Evidence map›Paper›PMID 27035224›Full record

ArticleMolecular medicine reports2016

Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile.

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

Open access · hybridAbstract read
In one paragraph

Article in Molecular medicine reports, 2016. 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
0.3field-weighted citation impact, top 35% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Modularity in Biological Networks.Frontiers in genetics · 2021
    Review
  4. Review
  5. 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

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

The present study aimed to screen for potential genes and subnetworks associated with pancreatic cancer (PC) using the gene expression profile. The expression profile GSE 16515 was downloaded from the Gene Expression Omnibus database, which included 36 PC tissue samples and 16 normal samples. Limma package in R language was used to screen differentially expressed genes (DEGs), which were grouped as up‑ and downregulated genes. Then, PFSNet was applied to perform subnetwork analysis for all the DEGs. Moreover, Gene Ontology (GO) and REACTOME pathway enrichment analysis of up‑ and downregulated genes was performed, followed by protein‑protein interaction (PPI) network construction using Search Tool for the Retrieval of Interacting Genes Search Tool for the Retrieval of Interacting Genes. In total, 1,989 DEGs including 1,461 up‑ and 528 downregulated genes were screened out. Subnetworks including pancreatic cancer in PC tissue samples and intercellular adhesion in normal samples were identified, respectively. A total of 8 significant REACTOME pathways for upregulated DEGs, such as hemostasis and cell cycle, mitotic were identified. Moreover, 4 significant REACTOME pathways for downregulated DEGs, including regulation of β‑cell development and transmembrane transport of small molecules were screened out. Additionally, DEGs with high connectivity degrees, such as CCNA2 (cyclin A2) and PBK (PDZ binding kinase), of the module in the protein‑protein interaction network were mainly enriched with cell‑division cycle. CCNA2 and PBK of the module and their relative pathway cell‑division cycle, and two subnetworks (pancreatic cancer and intercellular adhesion subnetworks) may be pivotal for further understanding of the molecular mechanism of PC.

Indexed as

Gene Expression ProfilingGene Expression Regulation, NeoplasticGenes, NeoplasmNeoplasm ProteinsPancreatic NeoplasmsFemaleHumansMaleNeoplasm Proteins

Identifiers

PMID27035224
PMCPMC4838159
OpenAlexW2302406006

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.