Black, James Robert Mackinlay; (2023) Genetic and non-genetic determinants of somatic evolution in cancer. Doctoral thesis (Ph.D), UCL (University College London).

Preview

Text Thesis_full_corrected.pdf - Submitted Version Download (19MB) | Preview

Abstract

Intra-tumour heterogeneity (ITH) provides the fuel for lung cancer evolution, leading to immune evasion and resistance to therapy. Using paired whole exome and RNA sequencing data, I have catalogued genetic and non-genetic determinants of tumour evolution using a variety of bioinformatic techniques. First, I investigated transcriptional variation in 947 regions from 354 non-small cell lung cancer tumours from patients prospectively recruited into the TRACERx study. Gene expression, and its ITH, related to patterns of positive and negative selection during tumour evolution. We observed frequent copy number independent allele-specific expression (ASE) that was underpinned by epigenomic dysfunction, and was also involved in genomic-transcriptomic parallel evolution, converging on cancer gene disruption. Characterising the transcriptomes of primary-metastatic tumour pairs, metastasis-seeding potential was linked to the evolutionary context of mutations and elevated proliferation within primary tumour regions. Second, RNA variant allele frequencies were interrogated to identify putative cancer genes with a novel computational tool, RVdriver, from bulk genomic-transcriptomic data within 7,948 paired exomes and transcriptomes across 30 cancer types. RVdriver leverages this information to identify known, as well as putatively novel, cancer genes, with comparable performance to DNA-based approaches. Furthermore, RNA VAFs of individual mutations are able to distinguish ‘driver’ from ‘passenger’ mutations within established cancer genes. Third, novel computational approaches were developed that leverage transcriptional data to understand tumour evolution. A metric cataloguing the relative overrepresentation of mutations in RNAseq can provide clone-level phenotyping to help understand ctDNA shedding and metastasis; whilst multi- region DNA-RNAseq provides the opportunity to measure phenotypic plasticity, which is associated with poor clinical outcome. Overall, this work highlights the potential value of multi-omic and systems- biology approaches in cataloguing tumour evolution and finding novel therapeutic vulnerabilities in cancer to bring about patient benefit.

Download activity - last month

Export as XMLJSONCSV

Download activity - last 12 months

Export as JSONCSVXML

Downloads by country - last 12 months

Export as JSONCSVXML

Archive Staff Only

View Item