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Single-cell transcriptome analysis identifies novel biomarkers involved in major liver cancer subtypes

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Abstract

Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the two aggressive subtypes of liver cancer (LC). Immense cellular heterogeneity and cross-talk between cancer and healthy cells make it challenging to treat these cancer subtypes. To address these challenges, the study aims to systematically characterize the tumor heterogeneity of LC subtypes using single-cell RNA sequencing (scRNA-seq) datasets. The study combined 51,927 single cells from HCC, ICC, and healthy scRNA-seq datasets. After integrating the datasets, cell groups with similar gene expression patterns are clustered and cluster annotation has been performed based on gene markers. Cell-cell communication analysis (CCA) was implemented to understand the cross-talk between various cell types. Further, differential gene expression analysis and enrichment analysis were carried out to identify unique molecular drivers associated with HCC and ICC. Our analysis identified T cells, hepatocytes, epithelial cells, and monocyte as the major cell types present in the tumor microenvironment. Among them, abundance of natural killer (NK) cells in HCC, epithelial cells, and hepatocytes in ICC was detected. CCA revealed key interaction between T cells to NK cells in HCC and smooth muscle cells to epithelial cells in the ICC. Additionally, SOX4 and DTHD1 are the top differentially expressed genes (DEGs) in HCC, while keratin and CCL4 are in ICC. Enrichment analysis of DEGs reveals major upregulated genes in HCC affect protein folding mechanism and in ICC alter pathways involved in cell adhesion. The findings suggest potential targets for the development of novel therapeutic strategies for the treatment of these two aggressive subtypes of LC.

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Data availability

All the data used in the study can be accessed from NCBI GEO. The integrated object and the whole script can be obtained from https://github.com/swainasish/liver_cancer_subtype.

Abbreviations

LC:

Liver cancer

HCC:

Hepatocellular carcinoma

ICC:

Intrahepatic cholangiocarcinoma

TME:

Tumor microenvironment

IntD:

Integrated dataset

scRNA-seq:

Single-cell RNA sequencing

CCA:

Cell-cell communication analysis

DEG:

Differentially expressed gene

PCA:

Principal component analysis

KNN:

K-nearest neighbor

SNN:

Shared nearest neighbor

NK cells:

Natural killer cells

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Acknowledgements

GEO is acknowledged for providing publicly accessible datasets.

Funding

This project was supported by the seed grant (project number I/SEED/PY/20200037) funded by Indian Institute of Technology, Jodhpur and returning expert grant (S/GIZ/PY/20220140) funded by Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH. 

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Authors and Affiliations

  1. Department of Bioscience & Bioengineering, Indian Institute of Technology, Jodhpur, Rajasthan, 342030, India

    Asish Kumar Swain, Prashant Pandey, Riddhi Sera & Pankaj Yadav

  2. School of Artificial Intelligence and Data Science, Indian Institute of Technology, Jodhpur, Rajasthan, 342030, India

    Pankaj Yadav

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  1. Asish Kumar Swain
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  2. Prashant Pandey
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  3. Riddhi Sera
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  4. Pankaj Yadav
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Contributions

AKS, PP, and RS performed the data analyses; PY designed and supervised the study; AKS, PP, and PY wrote the first manuscript draft; all authors contributed by comments and approved the final manuscript.

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Correspondence to Pankaj Yadav.

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Swain, A.K., Pandey, P., Sera, R. et al. Single-cell transcriptome analysis identifies novel biomarkers involved in major liver cancer subtypes. Funct Integr Genomics 23, 235 (2023). https://doi.org/10.1007/s10142-023-01156-3

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