Evidence map›Paper›PMID 29286604›Full record

ArticleAsian Pacific journal of cancer prevention : APJCP2017

Protein-Protein Interaction Network Analysis for a Biomarker Panel Related to Human Esophageal Adenocarcinoma

Majid Rezaei-Tavirani, Sina Rezaei-Taviran, Mansouri Mansouri, Mohammad Rostami-Nejad, Mostafa Rezaei-Tavirani

Abstract read
In one paragraph

Article in Asian Pacific journal of cancer prevention : APJCP, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

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0cells of the map it votes in
36citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

36 citing papers in PubMed.

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  12. Targeting colon cancer via antimicrobial RT2 peptide: a system biology study.Gastroenterology and hepatology from bed to bench · 2023
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  19. Identification ofCell journal · 2021
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Majid Rezaei-TaviraniFaculty of Medicine, Iran University of Medical Sciences, Tehran, Iran. Email: Tavirany@yahoo.com
Sina Rezaei-Taviran
Mansouri Mansouri
Mohammad Rostami-Nejad
Mostafa Rezaei-Tavirani

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Esophageal adenocarcinoma (EAC) is one of the mostlethal cancers in the world with a very poor prognosis. Identification of molecular diagnostic methods is an important goal. Since protein-protein interaction (PPI) network analysis is a suitable method for molecular assessment, in the present research a PPI network related to EAC was targeted. Material and Method: Cytoscape software and its applications including STRING DB, Cluster ONE and ClueGO were applied to analyze the PPI network. Result: Among 182 EAC-related proteins which were identified, 129 were included in a main connected component. Proteins based on centrality analysis of characteristics such as degree, betweenness, closeness and stress were screened and key nodes were introduced. Two clusters were determined of which only one was significant statistically. Gene ontology revealed 50 terms in three groups associated with EAC. Conclusion: The findings indicate nine crucial proteins could form a candidate biomarker panel for EAC. Furthermore, an important cluster with 27 proteins related to the disease was identified. Gene ontology analysis of this cluster showed main related terms to closely correspond with those for colorectal cancer.

Indexed as

Gene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksAdenocarcinomaBiomarkers, TumorCluster AnalysisEsophageal NeoplasmsGene OntologyHumansPrognosisProtein Interaction MapsSoftwareBiomarkers, Tumorcluster analysisEsophageal adenocarcinoma (EAC)protein-protein interaction (PPI) network analysis

Identifiers

PMID29286604
PMCPMC5980895

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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.