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

Abstract

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.

Keywords

• HCC
• multiomics
• single cell
• transcript factor
• tumor heterogeneity