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Single-cell RNA-sequencing reveals distinct patterns of cell state heterogeneity in mouse models of breast cancer.

ABSTRACT: Breast cancer stem cells (BCSCs) contribute to intra-tumoral heterogeneity and therapeutic resistance. However, the binary concept of universal BCSCs co-existing with bulk tumor cells is over-simplified. Through single-cell RNA-sequencing, we found that Neu, PyMT and BRCA1-null mammary tumors each corresponded to a spectrum of minimally overlapping cell differentiation states without a universal BCSC population. Instead, our analyses revealed that these tumors contained distinct lineage-specific tumor propagating cells (TPCs) and this is reflective of the self-sustaining capabilities of lineage-specific stem/progenitor cells in the mammary epithelial hierarchy. By understanding the respective tumor hierarchies, we were able to identify CD14 as a TPC marker in the Neu tumor. Additionally, single-cell breast cancer subtype stratification revealed the co-existence of multiple breast cancer subtypes within tumors. Collectively, our findings emphasize the need to account for lineage-specific TPCs and the hierarchical composition within breast tumors, as these heterogenous sub-populations can have differential therapeutic susceptibilities.

SUBMITTER: Yeo SK

PROVIDER: S-EPMC7447441 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Single-cell RNA-sequencing reveals distinct patterns of cell state heterogeneity in mouse models of breast cancer.

Yeo Syn Kok SK Zhu Xiaoting X Okamoto Takako T Hao Mingang M Wang Cailian C Lu Peixin P Lu Long Jason LJ Guan Jun-Lin JL

eLife 20200825

Breast cancer stem cells (BCSCs) contribute to intra-tumoral heterogeneity and therapeutic resistance. However, the binary concept of universal BCSCs co-existing with bulk tumor cells is over-simplified. Through single-cell RNA-sequencing, we found that Neu, PyMT and BRCA1-null mammary tumors each corresponded to a spectrum of minimally overlapping cell differentiation states without a universal BCSC population. Instead, our analyses revealed that these tumors contained distinct lineage-specific ...[more]

PMID: 32840210

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Project description:Background & aimsThe multiple vital functions of the human liver are performed by highly specialised parenchymal and non-parenchymal cells organised in complex collaborative sinusoidal units. Although crucial for homeostasis, the cellular make-up of the human liver remains to be fully elucidated. Here, single-cell RNA-sequencing was used to unravel the heterogeneity of human liver cells, in particular of hepatocytes (HEPs) and hepatic stellate cells (HSCs).MethodThe transcriptome of ~25,000 freshly isolated human liver cells was profiled using droplet-based RNA-sequencing. Recently published data sets and RNA in situ hybridisation were integrated to validate and locate newly identified cell populations.ResultsIn total, 22 cell populations were annotated that reflected the heterogeneity of human parenchymal and non-parenchymal liver cells. More than 20,000 HEPs were ordered along the portocentral axis to confirm known, and reveal previously undescribed, zonated liver functions. The existence of 2 subpopulations of human HSCs with unique gene expression signatures and distinct intralobular localisation was revealed (i.e. portal and central vein-concentrated GPC3 + HSCs and perisinusoidally located DBH + HSCs). In particular, these data suggest that, although both subpopulations collaborate in the production and organisation of extracellular matrix, GPC3 + HSCs specifically express genes involved in the metabolism of glycosaminoglycans, whereas DBH + HSCs display a gene signature that is reminiscent of antigen-presenting cells.ConclusionsThis study highlights metabolic zonation as a key determinant of HEP transcriptomic heterogeneity and, for the first time, outlines the existence of heterogeneous HSC subpopulations in the human liver. These findings call for further research on the functional implications of liver cell heterogeneity in health and disease.Lay summaryThis study resolves the cellular landscape of the human liver in an unbiased manner and at high resolution to provide new insights into human liver cell biology. The results highlight the physiological heterogeneity of human hepatic stellate cells.

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Single-cell RNA-sequencing reveals distinct patterns of cell state heterogeneity in mouse models of breast cancer.

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Single-cell RNA-sequencing reveals distinct patterns of cell state heterogeneity in mouse models of breast cancer.

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