Evidence map›Paper›PMID 27582426›Full record

ReviewSeminars in cell & developmental biology2017

Defining, distinguishing and detecting the contribution of heterogeneous methylation to cancer heterogeneity.

Thomas R Pisanic, Pornpat Athamanolap, Tza-Huei Wang

Abstract readReview
In one paragraph

Review in Seminars in cell & developmental biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

11 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Epigenetic heterogeneity in cancer.Biomarker research · 2019
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. 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 at 1 institution in 1 country.

Thomas R PisanicJohns Hopkins Institute for NanoBioTechnology, Baltimore, MD 21218, USA.
Pornpat AthamanolapDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Tza-Huei WangJohns Hopkins Institute for NanoBioTechnology, Baltimore, MD 21218, USA; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA; Cancer Biology Program, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD 21287, USA; Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA. Electronic address: thwang@jhu.edu.
Johns Hopkins University · US

Funding

ValidationU54CA151838 · NCI · JOHNS HOPKINS UNIVERSITY · PI LEVITSKY, HYAM ISAAC · 2010 to 2014
$11.9M
Multiplexed Detection of Cell Free DNA Biomarkers for CancerR01CA155305 · NCI · JOHNS HOPKINS UNIVERSITY · PI WANG, TZA-HUEI JEFF · 2011 to 2015
$1.7M
Digital Detection of Tumor-Derived Circulating Methylated DNAR21CA186809 · NCI · JOHNS HOPKINS UNIVERSITY · PI WANG, TZA-HUEI JEFF · 2014 to 2016
$698k
NCI NIH HHS R01 CA155305NCI NIH HHS R21 CA186809NCI NIH HHS U54 CA151838
6 · The paper itself

Abstract

DNA methylation is a fundamental means of epigenetic gene regulation that occurs in virtually all cell types. In many higher organisms, including humans, it plays vital roles in cell differentiation and homeostatic maintenance of cell phenotype. The control of DNA methylation has traditionally been attributed to a highly coordinated, linear process, whose dysregulation has been associated with numerous pathologies including cancer, where it occurs early in, and even prior to, the development of neoplastic tissues. Recent experimental evidence has demonstrated that, contrary to prevailing paradigms, methylation patterns are actually maintained through inexact, dynamic processes. These processes normally result in minor stochastic differences between cells that accumulate with age. However, various factors, including cancer itself, can lead to substantial differences in intercellular methylation patterns, viz. methylation heterogeneity. Advancements in molecular biology techniques are just now beginning to allow insight into how this heterogeneity contributes to clonal evolution and overall cancer heterogeneity. In the current review, we begin by presenting a didactic overview of how the basal bimodal methylome is established and maintained. We then provide a synopsis of some of the factors that lead to the accrual of heterogeneous methylation and how this heterogeneity may lead to gene silencing and impact the development of cancerous phenotypes. Lastly, we highlight currently available methylation assessment techniques and discuss their suitability to the study of heterogeneous methylation.

Indexed as

Genetic HeterogeneityAnimalsDNA MethylationHumansModels, GeneticNeoplasmsStochastic ProcessesCancerDNA methylationEpigeneticsMolecular diagnosticsTumor heterogeneity

Identifiers

PMID27582426
PMCPMC6339831
OpenAlexW2512098040

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.