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  • Periodic Reporting for period 1 - EpiPredict (Epigenetic regulation of endocrine therapy resistance in breast cancer: A systems medicine approach to predict treatment outcome)
H2020

EpiPredict Report Summary

Project ID: 642691
Funded under: H2020-EU.1.3.1.

Periodic Reporting for period 1 - EpiPredict (Epigenetic regulation of endocrine therapy resistance in breast cancer: A systems medicine approach to predict treatment outcome)

Reporting period: 2015-01-01 to 2016-12-31

Summary of the context and overall objectives of the project

The mission of EpiPredict is to train 12 early-stage researchers (ESRs) in a new approach to fully exploit epigenetics of complex diseases. EpiPredict focuses on a narrowly defined case, endocrine therapy-induced resistance in Estrogen Receptor positive (ER+) breast cancer, considering defined resistance interacting pathways. Given the frequent endocrine therapy treatment failure, resistance prevention and reversal is an urgent clinical problem. EpiPredict provides an intersectorial training programme employing a timely systems medicine approach combining next-generation systematic epigenetic, gene/protein profiling with innovative gene-specific epigenetic interference technologies and computational modelling. The ESRs are trained to excel within and beyond all disciplines, sectors and audiences of breast cancer endocrine treatment resistance. EpiPredict builds on the outstanding expertise and facilities of the participants to identify key epigenetic changes underlying endocrine-therapy-induced resistance. This knowledge will be the basis to characterize individual patient's diagnostic/prognostic biomarkers to predict, monitor and improve endocrine treatment outcome and discover susceptibility for possible epigenetic co-treatments. Strong involvement of the private sector ensures exploitation of EpiPredict achievements and exposure to an entrepreneurial mind-set. The ESRs will master urgently needed new approaches to address complex diseases taking personalized patient aspects into consideration, being equipped to succeed in their careers providing extra impulses to drive European translational science.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

ESR3/B1, ESR4/B2, ESR5/B3 and ESR7/B4 are generating new epigenetic, gene/protein profiling data and ESR1/B1, ESR2/B1, ESR4/B2 and ESR11/B2 are performing innovative computational and bioinformatics analyses with these and additional existing data sets. ESR6/B3, ESR10/B7, ESR8/B5, ESR9/B6 are building innovative epigenetic editing tools to obtain cause-consequence mechanistic insight of obtained findings. ESR10/B7 is developing novel epigenetic prediction methods being hosted at the private sector.

More details regarding the current state of EpiPredict ESR1-11 research projects:
ESR1 (UvA) is developing a stochastic model to simulate mRNA distribution of defined genes in single cells and discriminate between inherent stochasticity in gene expression and cell-cell variability derived from the presence of multiple cell subpopulations.
ESR2 (UvA) is using statistical methods to identify DNA methylation-based biomarkers to predict endocrine therapy treatment outcome.
ESR3 (UvA) is studying how phenotypic heterogeneity in isogenic cell populations contributes to resistance development, using single molecule RNA FISH in drug treated cell lines.
ESR4 (ICL) is characterizing genomic and epigenomic profiles of 56 ERa+ breast cancer patients and exploiting identification of putative cancer-specific key players.
ESR5 (DKFZ) is performing proteomic profiling with RPPA analysis to identify shifts in pathways during resistance development in resistant cell lines and during the process of resistance acquisition.
ESR6 (DKFZ) is establishing Xenograft mouse models to test epigenetic resistance development and validate effects of resistance-specific epigenetic interference in vivo.
ESR7 (UNIMIB) is performing untargeted metabolic profiling of resistant and sensitive cell lines received from B2 showing the identification of metabolites and pathways, which are suspected to induce resistance via epigenetic alteration.
ESR8 (UMCG) is creating epigenetic editing tools to epigenetically interfere with defined resistance genes, i.e. sgRNAs are developed that are needed for CRISPR-dCas9 editing.
ESR9 (MTA-SZBK) is generating an E.coli assay system designed to test the specificity of a targeted DNA methylation tool. The system utilizes CRISPR/dCas9-mediated targeting and CG-specific DNA methyltransferase M.Sssl.
ESR10 (Epiontis) is developing a sensitive DNA methylation based qPCR detection method for selected resistance involved genes. Until now a qPCR based assay has been developed to detect Myeloid Derived Suppressor Cells (MDSC) in cancer tissues.
ESR11 (ICL) is dissecting heterogeneity of drug-resistance networks to develop robust predictors of endocrine treatment, showing the identification of a very early-stage gene signature that could be used for endocrine therapy outcome prediction.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Progression beyond state-of-the-art at research scientific level:
1) We are actively using computational modeling to guide experimental technologies used within EpiPredict and uncover systems behaviour of breast cancer resistance development upon endocrine treatment. This inherently multidisciplinary approach is very powerful making full use of the excellent expertise and knowledge at the different partner institutes. We aim to oversee systems behaviour of resistance development taking systems properties and medical patient data into account. We are considering putting together a conceptual paper outlining our current views based on this systems medicine approach; 2) We are combining experience and knowledge of innovative technologies and we are actively crossing borders to integrate knowledge from the various disciplines involved. This way we define our case from an angle that goes far beyond state-of-the-art. Magnani et al, Nature Genetics 2017 is a first example of the ongoing collaborative, innovative and multidisciplinary research within EpiPredict. We expect several similar high impact studies to be finalized and published.

Regarding the current impact of the EpiPredict project:
1) The ESRs have through the EpiPredict host-based and Network-wide training gained a very critical mind-set. During EpiPredict meetings (e.g. monthly video conferences, annual meetings and secondments) the ESRs are reflecting on each other's research allowing to implement knowledge in a broad context. The fellows are expected to become excellent research leaders in their field. This will largely impact future EU research and benefit EU innovation capacity; 2) Our EpiPredict research initiated a thorough collaboration between partner labs. The positive atmosphere of this powerful initiation enables to stimulate epigenetic research in breast cancer resistance development research and serves as a harbour for future research allowing other research efforts to be connected and enable unprecedented research developments largely stimulating EU industrial exploitation in the breast cancer drug resistance field.

Outreach to the public at large: EpiPredict research dissemination is actively ongoing. With the three planned Science Cafés targeting different audiences (scientists in general, patients and industry) we are creating full awareness of the impact of epigenetics to understand complex ER+ breast cancer disease progression, to predict novel biomarkers of endocrine resistance development and to consider novel strategies to correct resistance development. This intense outreach is important to set the scene to stimulate socio-economic impact and wide-societal implications of the EpiPredict data.

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