Evidence map›Paper›PMID 27347177›Full record

ArticleOncology letters2016

Identification of disease-associated pathways in pancreatic cancer by integrating genome-wide association study and gene expression data.

Jin Long, Zhe Liu, Xingda Wu, Yuanhong Xu, Chunlin Ge

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 95% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 2 institutions in 1 country.

Jin LongDepartment of General Surgery, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.
Zhe LiuDepartment of General Surgery, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.
Xingda WuDepartment of General Surgery, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.
Yuanhong XuDepartment of General Surgery, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.
Chunlin GeDepartment of General Surgery, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.
First Hospital of China Medical University · CNChina Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to additionally understand the pathogenesis of pancreatic cancer (PC), the present study conducted pathway analysis based on genome-wide association study (GWAS) and gene expression data to predict genes that are associated with PC. GWAS data (accession no., pha002874.1) were downloaded from National Center for Biotechnology Information (NCBI) database of Genotypes and Phenotypes, which included data concerning 1,896 patients with PC and 1,939 control individuals. Gene expression data [accession no., GSE23952; human pancreatic carcinoma Panc-1 transforming growth factor-β (TGF-β) treatment assay] were downloaded from NCBI Gene Expression Omnibus. Gene set enrichment analysis was used to identify significant pathways in the GWAS or gene expression profiles. Meta-analysis was performed based on pathway analysis of the two data sources. In total, 58 and 280 pathways were identified to be significant in the GWAS and gene expression data, respectively, with 7 pathways significant in both the data profiles. Hsa 04350 TGF-β signaling pathway had the smallest meta P-value. Other significant pathways in the two data sources were negative regulation of DNA-dependent transcription, the nucleolus, negative regulation of RNA metabolic process, the cellular defense response, exocytosis and galactosyltransferase activity. By constructing the gene-pathway network, 5 pathways were closely associated, apart from exocytosis and galactosyltransferase activity pathways. Among the 7 pathways, 11 key genes (2.9% out of a total of 380 genes) from the GWAS data and 43 genes (10.5% out of a total of 409 genes) from the gene expression data were differentially expressed. Only Abelson murine leukemia viral oncogene homolog 1 from the nucleolus pathway was significantly expressed in by both data sources. Overall, the results of the present analysis provide possible factors for the occurrence of PC, and the identification of the pathways and genes associated with PC provides valuable data for investigating the pathogenesis of PC in future studies.

Indexed as

ABL1gene expression profileGWASmeta-analysispancreatic cancerTGF-β signaling pathway

Identifiers

PMID27347177
PMCPMC4906788
OpenAlexW2399489477

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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.