Abstract

BackgroundCancer 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.MethodsWe 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.ResultsDelineated 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.ConclusionsEMAT 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.

Highlights

  • Metastasis is one of the key hallmarks of cancer [1] and accounts for nearly 90% of cancer-related mortality

  • Our aims were to (i) elucidate prognostic subtypes in primary tumors based on an epithelial-to-mesenchymal transition (EMT)-mesenchymal-to-amoeboid transition (MAT) 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

  • EMAT4, the cluster with the lowest diseasespecific survival (DSS) probability, showed M-like characteristics (VIM was over-expressed in this cluster compared to the other three clusters, p = 4.8E−8, unpaired two-tailed t-test)

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Summary

Introduction

Metastasis is one of the key hallmarks of cancer [1] and accounts for nearly 90% of cancer-related mortality. Cancer cells within a tumor are known to possess different metastatic potentials [2]. The molecular basis underlying the observed heterogeneity in metastatic proclivity remains unclear and a suitable molecular classification is lacking. Independent of and in addition to those that determine the intrinsic molecular subtype of the cancer, influence its invasive potential and metastatic propensity. 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

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