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Project Goals

SYS-MEL investigators will perform fast-track validation of candidate protein biomarkers of interest via high-throughput assessment of human tissue specimens using a combination of antibody-based profiling and computer-assisted pathological interpretation. In addition, we will employ novel proprietary systems biology approaches to analyse multiple data points, together with pathway information, to provide a fully comprehensive viewpoint of tumour behaviour. Specifically, using the quantitative protein data generated, systems modelling will be utilised to provide added benefit over classical bio-statistical analysis, and will allow us to short-list highly specific panels of mechanistically-anchored next generation prognostic biomarkers. Along the same vein, we aim to create a panel of biomarkers that may be used to predict outcome to standard chemotherapy.

The central objective is to collectively develop molecular assays to aid in the clinical management of melanoma. SYS-MEL has 3 main elements, each representing a potential prognostic or predictive assay product.

1. To validate a protein-based panel of epigenetically regulated biomarkers that can better determine melanoma outcome (prognosis) than currently used parameters, which can then be further developed into a clinically applicable molecular diagnostic with commercial viability. We will focus on biomarkers identified from the epigenomic (DNA methylation) screen performed during the TargetMelanoma project, forming the basis of the prototype assay, EPI-MEL.

2. To translate the in-vitro-derived systems biology model developed by RCSI (DTIC-SYSACT) into clinical use to predict response/resistance to DTIC-based chemotherapy. By measuring the basal level of apoptotic proteins prior to treatment, this model can predict the ability of individual cell lines to induce the apoptotic pathway when treated with DTIC (or temozolomide (TMZ)), but also when treated with other pro-apoptotic drugs (TRAIL, cisplatin). In order to create a predictive assay with clinical utility, there is a requirement to integrate TMA technology and IHC quantitative image analysis within the modelling environment. Together this comprehensive analysis will form the basis of the potential predictive assay, APO-MEL.

3. To investigate components of the P-Rex1 pathway that drive migration of melanoblast and progression of metastasis, incorporating a computational system tailored to model complex signalling pathways.