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Simon Grelet, Ph.D.

Simon Grelet Ph.D.Assistant Professor

Postdoctoral Studies: Medical University of South Carolina, Hollings Cancer Center 
Ph.D.: Reims University, France 

Research Interests

Embryo-related tumor cell plasticity & primary tumor neurogenesis. 

Metastasis is the overwhelming cause of mortality in patients with solid tumors. To survive and disseminate, the tumor cells need to constantly adapt to their surrounding environment. Tumor cell plasticity associated with the epithelial-mesenchymal transition (EMT), a program observed in embryonic development, is reactivated during carcinomas progression and correlates with tumor dissemination and resistance to therapies. While observed in vivo, the EMT program is a highly dynamic and often incomplete process, resulting in cells exhibiting diverse intermediate states that maintain both epithelial and mesenchymal characteristics.

My laboratory explores the molecular mechanisms that are balancing tumor cell phenotypes and their biological impacts on the tumor microenvironment. By using genome-wide sequencing methodologies and CRISPR gene editing libraries applied to lineage tracing models, we identify new factors involved in the tumor-stroma interaction. Our current research focuses on primary tumor neurogenesis with a special emphasis on the contribution of post-transcriptional regulation and non-coding RNA species in this biological process.

Tumor neurogenesis is closely related to metastatic progression and is associated with poor clinical outcomes. The little-understood molecular mechanisms of cancer–nerve crosstalk represent therapeutic opportunities and our approach is intended to provide new tools in the prevention of cancer dissemination.

Research training positions are available for postdoc and graduate students. Email grelet.lab@gmail.com.

Research training will provide you the skills that are required for studying the Molecular Biology of the Cell as well as critical knowledge in the areas of both Cancer/Neuron cell Biology and Bioinformatics applied to high-throughput methodologies.