Can response to Epidermal Growth Factor Receptor antibodies in patients with metastatic Colorectal Cancer be predicted?
From 01-01-2009 to 31-12-2012
Description
Advanced bioinformatics methods successfully applied in earlier work (20,26,27) will be applied on a larger scale. For this purpose a novel set of unique metastatic biosamples will be used, to be prospectively collected from 250 chemo naive metastatic CRC patients in the framework of an investigator driven, industry sponsored phase I-II dose escalation study for irinotecan-cetuximab combination therapy (Everest II). In this trial biopsies of liver or other metastatic sites will be obtained at 3 different time points, in analogy to a previous trial perfomed by this group (Everest I)(20). Samples will be obtained at baseline (b1), at the third treatment administration (b2) and upon progression of disease (b3). Agreement was sought and obtained from the sponsor for an independent investigator driven biomarker analysis of these samples. The bioinformatics methodology to integrate the prospectively collected mutation,and microarray data will be fine tuned and customised for the purpose of this study for the purpose of (i) generating new insights in the yet unknown working mechanism of a promising drug (ii) applying advanced bioinformatics algorithms to generate the molecular signature for (a) sensitivity to EGFR inhibitors in chemo naive mCRC. (b) acquired resistance to EGFR inhibitors in mCRC. (iii) to identify druggable pathways in metastatic colorectal cancer The combination of the pre-mentioned factors puts the proposed study in a unique position to generate the new scientific observations needed to reach its objectives. Moreover: - The biosamples to be used constitute the only existing series worldwide of prospectively collected plasma, primary and metastatic tumour samples of patients treated with the irinotecan-cetuximab combination therapy. 7 - Obtained from both a chemonaive and chemorefractory (previous study, Everest I) patient population, potentially divergent action mechanisms can be detected. - Repetitive metastatic tumour samples will be obtained, allowing the generation of post treatment (week 3) as well as baseline plasma protein and metastatic tumour gene signatures. This way both static and dynamic expression profiles can be investigated, baseline predictive signatures can be refined and compensatory activation of pathways revealed
Team
- Bart De Moor, Co-promoter
- E. Van Cutsem, Co-promoter (External)
- Sabine Tejpar, Promoter (External)
Financing
Funding: FWO - Research Foundation - Flanders
Program/Grant Type: FWO Research Grant - FWO Research Grant
Events
2/09/2024:
PhD defense - Martijn Oldenhof
Machine Learning for Advanced Chemical Analysis and Structure Recognition in Drug Discovery
3/09/2024:
Meet the Jury Igor Tetko on Advanced Machine Learning in Drug Discovery
12/09/2024:
Multimodal analysis of cell-free DNA for sensitive cancer detection in low-coverage and low-sample settings
Seminar by Antoine Passemiers
News
STADIUS Alumni Herman Verrelst – new CEO of Biocartis
08 June 2017
Herman Verrelst, the founder of KU Leuven spin-off Cartagenia, who has been working in Silicon Valley, US for the last few years will be returning to Belgium to follow the steps of Rudi Pauwels as CEO of the Belgian diagnostic company, Biocartis.
Supporting healthcare policymaking via machine learning – batteries included!
29 May 2017
STADIUS takes the lead in the data analytics efforts in an ambitious European Project MIDAS.
Marc Claesen gives an interview about his PhD for the magazine of the Faculty of Engineering Sciences "Geniaal"
10 February 2017
Did you know that in Belgium approximately one third of type 2 diabetes patients are unaware of their condition?
Joos Vandewalle is nieuwe voorzitter KVAB
09 October 2016
Op 5 oktober 2016 heeft de Algemene Vergadering van de Academie KVAB Joos Vandewalle verkozen tot voorzitter van de KVAB.