Evidence map›Paper›PMID 31140417›Full record

ArticleNan fang yi ke da xue xue bao = Journal of Southern Medical University2019

[Bioinformatics analysis of COL1A1 regulated by miR-129-5p as a potential therapeutic target for gastric cancer].

Wanxia Yang, Yunyan Pan, Peiwen Guan, Xue Li, Chongge You

Abstract read
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Article in Nan fang yi ke da xue xue bao = Journal of Southern Medical University, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

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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.

Wanxia YangLaboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou 730030, China.
Yunyan PanLaboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou 730030, China.
Peiwen GuanLaboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou 730030, China.
Xue LiLaboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou 730030, China.
Chongge YouLaboratory Medicine Center, Lanzhou University Second Hospital, Lanzhou 730030, China.
Lanzhou University Second Hospital · CNLanzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo explore the pathogenesis of gastric cancer through a bioinformatic approach to provide evidence for the prevention and treatment of gastric cancer.

methodsThe differentially expressed genes (DEGs) in gastric cancer and normal gastric mucosa in GSE79973 dataset were analyzed using GEO2R online tool. GO analysis and KEGG pathway enrichment analysis of the DEGs in DAVID database were performed. The protein interaction network was constructed using STRING database, and the key genes (Hub genes) were screened and their functional modules were analyzed using Cytoscape software. The GEPIA database was used to validate the Hub genes, and the Target Scan database was used to predict the microRNAs that regulate the target genes; OncomiR was used to analyze the expressions of the microRNAs in gastric cancer tissues and their relationship with the survival outcomes of the patients.

resultsA total of 181 DEGs were identified in gastric cancer, and 10 hub genes were screened by the protein- protein interaction network. Functional analysis showed that these DEGs were involved mainly in protein digestion and absorption, PI3K-Akt signaling pathway, ECM-receptor interaction and platelet activation signal pathway. GEPIA database validation showed that COL1A1 was highly expressed in gastric cancer tissues and was associated with a poor prognosis of patients with gastric cancer. MiR-129-5p was found to bind to the 3'UTR of COL1A1 mRNA, and compared with that in normal tissues, miR-129-5p expression was obviously down-regulated in gastric cancer tissues, and was correlated with the prognosis of the patients.

conclusionsCOL1A1 under regulation by MiR-129-5p is a potential therapeutic target for gastric cancer.

Indexed as

Collagen Type IComputational BiologyMicroRNAsStomach NeoplasmsCollagen Type I, alpha 1 ChainGene Expression ProfilingGene Expression Regulation, NeoplasticHumansPhosphatidylinositol 3-KinasesCollagen Type ICollagen Type I, alpha 1 ChainMicroRNAsMirn129 microRNA, humanPhosphatidylinositol 3-Kinasesbioinformatic analysisCOL1A1differentially expressed genesgastric cancermiR-129-5p

Identifiers

PMID31140417
PMCPMC6743932
OpenAlexW2947356199

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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.