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Gene expression markers of Tumor Infiltrating Leukocytes

Overview of attention for article published in Journal for Immunotherapy of Cancer, February 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
24 X users
patent
2 patents

Citations

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570 Dimensions

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442 Mendeley
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Title
Gene expression markers of Tumor Infiltrating Leukocytes
Published in
Journal for Immunotherapy of Cancer, February 2017
DOI 10.1186/s40425-017-0215-8
Pubmed ID
Authors

Patrick Danaher, Sarah Warren, Lucas Dennis, Leonard D’Amico, Andrew White, Mary L. Disis, Melissa A. Geller, Kunle Odunsi, Joseph Beechem, Steven P. Fling

Abstract

Assays of the abundance of immune cell populations in the tumor microenvironment promise to inform immune oncology research and the choice of immunotherapy for individual patients. We propose to measure the intratumoral abundance of various immune cell populations with gene expression. In contrast to IHC and flow cytometry, gene expression assays yield high information content from a clinically practical workflow. Previous studies of gene expression in purified immune cells have reported hundreds of genes showing enrichment in a single cell type, but the utility of these genes in tumor samples is unknown. We use co-expression patterns in large tumor gene expression datasets to evaluate previously reported candidate cell type marker genes lists, eliminate numerous false positives and identify a subset of high confidence marker genes. Using a novel statistical tool, we use co-expression patterns in 9986 samples from The Cancer Genome Atlas (TCGA) to evaluate previously reported cell type marker genes. We compare immune cell scores derived from these genes to measurements from flow cytometry and immunohistochemistry. We characterize the reproducibility of our cell scores in replicate runs of RNA extracted from FFPE tumor tissue. We identify a list of 60 marker genes whose expression levels measure 14 immune cell populations. Cell type scores calculated from these genes are concordant with flow cytometry and IHC readings, show high reproducibility in replicate RNA samples from FFPE tissue and enable detailed analyses of the anti-tumor immune response in TCGA. In an immunotherapy dataset, they separate responders and non-responders early on therapy and provide an intricate picture of the effects of checkpoint inhibition. Most genes previously reported to be enriched in a single cell type have co-expression patterns inconsistent with cell type specificity. Due to their concise gene set, computational simplicity and utility in tumor samples, these cell type gene signatures may be useful in future discovery research and clinical trials to understand how tumors and therapeutic intervention shape the immune response.

X Demographics

X Demographics

The data shown below were collected from the profiles of 24 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 442 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Israel 1 <1%
France 1 <1%
Unknown 440 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 112 25%
Student > Ph. D. Student 79 18%
Other 34 8%
Student > Master 32 7%
Student > Bachelor 28 6%
Other 60 14%
Unknown 97 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 107 24%
Medicine and Dentistry 74 17%
Agricultural and Biological Sciences 57 13%
Immunology and Microbiology 46 10%
Computer Science 8 2%
Other 40 9%
Unknown 110 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 35. 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 October 2022.
All research outputs
#1,158,844
of 25,382,440 outputs
Outputs from Journal for Immunotherapy of Cancer
#277
of 3,422 outputs
Outputs of similar age
#23,425
of 323,958 outputs
Outputs of similar age from Journal for Immunotherapy of Cancer
#6
of 27 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 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,422 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.4. 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 323,958 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 92% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.