Evidence map›Paper›PMID 33742531›Full record

ArticleCancer medicine2021

Identification of MEG8/miR-378d/SOBP axis as a novel regulatory network and associated with immune infiltrates in ovarian carcinoma by integrated bioinformatics analysis.

Jian Lei, Zhen-Yu He, Jun Wang, Min Hu, Ping Zhou, Chen-Lu Lian, Li Hua, San-Gang Wu, Juan Zhou

Open access · goldAbstract read
In one paragraph

Article in Cancer medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 35% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
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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

9 authors at 2 institutions in 1 country.

Jian LeiDepartment of Obstetrics and Gynecology, the First Affiliated Hospital of Xiamen University, Xiamen, People's Republic of China.ORCID 0000-0002-5214-4730
Zhen-Yu HeDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangzhou, People's Republic of China.ORCID 0000-0003-1402-8963
Jun WangDepartment of Radiation Oncology, the First Affiliated Hospital of Xiamen University, Xiamen, People's Republic of China.
Min HuDepartment of Obstetrics and Gynecology, the First Affiliated Hospital of Xiamen University, Xiamen, People's Republic of China.
Ping ZhouDepartment of Radiation Oncology, the First Affiliated Hospital of Xiamen University, Xiamen, People's Republic of China.
Chen-Lu LianDepartment of Radiation Oncology, the First Affiliated Hospital of Xiamen University, Xiamen, People's Republic of China.
Li HuaDepartment of Obstetrics and Gynecology, the First Affiliated Hospital of Xiamen University, Xiamen, People's Republic of China.
San-Gang WuDepartment of Radiation Oncology, the First Affiliated Hospital of Xiamen University, Xiamen, People's Republic of China.ORCID 0000-0002-0556-2614
Juan ZhouDepartment of Obstetrics and Gynecology, the First Affiliated Hospital of Xiamen University, Xiamen, People's Republic of China.
First Affiliated Hospital of Xiamen University · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo investigate the potential molecular mechanism of ovarian cancer (OC) evolution and immunological correlation using the integrated bioinformatics analysis.

methodsData from the Gene Expression Omnibus was used to gain differentially expressed genes (DEGs). Gene Ontology and Kyoto Encyclopedia of Gene and Genome pathway analysis were completed by utilizing the Database for Annotation, Visualization, and Integrated Discovery. After multiple validations via The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) projects, the Human Protein Atlas, Kaplan-Meier (KM) plotter, and immune logical relationships of the key gene SOBP were evaluated based on Tumor Immune Estimation Resource, and Gene Set Enrichment Analysis (GSEA) software. Finally, the lncRNAs-miRNAs-mRNAs subnetwork was predicted by starBase, TargetScan, miRBD, and LncBase, individually. Correlation of expression and prognosis for mRNAs, miRNAs, and lncRNAs were confirmed by TCGA, Gene Expression Profiling Interactive Analysis 2 (GEPIA 2), starBase, and KM.

resultsA total of 192 shared DEGs were discovered from the four data sets, including 125 upregulated and 67 downregulated genes. Functional enrichment analysis presented that they were mainly enriched in cartilage development, pathway in PI3 K-Akt signaling pathway. Lower expression of SOBP was the independent prognostic factor for inferior prognosis in OC patients. The downregulation of SOBP enhanced the infiltration levels of B cells, CD8+ T cells, Macrophage, Neutrophil, and Dendritic cells. GSEA also disclosed low SOBP showed a significantly associated with the activation of various immune-related pathways. Finally, we first reported that the MEG8/miR-378d/SOBP axis was linked to the development and prognosis of OC through regulating the cytokines pathway.

conclusionsOur study establishes a novel MEG8/miR-378d/SOBP axis in the development and prognosis of OC, and the triple subnetwork probably affects the progression of the OC by regulating the cytokines pathway.

Indexed as

Biomarkers, TumorCarrier ProteinsComputational BiologyFemaleGene Expression Regulation, NeoplasticGene OntologyGene Regulatory NetworksHumansKaplan-Meier EstimateMicroRNAsNuclear ProteinsOvarian NeoplasmsReproducibility of ResultsRNA, Long NoncodingBiomarkers, TumorCarrier ProteinsMicroRNAsMIRN378 microRNA, humanNuclear ProteinsRNA, Long NoncodingSOBP protein, humanbioinformatics analysiscompeting endogenous RNAdifferently expressed genesovarian cancertumor-infiltrating lymphocytes

Identifiers

PMID33742531
PMCPMC8026926
OpenAlexW3137746079

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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.