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Spatial Tissue Proteomics Quantifies Inter- and Intratumor Heterogeneity in Hepatocellular Carcinoma (HCC)*

Overview of attention for article published in Molecular and Cellular Proteomics, January 2018
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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 (95th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

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4 news outlets
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35 X users
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1 Facebook page

Citations

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67 Dimensions

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108 Mendeley
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Title
Spatial Tissue Proteomics Quantifies Inter- and Intratumor Heterogeneity in Hepatocellular Carcinoma (HCC)*
Published in
Molecular and Cellular Proteomics, January 2018
DOI 10.1074/mcp.ra117.000189
Pubmed ID
Authors

Katarzyna Buczak, Alessandro Ori, Joanna M Kirkpatrick, Kerstin Holzer, Daniel Dauch, Stephanie Roessler, Volker Endris, Felix Lasitschka, Luca Parca, Alexander Schmidt, Lars Zender, Peter Schirmacher, Jeroen Krijgsveld, Stephan Singer, Martin Beck

Abstract

The inter-patient variability of tumor proteomes has been investigated on a large scale but many tumors display also intra-tumoral heterogeneity regarding morphological and genetic features. It remains largely unknown to what extent the local proteome of tumors intrinsically differs. Here, we used hepatocellular carcinoma as a model system to quantify both inter- and intra-tumor heterogeneity across human patient specimens with spatial resolution.  We defined proteomic features that distinguish neoplastic from the directly adjacent non-neoplastic tissue, such as decreased abundance of NADH dehydrogenase complex I. We then demonstrated the existence of intra-tumoral variations in protein abundance that re-occur across different patient samples, and affect clinically relevant proteins, even in the absence of obvious morphological differences or genetic alterations. Our work demonstrates the suitability and the benefits of using mass spectrometry based proteomics to analyze diagnostic tumor specimens with spatial resolution. Data are available via ProteomeXchange with identifier PXD007052.

X Demographics

X Demographics

The data shown below were collected from the profiles of 35 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 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 108 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 21%
Researcher 23 21%
Student > Master 12 11%
Other 8 7%
Student > Bachelor 7 6%
Other 14 13%
Unknown 21 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 43 40%
Agricultural and Biological Sciences 14 13%
Medicine and Dentistry 8 7%
Chemistry 6 6%
Engineering 5 5%
Other 7 6%
Unknown 25 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 45. 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 14 November 2021.
All research outputs
#917,558
of 25,382,440 outputs
Outputs from Molecular and Cellular Proteomics
#62
of 3,221 outputs
Outputs of similar age
#21,534
of 450,227 outputs
Outputs of similar age from Molecular and Cellular Proteomics
#4
of 59 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,221 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has done particularly well, scoring higher than 98% 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 450,227 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 95% of its contemporaries.
We're also able to compare this research output to 59 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 93% of its contemporaries.