Downregulation of miR‑486‑5p in papillary thyroid carcinoma tissue: A study based on microarray and miRNA sequencing

Construction of a Signature Model to Predict the Radioactive Iodine Response of Papillary Thyroid Cancer

Papillary thyroid cancer (PTC) accounts for about 90% of thyroid cancer. There are approximately 20%-30% of PTC patients showing disease persistence/recurrence and resistance to radioactive iodine (RAI) treatment. For these PTC patients with RAI refractoriness, the prognosis is poor. In this study, we aimed to establish a comprehensive prognostic model covering multiple signatures to increase the predictive accuracy for progression-free survival (PFS) of PTC patients with RAI treatment. The expression profiles of mRNAs and miRNAs as well as the clinical information of PTC patients were extracted from TCGA and GEO databases. A series of bioinformatics methods were successfully applied to filtrate a two-RNA model (IPCEF1 and hsa-mir-486-5p) associated with the prognosis of RAI-therapy. Finally, the RNA-based risk score was calculated based on the Cox coefficient of the individual RNA, which achieved good performances by the time-dependent receiver operating characteristic (tROC) curve and PFS analyses. Furthermore, the predictive power of the nomogram, integrated with the risk score and clinical parameters (age at diagnosis and tumor stage), was assessed by tROC curves. Collectively, our study demonstrated high precision in predicting the RAI response of PTC patients.

MicroRNAs in Papillary Thyroid Cancer: What Is New in Diagnosis and Treatment

Introduction

Papillary thyroid cancer (PTC) accounts for up to 80% of thyroid malignancies. New diagnostic and therapeutic options are suggested including innovative molecular methods. MicroRNAs (miRNAs) are nonprotein coding single-stranded RNAs that regulate many cell processes. The aim of the present study is to review the deregulated miRNAs associated with PTCs.

Methods

A bibliographic research was conducted, resulting in 272 articles referred to miRNAs and PTC. Regarding our exclusion criteria, 183 articles were finally included in our review.

Results

A remarkably large number of miRNAs have been found to be deregulated during PTC manifestation in the literature. The deregulated miRNAs are detected in tissue samples, serum/plasma, and FNA samples of patients with PTC. These miRNAs are related to several molecular pathways, involving genes and proteins responsible for important biological processes. MiRNA deregulation is associated with tumor aggressiveness, including larger tumor size, multifocality, extrathyroidal extension, lymphovascular invasion, lymph node and distant metastasis, and advanced tumor node metastasis stage.

Conclusion

MiRNAs are proposed as new diagnostic and therapeutic tools regarding PTC. They could be essential biomarkers for PTC diagnosis applied in serum and FNA samples, while their contribution to prognosis is of great importance.

Identification of key biomarkers for thyroid cancer by integrative gene expression profiles

Thyroid cancer is a frequently diagnosed malignancy and the incidence has been increased rapidly in recent years. Despite the favorable prognosis of most thyroid cancer patients, advanced patients with metastasis and recurrence still have poor prognosis. Therefore, the molecular mechanisms of progression and targeted biomarkers were investigated for developing effective targets for treating thyroid cancer. Eight chip datasets from the gene expression omnibus database were selected and the inSilicoDb and inSilicoMerging R/Bioconductor packages were used to integrate and normalize them across platforms. After merging the eight gene expression omnibus datasets, we obtained one dataset that contained the expression profiles of 319 samples (188 tumor samples plus 131 normal thyroid tissue samples). After screening, we identified 594 significantly differentially expressed genes (277 up-regulated genes plus 317 down-regulated genes) between the tumor and normal tissue samples. The differentially expressed genes exhibited enrichment in multiple signaling pathways, such as p53 signaling. By building a protein-protein interaction network and module analysis, we confirmed seven hub genes, and they were all differentially expressed at all the clinical stages of thyroid cancer. A diagnostic seven-gene signature was established using a logistic regression model with the area under the receiver operating characteristic curve (AUC) of 0.967. Seven robust candidate biomarkers predictive of thyroid cancer were identified, and the obtained seven-gene signature may serve as a useful marker for thyroid cancer diagnosis and prognosis.

Papillary Thyroid Carcinoma Tissue miR-146b, -21, -221, -222, -181b Expression in Relation with Clinicopathological Features

We analyzed miR-146b, miR-21, miR-221, miR-21, and miR-181b in formalin fixed paraffin-embedded papillary thyroid carcinoma (PTC) tissue samples of 312 individuals and evaluated their expression relationship with clinicopathological parameters. A higher expression of miR-21 was related to unifocal lesions (p < 0.011) and autoimmune thyroiditis (0.007). miR-221, miR-222 expression was higher in the PTC tissue samples with extrathyroidal extension (p = 0.049, 0.003, respectively). In a group of PTC patients with pT1a and pT1b sized tumors, the expression of miR-146b, miR-21, miR-221, and miR-222 in PTC tissue samples was lower than in patients with pT2, pT3, and pT4 (p = 0.032; 0.0044; 0.003; 0.001; 0.001, respectively). Patients with lymph node metastases had higher expression of miR-21, -221, -222, and -181b (p < 0.05). A high expression of miR-146b, miR-21, miR-221 panel was associated with decreased overall survival (OS) (Log rank p = 0.019). Univariate analysis revealed that presence of metastatic lymph nodes and high expression of miR-146b, miR-21, and miR-221 panels were associated with increased hazard of shorter OS. After multivariate analysis, only sex (male) and age (≥55 years) emerged as independent prognostic factors associated with shorter OS (HR 0.28 (95% CI 0.09–0.86) and HR 0.05 (95% CI 0.01–0.22), respectively). In conclusion, 5 analyzed miRs expression have significant relations to clinicopathologic parameters so further investigations of these molecules are expedient while searching for prognostic PTC biomarkers.

Circular RNA circRUNX1 promotes papillary thyroid cancer progression and metastasis by sponging MiR-296-3p and regulating DDHD2 expression

Papillary thyroid cancer (PTC) has a continuously increasing incidence and imposes a heavy medical burden to individuals and society due to its high proportion of lymph node metastasis and recurrence in recent years. Circular RNAs, a class of noncoding RNAs, participate in the progression of many cancers, but the role of circRNAs in PTC is still rarely reported. In this study, circRNA deep sequencing was performed to identify differentially expressed circRNAs in PTC. CircRUNX1 was selected for its high expression in PTC, and circRUNX1 silencing was directly associated with the week potential for migration, invasion and proliferation of PTC in vivo and in vitro. Fluorescence in situ hybridization (FISH) was further used to confirm the cytoplasmic localization of circRUNX1, indicating the possible function of circRUNX1 as a ceRNAs in PTC progression through miRNA binding. MiR-296-3p was then confirmed to be regulated by circRUNX1 and to target DDHD domain containing 2 (DDHD2) by luciferase reporter assays. The strong antitumor effect of miR-296-3p and the tumor-promoting effect of DDHD2 were further investigated in PTC, indicating that circRUNX1 modulates PTC progression through the miR-296-3p/DDHD2 pathway. Overall, circRUNX1 plays an oncogenic role in PTC and provides a potentially effective therapeutic strategy for PTC progression.

LncRNA GATA6-AS1 Inhibits the Progression of Non-Small Cell Lung Cancer via Repressing microRNA-543 to Up-Regulating RKIP

Background

Much evidence unveils the significance of long non-coding RNAs (lncRNAs) in diverse cancers. This study was designed to clarify the function and mechanism of lncRNA GATA6 antisense RNA 1 (GATA6-AS1) in the progression of non-small cell lung cancer (NSCLC).

Methods

GATA6-AS1, miR-543 and Raf kinase inhibitor protein (RKIP) mRNA expressions were detected by qRT-PCR. Chi-square test was adopted to analyze the relationship between GATA6-AS1 expression and the clinicopathological parameters of NSCLC patients. NSCLC cells H1299 and H460 cells were used as overexpression or knockdown models, respectively, and cell proliferation and metastasis were determined by CCK-8 and Transwell assays. RKIP, E-cadherin, N-cadherin, STAT3, p-STAT3 expressions in NSCLC cells were detected by Western blot. The targeting relationship between GATA6-AS1 and miR-543 was confirmed by dual-luciferase reporter assay.

Results

GATA6-AS1 was significantly lowly expressed in NSCLC tissues and cell lines, and its low expression level was significantly correlated with larger tumor size and positive lymph node metastasis. GATA6-AS1 overexpression inhibited the proliferation, migration, invasion and epithelial–mesenchymal transition of NSCLC cells, while GATA6-AS1 knockdown caused the opposite effects. Mechanistically, it was confirmed that GATA6-AS1 impeded NSCLC cell proliferation and metastasis by adsorbing miR-543 and up-regulating the expression of RKIP.

Conclusions

As a tumor suppressor, GATA6-AS1 participates in suppressing the progression of NSCLC by modulating the miR-543/RKIP axis.

Plasma-Derived miRNA-222 as a Candidate Marker for Papillary Thyroid Cancer

We analyzed five miRNA molecules (miR-221; miR-222; miR-146b; miR-21; miR-181b) in the plasma of patients with papillary thyroid cancer (PTC), nodular goiter (NG) and healthy controls (HC) and evaluated their diagnostic value for differentiation of PTC from NG and HC. Preoperative PTC plasma miRNA expression (n = 49) was compared with plasma miRNA in the HC group (n = 57) and patients with NG (n = 23). It was demonstrated that miR-221; miR-222; miR-146b; miR-21 and miR-181b were overexpressed in preoperative PTC plasma samples compared to HC (p < 0.0001; p < 0.0001; p < 0.0001; p < 0.0001; p < 0.002; respectively). The upregulation in tumor tissue of these miRNAs was consistent with The Cancer Genome Atlas Thyroid Carcinoma dataset. A significant decrease in miR-21; miR-221; miR-146b and miR-181b expression was observed in the plasma of PTC patients after total thyroidectomy (p = 0.004; p = 0.001; p = 0.03; p = 0.036; respectively). The levels of miR-222 were significantly higher in the preoperative PTC compared to the NG group (p = 0.004). ROC curve (receiver operating characteristic curve) analysis revealed miR-222 as a potential marker in distinguishing PTC from NG (AUC 0.711; p = 0.004). In conclusion; circulating miR-222 profiles might be useful in discriminating PTC from NG.

The role of microRNAs in the pathogenesis of thyroid cancer

Thyroid cancer is the most frequent type of cancers originating from the endocrine system. Early diagnosis leads to good clinical outcome in differentiated types of thyroid cancer. Yet, there are few treatment options for patients with medullary or anaplastic thyroid cancer. Thus, identification of molecular markers that explain the pathologic process during evolution of this cancer has practical significance. MicroRNAs (miRNAs) have been shown to influence the activity of thyroid cancer-related signaling pathways such as MAPK pathway and RET gene. These small transcripts not only can differentiate malignant tissues from non-malignant tissues, but also have differential expression in different stages of thyroid cancer. Assessment of serum levels of miRNAs is a practical noninvasive method for follow-up of patients after thyroidectomy. Moreover, the therapeutic effects of a number of miRNAs have been verified in xenograft models of thyroid cancer. In the current review, we summarize the data regarding the role of miRNAs in thyroid cancer.

Multi-omics Signatures and Translational Potential to Improve Thyroid Cancer Patient Outcome

Recent advances in high-throughput molecular and multi-omics technologies have improved our understanding of the molecular changes associated with thyroid cancer initiation and progression. The translation into clinical use based on molecular profiling of thyroid tumors has allowed a significant improvement in patient risk stratification and in the identification of targeted therapies, and thereby better personalized disease management and outcome. This review compiles the following: (1) the major molecular alterations of the genome, epigenome, transcriptome, proteome, and metabolome found in all subtypes of thyroid cancer, thus demonstrating the complexity of these tumors and (2) the great translational potential of multi-omics studies to improve patient outcome.