Transcriptomics

Dataset Information

0

Single-cell lineage tracing of metastatic cancer reveals selection of hybrid EMT states


ABSTRACT: The underpinnings of cancer metastasis remain poorly understood, in part due to a lack of tools for probing their emergence at high resolution. Here we present macsGESTALT, an inducible CRISPR-Cas9-based lineage recorder with highly efficient single-cell capture of both transcriptional and phylogenetic information. Applying macsGESTALT to a mouse model of metastatic pancreatic cancer, we recover ~380,000 CRISPR target sites and reconstruct dissemination of ~28,000 single cells across multiple metastatic sites. We find cells occupy a continuum of epithelial-to-mesenchymal transition (EMT) states. Metastatic potential peaks in rare, late-hybrid EMT states, which are aggressively selected from a predominately epithelial ancestral pool. The gene signatures of these late-hybrid EMT states are predictive of reduced survival in both human pancreatic and lung cancer patients, highlighting their relevance to clinical disease progression. Finally, we observe evidence for in vivo propagation of S100 family gene expression across clonally distinct metastatic subpopulations.

ORGANISM(S): Mus musculus

PROVIDER: GSE173958 | GEO | 2021/06/09

REPOSITORIES: GEO

Similar Datasets

2022-10-07 | GSE206657 | GEO
2022-10-07 | GSE206656 | GEO
2021-04-13 | GSE164612 | GEO
2022-10-07 | GSE206658 | GEO
2018-02-15 | GSE110586 | GEO
2018-02-15 | GSE110585 | GEO
2018-02-15 | GSE110584 | GEO
2023-12-13 | MODEL2208050002 | BioModels
2022-02-15 | GSE172609 | GEO
2022-02-15 | GSE172608 | GEO