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.

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

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.)

NarrowbandSSL (2019)

Development of Narrow Band Blue and Red Emitting Macromolecules for Solution-Processed Solid State Lighting Devices

Read More  

DEF2DEV (2019)

Identification of the mode of action of plant defensins during root development and plant defense responses.

Read More  

RipGEESE (2020)

Identifying the ripples of gene regulation evolution in the evolution of gene sequences to determine when animal nervous systems evolved

Read More