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Massively parallel sequencing fails to detect minor resistant subclones in tissue samples prior to tyrosine kinase inhibitor therapy

Overview of attention for article published in BMC Cancer, April 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)

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1 blog
twitter
6 tweeters

Citations

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6 Dimensions

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26 Mendeley
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1 CiteULike
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Title
Massively parallel sequencing fails to detect minor resistant subclones in tissue samples prior to tyrosine kinase inhibitor therapy
Published in
BMC Cancer, April 2015
DOI 10.1186/s12885-015-1311-0
Pubmed ID
Authors

Carina Heydt, Niklas Kumm, Jana Fassunke, Helen Künstlinger, Michaela Angelika Ihle, Andreas Scheel, Hans-Ulrich Schildhaus, Florian Haller, Reinhard Büttner, Margarete Odenthal, Eva Wardelmann, Sabine Merkelbach-Bruse

Abstract

Personalised medicine and targeted therapy have revolutionised cancer treatment. However, most patients develop drug resistance and relapse after showing an initial treatment response. Two theories have been postulated; either secondary resistance mutations develop de novo during therapy by mutagenesis or they are present in minor subclones prior to therapy. In this study, these two theories were evaluated in gastrointestinal stromal tumours (GISTs) where most patients develop secondary resistance mutations in the KIT gene during therapy with tyrosine kinase inhibitors. We used a cohort of 33 formalin-fixed, paraffin embedded (FFPE) primary GISTs and their corresponding recurrent tumours with known mutational status. The primary tumours were analysed for the secondary mutations of the recurrences, which had been identified previously. The primary tumours were resected prior to tyrosine kinase inhibitor therapy. Three ultrasensitive, massively parallel sequencing approaches on the GS Junior (Roche, Mannheim, Germany) and the MiSeq(TM) (Illumina, San Diego, CA, USA) were applied. Additionally, nine fresh-frozen samples resected prior to therapy were analysed for the most common secondary resistance mutations. With a sensitivity level of down to 0.02%, no pre-existing resistant subclones with secondary KIT mutations were detected in primary GISTs. The sensitivity level varied for individual secondary mutations and was limited by sequencing artefacts on both systems. Artificial T > C substitutions at the position of the exon 13 p.V654A mutation, in particular, led to a lower sensitivity, independent from the source of the material. Fresh-frozen samples showed the same range of artificially mutated allele frequencies as the FFPE material. Although we achieved a sufficiently high level of sensitivity, neither in the primary FFPE nor in the fresh-frozen GISTs we were able to detect pre-existing resistant subclones of the corresponding known secondary resistance mutations of the recurrent tumours. This supports the theory that secondary KIT resistance mutations develop under treatment by "de novo" mutagenesis. Alternatively, the detection limit of two mutated clones in 10,000 wild-type clones might not have been high enough or heterogeneous tissue samples, per se, might not be suitable for the detection of very small subpopulations of mutated cells.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 4%
Unknown 25 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 38%
Student > Ph. D. Student 5 19%
Other 4 15%
Professor 2 8%
Student > Bachelor 1 4%
Other 1 4%
Unknown 3 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 31%
Agricultural and Biological Sciences 6 23%
Medicine and Dentistry 4 15%
Immunology and Microbiology 2 8%
Philosophy 1 4%
Other 2 8%
Unknown 3 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 09 November 2015.
All research outputs
#2,569,874
of 19,211,930 outputs
Outputs from BMC Cancer
#558
of 6,931 outputs
Outputs of similar age
#38,194
of 237,791 outputs
Outputs of similar age from BMC Cancer
#1
of 1 outputs
Altmetric has tracked 19,211,930 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,931 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 91% 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 237,791 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 83% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them