Bulk and single‐cell transcriptome reveal the immuno‐prognostic subtypes and tumour microenvironment heterogeneity in HCC

Author:

Ji Daihan1,Lu Shuting1,Zhang Huarong1,Li Zhenli2,Wang Shenglin1,Miao Tongjie1,Jiang Zhiyu1,Ao Lu1ORCID

Affiliation:

1. Department of Bioinformatics, Fujian Key Laboratory of Medical Bioinformatics, School of Medical Technology and Engineering Fujian Medical University Fuzhou China

2. The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province Mengchao Hepatobiliary Hospital of Fujian Medical University Fuzhou China

Abstract

AbstractBackground & AimsAccumulating evidences suggest tumour microenvironment (TME) profoundly influence clinical outcome in hepatocellular carcinoma (HCC). Existing immune subtypes are susceptible to batch effects, and integrative analysis of bulk and single‐cell transcriptome is helpful to recognize immune subtypes and TME in HCC.MethodsBased on the relative expression ordering (REO) of 1259 immune‐related genes, an immuno‐prognostic signature was developed and validated in 907 HCC samples from five bulk transcriptomic cohorts, including 72 in‐house samples. The machine learning models based on subtype‐specific gene pairs with stable REOs were constructed to jointly predict immuno‐prognostic subtypes in single‐cell RNA‐seq data and validated in another single‐cell data. Then, cancer characteristics, immune landscape, underlying mechanism and therapeutic benefits between subtypes were analysed.ResultsAn immune‐related signature with 29 gene pairs stratified HCC samples individually into two risk subgroups (C1 and C2), which was an independent prognostic factor for overall survival. The machine learning models verified the immune subtypes from five bulk cohorts to two single‐cell transcriptomic data. Integrative analysis revealed that C1 had poorer outcomes, higher CNV burden and malignant scores, higher sensitivity to sorafenib, and exhibited an immunosuppressive phenotype with more regulators, e.g., myeloid‐derived suppressor cells (MDSCs), Mø_SPP1, while C2 was characterized with better outcomes, higher metabolism, more benefit from immunotherapy, and displayed active immune with more effectors, e.g., tumour infiltrating lymphocyte and dendritic cell. Moreover, both two single‐cell data revealed the crosstalk of SPP1‐related L–R pairs between cancer and immune cells, especially SPP1‐CD44, might lead to immunosuppression in C1.ConclusionsThe REO‐based immuno‐prognostic subtypes were conducive to individualized prognosis prediction and treatment options for HCC. This study paved the way for understanding TME heterogeneity between immuno‐prognostic subtypes of HCC.

Funder

Natural Science Foundation of Fujian Province

National Natural Science Foundation of China

Publisher

Wiley

Subject

Hepatology

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