Mark Robinson, PhD

During my PhD at Cardiff University I developed novel bioinformatics methods to analyze nucleosome maps generated by MNase-digest sequencing in order to understand the roles of chromatin remodelers in controlling developmental expression programs through nucleosome positioning. Following my PhD I moved to the lab of Dr. Niklas Feldhahn at Imperial College London where I first became interested in hematological oncology research. Our work mapping DNA-damage and enhancer reprogramming in transformed B-cells helped to explain why lineage specific markers recurrently mutated in B-cell acute lymphoblastic leukemia (B-ALL). I also performed topology mapping to identify oncogenic enhancer co-option, uncovering the mechanisms of MECOM expression and function underlying the dismal prognosis of this subset of acute myeloid leukemia patients. To further my interest in computational hematology-oncology I joined the lab of Dr. Markus Müschen in 2019 working alongside bench scientists to identify novel therapeutic vulnerabilities of B-cell malignancies. Through integrative analysis of clinical, transcriptional, proteomic and phosphoproteomics data in B-ALL and mantle cell lymphoma (MCL) models I helped uncover an unexpected mechanism of lipid-raft formation leading to PI3K amplification loop downstream of the B-cell receptor. Working alongside Dr. Lai Chan, my identification of mutational segregation between patient cohorts with STAT5- and ERK-pathway driven B-ALL helped lead to the development of a concept of oncogene convergence. This work showed that convergence on a single oncogenic driver was essential for development of B-ALL, and that activation of divergent pathways subverts oncogenesis. This convergence theory gives rise to the exciting possibility of combining divergent pathway activation synergistically with principal driver inhibition as a novel therapeutic strategy. By extending this analysis to study all major oncogenic pathways pan-cancer I now aim to identify whether oncogenic convergence is unique to B-ALL, or whether it represents a new hallmark of cancer that can be exploited to design personalized combination therapies.