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

• Published in: BMC cancer 2022-03, Vol.22 (1), p.229-229, Article 229
• Main Authors: Xu, Lijun, Zheng, Qing, Liu, Wenwen
• Format: Article
• Language: English
• Subjects: Antimitotic agents; Antineoplastic agents; Antineoplastic Agents - therapeutic use; Biomarkers, Tumor - genetics; Cancer; Carcinoma, Hepatocellular - genetics; Carcinoma, Hepatocellular - therapy; Care and treatment; Cell death; Chemotherapy; Databases, Genetic; Diagnosis; Dosage and administration; Female; Ferroptosis; Ferroptosis - genetics; Gene Expression Profiling; Health aspects; Hepatocellular carcinoma; Hepatoma; Humans; Immune profiles; Immunosuppression Therapy - methods; Immunosuppressive molecules; Kaplan-Meier Estimate; Liver Neoplasms - genetics; Liver Neoplasms - therapy; Male; Middle Aged; Overall survival; Patient outcomes; Prognosis; Proportional Hazards Models; Pyroptosis; Pyroptosis - genetics; Risk factors; ROC Curve; Treatment Outcome; Tumor Microenvironment - genetics; Tumor Microenvironment - immunology
• ISSN: 1471-2407; 1471-2407
• DOI: 10.1186/s12885-022-09301-0

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.