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

2022; Elsevier BV; Volume: 14; Issue: 3 Linguagem: Inglês

10.1016/j.jcmgh.2022.04.014

2352-345X

Qingyang Zhang, Daniel Wai‐Hung Ho, Yu‐Man Tsui, Irene Oi‐Lin Ng,

Cancer Immunotherapy and Biomarkers

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. 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. SummarySingle-cell RNA-sequencing (scRNA-seq) provides a cutting-edge method to better understand the heterogeneity of the hepatocellular carcinoma microenvironment by capturing the whole transcription expression of thousands of various individual cells. This review summarizes and discusses the latest achievements on hepatocellular carcinoma via scRNA-seq. Insights from scRNA-seq analysis would help advance prospective studies for personalized medicine and targeted therapy. Single-cell RNA-sequencing (scRNA-seq) provides a cutting-edge method to better understand the heterogeneity of the hepatocellular carcinoma microenvironment by capturing the whole transcription expression of thousands of various individual cells. This review summarizes and discusses the latest achievements on hepatocellular carcinoma via scRNA-seq. Insights from scRNA-seq analysis would help advance prospective studies for personalized medicine and targeted therapy. Hepatocellular carcinoma (HCC) is the major form of primary liver cancer and constitutes >85% of the cases.1El-Serag H.B. Rudolph K.L. Hepatocellular carcinoma: epidemiology and molecular carcinogenesis.Gastroenterology. 2007; 132: 2557-2576Abstract Full Text Full Text PDF PubMed Scopus (4440) Google Scholar Despite continuing efforts in the investigation of its pathogenesis, the current understanding remains far from adequate, largely owing to its extremely heterogeneous composition. Regarding the cancer cells, liver cancer stem cells (CSCs) constitute subtle but substantial fractions and are believed to exert adverse effects leading to refractory disease and metastasis. Many lines of evidence have indicated the complex involvement of tumor microenvironment (TME), particularly the immune cells, as well as their crosstalk in HCC.2Ho D.W.H. Tsui Y.M. Chan L.K. Sze K.M.F. Zhang X. Cheu J.W.S. Chiu Y.T. Lee J.M.F. Chan A.C.Y. Cheung E.T.Y. Yau D.T.W. Chia N.H. Lo I.L.O. Sham P.C. Cheung T.T. Wong C.C.L. Ng I.O.L. Single-cell RNA sequencing shows the immunosuppressive landscape and tumor heterogeneity of HBV-associated hepatocellular carcinoma.Nat Commun. 2021; 12: 3684Crossref PubMed Scopus (50) Google Scholar,3Sun Y. Wu L. Zhong Y. Zhou K. Hou Y. Wang Z. Zhang Z. Xie J. Wang C. Chen D. Huang Y. Wei X. Shi Y. Zhao Z. Li Y. Guo Z. Yu Q. Xu L. Volpe G. Qiu S. Zhou J. Ward C. Sun H. Yin Y. Xu X. Wang X. Esteban M.A. Yang H. Wang J. Dean M. Zhang Y. Liu S. Yang X. Fan J. Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma.Cell. 2021; 184: 404-421.e16Abstract Full Text Full Text PDF PubMed Scopus (151) Google Scholar The immune cells in the TME play a pivotal role in tumor immunosuppression. In this review, we (1) give an overview of the single-cell RNA sequencing (scRNA-seq) platforms and procedures; (2) summarize scRNA-seq use and the latest insights from such studies in HCC, ranging from the HCC cell population and the intricate immune ecosystem in the TME to cell-cell interaction; and (3) discuss scRNA-seq translational applications. Nowadays, RNA-seq is a widely adopted profiling strategy to interrogate the whole transcriptome of tens of thousands of genes. Nevertheless, the traditional "bulk-cell" RNA-seq approach suffers from mixing and adding up data from multiple cells, which inevitably masks the signals from individual cells, particularly the less abundant cell types. This is especially problematic for studying HCC, which is highly heterogeneous and composed of a rich content of malignant cells, immune cells, and stromal cells in the TME. Despite the fact that the cellular deconvolution algorithms provide computational estimation on cell type composition based on bulk-cell data,4Avila Cobos F. Alquicira-Hernandez J. Powell J.E. Mestdagh P. De Preter K. Benchmarking of cell type deconvolution pipelines for transcriptomics data.Nat Commun. 2020; 11: 5650Crossref PubMed Scopus (79) Google Scholar,5Jin H. Liu Z. A benchmark for RNA-seq deconvolution analysis under dynamic testing environments.Genome Biol. 2021; 22: 102Crossref PubMed Scopus (17) Google Scholar they still have fundamental limitations (eg, use of inappropriate reference or lack of suitable reference). In contrast, scRNA-seq overcomes the major limitations of bulk-cell approach (Figure 1). It allows us to differentiate cell types and analyze the heterogeneous characteristics, including the biological functions of different cell subpopulations and their possible interactions, and helps better understanding of the cellular and molecular regulatory mechanisms within the tumor ecosystem. scRNA-seq begins with single-cell capture, followed by conversion of RNA into complementary DNA, amplification, and library preparation (Figure 2). Regarding single-cell capture, there are different ways ranging from manual to microfluidic handling.6Svensson V. Vento-Tormo R. Teichmann S.A. Exponential scaling of single-cell RNA-seq in the past decade.Nat Protoc. 2018; 13: 599-604Crossref PubMed Scopus (388) Google Scholar Importantly, they differ in terms of their handling capacity and the number of genes that they can typically detect. There are currently 2 most frequently used platforms, utilizing plate-based (eg, Smart-seq2)7Picelli S. Bjorklund A.K. Faridani O.R. Sagasser S. Winberg G. Sandberg R. Smart-seq2 for sensitive full-length transcriptome profiling in single cells.Nat Methods. 2013; 10: 1096-1098Crossref PubMed Scopus (1265) Google Scholar and droplet-based (eg, 10X Genomics Chromium platforms [10X Genomics, Pleasanton, CA]) single-cell capture. In general, the plate-based platform sequences full-length transcripts and detects more genes per cell. This is particularly useful in targeting low-abundance transcripts and identifying alternative splicing events. Also, it is less limited by cell size. However, the number of cells analyzed is lower. On the other hand, the droplet-based platform has far greater throughput of experiment and can capture cells in the scale of thousands to even tens of thousands of cells. It is therefore particularly powerful to investigate the cellular landscapes and detect rare cell types or subclones of cells. However, it comes with a cost of providing sequencing information of only short intervals at either the 5′ or 3′ end of a gene, and there are also more frequent occurrences of dropout events for low-expression genes.8Wang X. He Y. Zhang Q. Ren X. Zhang Z. Direct comparative analyses of 10X Genomics Chromium and Smart-seq2.Genomics Proteomics Bioinformatics. 2021; 19: 253-266Crossref PubMed Scopus (54) Google Scholar Besides, its utility is sometimes limited by the fluidic tube diameter inside the system that poses an upper limit to the size of the cells that can be studied. The cell suspension must be ensured to contain single cells free of doublets and clumps beforehand, and this will rely very much on the efficiency of the tissue digestion process, the removal of undigested cell clumps, and the single-cell enrichment process such as using fluorescence-activated cell sorting (FACS). Overall, because cell viability of different subpopulations may be differently affected by the previously mentioned processes (eg, immune cells have higher viability, while hepatocytes are very fragile), investigators must keep in mind whether some cell types will be over- or underrepresented when analyzing the final single-cell sequencing dataset.9Kuksin M. Morel D. Aglave M. Danlos F.X. Marabelle A. Zinovyev A. Gautheret D. Verlingue L. Applications of single-cell and bulk RNA sequencing in onco-immunology.Eur J Cancer. 2021; 149: 193-210Abstract Full Text Full Text PDF PubMed Scopus (20) Google Scholar To obtain single-cell suspension, the tissues under study are usually dissociated by physical homogenization and enzymatic digestion at 37°C for certain duration of time to help release the single cells from the tissues. Any undigested tissue debris is filtered away by cell strainer of certain pore sizes (eg, 100 μm). To further remove clumps of cells, stepwise filtration using cell strainer of gradually decreasing pore sizes is recommended. On the other hand, for peripheral blood mononuclear cells, they can be easily harvested by collecting the buffy coat layer upon the use of Ficoll isolation protocol. Viability of cells and number of live cells available can then be determined by trypan blue staining. Depending on the cell types of the target populations to be investigated, FACS or magnetic-activated cell sorting can be used to enrich the particular cell type population according to the different cell surface markers recognized by the respective antibodies conjugated to the appropriate fluorophore or magnetic beads, respectively (eg, CD45 positivity for immune cells, CD45 negativity for nonimmune cells). FACS provides added advantage of eliminating doublets by proper gating of forward or side scatter signals, and dead cells by cell viability dye. Furthermore, our experience shows that subpopulations of different cell types will have their viability affected differently by the previous sample preparation processes. For instance, myeloid cells in peripheral blood mononuclear cells usually exist as single cells with high viability, thus sparing the need for FACS into single cells. On the other hand, cells in cancer tissues are subjected to the dissociation process and FACS, which inevitably creates some stress and poses adverse effects on their viability. Besides, whether cell type enrichment processes, such as FACS or magnetic-activated cell sorting for particular cell type populations, are included before scRNA-seq, may affect the distribution of different cell types, such as tumor-infiltrating myeloid cells and lymphoid cells, HCC cells and other nonmalignant stromal cells, in the samples under examination. After collecting sufficient cells of the enriched cell types, the cell suspension with single cells can be subjected to single-cell capture process. To date, the scRNA-seq technique has been increasing adopted in HCC investigation. The previous reports are summarized in Table 1.2Ho D.W.H. Tsui Y.M. Chan L.K. Sze K.M.F. Zhang X. Cheu J.W.S. Chiu Y.T. Lee J.M.F. Chan A.C.Y. Cheung E.T.Y. Yau D.T.W. Chia N.H. Lo I.L.O. Sham P.C. Cheung T.T. Wong C.C.L. Ng I.O.L. Single-cell RNA sequencing shows the immunosuppressive landscape and tumor heterogeneity of HBV-associated hepatocellular carcinoma.Nat Commun. 2021; 12: 3684Crossref PubMed Scopus (50) Google Scholar,3Sun Y. Wu L. Zhong Y. Zhou K. Hou Y. Wang Z. Zhang Z. Xie J. Wang C. Chen D. Huang Y. Wei X. Shi Y. Zhao Z. Li Y. Guo Z. Yu Q. Xu L. Volpe G. Qiu S. Zhou J. Ward C. Sun H. Yin Y. Xu X. Wang X. Esteban M.A. Yang H. Wang J. Dean M. Zhang Y. Liu S. Yang X. Fan J. Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma.Cell. 2021; 184: 404-421.e16Abstract Full Text Full Text PDF PubMed Scopus (151) Google Scholar,10Zheng H. Pomyen Y. Hernandez M.O. Li C. Livak F. Tang W. Dang H. Greten T.F. Davis J.L. Zhao Y. Mehta M. Levin Y. Shetty J. Tran B. Budhu A. Wang X.W. Single-cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma.Hepatology. 2018; 68: 127-140Crossref PubMed Scopus (164) Google Scholar, 11Lim C.J. Lee Y.H. Pan L. Lai L.Y. Chua C. Wasser M. Lim T.K.H. Yeong J. Toh H.C. Lee S.Y. Chan C.Y. Goh B.K.P. Chung A. Heikenwalder M. Ng I.O.L. Chow P. Albani S. Chew V. Multidimensional analyses reveal distinct immune microenvironment in hepatitis B virus-related hepatocellular carcinoma.Gut. 2019; 68: 916-927Crossref PubMed Scopus (150) Google Scholar, 12Ho D.W.H. Tsui Y.M. Sze K.M.F. Chan L.K. Cheung T.T. Lee E. Sham P.C. Tsui S.K.W. Lee T.K.W. Ng I.O.L. Single-cell transcriptomics reveals the landscape of intra-tumoral heterogeneity and sternness-related subpopulations in liver cancer.Cancer Lett. 2019; 459: 176-185Crossref PubMed Scopus (74) Google Scholar, 13Losic B. Craig A.J. Villacorta-Martin C. Martins S.N. Akers N. Chen X.T. Ahsen M.E. von Felden J. Labgaa I. D'Avola D. Allette K. Lira S.A. Furtado G.C. Garcia-Lezana T. Restrepo P. Stueck A. Ward S.C. Fiel M.I. Hiotis S.P. Gunasekaran G. Sia D. Schadt E.E. Sebra R. Schwartz M. Llovet J.M. Thung S. Stolovitzky G. Villanueva A. Intratumoral heterogeneity and clonal evolution in liver cancer.Nat Commun. 2020; 11: 291Crossref PubMed Scopus (150) Google Scholar, 14Song G.H. Shi Y. Zhang M.Y. Goswami S. Afridi S. Meng L. Ma J.Q. Chen Y. Lin Y.P. Zhang J. Liu Y.M. Jin Z.J. Yang S.X. Rao D.N. Zhang S. Ke A.W. Wang X.Y. Cao Y. Zhou J. Fan J. Zhang X.M. Xi R.B. Gao Q. Global immune characterization of HBV/HCV-related hepatocellular carcinoma identifies macrophage and T-cell subsets associated with disease progression.Cell Discov. 2020; 6: 90Crossref PubMed Scopus (40) Google Scholar, 15Sun Y.F. Wu L. Liu S.P. Jiang M.M. Hu B. Zhou K.Q. Guo W. Xu Y. Zhong Y. Zhou X.R. Zhang Z.F. Liu G. Liu S. Shi Y.H. Ji Y. Du M. Li N.N. Li G.B. Zhao Z.K. Huang X.Y. Xu L.Q. Yu Q.C. Peng D.H. Qiu S.J. Sun H.C. Dean M. Wang X.D. Chung W.Y. Dennison A.R. Zhou J. Hou Y. Fan J. Yang X.R. Dissecting spatial heterogeneity and the immune-evasion mechanism of CTCs by single-cell RNA-seq in hepatocellular carcinoma.Nat Commun. 2021; 12: 4091Crossref PubMed Scopus (35) Google Scholar, 16Chen V.L. Huang Q. Harouaka R. Du Y. Lok A.S. Parikh N.D. Garmire L.X. Wicha M.S. A dual-filtration system for single-cell sequencing of circulating tumor cells and clusters in HCC.Hepatol Commun. 2022 Jan 23; ([E-pub ahead of print])Crossref Scopus (1) Google Scholar, 17Juhling F. Saviano A. Ponsolles C. Heydmann L. Crouchet E. Durand S.C. El Saghire H. Felli E. Lindner V. Pessaux P. Pochet N. Schuster C. Verrier E.R. Baumert T.F. Hepatitis B virus compartmentalization and single-cell differentiation in hepatocellular carcinoma.Life Sci Alliance. 2021; 4e202101036Crossref PubMed Google Scholar, 18Liang J. Chen W. Ye J. Ni C. Zhai W. Single-cell transcriptomics analysis reveals intratumoral heterogeneity and identifies a gene signature associated with prognosis of hepatocellular carcinoma.Biosci Rep. 2022; 42BSR20212560Crossref Scopus (3) Google Scholar, 19Guan X. Wu Y. Zhang S. Liu Z. Fan Q. Fang S. Qiao S. Sun F. Liang C. Activation of FcRn mediates a primary resistance response to sorafenib in hepatocellular carcinoma by single-cell RNA sequencing.Front Pharmacol. 2021; 12709343Crossref Scopus (3) Google Scholar, 20Guan Y. Chen X. Wu M. Zhu W. Arslan A. Takeda S. Nguyen M.H. Majeti R. Thomas D. Zheng M. Peltz G. The phosphatidylethanolamine biosynthesis pathway provides a new target for cancer chemotherapy.J Hepatol. 2020; 72: 746-760Abstract Full Text Full Text PDF PubMed Scopus (19) Google Scholar, 21Vong J.S.L. Ji L. Heung M.M.S. Cheng S.H. Wong J. Lai P.B.S. Wong V.W.S. Chan S.L. Chan H.L.Y. Jiang P. Chan K.C.A. Chiu R.W.K. Lo Y.M.D. Single cell and plasma RNA sequencing for RNA liquid biopsy for hepatocellular carcinoma.Clin Chem. 2021; 67: 1492-1502Crossref PubMed Scopus (5) Google Scholar, 22Dong X. Wang F. Liu C. Ling J. Jia X. Shen F. Yang N. Zhu S. Zhong L. Li Q. Single-cell analysis reveals the intra-tumor heterogeneity and identifies MLXIPL as a biomarker in the cellular trajectory of hepatocellular carcinoma.Cell Death Discov. 2021; 7: 14Crossref PubMed Scopus (12) Google Scholar, 23Chen W.S. Liang Y. Zong M. Liu J.J. Kaneko K. Hanley K.L. Zhang K. Feng G.S. Single-cell transcriptomics reveals opposing roles of Shp2 in Myc-driven liver tumor cells and microenvironment.Cell Rep. 2021; 37109974Abstract Full Text Full Text PDF Scopus (9) Google Scholar, 24Ma L. Wang L. Khatib S.A. Chang C.W. Heinrich S. Dominguez D.A. Forgues M. Candia J. Hernandez M.O. Kelly M. Zhao Y. Tran B. Hernandez J.M. Davis J.L. Kleiner D.E. Wood B.J. Greten T.F. Wang X.W. Single-cell atlas of tumor cell evolution in response to therapy in hepatocellular carcinoma and intrahepatic cholangiocarcinoma.J Hepatol. 2021; 75: 1397-1408Abstract Full Text Full Text PDF PubMed Scopus (42) Google Scholar, 25Zheng B. Wang D. Qiu X. Luo G. Wu T. Yang S. Li Z. Zhu Y. Wang S. Wu R. Sui C. Gu Z. Shen S. Jeong S. Wu X. Gu J. Wang H. Chen L. Trajectory and functional analysis of PD-1(high) CD4(+)CD8(+) T cells in hepatocellular carcinoma by single-cell cytometry and transcriptome sequencing.Adv Sci (Weinh). 2020; 72000224Google Scholar, 26Zheng C. Zheng L. Yoo J.K. Guo H. Zhang Y. Guo X. Kang B. Hu R. Huang J.Y. Zhang Q. Liu Z. Dong M. Hu X. Ouyang W. Peng J. Zhang Z. Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing.Cell. 2017; 169: 1342-1356.e16Abstract Full Text Full Text PDF PubMed Scopus (991) Google Scholar, 27Zhang Q. He Y. Luo N. Patel S.J. Han Y. Gao R. Modak M. Carotta S. Haslinger C. Kind D. Peet G.W. Zhong G. Lu S. Zhu W. Mao Y. Xiao M. Bergmann M. Hu X. Kerkar S.P. Vogt A.B. Pflanz S. Liu K. Peng J. Ren X. Zhang Z. Landscape and dynamics of single immune cells in hepatocellular carcinoma.Cell. 2019; 179: 829-845.e20Abstract Full Text Full Text PDF PubMed Scopus (479) Google Scholar, 28Ma L. Hernandez M.O. Zhao Y. Mehta M. Tran B. Kelly M. Rae Z. Hernandez J.M. Davis J.L. Martin S.P. Kleiner D.E. Hewitt S.M. Ylaya K. Wood B.J. Greten T.F. Wang X.W. Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer.Cancer Cell. 2019; 36: 418-430.e6Abstract Full Text Full Text PDF PubMed Scopus (250) Google Scholar The samples in these reports consisted mostly of cells from primary tumors, while circulating tumor cells were studied in a few reports.15Sun Y.F. Wu L. Liu S.P. Jiang M.M. Hu B. Zhou K.Q. Guo W. Xu Y. Zhong Y. Zhou X.R. Zhang Z.F. Liu G. Liu S. Shi Y.H. Ji Y. Du M. Li N.N. Li G.B. Zhao Z.K. Huang X.Y. Xu L.Q. Yu Q.C. Peng D.H. Qiu S.J. Sun H.C. Dean M. Wang X.D. Chung W.Y. Dennison A.R. Zhou J. Hou Y. Fan J. Yang X.R. Dissecting spatial heterogeneity and the immune-evasion mechanism of CTCs by single-cell RNA-seq in hepatocellular carcinoma.Nat Commun. 2021; 12: 4091Crossref PubMed Scopus (35) Google Scholar,16Chen V.L. Huang Q. Harouaka R. Du Y. Lok A.S. Parikh N.D. Garmire L.X. Wicha M.S. A dual-filtration system for single-cell sequencing of circulating tumor cells and clusters in HCC.Hepatol Commun. 2022 Jan 23; ([E-pub ahead of print])Crossref Scopus (1) Google Scholar In brief, scRNA-seq has been reported to allow delineation of cell type abundance, cell-cell interactions, transition in cellular status, clonal evolution, heterogeneity landscape, and lineage hierarchy in terms of marker gene expression, mutation and inferred copy number variation (CNV) status, and gene expression profiling at single-cell resolution (Figure 3).Table 1A Summary of the Studies on Human HCC Using the scRNA-seq TechniqueReferenceSamplesPlatformCellsPatientsCell TypesData Accession Number2Ho D.W.H. Tsui Y.M. Chan L.K. Sze K.M.F. Zhang X. Cheu J.W.S. Chiu Y.T. Lee J.M.F. Chan A.C.Y. Cheung E.T.Y. Yau D.T.W. Chia N.H. Lo I.L.O. Sham P.C. Cheung T.T. Wong C.C.L. Ng I.O.L. Single-cell RNA sequencing shows the immunosuppressive landscape and tumor heterogeneity of HBV-associated hepatocellular carcinoma.Nat Commun. 2021; 12: 3684Crossref PubMed Scopus (50) Google ScholarHCC10X43,6458All cell typesSRP3184993Sun Y. Wu L. Zhong Y. Zhou K. Hou Y. Wang Z. Zhang Z. Xie J. Wang C. Chen D. Huang Y. Wei X. Shi Y. Zhao Z. Li Y. Guo Z. Yu Q. Xu L. Volpe G. Qiu S. Zhou J. Ward C. Sun H. Yin Y. Xu X. Wang X. Esteban M.A. Yang H. Wang J. Dean M. Zhang Y. Liu S. Yang X. Fan J. Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma.Cell. 2021; 184: 404-421.e16Abstract Full Text Full Text PDF PubMed Scopus (151) Google ScholarHCC, adjacent tissuesMIRALCS16,49818All cell typesCNP000065010Zheng H. Pomyen Y. Hernandez M.O. Li C. Livak F. Tang W. Dang H. Greten T.F. Davis J.L. Zhao Y. Mehta M. Levin Y. Shetty J. Tran B. Budhu A. Wang X.W. Single-cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma.Hepatology. 2018; 68: 127-140Crossref PubMed Scopus (164) Google ScholarHCC, cell linesSmart-seq1181HCC cells, HuH1 cells, HuH7 cellsn/a11Lim C.J. Lee Y.H. Pan L. Lai L.Y. Chua C. Wasser M. Lim T.K.H. Yeong J. Toh H.C. Lee S.Y. Chan C.Y. Goh B.K.P. Chung A. Heikenwalder M. Ng I.O.L. Chow P. Albani S. Chew V. Multidimensional analyses reveal distinct immune microenvironment in hepatitis B virus-related hepatocellular carcinoma.Gut. 2019; 68: 916-927Crossref PubMed Scopus (150) Google ScholarHCC (HBV + nonviral), adjacent tissues, PBMCsCyTOFn/a23Immune lineagesn/a12Ho D.W.H. Tsui Y.M. Sze K.M.F. Chan L.K. Cheung T.T. Lee E. Sham P.C. Tsui S.K.W. Lee T.K.W. Ng I.O.L. Single-cell transcriptomics reveals the landscape of intra-tumoral heterogeneity and sternness-related subpopulations in liver cancer.Cancer Lett. 2019; 459: 176-185Crossref PubMed Scopus (74) Google ScholarHCC PDTXFluidigm C1139n/aCSC clustersn/a13Losic B. Craig A.J. Villacorta-Martin C. Martins S.N. Akers N. Chen X.T. Ahsen M.E. von Felden J. Labgaa I. D'Avola D. Allette K. Lira S.A. Furtado G.C. Garcia-Lezana T. Restrepo P. Stueck A. Ward S.C. Fiel M.I. Hiotis S.P. Gunasekaran G. Sia D. Schadt E.E. Sebra R. Schwartz M. Llovet J.M. Thung S. Stolovitzky G. Villanueva A. Intratumoral heterogeneity and clonal evolution in liver cancer.Nat Commun. 2020; 11: 291Crossref PubMed Scopus (150) Google ScholarHCC10X38,5532All cell typesE-MTAB-5905; GSE112271; E-MTAB-5899; E-MTAB-8127; E-MTAB-587814Song G.H. Shi Y. Zhang M.Y. Goswami S. Afridi S. Meng L. Ma J.Q. Chen Y. Lin Y.P. Zhang J. Liu Y.M. Jin Z.J. Yang S.X. Rao D.N. Zhang S. Ke A.W. Wang X.Y. Cao Y. Zhou J. Fan J. Zhang X.M. Xi R.B. Gao Q. Global immune characterization of HBV/HCV-related hepatocellular carcinoma identifies macrophage and T-cell subsets associated with disease progression.Cell Discov. 2020; 6: 90Crossref PubMed Scopus (40) Google ScholarHCC, nontumor liver tissues10X41,6987Immune cell lineagesCRA00230815Sun Y.F. Wu L. Liu S.P. Jiang M.M. Hu B. Zhou K.Q. Guo W. Xu Y. Zhong Y. Zhou X.R. Zhang Z.F. Liu G. Liu S. Shi Y.H. Ji Y. Du M. Li N.N. Li G.B. Zhao Z.K. Huang X.Y. Xu L.Q. Yu Q.C. Peng D.H. Qiu S.J. Sun H.C. Dean M. Wang X.D. Chung W.Y. Dennison A.R. Zhou J. Hou Y. Fan J. Yang X.R. Dissecting spatial heterogeneity and the immune-evasion mechanism of CTCs by single-cell RNA-seq in hepatocellular carcinoma.Nat Commun. 2021; 12: 4091Crossref PubMed Scopus (35) Google ScholarHCCSmart-seq211310CTCsEGAS0000100520416Chen V.L. Huang Q. Harouaka R. Du Y. Lok A.S. Parikh N.D. Garmire L.X. Wicha M.S. A dual-filtration system for single-cell sequencing of circulating tumor cells and clusters in HCC.Hepatol Commun. 2022 Jan 23; ([E-pub ahead of print])Crossref Scopus (1) Google ScholarHCC whole bloodSmart-seq2386CTCsn/a17Juhling F. Saviano A. Ponsolles C. Heydmann L. Crouchet E. Durand S.C. El Saghire H. Felli E. Lindner V. Pessaux P. Pochet N. Schuster C. Verrier E.R. Baumert T.F. Hepatitis B virus compartmentalization and single-cell differentiation in hepatocellular carcinoma.Life Sci Alliance. 2021; 4e202101036Crossref PubMed Google ScholarHCC; normal human hepatocytesCEL-Seq2/Smart-seq2938 cells (420 HCC cells), 200 healthy hepatocytes2HCC cells (nonimmune cells)SRP165160; SRP27575618Liang J. Chen W. Ye J. Ni C. Zhai W. Single-cell transcriptomics analysis reveals intratumoral heterogeneity and identifies a gene signature associated with prognosis of hepatocellular carcinoma.Biosci Rep. 2022; 42BSR20212560Crossref Scopus (3) Google ScholarHCC10X57531All cell typesn/a19Guan X. Wu Y. Zhang S. Liu Z. Fan Q. Fang S. Qiao S. Sun F. Liang C. Activation of FcRn mediates a primary resistance response to sorafenib in hepatocellular carcinoma by single-cell RNA sequencing.Front Pharmacol. 2021; 12709343Crossref Scopus (3) Google ScholarHCC PDTXBD Rhapsody10,602n/aAll cell typesGSE17571620Guan Y. Chen X. Wu M. Zhu W. Arslan A. Takeda S. Nguyen M.H. Majeti R. Thomas D. Zheng M. Peltz G. The phosphatidylethanolamine biosynthesis pathway provides a new target for cancer chemotherapy.J Hepatol. 2020; 72: 746-760Abstract Full Text Full Text PDF PubMed Scopus (19) Google ScholariPSCs, hepatoblasts, hepatic organoidsFluidigm C1424n/aiPSC, hepatoblast, hepatic organoidGSE13938221Vong J.S.L. Ji L. Heung M.M.S. Cheng S.H. Wong J. Lai P.B.S. Wong V.W.S. Chan S.L. Chan H.L.Y. Jiang P. Chan K.C.A. Chiu R.W.K. Lo Y.M.D. Single cell and plasma RNA sequencing for RNA liquid biopsy for hepatocellular carcinoma.Clin Chem. 2021; 67: 1492-1502Crossref PubMed Scopus (5) Google ScholarHCC and paired normal liver10X5782 (HCC cells); 11,394 (normal liver cells)4All cell typesEGAS0000100519422Dong X. Wang F. Liu C. Ling J. Jia X. Shen F. Yang N. Zhu S. Zhong L. Li Q. Single-cell analysis reveals the intra-tumor heterogeneity and identifies MLXIPL as a biomarker in the cellular trajectory of hepatocellular carcinoma.Cell Death Discov. 2021; 7: 14Crossref PubMed Scopus (12) Google ScholarHCC and NTSmart-seq24056All cell typesGSE15490623Chen W.S. Liang Y. Zong M. Liu J.J. Kaneko K. Hanley K.L. Zhang K. Feng G.S. Single-cell transcriptomics reveals opposing roles of Shp2 in Myc-driven liver tumor cells and microenvironment.Cell Rep. 2021; 37109974Abstract Full Text Full Text PDF Scopus (9) Google ScholarMouse HCC cells10X27,327n/aAll cell typesGSE15756124Ma L. Wang L. Khatib S.A. Chang C.W. Heinrich S. Dominguez D.A. Forgues M. Candia J. Hernandez M.O. Kelly M. Zhao Y. Tran B. Hernandez J.M. Davis J.L. Kleiner D.E. Wood B.J. Greten T.F. Wang X.W. Single-cell atlas of tumor cell evolution in response to therapy in hepatocellular carcinoma and intrahepatic cholangiocarcinoma.J Hepatol. 2021; 75: 1397-1408Abstract Full Text Full Text PDF PubMed Scopus (42) Google ScholarHCC and iCCA biopsies10X56,72144All cell typesGSE15153025Zheng B. Wang D. Qiu X. Luo G. Wu T. Yang S. Li Z. Zhu Y. Wang S. Wu R. Sui C. Gu Z. Shen S. Jeong S. Wu X. Gu J. Wang H. Chen L. Trajectory and functional analysis of PD-1(high) CD4(+)CD8(+) T cells in hepatocellular carcinoma by single-cell cytometry and transcriptome sequencing.Adv Sci (Weinh). 2020; 72000224Google ScholarHCC10X17,432,60039Immune cell lineagesCRA00127626Zheng C. Zheng L. Yoo J.K. Guo H. Zhang Y. Guo X. Kang B. Hu R. Huang J.Y. Zhang Q. Liu Z. Dong M. Hu X. Ouyang W. Peng J. Zhang Z. Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing.Cell. 2017; 169: 1342-1356.e16Abstract Full Text Full Text PDF PubMed Scopus (991) Google ScholarHCC, NT, PBMCSmart-seq250636T cellsEGAS00001002072; GSE9863827Zhang Q. He Y. Luo N. Patel S.J. Han Y. Gao R. Modak M. Carotta S. Haslinger C. Kind D. Peet G.W. Zhong G. Lu S. Zhu W. Mao Y. Xiao M. Bergmann M. Hu X. Kerkar S.P. Vogt A.B. Pflanz S. Liu K. Peng J. Ren X. Zhang Z. Landscape and dynamics of single immune cells in hepatocellular carcinoma.Cell. 2019; 179: 829-845.e20Abstract Full Text Full Text PDF PubMed Scopus (479) Google ScholarHCC, adjacent tissues, hepatic lymph nodes, ascitic fluid, PBMC10X; Smart-seq266,187 (10X Genomics); 11,134 (Smart-Seq2)16CD45+ immune cellsHRA000069; EGAS0000100328Ma L. Hernandez M.O. Zhao Y. Mehta M. Tran B. Kelly M. Rae Z. Hernandez J.M. Davis J.L. Martin S.P. Kleiner D.E. Hewitt S.M. Ylaya K. Wood B.J. Greten T.F. Wang X.W. Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer.Cancer Cell. 2019; 36: 418-430.e6Abstract Full Text Full Text PDF PubMed Scopus (250) Google ScholarHCC, iCCA10X508219All cell typesGSE12544910X, 10X Genomics Chromium platform; CSC, cancer stem cell; CTC, circulating tumor cell; CyTOF, cytometry by time of flight; iCCA, intrahepatic cholangiocarcinoma; iPSC, induced pluripotent stem cell; MIRALCS, microwell full-length mRNA amplification and library construction system; n/a, not available; NT, nontumorous liver; PBMC, peripheral blood mononuclear cell; PDTX, patient-derived tumor x