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Gene expression meta-analysis reveals immune response convergence on the IFNγ-STAT1-IRF1 axis and adaptive immune resistance mechanisms in lymphoma

Overview of attention for article published in Genome Medicine, September 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 blog
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Citations

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51 Mendeley
Title
Gene expression meta-analysis reveals immune response convergence on the IFNγ-STAT1-IRF1 axis and adaptive immune resistance mechanisms in lymphoma
Published in
Genome Medicine, September 2015
DOI 10.1186/s13073-015-0218-3
Pubmed ID
Authors

Matthew A. Care, David R. Westhead, Reuben M. Tooze

Abstract

Cancers adapt to immune-surveillance through evasion. Immune responses against carcinoma and melanoma converge on cytotoxic effectors and IFNγ-STAT1-IRF1 signalling. Local IFN-driven immune checkpoint expression can mediate feedback inhibition and adaptive immune resistance. Whether such coupled immune polarization and adaptive resistance is generalisable to lymphoid malignancies is incompletely defined. The host response in diffuse large B-cell lymphoma (DLBCL), the commonest aggressive lymphoid malignancy, provides an empirical model. Using ten publicly available gene expression data sets encompassing 2030 cases we explore the nature of host response in DLBCL. Starting from the "cell of origin" paradigm for DLBCL classification, we use the consistency of differential expression to define polarized patterns of immune response genes in DLBCL, and derive a linear classifier of immune response gene expression. We validate and extend the results in an approach independent of "cell of origin" classification based on gene expression correlations across all data sets. T-cell and cytotoxic gene expression with polarization along the IFNγ-STAT1-IRF1 axis provides a defining feature of the immune response in DLBCL. This response is associated with improved outcome, particularly in the germinal centre B-cell subsets of DLBCL. Analysis of gene correlations across all data sets, independent of "cell of origin" class, demonstrates a consistent association with a hierarchy of immune-regulatory gene expression that places IDO1, LAG3 and FGL2 ahead of PD1-ligands CD274 and PDCD1LG2. Immune responses in DLBCL converge onto the IFNγ-STAT1-IRF1 axis and link to diverse potential mediators of adaptive immune resistance identifying future therapeutic targets.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 4%
Unknown 49 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 25%
Other 6 12%
Student > Ph. D. Student 6 12%
Student > Master 5 10%
Student > Postgraduate 3 6%
Other 9 18%
Unknown 9 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 27%
Medicine and Dentistry 12 24%
Agricultural and Biological Sciences 10 20%
Environmental Science 1 2%
Immunology and Microbiology 1 2%
Other 1 2%
Unknown 12 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 20 October 2015.
All research outputs
#4,111,540
of 22,828,180 outputs
Outputs from Genome Medicine
#830
of 1,442 outputs
Outputs of similar age
#53,154
of 267,781 outputs
Outputs of similar age from Genome Medicine
#24
of 36 outputs
Altmetric has tracked 22,828,180 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,442 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.6. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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 267,781 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 79% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.