scholarly journals Characterization of TERT and BRAF copy number variation in papillary thyroid carcinoma: An analysis of the cancer genome atlas study

2020 ◽  
Author(s):  
Brittany A. McKelvey ◽  
Martha A. Zeiger ◽  
Christopher B. Umbricht
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Copy Number Variation ◽  
Copy Number ◽  
The Cancer Genome Atlas ◽  
Papillary Thyroid ◽  
Number Variation ◽  
Cancer Genome Atlas ◽  
Genome Atlas

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 Inferring Homologous Recombination Deficiency of Ovarian Cancer From the Landscape of Copy Number Variation at Subchromosomal and Genetic Resolutions

2021 ◽  
Vol 11 ◽  
Author(s):  
Meng Zhang ◽  
Si-Cong Ma ◽  
Jia-Le Tan ◽  
Jian Wang ◽  
Xue Bai ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Homologous Recombination ◽  
Copy Number Variation ◽  
Copy Number ◽  
The Cancer Genome Atlas ◽  
Homologous Recombination Deficiency ◽  
Number Variation ◽  
Cancer Genome Atlas ◽  
Tumor Types ◽  
Pan Cancer

BackgroundHomologous recombination deficiency (HRD) is characterized by overall genomic instability and has emerged as an indispensable therapeutic target across various tumor types, particularly in ovarian cancer (OV). Unfortunately, current detection assays are far from perfect for identifying every HRD patient. The purpose of this study was to infer HRD from the landscape of copy number variation (CNV).MethodsGenome-wide CNV landscape was measured in OV patients from the Australian Ovarian Cancer Study (AOCS) clinical cohort and &gt;10,000 patients across 33 tumor types from The Cancer Genome Atlas (TCGA). HRD-predictive CNVs at subchromosomal resolution were identified through exploratory analysis depicting the CNV landscape of HRD versus non-HRD OV patients and independently validated using TCGA and AOCS cohorts. Gene-level CNVs were further analyzed to explore their potential predictive significance for HRD across tumor types at genetic resolution.ResultsAt subchromosomal resolution, 8q24.2 amplification and 5q13.2 deletion were predominantly witnessed in HRD patients (both p &lt; 0.0001), whereas 19q12 amplification occurred mainly in non-HRD patients (p &lt; 0.0001), compared with their corresponding counterparts within TCGA-OV. The predictive significance of 8q24.2 amplification (p &lt; 0.0001), 5q13.2 deletion (p = 0.0056), and 19q12 amplification (p = 0.0034) was externally validated within AOCS. Remarkably, pan-cancer analysis confirmed a cross-tumor predictive role of 8q24.2 amplification for HRD (p &lt; 0.0001). Further analysis of CNV in 8q24.2 at genetic resolution revealed that amplifications of the oncogenes, MYC (p = 0.0001) and NDRG1 (p = 0.0004), located on this fragment were also associated with HRD in a pan-cancer manner.ConclusionsThe CNV landscape serves as a generalized predictor of HRD in cancer patients not limited to OV. The detection of CNV at subchromosomal or genetic resolution could aid in the personalized treatment of HRD patients.

Analysis of TGCA data reveals genetic and epigenetic changes and biological function of MUC family genes in colorectal cancer

2019 ◽  
Vol 15 (35) ◽  
pp. 4031-4043 ◽  
Author(s):  
Zhipeng Jiang ◽  
Huashe Wang ◽  
Liang Li ◽  
Zehui Hou ◽  
Wei Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Copy Number Variation ◽  
Copy Number ◽  
Regulatory Networks ◽  
The Cancer Genome Atlas ◽  
Epigenetic Changes ◽  
Copy Number Variation Analysis ◽  
Number Variation ◽  
Cancer Genome Atlas ◽  
Drug Influence

Aim: Few studies focused on functions and regulatory networks of MUC family members in colorectal cancer based on comprehensive analysis of online database. Materials & methods: Copy number variation, methylation, pathway analysis and drug influence on MUC expression were analyzed based on The Cancer Genome Atlas and GTEx database. Results: Copy number variation analysis showed MUC heterozygous amplification and heterozygous deletion predominate. Methylation of MUC17, MUC12 and MUC4 were found related to gene expression. Function of MUC family genes mainly affects pathways such as apoptosis, cell cycle, DNA damage and EMT pathways. PLX4720, dabrafenib, gefitinib, afatinib and austocystin D can alter the expression of MUC gene. Conclusion: The genetic and epigenetic changes of MUC are related to the level of MUC expression in colorectal cancer.

scholarly journals Papillary Thyroid Carcinoma Variants are Characterized by Co-dysregulation of Immune and Cancer Associated Genes

Cancers ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1179 ◽  
Author(s):  
Jaideep Chakladar ◽  
Wei Tse Li ◽  
Michael Bouvet ◽  
Eric Y. Chang ◽  
Jessica Wang-Rodriguez ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Family Members ◽  
The Cancer Genome Atlas ◽  
Papillary Thyroid ◽  
Sequencing Data ◽  
Clinical Variables ◽  
Cancer Genome Atlas ◽  
Cell Variant ◽  
Immune Related Genes

Papillary thyroid carcinoma (PTC) variants exhibit different prognosis, but critical characteristics of PTC variants that contribute to differences in pathogenesis are not well-known. This study aims to characterize dysregulated immune-associated and cancer-associated genes in three PTC subtypes to explore how the interplay between cancer and immune processes causes differential prognosis. RNA-sequencing data from The Cancer Genome Atlas (TCGA) were used to identify dysregulated genes in each variant. The dysregulation profiles of the subtypes were compared using functional pathways clustering and correlations to relevant clinical variables, genomic alterations, and microRNA regulation. We discovered that the dysregulation profiles of classical PTC (CPTC) and the tall cell variant (TCPTC) are similar and are distinct from that of the follicular variant (FVPTC). However, unique cancer or immune-associated genes are associated with clinical variables for each subtype. Cancer-related genes MUC1, FN1, and S100-family members were the most clinically relevant in CPTC, while APLN and IL16, both immune-related, were clinically relevant in FVPTC. RAET-family members, also immune-related, were clinically relevant in TCPTC. Collectively, our data suggest that dysregulation of both cancer and immune associated genes defines the gene expression landscapes of PTC variants, but different cancer or immune related genes may drive the phenotype of each variant.

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