The pyroptosis-related gene signature predicts prognosis and indicates immune activity in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) remains one of the most common malignant tumors with poor survival. Pyroptosis is a kind of programmed cell death that can regulate the proliferation, invasion, and metastasis of tumor cells. However, the expression levels of pyroptosis-related genes (PRGs) in HCC and their relationship with prognosis are still unclear. Our study identified 35 PRGs through bioinformatics analysis that were differentially expressed between tumor samples and nontumor samples. According to these differentially expressed genes, HCC patients could be divided into two groups, cluster 1 and cluster 2. The least absolute shrinkage and selection operator (LASSO) Cox regression method was performed to construct a 10-gene signature that classified HCC patients in the cancer genome atlas (TCGA) database into low-risk and high-risk groups. The results showed that the survival rate of HCC patients in the low-risk group was significantly higher than that in the high-risk group (p < 0.001). The validation cohort, the Gene Expression Omnibus (GEO) cohort, was divided into two risk groups based on the median risk score calculated by the TCGA cohort. The overall survival (OS) of the low-risk group was significantly better than that of the high-risk group (p = 0.007). Univariate and multivariate Cox regression analyses revealed that the risk score was an independent factor in predicting OS in HCC patients. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that immune-related high-risk groups were rich in genes and had reduced immune status. PRGs play a significant role in tumor immunity and have the potential capability to predict the prognosis of HCC patients.

Deng M ，Sun S ，Zhao R ，Guan R ，Zhang Z ，Li S ，Wei W ，Guo R ... -  《-》

Construction and Validation of a Prognostic Gene-Based Model for Overall Survival Prediction in Hepatocellular Carcinoma Using an Integrated Statistical and Bioinformatic Approach.

Dessie EY ，Tu SJ ，Chiang HS ，Tsai JJP ，Chang YS ，Chang JG ，Ng KL ... -  《INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES》

Screening Prognosis-Related lncRNAs Based on WGCNA to Establish a New Risk Score for Predicting Prognosis in Patients with Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) remains an important cause of cancer death. The molecular mechanism of hepatocarcinogenesis and prognostic factors of HCC have not been completely uncovered. In this study, we screened out differentially expressed lncRNAs (DE lncRNAs), miRNAs (DE miRNAs), and mRNAs (DE mRNAs) by comparing the gene expression of HCC and normal tissue in The Cancer Genome Atlas (TCGA) database. DE mRNAs were used to perform Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the miRNA and lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a competitive endogenous RNA (ceRNA) network by weighted gene coexpression network analysis (WGCNA). Moreover, univariable Cox regression and Kaplan-Meier curve analyses of DE lncRNAs and DE mRNAs were conducted. Finally, the lasso-penalized Cox regression analysis and nomogram model were used to establish a new risk scoring system and predict the prognosis of patients with liver cancer. The expression of survival-related DE lncRNAs was verified by qRT-PCR. A total of 1896 DEmRNAs, 330 DElncRNAs, and 76 DEmiRNAs were identified in HCC and normal tissue samples. Then, the turquoise miRNA and turquoise lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a ceRNA network by WGCNA. In this ceRNA network, there were 566 lncRNA-miRNA-mRNA regulatory pairs, including 30 upregulated lncRNAs, 16 downregulated miRNAs, and 75 upregulated mRNAs. Moreover, we screened out 19 lncRNAs and 14 hub mRNAs related to prognosis from this ceRNA network by univariable Cox regression and Kaplan-Meier curve analyses. Finally, a new risk scoring system was established by selecting the optimal risk lncRNAs from the 19 prognosis-related lncRNAs through lasso-penalized Cox regression analysis. In addition, we established a nomogram model consisting of independent prognostic factors to predict the survival rate of HCC patients. Finally, the correlation between the risk score and immune cell infiltration and gene set enrichment analysis were determined. In conclusion, the results may provide potential biomarkers or therapeutic targets for HCC and the establishment of the new risk scoring system and nomogram model provides the new perspective for predicting the prognosis of HCC.

Zhou X ，Dou M ，Liu Z ，Jiao D ，Li Z ，Chen J ，Li J ，Yao Y ，Li L ，Li Y ，Han X ... -  《-》

Combination of ferroptosis and pyroptosis to construct a prognostic classifier and predict immune landscape, chemotherapeutic efficacy and immunosuppressive molecules in hepatocellular carcinoma.

The induction of ferroptosis and pyroptosis has been highlighted as a novel approach to decide cancer cell fate. However, few studies have systematically explored the role of combining these two novel cell death modalities in hepatocellular carcinoma  (HCC). Ferroptosis-related genes (FRGs) and pyroptosis-related genes (PRGs) were retrieved and downloaded from FerrDb and GeneCards database, respectively. A prognostic classifier integrating with prognostic differentially expressed FRGs and PRGs was constructed by the least absolute shrinkage and selection operator (LASSO) algorithm in the TCGA-LIHC dataset and verified using the ICGC (LIRI-JP) dataset. A total of 194 differentially expressed FRGs and PRGs were identified and named as differentially expressed genes (DEGs) and, out of them 79 were found dramatically correlated with prognosis in HCC. Based on 13 key DEGs with prognostic value, a novel expression signature was constructed and used to stratify HCC patients into 2 groups. Kaplan-Meier analysis demonstrated that high-risk patients had a more dismal prognosis. Receiver operating characteristic curve (ROC) and multivariate Cox analysis confirmed its predictive power and independent characteristic. Immune profile analysis demonstrated that high-risk group had prominent upregulation of immunosuppressive cells, including macrophages, Th2_cells and Treg. The correlation analysis between this signature and immunosuppressive molecules, Immunophenoscore (IPS) and chemotherapeutic efficacy demonstrated that low-risk group had a higher  IC50 of cisplatin, mitomycin and doxorubicin and negatively related with CTLA4, HAVCR2, LAG3, PDCD1, TIGIT and ICIs treatment represented by CTLA4-/PD-1-, CTLA4 + /PD-1-, CTLA4-/PD-1 + . In this research, a novel expression signature was identified based on FRGs and PRGs in HCC, and this signature could be used to predict prognosis and select patients potentially benefiting from immunotherapies and chemotherapy.

Xu L ，Zheng Q ，Liu W 《BMC CANCER》

Pyroptosis related genes signature predicts prognosis and immune infiltration of tumor microenvironment in hepatocellular carcinoma.

Little is known on the relationship between the expression of pyroptosis related genes (PRGs) and prognosis of hepatocellular carcinoma (HCC). In this study, a specific PRGs prognostic model was developed with an aim to improve therapeutic efficiency among HCC patients. In total, 42 PRGs that were differentially expressed between HCC tissues and adjacent tissues and we exhibited the mutation frequency, classification, the location of copy number variation (CNV) alteration and the CNV variation frequency of PRGs. Two clusters were distinguished by the consensus clustering analysis based on the 42 differentially expressed genes (DEGs). There were significant differences in clinical features including T stage, grade, gender, and stage among different clusters. Kaplan-Meier curve analysis showed that cluster 1 had a better prognosis than cluster 2. The prognostic value of PRGs for survival was evaluated to construct a multigene signature using The Cancer Genome Atlas (TCGA) cohort. Based on the univariate analysis and multivariate analysis, a 10-gene signature was built and all HCC patients in the TCGA cohort were divided into low-risk group and high-risk group. HCC patients in the high-risk group showed significantly lower survival possibilities than those in the low-risk group (P < 0.001). Utilizing the median risk score from the TCGA cohort, HCC patients from International Cancer Genome Consortium (ICGC)-LIRI-JP cohort and Gene Expression Omnibus (GEO) cohort (GSE14520) were divided into two risk subgroups. The result showed that overall survival (OS) time was decreased in the high-risk group. Combined with the clinical characteristics, the risk score was an independent factor for predicting the OS of HCC patients. Then, ROC curve and survival analysis were performed to evaluate the prognostic prediction value of the model. Finally, we constructed a PRGs clinical characteristics nomogram to further predict HCC patient survival probability. There were significant differences in immune cell infiltration, GSEA enrichment pathway, IC50 of chemotherapeutics, PRGs mutation frequency between high-risk group and low-risk group. This work suggests PRGs signature played a crucial role in predicting the prognosis, infiltration of cancer microenvironment, and sensitivity of chemotherapeutic agents.

Fang G ，Zhang Q ，Fan J ，Li H ，Ding Z ，Fu J ，Wu Y ，Zeng Y ，Liu J ... -  《BMC CANCER》