Multigene prognostic signatures (MGPS) enable identification of candidate patients (pts) for treatment de-escalation in early stage BC. However, currently available MGPS do not completely address clinical needs by adequately incorporating lymph node (LN)-positive pts and clinicopathological information (CPI). Here, we present OncoMasTR, a MGPS for determining the risk of distant recurrence (DR) in ER-positive, HER2-negative BC pts with up to 3 involved LNs. OncoMasTR, discovered via a novel network analysis methodology that determines upstream MTRs has been mechanistically verified and offers improved prognostic value compared to existing MGPS. OncoMasTR has been further trained to include LN-positive pts and CPI.
Two independent sample sets: 225 pts from Malmö University Hospital and 106 pts from Skåne University Hospital were used for training, cross-validation and refinement of OncoMasTR. RNA extracted from 225 archived tissues was analysed by RT-qPCR and expression levels of the MTRs were determined by normalising against the expression levels of reference genes. The strongest prognostic combinations of MTRs were identified using statistical models of all possible combinations of MTRs. Clinical performance of the models with the best cross-validated performance in the training data were further evaluated in the 106 independent samples.
OncoMasTR classifies up to 72% of LN0 pts and 60% of LN0-3 pts as low risk, with only 4.9% and 5.5% recurrence rate within the respective groups. When incorporating selected CPI, its prognostic performance further improved to a concordance index of above 0.8. Results showed that the OncoMasTR Molecular score (mS) alone adds statistically significant information to the CPI, and the Combined score (cS) also adds statistically significant information to the mS.
OncoMasTR offers significant prognostic information to the standard CPI and addresses the unmet clinical need of LN-positive pts. The binary output of OncoMasTR, giving no ambiguous intermediate group helps eliminate uncertainty in the formation of the final treatment decision. OncoMasTR is ready for large-scale clinical validation and, subsequently, clinical translation.
Clinical trial identification
Legal entity responsible for the study
S. Barron, B. Moran, C-J.A. Wang, T. Loughman, B. Fender, P. Dynoodt, C. Lopez-Ruiz: Employee of OncoMark Ltd. W. Gallagher: Employee of OncoMark Ltd, has stock or ownership of OncoMark Ltd, is a co-inventor of the patent licensed to OncoMark Ltd and received travel, accommodation and expense from OncoMark Ltd. All other authors have declared no conflicts of interest.