Evidence map›Paper›PMID 36238488›Full record

ArticleComputational and mathematical methods in medicine2022

Identification of Candidate MicroRNA-mRNA Subnetwork for Predicting the Osteosarcoma Progression by Bioinformatics Analysis.

Dejie Lu, Hanji Huang, Li Zheng, Kanglu Li, Xiaofei Cui, Xiong Qin, Mingjun Zheng, Nanchang Huang, Chaotao Chen, Jinmin Zhao and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. 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
0.1field-weighted citation impact, top 60% 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, 1 citations in OpenAlex.

  1. 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.

Dejie LuGuangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Hanji HuangGuangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Li ZhengGuangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Kanglu LiGuangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Xiaofei CuiGuangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Xiong QinGuangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Mingjun ZhengGuangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Nanchang HuangGuangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Chaotao ChenGuangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
Jinmin ZhaoGuangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.ORCID https://orcid.org/0000-0002-1047-8820
Bo ZhuGuangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.ORCID https://orcid.org/0000-0001-5856-6320
Guangxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteosarcoma (OS) is the pretty common primary cancer of the bone among the malignancies in adolescents. A single molecular component or a limited number of molecules is insufficient as a predictive biomarker of OS progression. Hence, it is necessary to find novel network biomarkers to improve the prediction and therapeutic effect for OS. Here, we identified 230 DE-miRNAs and 821 DE-mRNAs through two miRNA expression-profiling datasets and three mRNA expression-profiling datasets. We found that hsa-miR-494 is closely linked with the survival of OS patients. In addition, we analyzed GO and KEGG enrichment for targets of hsa-miR-494-5p and hsa-miR-494-3p through R programming. And five mRNAs were predicted as common targets of hsa-miR-494-5p and hsa-miR-494-3p. We further revealed that upregulated TRPS1 was strongly correlated with poor outcomes in OS patients through the survival analysis based on the TARGET database. The qRT-PCR study verified that the expression of hsa-miR-494-5p and hsa-miR-494-3p was declined considerably, while TRPS1 was notably raised in OS cells when compared to the osteoblasts. Thus, we generated a new regulatory subnetwork of key miRNAs and target mRNAs using Cytoscape software. These results indicate that the novel miRNA-mRNA subnetwork composed of hsa-miR-494-5p, hsa-miR-494-3p, and TRPS1 might be a characteristic molecule for assessing the prognostic value of OS patients.

Indexed as

MicroRNAsOsteosarcomaAdolescentBiomarkersComputational BiologyGene Regulatory NetworksHumansRepressor ProteinsRNA, MessengerBiomarkersMicroRNAsRepressor ProteinsRNA, MessengerTRPS1 protein, human

Identifiers

PMID36238488
PMCPMC9553349
OpenAlexW4296916550

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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.