Objectives: Autophagy-dependent cell death (ADCD) plays a pivotal role in solid tumors, ultimately influencing immunotherapeutic efficacy and cancer prognosis. However, its significance in hepatocellular carcinoma (HCC) remains underexplored. Methods: Through integrated analysis of single-cell and bulk transcriptomic data, this research systematically identified ADCD-associated genes in LIHC. This was achieved by applying AddModuleScore, ssGSEA, and WGCNA for robust gene screening. A prognostic model was developed for LIHC grounded in The Cancer Genome Atlas (TCGA) dataset. Its validity was confirmed through internal validation with an independent TCGA cohort and external validation using GEO datasets. Immune characteristics were assessed by adopting CIBERSORT and ESTIMATE algorithms. Through LASSO-Cox regression analysis, this research established a 9-gene ADCD signature and derived the ADCD-related risk score system (ADCDRS). Results: The ADCDRS demonstrated superior prognostic performance. Aside from that, this unique system was significantly associated with clinical features, immune infiltration patterns, and the tumor’s local environment. To improve clinical applicability, this research constructed a nomogram incorporating the ADCDRS. Additionally, potential therapeutic agents targeting specific risk subgroups were identified. Conclusion: This study highlights the prognostic and therapeutic potential of ADCD-related biomarkers in LIHC.
Zhang et al. (Sun,) studied this question.
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