The Prognostic Ease and Difficulty of Invasive Breast Carcinoma
Ali Tofigh,
Matthew Suderman,
Eric R. Paquet,
Julie Livingstone,
Nicholas Bertos,
Sadiq M. Saleh,
Hong Zhao,
Margarita Souleimanova,
Sean Cory,
Robert Lesurf,
Solmaz Shahalizadeh,
Norberto Garcia Lopez,
Yasser Riazalhosseini,
Atilla Omeroglu,
Josie Ursini-Siegel,
Morag Park,
Vanessa Dumeaux,
Michael Hallett
Affiliations
Ali Tofigh
The Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC H3A1A3, Canada; Centre for Bioinformatics, McGill University, Montreal, QC H3G0B1, Canada
Matthew Suderman
The Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC H3A1A3, Canada; Centre for Bioinformatics, McGill University, Montreal, QC H3G0B1, Canada
Eric R. Paquet
The Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC H3A1A3, Canada; Centre for Bioinformatics, McGill University, Montreal, QC H3G0B1, Canada
Julie Livingstone
The Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC H3A1A3, Canada; Centre for Bioinformatics, McGill University, Montreal, QC H3G0B1, Canada
Nicholas Bertos
The Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC H3A1A3, Canada
Sadiq M. Saleh
The Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC H3A1A3, Canada; Centre for Bioinformatics, McGill University, Montreal, QC H3G0B1, Canada; Department of Biochemistry, McGill University, Montreal, QC H3G1Y6, Canada
Hong Zhao
The Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC H3A1A3, Canada
Margarita Souleimanova
The Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC H3A1A3, Canada
Sean Cory
The Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC H3A1A3, Canada; Centre for Bioinformatics, McGill University, Montreal, QC H3G0B1, Canada
Robert Lesurf
The Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC H3A1A3, Canada; Centre for Bioinformatics, McGill University, Montreal, QC H3G0B1, Canada; Department of Biochemistry, McGill University, Montreal, QC H3G1Y6, Canada
Solmaz Shahalizadeh
Centre for Bioinformatics, McGill University, Montreal, QC H3G0B1, Canada
Norberto Garcia Lopez
Department of Human Genetics, McGill University, Montreal, QC H3A 1B1, Canada; McGill University Health Centre, McGill University, Montreal, QC H3A 1A1, Canada
Yasser Riazalhosseini
Department of Human Genetics, McGill University, Montreal, QC H3A 1B1, Canada; McGill University and Génome Québec Innovation Centre, Montreal, QC H3A 0G1, Canada
Atilla Omeroglu
Department of Pathology, McGill University, Montreal, QC H3A 2B4, Canada; McGill University Health Centre, McGill University, Montreal, QC H3A 1A1, Canada
Josie Ursini-Siegel
Lady Davis Institute for Medical Research, McGill University, Montreal, QC H3T1E2, Canada; Department of Oncology, McGill University, Montreal, QC H2W1S6, Canada
Morag Park
The Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC H3A1A3, Canada; Department of Biochemistry, McGill University, Montreal, QC H3G1Y6, Canada; Department of Oncology, McGill University, Montreal, QC H2W1S6, Canada
Vanessa Dumeaux
Department of Oncology, McGill University, Montreal, QC H2W1S6, Canada; Institute of Community Medicine, UiT the Arctic University of Norway, Tromso 9037, Norway
Michael Hallett
The Rosalind and Morris Goodman Cancer Research Centre, McGill University, Montreal, QC H3A1A3, Canada; Centre for Bioinformatics, McGill University, Montreal, QC H3G0B1, Canada; Department of Biochemistry, McGill University, Montreal, QC H3G1Y6, Canada; Corresponding author
Summary: Breast carcinoma (BC) has been extensively profiled by high-throughput technologies for over a decade, and broadly speaking, these studies can be grouped into those that seek to identify patient subtypes (studies of heterogeneity) or those that seek to identify gene signatures with prognostic or predictive capacity. The sheer number of reported signatures has led to speculation that everything is prognostic in BC. Here, we show that this ubiquity is an apparition caused by a poor understanding of the interrelatedness between subtype and the molecular determinants of prognosis. Our approach constructively shows how to avoid confounding due to a patient’s subtype, clinicopathological profile, or treatment profile. The approach identifies patients who are predicted to have good outcome at time of diagnosis by all available clinical and molecular markers but who experience a distant metastasis within 5 years. These inherently difficult patients (∼7% of BC) are prioritized for investigations of intratumoral heterogeneity. : Tofigh et al. perform a comprehensive and systematic comparison of existing prognostic signatures in breast cancer. The comparison establishes that the supposed ubiquity of prognostic genes and processes has been grossly overestimated and results from insufficient stratification by subtype and other clinicopathological variables. The study presents a refined subtyping scheme ablating these effects. Nevertheless, a set of patients is identified whose outcome appears inherently difficult to predict using all available information at time of diagnosis.
