Post-doctorate in omics data integration and network science “Proteogenomic analysis of patient-specific network perturbations caused by genetic alterations in cancer” Context The diagnostic of cancer in a patient begins with a clinical examination followed by a blood test, medical imaging and often ends with the histopathological analysis of a tumor biopsy in order to establish the cancer type and the therapeutic strategy. One of the objectives of the France Genomic Medicine 2025 plan is to improve diagnostic and treatment selection by also taking into account genomic profiling obtained from NGS sequencing. However, recent research from the NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) demonstrated that the integration of proteomic profiles with genomic information, now referred to as "proteogenomics," reveals subtypes of cancers that are inaccessible by NGS. Our project is a transverse initiative (https://proteogenomics.wordpress.com/) between three CEA french research centers CNRGH-LBI (National Human Genome Research Center – Bioinformatics lab), BIG-EDyP (Biosciences and Biotechnology Institute of Grenoble – Proteomics lab), LIST-LADIS (Laboratory of Embedded Systems and Technology – Big data analysis lab) and BIFI-COSNET lab (Institute for Biocomputation and Physics of Complex Systems – Complex systems and networks lab) from the University of Zaragoza to contribute to the emergence of proteogenomics in precision medicine. Our final goal is to implement a "patient-centered" software solution capable of structuring, integrating and interrogating genomic and proteomic profiles from the same tumor in order to improve diagnostic and therapy. We will develop methods that capture and model the deregulations of molecular networks at stake in cancer, to identify patient-specific network perturbations and exploit them to provide better diagnostic. We already achieved significant progress on two in silico developments (not yet published) which can be considered as building blocks to our project: - We designed and implemented a graph-based database to structure and interrogate multi-omic tumoral data. This database was constructed using the triple-store technology to allow writing complex queries and to facilitate aggregation of public biological data repositories. - We developed a proteogenomic workflow to analyse proteomic data using a priori information extracted from transcriptome profiling. This approach, evaluated on a cancer cell line, allowed us to identify genetic alterations translated at the proteome level. Objectives The post-doctorate will develop a methodology to explore patient-specific perturbations on molecular networks and particularly on signaling pathways caused by genetic alterations (single nucleotide variants, aberrant transcript splicing) identified from proteogenomic profiling of tumor biopsies. He will leverage complexity of these multi-omic data to assess the impact of genetic variants on multiple regulatory dimensions, from transcriptional to post-translational levels. To reach this goal, the applicant will first analyse onco-proteogenomic data to infer patient-specific genetic alterations affecting its genome, transcriptome, proteome or phosphoproteome. Then, he/she will work on (i) the structuring of data obtained from each patient to define relationships between multi-omic measurements and (ii) the development of complex queries to reveal multidimensional perturbations. These investigations will be carried out using the multilayer network formalism and algorithms. This rapidly expanding research field was already successfully applied to multi-omic data to extract biological subnetworks, to identify genes with maximum influence on the process of perturbation spreading and to classify patients into cancer subtypes. Resources This methodology will be developed using large-scale omics data made publicly available by several international research consortia (GTEX, CPTAC, NIH Epigenomics Roadmap) and tested on proteogenomic profiles in-house produced from cancer cell lines. Moreover, data storage and computational needs required by this large-scale project will be available at the CEA HPC infrastructure. Host laboratories The recruited young researcher will be hosted by the BIG-EDyP laboratory in Grenoble and will evolve within a multidisciplinary research team. He/she will also spend research periods in collaborating laboratories to optimize progression of the research project. Expected competences The applicant should have a PhD in computational biology or related domains. He/she should be experienced in omics fields with at least one of these fields of expertise: bioinformatics, data integration or network science, and strong interest for all of them. Moreover, programming experience is required. Research contract Funding for a one-year post-doctoral contract is already available with gross annual salary range from about €41,000 to €58,000 depending on experience. We are looking for a candidate motivated to apply for additional funding at the CEA Enhanced Eurotalents Programme (http://eurotalents.cea.fr/). Contact If you are interested by this opportunity please send your CV, a motivation letter and names of referees to christophe.battail@cea.fr.