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Identification of Long Non-Coding RNA Expression Profiles and Co-Expression Genes in Thyroid Carcinoma Based on The Cancer Genome Atlas (TCGA) Database.Med Sci Monit. 2019 Dec 19; 25:9752-9769.MS
Abstract
BACKGROUND
Thyroid carcinoma is a malignancy with high morbidity and mortality. Genetic alterations play pivot roles in the pathogenesis of thyroid carcinoma, where long noncoding RNA (lncRNA) have been identified to be crucial. This study sought to investigate the biological functions of lncRNA expression profiles in thyroid carcinoma. MATERIAL ANDMETHODS
The lncRNAs expression profiles were acquired from The Cancer Genome Atlas (TCGA) database according to 510 thyroid cancer tissues and 58 normal thyroid tissues. By using R package edgeR, differentially expressed RNAs were obtained. Also, an overall survival model was established based on Cox regression and clinical data then testified by Kaplan-Meier plot, receiver operating characteristic (ROC)-curve and C-index analysis. We investigated the co-expressed genes with lncRNAs involved in the prognostic model, as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted R package clusterProfile.RESULTS
A total of 352 lncRNAs were identified as differentially expressed in thyroid carcinoma, and an overall survival model consisting of 8 signature lncRNAs was proposed (ROC=0.862, C-index=0.893, P<0.05), 3 of which (DOCK9-DT, FAM111A-DT, and LINC01736) represent co-expressed mRNAs. However, as an oncogene, only FAM111A-DT increased the prognostic risk in thyroid carcinoma. Furthermore, we found differential genes LINC01016, LHX1-DT, IGF2-AS, ND MIR1-1HG-AS1, significantly related to lymph node metastasis (P<0.05).CONCLUSIONS
In this study, we clarified the differential lncRNA expression profiles which were related to the tumorigenesis and prognosis in thyroid carcinoma. Our results provide new rationale and understandings to the pathogenesis and regulatory mechanisms of thyroid carcinoma.Links
MeSH
Databases, GeneticGene ExpressionGene Expression ProfilingGene Expression Regulation, NeoplasticGene OntologyGene Regulatory NetworksHumansKaplan-Meier EstimateMicroRNAsPrognosisProportional Hazards ModelsRNA, Long NoncodingRNA, MessengerROC CurveReceptors, VirusSurvival AnalysisThyroid NeoplasmsTranscriptome
Pub Type(s)
Journal Article
Language
eng
PubMed ID
31856144
Citation
Zhang, Yun, et al. "Identification of Long Non-Coding RNA Expression Profiles and Co-Expression Genes in Thyroid Carcinoma Based On the Cancer Genome Atlas (TCGA) Database." Medical Science Monitor : International Medical Journal of Experimental and Clinical Research, vol. 25, 2019, pp. 9752-9769.
Zhang Y, Jin T, Shen H, et al. Identification of Long Non-Coding RNA Expression Profiles and Co-Expression Genes in Thyroid Carcinoma Based on The Cancer Genome Atlas (TCGA) Database. Med Sci Monit. 2019;25:9752-9769.
Zhang, Y., Jin, T., Shen, H., Yan, J., Guan, M., & Jin, X. (2019). Identification of Long Non-Coding RNA Expression Profiles and Co-Expression Genes in Thyroid Carcinoma Based on The Cancer Genome Atlas (TCGA) Database. Medical Science Monitor : International Medical Journal of Experimental and Clinical Research, 25, 9752-9769. https://doi.org/10.12659/MSM.917845
Zhang Y, et al. Identification of Long Non-Coding RNA Expression Profiles and Co-Expression Genes in Thyroid Carcinoma Based On the Cancer Genome Atlas (TCGA) Database. Med Sci Monit. 2019 Dec 19;25:9752-9769. PubMed PMID: 31856144.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR
T1 - Identification of Long Non-Coding RNA Expression Profiles and Co-Expression Genes in Thyroid Carcinoma Based on The Cancer Genome Atlas (TCGA) Database.
AU - Zhang,Yun,
AU - Jin,Taobo,
AU - Shen,Haipeng,
AU - Yan,Junfeng,
AU - Guan,Ming,
AU - Jin,Xin,
Y1 - 2019/12/19/
PY - 2019/12/20/entrez
PY - 2019/12/20/pubmed
PY - 2020/6/27/medline
SP - 9752
EP - 9769
JF - Medical science monitor : international medical journal of experimental and clinical research
JO - Med. Sci. Monit.
VL - 25
N2 - BACKGROUND Thyroid carcinoma is a malignancy with high morbidity and mortality. Genetic alterations play pivot roles in the pathogenesis of thyroid carcinoma, where long noncoding RNA (lncRNA) have been identified to be crucial. This study sought to investigate the biological functions of lncRNA expression profiles in thyroid carcinoma. MATERIAL AND METHODS The lncRNAs expression profiles were acquired from The Cancer Genome Atlas (TCGA) database according to 510 thyroid cancer tissues and 58 normal thyroid tissues. By using R package edgeR, differentially expressed RNAs were obtained. Also, an overall survival model was established based on Cox regression and clinical data then testified by Kaplan-Meier plot, receiver operating characteristic (ROC)-curve and C-index analysis. We investigated the co-expressed genes with lncRNAs involved in the prognostic model, as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted R package clusterProfile. RESULTS A total of 352 lncRNAs were identified as differentially expressed in thyroid carcinoma, and an overall survival model consisting of 8 signature lncRNAs was proposed (ROC=0.862, C-index=0.893, P<0.05), 3 of which (DOCK9-DT, FAM111A-DT, and LINC01736) represent co-expressed mRNAs. However, as an oncogene, only FAM111A-DT increased the prognostic risk in thyroid carcinoma. Furthermore, we found differential genes LINC01016, LHX1-DT, IGF2-AS, ND MIR1-1HG-AS1, significantly related to lymph node metastasis (P<0.05). CONCLUSIONS In this study, we clarified the differential lncRNA expression profiles which were related to the tumorigenesis and prognosis in thyroid carcinoma. Our results provide new rationale and understandings to the pathogenesis and regulatory mechanisms of thyroid carcinoma.
SN - 1643-3750
UR - https://www.unboundmedicine.com/medline/citation/31856144/Identification_of_Long_Non_Coding_RNA_Expression_Profiles_and_Co_Expression_Genes_in_Thyroid_Carcinoma_Based_on_The_Cancer_Genome_Atlas__TCGA__Database_
L2 - https://www.medscimonit.com/download/index/idArt/917845
DB - PRIME
DP - Unbound Medicine
ER -