Evidence map›Paper›PMID 31698791›Full record

ReviewCancers2019

Cell-Free DNA Methylation Profiling Analysis-Technologies and Bioinformatics.

Jinyong Huang, Liang Wang

Abstract readReview
In one paragraph

Review in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 1 pooled it
–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

48 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  19. Advances in cfDNA research for pregnancy-related diseases.Frontiers in cell and developmental biology · 2025
    Review
  20. 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

2 authors.

Jinyong HuangDepartment of Tumor Biology, H. Lee Moffitt Cancer Center, Tampa, Florida 33612, USA.
Liang WangDepartment of Tumor Biology, H. Lee Moffitt Cancer Center, Tampa, Florida 33612, USA.

Funding

Foundation for the National Institutes of Health R01CA212097
6 · The paper itself

Abstract

Analysis of circulating nucleic acids in bodily fluids, referred to as "liquid biopsies", is rapidly gaining prominence. Studies have shown that cell-free DNA (cfDNA) has great potential in characterizing tumor status and heterogeneity, as well as the response to therapy and tumor recurrence. DNA methylation is an epigenetic modification that plays an important role in a broad range of biological processes and diseases. It is well known that aberrant DNA methylation is generalizable across various samples and occurs early during the pathogenesis of cancer. Methylation patterns of cfDNA are also consistent with their originated cells or tissues. Systemic analysis of cfDNA methylation profiles has emerged as a promising approach for cancer detection and origin determination. In this review, we will summarize the technologies for DNA methylation analysis and discuss their feasibility for liquid biopsy applications. We will also provide a brief overview of the bioinformatic approaches for analysis of DNA methylation sequencing data. Overall, this review provides informative guidance for the selection of experimental and computational methods in cfDNA methylation-based studies.

Indexed as

bioinformaticcell-free DNADNA methylationliquid biopsiesnext-generation sequencing

Identifiers

PMID31698791
PMCPMC6896050

What OpenQuestion holds

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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.