A Patient-Derived, Pan-Cancer EMT Signature Identifies Global Molecular Alterations and Immune Target Enrichment Following Epithelial-to-Mesenchymal Transition

Clin Cancer Res. 2016 Feb 1;22(3):609-20. doi: 10.1158/1078-0432.CCR-15-0876. Epub 2015 Sep 29.


Purpose: We previously demonstrated the association between epithelial-to-mesenchymal transition (EMT) and drug response in lung cancer using an EMT signature derived in cancer cell lines. Given the contribution of tumor microenvironments to EMT, we extended our investigation of EMT to patient tumors from 11 cancer types to develop a pan-cancer EMT signature.

Experimental design: Using the pan-cancer EMT signature, we conducted an integrated, global analysis of genomic and proteomic profiles associated with EMT across 1,934 tumors including breast, lung, colon, ovarian, and bladder cancers. Differences in outcome and in vitro drug response corresponding to expression of the pan-cancer EMT signature were also investigated.

Results: Compared with the lung cancer EMT signature, the patient-derived, pan-cancer EMT signature encompasses a set of core EMT genes that correlate even more strongly with known EMT markers across diverse tumor types and identifies differences in drug sensitivity and global molecular alterations at the DNA, RNA, and protein levels. Among those changes associated with EMT, pathway analysis revealed a strong correlation between EMT and immune activation. Further supervised analysis demonstrated high expression of immune checkpoints and other druggable immune targets, such as PD1, PD-L1, CTLA4, OX40L, and PD-L2, in tumors with the most mesenchymal EMT scores. Elevated PD-L1 protein expression in mesenchymal tumors was confirmed by IHC in an independent lung cancer cohort.

Conclusions: This new signature provides a novel, patient-based, histology-independent tool for the investigation of EMT and offers insights into potential novel therapeutic targets for mesenchymal tumors, independent of cancer type, including immune checkpoints.

Publication types

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

MeSH terms

  • Biomarkers
  • Cell Line, Tumor
  • Cluster Analysis
  • Computational Biology / methods
  • Drug Resistance, Neoplasm / genetics
  • Epithelial-Mesenchymal Transition / genetics*
  • Gene Expression Profiling*
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks
  • Genomics / methods
  • Humans
  • MicroRNAs / genetics
  • Mutation
  • Neoplasms / genetics*
  • Neoplasms / immunology*
  • Neoplasms / metabolism
  • Neoplasms / mortality
  • Neoplasms / pathology
  • Prognosis
  • Transcriptome*
  • Tumor Microenvironment / genetics
  • Tumor Microenvironment / immunology


  • Biomarkers
  • MicroRNAs