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Spatial and molecular resolution of diffuse malignant mesothelioma heterogeneity by integrating label-free FTIR imaging, laser capture microdissection and proteomics

Overview of attention for article published in Scientific Reports, March 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

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11 news outlets
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2 X users

Citations

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52 Dimensions

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77 Mendeley
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Title
Spatial and molecular resolution of diffuse malignant mesothelioma heterogeneity by integrating label-free FTIR imaging, laser capture microdissection and proteomics
Published in
Scientific Reports, March 2017
DOI 10.1038/srep44829
Pubmed ID
Authors

Frederik Großerueschkamp, Thilo Bracht, Hanna C. Diehl, Claus Kuepper, Maike Ahrens, Angela Kallenbach-Thieltges, Axel Mosig, Martin Eisenacher, Katrin Marcus, Thomas Behrens, Thomas Brüning, Dirk Theegarten, Barbara Sitek, Klaus Gerwert

Abstract

Diffuse malignant mesothelioma (DMM) is a heterogeneous malignant neoplasia manifesting with three subtypes: epithelioid, sarcomatoid and biphasic. DMM exhibit a high degree of spatial heterogeneity that complicates a thorough understanding of the underlying different molecular processes in each subtype. We present a novel approach to spatially resolve the heterogeneity of a tumour in a label-free manner by integrating FTIR imaging and laser capture microdissection (LCM). Subsequent proteome analysis of the dissected homogenous samples provides in addition molecular resolution. FTIR imaging resolves tumour subtypes within tissue thin-sections in an automated and label-free manner with accuracy of about 85% for DMM subtypes. Even in highly heterogeneous tissue structures, our label-free approach can identify small regions of interest, which can be dissected as homogeneous samples using LCM. Subsequent proteome analysis provides a location specific molecular characterization. Applied to DMM subtypes, we identify 142 differentially expressed proteins, including five protein biomarkers commonly used in DMM immunohistochemistry panels. Thus, FTIR imaging resolves not only morphological alteration within tissue but it resolves even alterations at the level of single proteins in tumour subtypes. Our fully automated workflow FTIR-guided LCM opens new avenues collecting homogeneous samples for precise and predictive biomarkers from omics studies.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 1%
France 1 1%
Unknown 75 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 20 26%
Researcher 12 16%
Student > Master 8 10%
Student > Bachelor 4 5%
Professor > Associate Professor 4 5%
Other 10 13%
Unknown 19 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 13%
Physics and Astronomy 10 13%
Agricultural and Biological Sciences 8 10%
Chemistry 7 9%
Computer Science 4 5%
Other 15 19%
Unknown 23 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 84. 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 13 November 2018.
All research outputs
#430,178
of 22,962,258 outputs
Outputs from Scientific Reports
#4,837
of 123,970 outputs
Outputs of similar age
#10,117
of 308,953 outputs
Outputs of similar age from Scientific Reports
#195
of 4,387 outputs
Altmetric has tracked 22,962,258 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 123,970 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one has done particularly well, scoring higher than 96% 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 308,953 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 4,387 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.