Evidence map›Paper›PMID 26769141›Full record

ArticleModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc2016

High-definition CpG methylation of novel genes in gastric carcinogenesis identified by next-generation sequencing.

Jorge L Sepulveda, Jorge L Gutierrez-Pajares, Aesis Luna, Yuan Yao, John W Tobias, Steven Thomas, Yanghee Woo, Federico Giorgi, Elena V Komissarova, Andrea Califano and 2 more

Open access · bronzeAbstract readComparative Study
PubMed Publisher
In one paragraph

Article in Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
3.8field-weighted citation impact, top 7% 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

39 citing papers in PubMed, 57 citations in OpenAlex.

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  20. SGCE Promotes Breast Cancer Stem Cells by Stabilizing EGFR.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2020
    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

12 authors at 2 institutions in 1 country.

Jorge L SepulvedaDepartment of Pathology and Cell Biology, Columbia University, New York, NY, USA.
Jorge L Gutierrez-PajaresDepartment of Pathology and Cell Biology, Columbia University, New York, NY, USA.
Aesis LunaDepartment of Pathology and Cell Biology, Columbia University, New York, NY, USA.
Yuan YaoDepartment of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA.
John W TobiasDepartment of Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.
Steven ThomasDepartment of Pathology and Cell Biology, Columbia University, New York, NY, USA.
Yanghee WooDepartment of Surgery, Columbia University, New York, NY, USA.
Federico GiorgiDepartment of Systems Biology, Columbia University, New York, NY, USA.
Elena V KomissarovaDepartment of Systems Biology, Columbia University, New York, NY, USA.
Andrea CalifanoDepartment of Systems Biology, Columbia University, New York, NY, USA.
Timothy C WangDepartment of Medicine, Division of Gastroenterology, Columbia University, New York, NY, USA.
Antonia R SepulvedaDepartment of Pathology and Cell Biology, Columbia University, New York, NY, USA.
Columbia University · USUniversity of Pennsylvania · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastric cancers are the most frequent gastric malignancy and usually arise in the sequence of Helicobacter pylori-associated chronic gastritis. CpG methylation is a central mechanism of epigenetic gene regulation affecting cancer-related genes, and occurs early in gastric carcinogenesis. DNA samples from non-metaplastic gastric mucosa with variable levels of gastritis (non-metaplastic mucosa), intestinal metaplasia, or gastric cancer were screened with methylation arrays for CpG methylation of cancer-related genes and 30 gene targets were further characterized by high-definition bisulfite next-generation sequencing. In addition, data from The Cancer Genome Atlas were analyzed for correlation of methylation with gene expression. Overall, 13 genes had significantly increased CpG methylation in gastric cancer vs non-metaplastic mucosa (BRINP1, CDH11, CHFR, EPHA5, EPHA7, FGF2, FLI1, GALR1, HS3ST2, PDGFRA, SEZ6L, SGCE, and SNRPN). Further, most of these genes had corresponding reduced expression levels in gastric cancer compared with intestinal metaplasia, including novel hypermethylated genes in gastric cancer (FLI1, GALR1, SGCE, and SNRPN), suggesting that they may regulate neoplastic transformation from non-malignant intestinal metaplasia to cancer. Our data suggest a tumor-suppressor role for FLI1 in gastric cancer, consistent with recently reported data in breast cancer. For the genes with strongest methylation/expression correlation, namely FLI1, the expression was lowest in microsatellite-unstable tumors compared with other gastric cancer molecular subtypes. Importantly, reduced expression of hypermethylated BRINP1 and SGCE was significantly associated with favorable survival in gastric cancer. In summary, we report novel methylation gene targets that may have functional roles in discrete stages of gastric carcinogenesis and may serve as biomarkers for diagnosis and prognosis of gastric cancer.

Indexed as

CpG IslandsDNA MethylationEpigenesis, GeneticHigh-Throughput Nucleotide SequencingAdenocarcinomaBiomarkers, TumorCell Transformation, NeoplasticComputational BiologyDatabases, GeneticDisease ProgressionGastrectomyGastric MucosaGastritisGenetic Predisposition to DiseaseHumansMetaplasiaBiomarkers, Tumor

Identifiers

PMID26769141
OpenAlexW2239420344

What OpenQuestion holds

Textmetadata
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.