Proteomic & metabolomic GBM Classification & prognosis

Supports : INCA, Siric OncoLille, La Ligue Contre Le Cancer
Partners : Oncovet Clinical Research (OCR), CHRU Lille, UZH (Cancer Network Zurich, Pr. M. Weller), Anocef

 TechnologicalInnovations EarlyDiagnosis Gliomic

In many tumors, including glioma, intra-tumor molecular heterogeneity is linked to tumor microenvironment responsible for a poor prognosis of the patients, therapy resistance and tumor relapse. The treatment of gliomas is based on SBR classification of tumors of the central nervous system WHO (2007). This classification is questioned because of the incomplete inter-observer reproducibility but also intra-observer. Histo-molecular classifications of glioma tend to complement the WHO purely microscopic classification. Moreover, after expert collegiate replay slides, eliminating reproducibility problems, two patients with the same tumor (histological type and SBR grade) often have a very different life expectancy after receiving the same treatment. New biomarkers are absolutely necessary to streamline the therapeutic sequence, identify response factors to treatments that might improve the duration and quality of survival of patients with glioma. These biomarkers should better stratify patients in clinical trials. Recent clinical studies (EORTC, RTOG) confirmed the interest 1p19q the co-deletion in the management of grade 3 gliomas, inciting to adapt the therapeutic management according to the presence or absence of a deletion 1p19q. The most significant recent studies converge to epigenetic modifications (MGMT methylation, hyper methylation phenotype of gliomas with IDH1 mutation of genes / IDH2, hypomethylation mutation phenotype of gliomas with histone H3). Thus, it appears that it is necessary to create a novel classification of human glioma tumor heterogeneity to overcome recurrence and resistance to therapy. Evaluation of the discrepancy or correlation between the standard WHO 2007 classification the novel ones based on HR MALDI MSI coupled to Spatio-temporal micro-proteomic associated with clinical data will be the first main aim of the project. The second ones is to address the following questions i.e. i) do psychosocial factors (hopelessness, social support and emotional regulation) predict prognosis in BT, ii) ido local and circulating extracellular vesicles (EVs) reflect relevant biology profiles in relation to tumor cell secretion and the response of the tumor’s micro-environment, and perhaps mediate the effects of psychosocial and neurophysiological factors on BT prognosis.


  • Duhamel, M., Drelich, L., Wisztorski, M., Aboulouard, S., Gimeno, J. P., Ogrinc, N., ... & Salzet, M. (2022). Spatial analysis of the glioblastoma proteome reveals specific molecular signatures and markers of survival. Nature Communications, 13(1), 6665.
  • Drelich, L. (2020). De l’hétérogénéité intra-tumorale à la recherche de vésicules extracellulaires au sein de biopsie liquide en vue d’une médecine personnalisée (Doctoral dissertation, Université de Lille (2018-2021)).
  • Le Rhun, E., Seoane, J., Salzet, M., Soffietti, R., & Weller, M. (2020). Liquid biopsies for diagnosing and monitoring primary tumors of the central nervous system. Cancer letters, 480, 24-28.
  • Le Rhun, E. (2017). Recherche de biomarqueurs protéiques dans le but de réaliser une classification moléculaire des gliomes: étude GLIOMIC (Doctoral dissertation, Université du Droit et de la Santé-Lille II).
  • Lerhun E, Duhamel M, Wisztorski M, Gimeno JP, Zairi F, Escande D, Reyns N, Kobeissy F, Maurage CA, Salzet M, Fournier I Evaluation of Non-Supervised MALDI Mass Spectrometry Imaging Combined to MicroProteomics for Glioma Grade III Classification. Biochim Biophys Acta. (2017) 865(7):875-890
  • Duhamel, M., Le Rhun, E., Wisztorski, M., Zairi, F., Escande, F., Maurage, C., ... & Salzet, M. (2016). P06. 11 Classification of high-grade glioma using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry imaging (MALDI MSI): interim results of the GLIOMIC study.
  • Le Rhun, E., Duhamel, M., Wisztorski, M., Zairi, F., Maurage, C. A., Fournier, I., ... & Salzet, M. (2015). METB-07classification of high grade glioma using matrix-assisted laser desorption/ionization mass spectrometry imaging (Maldi MSI): interim results of the gliomic study. Neuro-oncology, 17(Suppl 5), v136.