Postdoctoral Fellow

Maria Rigau de Llobet

Profile

I am a bioinformatician and I did my PhD at the Spanish Cancer Research Centre and the Barcelona Supercomputing Centre, during which I studied genetic structural variants in healthy populations. During my postdoc at the Laboratory of Medical Sciences (London, UK), I studied determinants of 3D genome organization and the relationship with gene regulation in different developmental processes. At the IJC, I study the role of non-coding mutations in B cell Acute Lymphoblastoid Leukemia initiation and relapse.

Project description

B-cell acute lymphoblastic leukaemia (B-ALL) is the most common paediatric cancer. Unfortunately, 20% of diagnosed children relapse after treatment and 65% of relapsed patients perish. While the causes of relapse are not completely understood, there is evidence suggesting that non-coding mutations and the tumour microenvironment might play important roles in disease persistence. The overarching goal of this project is to decipher the cellular and molecular basis of relapse in paediatric B-other ALL, a B-ALL heterogeneous subtype characterized by high rate of unexpected relapse and mortality. Building on my expertise in integrating large multi-omics datasets to study non-coding genome variation and its impact on gene regulation, I will first use single-cell omics generated by the Javierre group to characterize the subpopulations of leukaemic cells and the tumour microenvironment cell types at diagnosis, remission and relapse. Comparing relapsed versus non-relapsed patients will allow me to discover new biomarkers to better predict relapse. I will combine these results with gene regulatory data of healthy B cell differentiation recently produced by the Javierre group to pinpoint regulatory elements (e.g., enhancers) and their target genes that, when mutated or epimutated, are likely to promote malignant transformation and/or relapse. Finally, focused on these regulatory elements and using DREC-seq, a new method developed by the group, I will perform the first comprehensive screening of non-coding mutations and epimutations underlying paediatric B-ALL. This will allow the disclosure of new alterations, genes and gene pathways potentially implicated in malignant transformation and relapse, which could be novel therapeutic targets and biomarkers. To achieve this, artificial intelligence knowledge acquired on the proposed secondment will be fundamental. This interdisciplinary project will provide unprecedented insights into our understanding of B-ALL. Moreover, it will allow to predict which patients will unexpectedly relapse and propose new therapeutic strategies to ultimately avoid relapse and mortality.