A multi‐omics‐based investigation of the immunological and prognostic impact of necroptosis‐related genes in patients with hepatocellular carcinoma

Abstract

Background Hepatocellular carcinoma (HCC) is the most common histological subtype of liver cancer and the third leading cause of death from cancer globally. Recent studies suggested cell death is also a key regulator of tumour progression. The purpose of this study was to generate a new predictive signature for HCC patients based on a complete analysis of necroptosis‐associated genes. Methods We extracted the mRNA expression profiles of HCC patients from the TCGA and ICGC databases and their clinical data. In addition, we used the IMvigor210 cohort to validate our model molecule's ability to predict the effect of immunotherapy. In the TCGA cohort, a seven‐gene risk‐prognostic model was constructed using univariate cox‐Lasoo regression. External validation was conducted using the ICGC cohort. The ssGSEA algorithm is used to determine the degree of immune function response. The CMAP databases are used for chemotherapy drug analysis and screening for drugs that reduce the expression of high‐risk genes. The cbioportal database was used to explore mutations in model genes. Results Survival analysis shows shorter survival for high‐risk patients. Immune function analysis revealed significant differences in the activity of immune pathways between risk subgroups. Varied risk scores result in dramatically diverse immune infiltration and tumour growth, as well as significantly different chemotherapeutic sensitivity. In addition, Apigenin and LY‐294002 reduced the expression of high‐risk genes, while Arecoline had the opposite effect. In the immunotherapy IMvigor210 cohort, risk scores were significantly different between the objective responder and non‐responder groups. By comparing the models constructed with published literature, it is suggested that our model has better predictive power. Conclusions We created a new prognostic signature of necroptosis‐related genes that can be used as potential prognostic biomarkers to guide effective personalized therapy for hepatocellular carcinoma patients.

Cuproptosis-Related Signature Predicts the Prognosis, Tumor Microenvironment, and Drug Sensitivity of Hepatocellular Carcinoma

“…Previous studies have constructed signatures associated with other cell death formats based on the TCGA-LIHC project. Yang and Jiang constructed a necroptosis-related signature with necroptosisrelated genes, and the 1-and 3-year AUC values were 0.741 and 0.648, respectively [53]. Wu et al constructed a pyroptosis-related signature with pyroptosis-related genes, and the 1-and 3-year AUC values were 0.785 and 0.71 [54], respectively, while 0.760 and 0.708 in a pyroptosisrelated long noncoding RNAs (lncRNAs) signature [55].…”

A necroptosis -related signature for predicting prognosis and immunotherapy in hepatocellular carcinoma

“…We also developed an NRG-related signature to predict OS in HCC, which is better than clinicopathology. Compared with NRGs related signatures for HCC which have been published (Li et al, 2022;Yang and Jiang, 2022), our signature had a better prognostic performance (Supplementary Figure S7). Most NRGs presented in our signature were associated with tumorigenesis and proliferation of HCC.…”

Relationships of Cuproptosis-Related Genes With Clinical Outcomes and the Tumour Immune Microenvironment in Hepatocellular Carcinoma

“…RCD-based HCC subtype and/or prognostic models are becoming a research hotspot for predicting HCC prognosis. Growing evidence suggests that prognostic models based on next-generation sequencing and public databases provide more comprehensive clinical-genetic prognostic value [ 41 , 42 , 43 ]. The role including clinical relevance and prognostic significance of CRGs in HCC is unknown.…”