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pmid:35747602

Comprehensive Bioinformatics Analysis to Reveal Key RNA Targets and Hub Competitive Endogenous RNA Network of Keratoconus.

Shuai Ouyang · Jingyu Ma · Qihang Sun · Jinyan Li · Yijia Chen · Lixia Luo

Frontiers in genetics · 2022 doi:10.3389/fgene.2022.896780

Paper

complete

Experiment

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Data

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Analysis

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Execution

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title
Comprehensive Bioinformatics Analysis to Reveal Key RNA Targets and Hub Competitive Endogenous RNA Network of Keratoconus.
doi
10.3389/fgene.2022.896780
pmid
35747602
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[0]
Shuai Ouyang
[1]
Jingyu Ma
[2]
Qihang Sun
[3]
Jinyan Li
[4]
Yijia Chen
[5]
Lixia Luo
journal
Frontiers in genetics
year
2022
abstract
Keratoconus (KC) is the most common corneal ectatic disease, with its pathological mechanisms unclear. We mainly performed bioinformatics approaches to reveal core RNA targets and hub competitive endogenous RNA (ceRNA) network and explored the potential regulatory mechanisms of ceRNA in KC. The high-throughput sequencing datasets GSE77938 and GSE151631 were downloaded from the Gene Expression Omnibus (GEO) database. The differential expression of mRNAs and lncRNAs was identified using the DESeq2 package. Functional enrichment analyses and protein-protein interaction (PPI) were executed. Then, the hub genes were filtered and molecular docking analysis was performed. Moreover, we predicted miRNAs through a website database and validated them using quantitative PCR (qPCR). Eventually, the lncRNA-miRNA-mRNA regulatory network was constructed by Cytoscape. We revealed that 428 intersected differentially expressed mRNA (DEGs) and 68 intersected differentially expressed lncRNA (DELs) were shared between the two datasets. Functional enrichment results innovatively showed that the ubiquitin-dependent protein catabolic process was upregulated in KC. The pathway enrichment showed that DEGs were mainly involved in NF-kB signaling and neurodegenerative diseases. In addition, we uncovered the top 20 hub genes in which FBXW11, FBXO9, RCHY1, and CD36 were validated by qPCR. Particularly, a small-molecule drug triptolide was predicted by molecular docking to be a candidate drug for treating KC. Moreover, we innovatively predicted and validated four core miRNAs (miR-4257, miR-4494, miR-4263, and miR-4298) and constructed a ceRNA network that contained 165 mRNA, eight lncRNAs, and four core miRNAs. Finally, we proposed a potential regulatory mechanism for KC. Overall, we uncovered a hub ceRNA network that might underlie a critical posttranslational regulatory mechanism in KC, in which miR-4257, miR-4494, miR-4263, and miR-4298 could be valuable biomarkers and provided core RNAs therapeutic targets for KC.
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Compared to the control samples with KC samples, the “DESeq2” package (Love et al., 2014) in R (version 4.0.1) software was utilized to identify the differentially expressed genes (DEGs) with thresholds of |log2 fold change| > 1.5 and FDR (adjusted p-value) < 0.05.
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sections[3] "High-Throughput RNA-Sequencing Datasets of KC Preparation and Screening of Differentially Expressed mRNAs and lncRNAs" paragraph 2
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Compared to the control samples with KC samples, the “DESeq2” package (Love et al., 2014) in R (version 4.0.1) software was utilized to identify the differentially expressed genes (DEGs) with thresholds of |log2 fold change| > 1.5 and FDR (adjusted p-value) < 0.05.
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The analysis identified 428 intersected differentially expressed mRNAs and 68 intersected differentially expressed lncRNAs shared between the two datasets.
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We revealed that 428 intersected differentially expressed mRNA (DEGs) and 68 intersected differentially expressed lncRNA (DELs) were shared between the two datasets.
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The analysis identified 428 intersected differentially expressed mRNAs and 68 intersected differentially expressed lncRNAs shared between the two datasets.
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ependent protein catabolic process, and cell apoptosis may play a critical role in the pathogenesis
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Compared to the control samples with KC samples, the “DESeq2” package (Love et al., 2014) in R (version 4.0.1) software was utilized to identify the differentially expressed genes (DEGs) with thresholds of |log2 fold change| > 1.5 and FDR (adjusted p-value) < 0.05.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35747602", "kind": "science-record", "revision": 5, "content_hash": "sha256:7aa9568e70710faefd821de54187f56a0777e3b3c99e9e84e1d24fcfd0860f9e", "created_at": "2026-11-01T18:14:46Z", "updated_at": "2026-11-01T22:49:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive Bioinformatics Analysis to Reveal Key RNA Targets and Hub Competitive Endogenous RNA Network of Keratoconus.", "doi": "10.3389/fgene.2022.896780", "pmid": "35747602", "authors": ["Shuai Ouyang", "Jingyu Ma", "Qihang Sun", "Jinyan Li", "Yijia Chen", "Lixia Luo"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Keratoconus (KC) is the most common corneal ectatic disease, with its pathological mechanisms unclear. We mainly performed bioinformatics approaches to reveal core RNA targets and hub competitive endogenous RNA (ceRNA) network and explored the potential regulatory mechanisms of ceRNA in KC. The high-throughput sequencing datasets GSE77938 and GSE151631 were downloaded from the Gene Expression Omnibus (GEO) database. The differential expression of mRNAs and lncRNAs was identified using the DESeq2 package. Functional enrichment analyses and protein-protein interaction (PPI) were executed. Then, the hub genes were filtered and molecular docking analysis was performed. Moreover, we predicted miRNAs through a website database and validated them using quantitative PCR (qPCR). Eventually, the lncRNA-miRNA-mRNA regulatory network was constructed by Cytoscape. We revealed that 428 intersected differentially expressed mRNA (DEGs) and 68 intersected differentially expressed lncRNA (DELs) were shared between the two datasets. Functional enrichment results innovatively showed that the ubiquitin-dependent protein catabolic process was upregulated in KC. The pathway enrichment showed that DEGs were mainly involved in NF-kB signaling and neurodegenerative diseases. In addition, we uncovered the top 20 hub genes in which FBXW11, FBXO9, RCHY1, and CD36 were validated by qPCR. Particularly, a small-molecule drug triptolide was predicted by molecular docking to be a candidate drug for treating KC. Moreover, we innovatively predicted and validated four core miRNAs (miR-4257, miR-4494, miR-4263, and miR-4298) and constructed a ceRNA network that contained 165 mRNA, eight lncRNAs, and four core miRNAs. Finally, we proposed a potential regulatory mechanism for KC. Overall, we uncovered a hub ceRNA network that might underlie a critical posttranslational regulatory mechanism in KC, in which miR-4257, miR-4494, miR-4263, and miR-4298 could be valuable biomarkers and provided core RNAs therapeutic targets for KC.", "claims": [{"id": "claim-method", "statement": "Compared to the control samples with KC samples, the “DESeq2” package (Love et al., 2014) in R (version 4.0.1) software was utilized to identify the differentially expressed genes (DEGs) with thresholds of |log2 fold change| > 1.5 and FDR (adjusted p-value) < 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35747602", "locator": "sections[3] \"High-Throughput RNA-Sequencing Datasets of KC Preparation and Screening of Differentially Expressed mRNAs and lncRNAs\" paragraph 2", "quote": "Compared to the control samples with KC samples, the “DESeq2” package (Love et al., 2014) in R (version 4.0.1) software was utilized to identify the differentially expressed genes (DEGs) with thresholds of |log2 fold change| > 1.5 and FDR (adjusted p-value) < 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35747602", "locator": "sections[22] \"Data Availability Statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis identified 428 intersected differentially expressed mRNAs and 68 intersected differentially expressed lncRNAs shared between the two datasets.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35747602", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We revealed that 428 intersected differentially expressed mRNA (DEGs) and 68 intersected differentially expressed lncRNA (DELs) were shared between the two datasets."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The analysis identified 428 intersected differentially expressed mRNAs and 68 intersected differentially expressed lncRNAs shared between the two datasets.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35747602"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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