Evidence map›Paper›PMID 33912448›Full record

ArticleFrontiers in oncology2021

Identification of Hub Genes Associated With Melanoma Development by Comprehensive Bioinformatics Analysis.

Jie Jiang, Chong Liu, Guoyong Xu, Tuo Liang, Chaojie Yu, Shian Liao, Zide Zhang, Zhaojun Lu, Zequn Wang, Jiarui Chen and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

15 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. 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

13 authors at 2 institutions in 1 country.

Jie JiangSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
Chong LiuSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
Guoyong XuSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
Tuo LiangSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
Chaojie YuSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
Shian LiaoSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
Zide ZhangSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
Zhaojun LuSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
Zequn WangSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
Jiarui ChenSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
Tianyou ChenSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
Hao LiSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
Xinli ZhanSpinal Orthopedic Ward, The First Clinical Affiliated Hospital of Guangxi Medical University, Nanning, China.
First Affiliated Hospital of GuangXi Medical University · CNGuangxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThis study aimed to identify important genes associated with melanoma to further develop new target gene therapies and analyze their significance concerning prognosis. MATERIALS AND

methodsGene expression data for melanoma and normal tissue were downloaded from three databases. Differentially co-expressed genes were identified by WGCNA and DEGs analysis. These genes were subjected to GO, and KEGG enrichment analysis and construction of the PPI visualized with Cytoscape and screened for the top 10 Hub genes using CytoHubba. We validated the Hub gene's protein levels with an immunohistochemical assay to confirm the accuracy of our analysis.

resultsA total of 435 differentially co-expressed genes were obtained. Survival curves showed that high expression of FOXM1,\ EXO1, KIF20A, TPX2, and CDC20 in melanoma patients with 5 of the top 10 hub genes was associated with reduced overall survival (OS). Immunohistochemistry showed that all five genes were expressed at higher protein levels in melanoma than in paracancerous tissues.

conclusionFOXM1, EXO1, KIF20A, TPX2, and CDC20 are prognosis-associated core genes of melanoma, and their high expression correlates with the low prognosis of melanoma patients and can be used as biomarkers for melanoma diagnosis, treatment, and prognosis prediction.

Indexed as

biomarkerdifferential expression gene analysisimmunohistochemistrymelanomapredict prognosisweighted gene co-expression network analysis

Identifiers

PMID33912448
PMCPMC8072149
OpenAlexW3112181448

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.