Cancer bioinformatics and systems biology : J. Colinge

Cancer bioinformatics and systems biology


Our current research falls in three axes.


Axis 1: We infer biological networks by integrating several omics with reference intra- (signaling, transcription) and inter-cell (tumor microenvironment) interactions to find active functional modules. We apply such methods to different rare, aggressive tumor cohorts or metastases, which display resistance to frontline therapy. We try to unravel resistance mechanisms and find targets able to break resistance.


Axis 2: Network inference from perturbation experiments. We set up different projects where the detailed, quantitative and predictive analysis of a chosen biological network is required. Extending modular response analysis methods (Kholodenko), we infer weighted, directed networks.


Axis 3: Computational proteomics. Main focus at the moment is the development (with clinical partners) of a an innovative experiment/computational framework to determine protein turnover parameters in biological fluids in patients and in vivo. We have obtained very promising results in the CSF and plasma introducing a new mathematical model integrated with MS data processing and bioinformatics pipelines. We want to explore a new class of biomarkers related to abnormal clearance rates or passage across biological barriers such as blood-brain in disease, e.g. Alzheimer disease



Jimenez-Dominguez G, Ravel P, Jalaguier S, Cavaillès V, Colinge J An R package for generic modular response analysis and its application to estrogen and retinoic acid receptor crosstalk. Sci Rep. 2021;11(1):7272. doi:10.1038/s41598-021-86544-0

Alame M, Cornillot E, Cacheux V, Tosato G, Four M, Oliveira L, Gofflot S, Delvenne P, Turtoi E, Cabello-Aguilar S, Nishiyama M, Turtoi A, Martineau V, Colinge J The molecular landscape and microenvironment of salivary duct carcinoma reveal new therapeutic opportunities. 2020;10(10):4383-4394. doi:10.7150/thno.42986

Cabello-Aguilar S, Alame M, Kon-Sun-Tack F, Fau C, Lacroix M, Colinge J SingleCellSignalR: inference of intercellular networks from single-cell transcriptomics. Nucleic Acids Res.. Mar 20, 2020. doi:10.1093/nar/gkaa183

Tanos R, Tosato G, Al Amir Dache Z, Pique Lasorsa L, Tousch G, El Messaoudi S, Meddeb R, Diab Assaf M, Ychou M, Pezet D, Gagnière J, Colombo P-E, Jacot W, Dupuy M, Adenis A, Mazard T, Mollevi C, Sayagués J, Colinge J, Thierry A Machine Learning-Assisted Evaluation of Circulating DNA Quantitative Analysis for Cancer Screening. Adv Sci (Weinh). 2020;7(18):2000486. doi:10.1002/advs.202000486

Lehmann S, Hirtz C, Vialaret J, Ory M, Combes G, Corre M, Badiou S, Cristol J-P, Hanon O, Cornillot E, Bauchet L, Gabelle A, Colinge J In Vivo Large-Scale Mapping of Protein Turnover in Human Cerebrospinal Fluid. Anal. Chem.. 2019;91(24):15500-15508. doi:10.1021/acs.analchem.9b03328


Team Leader  : Jacques Colinge

Institut de Recherche en
Cancérologie de Montpellier
Campus Val d’Aurelle
34298 Montpellier cedex 5


Tél. : 33 (0)4 67 61 23 92
Fax : 33 (0)4 67 61 37 87


partners / funding

© Institut de Recherche en Cancérologie de Montpellier - 2011 - Tous droits réservés - Mentions légales - Connexion - Conception : ID Alizés