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

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

SUBMITTER: Zhang QY

PROVIDER: S-EPMC9294331 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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

Zhang Qing-Yang QY Ho Daniel Wai-Hung DW Tsui Yu-Man YM Ng Irene Oi-Lin IO

Cellular and molecular gastroenterology and hepatology 20220514 3

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 sing ...[more]

PMID: 35577269

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Project description:BackgroundThe progression of bladder cancer (BC) from non-muscle-invasive bladder cancer (NMIBC) to muscle-invasive bladder cancer (MIBC) significantly increases disease severity. Although the tumor microenvironment (TME) plays a pivotal role in this process, the heterogeneity of tumor cells and TME components remains underexplored.MethodsWe characterized the transcriptomes of single cells from 11 BC samples, including 4 NMIBC, 4 MIBC, and 3 adjacent normal tissues. Bulk RNA-seq data were used to validate the clinical features of characteristic cells, and protein levels of these cells were further confirmed through immunohistochemistry (IHC) and multiplex immunofluorescence.ResultsBladder cancer progression was associated with distinct transcriptomic features in the TME. Tumor cells in MIBC displayed enhanced glycolytic activity and downregulation of chemokines and MHC-II molecules, reducing immune cell recruitment and facilitating immune evasion. This highlights glycolysis as a potential therapeutic target for disrupting tumor progression. We identified a T cell exhaustion pathway from naive CD8 + T cells (CD8 + TCF7) to terminally exhausted CD8 + STMN1 cells, with progressively declining immune surveillance. Targeting intermediate exhaustion states may restore T cell function and improve anti-tumor immunity. Macrophages polarized toward a pro-tumorigenic phenotype, while VEGFA + mast cells promoted angiogenesis in early-stage BC, suggesting their role as potential targets for therapeutic intervention in NMIBC. Furthermore, conventional dendritic cells (DCs) transformed into LAMP3 + DCs, contributing to an immunosuppressive microenvironment and enabling immune evasion.ConclusionThis study reveals dynamic changes in the TME during BC progression, including enhanced glycolysis, T cell exhaustion, and immune cell remodeling, which contribute to immune evasion and tumor progression. These findings identify critical pathways and cell populations as potential therapeutic targets, offering new strategies to improve treatment outcomes in BC patients.

Project description:Similarities between stem cells and cancer cells have implicated mammary stem cells in breast carcinogenesis. Recent evidence suggests that normal breast stem cells exist in multiple phenotypic states: epithelial, mesenchymal, and hybrid epithelial/mesenchymal (E/M). Hybrid E/M cells in particular have been implicated in breast cancer metastasis and poor prognosis. Mounting evidence also suggests that stem cell phenotypes change throughout the life course, for example, through embryonic development and pregnancy. The goal of this study was to use single cell RNA-sequencing to quantify cell state distributions of the normal mammary (NM) gland throughout developmental stages and when perturbed into a stem-like state in vitro using conditional reprogramming (CR). Using machine learning based dataset alignment, we integrate multiple mammary gland single cell RNA-seq datasets from human and mouse, along with bulk RNA-seq data from breast tumors in the Cancer Genome Atlas (TCGA), to interrogate hybrid stem cell states in the normal mammary gland and cancer. CR of human mammary cells induces an expanded stem cell state, characterized by increased expression of embryonic stem cell associated genes. Alignment to a mouse single-cell transcriptome atlas spanning mammary gland development from in utero to adulthood revealed that NM cells align to adult mouse cells and CR cells align across the pseudotime trajectory with a stem-like population aligning to the embryonic mouse cells. Three hybrid populations emerge after CR that are rare in NM: KRT18+/KRT14+ (hybrid luminal/basal), EPCAM+/VIM+ (hybrid E/M), and a quadruple positive population, expressing all four markers. Pseudotime analysis and alignment to the mouse developmental trajectory revealed that E/M hybrids are the most developmentally immature. Analyses of single cell mouse mammary RNA-seq throughout pregnancy show that during gestation, there is an enrichment of hybrid E/M cells, suggesting that these cells play an important role in mammary morphogenesis during lactation. Finally, pseudotime analysis and alignment of TCGA breast cancer expression data revealed that breast cancer subtypes express distinct developmental signatures, with basal tumors representing the most "developmentally immature" phenotype. These results highlight phenotypic plasticity of normal mammary stem cells and provide insight into the relationship between hybrid cell populations, stemness, and cancer.

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

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

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