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Modelling the Predictability and Repeatability of Tumour Evolution in Clear Cell Renal Cell Cancer

Total Cost €


EC-Contrib. €






 RCC_Evo project word cloud

Explore the words cloud of the RCC_Evo project. It provides you a very rough idea of what is the project "RCC_Evo" about.

identification    suppressor    inhibition    chromosome    mechanisms    tumours    fibroblasts    profiling    predictability    followed    tme    evolutionary    kidney    ccrcc    repeated    targetable    progression    characterised    leucocytes    xenografts    interim    cancer    incidence    center    metastatic    hptc    pdx    weaknesses    micro    hptcs    clinical    renal    preliminary    genotypes    tubule    genotype    vhl    subtypes    resolution    experimental    cohort    manipulation    bap1    repeatability    tracerx    mutational    tumour    genes    passaging    clear    previously    edited    heterogeneity    harbours    diagnosed    involvement    cell    driver    intratumoural    primary    cells    immune    clonal    refine    proximal    evolution    culture    frequently    patient    panel    sequence    subsequent    infiltrating    organoids    cancers    mutated    course    gene    checkpoint    co    trajectories    human    pbrm1    model    suggests    region    function    subtype    personalized    sequencing    pdos    longitudinal    rising    pdo    prediction    events    deleted    3p    biopsy    models    unknown    setd2   

Project "RCC_Evo" data sheet

The following table provides information about the project.


Organization address
address: 1 MIDLAND ROAD
city: LONDON
postcode: NW1 1AT

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 224˙933 €
 EC max contribution 224˙933 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2019
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2020
 Duration (year-month-day) from 2020-04-01   to  2022-03-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 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.

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The information about "RCC_EVO" are provided by the European Opendata Portal: CORDIS opendata.

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