Evidence map›Paper›PMID 30366258›Full record

ArticleBiosensors & bioelectronics2019

Highly sensitive detection of DNA hypermethylation in melanoma cancer cells.

Jared Nesvet, Giovanni Rizzi, Shan X Wang

Abstract read
In one paragraph

Article in Biosensors & bioelectronics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.9field-weighted citation impact, top 25% 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

9 citing papers in PubMed, 25 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Jared NesvetDepartment of Chemistry, Stanford University, Stanford, CA 94305, United States.
Giovanni RizziDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305, United States.
Shan X WangDepartment of Materials Science and Engineering, Stanford University, Stanford, CA 94305, United States. Electronic address: sxwang@stanford.edu.
Stanford University · US

Funding

Nano Characterization and Nano Fabrication CoreU54CA199075 · NCI · STANFORD UNIVERSITY · PI GAMBHIR, SANJIV S · 2015 to 2019
$9.6M
Giant MagnetoResistive (GMR) Sensors for Measuring Influenza VaccineR01AI125197 · NIAID · STANFORD UNIVERSITY · PI UTZ, PAUL JOSEPH, WANG, SHAN X. · 2016 to 2021
$5.0M
Ultra-Fast Epigenomic Maps for Monitoring AutoimmunityU19AI110491 · NIAID · STANFORD UNIVERSITY · PI UTZ, PAUL JOSEPH · 2014 to 2018
$3.6M
NCI NIH HHS U54 CA199075NIAID NIH HHS R01 AI125197NIAID NIH HHS U19 AI110491
6 · The paper itself

Abstract

Aberrant hypermethylation of CpG islands in the promoter region of tumor suppressor genes is a promising biomarker for early cancer detection. This methylation status is reflected in the methylation pattern of ctDNA shed from the primary tumor; however, to realize the full clinical utility of ctDNA methylation detection via liquid biopsy for early cancer diagnosis, improvements in the sensitivity and multiplexability of existing technologies must be improved. Additionally, the assay must be cheap and easy to perform in a clinical setting. We report the integration of methylation specific PCR (MSP) to melt curve analysis on giant magnetoresistive (GMR) biosensors to greatly enhance the sensitivity of our DNA hybridization assay for methylation detection. Our GMR sensor is functionalized with synthetic DNA probes that target methylated or unmethylated CpG sites in the MSP amplicon, and measures the difference in melting temperature (T

Indexed as

Biosensing TechniquesCpG IslandsDNA MethylationHumansMelanomaPromoter Regions, GeneticTumor Suppressor ProteinsTumor Suppressor ProteinsArrayCancerDNA meltingGMR sensorsMethylation specific PCRPCR

Identifiers

PMID30366258
PMCPMC6245664
OpenAlexW2895806690

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.