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Understanding tumour cell heterogeneity and its implication for immunotherapy in liver cancer using single-cell analysis

Published:November 29, 2020DOI:https://doi.org/10.1016/j.jhep.2020.11.036

      Summary

      Over the last decade, precision medicine and immunotherapeutic approaches have become increasingly popular in oncology. Early clinical trials reported promising results, but response rates in phase III clinical trials have been suboptimal. Knowledge gained from subsequent translational studies indicates the importance of targeting the tumour microenvironment to overcome resistance to immunotherapy. In this era of precision medicine, it is crucial to consider inter- as well as intratumoural heterogeneity. Single-cell analysis is a cutting-edge technology that enables us to better define the tumour cell community and to identify potential targets for immunotherapy or combination treatments. This review focuses on single-cell analysis in the context of immunotherapy in liver cancer, including the rationale behind studying hepatocellular carcinoma biology at a single-cell level. Single-cell technologies have the potential to revolutionise our understanding of resistance mechanisms and to guide drug discovery efforts, leading to further advances in personalised medicine.

      Keywords

      Linked Article

      • Is tissue hypoxia the principal mechanism for immune evasion and malignant progression in hepatocellular carcinoma?
        Journal of HepatologyVol. 75Issue 3
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          The advent of omics technologies and especially the possibility to analyze gene and protein expression patterns in single cells has greatly improved our understanding of intra-tumoral heterogeneity (ITH) and the dynamic nature of the tumor microenvironment (TME), both driving forces of tumor progression, therapy failure and, ultimately, patient prognosis. The outstanding review by Heinrich et al. comprehensively summarizes how single cell analyses have enabled us to better appreciate both ITH and composition of the TME of hepatocellular carcinoma (HCC).
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      • Hypoxia is a key regulator in liver cancer progression
        Journal of HepatologyVol. 75Issue 3
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          We appreciate the interest by Cramer and Vaupel in our review article on understanding tumor cell heterogeneity and its implication for immunotherapy in liver cancer by single cell analysis.1 Cramer and Vaupel2 questioned a statement in the article, “tumor diversity is triggered by hypoxia”, which refers to our recent study on using single cell technologies to define tumor cell landscape and its biology,3 and raised concerns about determining hypoxic status in tumours with HIF target genes since HIF can be activated by hypoxia-independent manners.
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      Why single-cell technology

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      Figure thumbnail gr1
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      In the last 5 years, high impact research articles have been published that describe the cellular landscape in HCC on a single-cell level. This review summarises what can be learned from single-cell analysis in liver cancer and its implications for immunotherapy.

      Single-cell analysis in liver cancer

      Single-cell analysis on a genomic and epigenomic level

      RNA sequencing is currently the most widely utilised approach for single-cell studies due to the inherent limitations of DNA sequencing on this scale. For any given cell, the average number of DNA copies at an individual allele will be 2 (1 for each chromosome). On the other hand, tens or hundreds of copies can exist of a particular transcript in a single-cell.
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      The authors isolated cells from 3 spatially distinct areas of the tumour with different tumour characteristics. CNVs and HBV integration sites strongly correlated between single cells isolated from tumours of 2 of the 3 patients, indicating a monoclonal origin.
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      The CNV profiles of single cells from the last patient with lobular multiple nodules suggests a polyclonal origin.
      DNA sequencing can also be used to profile chromatin accessibility, a relatively new approach to uncover epigenetic and upstream regulatory mechanisms that control transcription on a global scale. The premise behind chromatin accessibility profiling revolves around transcriptional activity, which is associated with open (euchromatin) or closed (heterochromatin) regions of DNA.
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      Euchromatin is typically more transcriptionally active, as the DNA is more accessible to the transcriptional machinery. Global promoter and enhancer activity can be profiled by sequencing approaches that use enzymes such as DNAse-I or hyperactive Tn5, which cut at regions of DNA that are not bound by nucleosomes, leading to enrichment of open chromatin regions.
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      The newest technique, Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) utilises hyperactive Tn5 and has been readily adopted for single-cell analysis because of the short processing time and low DNA input needed to create high quality data (Fig. 2). Compared to other methods such as DNase-seq, which require many steps at which cells are lost, the ATAC-seq assay and library preparation can be completed in 1 enzymatic step.
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      This significantly reduces the number of cells needed up front. As opposed to whole genome sequencing, ATAC-seq enriches for regions of DNA that are not bound by nucleosomes. By comparing fragments across all cells, regions where fragments overlap more than the average background can be called “peaks”. These peaks are then used for downstream analysis, such as finding the most variable peaks across cells, low dimensionality embedding and clustering.
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      Regardless, the data generated from scATAC-seq is much sparser than with scRNA-seq, as an order of magnitude more peaks can potentially be identified compared to genes and the peak count matrix is typically binarized. While few studies have been published using scATAC-seq, this technique has already generated exceptional data. Novel mechanisms of transcriptional regulation associated with outcome and response to immunotherapy have been described in acute myeloid leukaemia (AML) and basal cell carcinoma.
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      • Wu B.
      • Greenside P.G.
      • Chan S.M.
      • Koenig J.L.
      • et al.
      Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution.
      ,
      • Satpathy A.T.
      • Granja J.M.
      • Yost K.E.
      • Qi Y.
      • Meschi F.
      • McDermott G.P.
      • et al.
      Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion.
      One of the earliest studies to use scATAC-seq in cancer involved the sequencing of AML cells from 12 patients.
      • Corces M.R.
      • Buenrostro J.D.
      • Wu B.
      • Greenside P.G.
      • Chan S.M.
      • Koenig J.L.
      • et al.
      Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution.
      Variation in DNA accessibility increased with the progressive stages of development. ScATAC-seq was also used to profile how chromatin accessibility changed after anti-programmed cell death 1 (PD-1) therapy in the TME of 7 patients with basal cell carcinoma.
      • Satpathy A.T.
      • Granja J.M.
      • Yost K.E.
      • Qi Y.
      • Meschi F.
      • McDermott G.P.
      • et al.
      Massively parallel single-cell chromatin landscapes of human immune cell development and intratumoral T cell exhaustion.
      Overall, 37,818 cells were sequenced from pre and post-treatment biopsies. The authors mapped regulatory programmes including promoters, enhancers and transcription factor binding motifs that were altered upon treatment. Most notable among these are ~5,000 DNA regions associated with exhausted T cells, which were dramatically expanded in post therapy biopsies. Based on these exciting results, scATAC-seq studies are eagerly awaited in liver cancer.
      ScATAC-seq may provide insights into transcriptional regulations that are associated with immunotherapy.
      Figure thumbnail gr2
      Fig. 2scATAC-seq workflow to analyse genomic and epigenomic molecular alterations.

      Single-cell analysis on a transcriptomic level using scRNA-seq

      Several studies have used scRNA-seq in HCC (Table 1). Technical limitations include processing resected samples as well as the scarcity of primary tissue. Further, current guidelines do not recommend routine biopsies for diagnosis or treatment follow-up, which limits the availability of tissue. Technical variables that influence the power of different sequencing methods include sensitivity (probability to capture), accuracy (correspondence of read quantification) and precision of amplification (technical variation).
      • Ziegenhain C.
      • Vieth B.
      • Parekh S.
      • Reinius B.
      • Guillaumet-Adkins A.
      • Smets M.
      • et al.
      Comparative analysis of single-cell RNA sequencing methods.
      There are different sequencing platforms available and each of them have different advantages and disadvantages (Fig. 3). They differ in terms of cell throughput (high vs. low), the application of unique molecular identifiers and amplification methods.
      • Ziegenhain C.
      • Vieth B.
      • Parekh S.
      • Reinius B.
      • Guillaumet-Adkins A.
      • Smets M.
      • et al.
      Comparative analysis of single-cell RNA sequencing methods.
      A comparison of 6 different single-cell sequencing techniques revealed small differences in accuracy. 90% of the transcriptome results are stable regardless of technique.
      • Ziegenhain C.
      • Vieth B.
      • Parekh S.
      • Reinius B.
      • Guillaumet-Adkins A.
      • Smets M.
      • et al.
      Comparative analysis of single-cell RNA sequencing methods.
      • Picelli S.
      • Bjorklund A.K.
      • Faridani O.R.
      • Sagasser S.
      • Winberg G.
      • Sandberg R.
      Smart-seq2 for sensitive full-length transcriptome profiling in single cells.
      • Macosko E.Z.
      • Basu A.
      • Satija R.
      • Nemesh J.
      • Shekhar K.
      • Goldman M.
      • et al.
      Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.
      Zhang et. al. performed parallel scRNA-seq on both platforms (SMART-Seq and 10x genomics) to confirm stability. The analysis revealed that SMART-Seq has a higher sequencing depth and may be able to differentiate clusters that were hidden in the 10x genomics datasets, whereas 10x genomics seems to rescue clusters of rare cell populations that contain less than 10 cells.
      Table 1Overview of studies investigating the tumor microenvironment in hepatocellular carcinoma on a single cell level.
      Technical factorsEntityTissueCellsPatientsCheckpoint inhibitorSummaryRef.
      Multiregional, single cell, other omicsPLCNNSingle or combinations
      ScRNA-seq of unsorted single cell suspensionHCC, iCCATumour tissue5,115 (702 malignant

      4,380 non-malignant cells) +

      4,831 (1,290 malignant

      3,541 non-malignant cells)
      19 (12+7)Durvalumab/tremelimumab or pembrolizumabSingle cell analysis revealed intratumoural heterogeneity in malignant cells as well as in individual cell groups. Application of a diversity score on malignant cells could stratify patients into good and bad survival groups. VEGFA that higher expressed in more diverse tumours, may be responsible for reprogramming of the TME.
      • Ma L.
      • Hernandez M.O.
      • Zhao Y.
      • Mehta M.
      • Tran B.
      • Kelly M.
      • et al.
      Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer.
      RAN-seq, ScRNA-seq of CD4 and CD8 sorted immune cells (SMARTseq), TCR profilingHCCTumour tissue, adjacent liver, peripheral blood5,0636Treatment naïveDifferent T cell subsets can be detected in the tumour microenvironment. Trajectory analysis revealed transition from naïve T cells to exhausted or cytotoxic phenotypes. TCR sequencing demonstrates local distribution of clonally expanded T cells in the tumour. LAYN as a suppressive marker expressed on exhausted CD8 T cells and Tregs
      • Zheng C.
      • Zheng L.
      • Yoo J.K.
      • Guo H.
      • Zhang Y.
      • Guo X.
      • et al.
      Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing.
      ScRNA-seq of CD45 sorted immune cells, 10xGenomics + Smart SeqHCCTumour tissue, adjacent liver, hepatic lymph nodes, peripheral blood, ascites66,187 (10x Genomics)

      11,134 (Smart Seq)
      16Treatment naïveSMARTseq is able to differentiate closely related population, whereas 10x Genomics rescues rare cell population with few cells. LAMP3+ DCs are mature DCs that travel from the tumour to local LNs. They take a major part in T cell activation. Two major macrophage populations are present in the tumour, one of which is associated with survival prognosis.
      • Zhang Q.
      • He Y.
      • Luo N.
      • Patel S.J.
      • Han Y.
      • Gao R.
      • et al.
      Landscape and dynamics of single immune cells in hepatocellular carcinoma.
      RNA-Seq, DNA-Seq, TCR-Seq, SNP Array, ScRNA-seq multiregionalHCCTumour tissue, adjacent liver38,553 (for sc sequencing)14 (TCR seq), 2 (sc seq)Treatment naïveScRNA-seq shows transcriptomic heterogeneity in Tumour cells from spatially distinct regions. While a majority of transcription factors were ubiquitously active or inactive in all regions of the tumours, there were several transcription factors active in only one region.
      • Losic B.
      • Craig A.J.
      • Villacorta-Martin C.
      • Martins-Filho S.N.
      • Akers N.
      • Chen X.
      • et al.
      Intratumoral heterogeneity and clonal evolution in liver cancer.
      ScRNA-seqHCCTumour tissue (PDTX model)139 cellsPDTXTreatment naïveIntratumoural heterogeneity and stemness related subpopulations in liver cancer. Two major HCC subpopulations based on EPCAM expression. One rare subclone enriched in CD24+CD44+ with particular oncogenic features
      • Ho D.W.
      • Tsui Y.M.
      • Sze K.M.
      • Chan L.K.
      • Cheung T.T.
      • Lee E.
      • et al.
      Single-cell transcriptomics reveals the landscape of intra-tumoral heterogeneity and stemness-related subpopulations in liver cancer.
      ScRNA-seqHBV ass.

      HCC
      Tumour tissue96 tumour cells

      15 normal liver cells
      3Treatment naïveClonal evolution and HBV integration is an early event in the cancer development. It stays stable during tumour progression
      • Duan M.
      • Hao J.
      • Cui S.
      • Worthley D.L.
      • Zhang S.
      • Wang Z.
      • et al.
      Diverse modes of clonal evolution in HBV-related hepatocellular carcinoma revealed by single-cell genome sequencing.
      ScRNA-seq, CNV, DNA methylationHCCTumour tissue251Treatment naïveTwo cell subsets could be identified using triple-omics approach: CNV, DNA methylation and transcriptome analysis on a single cell level
      • Yu Hou
      • Huahu Guo
      • Chen Cao
      • Xianlong Li
      • Boqiang Hu
      • Ping Zhu
      • et al.
      Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas.
      ScRNA-seq of unsorted single cell suspensionHCCTumour tissue + 2 cell lines1 + 2 cell linesTreatment naïveCancer stem cells display a high degree of heterogeneity. Gene signatures generated from cancer stem cells correlate with patient survival when applied to bulk sequencing data.
      • Zheng H.
      • Pomyen Y.
      • Hernandez M.O.
      • Li C.
      • Livak F.
      • Tang W.
      • et al.
      Single cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma.
      WES, RNA-seq, MS, Metabolomics, CyTOF, ScRNA-seq (microwell seq) multiregionalHCCTumour tissue, adjacent liver, peripheral blood,19,6258 (4 single cell)Treatment naïve3 HCC subtypes with immunocompetent, immunodeficient, immunosuppressive features. Immunome and metabolome correspond better than transcriptome and proteome. No metabolomic target identified, but correlation with immune cell clusters targetable.
      • Zhang Q.
      • Lou Y.
      • Yang J.
      • Wang J.
      • Feng J.
      • Zhao Y.
      • et al.
      Integrated multiomic analysis reveals comprehensive tumour heterogeneity and novel immunophenotypic classification in hepatocellular carcinomas.
      TCR-seq, WES, multiregionalPLCTumor tissue, adjacent liver, blood5Intratumoral T cell clones are spatially heterogenous. TIL diversity correlated with immune response rather than mutation load.
      • Shi L.
      • Zhang Y.
      • Feng L.
      • Wang L.
      • Rong W.
      • Wu F.
      • et al.
      Multi-omics study revealing the complexity and spatial heterogeneity of tumor-infiltrating lymphocytes in primary liver carcinoma.
      Flow cytometry, RNA-seqHCCTumor tissue, adjacent liver, blood50Treatment naïveIntratumoral MAIT cells express an effector memory phenotype. They show significant elevated exhaustion marker expression (PD-1, TIM-3, CTLA-4) and a lower cytotoxicity profile (IFNg and IL-17)
      • Duan M.
      • Goswami S.
      • Shi J.Y.
      • Wu L.J.
      • Wang X.Y.
      • Ma J.Q.
      • et al.
      Activated and exhausted MAIT cells foster disease progression and indicate poor outcome in hepatocellular carcinoma.
      Figure thumbnail gr3
      Fig. 3RNA-seq workflow for single-cell studies. Patient samples are dissociated into single-cell suspension. Different pipelines are available for different platforms. After raw data processing including alignment and several steps of quality control, multiple bioinformatic approaches are available to answer different biological questions.
      Several research themes have emerged that employ single-cell methodology. Two studies focused on cancer stem cells (CSCs) in HCC.
      • Zheng H.
      • Pomyen Y.
      • Hernandez M.O.
      • Li C.
      • Livak F.
      • Tang W.
      • et al.
      Single cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma.
      • Ho D.W.
      • Tsui Y.M.
      • Sze K.M.
      • Chan L.K.
      • Cheung T.T.
      • Lee E.
      • et al.
      Single-cell transcriptomics reveals the landscape of intra-tumoral heterogeneity and stemness-related subpopulations in liver cancer.
      • JU Marquardt
      • Andersen J.B.
      • Thorgeirsson S.S.
      Functional and genetic deconstruction of the cellular origin in liver cancer.
      Liver CSCs appear to be highly heterogenous based on the expression of CSC markers. ScRNA-seq of patient-derived tumour xenografts identified 2 major subpopulations based on the expression of epithelial cell adhesion molecular (EPCAM) and intrinsic expression of other liver CSC markers. Most tumour cells had similar transcriptomics and formed several large clusters, albeit rare clusters with small numbers of cells could be identified that were differentially marked by stemness-related gene markers.
      • Ho D.W.
      • Tsui Y.M.
      • Sze K.M.
      • Chan L.K.
      • Cheung T.T.
      • Lee E.
      • et al.
      Single-cell transcriptomics reveals the landscape of intra-tumoral heterogeneity and stemness-related subpopulations in liver cancer.
      SMART-Seq analysis of 2 HCC cell lines (Huh1 and Huh7) and patient-derived cells that were positively sorted for CD133, CD24 and EPCAM, enabled investigation of global transcriptomic diversity on a single-cell level in the context of CSCs. Single cells showed transcriptomic heterogeneity, but this heterogeneity decreased in cell pools.
      • Zheng H.
      • Pomyen Y.
      • Hernandez M.O.
      • Li C.
      • Livak F.
      • Tang W.
      • et al.
      Single cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma.
      They generated a gene signature from Huh7 cells that were triple positive for CSC markers. When this 286-gene signature was applied to TCGA bulk sequencing data, it could robustly predict overall survival in patients with HCC.
      • Zheng H.
      • Pomyen Y.
      • Hernandez M.O.
      • Li C.
      • Livak F.
      • Tang W.
      • et al.
      Single cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma.
      ScRNA-seq analysis enables us to draw a very detailed picture of the TME of HCC (Fig. 4). One study comprehensively analysed the entire cell population in HCC, including the malignant cells, using the 10x genomics platform. ScRNA-seq revealed varying degrees of heterogeneity in malignant cells, which was associated with patient survival.
      • Ma L.
      • Hernandez M.O.
      • Zhao Y.
      • Mehta M.
      • Tran B.
      • Kelly M.
      • et al.
      Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer.
      CNV on a single-cell level enables the differentiation between malignant and non-malignant cells, allowing for further individual analysis that would not be possible with bulk sequencing.
      • Ma L.
      • Hernandez M.O.
      • Zhao Y.
      • Mehta M.
      • Tran B.
      • Kelly M.
      • et al.
      Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer.
      ,
      • Puram S.V.
      • Tirosh I.
      • Parikh A.S.
      • Patel A.P.
      • Yizhak K.
      • Gillespie S.
      • et al.
      Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer.
      Trajectory analysis of malignant cells revealed different tumour types (more stem-like or more differentiated) between patients.
      • Ma L.
      • Hernandez M.O.
      • Zhao Y.
      • Mehta M.
      • Tran B.
      • Kelly M.
      • et al.
      Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer.
      A correlation analysis of each individual cell can confirm ITH, which seems to be different among patients. Application of an intratumoural diversity score revealed significant differences in overall survival in patients treated with immune checkpoint inhibitors, indicating that a higher level of transcriptional diversity within the malignant cell population leads to more aggressive tumour characteristics.
      • Ma L.
      • Hernandez M.O.
      • Zhao Y.
      • Mehta M.
      • Tran B.
      • Kelly M.
      • et al.
      Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer.
      Since the biodiversity was further evident in the non-malignant cells, the authors suggested a possible reprogramming of the TME. Differential gene expression analysis revealed a high correlation with hypoxia induced genes indicating that tumour diversity is triggered by hypoxia. Vascular endothelial growth factor A (VEGFA), a direct target of HIF1a (hypoxia-inducible factor 1α), was highly expressed in more diverse tumours, suggesting that VEGFA drives TME reprogramming. Consequently, further single-cell analysis of T cells derived from high- and low-diversity tumours revealed different transcriptomic profiles. Overall, these findings provide a mechanistic explanation of tumour cell biodiversity and explain why some patients may respond to therapy while others do not (Fig. 5). Given the recent accelerated FDA approval of the combined bevacizumab/atezolizumab regimen,
      • Finn R.S.
      • Ducreux M.
      • Qin S.
      • Galle P.R.
      • Zhu A.X.
      • Ikeda M.
      • et al.
      IMbrave150: a randomized phase III study of 1L atezolizumab plus bevacizumab vs sorafenib in locally advanced or metastatic hepatocellular carcinoma.
      VEGFA enrichment might be a promising indicator of therapeutic response to VEGF-targeted therapy, while other multikinase inhibitors could hold promise in combination therapies, since several interact with the immune system, causing M1 polarisation of tumour-associated macrophages or supporting infiltration of CD4+ and CD8+ T cells into tumours.
      • Chen M.L.
      • Yan B.S.
      • Lu W.C.
      • Chen M.H.
      • Yu S.L.
      • Yang P.C.
      • et al.
      Sorafenib relieves cell-intrinsic and cell-extrinsic inhibitions of effector T cells in tumor microenvironment to augment antitumor immunity.
      • Sprinzl M.F.
      • Reisinger F.
      • Puschnik A.
      • Ringelhan M.
      • Ackermann K.
      • Hartmann D.
      • et al.
      Sorafenib perpetuates cellular anticancer effector functions by modulating the crosstalk between macrophages and natural killer cells.
      • Wu X.
      • Luo H.
      • Shi B.
      • Di S.
      • Sun R.
      • Su J.
      • et al.
      Combined antitumor effects of sorafenib and GPC3-CAR T cells in mouse models of hepatocellular carcinoma.
      Figure thumbnail gr4
      Fig. 4Lessons learned through single cells analysis about the tumour immune environment in patients with HCC. Transcriptomic profiling allows identification of immune subgroups, identification of processes like clonality and trajectory within T cells as well as identification of different states of activation and exhaustion. Comparison of tumour infiltrating immune cells with cells from non-tumourous sites can identify organ specific immune cell characteristics and gains information about tumour specific influences on its environment.
      Figure thumbnail gr5
      Fig. 5How can we apply single-cell analysis for treatment regimens in the future? (A) molecular interactions and cell development into a tumour supportive state could be interrupted on different levels. (B) personalised treatment approaches based on cellular compositions and subgroup state in every single patient.
      Two more scRNA-seq studies focusing on immune cells have provided a detailed insight into the liver TME. Using SMART-Seq, highly diverse T cell subpopulations that would not have been distinguished with conventional flow cytometry were shown to be present in HCC tumours.
      • Zheng C.
      • Zheng L.
      • Yoo J.K.
      • Guo H.
      • Zhang Y.
      • Guo X.
      • et al.
      Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing.
      It enabled a detailed description of intratumoural T cells and their characteristics, revealing subpopulations of regulatory T (Treg) cells and CD8+ T cells (Fig. 4). A certain subgroup of CD8+ T cells, so called CD8-LAYN+ T cells, is predominantly composed of T cells from the tumour itself and expresses high levels of exhaustion markers such as cytotoxic T lymphocyte-associated protein 4 (CTLA4), PDCD1 (also called PD1) and HAVCR2 (also called TIM3). LAYN seemed to have a suppressive function on T cells and could further stratify patients into 2 different survival groups using the TCGA data set.
      • Zheng C.
      • Zheng L.
      • Yoo J.K.
      • Guo H.
      • Zhang Y.
      • Guo X.
      • et al.
      Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing.
      In contrast, CD8-LEF+ T cells expressing mainly naïve markers were predominantly present in the peripheral blood. Subgroup analysis of the Treg cell population revealed a stratification into CTLA4high and a CTLA4low expressing groups, that showed a spatial distribution between tumour and peripheral blood, respectively.
      • Zheng C.
      • Zheng L.
      • Yoo J.K.
      • Guo H.
      • Zhang Y.
      • Guo X.
      • et al.
      Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing.
      Another group compared their CD8+ T cell scRNA-seq data to transcriptomic data of CD8+ T cells in chronic hepatitis and found that both show high expression of exhaustion markers. However, on a single-cell level, there were significant differences in phenotypes and functional states within the CD8+ T cell population, which is in line with results from flow cytometry.
      • Wang X.
      • He Q.
      • Shen H.
      • Lu X.J.
      • Sun B.
      Genetic and phenotypic difference in CD8(+) T cell exhaustion between chronic hepatitis B infection and hepatocellular carcinoma.
      ,
      • Shi F.
      • Shi M.
      • Zeng Z.
      • Qi R.Z.
      • Liu Z.W.
      • Zhang J.Y.
      • et al.
      PD-1 and PD-L1 upregulation promotes CD8(+) T-cell apoptosis and postoperative recurrence in hepatocellular carcinoma patients.
      Interestingly, in melanoma, known exhaustion signatures
      • Wherry E.J.
      • Ha S.J.
      • Kaech S.M.
      • Haining W.N.
      • Sarkar S.
      • Kalia V.
      • et al.
      Molecular signature of CD8+ T cell exhaustion during chronic viral infection.
      ,
      • Fuertes Marraco S.A.
      • Neubert N.J.
      • Verdeil G.
      • Speiser D.E.
      Inhibitory receptors beyond T cell exhaustion.
      were enriched in both immunotherapy responders and non-responders with no change before or after treatment, indicating that a simple analysis of exhaustion markers might not be sufficient to stratify patients. T cell enrichment within the tumour has previously been shown by CyTOF analysis.
      • Lavin Y.
      • Kobayashi S.
      • Leader A.
      • Amir E.D.
      • Elefant N.
      • Bigenwald C.
      • et al.
      Innate immune landscape in early lung adenocarcinoma by paired single-cell analyses.
      Notably, CD8+ T cell infiltration could not predict therapy response. The state of T cells and distinct immune cell signatures on different cell subtypes, not just raw cell frequencies, seems to be crucial for response to immunotherapy, which might go unseen in bulk sequencing data.
      scRNA-seq analysis also has the advantage of enabling analysis of temporal differences in cell differentiation or cell plasticity, which was limited with conventional methods.
      • Trapnell C.
      • Cacchiarelli D.
      • Grimsby J.
      • Pokharel P.
      • Li S.
      • Morse M.
      • et al.
      The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells.
      Different computational analysis options, such as Monocle 3,
      • Trapnell C.
      • Cacchiarelli D.
      • Grimsby J.
      • Pokharel P.
      • Li S.
      • Morse M.
      • et al.
      The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells.
      ,
      • Cao J.
      • Spielmann M.
      • Qiu X.
      • Huang X.
      • Ibrahim D.M.
      • Hill A.J.
      • et al.
      The single-cell transcriptional landscape of mammalian organogenesis.
      EMBEDDR,
      • Campbell K.
      • Ponting C.P.
      • Webber C.
      Laplacian eigenmaps and principal curves for high resolution pseudotemporal ordering of single-cell RNA-seq profiles.
      SCORPIUS
      • Cannoodt R.
      • Saelens W.
      • Sichien D.
      • Tavernier S.
      • Janssens S.
      • Guilliams M.
      • et al.
      SCORPIUS improves trajectory inference and identifies novel modules in dendritic cell development.
      or TSCAN,
      • Ji Z.
      • Ji H.
      TSCAN: pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis.
      can be used to map developmental trajectories and biological processes based on transcriptional similarities. Mapping of intratumoural CD8+ T cells using Monocle 2 demonstrated a transition from naïve T cells to effector T cells to exhausted T cells.
      • Zheng C.
      • Zheng L.
      • Yoo J.K.
      • Guo H.
      • Zhang Y.
      • Guo X.
      • et al.
      Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing.
      Trajectory analysis can also show the different directions of development, for instance CD4+ T cells in the tumour could develop an exhausted or cytotoxic phenotype. T cell receptor (TCR) sequencing could confirm this result, indicating an exclusive developmental fate.
      In a second study, the same group analysed the spatial distribution and migration patterns of different immune cell compartments in more detail.
      • Zhang Q.
      • He Y.
      • Luo N.
      • Patel S.J.
      • Han Y.
      • Gao R.
      • et al.
      Landscape and dynamics of single immune cells in hepatocellular carcinoma.
      ScRNA-seq confirmed an intratumoural abundance of Treg cells and exhausted T cells. Different subsets of myeloid-derived cells and natural killer (NK) cells showed a difference in spatial distribution between tumour and extratumoural locations such as ascites, which could be detected by deep sequencing on a single-cell level.
      • Zhang Q.
      • He Y.
      • Luo N.
      • Patel S.J.
      • Han Y.
      • Gao R.
      • et al.
      Landscape and dynamics of single immune cells in hepatocellular carcinoma.
      TCR sequencing enables us to investigate clonal expansions of unique T cells. By comparing the T cell composition at different locations we can draw conclusions regarding the relocation of specific T cells.
      • Han A.
      • Glanville J.
      • Hansmann L.
      • Davis M.M.
      Linking T-cell receptor sequence to functional phenotype at the single-cell level.
      TCR sequencing data could confirm a higher percentage of clonally expanded T cells in the tumour compared to the peripheral blood and to the adjacent liver (30% vs. 10%, respectively).
      • Guo X.
      • Zhang Y.
      • Zheng L.
      • Zheng C.
      • Song J.
      • Zhang Q.
      • et al.
      Global characterization of T cells in non-small-cell lung cancer by single-cell sequencing.
      ,
      • Shi L.
      • Zhang Y.
      • Feng L.
      • Wang L.
      • Rong W.
      • Wu F.
      • et al.
      Multi-omics study revealing the complexity and spatial heterogeneity of tumor-infiltrating lymphocytes in primary liver carcinoma.
      This indicates that these clonally expanded intratumoural T cells are specific to the tumour. Further, TCR sequencing demonstrated that 1 cycle of tremelimumab (anti-CTLA-4 inhibitor) significantly decreased T cell clonality in the peripheral blood of patients with HCC.
      • Agdashian D.
      • ElGindi M.
      • Xie C.
      • Sandhu M.
      • Pratt D.
      • Kleiner D.E.
      • et al.
      The effect of anti-CTLA4 treatment on peripheral and intra-tumoral T cells in patients with hepatocellular carcinoma.
      This provides the rationale for a tumour antigen-specific T cell therapy, like those successfully applied to other tumour entities.
      • Tran E.
      • Robbins P.F.
      • Lu Y.C.
      • Prickett T.D.
      • Gartner J.J.
      • Jia L.
      • et al.
      T-cell transfer therapy targeting mutant KRAS in cancer.
      ScRNA-seq demonstrated transcriptional heterogeneity within the malignant cell population which was associated with survival. Identification of alterations in more diverse subpopulations may have implications for immunotherapy.
      Single-cell analysis revealed 2 distinct macrophage subpopulations that were dominant in the tumour, with a transcriptome profile associated with myeloid-derived suppressor cells and tumour-associated macrophages. The differentiation between the subpopulations enabled a stratification into prognostically relevant groups.
      • Zhang Q.
      • He Y.
      • Luo N.
      • Patel S.J.
      • Han Y.
      • Gao R.
      • et al.
      Landscape and dynamics of single immune cells in hepatocellular carcinoma.
      A specific LAMP3+ subpopulation of dendritic cells – never detected in classical dendritic cell subset analysis – was also detected. LAMP3+ dendritic cells are an intratumoural subset and much less abundant in the adjacent liver. However, these dendritic cells were present but not detected in several other tumour entities. In vitro experiments identified LAMP3+ as a maturation marker expressed on dendritic cells.
      The identification of subgroups of professional antigen-presenting cells provides information to improve antigen presentation and to increase the immunogenicity of tumours. One approach to do so is locoregional therapy, which causes high tumour antigen release.
      • den Brok M.H.
      • Sutmuller R.P.
      • van der Voort R.
      • Bennink E.J.
      • Figdor C.G.
      • Ruers T.J.
      • et al.
      In situ tumor ablation creates an antigen source for the generation of antitumor immunity.
      ,
      • den Brok M.H.
      • Sutmuller R.P.
      • Nierkens S.
      • Bennink E.J.
      • Frielink C.
      • Toonen L.W.
      • et al.
      Efficient loading of dendritic cells following cryo and radiofrequency ablation in combination with immune modulation induces anti-tumour immunity.
      The immunological “side effects” caused by local therapies are of particular interest in the age of immunotherapy.
      • Greten T.F.
      • Mauda-Havakuk M.
      • Heinrich B.
      • Korangy F.
      • Wood B.J.
      Combined locoregional-immunotherapy for liver cancer.
      Several studies indicate that local procedures induce an immunogenic cell death that has modulating effects on immune cell composition and activation in the TME.
      • Zhang H.
      • Hou X.
      • Cai H.
      • Zhuang X.
      Effects of microwave ablation on T-cell subsets and cytokines of patients with hepatocellular carcinoma.
      • Hoechst B.
      • Ormandy L.A.
      • Ballmaier M.
      • Lehner F.
      • Kruger C.
      • Manns M.P.
      • et al.
      A new population of myeloid-derived suppressor cells in hepatocellular carcinoma patients induces CD4(+)CD25(+)Foxp3(+) T cells.
      • Arihara F.
      • Mizukoshi E.
      • Kitahara M.
      • Takata Y.
      • Arai K.
      • Yamashita T.
      • et al.
      Increase in CD14+HLA-DR -/low myeloid-derived suppressor cells in hepatocellular carcinoma patients and its impact on prognosis. Cancer immunology, immunotherapy.
      • Nobuoka D.
      • Motomura Y.
      • Shirakawa H.
      • Yoshikawa T.
      • Kuronuma T.
      • Takahashi M.
      • et al.
      Radiofrequency ablation for hepatocellular carcinoma induces glypican-3 peptide-specific cytotoxic T lymphocytes.
      • Chew V.
      • Lee Y.H.
      • Pan L.
      • Nasir N.J.M.
      • Lim C.J.
      • Chua C.
      • et al.
      Immune activation underlies a sustained clinical response to Yttrium-90 radioembolisation in hepatocellular carcinoma.
      Doxorubicin is an example of a classic chemotherapeutic that induces immunogenic cell death. It is the most commonly used chemotherapeutic for transarterial chemoembolisation (TACE) procedures in patients with HCC.
      • Apetoh L.
      • Mignot G.
      • Panaretakis T.
      • Kroemer G.
      • Zitvogel L.
      Immunogenicity of anthracyclines: moving towards more personalized medicine.
      Other locoregional therapies with a proven immunogenic effect are cryoablation or radiofrequency ablation.
      • den Brok M.H.
      • Sutmuller R.P.
      • van der Voort R.
      • Bennink E.J.
      • Figdor C.G.
      • Ruers T.J.
      • et al.
      In situ tumor ablation creates an antigen source for the generation of antitumor immunity.
      ,
      • den Brok M.H.
      • Sutmuller R.P.
      • Nierkens S.
      • Bennink E.J.
      • Frielink C.
      • Toonen L.W.
      • et al.
      Efficient loading of dendritic cells following cryo and radiofrequency ablation in combination with immune modulation induces anti-tumour immunity.
      One study reported tumour antigen-specific T cell responses in up to 60% of patients following radiofrequency ablation. However, the response was not durable enough to completely prevent recurrence, which is why combinations with immunotherapy seem to be a reasonable alternative suggestion.
      • Mizukoshi E.
      • Yamashita T.
      • Arai K.
      • Sunagozaka H.
      • Ueda T.
      • Arihara F.
      • et al.
      Enhancement of tumor-associated antigen-specific T cell responses by radiofrequency ablation of hepatocellular carcinoma.
      The first combination therapy of tremelimumab with TACE, radiofrequency ablation or cryoablation was well tolerated and led to increased intratumoural accumulation of CD8+ T cells and good clinical responses.
      • Duffy A.G.
      • Ulahannan S.V.
      • Makorova-Rusher O.
      • Rahma O.
      • Wedemeyer H.
      • Pratt D.
      • et al.
      Tremelimumab in combination with ablation in patients with advanced hepatocellular carcinoma.

      Single-cell analysis on a protein level using mass and flow cytometry

      Other analyses of liver cancer on the single-cell level have been performed by measuring protein abundance using CyTOF. A recent study compared the immunological profile between patients with hepatitis B-related and non-viral-related HCC in the tumour, non-tumour liver and the peripheral blood using CyTOF.
      • Lim C.J.
      • Lee Y.H.
      • Pan L.
      • Lai L.
      • Chua C.
      • Wasser M.
      • et al.
      Multidimensional analyses reveal distinct immune microenvironment in hepatitis B virus-related hepatocellular carcinoma.
      Comparison of the immune subsets revealed an overlap of 85% between viral and non-viral HCC samples, indicating a significant similarity. Additionally, immune cell composition between adjacent liver and tumour is distinct from the peripheral blood, whereas CD8+ T cells showed a progressive exhaustion from the periphery into the tumour, that can be reversed by anti-PD-1 treatment. Tumour-infiltrating lymphocytes (TILs) of unique hepatitis-related HCC clusters included a high abundance of Treg cells and resident memory CD8+ T cells with high PD-1 expression. TILs in non-viral-related HCC clusters were enriched in Tim-3+CD8+ T cells and NK cells expressing markers of cytotoxicity. The immunosuppressive function of hepatitis-associated Treg cells could be reversed by application of anti-PD-1 antibodies.
      • Shang B.
      • Liu Y.
      • Jiang S.J.
      • Liu Y.
      Prognostic value of tumor-infiltrating FoxP3+ regulatory T cells in cancers: a systematic review and meta-analysis.
      Thus, in a subset of patients, the immunological landscape of hepatitis-associated HCCs is distinct from non-viral-related HCCs, implying the need for individualised immunotherapy.
      Cellular composition is not uniform across the entirety of a tumour. Spatial distribution of tumour subclones and T cell clonal expansions have implications for immunotherapy response.
      Flow cytometry of samples from liver resections was used to analyse, in detail, the role of mucosal-associated invariant T (MAIT) cells in the context of liver cancer.
      • Duan M.
      • Goswami S.
      • Shi J.Y.
      • Wu L.J.
      • Wang X.Y.
      • Ma J.Q.
      • et al.
      Activated and exhausted MAIT cells foster disease progression and indicate poor outcome in hepatocellular carcinoma.
      MAIT cells are specialised innate-like T cells that account for 10% of CD4+ circulating T cells and 50% of all T cells in the normal human liver.
      • Duan M.
      • Goswami S.
      • Shi J.Y.
      • Wu L.J.
      • Wang X.Y.
      • Ma J.Q.
      • et al.
      Activated and exhausted MAIT cells foster disease progression and indicate poor outcome in hepatocellular carcinoma.
      ,
      • Kurioka A.
      • Ussher J.E.
      • Cosgrove C.
      • Clough C.
      • Fergusson J.R.
      • Smith K.
      • et al.
      MAIT cells are licensed through granzyme exchange to kill bacterially sensitized targets.
      Single-cell analysis of MAIT cells in HCC, adjacent liver and peripheral blood revealed an effector memory phenotype of MAIT cells in tumours, with an activated status and potentially decreased effector functions,
      • Duan M.
      • Goswami S.
      • Shi J.Y.
      • Wu L.J.
      • Wang X.Y.
      • Ma J.Q.
      • et al.
      Activated and exhausted MAIT cells foster disease progression and indicate poor outcome in hepatocellular carcinoma.
      as well as downregulation of “liver homing receptors” CCR6, CCR9 and CXCR6. This suggests a possible mechanism for the decreased absolute number within the tumour. Furthermore, intratumoural MAIT cells express significantly higher levels of PD-1, T-cell immunoglobulin mucin family member 3 (TIM-3) and CTLA-4.
      • Duan M.
      • Goswami S.
      • Shi J.Y.
      • Wu L.J.
      • Wang X.Y.
      • Ma J.Q.
      • et al.
      Activated and exhausted MAIT cells foster disease progression and indicate poor outcome in hepatocellular carcinoma.

      Spatial distribution

      Spatial transcriptomics and single-cell genomics approaches are highly complementary, because positional information on single cells within the morphological context of a tumour is lost during cellular dissociation prior to sequencing, while spatial transcriptomics cannot currently resolve transcriptomic profiles at single-cell resolution. One way to generate the spatially resolved whole transcriptome is to apply spatially barcoded capture probes – that bind to mRNA and synthesise complementary DNA – to fresh-frozen tissue sections.
      • Maniatis S.
      • Äijö T.
      • Vickovic S.
      • Braine C.
      • Kang K.
      • Mollbrink A.
      • et al.
      Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis.
      But each barcoded spot may contain several cells. Another way is to perform scRNA-seq of tissues from multiple regions of a tumour. In a recent study focusing on spatial distribution and clonal evolution in HCC, scRNA-seq was performed on 3 to 4 different tumour regions from 2 patients with HCC and described 2 opposing phenomena; for 1 patient, cells from all regions were distributed across all clusters, suggesting that tumour cells were transcriptomically similar despite coming from different locations within the tumour. For the other patient, cells from different regions remained separated based on clustering, suggesting different transcriptomic profiles from cells of different regions of the tumour.
      • Losic B.
      • Craig A.J.
      • Villacorta-Martin C.
      • Martins-Filho S.N.
      • Akers N.
      • Chen X.
      • et al.
      Intratumoral heterogeneity and clonal evolution in liver cancer.
      To conclude that the patient with no regional clustering had less ITH than the other, the authors labelled the cells based on their enrichment in well-known HCC molecular subclasses.
      • Hoshida Y.
      • Nijman S.M.
      • Kobayashi M.
      • Chan J.A.
      • Brunet J.P.
      • Chiang D.Y.
      • et al.
      Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma.
      A higher heterogeneity of the intratumoural subpopulations of patient 2 was demonstrated by the lack of uniformity in molecular classification across individual cells. Analysis of transcription factors revealed that even though key regulatory transcription factors were ubiquitously turned on, there was a high degree of regionality in activation patterns.
      • Losic B.
      • Craig A.J.
      • Villacorta-Martin C.
      • Martins-Filho S.N.
      • Akers N.
      • Chen X.
      • et al.
      Intratumoral heterogeneity and clonal evolution in liver cancer.
      Since heterogeneity encompasses not only tumour cells themselves but also the microenvironment, a detailed analysis of the immune cell composition on a single-cell level using CyTOF was performed, revealing 40 different immune cell clusters of all tumour-infiltrating immune cells.
      • Zhang Q.
      • Lou Y.
      • Yang J.
      • Wang J.
      • Feng J.
      • Zhao Y.
      • et al.
      Integrated multiomic analysis reveals comprehensive tumour heterogeneity and novel immunophenotypic classification in hepatocellular carcinomas.
      Treg cells, B cells and macrophages were found in clusters composed of cells contributed mainly from the tumour samples, indicating a crucial role in the regulation of immunity within the TME. Cluster analysis of all samples formed 3 immune clusters: Cluster 2 (immunodeficient) defined by a reduced infiltration of lymphocytes and high frequencies of dendritic and NK cells, Cluster 3 (immunosuppressive) defined by high frequencies of Treg cells, regulatory B cells and M2 polarised macrophages, and Cluster 1 (immunocompetent) defined by relatively normal T cell infiltration with reduced B cell abundance. Consistently, the expression of exhaustion markers such as PD-1, programmed cell death ligand 1 (PD-L1), TIM-3 and CTLA-4 was highest in Cluster 3. Interestingly, this classification is applicable to all intratumoural lesions indicating that there is no ITH on this level.
      • Zhang Q.
      • Lou Y.
      • Yang J.
      • Wang J.
      • Feng J.
      • Zhao Y.
      • et al.
      Integrated multiomic analysis reveals comprehensive tumour heterogeneity and novel immunophenotypic classification in hepatocellular carcinomas.
      This is an important consideration for therapy.
      Another study investigated spatial distribution using TCR sequencing analysis.
      • Shi L.
      • Zhang Y.
      • Feng L.
      • Wang L.
      • Rong W.
      • Wu F.
      • et al.
      Multi-omics study revealing the complexity and spatial heterogeneity of tumor-infiltrating lymphocytes in primary liver carcinoma.
      Comparing sequence overlap of the T cell repertoire, they found more similarities of T cell clonality between different tumour regions than compared to the adjacent liver and the peripheral blood. However, significant heterogeneity (ranging from 76–92%) in TCR repertoires was present between spatially distinct tumour locations (still within 1 tumour lesion). Only 8–24% were considered ubiquitous, indicating that TIL populations are spatially heterogenous within a tumour and the degree of heterogeneity is significantly different between patients.
      • Shi L.
      • Zhang Y.
      • Feng L.
      • Wang L.
      • Rong W.
      • Wu F.
      • et al.
      Multi-omics study revealing the complexity and spatial heterogeneity of tumor-infiltrating lymphocytes in primary liver carcinoma.
      Interestingly, non-synonymous mutations, that are known to influence T cell activation,
      • Rooney M.S.
      • Shukla S.A.
      • Wu C.J.
      • Getz G.
      • Hacohen N.
      Molecular and genetic properties of tumors associated with local immune cytolytic activity.
      did not correlate with the TCR repertoire within a region. It has previously been assumed that ITH is not entirely captured by somatic mutations alone and that the immune system is a major contributor.
      • Losic B.
      • Craig A.J.
      • Villacorta-Martin C.
      • Martins-Filho S.N.
      • Akers N.
      • Chen X.
      • et al.
      Intratumoral heterogeneity and clonal evolution in liver cancer.
      ,
      • Jamal-Hanjani M.
      • Wilson G.A.
      • McGranahan N.
      • Birkbak N.J.
      • Watkins T.B.K.
      • Veeriah S.
      • et al.
      Tracking the evolution of non-small-cell lung cancer.
      This contradicts the assumption that we gained from melanoma and NSCLC studies showing that a higher mutational load corresponds with patient response to immunotherapy.
      • Snyder A.
      • Makarov V.
      • Merghoub T.
      • Yuan J.
      • Zaretsky J.M.
      • Desrichard A.
      • et al.
      Genetic basis for clinical response to CTLA-4 blockade in melanoma.
      ,
      • Rizvi N.A.
      • Hellmann M.D.
      • Snyder A.
      • Kvistborg P.
      • Makarov V.
      • Havel J.J.
      • et al.
      Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer.
      • Le D.T.
      • Durham J.N.
      • Smith K.N.
      • Wang H.
      • Bartlett B.R.
      • Aulakh L.K.
      • et al.
      Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade.
      • McGranahan N.
      • Furness A.J.
      • Rosenthal R.
      • Ramskov S.
      • Lyngaa R.
      • Saini S.K.
      • et al.
      Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade.
      This spatial distribution in the TCR repertoire is of major importance when it comes to tumour specific T cell therapy and shows the importance of taking several biopsies, since only 10% of the T cell clones were shared between different tumour regions and even less were ubiquitous.
      • Shi L.
      • Zhang Y.
      • Feng L.
      • Wang L.
      • Rong W.
      • Wu F.
      • et al.
      Multi-omics study revealing the complexity and spatial heterogeneity of tumor-infiltrating lymphocytes in primary liver carcinoma.
      ,
      • Tran E.
      • Robbins P.F.
      • Lu Y.C.
      • Prickett T.D.
      • Gartner J.J.
      • Jia L.
      • et al.
      T-cell transfer therapy targeting mutant KRAS in cancer.
      Besides spatial differences, a single biopsy also may not capture changes in heterogeneity over time. This would require sequential biopsies, which are limited because of issues with tissue access. However, they might be important when it comes to tumour development and progression.
      • Li S.C.
      • Tachiki L.M.
      • Kabeer M.H.
      • Dethlefs B.A.
      • Anthony M.J.
      • Loudon W.G.
      Cancer genomic research at the crossroads: realizing the changing genetic landscape as intratumoral spatial and temporal heterogeneity becomes a confounding factor.
      Sequential evolution is most likely the source of heterogeneity in liver cancer. To investigate this, access to low-grade, high-grade, early and advanced lesions would be necessary.
      • JU Marquardt
      • Andersen J.B.
      • Thorgeirsson S.S.
      Functional and genetic deconstruction of the cellular origin in liver cancer.
      A better understanding of molecular mechanisms and especially the temporal dynamics that drive HCC progression under therapy are crucial for the development of therapeutic options and individualised medicine. To address this problem, 1 group developed a method using sequential flow cytometry analyses and scRNA-seq of circulating tumour cells.
      • D'Avola D.
      • Villacorta-Martin C.
      • Martins-Filho S.N.
      • Craig A.
      • Labgaa I.
      • von Felden J.
      • et al.
      High-density single cell mRNA sequencing to characterize circulating tumor cells in hepatocellular carcinoma.
      Circulating tumour cells were stained for HCC-specific markers and imaged using the imagestream platform. Subsequently, scRNA-seq enabled the identification of driver genes and molecular heterogeneity in these cells.
      • D'Avola D.
      • Villacorta-Martin C.
      • Martins-Filho S.N.
      • Craig A.
      • Labgaa I.
      • von Felden J.
      • et al.
      High-density single cell mRNA sequencing to characterize circulating tumor cells in hepatocellular carcinoma.
      This might be useful to detect novel gene mutations that develop during HCC evolution under therapy.
      The evidence of heterogeneity in immune cell composition and spatial distribution is a crucial factor to consider when it comes to immunotherapy. These studies provide a rationale for the combination of multiple checkpoint inhibitors to overcome resistance (Fig. 5). Some of the most investigated combinations incorporate an anti-PD-1/anti-PD-L1 antibody plus an anti-CTLA-4 antibody, with promising response rates of 40–60% achieved in melanoma, NSCLC and renal cancer.
      • Motzer R.J.
      • Tannir N.M.
      • McDermott D.F.
      • Aren Frontera O.
      • Melichar B.
      • Choueiri T.K.
      • et al.
      Nivolumab plus ipilimumab versus sunitinib in advanced renal-cell carcinoma.
      • Wolchok J.D.
      • Chiarion-Sileni V.
      • Gonzalez R.
      • Rutkowski P.
      • Grob J.J.
      • Cowey C.L.
      • et al.
      Overall survival with combined nivolumab and ipilimumab in advanced melanoma.
      • Hellmann M.D.
      • Paz-Ares L.
      • Bernabe Caro R.
      • Zurawski B.
      • Kim S.W.
      • Carcereny Costa E.
      • et al.
      Nivolumab plus ipilimumab in advanced non-small-cell lung cancer.
      However, overall response rates for advanced non-resectable HCC range between 15% and 31%.
      • Yau T.
      • Kang Y.-K.
      • Kim T.-Y.
      • El-Khoueiry A.B.
      • Santoro A.
      • Sangro B.
      • et al.
      Nivolumab (NIVO) + ipilimumab (IPI) combination therapy in patients (pts) with advanced hepatocellular carcinoma (aHCC): results from CheckMate 040.
      ,
      • Kelley R.K.
      • Abou-Alfa G.K.
      • Bendell J.C.
      • Kim T.-Y.
      • Borad M.J.
      • Yong W.-P.
      • et al.
      Phase I/II study of durvalumab and tremelimumab in patients with unresectable hepatocellular carcinoma (HCC): phase I safety and efficacy analyses.
      So far, clinical trials have failed to identify prognostic markers for therapeutic response that are robust enough to stratify patients.
      • Heinrich S.
      • Castven D.
      • Galle P.R.
      • JU Marquardt
      Translational considerations to improve response and overcome therapy resistance in immunotherapy for hepatocellular carcinoma.
      Much less is known about mechanisms leading to therapeutic resistance. High PD-L1 expression is associated with response to immunotherapy in NSCLC and melanoma.
      • Herbst R.S.
      • Soria J.C.
      • Kowanetz M.
      • Fine G.D.
      • Hamid O.
      • Gordon M.S.
      • et al.
      Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients.
      • Daud A.I.
      • Wolchok J.D.
      • Robert C.
      • Hwu W.J.
      • Weber J.S.
      • Ribas A.
      • et al.
      Programmed death-ligand 1 expression and response to the anti-programmed death 1 antibody pembrolizumab in melanoma.
      • Topalian S.L.
      • Hodi F.S.
      • Brahmer J.R.
      • Gettinger S.N.
      • Smith D.C.
      • McDermott D.F.
      • et al.
      Safety, activity, and immune correlates of anti-PD-1 antibody in cancer.
      Further, mismatch repair-deficiency is associated with PD-1 response in 12 tumour entities,
      • Le D.T.
      • Durham J.N.
      • Smith K.N.
      • Wang H.
      • Bartlett B.R.
      • Aulakh L.K.
      • et al.
      Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade.
      but is not very common in HCC.
      • Goumard C.
      • Desbois-Mouthon C.
      • Wendum D.
      • Calmel C.
      • Merabtene F.
      • Scatton O.
      • et al.
      Low levels of microsatellite instability at simple repeated sequences commonly occur in human hepatocellular carcinoma.
      However, this could only be partially confirmed in clinical trials for patients with advanced HCC.
      • El-Khoueiry A.B.
      • Sangro B.
      • Yau T.
      • Crocenzi T.S.
      • Kudo M.
      • Hsu C.
      • et al.
      Nivolumab in patients with advanced hepatocellular carcinoma (CheckMate 040): an open-label, non-comparative, phase 1/2 dose escalation and expansion trial.
      We urgently need a deeper understanding of cellular interactions on a single-cell level to dissect mechanisms of resistance to immunotherapy in HCC.

      Conclusion and future direction

      Single-cell technology has revolutionised our understanding of tumour biology. While we are entering an exciting era, critical challenges remain. The first of which relates to technical limitations. While single-cell measurements of mRNA, mutations, CNV, chromatin accessibility, DNA methylation and histone modifications provide rich information about cellular activities, they are usually carried out in different cells. Although efforts have been made to perform 2 different measurements in the same single-cell,
      • Cao J.
      • Cusanovich D.A.
      • Ramani V.
      • Aghamirzaie D.
      • Pliner H.A.
      • Hill A.J.
      • et al.
      Joint profiling of chromatin accessibility and gene expression in thousands of single cells.
      • Moffitt J.R.
      • Bambah-Mukku D.
      • Eichhorn S.W.
      • Vaughn E.
      • Shekhar K.
      • Perez J.D.
      • et al.
      Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region.
      • Angermueller C.
      • Clark S.J.
      • Lee H.J.
      • Macaulay I.C.
      • Teng M.J.
      • Hu T.X.
      • et al.
      Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity.
      there is still a long way to go before several measurements can be generated experimentally from an individual cell. Additionally, the spatial context of a single cell is informative in determining its interactions with adjacent cells. However, technical advances are needed to integrate this information with the genetic/epigenetic measurements from a single cell.
      • Maniatis S.
      • Äijö T.
      • Vickovic S.
      • Braine C.
      • Kang K.
      • Mollbrink A.
      • et al.
      Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis.
      ,
      • Ståhl P.L.
      • Salmén F.
      • Vickovic S.
      • Lundmark A.
      • Navarro J.F.
      • Magnusson J.
      • et al.
      Visualization and analysis of gene expression in tissue sections by spatial transcriptomics.
      Another technical limitation is the sparseness of single-cell data. For example, in scRNA-seq, dropout issues occur due to library preparation, sequencing depth or real biological state. Moreover, single-cell sequencing comes with higher costs and the risk of substantial sequencing artefacts.
      • Fittall M.W.
      • Van Loo P.
      Translating insights into tumor evolution to clinical practice: promises and challenges.
      ,
      • Navin N.E.
      Cancer genomics: one cell at a time.
      Second, the complicated tumour ecosystem poses significant biological challenges. The tumour cell population is highly heterogeneous both between tumours and within a tumour, making it difficult to determine tumour subpopulations as well as rare cell types, e.g. CSCs. Besides the nature of heterogeneity, tumour plasticity and the dynamic process of tumour evolution create great challenges in defining a tumour ecosystem. In addition to tumour cells, other cells, e.g. T cells, in the TME are also very complicated. While the lineage commitment of CD4+ or CD8+ T cells is irreversible, other specified lineage commitments may be more plastic than previously expected.
      • Bluestone J.A.
      • Mackay C.R.
      • O'shea J.J.
      • Stockinger B.
      The functional plasticity of T cell subsets.
      Nevertheless, the puzzle of tumour biology might be solved by searching for the key to the creation of such an intricate ecosystem rather than focusing on the phenomenon of tumour heterogeneity and plasticity.
      While our understanding of tumour biology has been greatly advanced by computational approaches developed for single-cell data, there remains much room to develop new methods to address different biological questions. Algorithms have been developed to integrate scATAC-seq data and scRNA-seq data, or spatial data and scRNA-seq data, for joint analysis.
      • Bluestone J.A.
      • Mackay C.R.
      • O'shea J.J.
      • Stockinger B.
      The functional plasticity of T cell subsets.
      More efforts are needed to integrate multi-omics data for the in-depth study of cellular mechanisms. In addition, dropout issues in single-cell datasets create critical problems for downstream analysis, including data normalisation, dimensional reduction and clustering. Developing methods specially for the sparse single-cell data would be very useful. Novel machine-learning strategies are clearly needed to overcome these challenges.
      Single-cell technology has vast implications for immunotherapy in HCC. Future combination therapies need to find a balance between additive and synergistic effects in contrast to toxic effects. Recent therapeutic approaches include combinations of anti-angiogenics, checkpoint inhibitors or local ablative treatments with immunotherapy.
      • Duffy A.G.
      • Ulahannan S.V.
      • Makorova-Rusher O.
      • Rahma O.
      • Wedemeyer H.
      • Pratt D.
      • et al.
      Tremelimumab in combination with ablation in patients with advanced hepatocellular carcinoma.
      ,
      • Finn R.S.
      • Qin S.
      • Ikeda M.
      • Galle P.R.
      • Ducreux M.
      • Kim T.Y.
      • et al.
      Atezolizumab plus bevacizumab in unresectable hepatocellular carcinoma.
      ,
      • Floudas C.S.
      • Xie C.
      • Brar G.
      • Morelli M.P.
      • Fioravanti S.
      • Walker M.
      • et al.
      Combined immune checkpoint inhibition (ICI) with tremelimumab and durvalumab in patients with advanced hepatocellular carcinoma (HCC) or biliary tract carcinomas (BTC).
      Combining chimeric antigen receptor T cells with checkpoint inhibitors might be another step to improve responses and patient outcomes in advanced HCC.
      • Zhang Q.
      • Zhang Z.
      • Peng M.
      • Fu S.
      • Xue Z.
      • Zhang R.
      CAR-T cell therapy in gastrointestinal tumors and hepatic carcinoma: from bench to bedside.
      • Gao H.
      • Li K.
      • Tu H.
      • Pan X.
      • Jiang H.
      • Shi B.
      • et al.
      Development of T cells redirected to glypican-3 for the treatment of hepatocellular carcinoma.
      • Yu M.
      • Luo H.
      • Fan M.
      • Wu X.
      • Shi B.
      • Di S.
      • et al.
      Development of GPC3-specific chimeric antigen receptor-engineered natural killer cells for the treatment of hepatocellular carcinoma.
      • Jiang Z.
      • Jiang X.
      • Chen S.
      • Lai Y.
      • Wei X.
      • Li B.
      • et al.
      Anti-GPC3-CAR T cells suppress the growth of tumor cells in patient-derived xenografts of hepatocellular carcinoma.
      The immune cell profile, individual neoantigen presentation and genomic alterations of the tumour itself may be the key to individualised medicine.
      The recent single-cell studies reviewed herein are beginning to reveal a network of cellular interactions in the tumour immune landscape that may improve our understanding of resistance mechanisms and lead to the development of ideal combination therapies (Fig. 5). Ideally, single-cell analysis would be used to identify a detailed cellular atlas for each patient, but this is still a concept for the future. A step in this direction might be offered by the application of CIBERSORTx, which enables the deconvolution of the immune cell composition using bulk sequencing data.
      • Newman A.M.
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      • et al.
      Determining cell type abundance and expression from bulk tissues with digital cytometry.
      ,
      • Rohr-Udilova N.
      • Klinglmüller F.
      • Schulte-Hermann R.
      • Stift J.
      • Herac M.
      • Salzmann M.
      • et al.
      Deviations of the immune cell landscape between healthy liver and hepatocellular carcinoma.
      Despite existing challenges, single-cell technologies have tremendous potential. Future research on liver cancer from a single-cell perspective will require interdisciplinary collaborations between experts in tumour biology, immunology, technique development and computational biology. The mechanistic understanding of varying responses to immunotherapy will also benefit from the comprehensive single-cell profiling of liver cancer. Moreover, the answers to many cancer-related questions will be found as single-cell techniques and computational approaches improve, paving the way for precision oncology.

      Abbreviations

      AML, acute myeloid leukaemia; ATAC-seq, Transposase-Accessible Chromatin sequencing; CSC, cancer stem cell; CTLA4, cytotoxic T lymphocyte-associated protein 4; CyTOF, cytometry by time of flight; EPCAM, epithelial cell adhesion molecule; HCC, hepatocellular carcinoma; MAIT, mucosal-associated invariant T; NK, natural killer; NGS, next-generation sequencing; NSCLC, non-small-lung cancer; PD-1, programmed cell death 1; PD-L1, programmed cell death ligand 1; ScRNA-seq, single-cell RNA sequencing; TACE, transarterial chemoembolisation; TCR, T cell receptor; TIL, tumour-infiltrating lymphocytes; TIM3, T-cell immunoglobulin mucin family member 3; TME, tumour microenvironment; Treg, regulatory T; VEGFA, vascular endothelial growth factor A.

      Financial support

      This work was supported by grants ( ZIA-BC010313 , ZIA-BC010876 , ZIA BC010877 , and ZIA BC011870 ) from the Intramural Research Program of the Center for Cancer Research of the National Cancer Institute .

      Authors’ contributions

      SH, AJC, BH, LM, TFG and XWW contributed to the literature research and writing of the manuscript. Figures were generated by SH. XWW designed and supervised the research process and the manuscript preparation. All authors have read and agreed to the published version of the manuscript.

      Conflict of interest

      The authors declare no conflict of interest.
      Please refer to the accompanying ICMJE disclosure forms for further details.

      Supplementary data

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