[BBC] post-doc offer

[Eric Bonnet]

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 at cea.fr.