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Precision oncology based on omics data: The NCT Heidelberg experience

Overview of attention for article published in International Journal of Cancer, June 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

policy
1 policy source
twitter
8 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
135 Dimensions

Readers on

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134 Mendeley
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Title
Precision oncology based on omics data: The NCT Heidelberg experience
Published in
International Journal of Cancer, June 2017
DOI 10.1002/ijc.30828
Pubmed ID
Authors

Peter Horak, Barbara Klink, Christoph Heining, Stefan Gröschel, Barbara Hutter, Martina Fröhlich, Sebastian Uhrig, Daniel Hübschmann, Matthias Schlesner, Roland Eils, Daniela Richter, Katrin Pfütze, Christina Geörg, Bettina Meißburger, Stephan Wolf, Angela Schulz, Roland Penzel, Esther Herpel, Martina Kirchner, Amelie Lier, Volker Endris, Stephan Singer, Peter Schirmacher, Wilko Weichert, Albrecht Stenzinger, Richard F. Schlenk, Evelin Schröck, Benedikt Brors, Christof von Kalle, Hanno Glimm, Stefan Fröhling

Abstract

Precision oncology implies the ability to predict which patients will likely respond to specific cancer therapies based on increasingly accurate, high-resolution molecular diagnostics as well as the functional and mechanistic understanding of individual tumors. While molecular stratification of patients can be achieved through different means, a promising approach is next-generation sequencing of tumor DNA and RNA, which can reveal genomic alterations that have immediate clinical implications. Furthermore, certain genetic alterations are shared across multiple histologic entities, raising the fundamental question of whether tumors should be treated by molecular profile and not tissue of origin. We here describe MASTER (Molecularly Aided Stratification for Tumor Eradication Research), a clinically applicable platform for prospective, biology-driven stratification of younger adults with advanced-stage cancer across all histologies and patients with rare tumors. We illustrate how a standardized workflow for selection and consenting of patients, sample processing, whole-exome/genome and RNA sequencing, bioinformatic analysis, rigorous validation of potentially actionable findings, and data evaluation by a dedicated molecular tumor board enables categorization of patients into different intervention baskets and formulation of evidence-based recommendations for clinical management. Critical next steps will be to increase the number of patients that can be offered comprehensive molecular analysis through collaborations and partnering, to explore ways in which additional technologies can aid in patient stratification and individualization of treatment, to stimulate clinically guided exploratory research projects, and to gradually move away from assessing the therapeutic activity of targeted interventions on a case-by-case basis towards controlled clinical trials of genomics-guided treatments. This article is protected by copyright. All rights reserved.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 134 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 32 24%
Student > Master 15 11%
Student > Ph. D. Student 10 7%
Other 9 7%
Student > Doctoral Student 9 7%
Other 27 20%
Unknown 32 24%
Readers by discipline Count As %
Medicine and Dentistry 37 28%
Biochemistry, Genetics and Molecular Biology 30 22%
Agricultural and Biological Sciences 9 7%
Nursing and Health Professions 3 2%
Computer Science 3 2%
Other 15 11%
Unknown 37 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 December 2021.
All research outputs
#3,307,149
of 26,017,215 outputs
Outputs from International Journal of Cancer
#1,471
of 12,554 outputs
Outputs of similar age
#57,491
of 333,894 outputs
Outputs of similar age from International Journal of Cancer
#19
of 120 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,554 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.3. This one has done well, scoring higher than 88% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 333,894 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.