Identification and validation a costimulatory molecule gene signature to predict the prognosis and immunotherapy response for hepatocellular carcinoma

Cancer Cell International

Jingyi Liu¹  Fangfang Yang²  Shuoyi Ma²  Yinan Hu²  Jiahao Yu²  Jingbo Wang²  Xia Zhou²  Ying Han²  Miao Zhang²  Yansheng Liu² 

[1] Department of Radiation Oncology, Xijing Hospital, Air Force Medical University;Institute of Digestive Diseases, Xijing Hospital, Air Force Medical University;

关键词: Hepatocellular carcinoma;    Costimulatory molecule;    Prognostic signature;    ssGSEA;    IPS;   

DOI  :  10.1186/s12935-022-02514-0

来源: DOAJ

【 摘 要 】

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. Costimulatory molecules have been proven to be the foundation of immunotherapy. However, the potential roles of costimulatory molecule genes (CMGs) in HCC remain unclear. Our study is aimed to develop a costimulatory molecule-related gene signature that could evaluate the prognosis of HCC patients. Methods Based on The Cancer Gene Atlas (TCGA) database, univariate Cox regression analysis was applied in CMGs to identify prognosis-related CMGs. Consensus clustering analysis was performed to stratify HCC patients into different subtypes and compared them in OS. Subsequently, the LASSO Cox regression analysis was performed to construct the CMGs-related prognostic signature and Kaplan–Meier survival curves as well as ROC curve were used to validate the predictive capability. Then we explored the correlations of the risk signature with tumor-infiltrating immune cells, tumor mutation burden (TMB) and response to immunotherapy. The expression levels of prognosis-related CMGs were validated based on qRT-PCR and Human Protein Atlas (HPA) databases. Results All HCC patients were classified into two clusters based on 11 CMGs with prognosis values and cluster 2 correlated with a poorer prognosis. Next, a prognostic signature of six CMGs was constructed, which was an independent risk factor for HCC patients. Patients with low-risk score were associated with better prognosis. The correlation analysis showed that the risk signature could predict the infiltration of immune cells and immune status of the immune microenvironment in HCC. The qRT-PCR and immunohistochemical results indicated six CMGs with differential expression in HCC tissues and normal tissues. Conclusion In conclusion, our CMGs-related risk signature could be used as a prediction tool in survival assessment and immunotherapy for HCC patients.

【 授权许可】

Unknown