Dataset Information

Max Planck Institute for molecular Genetics

ABSTRACT: Organisation EGAG00000000008

PROVIDER: EGAG00000000008 | EGA |

REPOSITORIES: EGA

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Publications

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

Schütte Moritz M Risch Thomas T Abdavi-Azar Nilofar N Boehnke Karsten K Schumacher Dirk D Keil Marlen M Yildiriman Reha R Jandrasits Christine C Borodina Tatiana T Amstislavskiy Vyacheslav V Worth Catherine L CL Schweiger Caroline C Liebs Sandra S Lange Martin M Warnatz Hans-Jörg HJ Butcher Lee M LM Barrett James E JE Sultan Marc M Wierling Christoph C Golob-Schwarzl Nicole N Lax Sigurd S Uranitsch Stefan S Becker Michael M Welte Yvonne Y Regan Joseph Lewis JL Silvestrov Maxine M Kehler Inge I Fusi Alberto A Kessler Thomas T Herwig Ralf R Landegren Ulf U Wienke Dirk D Nilsson Mats M Velasco Juan A JA Garin-Chesa Pilar P Reinhard Christoph C Beck Stephan S Schäfer Reinhold R Regenbrecht Christian R A CR Henderson David D Lange Bodo B Haybaeck Johannes J Keilholz Ulrich U Hoffmann Jens J Lehrach Hans H Yaspo Marie-Laure ML

Nature communications 20170210

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 bio ...[more]

PMID: 28186126

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Project description:Open science (OS) is of paramount importance for the improvement of science worldwide and across research fields. Recent years have witnessed a transition toward open and transparent scientific practices, but there is still a long way to go. Early career researchers (ECRs) are of crucial relevance in the process of steering toward the standardization of OS practices, as they will become the future decision makers of the institutional change that necessarily accompanies this transition. Thus, it is imperative to gain insight into where ECRs stand on OS practices. Under this premise, the Open Science group of the Max Planck PhDnet designed and conducted an online survey to assess the stance toward OS practices of doctoral candidates from the Max Planck Society. As one of the leading scientific institutions for basic research worldwide, the Max Planck Society provides a considerable population of researchers from multiple scientific fields, englobed into three sections: biomedical sciences, chemistry, physics and technology, and human and social sciences. From an approximate total population of 5,100 doctoral candidates affiliated with the Max Planck Society, the survey collected responses from 568 doctoral candidates. The survey assessed self-reported knowledge, attitudes, and implementation of different OS practices, namely, open access publications, open data, preregistrations, registered reports, and replication studies. ECRs seemed to hold a generally positive view toward these different practices and to be interested in learning more about them. Furthermore, we found that ECRs' knowledge and positive attitudes predicted the extent to which they implemented these OS practices, although levels of implementation were rather low in the past. We observed differences and similarities between scientific sections. We discuss these differences in terms of need and feasibility to apply these OS practices in specific scientific fields, but additionally in relation to the incentive systems that shape scientific communities. Lastly, we discuss the implications that these results can have for the training and career advancement of ECRs, and ultimately, for the consolidation of OS practices.

Dataset Information

Max Planck Institute for molecular Genetics

Publications

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

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