Competing endogenous RNA regulatory network in papillary thyroid carcinoma

Emerging landscape of circHIPK3 and its role in cancer and other diseases (Review)

Circular RNAs (circRNAs) are a special class of recently re‑discovered RNAs, which are covalently closed ring RNA molecules. circRNAs have been reported to possess multiple functions and are considered crucial regulators of several processes, and are therefore gaining increasing attention. In recent years, increasing evidence has shown that circRNAs are implicated in several crucial biological processes via regulation of gene expression, and their dysregulation is also associated with the development of numerous diseases, particularly acting as oncogenic or tumor‑suppressor molecules in cancer. Furthermore, circRNAs are involved in cell proliferation, differentiation, apoptosis, invasion and metastasis. In the present review, the biogenesis and functions of circRNAs are described, with a focus on the most recent research advances and the emerging roles of circular homeodomain‑interacting protein kinase 3 (circHIPK3) in human diseases. The present review may provide novel avenues for research on the roles of circHIPK3 as a clinical diagnostic and prognostic biomarker, as well as highlighting promising therapeutic targets for certain diseases and cancer.

CircHIPK3 Promotes Thyroid Cancer Tumorigenesis and Invasion through the Mirna-338-3p/RAB23 Axis

Objective：Thyroid cancer is a common type of endocrine malignancy, and its incidence has been steadily increasing in many regions of the world. Numerous studies have found that the circRNAs in various cancer types are aberrantly expressed, which could be potential biological diagnostic markers and therapeutic targets. The purpose of this study was to investigate the role of circHIPK3 in the development and progression of thyroid cancer and its mechanism. Subject and Methods：qRT-PCR was used to detect the relative expression levels of circHIPK3 in thyroid cancer cell lines (K1, CAL-62, TPC1), human thyroid normal cells (Nthy-ori 3-1), 10 pairs of thyroid cancer tissues and corresponding adjacent normal tissues. CCK-8 and Transwell assays were used to detect the proliferation and metastasis ability of cells. The targeted relationships between circHIPK3-miR-338-3p and miR-338-3p-RAB23 were predicted by bioinformatics analysis and verified by dual-luciferase reporter assays. Results and Conclusion: The downregulation of circHIPK3 significantly reduced the migration, invasion and proliferation of thyroid carcinoma. Then, we demonstrated that circHIPK3 up-regulated the expression of its target gene RAB23 by sponging miR-338-3p to promote the tumorigenesis and invasiveness of thyroid cancer. This study is the first to find that circHIPK3 plays the role of oncogenetic circRNA in thyroid cancer, which may provide new insights into how circRNA affects the progression of thyroid cancer. Our study also showed that circHIPK3 could be a novel biomarker for thyroid cancer.

Potential five-mRNA signature model for the prediction of prognosis in patients with papillary thyroid carcinoma

Although the mortality rate of papillary thyroid carcinoma (PTC) is relatively low, the recurrence rates of PTC remain high. The high recurrence rates are related to the difficulties in treatment. Gene expression profiles has provided novel insights into potential therapeutic targets and molecular biomarkers of PTC. The aim of the present study was to identify mRNA signatures which may categorize PTCs into high-and low-risk subgroups and aid with the predictions for prognoses. The mRNA expression profiles of PTC and normal thyroid tissue samples were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs were identified using the ‘EdgeR’ software package. Gene signatures associated with the overall survival of PTC were selected, and enrichment analysis was performed to explore the biological pathways and functions of the prognostic mRNAs using the Database for Visualization, Annotation and Integration Discovery. A signature model was established to investigate a specific and robust risk stratification for PTC. A total of 1,085 differentially expressed mRNAs were identified between the PTC and normal thyroid tissue samples. Among them, 361 mRNAs were associated with overall survival (P<0.05). A 5-mRNA prognostic signature for PTC (ADRA1B, RIPPLY3, PCOLCE, TEKT1 and SALL3) was identified to classify the patients into high-and low-risk subgroups. These prognostic mRNAs were enriched in Gene Ontology terms such as ‘calcium ion binding’, ‘enzyme inhibitor activity’, ‘carbohydrate binding’, ‘transcriptional activator activity’, ‘RNA polymerase II core promoter proximal region sequence-specific binding’ and ‘glutathione transferase activity’, and Kyoto Encyclopedia of Genes and Genomes signaling pathways such as ‘pertussis’, ‘ascorbate and aldarate metabolism’, ‘systemic lupus erythematosus’, ‘drug metabolism-cytochrome P450 and ‘complement and coagulation cascades’. The 5-mRNA signature model may be useful during consultations with patients with PTC to improve the prediction of their prognosis. In addition, the prognostic signature identified in the present study may reveal novel therapeutic targets for patients with PTC.

Proto-oncogene RTL4 promotes tumorigenesis and invasiveness of papillary thyroid cancer

BACKGROUND

Although the prognosis of papillary thyroid carcinoma (PTC) is good, its widespread prevalence still degrades the quality of life of tens of thousands of patients. PTC can even be life-threatening as a result of its aggressiveness and metastasis.

METHODS

Using complete transcriptome sequence analysis, cutting-edge research has revealed many tumor-associated genes. These related genes help us better understand the tumorigenesis and progression of PTC. We discovered that retrotransposon Gag like 4 (RTL4) is a novel potential PTC-associated gene. By Quantitative real-time polymerase chain reaction (qRT-PCR), we observed an obvious upregulation of RTL4 in PTC tissue. And, we validated the expression characteristics of RTL4 using data from the Cancer Genome Atlas (TCGA). Furthermore, we down-regulated RTL4 expression levels in relevant cell lines and studied the biological function of the RTL4 line in PTC by cell proliferation, colony formation, migration and invasion assays.

RESULTS

In the present study, high expression of RTL4 suggested lymph node metastasis (P = 0.028) and was associated with the pathological type (P = 0.001). RTL4 had the validity of distinguishing PTC tissues and normal tissues showed an AUC of 87.53% for the TCGA data set. The downregulation of RTL4 in the PTC cell lines distinctly inhibited cell colony formation, proliferation, migration, and invasion.

CONCLUSIONS

The result revealed RTL4 is closely related to the occurrence and development of PTC. RTL4 may participate in the HOTAIR-miR-206-ZCCHC16 ceRNA regulatory network and be regulated and play a role in the ceRNA regulatory network. It may be used as a target or indicator for the treatment and prognosis of PTC.

The Role of Long Non-Coding RNAs in Thyroid Cancer

Thyroid cancer, the most common endocrine malignancy, has become the most commonly diagnosed malignant solid tumor. Moreover, some cases have poor prognosis, and the survival period is only 3-5 months. Long noncoding RNAs (lncRNAs) are a group of functional RNA molecules more than 200 nucleotides in length that lack the ability to encode protein but participate in all aspects of gene regulation. Functionally, many lncRNAs play essential roles in epigenetic regulation at transcriptional and post-transcriptional levels via various molecular mechanisms. Recent studies have discovered important roles for lncRNAs during the complex process of carcinogenesis in thyroid cancer. In this review, we focus on lncRNAs dysregulated in thyroid cancer and summarize recently reported associations between lncRNAs and thyroid cancer in order to demonstrate the significant value of lncRNAs in diagnosis and treatment.

A susceptibility biomarker identification strategy based on significantly differentially expressed ceRNA triplets for ischemic cardiomyopathy

Ischemic cardiomyopathy (ICM) is a common human heart disease that causes death. No effective biomarkers for ICM could be found in existing databases, which is detrimental to the in-depth study of this disease. In the present study, ICM susceptibility biomarkers were identified using a proposed strategy based on RNA-Seq and miRNA-Seq data of ICM and normal samples. Significantly differentially expressed competing endogenous RNA (ceRNA) triplets were constructed using permutation tests and differentially expressed mRNAs, miRNAs and lncRNAs. Candidate ICM susceptible genes were screened out as differentially expressed genes in significantly differentially expressed ceRNA triplets enriched in ICM-related functional classes. Finally, eight ICM susceptibility genes and their significantly correlated lncRNAs with high classification accuracy were identified as ICM susceptibility biomarkers. These biomarkers would contribute to the diagnosis and treatment of ICM. The proposed strategy could be extended to other complex diseases without disease biomarkers in public databases.

Identification of key miRNAs in papillary thyroid carcinoma based on data mining and bioinformatics methods

MicroRNAs (miRNAs) are a class of short (approximately 22 nucleotides), non-coding and endogenous RNA molecules that play pivotal roles in the occurrence and development of cancer. The present study aimed to investigate key miRNAs involved in papillary thyroid carcinoma (PTC). Two independent datasets (GSE73182 and GSE113629) were obtained from the GEO database. The differentially expressed miRNAs (DEmiRNAs) between PTC tissues and normal thyroid tissues were analyzed by GEO2R with the Limma R package. Key miRNAs in PTC were identified by the VennDiagram R package. The targets of the key miRNAs were predicted by miRWalk and were functionally enriched by clusterProfiler R package. Five miRNAs including hsa-miR-146b-5p, hsa-miR-15a-5p, hsa-miR-21-5p, hsa-miR-221-3p and hsa-miR-222-3p were identified as key miRNAs in PTC. The expression levels of these key miRNAs were upregulated in PTC. This finding was also confirmed in the other dataset. Target prediction of miRNAs indicated that hsa-miR-146b-5p, hsa-miR-15a-5p, hsa-miR-21-5p, hsa-miR-221-3p and hsa-miR-222-3p exhibited 2, 41, 3, 14 and 8 target genes, respectively. Enrichment analysis indicated that these key miRNAs were mainly involved in nine biological processes, such as regulation of MAP kinase activity, JNK cascade signaling and regulation of protein serine/threonine kinase activity) and in 28 pathways, including the mitogen associated protein kinase, the sphingolipid, ErbB, Ras and the C-type lectin receptor signaling pathways. In conclusion, the present study identified several key miRNAs in PTC, which serve as potential targets for PTC diagnosis and treatment.

Construction of a Competitive Endogenous RNA Network in Uterine Corpus Endometrial Carcinoma

BACKGROUND Long non-coding RNAs (lncRNAs) affect post-transcriptional regulation by interfering with microRNAs (miRNAs), and by acting as competitive endogenous RNAs (ceRNAs). The roles and mechanisms of lncRNAs as ceRNAs in the progression and prognosis of uterine corpus endometrial carcinoma are not well understood. MATERIAL AND METHODS We analyzed high-throughput transcriptome data downloaded from The Cancer Genome Atlas database for 548 patients with uterine corpus endometrial carcinoma, and the we constructed a ceRNA network. Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses of differentially expressed messenger RNAs (DE-mRNAs) were performed using R software. Kaplan-Meier survival curves were generated for all RNAs in the ceRNA network. RESULTS We identified 2612 messenger RNAs (mRNAs), 1111 lncRNAs, and 187 miRNAs that were differentially expressed in uterine corpus endometrial carcinoma. We then identified mutual regulatory relationships between lncRNA-miRNA pairs and miRNA-mRNA pairs. A ceRNA regulatory network for uterine corpus endometrial carcinoma was successfully constructed, and consisted of 87 lncRNAs, 74 mRNAs, and 20 miRNAs. Nine lncRNAs, 3 miRNAs, and 22 mRNAs were associated with prognosis of uterine corpus endometrial carcinoma. We also analyzed the linear relationships between the expression of the 9 DE-lncRNAs and 22 DE-mRNAs with prognostic value. CONCLUSIONS Our study showed that the lncRNAs C2orf48 and LINC00261 might be key regulators of uterine corpus endometrial carcinoma and might serve as prognostic indicators. Our study contributes to the understanding of the molecular mechanisms of uterine corpus endometrial carcinoma, and it identifies lncRNAs that might serve as prognostic markers and therapeutic targets.

Gene Expression Patterns Unveil New Insights in Papillary Thyroid Cancer

Background and objectives: Papillary thyroid carcinoma is the most frequent variety of all malignant endocrine tumors. It represents a heterogeneous malignancy with various clinical outcomes, emphasizing the need to identify powerful biomarkers with clinical relevance. Materials and Methods: Available gene expression data (level 3) for thyroid cancers were downloaded from the Cancer Genome Atlas (TCGA), followed by bioinformatic analyses performed on the data set. Results: Based on gene expression analysis, we were able to identify common and specific gene signatures for the three main types of papillary thyroid carcinoma (classical, follicular variant, and tall-cell). The survival rate was not significantly different among the main subtypes, but we were able to identify a biological adhesion signature with impact in patient prognostic. Conclusions: Taken together, the gene expression signature and particular adhesion signature, along with ITGA10 and MSLN in particular, could be used as a prognostic tool with important clinical relevance.