Opendata, web and dolomites

RCC_Evo SIGNED

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

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 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.

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

Project "RCC_Evo" data sheet

The following table provides information about the project.

Coordinator
THE FRANCIS CRICK INSTITUTE LIMITED 

Organization address
address: 1 MIDLAND ROAD
city: LONDON
postcode: NW1 1AT
website: www.crick.ac.uk

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

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE FRANCIS CRICK INSTITUTE LIMITED UK (LONDON) coordinator 224˙933.00

Map

 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.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "RCC_EVO" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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

More projects from the same programme (H2020-EU.1.3.2.)

TheaTheor (2018)

Theorizing the Production of 'Comedia Nueva': The Process of Play Configuration in Spanish Golden Age Theater

Read More  

GuideArtifEvol (2019)

Tracking and guiding artificial enzyme evolution via landscape inference

Read More  

HOCOM (2019)

A Transparent Hole Conductor by Combinatorial Techniques for Next-Generation Energy Conversion Devices

Read More