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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.

SUBMITTER: Wang T

PROVIDER: S-EPMC9168757 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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

Wang Tingjie T Dang Ningxin N Tang Guangbo G Li Zihang Z Li Xiujuan X Shi Bingyin B Xu Zhong Z Li Lei L Yang Xiaofei X Xu Chuanrui C Ye Kai K

Molecular oncology 20220301 11

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 wit ...[more]

PMID: 35124891

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Project description:BackgroundDisulfidptosis is a new type of cellular death triggered in response to disulfide stress and is strongly linked to the progression of malignancies. Hepatocellular carcinoma (HCC) is a very common malignancy. Some reports have suggested a link between disulfidptosis-related genes (DRGs) and cancer; however, further research needs to be conducted.MethodsIn this study, HCC data from the Cancer Genome Atlas-Liver Hepatocellular Carcinoma and Gene Expression Omnibus data sets were collected and analyzed. A univariate Cox regression analysis, least absolute shrinkage and selection operator, and multivariate Cox regression analysis were conducted to identify the hub DRGs signature for prognosis. The HCC patients were allocated to high- and low-risk groups based on their disulfidptosis risk scores. The model was validated with a high degree of precision using both internal and external validation data sets. "ESTIMATE" and "CIBERSORT" packages were employed to assess the immunological landscapes and immune cell infiltration. The IMvigor210 cohort was chosen to validate the immunotherapy results. A drug sensitivity analysis was conducted to identify targeted medications. The expression of the hub DRGs in the HCC cells was confirmed using cytological techniques.ResultsThe bioinformatic analysis revealed that 16 genes showed differential expression. A prognostic model was developed based on four genes: RPN1, SLC2A1, SLC2A4, and SLC7A11. A notable difference in prognosis was observed between the two risk groups. Based on the results of the immune microenvironment, tumor mutation burden, immunotherapy, and drug screening analyses, the DRGs signature can be employed in HCC immunotherapy decision making. Further, the expression levels of the hub DRGs were significantly upregulated in the HCC cells.ConclusionsOur four-DRGs signature could be used to predict HCC prognosis. Further, this study showed that the hub DRGs could serve as biomarkers for immunotherapy prediction and could potentially guide targeted therapies.

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

Publications

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

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