Evidence map›Paper›PMID 26725182›Full record

ArticleJournal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer2016

Validation of SCT Methylation as a Hallmark Biomarker for Lung Cancers.

Yu-An Zhang, Xiaotu Ma, Adwait Sathe, Junya Fujimoto, Ignacio Wistuba, Stephen Lam, Yasushi Yatabe, Yi-Wei Wang, Victor Stastny, Boning Gao and 10 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
  2. Article
  3. Hypermethylation ofOncology letters · 2018
    Article
  4. Circulating tumor DNA: Solid data from liquid biopsies.The Journal of thoracic and cardiovascular surgery · 2017
    Article
  5. Article
  6. ITPKA Gene Body Methylation Regulates Gene Expression and Serves as an Early Diagnostic Marker in Lung and Other Cancers.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2016
    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

20 authors at 7 institutions in 4 countries.

Yu-An Zhang *
Xiaotu Ma *
Adwait Sathe *
Junya Fujimoto
Ignacio Wistuba
Stephen Lam
Yasushi Yatabe
Yi-Wei Wang
Victor Stastny
Boning Gao
Jill E Larsen
Luc Girard
Xiaoyun Liu
Kai Song
Carmen Behrens
Neda Kalhor
Yang Xie
Michael Q Zhang
John D Minna
Adi F Gazdar
The University of Texas Southwestern Medical Center · USThe University of Texas MD Anderson Cancer Center · USThe University of Texas at Dallas · USAichi Cancer Center · JPBC Cancer Agency · CASt. Jude Children's Research Hospital · USTianjin University · CN

Funding

UNIVERSITY OF TEXAS--SPORE IN LUNG CANCERP50CA070907 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI GIBBONS, DON LYNN · 1996 to 2024
$57.4M
PROTEIN CODING GENES IN THE HUMAN GENOMER01HG001696 · NHGRI · UNIVERSITY OF TEXAS DALLAS · PI ZHANG, MICHAEL Q · 1997 to 2010
$5.1M
Novel Reagents and New Biomarkers for Lung CancerU01CA084971 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI GAZDAR, ADI F. · 1999 to 2009
$4.5M
NCI NIH HHS P50 CA070907NCI NIH HHS P50CA70907NCI NIH HHS U01 CA084971NCI NIH HHS U01CA084971NHGRI NIH HHS HG001696NHGRI NIH HHS R01 HG001696
6 · The paper itself

Abstract

introductionThe human secretin gene (SCT) encodes secretin, a hormone with limited tissue distribution. Analysis of the 450k methylation array data in The Cancer Genome Atlas (TCGA) indicated that the SCT promoter region is differentially hypermethylated in lung cancer. Our purpose was to validate SCT methylation as a potential biomarker for lung cancer.

methodsWe analyzed data from TCGA and developed and applied SCT-specific bisulfite DNA sequencing and quantitative methylation-specific polymerase chain reaction assays.

resultsThe analyses of TCGA 450K data for 801 samples showed that SCT hypermethylation has an area under the curve (AUC) value greater than 0.98 that can be used to distinguish lung adenocarcinomas or squamous cell carcinomas from nonmalignant lung tissue. Bisulfite sequencing of lung cancer cell lines and normal blood cells allowed us to confirm that SCT methylation is highly discriminative. By applying a quantitative methylation-specific polymerase chain reaction assay, we found that SCT hypermethylation is frequently detected in all major subtypes of malignant non-small cell lung cancer (AUC = 0.92, n = 108) and small cell lung cancer (AUC = 0.93, n = 40) but is less frequent in lung carcinoids (AUC = 0.54, n = 20). SCT hypermethylation appeared in samples of lung carcinoma in situ during multistage pathogenesis and increased in invasive samples. Further analyses of TCGA 450k data showed that SCT hypermethylation is highly discriminative in most other types of malignant tumors but less frequent in low-grade malignant tumors. The only normal tissue with a high level of methylation was the placenta.

conclusionsOur findings demonstrated that SCT methylation is a highly discriminative biomarker for lung and other malignant tumors, is less frequent in low-grade malignant tumors (including lung carcinoids), and appears at the carcinoma in situ stage.

Indexed as

DNA MethylationBiomarkers, TumorCarcinoma, Non-Small-Cell LungCell Line, TumorCpG IslandsGene Expression Regulation, NeoplasticHumansLung NeoplasmsPromoter Regions, GeneticSecretinSequence Analysis, DNABiomarkers, TumorSecretinCancer biomarkerFFPE DNA SCT qMSPLung cancerSCT methylationSecretin

Identifiers

PMID26725182
PMCPMC4809190
OpenAlexW2284650234

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.