primarily in inflammation and innate immune responses (e.g., LYN, LY96, ANXA1). Furthermore, the amino acid transporter SLC7A5, distinguishing non-responders from responders, had significantly higher expression in tumors and metastases than in normal tissues (Kruskal–Wallis p = 8.2 × 10−20). The identified biomarkers underscore the significance of tumor metabolism and microenvironment in treatment resistance and can serve as a foundation for preclinical validation studies.
Funder
National Research, Development and Innovation Office of Hungary
Janos Bolyai Scholarship of the Hungarian Academy of Sciences
Subject
Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis