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• What are the optimal computational methods for evolutionary profiling based on somatic copy number variation (SCNV) in mesothelioma?
• Are SCNV evolutionary profiles in the PRiSM study associated with clinical phenotype (e.g., histological sub-type, systemic immune response, sarcopenia/altered body composition) and/or outcomes (including survival, subsequent chemotherapy response and/or tolerance)?
Relevance to cancer and the research themes and strategic areas of the Centre:
Recent whole genome sequencing data in Mesothelioma implicates clonal architecture as an important determinant of survival (1) in what is a highly heterogenous disease. However, this data is based on multi-region sampling from only 22 patients at a single centre.
This PhD studentship will utilise genomic, clinical, and imaging data from a recently completed multi-centre study called PRiSM (Prediction of Resistance to chemotherapy using Somatic Copy Number Variation in Mesothelioma) (2). PRiSM (led by Blyth) has collated genome-wide SCNV data (Illumina CytoSNP 850k), clinical outcomes and a range of additional phenotyping layers (including circulating blood biomarkers, body composition indices derived from CT, AI-derived tumour volumes (3) plus surplus tumour DNA) from 266 mesothelioma patients treated with chemotherapy at 4 UK centres. SCNV data are inherently valuable for evolutionary genomic questions, but current computational methods are generally based on sequencing data (1, 3-5). As part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium of ICGC, Yuan has played a leading role in development of evolutionary genomic methods and is ideally placed to support their adaption to SCNV data.
This project will address fundamental questions regarding the sequential events underpinning mesothelioma evolution, aligning well with the similarly focused PREDICT-Meso International Accelerator. The data generated will also support proper positioning of PREDICT-Meso genetically derived mouse models which, in the near future will incorporate temporally separated genomic events using tandem arrayed regulator (TAR) alleles (via the MRC National Mouse Genetics Network).
Techniques/model systems to be used:
• Integer somatic copy number analysis using ASCAT (6). This tool will be used to make allele specific copy number and tumour purity calls. The result will be our primary characterisation of genomic landscape in PRiSM samples.
• Copy number signature analysis (7). This analysis will be used to identify mutational processes underlying copy number alterations across PRiSM samples.
• Intratumour heterogeneity (ITH) analysis using surplus tumour DNA data (8). ITH of point mutations to provide complimentary characterisation of clonal architecture in PRiSM samples.
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