Evidence map›Paper›PMID 26362649›Full record

SynthesisGenome medicine2015

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

Matthew A Care, David R Westhead, Reuben M Tooze

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Genome medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.6field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. PD-1-PD-L1 immune-checkpoint blockade in B-cell lymphomas.Nature reviews. Clinical oncology · 2017
    Review
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Matthew A CareSection of Experimental Haematology, Wellcome Trust Brenner Building, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, LS9 7TF, UK.
David R WestheadBioinformatics Group, School of Molecular and Cellular Biology, University of Leeds, Leeds, UK.
Reuben M ToozeSection of Experimental Haematology, Wellcome Trust Brenner Building, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, LS9 7TF, UK. r.tooze@leeds.ac.uk.
University of Leeds · GB

Funding

Cancer Research UK 10066Cancer Research UK 17723Cancer Research UK C7845/A10066Cancer Research UK C7845/A17723Medical Research Council MR/L01629X/1
6 · The paper itself

Abstract

backgroundCancers 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.

methodsUsing 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.

resultsT-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.

conclusionImmune responses in DLBCL converge onto the IFNγ-STAT1-IRF1 axis and link to diverse potential mediators of adaptive immune resistance identifying future therapeutic targets.

Indexed as

Gene Expression Regulation, NeoplasticHumansInterferon-gammaInterferon Regulatory Factor-1Lymphoma, Large B-Cell, DiffuseSTAT1 Transcription FactorInterferon-gammaInterferon Regulatory Factor-1IRF1 protein, humanSTAT1 protein, humanSTAT1 Transcription Factor

Identifiers

PMID26362649
PMCPMC4566848
OpenAlexW2096915652

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.