Evidence map›Paper›PMID 27863398›Full record

ArticleOncotarget2016

Unique epigenetic gene profiles define human breast cancers with poor prognosis.

Samuel Peña-Llopis, Yihong Wan, Elisabeth D Martinez

Abstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

  1. Proteogenomic Analysis of HDAC4 and HDAC5 in Uveal Melanoma.Molecular medicine (Cambridge, Mass.) · 2026
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  9. Monosomy 3 Is Linked to Resistance to MEK Inhibitors in Uveal Melanoma.International journal of molecular sciences · 2021
    Article
  10. Article
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  12. Review
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  14. Article
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.

Samuel Peña-LlopisDepartment of Pharmacology, UT Southwestern Medical Center, Dallas, TX, USA.
Yihong WanDepartment of Pharmacology, UT Southwestern Medical Center, Dallas, TX, USA.
Elisabeth D MartinezDepartment of Pharmacology, UT Southwestern Medical Center, Dallas, TX, USA.

Funding

UT Southwestern Center for Translational Medicine (UL1/KL2/TL1)UL1TR001105 · NCATS · UT SOUTHWESTERN MEDICAL CENTER · PI TOTO, ROBERT DANIEL · 2013 to 2017
$24.5M
NCATS NIH HHS UL1 TR001105
6 · The paper itself

Abstract

Epigenetic enzymes are at the nexus of cellular regulatory cascades and can drive cancer-specific deregulation at all stages of the oncogenic process, yet little is known about their prognostic value in human patients. Here, we used qRT-PCR to profile at high resolution the expression of fifty-five epigenetic genes in over one hundred human breast cancer samples and patient-matched benign tissues. We correlated expression patterns with clinical and histological parameters and validated our findings in two independent large patient cohorts (TCGA and METABRIC). We found that human breast malignancies have unique epigenetic profiles and cluster into epigenetic subgroups. A subset of epigenetic genes defined an Epigenetic Signature as an independent predictor of patient survival that outperforms triple negative status and other clinical variables. Our results also suggest that breast cancer grade, but not stage, is driven by transcriptional alterations of epigenetic modifiers. Overall, this study uncovers the presence of epigenetic subtypes within human mammary malignancies and identifies tumor subgroups with specific pharmacologically targetable epigenetic susceptibilities not yet therapeutically exploited.

Indexed as

EpigenomicsBreast NeoplasmsCell Line, TumorFemaleHumansPrognosisProportional Hazards ModelsTranscriptomeepigenetic signatureexpression profilesmolecular targetsprognosistriple negative breast cancer

Identifiers

PMID27863398
PMCPMC5349877

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Registered trials

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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.