Gliomic : Integrating clinical data to MALDI MSI and spatial-resolved tissus proteomic
Support: INCA, Siric OncoLille, La Ligue Contre Le Cancer
Partners : Oncovet Clinical Research (OCR), CHRU Lille, UZH (Cancer Network Zurich, Pr. M. Weller)
Anocef, 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, hyperméthylateur 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.
Le Rhun, E., Duhamel, M., Wisztorski, M., Gimeno, J. P., Zairi, F., Escande, F., Reyns, N., Kobeissy, F., Maurage, C. A., Salzet, M., and Fournier, I. (2017) Evaluation of non-supervised MALDI mass spectrometry imaging combined with microproteomics for glioma grade III classification. Biochimica et biophysica acta 1865, 875-890
OmicSeth : Omics Senology Therapy
Support: Novartis, Pfizer
Partners : COL, OCR
Despite the advent of precision medicine for advanced breast cancer (ABC) patients with several authorized targeted therapies, personalized therapy has not been reached yet for these patients. Recent efforts to identify predictive biomarkers of response to targeted therapies such as everolimus or palbociclib have not been successful. Therapeutic strategies guided by tumor genomic alterations to identify candidate drivers of tumor progression to tailor treatments have not improved outcome. Moreover, due to the infrequency of genomic alterations in breast cancer, a candidate driver could not be detected in all patients. Another potential bottleneck responsible for this lack of success is the limited fidelity of transcription, which can alter the translation and functional role of the genomic alterations.
These difficulties can be addressed by analyzing the functional activity of actionable pathways and processes using high-throughput microproteomics. We propose a pilot prospective monocentric phase 2 trial to evaluate the feasibility and clinical benefit of prospectively using a high-throughput microproteomic technology to select approved drugs to treat patients with heavily pretreated and progressing advanced breast cancer, lacking genomic drivers. In this context, we also integrate the proteome issued from alternative proteins that we named the Ghost-Proteome which is issued from non-cod ing region of mRNA but is also implicated in tumor progression.