Abstract
Abstract Background Multigene prognostic signatures (MGPS) enable identification of candidate patients for treatment de-escalation in early stage breast cancer (BC). Here we present OncoMasTR, a MGPS for classifying the risk of distant metastasis (DM) in ER-positive, HER2-negative BC patients with up to 3 involved lymph nodes (LNs). OncoMasTR was discovered via a novel transcriptional network analysis methodology that identified genes that regulate previously identified prognostic biomarkers. These upstream genes, termed master transcriptional regulators (MTRs), were shown to provide improved prognostic performance compared with downstream genes. OncoMasTR has been mechanistically verified by RT-qPCR, immunohistochemistry and chromatin immunoprecipitation. OncoMasTR has been further trained to include clinicopathological information (CPI) to maximise its prognostic performance. Methods Two independent sample sets: 225 patients from Malmö University Hospital and 100 patients 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 to measure the expression levels of the MTRs. Statistical models of all possible combinations of MTRs were trained and cross-validated (1,000 times x 2-fold) using the first set of 225 samples. Statistical models with the best cross-validated performance were further evaluated on RT-qPCR data from the second independent set of 100 samples. Robustness of the data was verified by assessing the reproducibility of OncoMasTR across 6 days, using 6 unique kit lots, conducted by 4 operators on 3 RT-qPCR instruments. Results In the first training set of 225 patients, OncoMasTR classified up to 72% of LN0 patients and 58% of LN0-3 patients as low risk, with ≤ 5.0% DM within each group. When incorporating CPI, its prognostic performance further improved to a c (concordance) index > 0.8. Results showed that the OncoMasTR molecular score and CPI add statistically significant prognostic value to each other. In the independent verification set, all patients with DM were correctly classified as high risk (p<0.01). In relation to reproducibility, the OncoMasTR test displayed robust performance; the molecular score coefficient of variation was 2.6% across days, kit lots, operators and instruments. Individual MTR assays demonstrated linearity over >2000-fold RNA input range and PCR efficiencies ranged from 92% to 101%. Conclusions OncoMasTR development and verification results show analytical robustness and clinically accurate risk stratification. Furthermore, OncoMasTR's binary classification of risk avoids an ambiguous intermediate risk classification and has potential to provide clinicians with useful, actionable information to support treatment decisions. The OncoMasTR test is now ready for large-scale clinical validation. Citation Format: Barron S, Jirström K, Jernström H, Ingvar C, Moran B, Wang C-JA, Loughman T, Fender B, Dynoodt P, Lopez-Ruiz C, Russell N, Gallagher WM. Prognostic value of OncoMasTR: A novel multigene signature based on master transcriptional regulators [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P3-08-06.
Published Version
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