Exploration of DNA Methylation-Driven Genes in Papillary Thyroid Carcinoma Based on the Cancer Genome Atlas

2021 ◽  
Vol 28 (1) ◽  
pp. 99-114
Author(s):  
Yanwei Chen ◽  
Keke Wang ◽  
Mengyuan Shang ◽  
Shuangshuang Zhao ◽  
Zheng Zhang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Papillary Thyroid ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals lncRNA-miRNA-mRNA ceRNA Network in Thyroid Carcinoma from The Cancer Genome Atlas

2020 ◽  
Author(s):  
Guoheng Mo ◽  
Qunguang Jiang ◽  
Zixuan Wang ◽  
Zhaoting Zheng ◽  
XiaoSi Chen
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Molecular Mechanisms ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Papillary Thyroid ◽  
Cerna Network ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Abstract Increasing evidence indicates that the competitive endogenous RNA (ceRNA) hypothesis, that is, long non-coding RNA (LncRNA) can competitively bind microRNA (miRNA) through miRNA response elements to affect the expression of target RNA, and dysregulation of LncRNA expression plays a key role in tumor progression. The papillary thyroid carcinoma that we studied is the most significant pathological type of thyroid cancer, but its ceRNA network has not been extensively evaluated. We analyzed level-3 data from RNA-Seq of 58 para-carcinoma tissues and 501 patients with primary papillary thyroid carcinoma (PTC) using the DEseq software package and downloaded clinical information from The Cancer Genome Atlas (TCGA) to find potential biomarkers or therapeutic targets. As a result, 149 differential miRNAs were selected, including 117 up -regulated, 32 down-regulated, and 3099 differential mRNAs, including 1976 up-regulated, 1123 down-regulated, and 434 differential lncRNAs, including 331 up-regulated and 103 down-regulated (Fold Change > 2, P < 0.05). The interactions between these differentially expressed RNA groups constitute the ceRNA network of PTC. Moreover, we used the microde database to predict the miRNAs that may be acted by the above screened differential lncRNAs and intersected with the selected miRNAs, and further predicted the target genes of the intersecting miRNAs by TargetScan, miRTarBase and miRDB, and intersected with the selected mRNAs. From the constructed ceRNA network we can see that Linc00460 may cause the invasion and metastasis of PTC by competitively inhibiting hsa-mir-150 and upregulating the expression of its downstream target gene EREG. Our study identified a series of lncRNAs associated with PTC progression and prognosis, and this complex ceRNA interaction network provides guidance for better understanding of the molecular mechanisms of PTC and can be used as an effective diagnostic tool for PTC invasion, metastasis and prognosis. Kaplan-Meier analysis of the differentially expressed RNAs associated with PTC pathogenesis confirmed that the lncRNAs AC097717.1, C20orf203, EMX2OS were potentially associated with the prognosis of PTC (P<0.05).

scholarly journals FXR silencing in human colon cancer by DNA methylation and KRAS signaling

2014 ◽  
Vol 306 (1) ◽  
pp. G48-G58 ◽  
Author(s):  
Ann M. Bailey ◽  
Le Zhan ◽  
Dipen Maru ◽  
Imad Shureiqi ◽  
Curtis R. Pickering ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Colon Cancer ◽  
Epithelial To Mesenchymal Transition ◽  
Human Colon ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Human Colon Cancer ◽  
Mesenchymal Transition ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Farnesoid X receptor (FXR) is a bile acid nuclear receptor described through mouse knockout studies as a tumor suppressor for the development of colon adenocarcinomas. This study investigates the regulation of FXR in the development of human colon cancer. We used immunohistochemistry of FXR in normal tissue ( n = 238), polyps ( n = 32), and adenocarcinomas, staged I–IV ( n = 43, 39, 68, and 9), of the colon; RT-quantitative PCR, reverse-phase protein array, and Western blot analysis in 15 colon cancer cell lines; NR1H4 promoter methylation and mRNA expression in colon cancer samples from The Cancer Genome Atlas; DNA methyltransferase inhibition; methyl-DNA immunoprecipitation (MeDIP); bisulfite sequencing; and V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) knockdown assessment to investigate FXR regulation in colon cancer development. Immunohistochemistry and quantitative RT-PCR revealed that expression and function of FXR was reduced in precancerous lesions and silenced in a majority of stage I-IV tumors. FXR expression negatively correlated with phosphatidylinositol-4, 5-bisphosphate 3 kinase signaling and the epithelial-to-mesenchymal transition. The NR1H4 promoter is methylated in ∼12% colon cancer The Cancer Genome Atlas samples, and methylation patterns segregate with tumor subtypes. Inhibition of DNA methylation and KRAS silencing both increased FXR expression. FXR expression is decreased early in human colon cancer progression, and both DNA methylation and KRAS signaling may be contributing factors to FXR silencing. FXR potentially suppresses epithelial-to-mesenchymal transition and other oncogenic signaling cascades, and restoration of FXR activity, by blocking silencing mechanisms or increasing residual FXR activity, represents promising therapeutic options for the treatment of colon cancer.

scholarly journals DNA Methylation–Based Classifier for Accurate Molecular Diagnosis of Bone Sarcomas

2017 ◽  
pp. 1-11 ◽  
Author(s):  
S. Peter Wu ◽  
Benjamin T. Cooper ◽  
Fang Bu ◽  
Christopher J. Bowman ◽  
J. Keith Killian ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Synovial Sarcoma ◽  
Ewing Sarcoma ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Clinical Samples ◽  
Cpg Sites ◽  
A Genome ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Purpose Pediatric sarcomas provide a unique diagnostic challenge. There is considerable morphologic overlap between entities, increasing the importance of molecular studies in the diagnosis, treatment, and identification of therapeutic targets. We developed and validated a genome-wide DNA methylation–based classifier to differentiate between osteosarcoma, Ewing sarcoma, and synovial sarcoma. Methods DNA methylation status of 482,421 CpG sites in 10 Ewing sarcoma, 11 synovial sarcoma, and 15 osteosarcoma samples were determined using the Illumina Infinium HumanMethylation450 array. We developed a random forest classifier trained from the 400 most differentially methylated CpG sites within the training set of 36 sarcoma samples. This classifier was validated on data drawn from The Cancer Genome Atlas synovial sarcoma, TARGET-Osteosarcoma, and a recently published series of Ewing sarcoma. Results Methylation profiling revealed three distinct patterns, each enriched with a single sarcoma subtype. Within the validation cohorts, all samples from The Cancer Genome Atlas were accurately classified as synovial sarcoma (10 of 10; sensitivity and specificity, 100%), all but one sample from TARGET-Osteosarcoma were classified as osteosarcoma (85 of 86; sensitivity, 98%; specificity, 100%), and 14 of 15 Ewing sarcoma samples were classified correctly (sensitivity, 93%; specificity, 100%). The single misclassified osteosarcoma sample demonstrated high EWSR1 and ETV1 expression on RNA sequencing, although no fusion was found on manual curation of the transcript sequence. Two additional clinical samples that were difficult to classify by morphology and molecular methods were classified as osteosarcoma; one had been suspected of being a synovial sarcoma and the other of being Ewing sarcoma on initial diagnosis. Conclusion Osteosarcoma, synovial sarcoma, and Ewing sarcoma have distinct epigenetic profiles. Our validated methylation-based classifier can be used to provide diagnostic assistance when histologic and standard techniques are inconclusive.

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