A necroptosis-related prognostic model for predicting prognosis, immune landscape, and drug sensitivity in hepatocellular carcinoma based on single-cell sequencing analysis and weighted co-expression network - Li, Jingjing; Wu, Zhi; Wang, Shuchen; Li, Chan; Zhuang, Xuhui; He, Yuewen; Xu, Jianmei; Su, Meiyi; Wang, Yong; Ma, Wuhua; Fan, Dehui; Yue, Ting (Frontiers in Genetics, 2022)
Background: Hepatocellular carcinoma (HCC) is a highly lethal cancer and is the second leading cause of cancer-related deaths worldwide. Unlike apoptosis, necroptosis triggers an immune response by releasing damage-related molecular factors. However, the clinical prognostic features of necroptosis-associated genes in HCC are still not fully explored. Methods: We analyzed the single-cell datasets GSE125449 and GSE151530 from the GEO database and performed weighted co-expression network analysis on the TCGA data to identify the necroptosis genes. A prognostic model was built using COX and Lasso regression. In addition, we performed an analysis of survival, immunity microenvironment, and mutation. Furthermore, the modeled genes and pathways associated with HCC were localized within single-cell atlas. Results: Patients with HCC in the TCGA and ICGC cohorts were classified using a necroptosis-related model with significant differences in survival times between high- and low-NCPS groups. In addition, high NCPS patients expressed more immune checkpoint-related genes, suggesting immunotherapy and some chemotherapies may prove beneficial to them. In addition, a single-cell sequencing approach was conducted to investigate the expression of modeled genes and associated signaling pathways in different cell types. Conclusion: Through the analysis of single-cell and bulk multi-omics sequencing data, we constructed a prognostic model related to necroptosis and explored the relationship between high- and low-NCPS groups and immune cell infiltration in HCC. This provides a new reference for further understanding the role of necroptosis in HCC.