Transcriptional census of epithelial-mesenchymal plasticity in cancer

Cook, David P.; Vanderhyden, Barbara C.

doi:10.1101/2021.03.05.434142

Cited by 4 publications

(5 citation statements)

References 65 publications

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“…Using TCGA data 66 , we indeed found that expression of the pEMT gene module is associated with decreased progression-free survival (Extended Data Fig. 16, see Methods) 67,68 .…”

Section: Recurring Gene Modules Across Diverse Cancer Typesmentioning

confidence: 88%

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Recurrence of cancer cell states across diverse tumors and their interactions with the microenvironment

Barkley¹,

Moncada²,

Pour³

et al. 2021

Preprint

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While genetic tumor heterogeneity has long been recognized, recent work has revealed significant variation among cancer cells at the epigenetic and transcriptional levels. Profiling tumors at the single-cell level in individual cancer types has shown that transcriptional heterogeneity is organized into cancer cell states, implying that diverse cell states may represent stable and functional units with complementary roles in tumor maintenance and progression. However, it remains unclear to what extent these states span tumor types, constituting general features of cancer. Furthermore, the role of cancer cell states in tumor progression and their specific interactions with cells of the tumor microenvironment remain to be elucidated. Here, we perform a pan-cancer single-cell RNA-Seq analysis across 15 cancer types and identify a catalog of 16 gene modules whose expression defines recurrent cancer cell states, including 'stress', 'interferon response', 'epithelial-mesenchymal transition', 'metal response', 'basal' and 'ciliated'. Using mouse models, we find that induction of the interferon response module varies by tumor location and is diminished upon elimination of lymphocytes. Moreover, spatial transcriptomic analysis further links the interferon response in cancer cells to T cells and macrophages in the tumor microenvironment. Our work provides a framework for studying how cancer cell states interact with the tumor microenvironment to form organized systems capable of immune evasion, drug resistance, and metastasis.

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“…Using TCGA data 66 , we indeed found that expression of the pEMT gene module is associated with decreased progression-free survival (Extended Data Fig. 16, see Methods) 67,68 .…”

Section: Recurring Gene Modules Across Diverse Cancer Typesmentioning

confidence: 88%

“…TCGA survival analysis. Scoring and survival analysis were performed as in Cook et al 68 . Expression profiles were obtained from https://gdc.cancer.gov/node/905, normalized and z-scored.…”

Section: Methodsmentioning

confidence: 99%

Recurrence of cancer cell states across diverse tumors and their interactions with the microenvironment

Barkley¹,

Moncada²,

Pour³

et al. 2021

Preprint

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“…EMP is likely a highly context and tumor type-specific process involving different signaling (6). Although the presence or proportion of intermediate EMP cells was not correlated with more metastasis in our models, we did find that high expression of intermediate EMP marker genes was associated with poorer outcomes in a subset of BC patients whereas a mesenchymal or epithelial gene expression did not show a subtype-specific correlation.…”

Section: Discussionmentioning

confidence: 99%

Dissecting the contributions of tumor heterogeneity on metastasis at single-cell resolution

Winkler

Tan

Diadhiou

et al. 2022

Preprint

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Metastasis is the leading cause of cancer-related deaths, but metastasis research is challenged by limited access to patient material and a lack of experimental models that appropriately recapitulate tumor heterogeneity. Here, we analyzed single-cell transcriptomes of matched primary tumor and metastasis from patient-derived xenograft models of breast cancer, demonstrating that primary tumor and metastatic cells show profound transcriptional differences across heterogeneous tumors. While primary tumor cells upregulated several metabolic genes, metastatic cells displayed a motility phenotype in micrometastatic lesions and increased stress response signaling during metastatic progression. Additionally, we identified gene signatures that are associated with the metastatic potential and correlated with patient outcomes. Poorly metastatic primary tumors showed increased immune-regulatory control that may prevent metastasis, whereas highly metastatic primary tumors upregulated markers of epithelial-mesenchymal transition (EMT). We found that intra-tumor heterogeneity is dominated by epithelial-mesenchymal plasticity (EMP) which presented as a dynamic continuum with intermediate cell states that were characterized by novel, specific markers. These intermediate EMP markers correlated with worse patient outcomes and could serve as potential new therapeutic targets to block metastatic development.

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“…Meta-analysis serves to find robust signatures across datasets with significant technical variation 15 , thereby determining what markers and properties are likely to generalize to new data. This meta-analytic atlas resolves technical limitations with individual batches to better represent the continuous nature of the system and provide strongly replicable signatures.…”

Section: Discussionmentioning

confidence: 99%

“…Replicability across many datasets resolves some technical limitations of individual scRNAseq datasets, creating a more robust atlas 13,14 . The most comprehensive and robust cell atlases rely on meta-analysis across many scRNAseq datasets to characterize replicable cell types [15][16][17][18] . After identifying the present cell types, characterizing their functions can be done by evaluating the signatures that define the cell types for known processes and pathways [19][20][21] .…”

Section: Introductionmentioning

confidence: 99%

A Meta-Analytic Single-Cell Atlas of Mouse Bone Marrow Hematopoietic Development

Harris

Lee

Gillis

2021

Preprint

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The clinical importance of the hematopoietic system makes it one of the most heavily studied lineages in all of biology. A clear understanding of the cell types and functional programs during hematopoietic development is central to research in aging, cancer, and infectious diseases. Known cell types are traditionally identified by the expression of proteins on the surface of the cells. Stem and progenitor cells defined based on these markers are assigned functions based on their lineage potential. The rapid growth of single cell RNA sequencing technologies (scRNAseq) provides a new modality for evaluating the cellular and functional landscape of hematopoietic stem and progenitor cells. The popularity of this technology among hematopoiesis researchers enables us to conduct a robust meta-analysis of mouse bone marrow scRNAseq data. Using over 300,000 cells across 12 datasets, we evaluate the classification and function of cell types based on discrete clustering, in silico FACS sorting, and a continuous trajectory. We identify replicable signatures that define cell types based on genes and known cellular functions. Additionally, we evaluate the conservation of signatures associated with erythroid and monocyte lineage development across species using co-expression networks. The co-expression networks predict the effectiveness of the signature at identifying erythroid and monocyte cells in zebrafish and human scRNAseq data. Together, this analysis provides a robust reference, particularly marker genes and functional annotations, for future experiments in hematopoietic development.

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Transcriptional census of epithelial-mesenchymal plasticity in cancer

Cited by 4 publications

References 65 publications

Recurrence of cancer cell states across diverse tumors and their interactions with the microenvironment

Recurrence of cancer cell states across diverse tumors and their interactions with the microenvironment

Dissecting the contributions of tumor heterogeneity on metastasis at single-cell resolution

A Meta-Analytic Single-Cell Atlas of Mouse Bone Marrow Hematopoietic Development

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