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Nature genetics
08, 2022;54 (8): 1192-1201.

Cancer cell states recur across tumor types and form specific interactions with the tumor microenvironment.

Dalia Barkley, Reuben Moncada, Maayan Pour, Deborah A Liberman, Ian Dryg, Gregor Werba, Wei Wang, Maayan Baron, Anjali Rao, Bo Xia, Gustavo S França, Alejandro Weil, Deborah F Delair, Cristina Hajdu, Amanda W Lund, Iman Osman, Itai Yanai
Author Information
  1. Dalia Barkley: Institute for Computational Medicine, NYU Langone Health, New York, NY, USA. ORCID
  2. Reuben Moncada: Institute for Computational Medicine, NYU Langone Health, New York, NY, USA.
  3. Maayan Pour: Institute for Computational Medicine, NYU Langone Health, New York, NY, USA.
  4. Deborah A Liberman: Institute for Computational Medicine, NYU Langone Health, New York, NY, USA.
  5. Ian Dryg: Department of Dermatology, NYU Langone Medical Center, New York, NY, USA.
  6. Gregor Werba: Department of Surgery, NYU Langone Health, New York, NY, USA.
  7. Wei Wang: Department of Surgery, NYU Langone Health, New York, NY, USA.
  8. Maayan Baron: Institute for Computational Medicine, NYU Langone Health, New York, NY, USA.
  9. Anjali Rao: Institute for Computational Medicine, NYU Langone Health, New York, NY, USA. ORCID
  10. Bo Xia: Institute for Computational Medicine, NYU Langone Health, New York, NY, USA. ORCID
  11. Gustavo S França: Institute for Computational Medicine, NYU Langone Health, New York, NY, USA.
  12. Alejandro Weil: Department of Pathology, NYU Langone Medical Center, New York, NY, USA.
  13. Deborah F Delair: Department of Pathology, NYU Langone Medical Center, New York, NY, USA.
  14. Cristina Hajdu: Department of Pathology, NYU Langone Medical Center, New York, NY, USA.
  15. Amanda W Lund: Department of Dermatology, NYU Langone Medical Center, New York, NY, USA.
  16. Iman Osman: Department of Dermatology, NYU Langone Medical Center, New York, NY, USA.
  17. Itai Yanai: Institute for Computational Medicine, NYU Langone Health, New York, NY, USA. itai.yanai@nyulangone.org. ORCID
PMID: 35931863 DOI: 10.1038/s41588-022-01141-9

Abstract

Transcriptional heterogeneity among malignant cells of a tumor has been studied in individual cancer types and shown to be organized into cancer cell states; however, it remains unclear to what extent these states span tumor types, constituting general features of cancer. Here, we perform a pan-cancer single-cell RNA-sequencing analysis across 15 cancer types and identify a catalog of gene modules whose expression defines recurrent cancer cell states including 'stress', 'interferon response', 'epithelial-mesenchymal transition', 'metal response', 'basal' and 'ciliated'. Spatial transcriptomic analysis linked the interferon response in cancer cells to T cells and macrophages in the tumor microenvironment. Using mouse models, we further found that induction of the interferon response module varies by tumor location and is diminished upon elimination of lymphocytes. 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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Grants

  1. P50 CA225450/NCI NIH HHS
  2. U01 CA260432/NCI NIH HHS
  3. F30 CA257400/NCI NIH HHS
  4. R01 LM013522/NLM NIH HHS
  5. R21 CA264361/NCI NIH HHS

MeSH Term

Animals
Epithelial-Mesenchymal Transition
Gene Expression Profiling
Interferons
Mice
Neoplasms
Tumor Microenvironment

Chemicals

Interferons
Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

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