We have implemented the core management, research and training activities, developed communication and dissemination strategies, as well as creating a project website. 14 ESRs have been recruited and enrolled on PhD programmes and all appropriate ethics processes were in place.
AiPBAND research activities were grouped into five work packages (WPs)
WP1- The protocols of three biosensors have been developed, which can be used to test different types of biomarkers in the blood, including a graphene-based biosensor for the detection and quantification of methylated tumour suppressor gene (MGMT). Results of this work were successfully accepted for presentation at the 30th Anniversary World Congress on Biosensors. An optical biosensor platform using Surface Plasmon Resonance Imaging (SPRi) technology has been developed to detect GBM-associated miRNA biomarker. A review paper has been published about the applicability of SPR and localized SPR (LSPR)-based platforms (Bellassai N. et.al. Front Chem. 2019). Further optimization of the assay is required to provide a better enhancement factor. Moreover, digital ELISA bioassay for detecting multiplex protein and nucleic acid biomarkers at extremely low concentrations has been established. The platform shows a great degree of flexibility, offering a possibility for implementing multiplex assays to detect more than one target per sample.
WP2- Initial biomarker panels for GBM has been produced by a comprehensive literature review study which includes microRNA and protein biomarkers in body fluids and a survival prediction model for GBM was developed. In addition, a panel of miRNA biomarkers has been identified by next generation sequencing techniques. The plasma proteogenomics method has been developed and a GBM stem-cell panel has been profiled, using RNAseq and in-depth MS to detect stem cell specific proteins. The plasma and tissue validation cohort is currently being collected. Two relevant papers have been published (Pernemalm M., et. al., eLife, Issue 8, 2019; Chandran V.I. Clinical Cancer Research, 2019). Moreover, an in silico data-mining study to identify DNA methylation biomarkers is being carried out.
WP3- A machine learning model to integrate DNA methylation and gene expression data for cancer discrimination has been developed and published (Zhang X., Proceedings 2019 IEEE International Conference on Bioinformatics and Biomedicine). In addition, a query database has been developed to explore potential known biomarkers in brain cancer. Also, the architecture for an innovative cloud-based brain tumour diagnostic platform (CBDP) has been proposed for further development.
WP4- The protocol of developing a pre-clinical mouse model that accurately recreates the molecular profile reported in GBM patients has been developed. The model will be established to validate blood biomarkers identified in AiPBAND. Genetically characterised brain tumour samples from patients with glioblastoma and other forms of high-grade glioma have been provided too. These samples are made available for RNA sequencing and spatial transcriptome. In addition, a novel clinical trial strategy has been designed to reduce bias and false positive in biomarkers research. The validations of miRNA and protein biomarkers using two biosensors respectively are ongoing.
WP5- The current business model of an AiPBAND SME has been intensely investigated and a working draft of the AiPBAND Business Model (BM) canvas to reflex the possible BMs proposed. Further work will follow to develop and explore the innovative diagnostics and business models for potential industrial exploitations and clinical applications across Europe.
In parallel with the research developed by ESRs, a tailored training programme was implemented, covering fundamental and transferable skills. During this report period, six network-wide training events have been organised, which ESRs have been engaged in, from online presence to in person activities.
