A novel approach to triple-negative breast cancer molecular classification reveals a luminal immune-positive subgroup with good prognoses

Guillermo Prado-Vázquez,Angelo Gámez-Pozo,Mariana Díaz-Almirón,Enrique Espinosa,Rocío López-Vacas,Pilar Zamora,Andrea Zapater-Moros,Juan Ángel Fresno Vara,Paloma Maín,María Ferrer-Gómez,Jorge M Arevalillo,Jaime Feliú,Hilario Navarro,Lucía Trilla-Fuertes

doi:10.1038/s41598-018-38364-y

Abstract

Triple-negative breast cancer is a heterogeneous disease characterized by a lack of hormonal receptors and HER2 overexpression. It is the only breast cancer subgroup that does not benefit from targeted therapies, and its prognosis is poor. Several studies have developed specific molecular classifications for triple-negative breast cancer. However, these molecular subtypes have had little impact in the clinical setting. Gene expression data and clinical information from 494 triple-negative breast tumors were obtained from public databases. First, a probabilistic graphical model approach to associate gene expression profiles was performed. Then, sparse k-means was used to establish a new molecular classification. Results were then verified in a second database including 153 triple-negative breast tumors treated with neoadjuvant chemotherapy. Clinical and gene expression data from 494 triple-negative breast tumors were analyzed. Tumors in the dataset were divided into four subgroups (luminal-androgen receptor expressing, basal, claudin-low and claudin-high), using the cancer stem cell hypothesis as reference. These four subgroups were defined and characterized through hierarchical clustering and probabilistic graphical models and compared with previously defined classifications. In addition, two subgroups related to immune activity were defined. This immune activity showed prognostic value in the whole cohort and in the luminal subgroup. The claudin-high subgroup showed poor response to neoadjuvant chemotherapy. Through a novel analytical approach we proved that there are at least two independent sources of biological information: cellular and immune. Thus, we developed two different and overlapping triple-negative breast cancer classifications and showed that the luminal immune-positive subgroup had better prognoses than the luminal immune-negative. Finally, this work paves the way for using the defined classifications as predictive features in the neoadjuvant scenario.

Highlights

Triple-negative breast cancer is a heterogeneous disease characterized by a lack of hormonal receptors and HER2 overexpression
Our aim was to tackle the molecular analysis of Triple-negative breast cancer (TNBC) from a broad perspective, such as the cancer stem cell hypothesis, to provide a classification with clearer clinical implications
The results obtained with the first database were applied to a second database of patients treated with neoadjuvant chemotherapy, GSE25066

Summary

Introduction

Triple-negative breast cancer is a heterogeneous disease characterized by a lack of hormonal receptors and HER2 overexpression. Several studies have developed specific molecular classifications for triple-negative breast cancer These molecular subtypes have had little impact in the clinical setting. Tumors in the dataset were divided into four subgroups (luminal-androgen receptor expressing, basal, claudin-low and claudin-high), using the cancer stem cell hypothesis as reference. These four subgroups were defined and characterized through hierarchical clustering and probabilistic graphical models and compared with previously defined classifications. Other classifications have been proposed by Sabatier[9], Prat[10], Jézéquel[11], and Milioli[12] Despite these extensive studies, the designation of TNBC molecular subtypes has had little impact in the clinical setting

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Conclusion