Evidence map›Paper›PMID 29212414›Full record

ArticleEpigenetics2018

A suite of DNA methylation markers that can detect most common human cancers.

Lukas Vrba, Bernard W Futscher

Abstract read
In one paragraph

Article in Epigenetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

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

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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

2 authors.

Lukas Vrbaa The University of Arizona Cancer Center , Tucson , AZ 85724 , USA.ORCID 0000-0003-3042-6275
Bernard W Futschera The University of Arizona Cancer Center , Tucson , AZ 85724 , USA.ORCID 0000-0001-8367-434X

Funding

VITAMIN AP30CA023074 · NCI · UNIVERSITY OF ARIZONA · PI Justin M Snider · 1985 to 2026
$110.2M
SOUTHWEST ENVIRONMENTAL HEALTH SCIENCES CENTERP30ES006694 · NIEHS · UNIVERSITY OF ARIZONA · PI Paloma Inés Beamer · 1994 to 2026
$36.7M
NCI NIH HHS P30 CA023074NIEHS NIH HHS P30 ES006694
6 · The paper itself

Abstract

Cancer-specific DNA methylation from the tumor derived fraction of cell free DNA found in blood samples could be used for minimally invasive detection and monitoring of cancer. The knowledge of marker regions with cancer-specific DNA methylation is necessary to the success of such a process. We analyzed the largest cancer DNA methylation dataset available-TCGA Illumina HumanMethylation450 data with over 8,500 tumors-in order to find cancer-specific DNA methylation markers for most common human cancers. First, we identified differentially methylated regions for individual cancer types and those were further filtered against data from normal tissues to obtain marker regions with cancer-specific methylation, resulting in a total of 1,250 hypermethylated and 584 hypomethylated marker CpGs. From hypermethylated markers, optimal sets of six markers for each TCGA cancer type were chosen that could identify most tumors with high specificity and sensitivity [area under the curve (AUC): 0.969-1.000] and a universal 12 marker set that can detect tumors of all 33 TCGA cancer types (AUC >0.84). In addition to hundreds of new DNA methylation markers, our approach also identified markers that are in current clinical use, SEPT9 and GSTP1, indicating the validity of our approach and a significant potential utility for the newly discovered markers. The hypermethylated markers are linked to polycomb associated loci and a significant fraction of the discovered markers is within noncoding RNA genes; one of the best markers is MIR129-2. Future clinical testing of herein discovered markers will confirm new markers that will improve minimally invasive diagnosis and monitoring for multiple cancers.

Indexed as

DNA MethylationArea Under CurveBiomarkers, TumorCpG IslandsDatabases, FactualGlutathione S-Transferase piHumansMicroRNAsNeoplasmsReproducibility of ResultsSeptinsBiomarkers, TumorGlutathione S-Transferase piGSTP1 protein, humanMicroRNAsMirn129 microRNA, humanSEPTIN9 protein, humanSeptinsCancer markerDNA methylationTCGA

Identifiers

PMID29212414
PMCPMC5836970

What OpenQuestion holds

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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.