Integrating bulk and single‐cell RNA sequencing reveals cellular heterogeneity and immune infiltration in hepatocellular carcinoma

• Published in: Molecular oncology Vol. 16; no. 11; pp. 2195 - 2213
• Main Authors: Wang, Tingjie, Dang, Ningxin, Tang, Guangbo, Li, Zihang, Li, Xiujuan, Shi, Bingyin, Xu, Zhong, Li, Lei, Yang, Xiaofei, Xu, Chuanrui, Ye, Kai
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.06.2022; John Wiley and Sons Inc; Wiley
• Subjects: Apoptosis; Cholangiocarcinoma; Consortia; Cytotoxicity; Datasets; Gene expression; Genomes; HCC; Hepatocellular carcinoma; Immunotherapy; Ligands; Liver cancer; Lymphocytes; Lymphocytes T; Macrophages; Metastases; multiomics; Mutation; Proteins; single cell; Software; transcript factor; Transcription factors; tumor heterogeneity; Tumor microenvironment; Tumors; HCC; single cell; multiomics; transcript factor; tumor heterogeneity
• ISSN: 1574-7891; 1878-0261
• DOI: 10.1002/1878-0261.13190

Efficacy of immunotherapy in hepatocellular carcinoma (HCC) is blocked by its high degree of inter‐ and intra‐tumor heterogeneity and immunosuppressive tumor microenvironment. However, the correlation between tumor heterogeneity and immunosuppressive microenvironment in HCC has not been well addressed. Here, we endeavored to dissect inter‐ and intra‐tumor heterogeneity in HCC and uncover how they contribute to the immunosuppressive microenvironment. We performed consensus molecular subtyping with non‐negative matrix factorization (NMF) clustering to stratify the inter‐heterogeneity profile of HCC tumors. We grouped HCC tumors from the Cancer Genome Atlas (TCGA) patients into three subtypes (S1, S2 and S3), where S1 was characterized as a ‘hot tumor’ profile with high expression level of T cell genes and rate of immune scores. S2 was characterized as a ‘cold tumor’ profile with the highest tumor purity score, and S3 as an ‘immunosuppressed tumor’ profile with the poorest prognosis and a high expression level of immunosuppressive genes such as cytotoxic T‐lymphocyte‐associated protein‐4, TIGIT, and PDCD1. Moreover, we combined weighted gene co‐expression network analysis and single‐cell regulatory network inference and clustering (SCENIC) in the single‐cell dataset of the S3‐like subtype (CS3) and identified a transcription factor, BATF, which could upregulate immunosuppressive genes. Finally, we identified a cell interaction network in which a myeloid‐derived suppressor cell‐like macrophage subtype could promote the formation of immunosuppressive T‐cells. By integrating bulk and single‐cell RNA sequencing in this study, we defined a 108‐gene classifier and investigated cellular heterogeneity, as well as immune infiltration in hepatocellular carcinoma (HCC). Patients with a high level of cytotoxic T‐lymphocyte‐associated protein‐4, TIGIT and LAG3 showed the poorest prognosis in both the Cancer Genome Atlas and International Cancer Genome Consortium cohorts. Additionally, single‐cell RNA sequencing analysis revealed high expression levels of these immunosuppressive genes and poor patient survival within the CS3 cluster. Our research indicated that BATF could be regulating the expression of immunosuppressive genes in HCC.