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Molecular dissection of colorectal cancer in pre-clinical models identifies biomarkers predicting sensitivity to EGFR inhibitors.

Schütte, M; Risch, T; Abdavi-Azar, N; Boehnke, K; Schumacher, D; Keil, M; Yildiriman, R; Jandrasits, C; Borodina, T; Amstislavskiy, V; et al. Schütte, M; Risch, T; Abdavi-Azar, N; Boehnke, K; Schumacher, D; Keil, M; Yildiriman, R; Jandrasits, C; Borodina, T; Amstislavskiy, V; Worth, CL; Schweiger, C; Liebs, S; Lange, M; Warnatz, H-J; Butcher, LM; Barrett, JE; Sultan, M; Wierling, C; Golob-Schwarzl, N; Lax, S; Uranitsch, S; Becker, M; Welte, Y; Regan, JL; Silvestrov, M; Kehler, I; Fusi, A; Kessler, T; Herwig, R; Landegren, U; Wienke, D; Nilsson, M; Velasco, JA; Garin-Chesa, P; Reinhard, C; Beck, S; Schäfer, R; Regenbrecht, CRA; Henderson, D; Lange, B; Haybaeck, J; Keilholz, U; Hoffmann, J; Lehrach, H; Yaspo, M-L (2017) Molecular dissection of colorectal cancer in pre-clinical models identifies biomarkers predicting sensitivity to EGFR inhibitors. Nature Communications, 8. p. 14262. ISSN 2041-1723 https://doi.org/10.1038/ncomms14262
SGUL Authors: Fusi, Alberto

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Abstract

Colorectal carcinoma represents a heterogeneous entity, with only a fraction of the tumours responding to available therapies, requiring a better molecular understanding of the disease in precision oncology. To address this challenge, the OncoTrack consortium recruited 106 CRC patients (stages I-IV) and developed a pre-clinical platform generating a compendium of drug sensitivity data totalling >4,000 assays testing 16 clinical drugs on patient-derived in vivo and in vitro models. This large biobank of 106 tumours, 35 organoids and 59 xenografts, with extensive omics data comparing donor tumours and derived models provides a resource for advancing our understanding of CRC. Models recapitulate many of the genetic and transcriptomic features of the donors, but defined less complex molecular sub-groups because of the loss of human stroma. Linking molecular profiles with drug sensitivity patterns identifies novel biomarkers, including a signature outperforming RAS/RAF mutations in predicting sensitivity to the EGFR inhibitor cetuximab.

Item Type: Article
Additional Information: Copyright The Author(s) 2017. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Keywords: MD Multidisciplinary
SGUL Research Institute / Research Centre: Academic Structure > Infection and Immunity Research Institute (INII)
Journal or Publication Title: Nature Communications
ISSN: 2041-1723
Language: eng
Dates:
DateEvent
10 February 2017Published
13 December 2016Accepted
Publisher License: Creative Commons: Attribution 4.0
PubMed ID: 28186126
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/108677
Publisher's version: https://doi.org/10.1038/ncomms14262

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