Survival-based bioinformatics analysis to identify hub long non-coding RNAs along with lncRNA-miRNA-mRNA network for potential diagnosis/prognosis of thyroid cancer

Thyroid cancer (TC) is the most common endocrine cancer, accounting for 1.7% of all cancer cases. It has been reported that the existing approach to diagnosing TC is problematic. Therefore, it is essential to develop molecular biomarkers to improve the accuracy of the diagnosis. This study aimed to...

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Published inJournal of cell communication and signaling Vol. 17; no. 3; pp. 639 - 655
Main Authors Morovat, Pejman, Morovat, Saman, Hosseinpour, Milad, Moslabeh, Forough Ghasem Zadeh, Kamali, Mohammad Javad, Samadani, Ali Akbar
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.09.2023
John Wiley & Sons, Inc
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Online AccessGet full text
ISSN1873-9601
1873-961X
DOI10.1007/s12079-022-00697-9

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Abstract Thyroid cancer (TC) is the most common endocrine cancer, accounting for 1.7% of all cancer cases. It has been reported that the existing approach to diagnosing TC is problematic. Therefore, it is essential to develop molecular biomarkers to improve the accuracy of the diagnosis. This study aimed to screen hub lncRNAs in the ceRNA network (ceRNET) connected to TC formation and progression based on the overall survival rate. In this study, first, RNA-seq data from the GDC database were collected. A package called edgeR in R programming language was then used to obtain differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) in TC patients' samples compared to normal samples. Second, DEmRNAs were analyzed for their functional enrichment. Third, to identify RNAs associated with overall survival, the overall survival of these RNAs was analyzed using the Kaplan-Meier plotter database to create a survival associated with the ceRNA network (survival-related ceRNET). Next, the GeneMANIA plugin was used to construct a PPI network to better understand survival-related DEmRNA interactions. The survival ceRNET was then visualized with the Cytoscape software, and hub genes, including hub lncRNAs and hub mRNAs, were identified using the CytoHubba plugin. We found 45 DElncRNAs, 28 DEmiRNAs, and 723 DEmRNAs among thyroid tumor tissue and non-tumor tissue samples. According to KEGG, GO and DO analyses, 723 DEmRNAs were mainly enriched in cancer-related pathways. Importantly, the results found that ten DElncRNAs, four DEmiRNAs, and 68 DEmRNAs are associated with overall survival. In this account, the PPI network was constructed for 68 survival-related DEmRNAs, and ADAMTS9, DTX4, and CLDN10 were identified as hub genes. The ceRNET was created by combining six lncRNAs, 109 miRNAs, and 22 mRNAs related to survival using Cytoscape. in this network, ten hub RNAs were identified by the CytoHubba plugin, including mRNAs (CTXND1, XKRX, IGFBP2, ENTPD1, GALNT7, ADAMTS9) and lncRNAs (AC090673.1, AL162511.1, LINC02454, AL365259.1). This study suggests that three lncRNAs, including AL162511.1, AC090673.1, and AL365259.1, could be reliable diagnostic biomarkers for TC. The findings of this study provide a basis for future studies on the therapeutic potential of these lncRNAs. Graphical abstract
AbstractList Thyroid cancer (TC) is the most common endocrine cancer, accounting for 1.7% of all cancer cases. It has been reported that the existing approach to diagnosing TC is problematic. Therefore, it is essential to develop molecular biomarkers to improve the accuracy of the diagnosis. This study aimed to screen hub lncRNAs in the ceRNA network (ceRNET) connected to TC formation and progression based on the overall survival rate. In this study, first, RNA-seq data from the GDC database were collected. A package called edgeR in R programming language was then used to obtain differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) in TC patients' samples compared to normal samples. Second, DEmRNAs were analyzed for their functional enrichment. Third, to identify RNAs associated with overall survival, the overall survival of these RNAs was analyzed using the Kaplan-Meier plotter database to create a survival associated with the ceRNA network (survival-related ceRNET). Next, the GeneMANIA plugin was used to construct a PPI network to better understand survival-related DEmRNA interactions. The survival ceRNET was then visualized with the Cytoscape software, and hub genes, including hub lncRNAs and hub mRNAs, were identified using the CytoHubba plugin. We found 45 DElncRNAs, 28 DEmiRNAs, and 723 DEmRNAs among thyroid tumor tissue and non-tumor tissue samples. According to KEGG, GO and DO analyses, 723 DEmRNAs were mainly enriched in cancer-related pathways. Importantly, the results found that ten DElncRNAs, four DEmiRNAs, and 68 DEmRNAs are associated with overall survival. In this account, the PPI network was constructed for 68 survival-related DEmRNAs, and ADAMTS9, DTX4, and CLDN10 were identified as hub genes. The ceRNET was created by combining six lncRNAs, 109 miRNAs, and 22 mRNAs related to survival using Cytoscape. in this network, ten hub RNAs were identified by the CytoHubba plugin, including mRNAs (CTXND1, XKRX, IGFBP2, ENTPD1, GALNT7, ADAMTS9) and lncRNAs (AC090673.1, AL162511.1, LINC02454, AL365259.1). This study suggests that three lncRNAs, including AL162511.1, AC090673.1, and AL365259.1, could be reliable diagnostic biomarkers for TC. The findings of this study provide a basis for future studies on the therapeutic potential of these lncRNAs.
Thyroid cancer (TC) is the most common endocrine cancer, accounting for 1.7% of all cancer cases. It has been reported that the existing approach to diagnosing TC is problematic. Therefore, it is essential to develop molecular biomarkers to improve the accuracy of the diagnosis. This study aimed to screen hub lncRNAs in the ceRNA network (ceRNET) connected to TC formation and progression based on the overall survival rate. In this study, first, RNA-seq data from the GDC database were collected. A package called edgeR in R programming language was then used to obtain differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) in TC patients' samples compared to normal samples. Second, DEmRNAs were analyzed for their functional enrichment. Third, to identify RNAs associated with overall survival, the overall survival of these RNAs was analyzed using the Kaplan-Meier plotter database to create a survival associated with the ceRNA network (survival-related ceRNET). Next, the GeneMANIA plugin was used to construct a PPI network to better understand survival-related DEmRNA interactions. The survival ceRNET was then visualized with the Cytoscape software, and hub genes, including hub lncRNAs and hub mRNAs, were identified using the CytoHubba plugin. We found 45 DElncRNAs, 28 DEmiRNAs, and 723 DEmRNAs among thyroid tumor tissue and non-tumor tissue samples. According to KEGG, GO and DO analyses, 723 DEmRNAs were mainly enriched in cancer-related pathways. Importantly, the results found that ten DElncRNAs, four DEmiRNAs, and 68 DEmRNAs are associated with overall survival. In this account, the PPI network was constructed for 68 survival-related DEmRNAs, and ADAMTS9, DTX4, and CLDN10 were identified as hub genes. The ceRNET was created by combining six lncRNAs, 109 miRNAs, and 22 mRNAs related to survival using Cytoscape. in this network, ten hub RNAs were identified by the CytoHubba plugin, including mRNAs (CTXND1, XKRX, IGFBP2, ENTPD1, GALNT7, ADAMTS9) and lncRNAs (AC090673.1, AL162511.1, LINC02454, AL365259.1). This study suggests that three lncRNAs, including AL162511.1, AC090673.1, and AL365259.1, could be reliable diagnostic biomarkers for TC. The findings of this study provide a basis for future studies on the therapeutic potential of these lncRNAs.Thyroid cancer (TC) is the most common endocrine cancer, accounting for 1.7% of all cancer cases. It has been reported that the existing approach to diagnosing TC is problematic. Therefore, it is essential to develop molecular biomarkers to improve the accuracy of the diagnosis. This study aimed to screen hub lncRNAs in the ceRNA network (ceRNET) connected to TC formation and progression based on the overall survival rate. In this study, first, RNA-seq data from the GDC database were collected. A package called edgeR in R programming language was then used to obtain differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) in TC patients' samples compared to normal samples. Second, DEmRNAs were analyzed for their functional enrichment. Third, to identify RNAs associated with overall survival, the overall survival of these RNAs was analyzed using the Kaplan-Meier plotter database to create a survival associated with the ceRNA network (survival-related ceRNET). Next, the GeneMANIA plugin was used to construct a PPI network to better understand survival-related DEmRNA interactions. The survival ceRNET was then visualized with the Cytoscape software, and hub genes, including hub lncRNAs and hub mRNAs, were identified using the CytoHubba plugin. We found 45 DElncRNAs, 28 DEmiRNAs, and 723 DEmRNAs among thyroid tumor tissue and non-tumor tissue samples. According to KEGG, GO and DO analyses, 723 DEmRNAs were mainly enriched in cancer-related pathways. Importantly, the results found that ten DElncRNAs, four DEmiRNAs, and 68 DEmRNAs are associated with overall survival. In this account, the PPI network was constructed for 68 survival-related DEmRNAs, and ADAMTS9, DTX4, and CLDN10 were identified as hub genes. The ceRNET was created by combining six lncRNAs, 109 miRNAs, and 22 mRNAs related to survival using Cytoscape. in this network, ten hub RNAs were identified by the CytoHubba plugin, including mRNAs (CTXND1, XKRX, IGFBP2, ENTPD1, GALNT7, ADAMTS9) and lncRNAs (AC090673.1, AL162511.1, LINC02454, AL365259.1). This study suggests that three lncRNAs, including AL162511.1, AC090673.1, and AL365259.1, could be reliable diagnostic biomarkers for TC. The findings of this study provide a basis for future studies on the therapeutic potential of these lncRNAs.
Thyroid cancer (TC) is the most common endocrine cancer, accounting for 1.7% of all cancer cases. It has been reported that the existing approach to diagnosing TC is problematic. Therefore, it is essential to develop molecular biomarkers to improve the accuracy of the diagnosis. This study aimed to screen hub lncRNAs in the ceRNA network (ceRNET) connected to TC formation and progression based on the overall survival rate. In this study, first, RNA‐seq data from the GDC database were collected. A package called edgeR in R programming language was then used to obtain differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) in TC patients' samples compared to normal samples. Second, DEmRNAs were analyzed for their functional enrichment. Third, to identify RNAs associated with overall survival, the overall survival of these RNAs was analyzed using the Kaplan‐Meier plotter database to create a survival associated with the ceRNA network (survival‐related ceRNET). Next, the GeneMANIA plugin was used to construct a PPI network to better understand survival‐related DEmRNA interactions. The survival ceRNET was then visualized with the Cytoscape software, and hub genes, including hub lncRNAs and hub mRNAs, were identified using the CytoHubba plugin. We found 45 DElncRNAs, 28 DEmiRNAs, and 723 DEmRNAs among thyroid tumor tissue and non‐tumor tissue samples. According to KEGG, GO and DO analyses, 723 DEmRNAs were mainly enriched in cancer‐related pathways. Importantly, the results found that ten DElncRNAs, four DEmiRNAs, and 68 DEmRNAs are associated with overall survival. In this account, the PPI network was constructed for 68 survival‐related DEmRNAs, and ADAMTS9, DTX4, and CLDN10 were identified as hub genes. The ceRNET was created by combining six lncRNAs, 109 miRNAs, and 22 mRNAs related to survival using Cytoscape. in this network, ten hub RNAs were identified by the CytoHubba plugin, including mRNAs (CTXND1, XKRX, IGFBP2, ENTPD1, GALNT7, ADAMTS9) and lncRNAs (AC090673.1, AL162511.1, LINC02454, AL365259.1). This study suggests that three lncRNAs, including AL162511.1, AC090673.1, and AL365259.1, could be reliable diagnostic biomarkers for TC. The findings of this study provide a basis for future studies on the therapeutic potential of these lncRNAs. Graphical
Thyroid cancer (TC) is the most common endocrine cancer, accounting for 1.7% of all cancer cases. It has been reported that the existing approach to diagnosing TC is problematic. Therefore, it is essential to develop molecular biomarkers to improve the accuracy of the diagnosis. This study aimed to screen hub lncRNAs in the ceRNA network (ceRNET) connected to TC formation and progression based on the overall survival rate. In this study, first, RNA-seq data from the GDC database were collected. A package called edgeR in R programming language was then used to obtain differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) in TC patients' samples compared to normal samples. Second, DEmRNAs were analyzed for their functional enrichment. Third, to identify RNAs associated with overall survival, the overall survival of these RNAs was analyzed using the Kaplan-Meier plotter database to create a survival associated with the ceRNA network (survival-related ceRNET). Next, the GeneMANIA plugin was used to construct a PPI network to better understand survival-related DEmRNA interactions. The survival ceRNET was then visualized with the Cytoscape software, and hub genes, including hub lncRNAs and hub mRNAs, were identified using the CytoHubba plugin. We found 45 DElncRNAs, 28 DEmiRNAs, and 723 DEmRNAs among thyroid tumor tissue and non-tumor tissue samples. According to KEGG, GO and DO analyses, 723 DEmRNAs were mainly enriched in cancer-related pathways. Importantly, the results found that ten DElncRNAs, four DEmiRNAs, and 68 DEmRNAs are associated with overall survival. In this account, the PPI network was constructed for 68 survival-related DEmRNAs, and ADAMTS9, DTX4, and CLDN10 were identified as hub genes. The ceRNET was created by combining six lncRNAs, 109 miRNAs, and 22 mRNAs related to survival using Cytoscape. in this network, ten hub RNAs were identified by the CytoHubba plugin, including mRNAs (CTXND1, XKRX, IGFBP2, ENTPD1, GALNT7, ADAMTS9) and lncRNAs (AC090673.1, AL162511.1, LINC02454, AL365259.1). This study suggests that three lncRNAs, including AL162511.1, AC090673.1, and AL365259.1, could be reliable diagnostic biomarkers for TC. The findings of this study provide a basis for future studies on the therapeutic potential of these lncRNAs. Graphical abstract
Author Hosseinpour, Milad
Morovat, Saman
Moslabeh, Forough Ghasem Zadeh
Samadani, Ali Akbar
Morovat, Pejman
Kamali, Mohammad Javad
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Keywords Bioinformatics analysis
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Thyroid cancer
ceRNA network (ceRNET)
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PublicationCentury 2000
PublicationDate September 2023
PublicationDateYYYYMMDD 2023-09-01
PublicationDate_xml – month: 09
  year: 2023
  text: September 2023
PublicationDecade 2020
PublicationPlace Dordrecht
PublicationPlace_xml – name: Dordrecht
– name: Netherlands
PublicationTitle Journal of cell communication and signaling
PublicationTitleAbbrev J. Cell Commun. Signal
PublicationTitleAlternate J Cell Commun Signal
PublicationYear 2023
Publisher Springer Netherlands
John Wiley & Sons, Inc
Publisher_xml – name: Springer Netherlands
– name: John Wiley & Sons, Inc
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Snippet Thyroid cancer (TC) is the most common endocrine cancer, accounting for 1.7% of all cancer cases. It has been reported that the existing approach to diagnosing...
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SubjectTerms Bioinformatics
Bioinformatics analysis
Biomarkers
Biomedical and Life Sciences
Biomedicine
Cell Biology
ceRNA network (ceRNET)
Diagnosis
Hub genes
Insulin-like growth factor-binding protein 2
Life Sciences
LncRNA
Medical prognosis
MicroRNAs
miRNA
mRNA
Non-coding RNA
Research Article
Survival
Thyroid cancer
Tumors
Title Survival-based bioinformatics analysis to identify hub long non-coding RNAs along with lncRNA-miRNA-mRNA network for potential diagnosis/prognosis of thyroid cancer
URI https://link.springer.com/article/10.1007/s12079-022-00697-9
https://onlinelibrary.wiley.com/doi/abs/10.1007%2Fs12079-022-00697-9
https://www.ncbi.nlm.nih.gov/pubmed/36149574
https://www.proquest.com/docview/2847853588
https://www.proquest.com/docview/2717693266
https://pubmed.ncbi.nlm.nih.gov/PMC10409689
Volume 17
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