Analysis on heterogeneity of hepatocellular carcinoma immune cells and a molecular risk model by integration of scRNA-seq and bulk RNA-seq

• Published in: Frontiers in immunology Vol. 13; p. 1012303
• Main Authors: Liu, Xiaorui, Li, Jingjing, Wang, Qingxiang, Bai, Lu, Xing, Jiyuan, Hu, Xiaobo, Li, Shuang, Li, Qinggang
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 13.10.2022
• Subjects: autophagy; Carcinoma, Hepatocellular - pathology; hcc; Humans; Immunology; Liver Neoplasms - pathology; molecular subtypes; Nomograms; riskscore; RNA-Seq; ScRNA-seq; Single-Cell Analysis; ScRNA-seq; riskscore; molecular subtypes; hcc; autophagy
• ISSN: 1664-3224; 1664-3224
• DOI: 10.3389/fimmu.2022.1012303

Studies have shown that hepatocellular carcinoma (HCC) heterogeneity is a main cause leading to failure of treatment. Technology of single-cell sequencing (scRNA) could more accurately reveal the essential characteristics of tumor genetics. From the Gene Expression Omnibus (GEO) database, HCC scRNA-seq data were extracted. The FindCluster function was applied to analyze cell clusters. Autophagy-related genes were acquired from the MSigDB database. The ConsensusClusterPlus package was used to identify molecular subtypes. A prognostic risk model was built with the Least Absolute Shrinkage and Selection Operator (LASSO)-Cox algorithm. A nomogram including a prognostic risk model and multiple clinicopathological factors was constructed. Eleven cell clusters labeled as various cell types by immune cell markers were obtained from the combined scRNA-seq GSE149614 dataset. ssGSEA revealed that autophagy-related pathways were more enriched in malignant tumors. Two autophagy-related clusters (C1 and C2) were identified, in which C1 predicted a better survival, enhanced immune infiltration, and a higher immunotherapy response. LASSO-Cox regression established an eight-gene signature. Next, the HCCDB18, GSA14520, and GSE76427 datasets confirmed a strong risk prediction ability of the signature. Moreover, the low-risk group had enhanced immune infiltration and higher immunotherapy response. A nomogram which consisted of RiskScore and clinical features had better prediction ability. To precisely assess the prognostic risk, an eight-gene prognostic stratification signature was developed based on the heterogeneity of HCC immune cells.