RCC_Evo · Modelling the Predictability and Repeatability of Tumour Evolution in Clear Cell Renal Cell Cancer
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2020-04-01 → 2022-03-31
- EU contribution
- €224,934
- Participants
- 1
- Scheme
- MSCA-IF-EF-ST
Lines connect the coordinator with its partners.
Results in brief
Modelling the Predictability and Repeatability of Tumour Evolution in Clear Cell Renal Cell Cancer
Kidney cancer is among the 10 most frequently diagnosed cancers and its incidence is rising1. Clear cell Renal Cell Cancer (ccRCC), the most common subtype accounts for 75% of all cases. The Cancer Genome Atlas has defined the mutational landscape of ccRCC and have identified loss of the short arm of chromosome 3 and mutations in the VHL gene as the most common alteration in kidney cancer cells. This is followed by mutations of other genes, like PBRM1, SETD2 and BAP1. Tracking Renal Cell Cancer Evolution through therapy (TRACERx Renal) is a multi-center, longitudinal cohort study and evaluates how heterogeneous tumours are and how they have evolved over time. TRACERx has identified 7 subtypes of how tumours evolve and these associate with the clinical behaviour of ccRCC. Tumours with low heterogeneity rapidly progressed to multiple tissue sites. Tumours with high ITH showed attenuated progression, and metastatic capacity evolved gradually, starting with a solitary metastasis. Given these regarding the evolutionary subtypes and their association with clinical behaviour, understanding of the functional bases of these patterns is of major interest. Therefore, more faithful in vivo and in vitro models are necessary. Beside the intrinsic changes in tumour cells, the tumour microenvironment (TME) can have both tumour-promoting and suppressive functions and impact tumour progression. ccRCCs are highly immune infiltrated but in contrast to other solid cancer this is associated with worse prognosis for the patient. The majority of infiltrating immune cells are T cells, some of which show an exhausted phenotype, characterized by upregulation of inhibitory receptors, including PD-1 and CTLA-4, which have also been exploited as therapeutic targets. In advanced and metastatic tumours, infiltration of immunosuppressive macrophages has been described. The importance of the TME is further underlined by the fact that most approved therapies of ccRCC target the TME, either the immune compartments or targeting the blood vessel system. Molecular markers for therapy response are still missing, highlighting the ongoing need understand the underlying mechanisms of therapy response for each evolutionary subtype. The objectives of this project are: 1. Refine the ordering and clonal resolution in selected cases of the TRACERx Renal Study by micro-biopsy profiling (WP1). 2. Characterise the predictability of evolutionary trajectories will be addressed through repeated passaging of tumour PDOs followed by targeted panel sequencing to detect enrichment of mutations and changes in the clonal composition of organoids (WP2). 3. Analyse the metastatic capacity for metastatic drivers in the context of each evolutionary subtype and define the number of metastatic sites (WP3). 4. Characterise the response rates to immune checkpoint inhibition in PDO co-cultures for each evolutionary subtype (WP4). 5. Test the repeatability of the evolutionary trajectories through experimental manipulation of the genotype combination and sequence in normal kidney organoids (WP5).
Data: CORDIS, © European Union
Project objective
Kidney cancer is among the 10 most frequently diagnosed cancers and its incidence is rising. Clear cell Renal Cell Cancer (ccRCC) is the most common subtype and is characterized by early 3p loss. The deleted region on chromosome 3p harbours a number of tumour suppressor genes namely VHL, PBRM1, SETD2 and BAP1, which are frequently mutated subsequent to 3p loss. TRACERx Renal is a multi-center, longitudinal cohort study, which studies tumour evolution and intratumoural heterogeneity through multi-region profiling of primary tumours. Interim findings have defined 7 evolutionary subtypes. I will model the predictability and repeatability of these evolutionary trajectories in patient-derived tumour organoids (PDO), in patient-derived xenografts (PDX), and in gene-edited human proximal tubule cells (HPTC). Preliminary evidence suggests that ccRCC genotypes are associated with specific TME conditions. I will develop PDO models in which I will co-culture tumour cells with tumour infiltrating leucocytes and cancer associated fibroblasts. I will refine the mutational ordering and clonal resolution in selected cases of the TRACERx Renal Study by micro-biopsy profiling. Predictability of evolutionary trajectories will then be addressed through repeated passaging of tumour PDOs followed by targeted panel sequencing. The function of metastatic driver events will be characterised in PDX. The repeatability of the evolutionary trajectories will be studied through experimental manipulation of the genotype sequence in HPTCs. Co-culture PDOs will be used to define response to immune checkpoint inhibition. The results will allow a personalized prediction of the clinical course of ccRCC and the response to immune checkpoint inhibition. I will identify mechanisms of tumour progression and the involvement of the TME. This will result in the identification of previously unknown targetable weaknesses in ccRCC.
Original text from CORDIS.
Participants
- THE FRANCIS CRICK INSTITUTE LIMITED · LondonCoordinatorUnited Kingdom
Links
Data: CORDIS, © European Union
