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Review
. 2022;14(3):513-525.
doi: 10.1016/j.jcmgh.2022.04.014. Epub 2022 May 14.

Single-Cell Transcriptomics of Liver Cancer: Hype or Insights?

Qing-Yang Zhang  1 , Daniel Wai-Hung Ho  1 , Yu-Man Tsui  1 , Irene Oi-Lin Ng  2
Affiliations
Review

Single-Cell Transcriptomics of Liver Cancer: Hype or Insights?

Qing-Yang Zhang et al. Cell Mol Gastroenterol Hepatol. 2022.

Abstract

Hepatocellular carcinoma (HCC) is characterized by its high degrees of both inter- and intratumoral heterogeneity. Its complex tumor microenvironment is also crucial in promoting tumor progression. Recent advances in single-cell RNA sequencing provide an important highway to characterize the underlying pathogenesis and heterogeneity of HCC in an unprecedented degree of resolution. This review discusses the up-to-date discoveries from the latest studies of HCC with respect to the strength of single-cell RNA sequencing. We discuss its use in the dissection of the landscape of the intricate HCC ecosystem and highlight the major features at cellular levels, including the malignant cells, different immune cell types, and the various cell-cell interactions, which are crucial for developing effective immunotherapies. Finally, its translational applications will be discussed. Altogether, these explorations may give us some hints at the tumor growth and progression and drug resistance and recurrence, particularly in this era of personalized medicine.

Keywords: Hepatocellular Carcinoma; Immune Tumor Microenvironment; Single-Cell RNA-Sequencing.

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Figures

Figure 1
Figure 1
Comparison of scRNA-seq and bulk RNA-seq.
Figure 2
Figure 2
Experimental workflow of scRNA-seq on clinical HCC tissue samples using microfluidics platform.
Figure 3
Figure 3
Applications of scRNA-seq technique on HCC. An overview of the current main research capabilities for scRNA-seq data is shown. A wide variety of aspects can be reached through scientific analyses, including (A) depicting the single-cell profiles of HCC, (B) distinguishing the disease-specific population, (C) interpreting cell-cell communication across intricate tumor microenvironment, (D) identifying the key transcriptional factors and their regulatory networks, (E) reconstructing the lineage trajectory, (F) capturing the cancer stem cell population and exploring its potential applications in treatment, and (G) deciphering the differential expression genes on particular cell types or subsets.
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