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Paired-cell sequencing enables spatial gene expression mapping of liver endothelial cells.

ABSTRACT: Spatially resolved single-cell RNA sequencing (scRNAseq) is a powerful approach for inferring connections between a cell's identity and its position in a tissue. We recently combined scRNAseq with spatially mapped landmark genes to infer the expression zonation of hepatocytes. However, determining zonation of small cells with low mRNA content, or without highly expressed landmark genes, remains challenging. Here we used paired-cell sequencing, in which mRNA from pairs of attached mouse cells were sequenced and gene expression from one cell type was used to infer the pairs' tissue coordinates. We applied this method to pairs of hepatocytes and liver endothelial cells (LECs). Using the spatial information from hepatocytes, we reconstructed LEC zonation and extracted a landmark gene panel that we used to spatially map LEC scRNAseq data. Our approach revealed the expression of both Wnt ligands and the Dkk3 Wnt antagonist in distinct pericentral LEC sub-populations. This approach can be used to reconstruct spatial expression maps of non-parenchymal cells in other tissues.

SUBMITTER: Halpern KB

PROVIDER: S-EPMC6546596 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Paired-cell sequencing enables spatial gene expression mapping of liver endothelial cells.

Halpern Keren Bahar KB Shenhav Rom R Massalha Hassan H Toth Beata B Egozi Adi A Massasa Efi E EE Medgalia Chiara C David Eyal E Giladi Amir A Moor Andreas E AE Porat Ziv Z Amit Ido I Amit Ido I Itzkovitz Shalev S

Nature biotechnology 20180917 10

Spatially resolved single-cell RNA sequencing (scRNAseq) is a powerful approach for inferring connections between a cell's identity and its position in a tissue. We recently combined scRNAseq with spatially mapped landmark genes to infer the expression zonation of hepatocytes. However, determining zonation of small cells with low mRNA content, or without highly expressed landmark genes, remains challenging. Here we used paired-cell sequencing, in which mRNA from pairs of attached mouse cells wer ...[more]

PMID: 30222169

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Project description:BackgroundAccumulating evidence supports that tumor growth and cancer relapse are driven by cancer stem cells. Our previous work has demonstrated the existence of CD90(+) liver cancer stem cells (CSCs) in hepatocellular carcinoma (HCC). Nevertheless, the characteristics of these cells are still poorly understood. In this study, we employed a more sensitive RNA-sequencing (RNA-Seq) to compare the gene expression profiling of CD90(+) cells sorted from tumor (CD90(+)CSCs) with parallel non-tumorous liver tissues (CD90(+)NTSCs) and elucidate the roles of putative target genes in hepatocarcinogenesis.Methodology/principal findingsCD90(+) cells were sorted respectively from tumor and adjacent non-tumorous human liver tissues using fluorescence-activated cell sorting. The amplified RNAs of CD90(+) cells from 3 HCC patients were subjected to RNA-Seq analysis. A differential gene expression profile was established between CD90(+)CSCs and CD90(+)NTSCs, and validated by quantitative real-time PCR (qRT-PCR) on the same set of amplified RNAs, and further confirmed in an independent cohort of 12 HCC patients. Five hundred genes were differentially expressed (119 up-regulated and 381 down-regulated genes) between CD90(+)CSCs and CD90(+)NTSCs. Gene ontology analysis indicated that the over-expressed genes in CD90(+)CSCs were associated with inflammation, drug resistance and lipid metabolism. Among the differentially expressed genes, glypican-3 (GPC3), a member of glypican family, was markedly elevated in CD90(+)CSCs compared to CD90(+)NTSCs. Immunohistochemistry demonstrated that GPC3 was highly expressed in forty-two human liver tumor tissues but absent in adjacent non-tumorous liver tissues. Flow cytometry indicated that GPC3 was highly expressed in liver CD90(+)CSCs and mature cancer cells in liver cancer cell lines and human liver tumor tissues. Furthermore, GPC3 expression was positively correlated with the number of CD90(+)CSCs in liver tumor tissues.Conclusions/significanceThe identified genes, such as GPC3 that are distinctly expressed in liver CD90(+)CSCs, may be promising gene candidates for HCC therapy without inducing damages to normal liver stem cells.

Project description:BackgroundNumerous studies have used multi-region sampling approaches to characterize intra-tumor heterogeneity (ITH) in hepatocellular carcinoma (HCC). However, conventional multi-region sampling strategies do not preserve the spatial details of samples, and thus, the potential influences of spatial distribution on patient-wise ITH (represents the overall heterogeneity level of the tumor in a given patient) have long been overlooked. Furthermore, gene-wise transcriptional ITH (represents the expression pattern of genes across different intra-tumor regions) in HCC is also under-explored, highlighting the need for a comprehensive investigation.MethodsTo address the problem of spatial information loss, we propose a simple and easy-to-implement strategy called spatial localization sampling (SLS). We performed multi-region sampling and sequencing on 14 patients with HCC, collecting a total of 75 tumor samples with spatial information and molecular data. Normalized diversity score and integrated heterogeneity score (IHS) were then developed to measure patient-wise and gene-wise ITH, respectively.ResultsA significant correlation between spatial and molecular heterogeneity was uncovered, implying that spatial distribution of sampling sites did influence ITH estimation in HCC. We demonstrated that the normalized diversity score had the ability to overcome sampling location bias and provide a more accurate estimation of patient-wise ITH. According to this metric, HCC tumors could be divided into two classes (low-ITH and high-ITH tumors) with significant differences in multiple biological properties. Through IHS analysis, we revealed a highly heterogenous immune microenvironment in HCC and identified some low-ITH checkpoint genes with immunotherapeutic potential. We also constructed a low-heterogeneity risk stratification (LHRS) signature based on the IHS results which could accurately predict the survival outcome of patients with HCC on a single tumor biopsy sample.ConclusionsThis study provides new insights into the complex phenotypes of HCC and may serve as a guide for future studies in this field.

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Paired-cell sequencing enables spatial gene expression mapping of liver endothelial cells.

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Paired-cell sequencing enables spatial gene expression mapping of liver endothelial cells.

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