Dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation

Abstract

Cancer patients often harbor occult metastases, a potential source of relapse that is targetable only through systemic therapy. Studies of this occult fraction have been limited by a lack of tools with which to isolate discrete cells on spatial grounds. We developed PIC-IT, a photoconversion-based isolation technique allowing efficient recovery of cell clusters of any size – including single-metastatic cells – which are largely inaccessible otherwise. In a murine pancreatic cancer model, transcriptional profiling of spontaneously arising microcolonies revealed phenotypic heterogeneity, functionally reduced propensity to proliferate and enrichment for an inflammatory-response phenotype associated with NF-κB/AP-1 signaling. Pharmacological inhibition of NF-κB depleted microcolonies but had no effect on macrometastases, suggesting microcolonies are particularly dependent on this pathway. PIC-IT thus enables systematic investigation of metastatic heterogeneity. Moreover, the technique can be applied to other biological systems in which isolation and characterization of spatially distinct cell populations is not currently feasible.

Data availability

Sequencing data have been deposited in GEO under the accession code GSE158078.

Article and author information

Author details

  1. Yogev Sela

    Medicine, University of Pennsylvania, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Jinyang Li

    Perelman School of Medicine, Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8125-6603
  3. Paola Kuri

    Department of Dermatology, Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Allyson Merrell

    Medicine, University of Pennsylvania, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Ning Li

    Department of Biomedical Sciences, University of Pennsylvania, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Chris Lengner

    Department of Biomedical Sciences, University of Pennsylvania, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Pantelis Rompolas

    Department of Dermatology, Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Ben Z Stanger

    Medicine, University of Pennsylvania, Philadelphia, United States
    For correspondence
    bstanger@upenn.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0410-4037

Funding

National Cancer Institute (CA229803)

  • Ben Z Stanger

National Institutes of Health (DK083355)

  • Ben Z Stanger

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#804643) of the University of Pennsylvania.

Reviewing Editor

  1. C Daniela Robles-Espinoza, International Laboratory for Human Genome Research, Mexico

Publication history

  1. Received: September 18, 2020
  2. Accepted: February 19, 2021
  3. Accepted Manuscript published: February 23, 2021 (version 1)
  4. Version of Record published: March 3, 2021 (version 2)

Copyright

© 2021, Sela et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Yogev Sela
  2. Jinyang Li
  3. Paola Kuri
  4. Allyson Merrell
  5. Ning Li
  6. Chris Lengner
  7. Pantelis Rompolas
  8. Ben Z Stanger
(2021)
Dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation
eLife 10:e63270.
https://doi.org/10.7554/eLife.63270

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