Periodic Reporting for period 1 - RCC_Evo (Modelling the Predictability and Repeatability of Tumour Evolution in Clear Cell Renal Cell Cancer)
Berichtszeitraum: 2020-04-01 bis 2022-03-31
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).
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).
We have established successful protocols to derive patient-derived and normal kidney organoids and have commenced gene-editing of these organoids and have established cultures from 24 patients with ccRCC and multiple regions per patient. We have performed initial sequencing analysis and have optimised the culture conditions to prevent tumour cells being overgrown by normal kidney cells. We are currently establishing normal kidney organoid cultures with 3p loss which will be the basis to model tumorigenesis in vitro. We have leveraged RNA sequencing data from the 67 patients and 169 regions of the TRACERx renal cohort to identify the TIME conditions associated with genomic alterations in kidney cancer. These data will be the basis of future co-culture experiments to test how they influence clonal behaviour. For co-culture experiments we have established a cohort of 10 cases with RCC and we are currently screening multiple tissue regions of these patients for response to anti-PD1 inhibition, and we will associate these findings with detailed characterisation of the immune cell composition (by multiparametric analysis of immune cell subsets and single cell RNA sequencing).
We are planning to disseminate the data on the TIME obtained by RNA sequencing within the next months and expect to have results to disseminate on the patient-derived organoid cultures within the next year.
We are planning to disseminate the data on the TIME obtained by RNA sequencing within the next months and expect to have results to disseminate on the patient-derived organoid cultures within the next year.
Kidney cancer is among the 10th most common cancers in the western world. The results from this project have the potential to improve management of ccRCC. Identifying the functional basis of tumour evolution will allow better prediction of the clinical course of ccRCC, especially immediately after surgery. WP4 will further allow us to redefine the options of therapeutical intervention by providing a more detailed mechanisms of anti-tumour immune response.