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Intratumoral microbial heterogeneity affected tumor immune microenvironment and determined clinical outcome of HBV-related HCC
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 IM...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10521776/ https://www.ncbi.nlm.nih.gov/pubmed/37114494 http://dx.doi.org/10.1097/HEP.0000000000000427 |
Sumario: | 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. |
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