Abstract

ObjectiveAdrenocortical carcinoma (ACC) is a rare but highly aggressive malignancy with limited treatment options. Anoikis plays a critical role in the progression of various cancers; however, its function in ACC remains unclear.MethodsBased on the GSE19776 and GSE12368 datasets, differentially expressed genes and significantly dysregulated anoikis-related genes were identified. Core ARGs were selected via protein-protein interaction network analysis and least absolute shrinkage and selection operator (LASSO)-Cox regression analysis to construct a risk-scoring model. Functional enrichment analyses, immune microenvironment association analysis, drug sensitivity analysis, mutation profiling, and in vitro experiments targeting SKP2 under routine adherent culture conditions were subsequently performed.ResultsWe identified 32 significantly dysregulated ARGs and established a risk model based on six core genes: BIRC5, CASP9, CDK1, EZH2, MDM2, and SKP2. Patients in the high-risk group had significantly shorter overall survival Functional analyses revealed that high-risk Adrenocortical carcinoma was primarily associated with biological processes such as DNA replication and cell cycle regulation. High-risk patients were also characterized by lower immune scores and altered immune cell infiltration patterns. High-risk patients showed increased sensitivity to chemotherapeutic agents including Gallibiscoquinazole, Cisplatin, Axitinib, and Zoledronate. Mutation profiling further identified TP53 missense mutation as a dominant molecular feature. Under routine adherent culture conditions, SKP2 knockdown inhibited ACC cell proliferation and migration, promoted apoptosis, and induced cell cycle arrest at the G0/G1 phase.ConclusionThe anoikis-based risk model may serve as a useful prognostic tool for ACC. ARGs may contribute to ACC progression and are associated with immune microenvironment features, providing a potential basis for further mechanistic and translational studies.