Summary
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.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/835297 |
| Start date: | 01-06-2019 |
| End date: | 30-11-2024 |
| Total budget - Public funding: | 2 500 000,00 Euro - 2 500 000,00 Euro |
Cordis data
Original description
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.Status
SIGNEDCall topic
ERC-2018-ADGUpdate Date
27-04-2024
Images
No images available.
Geographical location(s)
