Evidence map›Paper›PMID 35234924›Full record

ArticleNucleic acids research2022

Summarizing internal dynamics boosts differential analysis and functional interpretation of super enhancers.

Xiang Liu, Bo Zhao, Timothy I Shaw, Brooke L Fridley, Derek R Duckett, Aik Choon Tan, Mingxiang Teng

Abstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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  5. 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

7 authors.

Xiang LiuDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.ORCID 0000-0002-7081-3694
Bo ZhaoDivision of Infectious Disease, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
Timothy I ShawDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
Brooke L FridleyDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.ORCID 0000-0001-7739-7956
Derek R DuckettDepartment of Drug Discovery, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
Aik Choon TanDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.ORCID 0000-0003-2955-8369
Mingxiang TengDepartment of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.ORCID 0000-0002-8536-8941

Funding

TRANSLATIONAL RESEARCHP30CA076292 · NCI · UNIVERSITY OF SOUTH FLORIDA · PI Christine O'Connell · 1998 to 2026
$93.5M
Targeting Epstein-Barr Virus super-enhancersR01AI123420 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI Bo Zhao · 2016 to 2026
$5.1M
Developing CDK12 inhibitors to overcome therapy resistance in HER2+ and KRAS driven breast and lung cancersR01CA262530 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI DUCKETT, DEREK RONALD, HAURA, ERIC B. · 2021 to 2025
$3.5M
NCI NIH HHS P30 CA076292NCI NIH HHS R01 CA262530NIAID NIH HHS R01 AI123420
6 · The paper itself

Abstract

Super enhancers (SEs) are broad enhancer domains usually containing multiple constituent enhancers that hold elevated activities in gene regulation. Disruption in one or more constituent enhancers causes aberrant SE activities that lead to gene dysregulation in diseases. To quantify SE aberrations, differential analysis is performed to compare SE activities between cell conditions. The state-of-art strategy in estimating differential SEs relies on overall activities and neglect the changes in length and structure of SEs. Here, we propose a novel computational method to identify differential SEs by weighting the combinatorial effects of constituent-enhancer activities and locations (i.e. internal dynamics). In addition to overall activity changes, our method identified four novel classes of differential SEs with distinct enhancer structural alterations. We demonstrate that these structure alterations hold distinct regulatory impact, such as regulating different number of genes and modulating gene expression with different strengths, highlighting the differentiated regulatory roles of these unexplored SE features. When compared to the existing method, our method showed improved identification of differential SEs that were linked to better discernment of cell-type-specific SE activity and functional interpretation.

Indexed as

Enhancer Elements, GeneticGene Expression RegulationCell Differentiation

Identifiers

PMID35234924
PMCPMC8989535

What OpenQuestion holds

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LicenceCC BY-NC
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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.