Cancer Research UK & Royal College of Surgeons Clinician Scientist Fellow, Wellcome Trust Sanger Institute.
Honorary Consultant Urologist, Addenbrooke’s Hospital, Cambridge
Email : firstname.lastname@example.org
Tom Mitchell is currently employed through a clinician scientist fellowship from Cancer Research UK and the Royal College of Surgeons. He practices as an Honorary Consultant in Urology at Addenbrooke’s Hospital with a specialist interest in the surgical management of patients who have kidney cancer. His research priority is to improve outcomes for these patients through improved understanding of tumour behaviour.
Tom’s research focusses on understanding how tumours arise and develop. The investigations began through interrogating the clonality of copy number events in multiple individual tumours to gain a consensus order in which these events occur. These methods were first applied in prostate cancer, via the International Cancer Genome Collaborative (ICGC), demonstrating common evolutionary trajectories . The concepts and specific ordering methods were further developed with an international consortium in the Evolution and Heterogeneity subgroup of the ICGC-Pan Cancer Analysis of Whole Genomes (PCAWG) project [2,3].
Such enquiries laid the foundation for timing the landmark events in clear cell renal cell carcinoma (ccRCC). Here, molecular clocks and newly defined genomic features were used to demonstrate that the hallmark event in ccRCC, loss of the short arm of chromosome 3, occurred in adolescence; many decades prior to eventual diagnosis. The relative risk of acquiring biallelic loss of VHL was calculated using an inversion of Knudson’s hypothesis, concluding that every one of us by the end of our adolescence harboured several hundred cells with 3p loss in our kidneys . To further understand the initial events underpinning kidney cancer initiation we used long-read sequencing technologies, to show that these complex genomic events often arise from single cell division errors .
Recent investigations have focussed on understanding the single cell multicellular environment of the normal and cancerous kidneys. The generation of RNA sequencing data from many hundreds of thousands of single cells has reveal multiple insights into immune function, kidney epithelial cell function, and oncogenesis. This dataset is the largest comprehensive single cell map of a renal tissue studied to date – encompassing human fetal, pediatric and adult kidneys [6,7].
Currently, the generation of additional spatial and single cell sequencing data aims to comprehensively understand the single cellular dynamics of kidney cancers; from the initiating events that precede cancer, to relatively indolent small renal masses, through to higher risk tumours and their response to systemic therapy.