Survival prediction and analysis of drug-resistance genes in HER2-positive breast cancer

Despite the approval of several therapeutic agents for HER2-positive breast cancer, drug resistance remains a significant challenge, hindering the patient's prognosis. Thus, our study aimed to establish a risk model to predict the prognosis of patients and identify key genes regulating drug resistance in HER2-positive breast cancer. Utilizing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), a predictive model was constructed based on 5 drug resistance-related genes, which demonstrated a notable capacity to indicate the survival rates of patients. Besides, through eccDNA and transcriptome sequencing of drug-sensitive and resistant cancer cells, 3 significant DEGs were identified: MED1, MED24, and NMD3. Among them, MED1 showed the most significant elevation in drug-resistance cells, highlighting its crucial role in mediating drug resistance. MED1 may serve as a valuable target for alleviating drug resistance in HER2-positive breast cancer. [Display omitted] •We identified critical genes associated with ErbB signaling pathway.•We constructed a significant predictive model based on five genes that were related to ErbB signaling pathway.•We performed eccDNA and transcriptome sequencing to identify crucial DEGs that related to drug resistance.•We screened out crucial non-coding RNA network that could promote drug-resistance of HER2-positive breast cancer.•Three key genes, including MED1, MED24, and NMD3 were found most significantly altered after drug resistance.