Evidence map›Paper›PMID 28258094›Full record

ArticleMolecular cancer research : MCR2017

Nucleome Analysis Reveals Structure-Function Relationships for Colon Cancer.

Laura Seaman, Haiming Chen, Markus Brown, Darawalee Wangsa, Geoff Patterson, Jordi Camps, Gilbert S Omenn, Thomas Ried, Indika Rajapakse

Open access · bronzeAbstract read
In one paragraph

Article in Molecular cancer research : MCR, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

21 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
  2. Article
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  5. Chromatin Mechanisms Driving Cancer.Cold Spring Harbor perspectives in biology · 2022
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Bioinformatics for The Prognostic Value and Function of Cubilin (CUBN) in Colorectal Cancer.Medical science monitor : international medical journal of experimental and clinical research · 2020
    Article
  11. Structural variation in the sequencing era.Nature reviews. Genetics · 2020
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Visual Pattern-Driven Exploration of Big Data.2018 International Symposium on Big Data Visual and Immersive Analytics (BDVA) : Konstanz, Germany, October 17 -19, 2018. IEEE International Symposium on Big Data Visual and Immersive Analytics (4th : 2018 : Konstanz, Germany) · 2018
    Article
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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

9 authors at 3 institutions in 2 countries.

Laura SeamanDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan.
Haiming ChenDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan.
Markus BrownCancer Genomics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Darawalee WangsaCancer Genomics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Geoff PattersonDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan.
Jordi CampsGastrointestinal and Pancreatic Oncology Group, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Barcelona, Catalonia, Spain.
Gilbert S OmennDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan.
Thomas RiedCancer Genomics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Indika RajapakseDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan. indikar@umich.edu.
University of Michigan · USNational Institutes of Health · USUniversitat Autònoma de Barcelona · ES

Funding

Strategic Vision & Impact on Environmental HealthP30ES017885 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Dana Dolinoy · 2011 to 2026
$21.3M
Identification and functional characterization of colorectal cancer genesZIABC010833 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI RIED, THOMAS · 2009 to 2022
$12.1M
Prediction of Therapy Response in Colorectal CancerZIABC010837 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI RIED, THOMAS · 2009 to 2022
$8.9M
Intramural NIH HHS ZIA BC010833Intramural NIH HHS ZIA BC010837NIEHS NIH HHS P30 ES017885
6 · The paper itself

Abstract

Chromosomal translocations and aneuploidy are hallmarks of cancer genomes; however, the impact of these aberrations on the nucleome (i.e., nuclear structure and gene expression) is not yet understood. Here, the nucleome of the colorectal cancer cell line HT-29 was analyzed using chromosome conformation capture (Hi-C) to study genome structure, complemented by RNA sequencing (RNA-seq) to determine the consequent changes in genome function. Importantly, translocations and copy number changes were identified at high resolution from Hi-C data and the structure-function relationships present in normal cells were maintained in cancer. In addition, a new copy number-based normalization method for Hi-C data was developed to analyze the effect of chromosomal aberrations on local chromatin structure. The data demonstrate that at the site of translocations, the correlation between chromatin organization and gene expression increases; thus, chromatin accessibility more directly reflects transcription. In addition, the homogeneously staining region of chromosome band 8q24 of HT-29, which includes the MYC oncogene, interacts with various loci throughout the genome and is composed of open chromatin. The methods, described herein, can be applied to the assessment of the nucleome in other cell types with chromosomal aberrations.

Indexed as

Cell NucleusChromosomesColonic NeoplasmsComputational BiologyDNA Copy Number VariationsGenome, HumanGenomic Structural VariationHigh-Throughput Nucleotide SequencingHT29 CellsHumansNucleic Acid ConformationStructure-Activity RelationshipTranslocation, Genetic

Identifiers

PMID28258094
PMCPMC7934948
OpenAlexW2593509139

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.