ABSTRACT: The dysregulation of circular RNAs (circRNAs) has been implicated in the development and progression of papillary thyroid cancer (PTC). In this study, we analyzed the dysregulated circRNA profile using PTC tissues and matched adjacent normal tissues by RNA-seq.
Project description:Background: Non-coding circular RNAs (circRNAs) have displayed dysregulated expression in several human cancers. Here, we profiled the circRNA expression of papillary thyroid carcinoma (PTC) tumors to improve our understanding of PTC pathogenesis as well as to identify potential circRNA biomarkers for PTC.
Project description:To evaluate the expression profiles of circular RNAs (circRNAs) in papillary thyroid cancer (PTC) and to find new PTC biomarkers. Objective: The goal of this study was to characterize the expression profiles of circular RNAs (circRNAs) in papillary thyroid carcinoma (PTC), analyze their biological function, and discover new biomarkers for PTC. Methods: From June 2019 to July 2020, 68 patients admitted to Qilu Hospital and confirmed with PTC were included in this study. PTC and paired healthy tissue samples were collected and analyzed. The circRNA expression profiles of 4 pairs of samples were determined using high-throughput sequencing. Differentially expressed circRNAs were discovered to be associated with multiple related microRNAs (miRNAs) and messenger RNAs using bioinformatics analysis (mRNAs). Results: 89 upregulated and 14 downregulated circRNAs were identified in PTC tissues using high-throughput sequencing (fold change ≥ 2; p < 0.05). Among the upregulated circRNAs, we identified 14 significantly regulated circRNAs that play an important role in the pathogenesis of thyroid cancer using the network map of circRNA–miRNA–mRNA interactions. Following that, we validated the expression levels of seven candidate circRNAs (hsa_circ_0031584, hsa_circ_0082002, hsa_circ_0000660, hsa_circ_0067938, hsa_circ_0002483, hsa_circ_0003692, and hsa_circ_0006509) and discovered that among the circRNAs that we verified to be significantly differentially expressed Conclusions: The findings imply that dysregulated circRNAs may play an important role in the pathogenesis of PTC. We also discovered 14 circRNAs that were significantly upregulated and could be used to diagnose and treat PTC.
Project description:CircRNA deregulation could be a crucial event in thyroid carcinoma. To investigate circRNA signatures present in several papillary thyroid carcinoma (PTC) patients to complement our understanding of PTC pathogenesis. Using microarray technology, we screened the circRNA profiles in 3 pairs of PTC tumors and matching adjacent normal tissues. This study evaluated circRNAs expression profiles and their ability to serve as reliable biomarkers and new potential diagnostic and therapeutic targets for PTC
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of Papillary Thyroid Cancer tissue sample and adjacent normal tissue. The goals of this study are to analysis the different circRNAs expression between Cancer tissue sample and adjacent normal tissue. Quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis. We performed circRNA-seq in Papillary Thyroid Cancer tissue sample and adjacent normal tissue. We found that through the deep sequencing of four pairs PTC and adjacent nontumor tissues, we identified 16569 circRNAs, 720 circRNAs were differentials expressed, among them, 301 upregulated and 419 downregulated.
Project description:Papillary thyroid cancer (PTC) is a common endocrine tumor with rapidly increasing incidence in recent years. Although the majority of PTC are relatively indolen and have a good prognosis, it still has a certain proportion of PTC which is highly aggressive with lymphatic metastasis, iodine resistance and easy to recur. Circular RNAs as an class of noncoding RNAs are linked to a variety of tumor processes including PTC. In the current study, a circRNA deep sequencing was performed to identify alterations in circRNA expression levels of PTC tissues. CircTIAM1 was then selected as its increased expression in PTC and associated with migration, apoptosis and proliferation of PTC in vivo and in vitro. Mechanistically, circTIAM1 acted as a sponge of miR-646 and functioned in PTC through targeting mir-646 and HNRNPA1. Fluorescence in situ hybridization (FISH) and luciferase reporter assays further confirmed these connerctions. Overall, our results reveal an important oncogenic role of circTIAM1 in PTC and provide a potentially effective therapeutic strategy for PTC progression.
Project description:We profiled the gene expression of 11 anaplastic thyroid carcinomas (ATC), 49 papillary thyroid carcinomas (PTC) and 45 normal thyroids (N) We hibridized a series of anaplastic thyroid carcinomas (ATC) and papillary thyroid carcinomas (PTC) onto Affymetrix U133 Plus 2.0 arrays. ATCs were obtained from different hospitals in France and Belgium. Paired RNA samples of PTCs and non-tumoral thyroid tissues were obtained from Ukraine via the Chernobyl Tissue Bank (www.chernobyltissuebank.com). Diagnoses were confirmed by the members of the International Pathology Panel of the Chernobyl Tissue Bank.
Project description:We profiled the microRNA expression of 5 pairs of PTC and normal thyroid tissues. All the tissues were immediately snap-frozen in liquid nitrogen and confirmed as papillary thyroid carcinoma by expert pathologists. Numerous deregulated mature microRNAs were identified comparing PTC tissues versus normal thyroid tissues. Details about the clinical-pathological characteristics of the samples are also provided.
Project description:Thyroid gland is among the most sensitive organs to ionizing radiation. Whether low-dose radiation-induced papillary thyroid cancer (PTC) differs from sporadic PTC is yet unknown. We used microarrays to identify gene signature of radiation-induced papillary thyroid carcinomas
Project description:Papillary thyroid carcinoma (PTC), the most common form of thyroid carcinomas, is a well-differentiated tumor and accounts for about 80% of all thyroid carcinomas. With the advantage of providing comprehensively analysis of global proteins in samples, proteomics techniques are increasingly applied in the field of identifying novel biomarkers in thyroid cancer. In this study, we conducted a TMT labeling-based quantitative proteomics analysis and bioinformatics analysis to compare the alternation of global proteins in tumor tissues and para-tumor tissues between PTC with LNM and without LNM.