Postdoctoral Fellow

Gerard Martínez-Cebrián

Profile

 

I hold a PhD in Biomedicine by Univseritat Pompeu Fabra (Barcelona) specialized in transcription regulation. After completing my PhD, I started my first postdoc at New York University to continue to learn new aspects and techniques relevant for transcription and epigenetic regulation in Rhabdomyosarcoma biology and muscle differentiation. Now, at Institut Josep Carreras, I focus on transcription regulation in acute myeloid leukemia. I use my bioinformatician skills and my wet lab knowledge to narrow the link between basic research and new therapeutic targets and treatments for life-threatening diseases with a genetic background using advanced sequencing techniques.

Project description

Mechanisms of gene expression of cohesin-mutant AML

Acute myeloid leukemia (AML) is a highly aggressive cancer that affects white blood cell progenitors in the bone marrow. Despite being one of the deadliest subtypes of leukemia, AML treatment has not undergone significant improvements in the last 30 years. This is mainly due to our lack of understanding of the biology underlying the most commonly mutated genes in AML, holding back the development of personalized treatments. Therefore, an in-depth understanding of each AML subtype is urgently required to find new specific vulnerabilities. This is the case of mutations in the cohesin complex, which are found in up to 15% of AML patients. Cohesin is a ring-shaped protein complex that acts as a global organizer of 3D genome topology and has an essential role in the regulation of gene expression. Despite their frequency, the mechanistic consequences of cohesin mutations in AML are not fully understood. In this research proposal, we aim to identify gene expression patterns associated to cohesin mutations in a cohort of cellular models, including primary human hematopoietic stem cells and AML patient data. In collaboration with Dr. Aristotelis Tsirigos at NYU, we will develop new machine learning models that link cohesin-specific gene expression patterns to biological mechanisms using an array of multi-omics techniques, including Cut&Run, ATAC-seq and HiC. Finally, through established partnerships with cutting-edge biotech companies, we plan to design, produce and test new small molecule compounds that target pathways specifically deregulated in cohesin-mutant AML. Overall, this research proposal aims to deepen our understanding of the role of cohesin in AML with the final goal of finding new strategies for a muchneeded personalized therapy.

Free keywords:  Cohesin, Bioinformatics, Sequencing, Machine Learning, AML