lncRNAs In Thyroid Cancer Research Articles

Identification of non-coding RNA related prognosis biomarkers based on ceRNA network in thyroid cancer.

Introduction: Thyroid cancer (THCA) has become a serious malignant tumor worldwide. Identification of non-coding RNA related regulators is very necessary to improve the knowledge of THCA treatment. The aim of this study was to identify novel therapeutic targets and prognosis biomarkers for predicting pathological characteristics and subsequently treating THCA. Methods: We investigated the alterations of miRNAs, mRNAs and lncRNAs in THCA. Functional enrichment and clustering analysis were conducted for these aberrantly expressed RNAs. Multiple interaction networks among miRNAs, mRNAs and lncRNAs were constructed and the functional modules associated with THCA patients' prognosis were identified. Furthermore, we evaluated the prognostic roles of the important miRNAs, mRNAs and lncRNAs in THCA and investigated the regulatory potential of non-coding RNAs on immune cell infiltration. Results: We firstly identified that miR-4709-3p and miR-146b-3p could significantly classify patients into high/low risk groups, which may be potential prognosis biomarkers of THCA. Secondly, we constructed a THCA-related miRNA-mRNA network, which displayed small world network topological characters. Two THCA-related functional modules were identified from the miRNA-mRNA network by MCODE. Results showed that two modules could implicate in known cancer pathways, such as apoptosis and focal adhesion. Thirdly, a THCA-related miRNA-lncRNA network was constructed. A subnetwork of miRNA-lncRNA network showed strong prognosis effect in THCA. Fourthly, we constructed a THCA-related mRNA-lncRNA network and detected several typical lncRNA-miRNA-mRNA crosstalk, such as AC068138, BCL2, miR-21 and miR-146b, which had good prognosis effect in THCA. Immune infiltration results showed that lncRNAs LA16c-329F2, RP11-395N3, RP11-423H2, RP11-399B17 and RP11-1036E20 were high related to neutrophil and dendritic cell infiltration. Discussion: Non-coding RNA-mediated gene regulatory network has the strong regulatory potential in pathological processes of THCA. All these results could help us uncover the non-coding RNA-mediated regulatory mechanism in THCA.

Construction and Validation of an Immune-Related lncRNA Prognosis Model for Thyroid Cancer.

Immune-related long noncoding RNAs (lncRNAs) play an important role in the development of cancer. This study aimed to identify immune-related lncRNAs in thyroid cancer (THCA) and develop a prognostic model for THCA. We downloaded immune-related gene sets from the Gene Set Enrichment Analysis (GSEA) website and obtained THCA gene expression and clinical data from The Cancer Genome Atlas (TCGA) database. Immune-related lncRNAs were then obtained by performing correlation analysis on the expression of lncRNAs and immune-related genes. A prognostic model for THCA immune-related lncRNAs was developed through univariate Cox regression and multiple Cox regression analyses. We confirmed the results in clinical samples using quantitative real-time PCR. A total of 26 immune-related lncRNAs in THCA were obtained. Then we constructed a prognosis model composed of seven lncRNAs (LINC01614, AC017074.1, LINC01184, LINC00667, ACVR2B-AS1, AC090673.1, and LINC00900). Our model can be used as an independent prognostic factor. Principal component analysis displayed that the lncRNAs in the model can distinguish between high and low-risk groups. Clinical correlation analysis showed that the expression levels of AC090673.1 (P<0.05), LINC01184 (P<0.001), and LINC01614 (P<0.001) were related to disease stage, and LINC00900 (P<0.001) and LINC01614 (P<0.001) were related to T stage. We validated this model in cancer and paracancerous tissues from 24 THCA patients. We identified and experimentally validated seven immune-related lncRNAs that can serve as potential biomarkers for THCA prognosis.

Identification of Three Prognosis-Related Differentially Expressed lncRNAs Driven by Copy Number Variation in Thyroid Cancer.

Thyroid cancer as the malignant tumor with the highest incidence in the endocrine system also shows a fast growth and development. In this work, we developed a new method to identify copy number variation– (CNV–) driven differentially expressed lncRNAs in thyroid cancer for predicting cancer prognosis. The data of RNA sequencing, CNV, methylation, mutation, and clinical details of thyroid cancer were obtained from the Cancer Genome Atlas database (TCGA). Molecular subtypes were clustered by iClusterPlus. Weighted gene co-expression network analysis (WGCNA) was employed to show co-expression modules. DEseq2 was conducted to identify protein coding genes (PCGs) and differentially expressed lncRNAs. CNV was detected using GISTIC 2.0. Three molecular subtypes were identified, and 68 differentially expressed lncRNAs (DElncRNAs) related to cancer were found among different molecular subtypes. CNV of FOXD2-AS1, FAM181A-AS1, and RNF157-AS1 was associated with overall survival and was involved in cancer-related pathways. These three DElncRNAs discovered based on CNV could serve as prognostic biomarkers to predict prognosis for thyroid cancer and new targets to explore molecular drugs.

An autophagy-related lncRNA prognostic risk model for thyroid cancer.

Thyroid cancer (TC) is the most common malignancy of the endocrine system and its incidence is gradually rising. Research has demonstrated a close link between autophagy and thyroid cancer. We constructed a prognostic model of autophagy-related long non-coding RNA (lncRNA) in thyroid cancer and explored its prognostic value. The data used in this study were all obtained from The Cancer Genome Atlas (TCGA) database and the Human Autophagy Database (HADb). We construct a co-expression network by autophagy-related genes and lncRNA to obtain autophagy-related lncRNAs. After univariate Cox regression analysis and multivariate Cox regression analysis, autophagy-related lncRNAs significantly associated with prognosis were identified. Based on the risk score of lncRNA, thyroid cancer patients are divided into high-risk group and low-risk group. A total of 14,142 lncRNAs and 212 autophagy-related genes (ATGs) were obtained from the TCGA database and the HADb, respectively. We performed lncRNA-ATGs correlation analysis and finally obtained 1,166 autophagy-associated lncRNAs. Subsequently, we conducted univariate Cox regression analysis and multivariate Cox regression analysis, nine autophagy-related lncRNAs (AC092279.1, AC096677.1, DOCK9-DT, LINC02454, AL136366.1, AC008063.1, AC004918.3, LINC02471 and AL162231.2) significantly associated with prognosis were identified. Based on these autophagy-related lncRNAs, a risk model was constructed. The area under the curve (AUC) of the risk score was 0.905, proving that the accuracy of risk signature was superior. In addition, multiple regression analysis showed that risk score was a significant independent prognostic risk factor for thyroid cancer. In this study, nine autophagy-related lncRNAs in thyroid cancer were established to predict the prognosis of thyroid cancer patients.

Expression and function of long non-coding RNA LINC01420 in thyroid cancer.

The Human Genome Project revealed that >90% of the human genome was found to transcribe non-coding RNAs, including micro RNAs and long non-coding RNAs (lncRNAs). lncRNAs have been identified to play a crucial role in cancer progression. Thyroid cancer (TC) is a common type of endocrine cancer; however, the functional roles of lncRNAs in TC have yet to be fully elucidated. The present study investigated whether LINC01420 was upregulated in TC tissues, compared with normal thyroid tissues, and the results suggested that LINC01420 may play a regulatory role in TC. Bioinformatics analysis demonstrated that LINC01420 was associated with translation, rRNA processing, mRNA splicing, regulation of transcription, DNA repair and double-strand break repair. Furthermore, the exact role of LINC01420 in TC was explored by performing a loss-of-function assay, which revealed that the knockdown of LINC01420 inhibited TC cell proliferation and cell cycle progression. The findings of the present study provide a novel insight into the molecular mechanisms underlying TC development. Moreover, they suggest that LINC01420 may serve as a potential therapeutic target for the treatment of TC, and that increased LINC01420 expression levels show potential as a prognostic marker for the disease.

Long Non-Coding RNA ZFAS1 as a Novel Potential Biomarker for Predicting the Prognosis of Thyroid Cancer.

BackgroundThyroid cancer is a type of endocrine cancers with rapidly increased incidence. Recent studies have indicated long non-coding RNAs (lncRNAs) played crucial roles in thyroid cancer tumorigenesis and progression. However, the roles of most lncRNAs in thyroid cancer were still unclear.Material/MethodsWe used TCGA (The Cancer Genome Atlas), GSE50901, GSE29265, and GSE33630 datasets to analyze the expression pattern of ZFAS1 (ZNFX1 antisense RNA 1). The correlation between ZFAS1 and clinicopathological features in thyroid cancer was analyzed. Cell proliferation and cell cycle assays were used to validate the roles of ZFAS1 in thyroid cancer cell lines. DAVID (the database for annotation, visualization and integrated discover) system was used to perform GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis. The starBase datasets and Cytoscape was used to perform ceRNA (competitive endogenous RNA) network.ResultsWe demonstrated ZFAS1 was highly expressed in thyroid cancer compared to normal samples. Moreover, upregulation of ZFAS1 was positively correlated with clinicopathological features and poor prognosis in thyroid cancer. Functional validation showed knockdown of ZFAS1 suppressed cell proliferation and cell cycle in thyroid cancer cells. Bioinformatics analysis showed ZFAS1 was associated with translation, rRNA processing, intra-Golgi vesicle-mediated transport, ribosome, and ubiquitin-mediated proteolysis.ConclusionsOur study suggested ZFAS1 could serve as a biomarker for thyroid cancer.

Identification of differential expressed lncRNAs in human thyroid cancer by a genome-wide analyses.

Recently, a growing number of evidence has revealed that long noncoding RNAs (lncRNAs) act as key regulators in various cellular biologic processes, and dysregulation of lncRNAs involves in tumorigenesis and cancer progression. However, the expression pattern, clinical relevance, and biologic function of most lncRNAs in human thyroid cancer remain unclear. To identify more thyroid‐cancer‐associated lncRNAs, we analyzed the expression profile of lncRNAs in thyroid cancer tissues and adjacent normal or non‐tumor tissues using RNA sequencing data and gene microarray data from The Cancer Genome Atlas and Gene Expression Omnibus. Annotation and analyses of these data revealed that hundreds of lncRNAs are differentially expressed in thyroid cancer tissues when compared with normal tissues. By copy number variation analyses, we identified that some of those dysregulated lncRNAs genome locus are accompanied with the copy number amplification or deletion. Moreover, some lncRNAs expression levels are significantly associated with thyroid cancer patients overall or recurrence‐free survival time, such as RUNDC3A‐AS1, FOXD2‐AS1, PAX8‐AS1, and CRYM‐AS1. Furthermore, we validated an lncRNA termed LINC00704 in thyroid cancer cells by performing loss of function assays. Downregulation of LINC00704 could significantly impair thyroid cancer cells proliferation, colony formation, inhibit cell‐cycle progression and cell invasion, and induce cell apoptosis. Taken together, our findings reveal that lots of lncRNAs are dysregulated and may play critical roles in thyroid cancer, and this study could provide useful resource for identification and investigation of novel lncRNA candidates for thyroid cancer.

Role of lncRNAs in Thyroid Cancer

Thyroid cancer is the most common endocrine cancer in the word and its incidence is on the rise. Though generally associated with a very good prognosis, few cases may demonstrate resistance to treatment such as radio-iodine therapy. lncRNAs have shown to be involved in several steps of thyroid carcinogenesis. It can act as a prognostic and diagnostic marker. Altered levels of specific lncRNAs have also shown to be associated with resistance to radioiodine treatment. Therapy with lncRNA has also shown to return radio-sensitivity in thyroid cancer cell lines.

Long non-coding RNAs in thyroid cancer: Biological functions and clinical significance

Thyroid cancer is the most common endocrine malignant tumor with rapidly increasing incidence in recent decades. Although the majority of thyroid cancers are relatively indolent, some cases still have a risk of developing into more aggressive and lethal forms of thyroid cancers. Similar to other malignancies, thyroid tumorigenesis is a multistep process involving the accumulation of a large number of genetic and epigenetic alterations. Thus, determination of the mechanisms of tumorigenesis is an urgent need for thyroid cancer treatment. Long noncoding RNAs (LncRNAs) have recently been demonstrated to participate in cancer progression. However, their role and molecular mechanism in thyroid cancer remain largely unclear. In this review, we focus on the dysregulation of lncRNAs in thyroid cancer, summarize the latest findings regarding the functions and mechanism of lncRNAs in thyroid cancer, and discuss their potential clinical significance in diagnosis and prognosis of thyroid cancer.