Evidence map›Paper›PMID 27871313›Full record

ArticleBMC cancer2016

Conservation of immune gene signatures in solid tumors and prognostic implications.

Julia Chifman, Ashok Pullikuth, Jeff W Chou, Davide Bedognetti, Lance D Miller

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed
3.2field-weighted citation impact, top 7% 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

60 citing papers in PubMed, 126 citations in OpenAlex.

  1. Single-Cell Pan-Cancer Atlas Reveals GPR171 as a Candidate Marker of CD8International journal of molecular sciences · 2026
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  8. Classification of bladder cancer based on immune cell infiltration and construction of a risk prediction model for prognosis.Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences · 2023
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  20. Advances in CRISPR/Cas9.BioMed research international · 2022
    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

5 authors at 2 institutions in 2 countries.

Julia ChifmanDepartment of Cancer Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, 27157, NC, USA.
Ashok PullikuthDepartment of Cancer Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, 27157, NC, USA.
Jeff W ChouDepartment of Cancer Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, 27157, NC, USA.
Davide BedognettiSidra Medical and Research Center, Doha, Qatar.
Lance D MillerDepartment of Cancer Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, 27157, NC, USA. ldmiller@wakehealth.edu.ORCID 0000-0003-3799-2528
Wake Forest University · USSidra Medical and Research Center · QA

Funding

Tumor Tissue CoreP30CA012197 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Ruben A. Mesa · 1985 to 2026
$55.4M
Training Program in Cancer BiologyT32CA079448 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI KRIDEL, STEVEN J. · 2000 to 2014
$6.5M
NCI NIH HHS P30 CA012197NCI NIH HHS T32 CA079448
6 · The paper itself

Abstract

backgroundTumor-infiltrating leukocytes can either limit cancer growth or facilitate its spread. Diagnostic strategies that comprehensively assess the functional complexity of tumor immune infiltrates could have wide-reaching clinical value. In previous work we identified distinct immune gene signatures in breast tumors that reflect the relative abundance of infiltrating immune cells and exhibited significant associations with patient outcomes. Here we hypothesized that immune gene signatures agnostic to tumor type can be identified by de novo discovery of gene clusters enriched for immunological functions and possessing internal correlation structure conserved across solid tumors from different anatomic sites.

methodsWe assembled microarray expression datasets encompassing 5,295 tumors of the breast, colon, lung, ovarian and prostate. Unsupervised clustering methods were used to determine number and composition of gene clusters within each dataset. Immune-enriched gene clusters (signatures) identified by gene ontology enrichment were analyzed for internal correlation structure and conservation across tumors then compared against expression profiles of: 1) flow-sorted leukocytes from peripheral blood and 2) >300 cancer cell lines from solid and hematologic cancers. Cox regression analysis was used to identify signatures with significant associations with clinical outcome.

resultsWe identified nine distinct immune-enriched gene signatures conserved across all five tumor types. The signatures differentiated specific leukocyte lineages with moderate discernment overall, and naturally organized into six discrete groups indicative of admixed lineages. Moreover, seven of the signatures exhibit minimal and uncorrelated expression in cancer cell lines, suggesting that these signatures derive predominantly from infiltrating immune cells. All nine immune signatures achieved statistically significant associations with patient prognosis (p<0.05) in one or more tumor types with greatest significance observed in breast and skin cancers. Several signatures indicative of myeloid lineages exhibited poor outcome associations that were most apparent in brain and colon cancers.

conclusionsThese findings suggest that tumor infiltrating immune cells can be differentiated by immune-specific gene expression patterns that quantify the relative abundance of multiple immune infiltrates across a range of solid tumor types. That these markers of immune involvement are significantly associated with patient prognosis in diverse cancers suggests their clinical utility as pan-cancer markers of tumor behavior and immune responsiveness.

Indexed as

Evolution, MolecularGene Expression Regulation, NeoplasticTranscriptomeBiomarkersCluster AnalysisComputational BiologyDatasets as TopicGene Expression ProfilingHumansImmunityLeukocytesMolecular Sequence AnnotationNeoplasmsPrognosisBiomarkersConsensus clusteringEnrichment scoresImmune signaturesSurvival analysis

Identifiers

PMID27871313
PMCPMC5118876
OpenAlexW2552779786

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.