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University of Pennsylvania

Single-Cell Lineage Tracing Of Cancer Metastasis

Abstract

dc:description.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.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Simeonov, Kamen
Advisor dc:contributor.advisor
  • Christopher Lengner

Rights

dc:rights
Statement dc:rights
  • Kamen Simeonov
Language dc:language
en

Identifiers

dc:identifier.*
Repository record dc:identifier.uri
https://repository.upenn.edu/handle/20.500.14332/31993
OAI identifier oai:identifier
oai:repository.upenn.edu:20.500.14332/31993

Chain of custody

source
Harvested from
University of Pennsylvania
Base URL
repository.upenn.edu/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Simeonov, Kamen. Single-Cell Lineage Tracing Of Cancer Metastasis. 2021. https://repository.upenn.edu/handle/20.500.14332/31993