Translational cancer research · 2026
Establishment and validation of a novel anoikis-related prognostic signature of lung squamous cell carcinoma.
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Wei Zhengpan, Zhang Kaishang, Li Kaiyuan, Sun Shaowu, Liu Xu, Fan Wenbo, Wang Zelong, Zhao Tianliang, Yan Tongfa, Yan Bin, Zhao Zhiqian, Zhao Qihang, Zhang Guoqing, Pan Xue, Li Xiangnan
Аннотация
BACKGROUND: Lung squamous cell carcinoma (LUSC) remains a highly lethal malignancy due to its propensity for metastasis and the limited availability of reliable prognostic biomarkers. Anoikis, a detachment-induced cell death mechanism, plays dual roles in tumor suppression and metastasis, yet its prognostic implications in LUSC are poorly characterized. This study aimed to develop an anoikis-related gene (ARG) signature for risk stratification and therapeutic exploration in LUSC.
METHODS: Transcriptomic data from The Cancer Genome Atlas (TCGA)-LUSC (n=496) and Gene Expression Omnibus (GEO) cohorts (GSE3141/GSE73403; n=121) were analyzed. Differentially expressed ARGs were identified using limma package. Prognostic genes were screened via univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression to construct a risk model. Immune infiltration was evaluated using CIBERSORT, single-sample Gene Set Enrichment Analysis (ssGSEA), and ESTIMATE. Experimental validation included CSNK2A1 knockdown in LUSC cell lines (SK-1, H226) to assess migration, invasion, and proliferation. Drug sensitivity and molecular docking were performed using oncoPredict and AutoDock Vina.
RESULTS: A total of 307 differentially expressed ARGs were identified, with 37 showing prognostic significance. Unsupervised clustering divided LUSC into two subgroups with distinct survival (P<0.001) and immune microenvironments. Cluster B exhibited higher immune and stromal scores but poorer outcomes, enriched in exhausted CD8+ T cells and M2 macrophages. A six-gene risk signature (AKT2, CSNK2A1, CD151, TDGF1, BAG4, SNAI1) stratified patients into high-/low-risk groups, validated across cohorts (5-year AUC: 0.642-0.728). High-risk patients showed sensitivity to Wee1 inhibitors (P<0.001). CSNK2A1 knockdown suppressed migration, invasion, and proliferation in vitro. A nomogram integrating risk score and T-stage improved prognostic accuracy [5-year area under the curve (AUC): 0.728].
METHODS: Transcriptomic data from The Cancer Genome Atlas (TCGA)-LUSC (n=496) and Gene Expression Omnibus (GEO) cohorts (GSE3141/GSE73403; n=121) were analyzed. Differentially expressed ARGs were identified using limma package. Prognostic genes were screened via univariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression to construct a risk model. Immune infiltration was evaluated using CIBERSORT, single-sample Gene Set Enrichment Analysis (ssGSEA), and ESTIMATE. Experimental validation included CSNK2A1 knockdown in LUSC cell lines (SK-1, H226) to assess migration, invasion, and proliferation. Drug sensitivity and molecular docking were performed using oncoPredict and AutoDock Vina.
RESULTS: A total of 307 differentially expressed ARGs were identified, with 37 showing prognostic significance. Unsupervised clustering divided LUSC into two subgroups with distinct survival (P<0.001) and immune microenvironments. Cluster B exhibited higher immune and stromal scores but poorer outcomes, enriched in exhausted CD8+ T cells and M2 macrophages. A six-gene risk signature (AKT2, CSNK2A1, CD151, TDGF1, BAG4, SNAI1) stratified patients into high-/low-risk groups, validated across cohorts (5-year AUC: 0.642-0.728). High-risk patients showed sensitivity to Wee1 inhibitors (P<0.001). CSNK2A1 knockdown suppressed migration, invasion, and proliferation in vitro. A nomogram integrating risk score and T-stage improved prognostic accuracy [5-year area under the curve (AUC): 0.728].