Evidence map›Paper›PMID 32963620›Full record

ArticleOncology letters2020

Identification of hub genes associated with esophageal cancer progression using bioinformatics analysis.

Jiangfen Li, Yufang Xie, Xueli Wang, Chenhao Jiang, Xin Yuan, Anzhi Zhang, Lan Yang, Chunxia Liu, Hong Zou, Feng Li and 1 more

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

6 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. [Research Advances of RAD51AP1 in Tumor Progression and Drug Resistance].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2023
    Review
  4. Article
  5. Article
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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

11 authors at 1 institution in 1 country.

Jiangfen LiDepartment of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases (Ministry of Education), The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832000, P.R. China.
Yufang XieDepartment of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases (Ministry of Education), The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832000, P.R. China.
Xueli WangDepartment of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases (Ministry of Education), The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832000, P.R. China.
Chenhao JiangDepartment of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases (Ministry of Education), The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832000, P.R. China.
Xin YuanDepartment of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases (Ministry of Education), The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832000, P.R. China.
Anzhi ZhangDepartment of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases (Ministry of Education), The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832000, P.R. China.
Lan YangDepartment of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases (Ministry of Education), The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832000, P.R. China.
Chunxia LiuDepartment of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases (Ministry of Education), The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832000, P.R. China.
Hong ZouDepartment of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases (Ministry of Education), The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832000, P.R. China.
Feng LiDepartment of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases (Ministry of Education), The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832000, P.R. China.
Jianming HuDepartment of Pathology and Key Laboratory for Xinjiang Endemic and Ethnic Diseases (Ministry of Education), The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang 832000, P.R. China.
Shihezi University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The underlying causes of esophageal cancer (EC) are unknown. To explore the molecular mechanisms that lead to EC, gene expression profiles of large cohorts of patients with EC were obtained from The Cancer Genome Atlas and the Gene Expression Omnibus (GEO) databases (GSE5364, GSE20347 and GSE23400). The present study identified 83 upregulated and 22 downregulated genes between EC and normal tissue using R statistical software and the GEO2R web tool. The Database for Annotation, Visualization and Integrated Discovery was used to identify the associated pathways, and for functional annotation of the differentially expressed genes (DEGs). Protein-protein interactions of these DEGs were analyzed based on the Search Tool for the Retrieval of Interacting Genes database, and hub genes were visualized using Cytoscape software. An online Kaplan-Meier plotter survival analysis tool was utilized to evaluate the prognostic value of hub gene expression in patients with EC. Further analysis of an additional dataset from GEO (GSE21293) revealed that these genes were associated with infiltration and metastasis in EC. In addition, the Gene Expression Profiling Interactive Analysis tool was used to evaluate expression levels of hub genes in patients with EC for different pathological stages. The Ualcan analysis tool was used to evaluate the expression levels of hub genes for different histological types. Overall, ubiquitin conjugating enzyme E2 C, cyclin dependent kinase inhibitor 3, CDC28 protein kinase regulatory subunit 2, kinesin family member 20A (KIF20A) and RAD51 associated protein 1 (RAD51AP1) were upregulated in EC tissues compared with normal tissues, and upregulation of these genes was a poor prognostic factor for patients with EC, indicating that these genes may mediate EC cell infiltration and metastasis. Among the hub genes, KIF-20A had potential value for predicting the pathological stage of EC. KIF20A and RAD51AP1 were more informative biomarkers of esophageal squamous cell carcinoma. Further studies are required to explore the value of these genes in the treatment of EC.

Indexed as

CDC28 protein kinase regulatory subunit 2cyclin dependent kinase inhibitor 3esophageal cancerexpression profiling datahub geneskinesin family member 20ARAD51 associated protein 1ubiquitin conjugating enzyme E2 C

Identifiers

PMID32963620
PMCPMC7491038
OpenAlexW3084382425

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.