ArticleIET systems biology
Integrated Analysis Identifies an Anoikis-Related Gene Signature for Predicting Prognosis in Patients With Triple-Negative Breast Cancer.
Article in IET systems biology. 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
Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with limited therapeutic options and poor prognosis. Anoikis resistance contributes to tumour dissemination, metastasis and therapeutic resistance. However, anoikis-related molecular signatures integrating single-cell and bulk transcriptomic data for prognostic prediction in TNBC remain insufficiently characterised. Bulk RNA-seq data from TCGA-TNBC and GSE58812, together with single-cell transcriptomic data, were analysed. Anoikis-related genes were identified by WGCNA and single-cell module scoring. A prognostic signature was constructed using Cox and LASSO regression. Immune features and immunotherapy-related indicators were evaluated, and STC2 was validated by tissue microarray, immunohistochemistry and in vitro anoikis assays. An anoikis-related gene signature (ASS1, COL18A1, STC2, DHX36, S100B and TGFBI) was established. High-risk patients exhibited poor overall survival, increased cancer-associated fibroblast infiltration and reduced T-cell infiltration. Additionally, high anoikis risk scores were associated with increased mutations frequencies of PTEN, PIK3CA and ZEB2, along with lower tumour mutation burden, microsatellite instability and PD-L1 levels. IHC staining confirmed that patients with low STC2 expression had poor prognosis. Furthermore, STC2 knockdown reduced anoikis-related apoptotic rates in an MDA-MB-231-based anoikis-mimic model in vitro. This study established an anoikis-related gene signature that may improve prognostic stratification and reflect immunotherapy-related features in TNBC.
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