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.

Synthetic diagram of the TOnG team translational project


Study of GBM inter and intratumor molecular heterogeneity

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? 

An epigenetic prognostic-predictive marker identified by a methylome study of a homogeneously treated cohort of GBMs (n = 400): the methylation status of the DGKI gene promoter identify among MGMT promoter methylated GBM patients (potentially good responders) those who will not respond to the standard treatment. The assessment of DGKI methylation status therefore improves the conventional MGMT stratification of GBM patients receiving standard treatment (Etcheverry A, Aubry M, et al. PloS One. 2014 Sep).

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?

Transcriptome signature of 100 genes summarizing the GBM intratumor heterogeneity. Heatmap and samples hierarchical clustering for transcriptome data. Samples are colored according to the intratumor gradient: green for the peripheral brain zone, yellow for the interface zone, red for the tumor zone, and blue for the necrotic zone (see figure 2). (Aubry M, de Tayrac M, et al. OncoTarget, 2015).


Functional studies on glioma cell lines: cellular nuclear expression of a transcription factor that is differentially expressed through the intratumor gradient (figure 4).

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? 

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