Project description
Genomic instability and models of tumour evolution
Despite progress in cancer drug development, the majority of patients with advanced disease have poor prognoses due to cancer drug resistance. Longitudinal clinical studies have revealed that tumour DNA copy-number heterogeneity correlates with drug resistance, disease recurrence and death in non-small cell lung cancer (NSCLC). Current animal models of NSCLC do not reflect the multiple distinct patterns of genome instability and intra-tumour heterogeneity observed in patients. The EU-funded PROTEUS project aims to develop mouse lung cancer models that better recapitulate the tumour immune evasion and genome instability processes observed in patients with NSCLC. This will help elucidate the evolutionary patterns of genomic instability, understand mechanisms of immune evasion and test novel therapies aimed at improving patient stratification, treatment and survival.
Objective
Despite progress in cancer drug development, the majority of patients who present with advanced, metastatic, solid tumours have incurable disease due to underlying cancer genomic diversity that provides a substrate for evolution and selection of drug resistance. The aim of this proposal is to describe, synthesise and model the micro- and macroevolutionary patterns of genomic instability underpinning the evolutionary dynamics of tumour life histories, to improve patient stratification, treatment and survival outcomes. Longitudinal clinical studies such as TRACERx are highlighting the complex processes that generate this intra-tumour heterogeneity (ITH). Genome Instability (GIN) describes aberrant changes within the genome, encompassing genome doubling (GD), numerical or structural chromosomal instability (CIN), and elevated DNA sequence mutational diversity. TRACERx has revealed that elevated DNA copy-number ITH rather than DNA sequence diversity is associated with increased risk of recurrence or death in non-small cell lung cancer (NSCLC). Why macroevolutionary CIN rather than somatic mutational diversity is associated with poor outcome remains unclear. Current animal models of NSCLC do not sufficiently model the multiple distinct patterns of GIN operating in patients. We aim to develop mouse lung cancer models that recapitulate the patterns of GIN observed in NSCLC patients. Using tumour barcode sequencing, a sensitive method of quantifying cellular fitness and individual tumour growth, we will investigate the effects of targeted-, chemo- and immuno-therapy on the newly generated GIN models. We will decipher if distinct patterns of GIN increase metastatic potential and treatment failure, and test if high mutational burden or high CIN increases the frequency of GD in cancer. Finally, we aim to investigate the effects of GIN upon immune surveillance, immune evasion, immunotherapy response, and the interactions between tumours and the tumour microenvironment.
Fields of science
- natural sciencesbiological sciencesgeneticsDNA
- medical and health sciencesclinical medicineoncologylung cancer
- medical and health sciencesbasic medicinepharmacology and pharmacydrug resistance
- medical and health sciencesbasic medicineimmunologyimmunotherapy
- natural sciencesbiological sciencesgeneticsgenomes
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Funding Scheme
ERC-ADG - Advanced GrantHost institution
NW1 1AT London
United Kingdom