Exploration of the role of drug resistance-associated anoikis-related genes in HER2-Negative breast cancer through bioinformatics analysis
Year: 2025
Type: article
Abstract: To explore the potential functions and impacts of anoikis-related genes (ARGs) in breast cancer chemotherapy and to construct a prognosis model for HER2-negative breast cancer (HNBC) based on drug resistance-related ARGs. Breast cancer remains a leading cause of cancer-related mortality, with HER2-negative subtypes exhibiting high rates of metastasis and recurrence. Standard treatments for HNBC include taxane- and anthracycline-based chemotherapies, which aim to mitigate recurrence and metastasis. Anoikis, a specialized form of programmed cell death, plays a pivotal role in maintaining tissue homeostasis by eliminating detached cells. Cancer cells often develop resistance to anoikis, enabling survival in adverse conditions and promoting tumor progression. To investigate the intersection of breast cancer drug resistance-related genes and anoikis-related genes (ARGs) and to assess their potential as biomarkers for HNBC. The study also aims to analyze differences in immune microenvironment and drug sensitivity among different prognosis score groups. A bioinformatics approach was employed to identify the intersection of breast cancer drug resistance-related genes and ARGs. A prognosis model for HNBC was developed based on these identified drug resistance-related ARGs. The study further examined differences in the immune microenvironment and drug sensitivity among different prognosis score groups. A prognosis model for HNBC was successfully constructed based on drug resistance-related ARGs. The study identified significant differences in immune microenvironment and drug sensitivity across different prognosis score groups. The findings suggest that ARGs could be key in tailoring more effective therapeutic approaches for patients with HER2-negative breast cancer. • Identified anoikis-related genes (ARGs) linked to chemotherapy resistance in HER2-negative breast cancer (HNBC). • Created a prognostic model for HNBC using drug resistance-related ARGs, enabling improved risk stratification. • Found significant immune microenvironment variations across prognosis score groups. • Noted distinct drug sensitivity patterns among prognosis score groups, guiding personalized therapy. • ARGs emerged as potential biomarkers, advancing personalized treatment strategies for HNBC.
Authors: Yuanzhao Wu, Cong Chen, Zao Jin, Kesi Zheng
Institutions: Wenzhou Medical University, Wenzhou City People's Hospital
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,700
Award: G4706947603
OpenAlex ID: W4407834122
