ArticleFrontiers in molecular biosciences2026
An anoikis-based risk model predicts outcomes and is associated with the immune microenvironment in adrenocortical carcinoma.
Article in Frontiers in molecular biosciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: Adrenocortical 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. Methods: Based 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 Results: We identified 32 significantly dysregulated ARGs and established a risk model based on six core genes: Conclusion: The 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.
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