Evidence map›Paper›PMID 36915458›Full record

ArticleJournal of gastrointestinal oncology2023

Network and pathway-based analysis of candidate genes associated with esophageal adenocarcinoma.

Junfeng Li, Ling Peng, Hanbing Li, Yan Cai, Peng Yao, Qin Chen, Xiaolei Li, Qiuxi Zhou

Open access · diamondAbstract read
In one paragraph

Article in Journal of gastrointestinal oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.3field-weighted citation impact, top 22% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

8 authors at 5 institutions in 1 country.

Junfeng LiDepartment of Thoracic Surgery, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, China.
Ling PengDepartment of General Internal Medicine, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Cancer Hospital Affiliated to University of Electronic Science and Technology of China, Chengdu, China.
Hanbing LiDepartment of Thyroid and Breast Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Yan CaiDepartment of Thoracic Surgery, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, China.
Peng YaoDepartment of Thoracic Surgery, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, China.
Qin ChenDepartment of Thoracic Surgery, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, China.
Xiaolei LiDepartment of Thoracic Surgery, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Nanchong, China.
Qiuxi ZhouDepartment of General Internal Medicine, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Cancer Hospital Affiliated to University of Electronic Science and Technology of China, Chengdu, China.
Nanchong Central Hospital · CNAffiliated Hospital of North Sichuan Medical College · CNNorth Sichuan Medical University · CNSichuan Cancer Hospital · CNUniversity of Electronic Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Previous studies have made some headway in analyzing esophageal adenocarcinoma (EA) with respect to pathogenic factors, treatment methods, and prognosis. However, far less is known about the molecular mechanisms. Thus, a comprehensive analysis focusing on the biological function and interaction of EA genes would provide valuable information for understanding the pathogenesis of EA, which may provide new insights into gene function as well as potential therapy targets. Methods: We selected 109 genes related to EA by reviewing 458 publications from the PubMed database. In addition, performing gene enrichment assays, pathway enrichment assays, pathway crosstalk analysis, and extraction of EA-specific subnetwork were used to describe the relevant biochemical processes. Results: Function analysis revealed that biological processes and biochemical pathways associated with apoptotic and metabolic processes, a variety of cancers, and drug reaction pathways. Further, 12 novel genes ( Conclusions: Overall, by integrating pathways and networks to explore the pathogenetic mechanisms underlying EA, our results could significantly improve our understanding of the molecular mechanisms of EA and form a basis for selection of potential molecular targets for further exploration.

Indexed as

Esophageal adenocarcinomafunction enrichment analysisoncogenepathway crosstalkprotein-protein interaction network

Identifiers

PMID36915458
PMCPMC10007923
OpenAlexW4320887630

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.