Evidence map›Paper›PMID 39308540›Full record

ArticleGastroenterology and hepatology from bed to bench2024

Stage analysis of pancreatic ductal adenocarcinoma via network analysis.

Ayad Bahadorimonfared, Masoumeh Farahani, Mostafa Rezaei Tavirani, Zahra Razzaghi, Babak Arjmand, Mitra Rezaei, Abdolrahim Nikzamir, Mohammad Javad Ehsani Ardakani, Vahid Mansouri

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Article in Gastroenterology and hepatology from bed to bench, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

9 authors.

Ayad BahadorimonfaredDepartment of Health & Community Medicine, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Masoumeh FarahaniSkin Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mostafa Rezaei TaviraniProteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Zahra RazzaghiLaser Application in Medical Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Babak ArjmandCell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
Mitra RezaeiGenomic Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Abdolrahim NikzamirCeliac Disease and Gluten Related Disorders Research Center, Research Institute for Gastroenterology and Liver Disease, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mohammad Javad Ehsani ArdakaniGastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Vahid MansouriProteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: This study aimed to introduce a biomarker panel to detect pancreatic ductal adenocarcinoma (PDAC) in the early stage, and also differentiate of stages from each other. Background: PDAC is a lethal cancer with poor prognosis and overall survival. Methods: Gene expression profiles of PDAC patients were extracted from the Gene Expression Omnibus (GEO) database. The genes that were significantly differentially expressed (DEGs) for Stages I, II, and III in comparison to the healthy controls were identified. The determined DEGs were assessed via protein-protein interaction (PPI) network analysis, and the hub-bottleneck nodes of analyzed networks were introduced. Results: A number of 140, 874, and 1519 significant DEGs were evaluated via PPI network analysis. A biomarker panel including ALB, CTNNB1, COL1A1, POSTN, LUM, and ANXA2 is presented as a biomarker panel to detect PDAC in the early stage. Two biomarker panels are suggested to recognize other stages of illness. Conclusion: It can be concluded that ALB, CTNNB1, COL1A1, POSTN, LUM, and ANXA2 and also FN1, HSP90AA1, LOX, ANXA5, SERPINE1, and WWP2 beside GAPDH, AKT1, EGF, CASP3 are suitable sets of gene to separate stages of PDAC.

Indexed as

GeneNetwork analysisPancreatic ductal adenocarcinomastage

Identifiers

PMID39308540
PMCPMC11413388

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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.