Evidence map›Paper›PMID 30548162›Full record

ArticlePigment cell & melanoma research2019

Local genomic features predict the distinct and overlapping binding patterns of the bHLH-Zip family oncoproteins MITF and MYC-MAX.

Miroslav Hejna, Wooyoung M Moon, Jeffrey Cheng, Akinori Kawakami, David E Fisher, Jun S Song

Erratum issuedOpen access · greenAbstract read
In one paragraph

Article in Pigment cell & melanoma research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
0.6field-weighted citation impact, top 31% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Article
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  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Mechanisms of Binding Specificity among bHLH Transcription Factors.International journal of molecular sciences · 2021
    Review
  11. Article
  12. Article
  13. Article
  14. MITF-the first 25 years.Genes & development · 2019
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Miroslav HejnaDepartment of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois.
Wooyoung M MoonDepartment of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois.
Jeffrey ChengDepartment of Dermatology, University of California, San Francisco, California.
Akinori KawakamiCutaneous Biology Research Center and Department of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
David E FisherCutaneous Biology Research Center and Department of Dermatology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
Jun S SongDepartment of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois.ORCID 0000-0002-0422-2175
University of Illinois Urbana-Champaign · USHarvard University · USUniversity of California, San Francisco · US

Funding

Transcriptional mechanisms and melanomaP01CA163222 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI DAVID E FISHER · 2013 to 2026
$25.3M
The MITF transcriptional network: melanoma risk and carcinogenesisR01AR043369 · NIAMS · MASSACHUSETTS GENERAL HOSPITAL · PI DAVID E FISHER · 1996 to 2026
$9.4M
Predicting Transcriptional and Epigenetic Networks in Cancer from Sequencing DataR01CA163336 · NCI · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI Jun S Song · 2012 to 2026
$4.4M
A druggable dependency in low-MITF/high-AXL melanoma: preclinical efficacy and mechanism of action in a key treatment-resistant subclass.R01CA222871 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI FISHER, DAVID E · 2018 to 2022
$1.8M
Role of DNA Methylation and Hydroxymethylation in Epidermal HomeostasisK08AR067243 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHENG, JEFFREY B · 2015 to 2019
$834k
NCI NIH HHS 2R01CA163336NCI NIH HHS 5P01CA163222NCI NIH HHS P01 CA163222NCI NIH HHS R01 CA163336NCI NIH HHS R01 CA222871NIAMS NIH HHS 5R01AR043369NIAMS NIH HHS K08 AR067243NIAMS NIH HHS R01 AR043369
6 · The paper itself

Abstract

MITF and MYC are well-known oncoproteins and members of the basic helix-loop-helix leucine zipper (bHLH-Zip) family of transcription factors (TFs) recognizing hexamer E-box motifs. MITF and MYC not only share the core binding motif, but are also the two most highly expressed bHLH-Zip transcription factors in melanocytes, raising the possibility that they may compete for the same binding sites in select oncogenic targets. Mechanisms determining the distinct and potentially overlapping binding modes of these critical oncoproteins remain uncharacterized. We introduce computational predictive models using local sequence features, including a boosted convolutional decision tree framework, to distinguish MITF versus MYC-MAX binding sites with up to 80% accuracy genomewide. Select E-box locations that can be bound by both MITF and MYC-MAX form a separate class of MITF binding sites characterized by differential sequence content in the flanking region, diminished interaction with SOX10, higher evolutionary conservation, and less tissue-specific chromatin organization.

Indexed as

Genome, HumanAmino Acid MotifsArea Under CurveBase CompositionBase SequenceBasic Helix-Loop-Helix Leucine Zipper Transcription FactorsBinding SitesEpigenesis, GeneticHumansMicrophthalmia-Associated Transcription FactorProtein BindingProto-Oncogene Proteins c-mycROC CurveSOXE Transcription FactorsBasic Helix-Loop-Helix Leucine Zipper Transcription FactorsMAX protein, humanMicrophthalmia-Associated Transcription FactorProto-Oncogene Proteins c-mycSOXE Transcription Factorsboosted convolutional decision treecobinding factorsmachine learningMITFMYC-MAX

Identifiers

PMID30548162
PMCPMC6555698
OpenAlexW2905577891

What OpenQuestion holds

Textmetadata
LicenceTDM
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.