Superior breast cancer metastasis risk stratification using an epithelial-mesenchymal-amoeboid transition gene signature

Amin Emad, Tania Ray, Tor W. Jensen, Meera Parat, Rachael Natrajan, Saurabh Sinha, Partha S. Ray

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Cancer cells are known to display varying degrees of metastatic propensity, but the molecular basis underlying such heterogeneity remains unclear. Our aims in this study were to (i) elucidate prognostic subtypes in primary tumors based on an epithelial-to-mesenchymal-to-amoeboid transition (EMAT) continuum that captures the heterogeneity of metastatic propensity and (ii) to more comprehensively define biologically informed subtypes predictive of breast cancer metastasis and survival in lymph node-negative (LNN) patients. Methods: We constructed a novel metastasis biology-based gene signature (EMAT) derived exclusively from cancer cells induced to undergo either epithelial-to-mesenchymal transition (EMT) or mesenchymal-to-amoeboid transition (MAT) to gauge their metastatic potential. Genome-wide gene expression data obtained from 913 primary tumors of lymph node-negative breast cancer (LNNBC) patients were analyzed. EMAT gene signature-based prognostic stratification of patients was performed to identify biologically relevant subtypes associated with distinct metastatic propensity. Results: Delineated EMAT subtypes display a biologic range from less stem-like to more stem-like cell states and from less invasive to more invasive modes of cancer progression. Consideration of EMAT subtypes in combination with standard clinical parameters significantly improved survival prediction. EMAT subtypes outperformed prognosis accuracy of receptor or PAM50-based BC intrinsic subtypes even after adjusting for treatment variables in 3 independent, LNNBC cohorts including a treatment-naïve patient cohort. Conclusions: EMAT classification is a biologically informed method that provides prognostic information beyond that which can be provided by traditional cancer staging or PAM50 molecular subtype status and may improve metastasis risk assessment in early stage, LNNBC patients, who may otherwise be perceived to be at low metastasis risk.

Original languageEnglish (US)
Article number1304
JournalBreast Cancer Research
Volume22
Issue number1
DOIs
StatePublished - Jul 8 2020

Keywords

  • Breast cancer subtypes
  • Epithelial-to-mesenchymal transition
  • Mesenchymal-to-amoeboid transition
  • Metastasis
  • Metastatic risk assessment

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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