Biomarker For Papillary Thyroid Carcinoma Research Articles

Identification of prognostic biomarkers for papillary thyroid carcinoma by a weighted gene co-expression network analysis.

AimWhole transcriptome analysis was conducted to identify differentially expressed RNAs and regulatory networks associated with papillary thyroid carcinoma (PTC).MethodsA weighted gene co‐expression network analysis based on high‐throughput sequencing data for six pairs of PTC and adjacent tissue samples was conducted to understand the biological functions and regulatory networks involving long non‐coding RNAs (lncRNAs), circular RNAs (circRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs).ResultsWe detected 131, 338, 31, and 556 differentially expressed circRNAs, lncRNAs, miRNAs, and mRNAs, respectively. We identified modules that were significantly positively and negatively related to cancer and lymph node metastasis. Gray and turquoise modules were positively correlated with cancer phenotypes (p < 0.05), whereas yellow, brown, and blue modules were negatively correlated with cancer (p < 0.05). Gray module was positively correlated with lateral lymph node metastasis (p = 0.02). Kaplan–Meier analyses revealed that the levels of transmembrane protein 63C (TMEM63C), lysyl oxidase‐like 1 (LOXL1), collagen type V alpha 1 chain (COL5A1), ADAM metalloproteinase with thrombospondin type I motif 2 (ADAMTS2), and LysM‐domain containing 3 (LYSMD3) were significantly associated with overall survival (p < 0.05). Significant increase in the expression of COL5A1 and LOXL1 in tumor tissues was validated by quantitative real‐time polymerase chain reaction (p < 0.05). COL5A1 and LOXL1 promoted PTC cell growth and invasion in vitro.ConclusionsWe identified COL5A1 and LOXL1 as potential prognostic biomarkers, providing new insights into the occurrence and progression of PTC.

Comprehensive Analysis of the PROSER2-AS1-Related ceRNA Network and Immune Cell Infiltration in Papillary Thyroid Carcinoma.

BackgroundPapillary thyroid carcinoma (PTC) is a malignant tumor of the endocrine system, and distant metastasis leads to poor prognosis for patients with PTC. The competitive endogenous RNA (ceRNA) network and tumor-infiltrating immune cells might participate in tumor prognosis and distant metastasis. However, few studies have focused on ceRNAs and immune cells in PTC.MethodsWe identified differentially expressed lncRNAs (DELs) using the GEO2R tool of the GEO database. Through comprehensive analysis, we selected lncRNA PROSER2-AS1 and constructed a PROSER2-AS1-mediated ceRNA network. Survival was analyzed with a Kaplan-Meier (KM) curve. Gene set enrichment analysis (GSEA) was performed to determine the function of PROSER2-AS1 in the ceRNA network using TCGA database. Moreover, the relationship between PROSER2-AS1 and immune cell infiltration was analyzed with ssGSEA using the “GSVA” package in R.ResultsComprehensive analysis of the GSE66783 dataset revealed 105 significantly differentially expressed lncRNAs. Univariate and multivariate Cox regression analyses were performed to assess the prognostic significance of the DELs, and we identified lncRNA PROSER2-AS1 as an independent factor for prognosis in PTC (p < 0.05). Considering the online tools LncRNASNP2 and miRWalk3.0, we constructed a PROSER2-AS1-related ceRNA network. Furthermore, the GSEA results suggested that PROSER2-AS1 may be involved in immune cell infiltration and that PROSER2-AS1 was correlated with 14 types of tumor-infiltrating immune cells. PROSER2-AS1 might function through TGFBR3.ConclusionlncRNA PROSER2-AS1 and related mRNAs (TGFBR3) may be potential prognostic biomarkers in PTC and may correlate with immune infiltrates.

APOE Is a Prognostic Biomarker and Correlates with Immune Infiltrates in Papillary Thyroid Carcinoma.

Background: Recent research showed that abnormal lipid metabolism was associated with cancers. As one of the genes that can regulate the level of lipid metabolism, abnormal APOE expression was associated with carcinogenesis. However, the clinical value of APOE in papillary thyroid carcinoma (PTC) remains to be determined.Methods: ONCOMINE, GEPIA, UALCAN, STRING, GeneMANIA, LinkedOmics, GSCALite, TISIDB, EPIC and TIMER were utilized to achieve comprehensively bioinformatics analysis of APOE in this study. And the immunohistochemical staining of APOE was used to verify the predicted results.Results: The mRNA level and protein level of APOE of PTC tissues were significantly elevated in TCGA cohort and Shanghai cohort. PTC patients with low mRNA level of APOE were associated with a bad prognosis. The functions of APOE co-expressed genes were mainly enriched in adaptive immune response, protein-lipid complex subunit organization, actin cytoskeleton reorganization, cell chemotaxis, protein activation cascade and transcriptional misregulation in cancer. APOE level was significantly correlated with tumor-infiltrating cells (B cells, CD8+ T cells, neutrophils, and dendritic) and immune biomarkers in PTC.Conclusions: APOE is a potential independent biomarker for PTC and APOE expression is positively correlated with immune cell infiltration in PTC.

Identification of Potential lncRNAs and miRNAs as Diagnostic Biomarkers for Papillary Thyroid Carcinoma Based on Machine Learning.

Background Papillary thyroid carcinoma (PTC) accounts for most of the proportion of thyroid cancer (TC). The objective of this study was to identify diagnostic, differentially expressed long noncoding RNAs (lncRNAs) and microRNAs (miRNAs), contributing to understanding the epigenetics mechanism of PTC. Methods The data of lncRNA, miRNA, and mRNA were downloaded from the Cancer Genome Atlas (TCGA) dataset, followed by functional analysis of differentially expressed mRNAs. Optimal diagnostic lncRNA and miRNA biomarkers were identified via random forest. The regulatory network between optimal diagnostic lncRNA and mRNAs and optimal diagnostic miRNA and mRNAs was identified, followed by the construction of ceRNA network of lncRNA-mRNA-miRNA. Expression validation and diagnostic analysis of lncRNAs, miRNAs, and mRNAs were performed. Overexpression of ADD3-AS1 was performed in PTC-UC3 cell lines, and cell proliferation and invasion assay were used for investigating the role of ADD3-AS1 in PTC. Results A total of 107 differentially expressed lncRNAs, 81 differentially expressed miRNAs, and 515 differentially expressed mRNAs were identified. 11 lncRNAs and 6 miRNAs were regarded as the optimal diagnostic biomarkers for PTC. The epigenetic modifications via the above diagnostic lncRNAs and miRNAs were identified, including MIR181A2HG-FOXP2-hsa-miR-146b-3p, BLACAT1/ST7-AS1-RPS6KA5-hsa-miR-34a-5p, LBX2-AS1/MIR100HG-CDHR3-hsa-miR-34a-5p, ADD3-AS1-PTPRE-hsa-miR-9-5p, ADD3-AS1-TGFBR1-hsa-miR-214-3p, LINC00506-MMRN1-hsa-miR-4709-3p, and LOC339059-STK32A-hsa-miR-199b-5p. In the functional analysis, MMRN1 and TGFBR1 were involved in cell adhesion and endothelial cell migration, respectively. Overexpression of ADD3-AS1 inhibited cell growth and invasion in PTC cell lines. Conclusion The identified lncRNAs/miRNAs/mRNA were differentially expressed between normal and cancerous tissues. In addition, identified altered lncRNAs and miRNAs may be potential diagnostic biomarkers for PTC. Additionally, epigenetic modifications via the above lncRNAs and miRNAs may be involved in tumorigenesis of PTC.

Aberrant expression of five miRNAs in papillary thyroid carcinomas.

BackgroundThe miRNAs play critical roles in the progression of various tumors. Our study aimed to screen and identify miRNAs to investigate their diagnostic and prognostic value for papillary thyroid carcinoma (PTC).MethodsmiRNAs were evaluated in PTC (n = 30) tissues, A‐PTC (n = 30), benign nodules (n = 35) and A‐benign nodules (n = 35). The expression levels of five miRNAs were quantified using real‐time, quantitative PCR. ROC analysis was used to evaluate the miRNA diagnostic value.ResultsThe expression of miR‐1296‐5p, miR‐1301‐3p, and miR‐532‐5p was significantly downregulated (p = 0.0001, p = 0.0006, p = 0.0024, respectively), while miR‐551b‐3p and miR‐455‐3p were significantly upregulated in PTC tissues compared to A‐PTC tissues (p = 0.0005, p = 0.0046, respectively). Interestingly, the expression of miR‐1296‐5p was downregulated, while miR‐551b‐3p and miR‐455‐3p were upregulated in the A‐PTC group compared to the A‐benign group. Moreover, the miR‐1296‐5p expression level was associated with tumor size, the number of foci and the TNM stage; the miR‐455‐3p expression level was correlated with patient age, tumor size, and TNM stage; and the miR‐532‐5p expression level was correlated with patient age, lymph node metastasis and TNM stage correspondingly. ROC analysis revealed that the AUCs for miR‐1301‐3p, miR‐1296‐5p, miR‐455‐3p, miR‐532‐5p, and miR‐551b‐3p were 0.773, 0.790, 0.783, 0.744, and 0.650, respectively.ConclusionsOur results indicated that miR‐1296‐5p, miR‐1301‐3p, miR‐532‐5p, miR‐551b‐3p, and miR‐455‐3p are aberrantly expressed in papillary thyroid carcinomas and correlated with clinicopathological features. ROC curve analysis indicated that these five miRNAs have a potential diagnostic value. Consequently, we speculate that the five altered miRNAs may serve as potential diagnostic and prognostic biomarkers for PTC.

Genome-wide scanning for CHD1L gene in papillary thyroid carcinoma complicated with type 2 diabetes mellitus.

Papillary thyroid carcinoma (PTC) represents the most common subtype of thyroid cancer (TC). This study was set out to explore the potential effect of CHD1L on PTC and type 2 diabetes mellitus (T2DM). We searched for T2DM susceptibility genes through the GWAS database and obtained T2DM-related differentially expressed gene from the GEO database. The expression and clinical data of TC and normal samples were collated from the TCGA database. Receiver operating characteristic (ROC) curve analysis was subsequently applied to assess the sensitivity and specificity of the CHD1L for the diagnosis of PTC. The MCP-counter package in R language was then utilized to generate immune cell score to evaluate the relationship between CHD1L expression and immune cells. Then, we performed functional enrichment analysis of co-expressed genes and DEGs to determine significantly enriched GO terms and KEGG to predict the potential functions of CHD1L in PTC samples and T2DM adipose tissue. From two genes (ABCB9, CHD1L) were identified to be DEGs (p < 1 * 10-5) that exerted effects on survival (HR > 1, p < 0.05) in PTC and served as T2DM susceptibility genes. The gene expression matrix-based scoring of immunocytes suggested that PTC samples with high and low CHD1L expression presented with significant differences in the tumor microenvironment (TME). The enrichment analysis of CHD1L co-expressed genes and DEGs suggested that CHD1L was involved in multiple pathways to regulate the development of PTC. Among them, Kaposi sarcoma-associated herpesvirus infection, salmonella infection and TNF signaling pathways were highlighted as the three most relevant pathways. GSEA analysis, employed to analyze the genome dataset of PTC samples and T2DM adipose tissue presenting with high and low expression groups of CHD1L, suggests that these differential genes are related to chemokine signaling pathway, leukocyte transendothelial migration and TCELL receptor signaling pathway. CHD1L may potentially serve as an early diagnostic biomarker for PTC, and a target of immunotherapy for PTC and T2DM.

Integrated bioinformatics analysis and screening of hub genes in papillary thyroid carcinoma.

BackgroundWith the increasing incidence of papillary thyroid carcinoma (PTC), PTC continues to garner attention worldwide; however its pathogenesis remains to be elucidated. The purpose of this study was to explore key biomarkers and potential new therapeutic targets for, PTC.MethodsGEO2R and Venn online software were used for screening of differentially expressed genes. Hub genes were screened via STRING and Cytoscape, followed by Gene Ontology and KEGG enrichment analysis. Finally, survival analysis and expression validation were performed using the UALCAN online software and immunohistochemistry.ResultsWe identified 334 consistently differentially expressed genes (DEGs) comprising 136 upregulated and 198 downregulated genes. Gene Ontology enrichment analysis results suggested that the DEGs were mainly enriched in cancer-related pathways and functions. PPI network visualization was performed and 17 upregulated and 13 downregulated DEGs were selected. Finally, the expression verification and overall survival analysis conducted using the Gene Expression Profiling Interactive Analysis Tool (GEPIA) and UALCAN showed that LPAR5, TFPI, and ENTPD1 were associated with the development of PTC and the prognosis of PTC patients, and the expression of LPAR5, TFPI and ENTPD1 was verified using a tissue chip.ConclusionsIn summary, the hub genes and pathways identified in the present study not only provide information for the development of new biomarkers for PTC but will also be useful for elucidation of the pathogenesis of PTC.

Cartilage oligomeric matrix protein affects the biological behavior of papillary thyroid carcinoma cells by activating the PI3K/AKT/Bcl-2 pathway.

Objective: To explore the effect of cartilage oligomeric matrix protein (COMP) on papillary thyroid carcinoma (PTC).Methods: COMP expression levels in PTC tissues and matched adjacent normal tissues were measured using tissue microarrays. Human PTC cells were cultured and transduced with lentiviral short hairpin RNA against COMP (COMP-shRNA), a negative control (NC) shRNA, or mock transfected (Control). We used the Cell Counting Kit-8, performed colony formation assays, wound healing assays, Transwell invasion assays, flow cytometry, and measured the expression of apoptosis-related proteins at the mRNA and protein levels to explore the effects of COMP on the biological behavior of PTC cells and to discover the specific signaling pathway involved in these processes.Results: COMP expression was significantly higher in PTC tissues than in adjacent normal tissues. At the cellular level, COMP promoted cell migration, increased the invasiveness of PTC cells, and inhibited apoptosis. However, differences in cell proliferation were only observed within 72 hours. At the same time, colony formation assays showed that silencing COMP inhibited the proliferation of PTC cells. We also found that COMP regulated the behavior of PTC cells by activating the PI3K/AKT/Bcl-2 pathway.Conclusions: COMP is upregulated in PTC, which enhances cancer cell invasion and inhibits apoptosis, contributing to the development and progression of PTC. Thus, COMP may serve as a new biomarker for PTC.

Decreased serum exosomal miR-29a expression and its clinical significance in papillary thyroid carcinoma.

BackgroundAberrant levels of circulating microRNAs (miRNAs) are potential biomarkers in papillary thyroid carcinoma (PTC) diagnosis and therapy. The aim of this study was to evaluate serum exosomal miR‐29a expression as a non‐invasive biomarker for PTC diagnosis and prognosis.MethodsQuantitative reverse transcription polymerase chain reaction was applied to measure serum exosomal miR‐29a expression levels in blood samples of 119 patients with PTC and 100 control subjects.ResultsSerum exosomal miR‐29a expression levels were significantly decreased in PTC cases. In addition, receiver operating characteristic (ROC) analysis revealed serum exosomal miR‐29a could well differentiate PTC from normal controls. Moreover, serum exosomal miR‐29a levels increased progressively and significantly 30 days and 90 days after surgery. Furthermore, PTC patients with lower serum exosomal miR‐29a expression had higher risk of recurrence. Decreased serum exosomal miR‐29a expression was significantly associated with worse clinical variables including tumor size, extrathyroidal extension, and TNM stage, as well as shorter survival. Finally, both univariate and multivariate identified serum exosomal miR‐29a as an independent prognostic indicator for overall survival.ConclusionThese results demonstrated that serum exosomal miR‐29a might serve as a potential biomarker for PTC diagnosis and prognosis.

Analysis of the expression and potential molecular mechanism of interleukin-1 receptor antagonist (IL1RN) in papillary thyroid cancer via bioinformatics methods

BackgroundInterleukin-1 receptor antagonist (IL1RN) has been reported as a biomarker of many cancers. However, the biological function of IL1RN in papillary thyroid carcinoma (PTC) remains undetermined.MethodsWe obtained IL1RN expression data from The Cancer Genome Atlas (TCGA) database. Enrichment analysis of coexpressed genes and IL1RN methylation analysis were performed via LinkedOmics. The correlations between IL1RN and immune infiltrates were investigated via ESTIMATE, TIMER and TISIDB. We analyzed the association of IL1RN expression with pancancer overall survival (OS) via Gene Expression Profiling Interactive Analysis (GEPIA).ResultsIL1RN showed higher expression levels and lower methylation levels in PTC tissues than in normal tissues. Higher IL1RN expression was significantly associated with shorter progression-free survival (PFS), advanced tumor stage, tumor metastasis, increased incidence of BRAF mutations, and decreased incidence of N-RAS and H-RAS mutations. Genes coexpressed with IL1RN participate primarily in immune-related pathways. IL1RN expression positively correlated with immune infiltration, tumor progression and poor OS for all cancers.ConclusionsIL1RN is a good prognostic and diagnostic biomarker for PTC. IL1RN may promote thyroid cancer progression through immune-related pathways. Methylation may act as an upstream regulator of IL1RN expression and biological function. Additionally, IL1RN was shown to have broad prognostic value in a pancancer cohort.

Prediction Biomarkers Associated with Lymph Node Metastasis and Prognosis were Identified in Papillary Thyroid Carcinoma via Integrated Bioinformatics Analysis.

Prediction biomarkers associated with prognosis and lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) are needed to facilitate clinicians in choosing appropriate therapies. We hope to identify key genes associated with LNM and prognosis in PTC. GSE29265, GSE33630, GSE3467, GSE3678 and GSE58545 gene expression profiles were acquired from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between PTC tissues and normal thyroid tissues were selected with the GEO2R tool, and common DEGs among the five datasets were integrated with Venn software online. A proteinprotein interaction (PPI) network of the common DEGs was visualized. We analyzed the PPI network and determined core genes using the Cytoscape software. Furthermore, we employed UALCAN to verify the expression and promoter methylation status of the core genes in thyroid carcinoma (THCA). Additionally, the Kaplan-Meier plotter online tool was used to analyze the relationship between overall survival and core gene expressions in THCA. TNS3, DUSP6, DUSP4 and PTPRE were identified as core genes. Expression of these 4 genes and the promoter methylation status of DUSP4 and PTPRE were strongly associated with LNM (P<0.05). High expression of 3 genes (DUSP6, DUSP4 and PTPRE) was related to a significantly better survival than low expression of the 3 genes in THCA. In contrast, high TNS3 expression was related to significantly worse survival (P<0.05). TNS3, DUSP6, DUSP4, PTPRE and DUSP4 and PTPRE promoter methylation status might be useful predictive biomarkers of LNM in PTC. Additionally, these genes may be prognostic biomarkers in PTC.

Upregulation of miR-421 predicts poor prognosis and promotes proliferation, migration, and invasion of papillary thyroid cancer cells.

Background:Papillary thyroid carcinoma (PTC) represents the most frequent subtype of thyroid cancer (TC) with poor prognosis mainly due to the severe invasion and metastasis. As an oncogene, microRNA-421 (miR-421) is involved in the development of various cancers. This study was to investigate the clinical significance of miR-421 in PTC and its effects on the biological function of PTC cells.Methods:The expression level of miR-421 in all tissues and PTC cell lines was measured by quantitative real-time polymerase chain reaction (qRT-PCR). Subsequently, the relationship between miR-421 expression and the clinicopathological feature was detected by chi-square analysis in 106 patients with PTC. In addition, Kaplan-Meier and multivariate Cox regression analysis were used to detect the survival time and the prognostic value of miR-421. Finally, the regulatory effect of miR-421 on the proliferation, migration, and invasion ability of PTC cells was detected by Cell Counting Kit (CCK-8) and Transwell assay.Results:Compared with all control groups, the expression of miR-421 was significantly increased in 106 patients tissues and PTC cell lines (p < 0.001). In addition, patients with miR-421 upregulated in PTC showed more positive lymph node metastasis (p = 0.011), positive tumor infiltration (p = 0.031), and TNM stage III/IV (p = 0.019), and when miR-421 expression level was elevated, the survival rate of PTC patients was poor (log-rank test, p = 0.023). Furthermore, miR-421 might be an independent prognostic biomarker for PTC (hazard ratio [HR] = 3.172, 95% CI = 1.071-9.393, p = 0.037). Finally, increased levels of miR-421 can significantly promote cell proliferation, migration, and invasion (p < 0.01).Conclusion:miR-421 is a novel oncogene of PTC and is a valuable prognostic biomarker. Moreover, the upregulation of miR-421 enhances the proliferation, migration, and invasion of PTC cells.

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.

The Fractal and GLCM Textural Parameters of Chromatin May Be Potential Biomarkers of Papillary Thyroid Carcinoma in Hashimoto's Thyroiditis Specimens.

Occasionally, Hashimoto's thyroiditis (HT) and papillary thyroid carcinoma (PTC) share similar nuclear features. The current study aims to quantify the differences between the investigated specimens of HT-associated PTC versus the HT alone, to reduce the subjective experience of an observer, by the use of fractal parameters as well as gray-level co-occurrence matrix (GLCM) textural parameters. We have analyzed 250 segmented nuclei per group (nn = 25 per patient and np = 10 patients per group) using the ImageJ software (NIH, Bethesda, MD, USA) as well as an in-house written code for the GLCM analysis. The mean values of parameters were calculated for each patient. The results demonstrated that the malignant cells from the HT-associated PTC specimens showed lower chromatin fractal dimension (p = 0.0321) and higher lacunarity (p = 0.0038) compared with the corresponding cells from the HT specimens. Also, there was a statistically significant difference between the investigated specimens, in the contrast, correlation, angular second moment, and homogeneity, of the GLCM corresponding to the visual texture of follicular cell chromatin. The differences in chromatin fractal and GLCM parameters could be integrated with other diagnostic methods for the improved evaluation of distinctive features of the HT-associated PTC versus the HT in cytology and surgical pathology specimens.

MiR-7-5pand miR-451 as diagnostic biomarkers for papillary thyroid carcinoma in formalin-fixed paraffin-embedded tissues.

MiR-7-5p and miR-451 are important members of the small RNA family, which have been shown to be significantly downregulated in various human tumors and play a key role in the occurrence and development of tumors. However, little is known about their role in endocrine malignancies. This study aimed to investigate the diagnostic value of miR-7-5p and miR-451 levels in formalin-fixed paraffin-embedded tissues of papillary thyroid carcinoma (PTC) patients, as well as the relationship between clinicopathological characteristics and the two miRNAs. Quantitative real-time PCR (qRT-PCR) was performed to detect the expression levels of miR-7-5p and miR-451 in 101 PTC tissues and in 40 nodular goiter tissues (controls). MiR-7-5p and miR-451 levels were significantly downregulated in PTC patients compared with controls (P < 0.001). MiR-7-5p expression was further downregulated in tumors with larger diameter and advanced tumor stages (all P < 0.05). Moreover, the two miRNAs showed great capability of discriminating PTC patients from controls with 89.5% (miR-7-5p) and 76.8% (miR-451) diagnostic accuracy. Furthermore, according to univariable/multivariate logistic regression, miR-7-5p was significantly associated with PTC (P < 0.001). In conclusion, MiR-7-5p and miR-451 may be used as potential diagnostic biomarkers for identification and validation of PTC patients. Moreover, miR-7-5p appears to be associated with the aggressiveness of PTC.

PIWI-interacting RNAs piR-13643 and piR-21238 are promising diagnostic biomarkers of papillary thyroid carcinoma.

Emerging studies demonstrate that PIWI-interacting RNAs (piRNAs) participate in the development of cancers. 75 pairs of papillary thyroid carcinoma (PTC) samples and 31 benign thyroid nodule samples were included in this three-phase biomarker identifying study. First, piRNA expression profiles of five pairs of PTC samples were acquired piRNA sequencing. The expression of all upregulated piRNAs were further validated by RT-qPCR. Paired t and nonparametric test were used to evaluate the association between all upregulated piRNAs and clinic stage. The expression levels of key piRNAs were corrected by demographic data to construct a multivariate model to distinguish malignant nodules from benign. Additionally, the intersection between target genes of key piRNAs and differentially expressed genes in The Cancer Genome Atlas (TCGA) PTC samples were used to perform enrichment analysis. Only piR-13643 and piR-21238 were significantly upregulated in PTC and associated with clinic stage. Moreover, both piR-13643 (Area Under Curve (AUC): 0.821) and piR-21238 (AUC: 0.823) showed better performance in distinguishing malignant nodules from benign than currently used biomarkers HBME1 (AUC: 0.590). Based on our findings, piR-13643 and piR-21238 were observed to be significantly upregulated in human PTC. PIWI-interacting RNAs could serve as promising novel biomarkers for accurate detection of PTC.

Hypermethylated RASSF1 and SLC5A8 promoters alongside BRAFV600E mutation as biomarkers for papillary thyroid carcinoma.

Circulating cell-free DNA (cfDNA) has been considered as a diagnostic source to track genetic and epigenetic alterations in cancer. We aimed to study mutation in addition to the methylation status in the promoter regions of RASSF1 and SLC5A8 genes in tissues and circulating free DNA samples of patients affected with papillary thyroid carcinoma (PTC) and thyroid nodules as controls. BRAFV600E mutation was studied by ARMS-scorpion real-time polymerase chain reaction method in 57 PTC and 45 thyroid nodule cases. Methylation status of RASSF1 and SLC5A8 promoter regions was analyzed by methylation-specific high-resolution melting curve analysis. BRAFV600E mutation was found in 39 (68.4%) out of 57 PTC tissue samples, while in 33 (49.1%) cases of cfDNA, this mutation was detected. The frequency of BRAFV600E mutation in cfDNA was significantly different between metastatic and nonmetastatic PTC cases (22 of 33 PTC cases vs. 5 of 34 thyroid nodule samples). Methylation levels of three promoter regions of SLC5A8 and proximal promoter region of RASSF1 was significantly different between PTC and thyroid nodule cases in both cfDNA and tissue DNA. In addition, the methylation status of these two genes in tissue DNA was reflected in methylation status observed in cfDNA. This study confirmed that BRAFV600E mutation is better for discrimination between papillary thyroid carcinoma and thyroid nodules. On the other hand, hypermethylation in the more proximal promoter regions to RASSF1 and SLC5A8 genes showed higher sensitivity and more acceptable specificity for this discrimination.

Comprehensive transcriptomic analysis of papillary thyroid cancer: potential biomarkers associated with tumor progression.

Identification of stage-specific prognostic/predictive biomarkers in papillary thyroid carcinoma (PTC) could lead to its more efficient clinical management. The main objective of this study was to characterize the stage-specific deregulation in genes and miRNA expression in PTC to identify potential prognostic biomarkers. 495 RNASeq and 499 miRNASeq PTC samples (stage I-IV) as well as, respectively, 56 and 57 normal samples were retrieved from The Cancer Genome Atlas (TCGA). Differential expression analysis was performed using DESeq2 to identify deregulation of genes and miRNAs between sequential stages. To identify the minority of patients who progress to higher stages, we performed clustering analysis on stage I RNASeq data. An independent PTC RNASeq data set (BioProject accession PRJEB11591) was also used for the validation of the results. LTF and PLA2R1 were identified as two promising biomarkers down-regulated in a subgroup of stage I (both in TCGA and in the validation data set) and in the majority of stage IV of PTC (in TCGA data set). hsa-miR-205, hsa-miR-509-2, hsa-miR-514-1 and hsa-miR-514-2 were also detected as up-regulated miRNAs in both PTC patients with stage I and stage III. Hierarchical clustering of stage I samples showed substantial heterogeneity in the expression pattern of PTC indicating the necessity of categorizing stage I patients based on the expressional alterations of specific biomarkers. Stage I PTC patients showed large amount of expressional heterogeneity. Therefore, risk stratification based on the expressional alterations of candidate biomarkers could be an important step toward personalized management of these patients.

Redox Status and Antioxidative Cofactor Metals Influence Clinical and Pathological Characteristics of Papillary Thyroid Carcinoma and Colloid Goiter.

Papillary thyroid carcinoma (PTC) is the endocrine neoplasm that occurs the most often worldwide, and its molecular pathophysiology is still not well characterized. Redox status is recognized as an important factor of carcinogenesis, but its influence on the PTC's clinical course needs to be better elucidated. The aim of this research was to determine the tissue redox status of 65 PTC and 45 colloid goiter (CG) patients together with antioxidative cofactor metal profiling. The malondialdehyde (MDA) concentration was used to access the prooxidation level, while antioxidant mechanisms were estimated by assaying the activities of superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), and glutathione reductase (GR). The antioxidative cofactor metals included quantification of Se, Cu, Zn, and Mn concentration. PTC tissues had normal prooxidation levels and increased GPx and GR activity. The activity of SOD has been significantly reduced in multicentric PTC dissemination and increased in smokers. SOD activity was directly dependent on MDA levels in CG tissues. CG patients with retrosternal goiter had reduced MDA concentration and SOD activity. Numerous correlations between redox parameters in PTC tissues reveal good co-activation of antioxidative mechanisms and cooperative response on prooxidation. PTC tissues had decreased Se levels and increased concentration of Cu and Mn in comparison to other tissues. MDA concentration and SOD activity were significant predictors of PTC's multicentric dissemination and for the existence of lymph node metastases, respectively. Particularly, the concentration of Cu predicted the retrosternal localization in CG patients. Significant findings presented in this study provide a possibility for development of novel prognostic molecular biomarkers of PTC and CG.

Tumor promoting effects of glucagon receptor: a promising biomarker of papillary thyroid carcinoma via regulating EMT and P38/ERK pathways.

Glucagon is a crucial hormone involved in the maintenance of glucose homeostasis. Large efforts to define the role of glucagon receptor (GCGR) have been continuously made in recent years, but it is still incomplete about its function and mechanism. We performed this study to verify its potential impacts on papillary thyroid carcinoma (PTC) progression. Correlation between GCGR expression and PTC was elaborated using The Cancer Genome Atlas (TCGA) database. The Kaplan-Meier method was used to analyze the connection between GCGR expression and prognosis of PTC patients. GCGR expression was measured by quantitative real-time polymerase chain reaction (qRT-PCR) and western blot analysis; simultaneously, cell viability was elucidated using cell proliferation and colony formation assays following siRNAs strategy. Transwell analyses were conducted to measure the invasion and migration of PTC cells. Flow cytometry analysis was conducted to examine apoptotic ability. The cAMP ELISA kit was employed to measure the cAMP level in PTC cells. Our data determined that the expression level of GCGR was increased in PTC tissues and cells in contrast to normal tissues and Nthy-ori 3-1, respectively. Up-regulated GCGR expression was linked with the lower survival rate in patients with PTC. Functional analysis in vitro suggested that GCGR knockdown attenuated PTC cell proliferation, colony formation, invasion, and migration whilst intensified apoptosis. Down-regulated GCGR was able to increase cAMP level. Furthermore, reduction of GCGR could result in the inactivation of epithelial-mesenchymal transition (EMT) and P38/ERK pathways. In conclusion, the findings of this study disclosed that GCGR promoted PTC cell behaviors by mediating the EMT and P38/ERK pathways, serving as a potential diagnostic and prognostic biomarker as well as therapeutic target for PTC.