The OncoMark Process

The OncoMasTR Technology was originally developed by researchers in Trinity College Dublin (TCD) in collaboration with Prof. William Gallagher of University College Dublin (UCD) (who was also founder and the Chief Scientific Officer of OncoMark). The central hypothesis of the work was to identify upstream ‘drivers’ of cancer progression, rather than ‘passenger’ genes, which other cancer biomarker signatures had identified. Upstream drivers represent a more accurate and reliable indicator of tumour progression.



Several multigene prognostic signatures, which identify the risk of women with early stage, lymph node-negative breast cancer of developing a recurrence after surgical resection, have been developed in recent years [1],[2]. Many of these have been adopted in the clinic and have proven useful in terms of stratifying patients into lower and higher recurrence risk groups. However, since there was little overlap in the genes represented in these signatures, it was hypothesized that identifying and measuring gene expression of the upstream Master Transcriptional Regulators (MTRs) would allow the development of more accurate tests to help inform on best treatment options.



A novel bioinformatic algorithm termed ARACNe [3],[4]  was used to predict the upstream MTRs of two independent breast cancer prognosis biomarker signatures. ARACNe uses networks constructed from gene expression datasets to infer direct transcriptional interactions. A panel of Master Transcriptional Regulators (MTRs), commonly associated with poor prognosis in existing tests and that shared a common role in cell proliferation, was identified.

In this way, a mechanistically anchored panel of biomarkers was identified comprising up to 10 MTRs. These were brought forward for the development of the OncoMasTR Test.

Development of the OncoMasTR test

Through a network of clinical and scientific collaborators, the OncoMark team successfully combined the mRNA expression levels of prognosis-linked MTRs with standard clinical risk factors into a risk scoring algorithm which underpins the OncoMasTR Test [5]. The test was subjected to training and refinement using microarray databases and real-world patient samples before independent clinical validation using the TransATAC cohort [6].

The results revealed that the OncoMasTR test was capable of classifying patients as low risk with more accuracy compared to the leading breast cancer prognostic test in the market thereby supporting the ongoing technical, clinical and commercial translation of the test.


[1] Duffy MJ et al. Eur J Cancer, 2017; 75, 284-295 

[2] Stein RC et al. Health Technol Assess, 2016; 20(10), xxiii-xxix 

[3] Margolin AA et al. Nat Protoc, 2006; 1, 662-671 

[4] Carro MS et al. Nature, 2010; 463, 318-325 

[5] Lanigan F et al. FEBS J., 2015; 282(18), 3455-3473 

[6] Buus R, Sestak I, Barron S et al. Validation of the OncoMasTR Risk Score in Estrogen Receptor–Positive/HER2-Negative Patients: A TransATAC study. Clin Cancer Res February 1 2020; (26) (3) 623-631; DOI: 10.1158/1078-0432.CCR-19-0712