1. Comprehensive analysis of immune-related prognostic genes in the tumour microenvironment of hepatocellular carcinoma
- Author
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Dongliang Wang, Caiyun Liu, Peiming Guo, Guangjun Shi, Erhong Meng, Shuai Hong, Siyao Liu, Luan Li, Chengzhen Li, Guanying Yu, Dongsheng Zhang, Xinyin Han, Weike Gao, and Lei Zhang
- Subjects
0301 basic medicine ,Oncology ,Cancer Research ,medicine.medical_specialty ,Carcinoma, Hepatocellular ,Hepatocellular carcinoma ,medicine.medical_treatment ,Prognostic ,lcsh:RC254-282 ,03 medical and health sciences ,0302 clinical medicine ,Immune system ,Surgical oncology ,Internal medicine ,Genetics ,Biomarkers, Tumor ,Tumor Microenvironment ,Medicine ,Humans ,Gene ,Chemotherapy ,business.industry ,Proportional hazards model ,Liver Neoplasms ,Immunotherapy ,Biomarker ,medicine.disease ,Prognosis ,lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,Survival Analysis ,Immune ,030104 developmental biology ,030220 oncology & carcinogenesis ,Biomarker (medicine) ,business ,Research Article - Abstract
Background The mortality rate of hepatocellular carcinoma (HCC) remains high worldwide despite surgery and chemotherapy. Immunotherapy is a promising treatment for the rapidly expanding HCC spectrum. Therefore, it is necessary to further explore the immune-related characteristics of the tumour microenvironment (TME), which plays a vital role in tumour initiation and progression. Methods In this research, 866 immune-related differentially expressed genes (DEGs) were identified by integrating the DEGs of samples from The Cancer Genome Atlas (TCGA)-HCC dataset and the immune-related genes from databases (InnateDB; ImmPort). Afterwards, 144 candidate prognostic genes were defined through weighted gene co-expression network analysis (WGCNA). Results Seven immune-related prognostic DEGs were identified using the L1-penalized least absolute shrinkage and selection operator (LASSO) Cox proportional hazards (PH) model, and the ImmuneRiskScore model was constructed on this basis. The prognostic index of the ImmuneRiskScore model was then validated in the relevant dataset. Patients were divided into high- and low-risk groups according to the ImmuneRiskScore. Differences in the immune cell infiltration of patients with different ImmuneRiskScore values were clarified, and the correlation of immune cell infiltration with immunotherapy biomarkers was further explored. Conclusion The ImmuneRiskScore of HCC could be a prognostic marker and can reflect the immune characteristics of the TME. Furthermore, it provides a potential biomarker for predicting the response to immunotherapy in HCC patients.
- Published
- 2021