Project: Synthetic Lethality for Personalized Therapy-based Stratification In Acute Leukemia

Acronym	SYNtherapy (Reference Number: ERAPERMED2018-275)
Duration	01/03/2019 - 28/02/2022
Project Topic	High-throughput technologies have dramatically improved our understanding of acute leukemia pathogenesis. Omics-based personalized approaches have the potential to offer individualized, highly specific therapies. Currently most of them exploit the phenomenon of ‘oncogene addiction’: tumor cells depend on an oncogene/oncogenic pathway for survival. However, for tumors with no targetable gain-of-function oncogenes the therapy is still based on DNA-damaging agents. In these tumors it is possible to identify patient-specific secondary targets whose disruption in conjunction with genomic alteration results in synthetic lethality (SL). There are two possible SL approaches: Gene to Drug (G-D), where the synergism is reached by associating a primary genetic alteration with a secondary drug; Drug to Drug (D-D), where the synergism is reached by combining the effect of two different drugs. Our aim is to develop a machine learning-based model to predict personalized treatment for relapsed/refractory acute leukemias. We will exploit the above-mentioned SL approaches by multilayer analysis of omics data, including RNA-Seq, Copy Number Alterations (CNAs) by SNP array and DNA targeted Next Generation Sequencing (NGS) (WP2). Differential expression analysis of RNA-Seq data will provide primary molecular markers that will be propagated in protein-protein interaction networks, to identify secondary non- altered potential markers (G-D SL and D-D SL). The candidates will be reduced by selecting DDR-related genes for which a drug inhibitor is known (WP3). The selected drugs will be screened ex-vivo to identify the most effective for each patient (WP4). The integrated omics data and ex-vivo test results will be used as training dataset for the predictive model (WP3). A multi-centric investigator-initiated clinical trial will test the performance of the predictive model as well as the practical feasibility of the whole procedure (from sample collection to drug administration) (WP1-5).
Network	ERA PerMed
Call	1st Joint Transnational Call for Proposals (2018)

Project partner

Number	Name	Role	Country
4	Fundación Instituto de Ciencias de la Salud de Castilla y León- Instituto de Investigación Biomédica de Salamanca (IBSAL)	Coordinator	Spain
5	Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST)-IRCCS	Partner	Italy
6	Charité University Medicine Berlin	Partner	Germany
7	Tel Aviv University	Partner	Israel