Evidence map›Paper›PMID 31173206›Full record

ArticleMolecular medicine reports2019

Identification of critical genes associated with human osteosarcoma metastasis based on integrated gene expression profiling.

Hongwu Fan, Shan Lu, Shengqun Wang, Shanyong Zhang

Open access · hybridAbstract read
In one paragraph

Article in Molecular medicine reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

26 citing papers in PubMed, 45 citations in OpenAlex.

  1. [Glutamine metabolic reprogramming in regulating the occurrence and development of osteosarcoma].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2025
    Review
  2. Review
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  5. The Impact of Developmental and Metabolic Cues on Cytoophidium Formation.International journal of molecular sciences · 2024
    Review
  6. Article
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  12. Identification of Key Genes and Pathways in Osteosarcoma by Bioinformatics Analysis.Computational and mathematical methods in medicine · 2022
    Article
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  14. Article
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  16. circKMT2D contributes to HExperimental and therapeutic medicine · 2020
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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

4 authors at 2 institutions in 1 country.

Hongwu FanDepartment of Orthopedics, China Japan Union Hospital of Jilin University, Changchun, Jilin 130021, P.R. China.
Shan LuDepartment of Anesthesiology, China Japan Union Hospital of Jilin University, Changchun, Jilin 130021, P.R. China.
Shengqun WangDepartment of Orthopedics, China Japan Union Hospital of Jilin University, Changchun, Jilin 130021, P.R. China.
Shanyong ZhangDepartment of Spinal Surgery, The Second Hospital of Jilin University, Changchun, Jilin 130041, P.R. China.
Jilin University · CNSecond Affiliated Hospital of Jilin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteosarcoma is the most common type of malignant bone cancer, which often affects teenagers and young adults. The present study aimed to screen for critical genes and microRNAs (miRNAs/miRs) involved in osteosarcoma. A total of four microarray datasets (accession numbers GSE32981, GSE21257, GSE14827 and GSE14359) were downloaded from the Gene Expression Omnibus database. Following data preprocessing, module analysis was performed to identify the stable modules using the weighted gene co‑expression network analysis (WGCNA) package. The differentially expressed genes (DEGs) between metastatic samples and non‑metastatic samples were screened, followed by gene co‑expression network construction, and Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Subsequently, prognosis‑associated genes were screened and a miRNA‑target gene regulatory network was constructed. Finally, the data for critical genes were validated. WGCNA analysis identified six modules; blue and yellow modules were significantly positively associated with osteosarcoma metastasis. A total of 1,613 DEGs were screened between primary tissue samples and metastatic samples. Following comparison of the genes in the two (blue and yellow) modules, a total of 166 DEGs were identified (metastatic samples vs. non‑metastatic samples). Functional enrichment analysis demonstrated that these DEGs were mainly involved in 'defense response', 'p53 signaling pathway' and 'lysosome'. By utilizing the clinical information in GSE21257, 10 critical genes associated with osteosarcoma prognosis were obtained, including CTP synthase 2 (CTPS2), tumor protein p53 inducible protein 3 (TP53I3) and solute carrier family 1 member 1 (SLC1A1). In addition, hsa‑miR‑422a and hsa‑miR‑194 were highlighted in the miRNA‑target gene network. Finally, matrix metallopeptidase 3 (MMP3) and vascular endothelial growth factor B (VEGFB) were predicted as critical genes in osteosarcoma metastasis. CTPS2, TP53I3 and SLC1A1 may serve major roles in osteosarcoma development, and hsa‑miR‑422a, hsa‑miR‑194, MMP3 and VEGFB may be associated with osteosarcoma metastasis.

Indexed as

Gene Expression Regulation, NeoplasticGene Regulatory NetworksBone NeoplasmsCarbon-Nitrogen LigasesDatabases, GeneticExcitatory Amino Acid Transporter 3Gene Expression ProfilingGene OntologyHumansIntracellular Signaling Peptides and ProteinsMatrix Metalloproteinase 3MicroRNAsMolecular Sequence AnnotationNeoplasm MetastasisNeoplasm ProteinsOsteosarcomaCarbon-Nitrogen LigasesCTP synthetaseExcitatory Amino Acid Transporter 3Intracellular Signaling Peptides and ProteinsMatrix Metalloproteinase 3MicroRNAsMIRN194 microRNA, humanMIRN422 microRNA, humanMMP3 protein, humanNeoplasm ProteinsProto-Oncogene ProteinsSLC1A1 protein, humanTP53I3 protein, humanVascular Endothelial Growth Factor BVEGFB protein, human

Identifiers

PMID31173206
PMCPMC6625205
OpenAlexW2948656673

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.