Evidence map›Paper›PMID 40748712›Full record

ArticleBioinformatics (Oxford, England)2025

Tracing regulatory element networks using epigenetic traits to identify key transcription factors: TENET R/Bioconductor package.

Daniel J Mullen, Zexun Wu, Ethan Nelson-Moore, Huan Cao, Lauren Han, Ite A Offringa, Suhn K Rhie

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

7 authors.

Daniel J MullenDepartment of Cancer Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Zexun WuDepartment of Cancer Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Ethan Nelson-MooreDepartment of Cancer Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Huan CaoDepartment of Cancer Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Lauren HanDepartment of Cancer Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Ite A OffringaDepartment of Cancer Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.
Suhn K RhieDepartment of Cancer Biology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, United States.ORCID 0000-0002-5522-5296

Funding

Identification and Clinical Validation of Key Transcription Factor Isoforms Linked to Breast and Prostate Cancer Subgroups using Epigenetic TraitsK01CA229995 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI RHIE, SUHN KYONG · 2018 to 2020
$637k
Mapping regulatory elements and chromatin structures in prostate tumor subtypes at single nucleosome resolutionR21CA264637 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI RHIE, SUHN KYONG · 2021 to 2022
$420k
Reversing molecular cancer phenotypes by targeting epigenetic alterations in prostate cancerR21CA260082 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI RHIE, SUHN KYONG · 2021 to 2021
$386k
John H. Richardson Endowed Postdoctoral Fellowship in Oncology ResearchNCI NIH HHS K01 CA229995NCI NIH HHS R21 CA260082NCI NIH HHS R21 CA264637USC Center for Genetic EpidemiologyUSC Keck School of MedicineUSC Norris Comprehensive Cancer Center
6 · The paper itself

Abstract

summaryThere is a lack of publicly available bioinformatic tools that can be widely used by researchers to identify transcription factors (TFs) that regulate cell type-specific regulatory elements (REs). To address this, we developed the Tracing regulatory Element Networks using Epigenetic Traits (TENET) R/Bioconductor package. By collecting hundreds of histone mark and open chromatin datasets from a variety of cell lines, primary cells, and tissues, and comparing these features along with matched DNA methylation and gene expression data, TENET identifies TFs and REs linked to a specific cell type. Moreover, we developed methods to interrogate findings using motifs, clinical information, and other genomic and chromatin conformation capture datasets, and applied them to pan-cancer data, highlighting TFs and REs associated with ten different cancer types. TENET enables researchers to better characterize the 3D epigenomes of cell types of interest for future clinical applications. AVAILABILITY AND IMPLEMENTATION: TENET is available at http://bioconductor.org/packages/TENET. Curated functional genomic datasets utilized by TENET are available at http://bioconductor.org/packages/TENET.AnnotationHub. Example datasets are available at http://bioconductor.org/packages/TENET.ExperimentHub.

Indexed as

Computational BiologyEpigenesis, GeneticEpigenomicsGene Regulatory NetworksRegulatory Elements, TranscriptionalSoftwareTranscription FactorsChromatinDNA MethylationHumansChromatinTranscription Factors

Identifiers

PMID40748712
PMCPMC12349384

What OpenQuestion holds

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LicenceCC BY
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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.