Intratumoral microbial heterogeneity affected tumor immune microenvironment and determined clinical outcome of HBV-related HCC

Abstract

Background and aims: The intratumoral microbiome has been reported to regulate the development and progression of cancers. We aimed to characterize intratumoral microbial heterogeneity (IMH) and establish microbiome-based molecular subtyping of HBV-related HCC to elucidate the correlation between IMH and HCC tumorigenesis.

Approach and results: A case-control study was designed to investigate microbial landscape and characteristic microbial signatures of HBV-related HCC tissues adopting metagenomics next-generation sequencing. Microbiome-based molecular subtyping of HCC tissues was established by nonmetric multidimensional scaling. The tumor immune microenvironment of 2 molecular subtypes was characterized by EPIC and CIBERSORT based on RNA-seq and verified by immunohistochemistry. The gene set variation analysis was adopted to explore the crosstalk between the immune and metabolism microenvironment. A prognosis-related gene risk signature between 2 subtypes was constructed by the weighted gene coexpression network analysis and the Cox regression analysis and then verified by the Kaplan-Meier survival curve.IMH demonstrated in HBV-related HCC tissues was comparably lower than that in chronic hepatitis tissues. Two microbiome-based HCC molecular subtypes, defined as bacteria- and virus-dominant subtypes, were established and significantly correlated with discrepant clinical-pathologic features. Higher infiltration of M2 macrophage was detected in the bacteria-dominant subtype with to the virus-dominant subtype, accompanied by multiple upregulated metabolism pathways. Furthermore, a 3-gene risk signature containing CSAG4 , PIP4P2 , and TOMM5 was filtered out, which could predict the clinical prognosis of HCC patients accurately using the Cancer Genome Atlas data.

Conclusions: Microbiome-based molecular subtyping demonstrated IMH of HBV-related HCC was correlated with a disparity in clinical-pathologic features and tumor microenvironment (TME), which might be proposed as a biomarker for prognosis prediction of HCC.