Emergence of a High-Plasticity Cell State during Lung Cancer Evolution
Name
nihms-1612080.pdf
Description
Accepted version
Size
3.51 MB
Format
Unknown
Checksum (MD5)
81998c113d668cb78e4ee2b46cc985cc
Author(s)
Marjanovic, Nemanja Despot
Hofree, Matan
Chan, Jason E.
Canner, David
Wu, Katherine
Trakala, Marianna
Hartmann, Griffin G.
Smith, Olivia C.
Kim, Jonathan Y.
Evans, Kelly Victoria
Date Issued
August 2020
Journal
Cancer Cell
Publisher
Elsevier BV
Version
Author's final manuscript
Abstract
Tumor evolution from a single cell into a malignant, heterogeneous tissue remains poorly understood. Here, we profile single-cell transcriptomes of genetically engineered mouse lung tumors at seven stages, from pre-neoplastic hyperplasia to adenocarcinoma. The diversity of transcriptional states increases over time and is reproducible across tumors and mice. Cancer cells progressively adopt alternate lineage identities, computationally predicted to be mediated through a common transitional, high-plasticity cell state (HPCS). Accordingly, HPCS cells prospectively isolated from mouse tumors and human patient-derived xenografts display high capacity for differentiation and proliferation. The HPCS program is associated with poor survival across human cancers and demonstrates chemoresistance in mice. Our study reveals a central principle underpinning intra-tumoral heterogeneity and motivates therapeutic targeting of the HPCS. Cellular states capable of promoting tumor progression and resisting therapies exist in heterogeneous tumors. Marjanovic et al. discover that a high-plasticity cell state common to mouse and human lung tumors drives cellular heterogeneity, is highly tumorigenic and drug resistant, and associates with poor patient prognosis.
MIT Department
Koch Institute for Integrative Cancer Research at MIT
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Department of Biology
Howard Hughes Medical Institute
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.ccell.2020.06.012
