A gene expression signature distinguishes normal tissues of sporadic and radiation-induced papillary thyroid carcinomas

T-Box Transcription Factor 22 Is an Immune Microenvironment-Related Biomarker Associated With the BRAF V600E Mutation in Papillary Thyroid Carcinoma

Papillary thyroid cancer (PTC) is the most common malignant disease in endocrine systems. T-box transcription factor 22 (TBX22) is a phylogenetically conserved family member that has not been widely characterized in cancers. In this study, we explored the potential clinical significance and biological functions of TBX22 in PTC. Comprehensive analyses of TBX22 were based on the public databases and our local qRT-PCR cohort. We observed that TBX22 was significantly downregulated in PTC compared with normal tissues. TBX22 was associated with several clinicopathological factors in PTC. Low TBX22 expression correlated with BRAF ^V600E and TERT mutation. Functional enrichment analysis revealed that cancer-related pathways and immune progress were closely associated with TBX22 in PTC. In TBX22-low PTC, high immune infiltration levels with increased CD8⁺ T cells, natural killer, M1 macrophages, and T-regulatory cells were observed. TBX22 was negatively correlated with the activity of different steps of the anticancer immunity cycle. Functionally, overexpression of TBX22 inhibited the proliferation, invasion, and migration in PTC cells, while knocking down of TBX22 showed the opposite effects. The present findings disclose that TBX22, as an immune microenvironment-related biomarker, could be an important tumor suppresser gene and might inform the management of PTC patients better.

Identification and validation of L Antigen Family Member 3 as an immune-related biomarker associated with the progression of papillary thyroid cancer

BACKGROUND

Papillary thyroid cancer (PTC) is heterogeneous cancer with many different immune cells involved in its pathogenesis. L Antigen Family Member 3 (LAGE3) is an ESO/LAGE gene family member that has not been extensively studied in PTC.

METHODS

Comprehensive bioinformatics analyses of LAGE3 were based on The Cancer Genome Atlas, Gene Expression Omnibus, and Genomics of Drug Sensitivity in Cancer (GDSC) databases. We also performed RNA-sequencing on 78 paired samples from local PTC patients.

RESULTS

We observed that LAGE3 was significantly up-regulated in most solid tumor types, including PTC compared with corresponding normal tissues. The high level of LAGE3 was also significantly associated with advanced malignancy. LAGE3 expression was significantly associated with cancer-related pathways, biochemical metabolism, and immune-related terms. Further, tumor microenvironment analysis indicated LAGE3 was positively correlated with different immune cells infiltrating levels and the activity of different steps of the cancer-immunity cycle. Analyses based on the GDSC database revealed that low levels of LAGE3 might be resistant to WZ3105, I-BET-762, and PHA-793887. In addition, the experimental results validated that knocking down LAGE3 could affect proliferation, migration, and invasion in the PTC cell lines.

CONCLUSION

This study discloses that LAGE3 plays an oncogenic and cancer-immunological role, also providing novel PTC biological and clinical implications.

Impact of Lin28 on lymph node metastasis in papillary thyroid carcinoma

Lin28 is involved in the progression of several types of tumors. Data collected from clinical trials have suggested that Lin28 expression is correlated with poor prognosis in thyroid carcinoma. The present study was conducted to investigate the association between Lin28 expression and the clinicopathological parameters of papillary thyroid carcinoma (PTC). Accordingly, the clinical data and diagnostic results from 237 patients with PTC were collected. Immunohistochemical staining was performed to evaluate the Lin28 expression levels in thyroid tissue samples. Associations between the expression levels and clinicopathological parameters were evaluated. Lin28 was expressed in 96/237 (40.5%) of PTC specimens. Compared with patients with no Lin28 expression, patients with expression had higher rates of lymph node metastasis (P<0.001) and larger tumors (P=0.011). Multivariate analysis revealed that Lin28 was associated with lymph node metastasis. Next, bioinformatics analysis was performed based using the Gene Expression Omnibus database and The Cancer Genome Atlas database. Lin28 expression was associated with aggressive tumor characteristics, such as lymph node metastasis and larger tumors. In conclusion, the present study revealed that Lin28 expression served as a risk factor for lymph node metastasis. Accordingly, Lin28 expression may be used as a prognostic marker to predict lymph node metastasis in patients with PTC. In addition, Lin28 may serve as a therapeutic target in the management of this tumor type, which may help improve patient outcomes.

The molecular and gene/miRNA expression profiles of radioiodine resistant papillary thyroid cancer

Background

Papillary thyroid cancer (PTC) is the most frequent endocrine tumor. Radioiodine (RAI) treatment is highly effective in these tumors, but up to 60% of metastatic cases become RAI-refractory. Scanty data are available on either the molecular pattern of radioiodine refractory papillary thyroid cancers (PTC) or the mechanisms responsible for RAI resistance.

Methods

We analyzed the molecular profile and gene/miRNA expression in primary PTCs, synchronous and RAI-refractory lymph node metastases (LNMs) in correlation to RAI avidity or refractoriness.

We classified patients as RAI+/D+ (RAI uptake/disease persistence), RAI−/D+ (absent RAI uptake/disease persistence), and RAI+/D- (RAI uptake/disease remission), and analyzed the molecular and gene/miRNA profiles, and the expression of thyroid differentiation (TD) related genes.

Results

A different molecular profile according to the RAI class was observed: BRAF^V600E cases were more frequent in RAI−/D+ (P = 0.032), and fusion genes in RAI+/D+ cases. RAI+/D- patients were less frequently pTERT mutations positive, and more frequently wild type for the tested mutations/fusions. Expression profiles clearly distinguished PTC from normal thyroid. On the other hand, in refractory cases (RAI+/D+ and RAI−/D+) no distinctive PTC expression patterns were associated with either tissue type, or RAI uptake, but with the driving lesion and BRAF−/RAS-like subtype. Primary tumors and RAI-refractory LNMs with BRAF^V600E mutation display transcriptome similarity suggesting that RAI minimally affects the expression profiles of RAI-refractory metastases. Molecular profiles associated with the expression of TPO, SLC26A4 and TD genes, that were found more downregulated in BRAF^V600E than in gene fusions tumors.

Conclusions

The present data indicate a different molecular profile in RAI-avid and RAI-refractory metastatic PTCs. Moreover, BRAF^V600E tumors displayed reduced differentiation and intrinsic RAI refractoriness, while PTCs with fusion oncogenes are RAI-avid but persistent, suggesting different oncogene-driven mechanisms leading to RAI refractoriness.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-020-01757-x.

Identification of Hub Genes in Anaplastic Thyroid Carcinoma: Evidence From Bioinformatics Analysis

Anaplastic thyroid carcinoma (ATC) is a rare type of thyroid cancer that results in fatal clinical outcomes; the pathogenesis of this life-threatening disease has yet to be fully elucidated. This study aims to identify the hub genes of ATC that may play key roles in ATC development and could serve as prognostic biomarkers or therapeutic targets. Two microarray datasets (GSE33630 and GSE53072) were obtained from the Gene Expression Omnibus database; these sets included 16 ATC and 49 normal thyroid samples. Differential expression analyses were performed for each dataset, and 420 genes were screened as common differentially expressed genes using the robust rank aggregation method. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted to explore the potential bio-functions of these differentially expressed genes (DEGs). The terms and enriched pathways were primarily associated with cell cycle, cell adhesion, and cancer-related signaling pathways. Furthermore, a protein-protein interaction network of DEG expression products was constructed using Cytoscape. Based on the whole network, we identified 7 hub genes that included CDK1, TOP2A, CDC20, KIF11, CCNA2, NUSAP1, and KIF2C. The expression levels of these hub genes were validated using quantitative polymerase chain reaction analyses of clinical specimens. In conclusion, the present study identified several key genes that are involved in ATC development and provides novel insights into the understanding of the molecular mechanisms of ATC development.

The differences of regulatory networks between papillary and anaplastic thyroid carcinoma: an integrative transcriptomics study

BACKGROUND

Unlike papillary thyroid cancer (PTC), anaplastic thyroid carcinoma (ATC) is extremely aggressive and rapidly lethal without effective therapies. However, the differences of master regulators and regulatory networks between PTC and ATC remain unclear. Methods: Three representative datasets comprising 32 ATC, 69 PTC, and 78 normal thyroid tissue samples were combined to form a large dataset. Differentially expressed genes (DEGs) were identified and enriched by limma package and gene set enrichment analysis, respectively. Subsequently, protein-protein interaction network and transcription factors (TFs) regulatory network were constructed to identify gene modules and master regulators. Further, master regulators were validated by RT-PCR and western blot. Finally, Kaplan-Meier plotter was applied to evaluate their prognostic values. Results: A total of 560 DEGs were identified as ATC-specific malignant signature. The regulatory network analysis showed that nine master regulators were significantly correlated with three gene modules and potentially regulated the expression of DEGs in three gene modules, respectively. Furthermore, CREB3L1, FOSL2, E2F1 and CAT were significantly associated with overall survival of thyroid cancer patients. FOXM1, FOSL2, MYBL2, AVEN and E2F1 were unfavorable factors of recurrence-free survival (RFS), while CAT was a favorable factor of RFS. RT-PCR and western blot confirmed that six TFs were obviously up-regulated in ATC tissues/cell line as compared with PTC and normal thyroid tissues/cell lines, respectively. In addition, 19 ATC-specific kinases were identified to illustrate the potential post-translational modification. Conclusions: Our findings provide a comprehensive insight into malignant mechanism of ATC, which may indicate their value in the future investigation of ATC.

Transcriptome network of the papillary thyroid carcinoma radiation marker CLIP2

Background

We present a functional gene association network of the CLIP2 gene, generated by de-novo reconstruction from transcriptomic microarray data. CLIP2 was previously identified as a potential marker for radiation induced papillary thyroid carcinoma (PTC) of young patients in the aftermath of the Chernobyl reactor accident. Considering the rising thyroid cancer incidence rates in western societies, potentially related to medical radiation exposure, the functional characterization of CLIP2 is of relevance and contributes to the knowledge about radiation-induced thyroid malignancies.

Methods

We generated a transcriptomic mRNA expression data set from a CLIP2-perturbed thyroid cancer cell line (TPC-1) with induced CLIP2 mRNA overexpression and siRNA knockdown, respectively, followed by gene-association network reconstruction using the partial correlation-based approach GeneNet. Furthermore, we investigated different approaches for prioritizing differentially expressed genes for network reconstruction and compared the resulting networks with existing functional interaction networks from the Reactome, Biogrid and STRING databases. The derived CLIP2 interaction partners were validated on transcript and protein level.

Results

The best reconstructed network with regard to selection parameters contained a set of 20 genes in the 1st neighborhood of CLIP2 and suggests involvement of CLIP2 in the biological processes DNA repair/maintenance, chromosomal instability, promotion of proliferation and metastasis. Peptidylprolyl Isomerase Like 3 (PPIL3), previously identified as a potential direct interaction partner of CLIP2, was confirmed in this study by co-expression at the transcript and protein level.

Conclusion

In our study we present an optimized preselection approach for genes subjected to gene-association network reconstruction, which was applied to CLIP2 perturbation transcriptome data of a thyroid cancer cell culture model. Our data support the potential carcinogenic role of CLIP2 overexpression in radiation-induced PTC and further suggest potential interaction partners of the gene.

Downregulation of miR‑193a‑3p via targeting cyclin D1 in thyroid cancer

Thyroid cancer (TC) is a frequently occurring malignant tumor with a rising steadily incidence. microRNA (miRNA/miR)‑193a‑3p is an miRNA that is associated with tumors, playing a crucial role in the genesis and progression of various cancers. However, the expression levels of miR‑193a‑3p and its molecular mechanisms in TC remain to be elucidated. The present study aimed to probe the expression of miR‑193a‑3p and its clinical significance in TC, including its underlying molecular mechanisms. Microarray and RNA sequencing data gathered from three major databases, specifically Gene Expression Omnibus (GEO), ArrayExpress and The Cancer Genome Atlas (TCGA) databases, and the relevant data from the literature were used to examine miR‑193a‑3p expression. Meta‑analysis was also conducted to evaluate the association between clinicopathological parameters and miR‑193a‑3p in 510 TC and 59 normal samples from the TCGA database. miRWalk 3.0, and the TCGA and GEO databases were used to predict the candidate target genes of miR‑193a‑3p. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes and protein‑protein interaction network enrichment analyses were conducted by using the predicted candidate target genes to investigate the underlying carcinogenic mechanisms. A dual luciferase assay was performed to validate the targeting regulatory association between the most important hub gene cyclin D1 (CCND1) and miR‑193a‑3p. miR‑193a‑3p expression was considerably downregulated in TC compared with in the non‑cancer controls (P<0.001). The area under the curve of the summary receiver operating characteristic was 0.80. Downregulation of miR‑193a‑3p was also significantly associated with age, sex and metastasis (P=0.020, 0.044 and 0.048, respectively). Bioinformatics analysis indicated that a low miR‑193a‑3p expression may augment CCND1 expression to affect the biological processes of TC. In addition, CCND1, as a straightforward target, was validated through a dual luciferase assay. miR‑193a‑3p and CCND1 may serve as prognostic biomarkers of TC. Finally, miR‑193a‑3p may possess a crucial role in the genesis and progression of TC by altering the CCND1 expression.

Biologically-based modeling of radiation risk and biomarker prevalence for papillary thyroid cancer in Japanese a-bomb survivors 1958-2005

PURPOSE

Thyroid cancer of papillary histology (PTC) is the dominant type in radio-epidemiological cohorts established after nuclear accidents or warfare. Studies on post-Chernobyl PTC and on thyroid cancer in the life span study (LSS) of Japanese a-bomb survivors consistently revealed high radiation risk after exposure during childhood and adolescence. For post-Chernobyl risk assessment overexpression of the CLIP2 gene was proposed as molecular biomarker to separate radiogenic from sporadic PTC. Based on such binary marker a biologically-based risk model of PTC carcinogenesis has been developed for observational Chernobyl data. The model featured two independent molecular pathways of disease development, of which one was associated with radiation exposure. To gain credibility the concept for a mechanistic risk model must be based on general biological features which transcend findings in a single cohort. The purpose of the present study is therefore to demonstrate portability of the model concept by application to PTC incidence data in the LSS. By exploiting the molecular two-path concept we improve the determination of the probability of radiation causing cancer (POC).

MATERIALS AND METHODS

The current analysis uses thyroid cancer incidence data of the LSS with thyroid cancer diagnoses and papillary histology (n = 292) from the follow-up period between 1958 and 2005. Risk analysis was performed with both descriptive and biologically-based models.

RESULTS

Judged by goodness-of-fit all applied models described the data almost equally well. They yielded similar risk estimates in cohorts post-Chernobyl and LSS. The preferred mechanistic model was selected by biological plausibility. It reflected important features of an imperfect radiation marker which are not easily addressed by descriptive models. Precise model predictions of marker prevalence in strata of epidemiological covariables can be tested by molecular measurements. Application of the radiation-related molecular pathway from our preferred model in retrospective risk assessment decreases the threshold dose for 50% POC from 0.33 (95% confidence interval (CI) 0.18; 0.64) Gy to 0.04 (95% CI 0.01; 0.19) Gy for females and from 0.43 (95% CI 0.17; 1.84) Gy to 0.19 (95% CI 0.05; 1.00) Gy for males. These improvements are still not sufficient to separate radiation-induced from sporadic PTC cases at very low doses <0.015 Gy typical for the Fukushima accident.

CONCLUSIONS

Successful application of our preferred mechanistic model to LSS incidence data confirms and improves the biological two-path concept of radiation-induced PTC. Model predictions suggest further molecular validation studies to consolidate the basis of biologically-based risk estimation.

The role of dual oxidases in physiology and cancer

NOX/DUOX enzymes are transmembrane proteins that carry electrons through biological membranes generating reactive oxygen species. The NOX family is composed of seven members, which are NOX1 to NOX5 and DUOX1 and 2. DUOX enzymes were initially called thyroid oxidases, based on their high expression level in the thyroid tissue. However, DUOX expression has been documented in several extrathyroid tissues, mostly at the apical membrane of the salivary glands, the airways, and the intestinal tract, revealing additional cellular functions associated with DUOX-related H2O2 generation. In this review, we will briefly summarize the current knowledge regarding DUOX structure and physiological functions, as well as their possible role in cancer biology.

Aging-associated genes TNFRSF12A and CHI3L1 contribute to thyroid cancer: An evidence for the involvement of hypoxia as a driver

The prevalence of thyroid cancer (TC) is high in the elderly. The present study was based on the hypothesis that genes, which have increased activity with aging, may play a role in the development of TC. A large-scale literature-based data analysis was conducted to explore the genes that are implicated in both TC and aging. Subsequently, a mega-analysis of 16 RNA expression datasets (1,222 samples: 439 healthy controls, and 783 patients with TC) was conducted to test a set of genes associated with aging but not TC. To uncover a possible link between these genes and TC, a functional pathway analysis was conducted, and the results were validated by analysis of gene co-expression. A multiple linear regression (MLR) model was employed to study the possible influence of sample size, population region and study age on the gene expression levels in TC. A total of 262 and 816 genes were identified to have increased activity with aging and TC, respectively; with a significant overlap of 63 genes (P<3.82×10⁻³⁵). The mega-analysis revealed two aging-associated genes (CHI3L1 and TNFRSF12A) to be significantly associated with TC (P<2.05×10⁻⁸), and identified the association with multiple hypoxia-driven pathways through functional pathway analysis, also confirmed by the co-expression analysis. The MLR analysis identified population region as a significant factor contributing to the expression levels of CHI3L1 and TNFRSF12A in TC samples (P<3.24×10⁻⁴). The determination of genes that promote aging was warranted due to their possible involvement in TC. The present study suggests CHI3L1 and TNFRSF12A as novel common risk genes associated with both aging and TC.

Identification of hub genes in papillary thyroid carcinoma: robust rank aggregation and weighted gene co-expression network analysis

BACKGROUND

Papillary thyroid carcinoma (PTC), which is the most common endocrine malignancy, has been steadily increasing worldwide in incidence over the years, while mechanisms underlying the pathogenesis and diagnostic for PTC are incomplete. The purpose of this study is to identify potential biomarkers for diagnosis of PTC, and provide new insights into pathogenesis of PTC.

METHODS

Based on weighted gene co-expression network analysis, Robust Rank Aggregation, functional annotation, GSEA and DNA methylation, were employed for investigating potential biomarkers for diagnosis of PTC.

RESULTS

Black and turquoise modules were identified in the gene co-expression network constructed by 1807 DEGs that from 6 eligible gene expression profiles of Gene Expression Omnibus database based on Robust Rank Aggregation and weighted gene co-expression network analysis. Hub genes were significantly down-regulated and the expression levels of the hub genes were different in different stages in hub gene verification. ROC curves indicated all hub genes had good diagnostic value for PTC (except for ABCA6 AUC = 89.5%, the 15 genes with AUC > 90%). Methylation analysis showed that hub gene verification ABCA6, ACACB, RMDN1 and TFPI were identified as differentially methylated genes, and the decreased expression level of these genes may relate to abnormal DNA methylation. Moreover, the expression levels of 8 top hub genes were correlated with tumor purity and tumor-infiltrating immune cells. These findings, including functional annotations and GSEA provide new insights into pathogenesis of PTC.

CONCLUSIONS

The hub genes and methylation of hub genes may as potential biomarkers provide new insights for diagnosis of PTC, and all these findings may be the direction to study the mechanisms underlying of PTC in the future.

Clinicopathological value and underlying molecular mechanism of annexin A2 in 992 cases of thyroid carcinoma

BACKGROUND

Thyroid carcinoma (THCA) is one of the most frequent endocrine cancers and has increasing morbidity. Annexin A2 (ANXA2) has been found to be highly expressed in various cancers; however, its expression level and potential mechanism in THCA remain unknown. This study investigated the clinicopathological value and primary molecular machinery of ANXA2 in THCA.

MATERIAL AND METHODS

Public RNA-sequencing and microarray data were obtained and analyzed with ANXA2 expression in THCA and corresponding non-cancerous thyroid tissue. A Pearson correlation coefficient calculation was used for the acquisition of ANXA2 coexpressed genes, while edgR, limma, and Robust Rank Aggregation were employed for differentially expressed gene (DEG) in THCA. The probable mechanism of ANXA2 in THCA was predicted by gene ontology and pathway enrichment. A dual-luciferase reporter assay was employed to confirm the targeting relationships between ANXA2 and its predicted microRNA (miRNA).

RESULTS

Expression of ANXA2 was significantly upregulated in THCA tissues with a summarized standardized mean difference of 1.09 (P < 0.0001) based on 992 THCA cases and 589 cases of normal thyroid tissue. Expression of ANXA2 was related to pathologic stage. Subsequently, 1442 genes were obtained when overlapping 4542 ANXA2 coexpressed genes with 2248 DEGs in THCA; these genes were mostly enriched in pathways of extracellular matrix-receptor interaction, cell adhesion molecules, and complement and coagulation cascades. MiR-23b-3p was confirmed to target ANXA2 by dual-luciferase reporter assay.

CONCLUSIONS

Upregulated expression of ANXA2 may promote the malignant biological behavior of THCA by affecting the involving pathways or being targeted by miR-23b-3p.

Immune gene signature delineates a subclass of thyroid cancer with unfavorable clinical outcomes

Thyroid cancer (THCA) is a heterogeneous disease with multiple clinical outcomes Immune cells regulate its progression. Three immunomolecular subtypes (C1, C2, C3) were identified in gene expression data sets from TCGA and GEO databases. Among them, subtype C3 had highest frequency of BRAF mutations, lowest frequency of RAS mutations, highest mutation load and shorter progression-free survival. Functional enrichment analysis for the genes revealed that C1 was up-regulated in the ERK cascade pathway, C2 was up-regulated in cell migration and proliferation pathways, while C3 was enriched in body fluid, protein regulation and response to steroid hormones functions. Notably, the three molecular subtypes exhibit differences in immune microenvironments as shown by timer database and analysis of immune expression signatures. The abundance of B_cell, CD4_Tcell, Neutrophil, Macrophage and Dendritic cells in C2 subtype were lower than in C1 and C3 subtypes Leukocyte fraction, proliferation macrophage regulation, lymphocyte infiltration, IFN gamma response and TGF beta response scores were significantly higher in C3 compared with C1 and C2 subtypes. Unlike C3 subtype, it was observed that C1 and C2 subtypes were significantly negatively correlated with most immune checkpoint genes in two different cohorts. The characteristic genes were differentially expressed between cancer cells, adjacent tissues, and metastatic tissues in different cohorts. In summary, THCA can be subclassified into three molecular subtypes with distinct histological types, genetic and transcriptional phenotypes, all of which have potential clinical implications.

Identification of Potential Biomarkers for Thyroid Cancer Using Bioinformatics Strategy: A Study Based on GEO Datasets

Background

The molecular mechanisms and genetic markers of thyroid cancer are unclear. In this study, we used bioinformatics to screen for key genes and pathways associated with thyroid cancer development and to reveal its potential molecular mechanisms.

Methods

The GSE3467, GSE3678, GSE33630, and GSE53157 expression profiles downloaded from the Gene Expression Omnibus database (GEO) contained a total of 164 tissue samples (64 normal thyroid tissue samples and 100 thyroid cancer samples). The four datasets were integrated and analyzed by the RobustRankAggreg (RRA) method to obtain differentially expressed genes (DEGs). Using these DEGs, we performed gene ontology (GO) functional annotation, pathway analysis, protein-protein interaction (PPI) analysis and survival analysis. Then, CMap was used to identify the candidate small molecules that might reverse thyroid cancer gene expression.

Results

By integrating the four datasets, 330 DEGs, including 154 upregulated and 176 downregulated genes, were identified. GO analysis showed that the upregulated genes were mainly involved in extracellular region, extracellular exosome, and heparin binding. The downregulated genes were mainly concentrated in thyroid hormone generation and proteinaceous extracellular matrix. Pathway analysis showed that the upregulated DEGs were mainly attached to ECM-receptor interaction, p53 signaling pathway, and TGF-beta signaling pathway. Downregulation of DEGs was mainly involved in tyrosine metabolism, mineral absorption, and thyroxine biosynthesis. Among the top 30 hub genes obtained in PPI network, the expression levels of FN1, NMU, CHRDL1, GNAI1, ITGA2, GNA14 and AVPR1A were associated with the prognosis of thyroid cancer. Finally, four small molecules that could reverse the gene expression induced by thyroid cancer, namely ikarugamycin, adrenosterone, hexamethonium bromide and clofazimine, were obtained in the CMap database.

Conclusion

The identification of the key genes and pathways enhances the understanding of the molecular mechanisms for thyroid cancer. In addition, these key genes may be potential therapeutic targets and biomarkers for the treatment of thyroid cancer.

Dissecting the Role of Thyrotropin in the DNA Damage Response in Human Thyrocytes after 131I, γ Radiation and H2O2

BACKGROUND

The early molecular events in human thyrocytes after 131I exposure have not yet been unravelled. Therefore, we investigated the role of TSH in the 131I-induced DNA damage response and gene expression in primary cultured human thyrocytes.

METHODS

Following exposure of thyrocytes, in the presence or absence of TSH, to 131I (β radiation), γ radiation (3 Gy), and hydrogen peroxide (H2O2), we assessed DNA damage, proliferation, and cell-cycle status. We conducted RNA sequencing to profile gene expression after each type of exposure and evaluated the influence of TSH on each transcriptomic response.

RESULTS

Overall, the thyrocyte responses following exposure to β or γ radiation and to H2O2 were similar. However, TSH increased 131I-induced DNA damage, an effect partially diminished after iodide uptake inhibition. Specifically, TSH increased the number of DNA double-strand breaks in nonexposed thyrocytes and thus predisposed them to greater damage following 131I exposure. This effect most likely occurred via Gα q cascade and a rise in intracellular reactive oxygen species (ROS) levels. β and γ radiation prolonged thyroid cell-cycle arrest to a similar extent without sign of apoptosis. The gene expression profiles of thyrocytes exposed to β/γ radiation or H2O2 were overlapping. Modulations in genes involved in inflammatory response, apoptosis, and proliferation were observed. TSH increased the number and intensity of modulation of differentially expressed genes after 131I exposure.

CONCLUSIONS

TSH specifically increased 131I-induced DNA damage probably via a rise in ROS levels and produced a more prominent transcriptomic response after exposure to 131I.

Clinical Significance and Potential Regulatory Mechanisms of Serum Response Factor in 1118 Cases of Thyroid Cancer Based on Gene Chip and RNA-Sequencing Data

Background

Thyroid cancer (TC) is one of the most prevalent endocrine malignancies and there may be many unclarified molecular events and gene types involved in TC. The objective of this study was to assess the clinical implications and potential mechanisms of serum response factor (SRF) in TC.

Material/Methods

RNA-sequencing and gene chip data with TC expression were collected from The Cancer Genome Atlas/Genotype-Tissue Expression, Gene Expression Omnibus, ArrayExpress, Sequence Read Archive, and Oncomine. SRF expression of all TC and adjacent non-cancerous tissue were calculated using the t test, STATA, and Meta-DiSc. The related pathways of the potential SRF target genes and target miRNAs were explored. Dual-luciferase reporter assay was performed to validate the association between SRF and its putative miRNA.

Results

One RNA-sequencing and 15 gene chips were collected, and the pooled standardized mean difference of SRF was −1.00. Furthermore, the area under the curve of sROC of SRF in TC was 0.8251, indicating a dramatic decreased expression of SRF in TC tissues based on 1118 cases. The intersection of differentially expressed genes in TC, SRF co-expressed genes, and SRF potential target genes achieved from Cistrome Cancer led to 169 overlapped genes. miR-330-5p was predicted to target SRF, which was further confirmed by dual-luciferase reporter assay.

Conclusions

The reduction of SRF appears to play a crucial role in the origin of TC. These properties are accomplished by the target genes of SRF, as a transcription factor, or by the axes with the associated miRNAs.

Cancer Associated Fibroblasts and Senescent Thyroid Cells in the Invasive Front of Thyroid Carcinoma

Thyroid carcinoma (TC) comprises several histotypes with different aggressiveness, from well (papillary carcinoma, PTC) to less differentiated forms (poorly differentiated and anaplastic thyroid carcinoma, PDTC and ATC, respectively). Previous reports have suggested a functional role for cancer-associated fibroblasts (CAFs) or senescent TC cells in the progression of PTC. In this study, we investigated the presence of CAFs and senescent cells in proprietary human TCs including PTC, PDTC, and ATC. Screening for the driving lesions BRAFV600E and N/H/KRAS mutations, and gene fusions was also performed to correlate results with tumor genotype. In samples with unidentified drivers, transcriptomic profiles were used to establish a BRAF- or RAS-like molecular subtype based on a gene signature derived from The Cancer Genome Atlas. By using immunohistochemistry, we found co-occurrence of stromal CAFs and senescent TC cells at the tumor invasive front, where deposition of collagen (COL1A1) and expression of lysyl oxidase (LOX) enzyme were also detected, in association with features of local invasion. Concurrent high expression of CAFs and of the senescent TC cells markers, COL1A1 and LOX was confirmed in different TC histotypes in proprietary and public gene sets derived from Gene Expression Omnibus (GEO) repository, and especially in BRAF mutated or BRAF-like tumors. In this study, we show that CAFs and senescent TC cells co-occur in various histotypes of BRAF-driven thyroid tumors and localize at the tumor invasive front.

BCL2 and hsa-miR-181a-5p are potential biomarkers associated with papillary thyroid cancer based on bioinformatics analysis

Background

The morbidity of thyroid carcinoma has been rising worldwide and increasing faster than any other cancer type. The most common subtype with the best prognosis is papillary thyroid cancer (PTC); however, the exact molecular pathogenesis of PTC is still not completely understood.

Methods

In the current study, 3 gene expression datasets (GSE3678, GSE3467, and GSE33630) and 2 miRNA expression datasets (GSE113629 and GSE73182) of PTC were selected from the Gene Expression Omnibus (GEO) database and were further used to identify differentially expressed genes (DEGs) and deregulated miRNAs between normal thyroid tissue samples and PTC samples. Then, Gene Ontology (GO) and pathway enrichment analyses were conducted, and a protein-protein interaction (PPI) network was constructed to explore the potential mechanism of PTC carcinogenesis. The hub gene detection was performed using the CentiScaPe v2.0 plugin, and significant modules were discovered using the MCODE plugin for Cytoscape. In addition, a miRNA-gene regulatory network in PTC was constructed using common deregulated miRNAs and DEGs.

Results

A total of 263 common DEGs and 12 common deregulated miRNAs were identified. Then, 6 significant KEGG pathways (P < 0.05) and 82 significant GO terms were found to be enriched, indicating that PTC was closely related to amino acid metabolism, development, immune system, and endocrine system. In addition, by constructing a PPI network and miRNA-gene regulatory network, we found that hsa-miR-181a-5p regulated the most DEGs, while BCL2 was targeted by the most miRNAs.

Conclusions

The results of this study suggested that hsa-miR-181a-5p and BCL2 and their regulatory networks may play important roles in the pathogenesis of PTC.

LncRNAs SNHG12 and LINC00152 were associated with progression of patients with papillary thyroid carcinoma

Aim: To investigate the clinical roles of LINC00152 and SNHG12 in papillary thyroid carcinoma (PTC). Methods: LINC00152 and SNHG12 expression was sought and analysis in gene expression omnibus, The Cancer Genome Atlas and GEPIA datasets. Tumor and adjacent normal tissues were collected from 97 PTC and 44 benign thyroid nodules patients. The expression was evaluated by quantitative real-time polymerase chain reaction. The association between the expression level and clinicopathologic characteristics was analyzed by χ² test. Receiver operating characteristic curves were plotted to evaluate the diagnostic value. Results: The expression of SNHG12 and LINC00152 were significantly higher in PTC tissues than in adjacent normal tissues not only in gene expression omnibus database but the validated samples. More interesting, LINC00152 expression level was also significantly higher in PTC tissues than that in benign thyroid nodules. The upregulation of LINC00152 and SNHG12 was associated with the malignant progression of PTC. Receiver operating characteristic curve analysis also demonstrated that there was a good trend, which indicates that they may have certain diagnostic value. Conclusion: LINC00152 and SNHG12 might serve as serve as potential related molecules of PTC.

Bioinformatics analysis to screen key genes in papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common type of thyroid carcinoma, and its incidence has been on the increase in recent years. However, the molecular mechanism of PTC is unclear and misdiagnosis remains a major issue. Therefore, the present study aimed to investigate this mechanism, and to identify key prognostic biomarkers. Integrated analysis was used to explore differentially expressed genes (DEGs) between PTC and healthy thyroid tissue. To investigate the functions and pathways associated with DEGs, Gene Ontology, pathway and protein-protein interaction (PPI) network analyses were performed. The predictive accuracy of DEGs was evaluated using the receiver operating characteristic (ROC) curve. Based on the four microarray datasets obtained from the Gene Expression Omnibus database, namely GSE33630, GSE27155, GSE3467 and GSE3678, a total of 153 DEGs were identified, including 66 upregulated and 87 downregulated DEGs in PTC compared with controls. These DEGs were significantly enriched in cancer-related pathways and the phosphoinositide 3-kinase-AKT signaling pathway. PPI network analysis screened out key genes, including acetyl-CoA carboxylase beta, cyclin D1, BCL2, and serpin peptidase inhibitor clade A member 1, which may serve important roles in PTC pathogenesis. ROC analysis revealed that these DEGs had excellent predictive performance, thus verifying their potential for clinical diagnosis. Taken together, the findings of the present study suggest that these genes and related pathways are involved in key events of PTC progression and facilitate the identification of prognostic biomarkers.

Transcriptome Analyses Identify a Metabolic Gene Signature Indicative of Dedifferentiation of Papillary Thyroid Cancer

CONTEXT

Metabolic reprogramming is a common feature of tumorigenesis. It remains unknown concerning the expression pattern of metabolism-associated genes in dedifferentiated thyroid cancer (DDTC).

OBJECTIVE

This study aimed to identify a useful signature to indicate dedifferentiation of papillary thyroid cancer (PTC).

DESIGN AND SETTING

We used one discovery and two validation cohorts to screen out aberrant metabolic genes in DDTC, and further used The Cancer Genome Atlas (TCGA) cohort to search for independent risk factors for the low-differentiated phenotype of PTC as a signature of dedifferentiation. The prediction of the signature for DDTC was validated in the TCGA cohort and the combined Gene Expression Omnibus cohort. We also analyzed the correlations of the signature risk score with clinicopathological features of PTC. Gene set enrichment analyses were performed in the TCGA cohort.

RESULTS

Significant enrichment of metabolic pathways correlated with differentiation status of PTC. A signature of metabolic genes including LPCAT2, ACOT7, HSD17B8, PDE8B, and ST3GAL1 was discovered and validated across three cohorts. The signature was not only predictive of DDTC but also significantly associated with BRAFV600E mutation (P < 0.001), T3/T4 stage (P < 0.001), extrathyroidal extension (P < 0.001), lymph node metastasis (P < 0.001), and tumor/lymph node/metastasis III/IV stage (P < 0.001) in PTC. Downregulations of LPCAT2 expression (P = 0.009) and ST3GAL1 expression (P = 0.005) increased risks of decreased disease-free survival for patients. Furthermore, the signature was implicated in a number of oncogenic biological pathways.

CONCLUSIONS

Our findings suggest that metabolic deregulations mediate dedifferentiation of PTC, and that the metabolic gene signature can be used as a biomarker for DDTC.

Long non-coding RNA small nucleolar RNA host gene 7 is upregulated and promotes cell proliferation in thyroid cancer

Thyroid cancer (THCA) is one of the most common types of endocrine cancer worldwide. However, the mechanisms underlying THCA progression have not been fully elucidated. Recent studies have demonstrated that long non-coding RNAs (lncRNAs) are dysregulated in human diseases, and are involved in regulating various biological processes. Furthermore, several reports have indicated that lncRNAs serve important roles in THCA. In the present study, a dataset from The Cancer Genome Atlas was used to analyze the expression levels and the clinical information of small nucleolar RNA host gene 7 (SNHG7) in THCA. Starbase was used to construct the competing endogenous RNA network. The Molecule Annotation System was used to analyze the data from Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. Furthermore, cell proliferation and cell cycle assays were used to detect the functions of SNHG7 in THCA. The present study revealed for the first time, to the best of our knowledge, that SNHG7 is markedly upregulated in THCA samples following analysis of The Cancer Genome Atlas datasets. SNHG7 expression was higher in advanced stage compared with early stage THCA samples. In addition, high expression levels of SNHG7 were associated with shorter survival times in THCA patients compared with low expression levels. Bioinformatics analysis revealed that SNHG7 was associated with the processes of ‘protein translation’, ‘viral life cycle’, ‘RNA processing’, ‘mRNA splicing’, ‘histone ubiquitination’, ‘endoplasmic reticulum-to-Golgi vesicle-mediated transport’, ‘sister chromatid cohesion’, ‘DNA damage checkpoint regulation’, ‘translation’ and ‘the spliceosome’. Additionally, knockdown of SNHG7 significantly inhibited thyroid cancer cell proliferation and cell cycle progression in vitro. Taken together, the results obtained in the present study suggested that SNHG7 may serve as a novel therapeutic and prognostic target for THCA.

Senescent thyrocytes and thyroid tumor cells induce M2-like macrophage polarization of human monocytes via a PGE2-dependent mechanism

BACKGROUND

Thyroid carcinoma includes several variants characterized by different biological and clinical features: from indolent microcarcinoma to undifferentiated and aggressive anaplastic carcinoma. Inflammation plays a critical role in thyroid tumors. Conditions predisposing to cancer, as well as oncogene activity, contribute to the construction of an inflammatory microenvironment that facilitates thyroid tumor progression. Moreover, oncogene-induced senescence, a mechanism tightly connected with inflammation, and able to restrain or promote cancer progression, is involved in thyroid cancer. The interactions between thyroid tumor cells and the microenvironment are not completely clarified.

METHODS

We characterize in vitro the interplay between macrophages and senescent thyrocytes and tumor-derived cell lines, modeling early and late thyroid tumor stages, respectively. Purified peripheral blood-derived human monocytes were exposed to thyroid cell-derived conditioned medium (CM) and assessed for phenotype by flow cytometry. The factors secreted by thyroid cells and macrophages were identified by gene expression analysis and ELISA. The protumoral effect of macrophages was assessed by wound healing assay on K1 thyroid tumor cells. The expression of PTGS2 and M2 markers in thyroid tumors was investigated in publicly available datasets.

RESULTS

Human monocytes exposed to CM from senescent thyrocytes and thyroid tumor cell lines undergo M2-like polarization, showing high CD206 and low MHC II markers, and upregulation of CCL17 secretion. The obtained M2-like macrophages displayed tumor-promoting activity. Among genes overexpressed in polarizing cells, we identified the prostaglandin-endoperoxide synthase enzyme (PTGS2/COX-2), which is involved in the production of prostaglandin E2 (PGE2). By using COX-2 inhibitors we demonstrated that the M2-like polarization ability of thyroid cells is related to the production of PGE2. Co-expression of PTGS2 and M2 markers is observed a significant fraction of human thyroid tumors.

CONCLUSIONS

Our results demonstrate that both senescent thyrocytes and thyroid tumor cell lines trigger M2-like macrophage polarization that is related to PGE2 secretion. This suggests that the interaction with the microenvironment occurs at both early and late thyroid tumor stages, and favors tumor progression. The co-expression of PTGS2 gene and M2 markers in human thyroid carcinoma highlights the possibility to counteract tumor growth through COX-2 inhibition.

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

Background

Thyroid 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/Methods

We 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.

Results

We 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.

Conclusions

Our study suggested ZFAS1 could serve as a biomarker for thyroid cancer.

Identification of a Five-Gene Signature and Establishment of a Prognostic Nomogram to Predict Progression-Free Interval of Papillary Thyroid Carcinoma

Background: The incidence of papillary thyroid carcinoma (PTC) is high and increasing worldwide. Although prognosis is relatively good, it is important to select the minority of patients with poorer prognosis to avoid side effects associated with unnecessary over-treatment in low-risk patients; this requires accurate prognostic predictions. Materials and Methods: Six PTC expression datasets were obtained from the gene expression omnibus (GEO) database. Level 3 mRNA expression and clinicopathological data were obtained from The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) database. Through integrated analysis of these datasets, highly reliable differentially-expressed genes (DEGs) between tumor and normal tissue were identified and lasso Cox regression was applied to identify DEGs related to the progression-free interval (PFI) and to establish a prognostic gene signature. The performance of a five-gene signature was evaluated based on a Kaplan-Meier curve, receiver operating characteristic (ROC), and Harrell's concordance index (C-index). Multivariate Cox regression analysis was used to identify factors associated with PTC prognosis. Finally, a prognostic nomogram was established based on the TCGA-THCA dataset. Results: A novel five-gene signature was established to predict the PTC PFI, which included PLP2, LYVE1, FABP4, TGFBR3, and FXYD6, and the ROC curve and C-index showed good performance in both training and validation datasets. This could classify patients into high- and low-risk groups with distinct PFIs and differentiate PTC tumors from normal tissue. Univariate Cox regression revealed that this signature was an independent prognostic factor for PTC. The established nomogram, incorporating the prognostic gene signature and clinical parameters, was able to predict the PFI with high efficiency. The gene signature-based nomogram was superior to the American Thyroid Association (ATA) risk stratification to predict PTC PFI. Conclusions: Our study identified a five-gene signature and established a prognostic nomogram, which were reliable in predicting the PFI of PTC; this could be beneficial for individualized treatment and medical decision making.

Identification of Long Noncoding RNA MIR22HG as a Novel Biomarker in Thyroid Cancer

Thyroid cancer (TC) is the one of the most common endocrine malignancy. However, currently there are no specific and sensitive biomarkers for predicting the prognosis for TC. In this study, we for the first time showed MIR22HG was down-regulated in thyroid cancer by analyzing public datasets, including TCGA, GSE29265, GSE33630, and GSE55091. Furthermore, we observed the lower expression levels of MIR22HG were significantly related to higher age, lymph node metastasis status, residual tumor status, N stage, Grade, and T stage in TC. We also observed higher MIR22HG expression was associated with longer overall and disease-free survival time in TC. In order to explore the potential mechanisms of MIR22HG regulating TC progression, 4 hub gene networks regulated by MIR22HG were constructed in the present study. Bioinformatics analysis showed MIR22HG was associated with apoptotic process, regulation of transcription, mRNA splicing, regulation of cell cycle, and Hippo signaling pathway in TC. These results suggested MIR22HG could serve as a novel biomarker for thyroid cancer.

RADIATION AND THYROID CANCER-AN OVERVIEW

It has long been known that the thyroid is a radiosensitive organ. It is the only organ in the body to both take up and bind iodine, and therefore exposure to radioiodine in fallout from nuclear power plants poses an increased danger to the thyroid. Studies following the Chernobyl accident have shown that children are most at risk from the development of thyroid cancer following exposure to radioactive iodine in fallout. This article reviews what we know so far about the type of thyroid cancer induced by radiation, its molecular biology and clinical outcome.

Meta-analysis of microarray datasets identify several chromosome segregation-related cancer/testis genes potentially contributing to anaplastic thyroid carcinoma

AIM

Anaplastic thyroid carcinoma (ATC) is the most lethal thyroid malignancy. Identification of novel drug targets is urgently needed.

MATERIALS & METHODS

We re-analyzed several GEO datasets by systematic retrieval and data merging. Differentially expressed genes (DEGs) were filtered out. We also performed pathway enrichment analysis to interpret the data. We predicted key genes based on protein-protein interaction networks, weighted gene co-expression network analysis and genes' cancer/testis expression pattern. We also further characterized these genes using data from the Cancer Genome Atlas (TCGA) project and gene ontology annotation.

RESULTS

Cell cycle-related pathways were significantly enriched in upregulated genes in ATC. We identified TRIP13, DLGAP5, HJURP, CDKN3, NEK2, KIF15, TTK, KIF2C, AURKA and TPX2 as cell cycle-related key genes with cancer/testis expression pattern. We further uncovered that most of these putative key genes were critical components during chromosome segregation.

CONCLUSION

We predicted several key genes harboring potential therapeutic value in ATC. Cell cycle-related processes, especially chromosome segregation, may be the key to tumorigenesis and treatment of ATC.

Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning

Background: Gene signatures derived from transcriptomic data using machine learning methods have shown promise for biodosimetry testing. These signatures may not be sufficiently robust for large scale testing, as their performance has not been adequately validated on external, independent datasets. The present study develops human and murine signatures with biochemically-inspired machine learning that are strictly validated using k-fold and traditional approaches. Methods: Gene Expression Omnibus (GEO) datasets of exposed human and murine lymphocytes were preprocessed via nearest neighbor imputation and expression of genes implicated in the literature to be responsive to radiation exposure (n=998) were then ranked by Minimum Redundancy Maximum Relevance (mRMR). Optimal signatures were derived by backward, complete, and forward sequential feature selection using Support Vector Machines (SVM), and validated using k-fold or traditional validation on independent datasets. Results: The best human signatures we derived exhibit k-fold validation accuracies of up to 98% ( DDB2,  PRKDC, TPP2, PTPRE, and GADD45A) when validated over 209 samples and traditional validation accuracies of up to 92% ( DDB2,  CD8A,  TALDO1,  PCNA,  EIF4G2,  LCN2,  CDKN1A,  PRKCH,  ENO1,  and PPM1D) when validated over 85 samples. Some human signatures are specific enough to differentiate between chemotherapy and radiotherapy. Certain multi-class murine signatures have sufficient granularity in dose estimation to inform eligibility for cytokine therapy (assuming these signatures could be translated to humans). We compiled a list of the most frequently appearing genes in the top 20 human and mouse signatures. More frequently appearing genes among an ensemble of signatures may indicate greater impact of these genes on the performance of individual signatures. Several genes in the signatures we derived are present in previously proposed signatures. Conclusions: Gene signatures for ionizing radiation exposure derived by machine learning have low error rates in externally validated, independent datasets, and exhibit high specificity and granularity for dose estimation.

Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning

Background: Gene signatures derived from transcriptomic data using machine learning methods have shown promise for biodosimetry testing. These signatures may not be sufficiently robust for large scale testing, as their performance has not been adequately validated on external, independent datasets. The present study develops human and murine signatures with biochemically-inspired machine learning that are strictly validated using k-fold and traditional approaches. Methods: Gene Expression Omnibus (GEO) datasets of exposed human and murine lymphocytes were preprocessed via nearest neighbor imputation and expression of genes implicated in the literature to be responsive to radiation exposure (n=998) were then ranked by Minimum Redundancy Maximum Relevance (mRMR). Optimal signatures were derived by backward, complete, and forward sequential feature selection using Support Vector Machines (SVM), and validated using k-fold or traditional validation on independent datasets. Results: The best human signatures we derived exhibit k-fold validation accuracies of up to 98% ( DDB2,  PRKDC, TPP2, PTPRE, and GADD45A) when validated over 209 samples and traditional validation accuracies of up to 92% ( DDB2,  CD8A,  TALDO1,  PCNA,  EIF4G2,  LCN2,  CDKN1A,  PRKCH,  ENO1,  and PPM1D) when validated over 85 samples. Some human signatures are specific enough to differentiate between chemotherapy and radiotherapy. Certain multi-class murine signatures have sufficient granularity in dose estimation to inform eligibility for cytokine therapy (assuming these signatures could be translated to humans). We compiled a list of the most frequently appearing genes in the top 20 human and mouse signatures. More frequently appearing genes among an ensemble of signatures may indicate greater impact of these genes on the performance of individual signatures. Several genes in the signatures we derived are present in previously proposed signatures. Conclusions: Gene signatures for ionizing radiation exposure derived by machine learning have low error rates in externally validated, independent datasets, and exhibit high specificity and granularity for dose estimation.

miRNA expression and function in thyroid carcinomas: a comparative and critical analysis and a model for other cancers

As in many cancer types, miRNA expression profiles and functions have become an important field of research on non-medullary thyroid carcinomas, the most common endocrine cancers. This could lead to the establishment of new diagnostic tests and new cancer therapies. However, different studies showed important variations in their research strategies and results. In addition, the action of miRNAs is poorly considered as a whole because of the use of underlying dogmatic truncated concepts. These lead to discrepancies and limits rarely considered. Recently, this field has been enlarged by new miRNA functional and expression studies. Moreover, studies using next generation sequencing give a new view of general miRNA differential expression profiles of papillary thyroid carcinoma. We analyzed in detail this literature from both physiological and differential expression points of view. Based on explicit examples, we reviewed the progresses but also the discrepancies and limits trying to provide a critical approach of where this literature may lead. We also provide recommendations for future studies. The conclusions of this systematic analysis could be extended to other cancer types.

Lessons from Fukushima: Latest Findings of Thyroid Cancer After the Fukushima Nuclear Power Plant Accident

The increase in risk for late-onset thyroid cancer due to radiation exposure is a potential health effect after a nuclear power plant accident mainly due to the release of radioiodine in fallout. The risk is particularly elevated in those exposed during infancy and adolescence. To estimate the possibility and extent of thyroid cancer occurrence after exposure, it is of utmost importance to collect and analyze epidemiological information providing the basis for evaluation of radiation risk, and to consider radiobiology and molecular genetics. In this regard, the dose-response of cancer risk, temporal changes in the rates of thyroid cancer, its histopathological types and subtypes, and frequency of underlying genetic abnormalities are important. At present, however, it is difficult or impossible to distinguish radiation-induced thyroid cancer from spontaneous/sporadic thyroid cancer because molecular radiation signatures, biomarkers of radiation exposure, or genetic factors specific to radiation-induced cancer have not yet been identified. The large-scale ultrasound screening in Fukushima Prefecture of Japan demonstrated a high detection rate of thyroid cancer in young individuals, revealing 116 and 71 cases in the first and second rounds, respectively, among the same cohort of approximately 300,000 subjects. These findings raised concerns among residents and the public that it might be due to putative exposure to radiation from the accident at Fukushima Daiichi Nuclear Power Plant. This review summarizes evaluations by international organizations and reviews scientific publications by the authors and others on childhood thyroid cancer, especially those relevant to radiation, including basic studies on molecular mechanisms of thyroid carcinogenesis. Clinical details are also provided on surgical cases in Fukushima Prefecture, and the effect of thyroid ultrasound screening is discussed. Correct understanding of issues relating to radiation and the thyroid are essential for interpretation of thyroid cancer in Fukushima.

Insulin Resistance Associated With Differentiated Thyroid Carcinoma: Penalized Conditional Logistic Regression Analysis of a Matched Case-Control Study Data

BACKGROUND

In the recent years, thyroid cancer incidence has increased worldwide. It has been questioned whether factors, such as insulin resistance, are involved in this rise. The main aim of this study was to examine the association between insulin resistance and differentiated thyroid cancer.

METHODS

This case-control study was performed on 30 newly diagnosed patients with differentiated thyroid cancer and 30 healthy controls. Thirty euthyroid patients recently diagnosed with differentiated thyroid cancer, based on the fine needle aspiration cytology, were examined for insulin resistance before thyroidectomy in the euthyroid state. For each patient in the case group, one healthy euthyroid individual without thyroid nodule from general population was matched based on gender, age (± 1 year), and body mass index (BMI) (± 1). Thyroid function test, thyroid antibodies, serum glucose, serum insulin, and thyroid ultrasonography was performed for all participants. Insulin resistance was defined based on homeostasis model assessment of insulin resistance (HOMA-IR) to be more than 2.5.

RESULTS

In the patient group, 24 (80%) cases were female and 6 (20%) were male. Insulin resistance was more prevalent in the case group than the control group (43.3% versus 13.3%). Insulin sensitivity index was lower in the case group than in the control group (50 and 81, respectively). There was a significant positive association between serum HOMA-IR levels and differentiated thyroid cancer (OR: 2.43 for 1 unit increase in HOMA-IR, 95% CI: 1.35 - 5.51; P = 0.001). Insulin resistance was significantly associated with differentiated thyroid cancer (OR: 4, 95 % CI: 1.27 - 17.6; P = 0.016).

CONCLUSIONS

There was a significant association between insulin resistance and differentiated thyroid carcinoma. More research with a larger sample size and prospective design are needed to determine the role of this factor in the development of differentiated thyroid cancers.

Vitamin D Deficiency Associated with Differentiated Thyroid Carcinoma: A Case- Control Study

Objective:

In recent decades, the incidence of thyroid cancer has increased throughout the world. It is unclear whether factors such as vitamin D deficiency may have been involved in this increase. The present case-control study was conducted to examine any association between Vitamin D deficiency and thyroid cancers.

Methods:

The study was conducted on 85 patients with differentiated thyroid cancer diagnosed based on fine needle aspiration biopsy as the case group and 85 healthy controls. Serum levels of vitamin D were evaluated before thyroidectomy. For each patient in the case group, one healthy euthyroid person without any thyroid nodules from the general population matched based on season, sex, age (± 1 year) and BMI (± 1) was selected. Finally, 85 pairs were obtained considering inclusion and exclusion criteria. Thyroid function, thyroid antibodies and serum vitamin D were assessed and thyroid sonography was performed in all participants.

Results:

In the patient group, 72 (85%) were female and 13 (15%) were male. The mean (SD) serum vitamin D level was 8.00 (±3.7) in patient group, as compared to 13.4 (±7.90) in the control group, the difference being significant (OR: 6, 95 %CI: 1.02-113.3; P=0.046).

Conclusion:

A significant association was noted between vitamin D deficiency and differentiated thyroid cancer. Further studies with a prospective design are necessary to further define the roles of this factor.

A loss-of-function genetic screening identifies novel mediators of thyroid cancer cell viability

RET, BRAF and other protein kinases have been identified as major molecular players in thyroid cancer. To identify novel kinases required for the viability of thyroid carcinoma cells, we performed a RNA interference screening in the RET/PTC1(CCDC6-RET)-positive papillary thyroid cancer cell line TPC1 using a library of synthetic small interfering RNAs (siRNAs) targeting the human kinome and related proteins. We identified 14 hits whose silencing was able to significantly reduce the viability and the proliferation of TPC1 cells; most of them were active also in BRAF-mutant BCPAP (papillary thyroid cancer) and 8505C (anaplastic thyroid cancer) and in RAS-mutant CAL62 (anaplastic thyroid cancer) cells. These included members of EPH receptor tyrosine kinase family as well as SRC and MAPK (mitogen activated protein kinases) families. Importantly, silencing of the identified hits did not affect significantly the viability of Nthy-ori 3-1 (hereafter referred to as NTHY) cells derived from normal thyroid tissue, suggesting cancer cell specificity. The identified proteins are worth exploring as potential novel druggable thyroid cancer targets.

Targeting COPZ1 non-oncogene addiction counteracts the viability of thyroid tumor cells

Thyroid carcinoma is generally associated with good prognosis, but no effective treatments are currently available for aggressive forms not cured by standard therapy. To find novel therapeutic targets for this tumor type, we had previously performed a siRNA-based functional screening to identify genes essential for sustaining the oncogenic phenotype of thyroid tumor cells, but not required to the same extent for the viability of normal cells (non-oncogene addiction paradigm). Among those, we found the coatomer protein complex ζ1 (COPZ1) gene, which is involved in intracellular traffic, autophagy and lipid homeostasis. In this paper, we investigated the mechanisms through which COPZ1 depletion leads to thyroid tumor cell death. We showed that siRNA-mediated COPZ1 depletion causes abortive autophagy, endoplasmic reticulum stress, unfolded protein response and apoptosis. Interestingly, we observed that mouse tumor xenografts, locally treated with siRNA targeting COPZ1, showed a significant reduction of tumor growth. On the whole, we demonstrated for the first time the crucial role of COPZ1 in the viability of thyroid tumor cells, suggesting that it may be considered an attractive target for novel therapeutic approaches for thyroid cancer.

A transcriptomic insight into the impacts of mast cells in lung, breast, and colon cancers

To date, the exact impact of mast cells in tumor microenvironment is still controversial because of inconsistency in observations regarding the relationship between mast cell infiltrates and cancer development and prognosis. The discrepancies in previous studies have motivated us to examine the roles of mast cells in cancer pathology from different perspectives. Here, we investigated the impact of mast cells on transcriptomic profiles in the tissue microenvironment. Mice carrying the W-sh mutation in c-kit (Kit^W-sh ) are deficient in mast cell production and were used to assess the influence of mast cells on gene expression. By examining the transcriptomic profile among wild-type mice, Kit^W-sh mice, and Kit^W-sh mice with mast cell engraftment, we identified a list of "mast cell-dependent genes," which are enriched for cancer-related pathways. Utilizing whole-genome gene expression data from both mouse models and human cancer patients, we demonstrated that the expression profile of the mast cell-dependent genes differs between tumor and normal tissues from lung, breast, and colon, respectively. Mast cell infiltration is potentially increased in tumors compared with normal tissues, suggesting that mast cells might participate in tumor development. Accordingly, a prognostic molecular signature was developed based on the mast cell-dependent genes, which predicted recurrence-free survival for human patients with lung, breast, and colon cancers, respectively. Our study provides a novel transcriptomic insight into the impact of mast cells in the tumor microenvironment, though further experimental investigation is needed to validate the exact role of individual mast cell-dependent genes in different cancers.

Radiation and Thyroid Cancer

Radiation-induced damage is a complex network of interlinked signaling pathways, which may result in apoptosis, cell cycle arrest, DNA repair, and cancer. The development of thyroid cancer in response to radiation, from nuclear catastrophes to chemotherapy, has long been an object of study. A basic overview of the ionizing and non-ionizing radiation effects of the sensitivity of the thyroid gland on radiation and cancer development has been provided. In this review, we focus our attention on experiments in cell cultures exposed to ionizing radiation, ultraviolet light, and proton beams. Studies on the involvement of specific genes, proteins, and lipids are also reported. This review also describes how lipids are regulated in response to the radiation-induced damage and how they are involved in thyroid cancer etiology, invasion, and migration and how they can be used as both diagnostic markers and drug targets.

Clinicopathological relevance of antithyroglobulin antibodies in low-risk papillary thyroid cancer

OBJECTIVE

The extent of initial surgical management in papillary thyroid cancer (PTC) is controversial. We examined whether the presence of perioperative antithyroglobulin antibodies (TGA) could predict long-term recurrence and occurrence of adverse features among a homogenous group of patients with PTC.

METHODS

The clinical features of patients with PTC treated at a single institution (Jewish General Hospital, McGill University, Montreal, Canada) were obtained from the medical records, and all clinicopathologic information was reviewed. Only low-risk PTC without clinical evidence of nodal disease before surgery and treated with 30 mCi of radioactive iodine was included in the study.

RESULTS

The chart review retrieved 361 patients with a median follow-up of 85.0 months (Q25-Q75 73-98). Forty-two (11.6%) patients had presence of perioperative TGA. Perioperative TGAs were associated with present extrathyroidal extension (P=.005), unsuspected nodal disease (P=.001) and autoimmune thyroiditis (P<.0001). Overall, 17 (4.7%) patients experienced locoregional recurrence. Perioperative TGAs were a significant predictor of recurrence in univariable (P=.021) but not in multivariable analysis (P=.13).

CONCLUSION

Presence of perioperative TGAs is associated with aggressive histological features and the presence of thyroiditis. Detection of TGA perioperatively may encourage surgeons to consider more extensive initial surgery.

Ionizing radiation biomarkers in epidemiological studies - An update

Recent epidemiology studies highlighted the detrimental health effects of exposure to low dose and low dose rate ionizing radiation (IR): nuclear industry workers studies have shown increased leukaemia and solid tumour risks following cumulative doses of <100mSv and dose rates of <10mGy per year; paediatric patients studies have reported increased leukaemia and brain tumours risks after doses of 30-60mGy from computed tomography scans. Questions arise, however, about the impact of even lower doses and dose rates where classical epidemiological studies have limited power but where subsets within the large cohorts are expected to have an increased risk. Further progress requires integration of biomarkers or bioassays of individual exposure, effects and susceptibility to IR. The European DoReMi (Low Dose Research towards Multidisciplinary Integration) consortium previously reviewed biomarkers for potential use in IR epidemiological studies. Given the increased mechanistic understanding of responses to low dose radiation the current review provides an update covering technical advances and recent studies. A key issue identified is deciding which biomarkers to progress. A roadmap is provided for biomarker development from discovery to implementation and used to summarise the current status of proposed biomarkers for epidemiological studies. Most potential biomarkers remain at the discovery stage and for some there is sufficient evidence that further development is not warranted. One biomarker identified in the final stages of development and as a priority for further research is radiation specific mRNA transcript profiles.

Elucidation of the molecular mechanisms of anaplastic thyroid carcinoma by integrated miRNA and mRNA analysis

To elucidate the complex molecular mechanisms of anaplastic thyroid carcinoma (ATC), the mRNA and miRNA expression profiles of ATC were systematically explored. A total of 55 common differentially expressed genes (DEGs) were obtained from two mRNA expression datasets including 23 ATC samples and 24 paired normal samples. Gene expression levels of three randomly selected DEGs, VCAN, COL5A1 and KCNJ16, were examined using RT-PCR in 10 ATC samples. Notably, the ATC and normal samples were clearly classified into two groups based on their common DEGs. Moreover 23 common DEGs, such as TG, NKX2-1, KCNJ16 and CTHRC1, were predicted to be the potential targets of 17 identified miRNAs in ATC. Meanwhile, several miRNA target genes were associated with biological processes related to tumor progression such as angiogenesis, cell migration or growth and potassium channel regulation. In summary, the poor prognosis of ATC is possibly caused via complex biological processes. Firstly, angiogenesis was activated by the high expression of CTHRC1, VCAN and POSTN, providing necessary nutrition for tumor cells. Then tumor distant metastasis was induced via stimulation of cell migration and cell growth or regulation of cell-cell interaction. Moreover, intracellular potassium concentration changes promoted ATC progression indirectly. Hence, identification of these critical DEGs was valuable in understanding the molecular mechanisms of ATC.

NADPH oxidases: new actors in thyroid cancer?

Hydrogen peroxide (H2O2) is a crucial substrate for thyroid peroxidase, a key enzyme involved in thyroid hormone synthesis. However, as a potent oxidant, H2O2 might also be responsible for the high level of oxidative DNA damage observed in thyroid tissues, such as DNA base lesions and strand breakages, which promote chromosomal instability and contribute to the development of tumours. Although the role of H2O2 in thyroid hormone synthesis is well established, its precise mechanisms of action in pathological processes are still under investigation. The NADPH oxidase/dual oxidase family are the only oxidoreductases whose primary function is to produce reactive oxygen species. As such, the function and expression of these enzymes are tightly regulated. Thyrocytes express dual oxidase 2, which produces most of the H2O2 for thyroid hormone synthesis. Thyrocytes also express dual oxidase 1 and NADPH oxidase 4, but the roles of these enzymes are still unknown. Here, we review the structure, expression, localization and function of these enzymes. We focus on their potential role in thyroid cancer, which is characterized by increased expression of these enzymes.

UHRF1 suppression promotes cell differentiation and reduces inflammatory reaction in anaplastic thyroid cancer

Anaplastic thyroid cancer (ATC), an undifferentiated subtype of thyroid cancer, is one of the most malignant endocrine cancer with low survival rate, and resistant to chemotherapy and radiation therapy. Here we found that UHRF1 was highly expressed in human ATC compared with normal tissue and papillary thyroid cancer (PTC). Knockdown of UHRF1 inhibited proliferation of ATC in vitro and in vivo. Consistently, overexpression of UHRF1 promoted the proliferation of thyroid cancer cells. Moreover, UHRF1 suppression induced differentiation of three-dimensional (3D) cultured ATC cells and down-regulated the expression of dedifferentiation marker (CD97). The stem cell markers (Sox2, Oct4 and Nanog) were suppressed simultaneously. In addition, UHRF1 knockdown reduced the transcription of cytokines (IL-8, TGF-α and TNF-α), which might relieve the inflammatory reaction in ATC patients. This study demonstrated a role of UHRF1 in ATC proliferation, dedifferentiation and inflammatory reaction, presenting UHRF1 as a potential target in ATC therapy.

A robust biomarker of differential correlations improves the diagnosis of cytologically indeterminate thyroid cancers

The fine-needle aspiration of thyroid nodules and subsequent cytological analysis is unable to determine the diagnosis in 15 to 30% of thyroid cancer cases; patients with indeterminate cytological results undergo diagnostic surgery which is potentially unnecessary. Current gene expression biomarkers based on well-determined cytology are complex and their accuracy is inconsistent across public datasets. In the present study, we identified a robust biomarker using the differences in gene expression values specifically from cytologically indeterminate thyroid tumors and a powerful multivariate search tool coupled with a nearest centroid classifier. The biomarker is based on differences in the expression of the following genes: CCND1, CLDN16, CPE, LRP1B, MAGI3, MAPK6, MATN2, MPPED2, PFKFB2, PTPRE, PYGL, SEMA3D, SERGEF, SLC4A4 and TIMP1. This 15-gene biomarker exhibited superior accuracy independently of the cytology in six datasets, including The Cancer Genome Atlas (TCGA) thyroid dataset. In addition, this biomarker exhibited differences in the correlation coefficients between benign and malignant samples that indicate its discriminatory power, and these 15 genes have been previously related to cancer in the literature. Thus, this 15-gene biomarker provides advantages in clinical practice for the effective diagnosis of thyroid cancer.

Gene signature of the post-Chernobyl papillary thyroid cancer

Purpose

Following the nuclear accidents in Chernobyl and later in Fukushima, the nuclear community has been faced with important issues concerning how to search for and diagnose biological consequences of low-dose internal radiation contamination. Although after the Chernobyl accident an increase in childhood papillary thyroid cancer (PTC) was observed, it is still not clear whether the molecular biology of PTCs associated with low-dose radiation exposure differs from that of sporadic PTC.

Methods

We investigated tissue samples from 65 children/young adults with PTC using DNA microarray (Affymetrix, Human Genome U133 2.0 Plus) with the aim of identifying molecular differences between radiation-induced (exposed to Chernobyl radiation, ECR) and sporadic PTC. All participants were resident in the same region so that confounding factors related to genetics or environment were minimized.

Results

There were small but significant differences in the gene expression profiles between ECR and non-ECR PTC (global test, p < 0.01), with 300 differently expressed probe sets (p < 0.001) corresponding to 239 genes. Multifactorial analysis of variance showed that besides radiation exposure history, the BRAF mutation exhibited independent effects on the PTC expression profile; the histological subset and patient age at diagnosis had negligible effects. Ten genes (PPME1, HDAC11, SOCS7, CIC, THRA, ERBB2, PPP1R9A, HDGF, RAD51AP1, and CDK1) from the 19 investigated with quantitative RT-PCR were confirmed as being associated with radiation exposure in an independent, validation set of samples.

Conclusion

Significant, but subtle, differences in gene expression in the post-Chernobyl PTC are associated with previous low-dose radiation exposure.

Electronic supplementary material

The online version of this article (doi:10.1007/s00259-015-3303-3) contains supplementary material, which is available to authorized users.

Aberrant Activation of Notch Signaling Inhibits PROX1 Activity to Enhance the Malignant Behavior of Thyroid Cancer Cells

Papillary thyroid cancer (PTC) is one of the most common endocrine malignancies associated with significant morbidity and mortality. Although multiple studies have contributed to a better understanding of the genetic alterations underlying this frequently arising disease, the downstream molecular effectors that impact PTC pathogenesis remain to be further defined. Here, we report that the regulator of cell fate specification, PROX1, becomes inactivated in PTC through mRNA downregulation and cytoplasmic mislocalization. Expression studies in clinical specimens revealed that aberrantly activated NOTCH signaling promoted PROX1 downregulation and that cytoplasmic mislocalization significantly altered PROX1 protein stability. Importantly, restoration of PROX1 activity in thyroid carcinoma cells revealed that PROX1 not only enhanced Wnt/β-catenin signaling but also regulated several genes known to be associated with PTC, including thyroid cancer protein (TC)-1, SERPINA1, and FABP4. Furthermore, PROX1 reexpression suppressed the malignant phenotypes of thyroid carcinoma cells, such as proliferation, motility, adhesion, invasion, anchorage-independent growth, and polyploidy. Moreover, animal xenograft studies demonstrated that restoration of PROX1 severely impeded tumor formation and suppressed the invasiveness and the nuclear/cytoplasmic ratio of PTC cells. Taken together, our findings demonstrate that NOTCH-induced PROX1 inactivation significantly promotes the malignant behavior of thyroid carcinoma and suggest that PROX1 reactivation may represent a potential therapeutic strategy to attenuate disease progression.

Revisiting the transcriptional analysis of primary tumours and associated nodal metastases with enhanced biological and statistical controls: application to thyroid cancer

Background:

Transcriptome profiling has helped characterise nodal spread. The interpretation of these data, however, is not without ambiguities.

Methods:

We profiled the transcriptomes of papillary thyroid cancer nodal metastases, associated primary tumours and primary tumours from N0 patients. We also included patient-matched non-cancerous thyroid and lymph node samples as controls to address some limits of previous studies.

Results:

The transcriptomes of patient-matched primary tumours and metastases were more similar than those of unrelated metastases/primary pairs, as previously reported in other organ systems. This similarity partly reflected patient background. Lymphoid tissues in the metastases confounded the comparison of patient-matched primary tumours and metastases. We circumvented this with an original data adjustment, revealing a differential expression of stroma-related gene signatures also regulated in other organs. The comparison of N0 vs N+ primary tumours uncovered a signal irreproducible across independent data sets. This signal was also detectable when comparing the non-cancerous thyroid tissues adjacent to N0 and N+ tumours, suggesting a cohort-specific bias also likely present in previous similarly sized studies. Classification of N0 vs N+ yielded an accuracy of 63%, but additional statistical controls absent in previous studies revealed that this is explainable by chance alone. We used large data sets from The Cancer Genome Atlas: N0 vs N+ classification was not better than random for most cancers. Yet, it was significant, but of limited accuracy (<70%) for thyroid, breast and head and neck cancers.

Conclusions:

The clinical potential of gene expression to predict nodal metastases seems limited for most cancers.

Dose-dependent expression of CLIP2 in post-Chernobyl papillary thyroid carcinomas

This study showed a clear dose-response relationship for the CLIP2 radiation marker in post-Chernobyl papillary thyroid carcinoma cohorts for young patients and hints to different molecular mechanisms in tumors induced at low doses compared to moderate/high doses.

A previous study on papillary thyroid carcinomas (PTC) in young patients who were exposed to ¹³¹iodine from the Chernobyl fallout revealed an exclusive gain of chromosomal band 7q11.23 in exposed cases compared to an age-matched control cohort. CLIP2, a gene located within band 7q11.23 was shown to be differentially expressed between exposed and non-exposed cases at messenger RNA and protein level. Therefore, a standardized procedure for CLIP2 typing of PTCs has been developed in a follow-up study. Here we used CLIP2 typing data on 117 post-Chernobyl PTCs from two cohorts of exposed patients with individual dose estimates and 24 non-exposed controls to investigate a possible quantitative dose-response relationship of the CLIP2 marker. The ‘Genrisk-T’ cohort consisted of 45 PTCs and the ‘UkrAm’ cohort of 72 PTCs. Both cohorts differed in mean dose (0.59 Gy Genrisk-T, 1.2 Gy UkrAm) and mean age at exposure (AaE) (2 years Genrisk-T, 8 years UkrAm), whilst the median latency (16 years Genrisk-T, 18 years UkrAm) was comparable. We analyzed the association between the binary CLIP2 typing and continuous thyroid dose with logistic regression. A clear positive dose-response relationship was found for young PTC cases [age at operation (AaO) < 20 years, AaE < 5 years]. In the elder age group a higher proportion of sporadic tumors is assumed due to a negligible dose response, suggesting different molecular mechanisms in sporadic and radiation-induced cases. This is further supported by the association of elder patients (AaO > 20 years) with positivity for BRAF V600E mutation.

Radiation signatures in childhood thyroid cancers after the Chernobyl accident: possible roles of radiation in carcinogenesis

After the Tokyo Electric Power Company Fukushima Daiichi nuclear power plant accident, cancer risk from low-dose radiation exposure has been deeply concerning. The linear no-threshold model is applied for the purpose of radiation protection, but it is a model based on the concept that ionizing radiation induces stochastic oncogenic alterations in the target cells. As the elucidation of the mechanism of radiation-induced carcinogenesis is indispensable to justify the concept, studies aimed at the determination of molecular changes associated with thyroid cancers among children who suffered effects from the Chernobyl nuclear accident will be overviewed. We intend to discuss whether any radiation signatures are associated with radiation-induced childhood thyroid cancers.