Integrating the molecular subtypes of breast cancer into a novel prognostic model
Haibe-Kains B, Desmedt C, Rothé F, Piccart MJ, Bontempi G and Sotiriou C
Background: The early gene
expression studies in breast cancer have provided a molecular
classification of these tumors into at least three clinically relevant
subtypes (ER-/HER2-, HER2+ or ER+/HER2). Our group recently introduced
a robust method for subtype identification, exhibiting numerous
advantages compared to the hierarchical clustering used in the initial
publications. From a prognostic point of view, several signatures have
been identified in the global population of patients. However, the
majority of these only added significant prognostic information in the
ER+/HER2-. Here, we propose a novel prognostic model which takes into
the account the molecular heterogeneity of breast cancer.
Methods: We developed a
two-step prognostic model called GENIUS (Gene Expression progNostic
Index Using Subtypes). The first step consists in an accurate
assessment of the probabilities for a patient to belong to each of the
three breast cancer molecular subtypes. The second step is a
combination of these probabilities with subtype specific prognostic
signatures, which results in the final GENIUS risk score.
Results: We computed the GENIUS
risk score for more than 1000 untreated node-negative breast cancer
patients collected from numerous microarray datasets. Compared to
current gene signatures, GENIUS yielded significantly better
performance in the global population of patients (concordance index of
0.71, superiority test p-values < 0.05) and was very competitive in
each subtype (concordance indices of 0.7, 0.66 and 0.66 in the
ER+/HER2-, ER-/HER2- and HER2+ subtypes, respectively). Although GENIUS
outperformed clinical guidelines (superiority test p-values < 0.05),
our results suggest that the combination of GENIUS and these guidelines
might improve the predictions.
Conclusions: This novel
prognostic model, which considers the molecular heterogeneity of breast
cancer, outperforms the current clinical guidelines and gene
signatures. GENIUS was the only signature to be highly prognostic in
all the molecular subtypes. Additionally, the modular architecture of
the model allows plugging in any other gene expression signatures,
potentially enlarging its usability.