banda transcan 2 2016ul

Title:
Predictive models of therapy response in pancreatic neuroendocrine tumors

Project Coordinator:
Thomas M.  Gress / Malte Buchholz (Germany), University of Marburg, Clinic for Gastroenterology, Endocrinology and Metabolism, Marburg

Project Partners:
Hans Kestler (Germany), Ulm University, Institute of Medical Systems Biology, Ulm
Massimo Milione (Italy), IRCCS Foundation, National Cancer Institute, Milano
Emmanuel Barillot (France), Institut Curie, Bioinformatics and Computational Systems Biology, Paris

Project Abstract:
Pancreatic neuroendocrine tumors (PanNETs) are rare neoplasms of the pancreas and have a mortality rate of 60%. Systemic therapies form the mainstay of treatment, but no molecular markers are currently established that predict an individual patient’s response to any given therapy. Different regimens are thus often administered sequentially until objective response is achieved, placing considerable burden on patients and diminishing therapeutic windows. The clinical partners in this consortium have access to large clinically and molecularly well-defined cohorts of PanNET patients, including samples and data from the most comprehensive molecular analysis of PanNET tumors to date conducted within the International Cancer Genome Consortium (ICGC). Complementary to this, the participating computational biology groups contribute expertise and computational tools for statistical analysis of high-throughput biological data, integration of heterogeneous biological data, and network modeling. Creating unique synergies, this collaborative project will perform systems biology-based analyses of the PanNET data as well as additional publicly available data sets in order to i) identify novel marker signatures in PanNET samples predicting individual patient response to approved therapies; ii) develop new computational methods and construct models of regulatory networks in PanNET to identify novel opportunities for therapeutic intervention with substances used in treatment of other cancers; and iii) validate predictions derived from these analyses in in vitro and in vivo models of PanNET. We expect this project to i) Implement precision biomarker models for a better therapeutic stratification of PanNET patients, ii) improve clinical decision making and medical treatment of PanNET patients, iii) improve our knowledge of fundamental biological mechanisms active in PanNET and iv) generate significant methodological advancements in the field of precision medicine and systems biology.

 

(Project funded under JTC 2017)


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TRANSCAN-3   JOINT TRANSNATIONAL CALL 2022 on:
 "Novel translational approaches to tackle the challenges of hard-to-treat cancers from early diagnosis to therapy"  

is open for submission

Please visit the TRANSCAN-3 website at
https://transcan.eu/funding/calls/joint-call-jtc-2022-.kl


Other news:

The Digital Institute for Cancer Outcomes Research (DIGICORE),  is delighted to announce an innovative new training programme for early career researchers in oncology: IDEAL4RWE.
 Please register for an introductory webinar on the19th April 2022(https://lnkd.in/ez7y4kWU).
Brochure for more details: https://tinyurl.com/y7aurdtk


 The first TRANSCAN-3 call (JTC 2021) on:
"Next generation cancer immunotherapy: targeting the tumour microenvironment"
is closed for submission

International Networking Event (virtual)
on 22 April 2021 hrs 9:00 CET
will focus on the forthcoming co-funded JTC 2021 on:
"Next generation cancer immunotherapy: targeting the tumour microenvironment" 
the event is organized by TUBITAK under the “Turkey in Horizon 2020 Phase II” Technical Assistance Project
in cooperation with TRANSCAN-3

The new ERA-NET Cofund TRANSCAN-3:
 Sustained collaboration of national and regional programmes in cancer research
is funded by the European Commission under H2020  which started on 1st March 2021 and will last five years (G. A. no. 964264)

A TRANSCAN-2 brochure, highlighting key achievements, is available for download

 

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All the TRANSCAN-2 newsletters:

Newsletter 10, Sept.2020
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Newsletter 8, May 2019
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Newsletter 5, March 2018
Newsletter 4, Dec. 2017
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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 643638.

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