Mosser Group Research

The research interests of the team are focusing on the understanding of the genetic and epigenetic mechanisms linked to the development of sporadic cancers (mainly glioblastoma and colorectal cancer).

We are looking for the molecular elements associated with tumor molecular heterogeneity in terms of aggressiveness and response to therapy. Our project is thus within the scope of the improvement of solid tumors personalized medicine by using and identifying new relevant genetic and epigenetic biomarkers. By contributing to the tumor molecular stratification and to the individualization of patient care, this translational project must lead to an impact on the solid tumor diagnosis or prognostication.

To that purpose, we benefit from large regional, national and European cohorts. We also rely on the Environmental & Human Genomics platform (BIOSIT and OSUR SFR) that we have in charge. Therefore we are using and developing tailored ‘omic’ approaches required for our research. For instance, technological innovations such as Next Generation Sequencing (NGS) and genotyping of circulating DNA are developed to allow patient monitoring on liquid biopsies for therapy response assessment and relapse or treatment failure anticipation.

The expertise in Functional Genomics acquired by the team and relying on the Environmental & Human Genomics platform has been applied to the study of glioblastoma (GBM). GBM is the most frequent and the most aggressive primary brain tumor in adult. The standard therapy associates surgery, radiotherapy and alkylating chemotherapy. But the prognosis remains dismal (survival median = 15 months). There is still no efficient therapy. New strategies have to be proposed. They may rely on a better knowledge of GBM predispositions, epigenetic mechanisms, intratumor heterogeneity characteristics, or microenvironment analysis (tumor progenitor cell renewal or tumor immune infiltration characteristics).

Is the development or the use of “omic” and cellular approaches to study intertumor heterogeneity of GBM able to characterize new key somatic markers and putative therapeutic targets for GBM? 

Un marqueur épigénétique prédictif-pronostique identifié par une étude du méthylome d’une cohorte de GBM traités de façon homogène (n=400) : le statut de méthylation du promoteur de DGKI identifie parmi les patients dont le promoteur de MGMT est méthylé (potentiellement bon répondeurs) ceux qui ne tirent pas bénéfice du traitement standard. La prise en compte du statut de méthylation du promoteur DGKI améliore la stratification classique basée sur le promoteur MGMT pour les patients GBM traités par le trait

Besides, the GBM intratumor heterogeneity is poorly described. However its characterization is challenging given the systematic tumor recurrence starting from disseminated cells near the resection site. Therapeutic improvement may require biomarkers of tumor infiltration.

Are ‘omic’ approaches able to identify such markers of tumor infiltration in the brain?

Signature transcriptomique d’un panel de 100 gènes caractéristiques de l’hétérogénéité moléculaire intra-tumorale du GBM. Clustering hiérarchique des échantillons et « heatmap » des données du transcriptome. Les échantillons tumoraux sont représentés en couleur en fonction du gradient intra-tumoral : zone macroscopiquement normale en vert, zone infiltrée en jaune, tumeur floride en rouge et zone nécrotique en bleu. (Aubry M, de Tayrac M, et al. OncoTarget, 2015).

 

Etude fonctionnelle sur lignées cellulaires de gliome : expression nucléaire cellulaire d’un facteur de transcription d’expression différentielle en fonction du gradient intra-tumoral du GBM.

Technological innovations such as Next Generation Sequencing and genotyping cell-free circulating tumor DNA will improve patient care. The Rennes cancer somatic genetic laboratory is involved in the weekly molecular theranostic diagnosis of solid tumors with 2800 samples per year. This lab is the first in France using targeted-NGS as a routine method for the genotyping of solid tumors on a dedicated gene panel. This custom panel includes 100 putative predictive targets distributed within 20 cancer key-genes.

Now the question is to know whether NGS is useful to detect or identify genetic markers of sensitivity-resistance to targeted therapies in order to anticipate relapse or treatment failure. Applied to plasma free DNA, will this NGS based protocol allow the monitoring of patients affected by solid tumors, especially those treated by successive generations of tyrosine kinase inhibitors (TKI), and thus improve their progression free and overall survivals?