Aberrantly methylated genes in human papillary thyroid cancer and their association with BRAF/RAS mutation

A ferroptosis-related signature predicts the clinical diagnosis and prognosis, and associates with the immune microenvironment of lung cancer

Targeting ferroptosis-related pathway is a potential strategy for treatment of lung cancer (LC). Consequently, exploration of ferroptosis-related markers is important for treating LC. We collected LC clinical data and mRNA expression profiles from TCGA and GEO database. Ferroptosis-related genes (FRGs) were obtained through FerrDB database. Expression analysis was performed to obtain differentially expressed FRGs. Diagnostic and prognostic models were constructed based on FRGs by LASSO regression, univariate, and multivariate Cox regression analysis, respectively. External verification cohorts GSE72094 and GSE157011 were used for validation. The interrelationship between prognostic risk scores based on FRGs and the tumor immune microenvironment was analyzed. Immunocytochemistry, Western blotting, and RT-qPCR detected the FRGs level. Eighteen FRGs were used for diagnostic models, 8 FRGs were used for prognostic models. The diagnostic model distinguished well between LC and normal samples in training and validation cohorts of TCGA. The prognostic models for TCGA, GSE72094, and GSE157011 cohorts significantly confirmed lower overall survival (OS) in high-risk group, which demonstrated excellent predictive properties of the survival model. Multivariate Cox regression analysis further confirmed risk score was an independent risk factor related with OS. Immunoassays revealed that in high-risk group, a significantly higher proportion of Macrophages_M0, Neutrophils, resting Natural killer cells and activated Mast cells and the level of B7H3, CD112, CD155, B7H5, and ICOSL were increased. In conclusion, diagnostic and prognostic models provided superior diagnostic and predictive power for LC and revealed a potential link between ferroptosis and TIME.

Identification and validation of a five-gene prognostic signature based on bioinformatics analyses in breast cancer

Background

This study aimed to identify prognostic signatures to predict the prognosis of breast cancer (BRCA) patients based on a series of comprehensive analyses of gene expression data.

Methods

The RNA-sequencing expression data and corresponding BRCA patient clinical data were collected from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. Firstly, the differently expressed genes (DEGs) related to prognosis between tumor tissues and normal tissues were ascertained by performing R package "limma". Secondly, the DEGs were used to construct a polygenic risk scoring model by the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator Cox regression (Lasso-cox) analysis method. Thirdly, survival analysis was performed to investigate the risk score values in the TCGA cohort. And the enrichment analysis, immune cell infiltration levels analysis, and protein-protein internet (PPI) analysis were performed. Simultaneously, the GEO cohort was used to validate the model. Lastly, we constructed a nomogram to explore the influence of polygenic risk score and other clinical factors on the survival probability of patients with BRCA.

Results

A total of 1000 DEGs including 396 upregulated genes and 604 downregulated genes were identified from the TCGA-BRCA dataset. We obtained 5 prognosis-related genes, as the key biomarkers by Lasso-cox analysis (FBXL19, HAGHL, PHKG2, PKMYT1, and TXNDC17), all of which were significantly upregulated in breast tumors. The prognostic prediction of the 5 genes model was great in training and validation cohorts. Moreover, the high-risk group had a poorer prognosis. The Cox regression analysis showed that the comprehensive risk score for 5 genes was an independent prognosis factor.

Conclusion

The 5 genes risk model constructed in this study had an independent predictive ability to distinguish patients with a high risk of death from those with a low-risk score, and it can be used as a practical and reliable prognostic tool for BRCA.

Induction of BRAF^V600E Mutation in Thyroid Cells Leads to Frequent Hypermethylation

Objectives.

The BRAF^V600E mutation is a major driver mutation in papillary thyroid cancer. The aim of this study was to elucidate the correlation between DNA methylation and gene expression changes induced by the BRAF^V600E mutation in thyroid cells.

Methods.

We used Nthy/BRAF cell lines generated by transfection of Nthy/ori cells with the wild-type BRAF gene (Nthy/WT cells) and the V600E mutant-type BRAF gene (Nthy/V600E cells). We performed gene expression microarray and DNA methylation array analyses for Nthy/WT and Nthy/V600E cells. Two types of array data were integrated to identify inverse correlations between methylation and gene expression. The results were verified in silico using data from The Cancer Genome Atlas (TCGA) and in vivo through pyrosequencing and quantitative real-time polymerase chain reaction (qRT-PCR).

Results.

In the Nthy/V600E cells, 199,821 probes were significantly hypermethylated, and 697 genes showed a “hypermethylation-downregulation” pattern in Nthy/V600E. Tumor suppressor genes and apoptosis-related genes were included. In total, 66,446 probes were significantly hypomethylated, and 227 genes showed a “hypomethylation-upregulation” pattern in Nthy/V600E cells. Protooncogenes and developmental protein-coding genes were included. In the TCGA analysis, 491/697 (70.44%) genes showed a hypermethylation-downregulation pattern, and 153/227 (67.40%) genes showed a hypomethylation-upregulation pattern. Ten selected genes showed a similar methylation-gene expression pattern in pyrosequencing and qRT-PCR.

Conclusion.

Induction of the BRAF^V600E mutation in thyroid cells led to frequent hypermethylation. Anticancer genes, such as those involved in tumor suppression or apoptosis, were downregulated by upstream hypermethylation, whereas carcinogenic genes, such as protooncogenes, were upregulated by hypomethylation. Our results suggest that the BRAF^V600E mutation in thyroid cells modulates DNA methylation and results in cancer-related gene expression.

Deciphering the etiology and role in oncogenic transformation of the CpG island methylator phenotype: a pan-cancer analysis

Numerous cancer types have shown to present hypermethylation of CpG islands, also known as a CpG island methylator phenotype (CIMP), often associated with survival variation. Despite extensive research on CIMP, the etiology of this variability remains elusive, possibly due to lack of consistency in defining CIMP. In this work, we utilize a pan-cancer approach to further explore CIMP, focusing on 26 cancer types profiled in the Cancer Genome Atlas (TCGA). We defined CIMP systematically and agnostically, discarding any effects associated with age, gender or tumor purity. We then clustered samples based on their most variable DNA methylation values and analyzed resulting patient groups. Our results confirmed the existence of CIMP in 19 cancers, including gliomas and colorectal cancer. We further showed that CIMP was associated with survival differences in eight cancer types and, in five, represented a prognostic biomarker independent of clinical factors. By analyzing genetic and transcriptomic data, we further uncovered potential drivers of CIMP and classified them in four categories: mutations in genes directly involved in DNA demethylation; mutations in histone methyltransferases; mutations in genes not involved in methylation turnover, such as KRAS and BRAF; and microsatellite instability. Among the 19 CIMP-positive cancers, very few shared potential driver events, and those drivers were only IDH1 and SETD2 mutations. Finally, we found that CIMP was strongly correlated with tumor microenvironment characteristics, such as lymphocyte infiltration. Overall, our results indicate that CIMP does not exhibit a pan-cancer manifestation; rather, general dysregulation of CpG DNA methylation is caused by heterogeneous mechanisms.

Role of Advanced Glycation End-Products and Other Ligands for AGE Receptors in Thyroid Cancer Progression

To date, thyroid cancers (TCs) remain a clinical challenge owing to their heterogeneous nature. The etiopathology of TCs is associated not only with genetic mutations or chromosomal rearrangements, but also non-genetic factors, such as oxidative-, nitrosative-, and carbonyl stress-related alterations in tumor environment. These factors, through leading to the activation of intracellular signaling pathways, induce tumor tissue proliferation. Interestingly, the incidence of TCs is often coexistent with various simultaneous mutations. Advanced glycation end-products (AGEs), their precursors and receptors (RAGEs), and other ligands for RAGEs are reported to have significant influence on carcinogenesis and TCs progression, inducing gene mutations, disturbances in histone methylation, and disorders in important carcinogenesis-related pathways, such as PI₃K/AKT/NF-kB, p21/MEK/MPAK, or JAK/STAT, RAS/ERK/p53, which induce synthesis of interleukins, growth factors, and cytokines, thus influencing metastasis, angiogenesis, and cancer proliferation. Precursors of AGE (such as methylglyoxal (MG)) and selected ligands for RAGEs: AS1004, AS1008, and HMGB1 may, in the future, become potential targets for TCs treatment, as low MG concentration is associated with less aggressive anaplastic thyroid cancer, whereas the administration of anti-RAGE antibodies inhibits the progression of papillary thyroid cancer and anaplastic thyroid cancer. This review is aimed at collecting the information on the role of compounds, engaged in glycation process, in the pathogenesis of TCs. Moreover, the utility of these compounds in the diagnosis and treatment of TCs is thoroughly discussed. Understanding the mechanism of action of these compounds on TCs pathogenesis and progression may potentially be the grounds for the development of new treatment strategies, aiming at quality-of-life improvements.

A Five-mRNA Expression Signature to Predict Survival in Oral Squamous Cell Carcinoma by Integrated Bioinformatic Analyses

Objectives: This study was designed to identify a messenger RNA (mRNA) expression signature to predict survival in patients with oral squamous cell carcinoma (OSCC).

Methods: mRNA expression profiles were integrated with clinical data from 280 samples, including 19 normal tissues and 261 OSCC tissues in The Cancer Genome Atlas. We identified differentially expressed mRNAs (DEmRNAs) between the OSCC and normal tissue samples and developed a novel mRNA-focused expression signature using a Cox regression analysis and other bioinformatic methods. The prognostic value of this signature was evaluated by Kaplan–Meier analysis, multivariable COX regression, and receiver operating characteristic (ROC) curve analysis. Protein–protein interaction (PPI) network, gene ontology, and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed to predict the function of the DEmRNAs. Signature-related mRNAs were analyzed by gene set enrichment analyses (GSEA) and validated by quantitative real-time polymerase chain reaction (qRT-PCR) in 20 paired OSCC and adjacent healthy tissues.

Results: We identified a novel 5-mRNA expression signature (HOXA1, CELSR3, HIST1H3J, ZFP42, and ASCL4) that could predict patient outcomes in OSCC. The risk score based on the signature was able to separate OSCC patients into high- and low-risk groups that showed significantly different overall survival (p < 0.001, log-rank test). The signature was further validated as an effective independent prognostic predictor of OSCC by multivariate Cox regression analysis (hazard ratio = 3.747, confidence interval: 2.279–5.677, p < 0.001) and ROC curve of the third year (area under the curve = 0.733). Functional analysis demonstrated that the key hub genes in the PPI network were mainly enriched in cell division, cell proliferation, and the p53 signaling pathway. GSEA results showed that the 5 mRNAs were significantly enriched in mismatch repair, DNA replication, and the NOTCH signaling pathway. Finally, qRT-PCR results showed that the 5 mRNAs were upregulated in OSCC tissue in agreement with the predictions from our bioinformatics analysis.

Conclusions: We identified a novel 5-mRNA signature that could predict the survival of patients with OSCC and may be a promising biomarker for personalized cancer treatments.

Immune infiltration and a ferroptosis-associated gene signature for predicting the prognosis of patients with endometrial cancer

Ferroptosis, a form of programmed cell death induced by excess iron-dependent lipid peroxidation product accumulation, plays a critical role in cancer. However, there are few reports about ferroptosis in endometrial cancer (EC). This article explores the relationship between ferroptosis-related gene (FRG) expression and prognosis in EC patients. One hundred thirty-five FRGs were obtained by mining the literature, retrieving GeneCards and analyzing 552 malignant uterine corpus endometrial carcinoma (UCEC) samples, which were randomly assigned to training and testing groups (1:1 ratio), and 23 normal samples from The Cancer Genome Atlas (TCGA). We established a signature using eight screened FRGs (MDM2, GPX4, PRKAA2, PRNP, SLC11A2, ATP5MC3, PHKG2 and ACO1) related to overall survival using LASSO regression analysis. The samples were divided into low- and high-risk subgroups according to the median risk score. Kaplan-Meier survival curves showed that the low-risk group had better OS. ROC curves showed that this signature performed well in predicting OS (1-, 2-, 3-, and 5-year AUCs of 0.676, 0.775, 0.797, and 0.826, respectively). We systematically analyzed the immune infiltrating profile in UCEC samples from TCGA. Overall, our study identified a novel prognostic signature of 8 FRGs that can potentially predict the prognosis of EC.

Distinguishing Glioblastoma Subtypes by Methylation Signatures

Glioblastoma, also called glioblastoma multiform (GBM), is the most aggressive cancer that initiates within the brain. GBM is produced in the central nervous system. Cancer cells in GBM are similar to stem cells. Several different schemes for GBM stratification exist. These schemes are based on intertumoral molecular heterogeneity, preoperative images, and integrated tumor characteristics. Although the formation of glioblastoma is remarkably related to gene methylation, GBM has been poorly classified by epigenetics. To classify glioblastoma subtypes on the basis of different degrees of genes' methylation, we adopted several powerful machine learning algorithms to identify numerous methylation features (sites) associated with the classification of GBM. The features were first analyzed by an excellent feature selection method, Monte Carlo feature selection (MCFS), resulting in a feature list. Then, such list was fed into the incremental feature selection (IFS), incorporating one classification algorithm, to extract essential sites. These sites can be annotated onto coding genes, such as CXCR4, TBX18, SP5, and TMEM22, and enriched in relevant biological functions related to GBM classification (e.g., subtype-specific functions). Representative functions, such as nervous system development, intrinsic plasma membrane component, calcium ion binding, systemic lupus erythematosus, and alcoholism, are potential pathogenic functions that participate in the initiation and progression of glioblastoma and its subtypes. With these sites, an efficient model can be built to classify the subtypes of glioblastoma.

New Insights into Mechanisms of Endocrine-Disrupting Chemicals in Thyroid Diseases: The Epigenetic Way

In recent years, the presence in the environment of chemical compounds with thyroid-disrupting effects is progressively increased. This phenomenon has risen concern for human health as the preservation of thyroid system homeostasis is essential for fetal development and for maintaining psychological and physiological wellbeing. An increasing number of studies explored the role of different classes of toxicants in the occurrence and severity of thyroid diseases, but large epidemiological studies are limited and only a few animal or in vitro studies have attempted to identify the mechanisms of chemical action. Recently, epigenetic changes such as alteration of methylation status or modification of non-coding RNAs have been suggested as correlated to possible deleterious effects leading to different thyroid disorders in susceptible individuals. This review aims to analyze the epigenetic alterations putatively induced by chemical exposures and involved in the onset of frequent thyroid diseases such as thyroid cancer, autoimmune thyroiditis and disruption of fetal thyroid homeostasis.

Tamoxifen exposure in pregnancy after synchronous breast and thyroid cancer

Thyroid and breast cancer are the most common cancers among young women, which are either synchronous or metachronous, but the association is yet to be elucidated. With the improvement of diagnosis and treatment, there is an increase in breast and thyroid cancer survivors. Hence, attention is shifting towards survivorship. Here, we report the case of a young lady diagnosed with synchronous thyroid and breast cancer who unexpectedly became pregnant during tamoxifen treatment. After a multidisciplinary discussion, endocrine therapy was interrupted and she delivered a healthy baby at term. In conclusion, oncologists should be aware of breast and thyroid cancer co-occurrence and examinations should be conducted together in diagnosis and follow-up. Also, pregnancy is feasible and can be considered after synchronous breast and thyroid cancer diagnosis. Physicians need to emphasise the use of barrier contraceptives to patients undergoing endocrine therapy. However, the optimum timing for pregnancy after breast cancer and the safety of endocrine therapy interruption in hormonal-positive patients should be discussed and managed by a multidisciplinary team.

PD-1, CTLA4, PD-L1 and PD-L2 DNA methylation in papillary thyroid carcinoma

Aim: We investigated DNA methylation patterns of immune checkpoint genes PD-1, PD-L1, PD-L2, CTLA4 and an adjacent long noncoding RNA in papillary thyroid carcinoma (PTC). Materials & methods: DNA methylation and mRNA expression were examined in PTCs. DNA methylation was correlated with mRNA expression, BRAF and RAS mutational status, and immune cell infiltration. Results: Inverse correlations between DNA methylation and mRNA expression were observed. Immune checkpoint expression correlated positively, and DNA methylation negatively, with immune cell infiltration. Higher DNA methylation levels accompanied by lower immune checkpoint expression were observed in RAS-mutated tumors. Conclusion: We suggest epigenetic regulation of immune checkpoints in PTC. Methylation was associated with BRAF and RAS mutation status. DNA methylation might be a promising biomarker candidate in the context of immunotherapies in PTC.

Methylation in HOX Clusters and Its Applications in Cancer Therapy

HOX genes are commonly known for their role in embryonic development, defining the positional identity of most structures along the anterior–posterior axis. In postembryonic life, HOX gene aberrant expression can affect several processes involved in tumorigenesis such as proliferation, apoptosis, migration and invasion. Epigenetic modifications are implicated in gene expression deregulation, and it is accepted that methylation events affecting HOX gene expression play crucial roles in tumorigenesis. In fact, specific methylation profiles in the HOX gene sequence or in HOX-associated histones are recognized as potential biomarkers in several cancers, helping in the prediction of disease outcomes and adding information for decisions regarding the patient’s treatment. The methylation of some HOX genes can be associated with chemotherapy resistance, and its identification may suggest the use of other treatment options. The use of epigenetic drugs affecting generalized or specific DNA methylation profiles, an approach that now deserves much attention, seems likely to be a promising weapon in cancer therapy in the near future. In this review, we summarize these topics, focusing particularly on how the regulation of epigenetic processes may be used in cancer therapy.

Potential of epigenetic events in human thyroid cancer

Thyroid cancer remains the highest prevailing endocrine malignancy, and its incidence rate has progressively increased in the previous years. Above 95% of thyroid tumor are follicular cells types of carcinoma in which are considered invasive type of tumor. The pathogenesis and molecular mechanism of thyroid tumors are yet remains elucidated, in spite of activating RET, RAS and BRAF carcinogenesis have been well introduced. Nemours molecular alterations have been defined and have revealed promise for their diagnostic, prognostic and therapeutic capacity but still need further confirmation. Among different types of mechanisms, the current article reviews the importance of epigenetic modifications in thyroid cancer. Increasing data from previous reports demonstrate that acquired epigenetic abnormalities together with genetic changes plays an important role in alteration of gene expression patterns. Aberrant DNA methylation has been well known in the CpG regions and profile of microRNAs (mi-RNAs) expression also involved in cancer development. In addition, the gene expression through epigenetic control contribution to thyroid cancer is analyzed and it is semi considered in the clinic. However the epigenetic of the thyroid cancer is yet remains in its early stages, and it carries encouraging potential thyroid cancer detections in its early stages, assessment of prognosis and targeted cancer treatment.

Identification of a Robust Methylation Classifier for Cutaneous Melanoma Diagnosis

Early diagnosis improves melanoma survival, yet the histopathological diagnosis of cutaneous primary melanoma can be challenging, even for expert dermatopathologists. Analysis of epigenetic alterations, such as DNA methylation, that occur in melanoma can aid in its early diagnosis. Using a genome-wide methylation screening, we assessed CpG methylation in a diverse set of 89 primary invasive melanomas, 73 nevi, and 41 melanocytic proliferations of uncertain malignant potential, classified based on interobserver review by dermatopathologists. Melanomas and nevi were split into training and validation sets. Predictive modeling in the training set using ElasticNet identified a 40-CpG classifier distinguishing 60 melanomas from 48 nevi. High diagnostic accuracy (area under the receiver operator characteristic curve = 0.996, sensitivity = 96.6%, and specificity = 100.0%) was independently confirmed in the validation set (29 melanomas, 25 nevi) and other published sample sets. The 40-CpG melanoma classifier included homeobox transcription factors and genes with roles in stem cell pluripotency or the nervous system. Application of the 40-CpG melanoma classifier to the diagnostically uncertain samples assigned melanoma or nevus status, potentially offering a diagnostic tool to assist dermatopathologists. In summary, the robust, accurate 40-CpG melanoma classifier offers a promising assay for improving primary melanoma diagnosis.

HORMAD2 methylation-mediated epigenetic regulation of gene expression in thyroid cancer

This study is aimed to investigate the methylation level of candidate genes and its impact on thyroid carcinoma (THCA) development. Infinium Human Methylation 450 BeadChip Arrays by Illumina (Illumina HM450K) was the most popular CpG microarray platform widely used in biological and medical research. The methylation level of differentially expressed genes and their corresponding CpG sites were analysed by R programme. The expression of HORMAD2 was evaluated by qRT-PCR and Western blot, while the methylation level was examined via methylation-specific PCR. Cell viability, metastasis, cell cycle and apoptosis were detected by MTT assay, transwell and wound healing assay and flow cytometry, respectively, after treatment with 5-aza-2'-deoxycytidine (5-Aza). Tumour formation assay was used to analyse thyroid tumour growth in nude mice in vivo. The methylation levels of all 116 differentially expressed genes were analysed. HORMAD2 was significantly hypermethylated and its mRNA expression was inhibited in THCA cells. After treatment with 5-Aza, HORMAD2 expression was up-regulated in THCA cells and its overexpression can suppress thyroid cancer cell viability, mobility and invasiveness remarkably. Up-regulation of HORMAD2 in THCA cells could prolong G0/G1 phase and shorten S phase to impede cell mitosis as well as promote thyroid cancer cells apoptosis. Furthermore, tumour formation assay showed that increased HORMAD2 level impeded tumour growth in vivo. Hypermethylation of HORMAD2 could induce THCA progression, while hypomethylation of HORMAD2 retard cell growth and mobility and facilitate apoptosis through increasing its mRNA expression.

The epigenetic landscape of differentiated thyroid cancer

Differentiated thyroid carcinoma of follicular cell-derivation is the most common endocrine neoplasm with a rapidly increasing incidence. The majority represent papillary carcinomas; more rarely, they are follicular carcinomas. The vast majority have indolent behavior, however a significant proportion progress to develop lymph node metastases and a smaller proportion disseminate systemically. While common and frequent genetic events have been described to underlie the development of these neoplasms, the factors contributing to differing behaviors among tumors with similar genetic alterations remain unclear. This review focuses on epigenetic mechanisms targeting major signaling pathways that underlie the spectrum of biological behaviors and that may have potential diagnostic, prognostic and therapeutic value.

Kallikreins Stepwise Scoring Reveals Three Subtypes of Papillary Thyroid Cancer with Prognostic Implications

BACKGROUND

Papillary thyroid cancer (PTC) is the most common type of thyroid cancer. Unlike most cancers, its incidence has dramatically increased in the last decades mainly due to increased diagnosis of indolent PTCs. Adequate risk stratification is crucial to avoid the over-treatment of low-risk patients, as well as the under-treatment of high-risk patients, but the currently available markers are still insufficient. Kallikreins (KLKs) are emergent biomarkers in cancer, but their involvement in PTC is unknown.

METHODS

This study analyzed DNA methylation (HumanMethylation arrays) and gene expression (RNA-Seq) of KLKs, BRAF and RAS mutations, and clinical data from four published thyroid cancer data sets including normal and tumor tissues (n = 73, n = 475, n = 20, and n = 82) as discovery, training, and validation series. The C4.5 classification algorithm was used to generate a decision tree. Disease-free survival was estimated using Kaplan-Meier and Cox approaches. Specific analyses were performed using real-time polymerase chain reaction and immunohistochemistry.

RESULTS

The entire KLK family was deregulated in PTC, displaying a specific epigenetic and transcriptional profile strongly associated with BRAF^V600E or RAS mutations. Thus, a decision-tree algorithm was developed based on three KLKs with >80% sensitivity and >95% specificity, identifying BRAF- and RAS-mutated tumors. Notably, tumors lacking these mutations were classified as BRAF- or RAS-like. Most importantly, the KLK algorithm uncovered a novel PTC subtype showing favorable prognostic features.

CONCLUSIONS

The KLK algorithm could lead to a new clinically applicable strategy with important implications for the risk stratification of PTC and the management of patients.

Integrated data analysis reveals potential drivers and pathways disrupted by DNA methylation in papillary thyroid carcinomas

BACKGROUND

Papillary thyroid carcinoma (PTC) is a common endocrine neoplasm with a recent increase in incidence in many countries. Although PTC has been explored by gene expression and DNA methylation studies, the regulatory mechanisms of the methylation on the gene expression was poorly clarified. In this study, DNA methylation profile (Illumina HumanMethylation 450K) of 41 PTC paired with non-neoplastic adjacent tissues (NT) was carried out to identify and contribute to the elucidation of the role of novel genic and intergenic regions beyond those described in the promoter and CpG islands (CGI). An integrative and cross-validation analysis were performed aiming to identify molecular drivers and pathways that are PTC-related.

RESULTS

The comparisons between PTC and NT revealed 4995 methylated probes (88% hypomethylated in PTC) and 1446 differentially expressed transcripts cross-validated by the The Cancer Genome Atlas data. The majority of these probes was found in non-promoters regions, distant from CGI and enriched by enhancers. The integrative analysis between gene expression and DNA methylation revealed 185 and 38 genes (mainly in the promoter and body regions, respectively) with negative and positive correlation, respectively. Genes showing negative correlation underlined FGF and retinoic acid signaling as critical canonical pathways disrupted by DNA methylation in PTC. BRAF mutation was detected in 68% (28 of 41) of the tumors, which presented a higher level of demethylation (95% hypomethylated probes) compared with BRAF wild-type tumors. A similar integrative analysis uncovered 40 of 254 differentially expressed genes, which are potentially regulated by DNA methylation in BRAFV600E-positive tumors. The methylation and expression pattern of six selected genes (ERBB3, FGF1, FGFR2, GABRB2, HMGA2, and RDH5) were confirmed as altered by pyrosequencing and RT-qPCR.

CONCLUSIONS

DNA methylation loss in non-promoter, poor CGI and enhancer-enriched regions was a significant event in PTC, especially in tumors harboring BRAFV600E. In addition to the promoter region, gene body and 3'UTR methylation have also the potential to influence the gene expression levels (both, repressing and inducing). The integrative analysis revealed genes potentially regulated by DNA methylation pointing out potential drivers and biomarkers related to PTC development.

CXCL12 methylation-mediated epigenetic regulation of gene expression in papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer, and its incidence rate is rapidly growing. It is necessary to understand the pathogenesis of PTC to develop effective diagnosis methods. Promoter methylation has been recognized to contribute to the alterations in gene expression observed in tumorigenesis. Our RNA-seq data identified 1191 differentially expressed mRNAs and 147 differentially expressed lncRNAs in PTC. Next, promoter methylation of these genes was detected by reduced representation bisulfite sequencing (RRBS) technology and comprehensively analyzed to identify differential methylation. In total, 14 genes (13 mRNAs and 1 lncRNA), in which methylation was intimately involved in regulating gene expression, were proposed as novel diagnostic biomarkers. To gain insights into the relationships among these 14 genes, a core co-function network was constructed based on co-expression, co-function and co-methylation data. Notably, CXCL12 was identified as an essential gene in the network that was closely connected with the other genes. These data suggested that CXCL12 down-regulation in PTC may be caused by promoter hypermethylation. Our study was the first to perform an RRBS analysis for PTC and suggested that CXCL12 may contribute to PTC development by methylation-mediated epigenetic regulation of gene expression.

Promoter hypermethylation of SHOX2 and SEPT9 is a potential biomarker for minimally invasive diagnosis in adenocarcinomas of the biliary tract

BACKGROUND

Biliary tract carcinoma (BTC) is a fatal malignancy which aggressiveness contrasts sharply with its relatively mild and late clinical presentation. Novel molecular markers for early diagnosis and precise treatment are urgently needed. The purpose of this study was to evaluate the diagnostic and prognostic value of promoter hypermethylation of the SHOX2 and SEPT9 gene loci in BTC.

METHODS

Relative DNA methylation of SHOX2 and SEPT9 was quantified in tumor specimens and matched normal adjacent tissue (NAT) from 71 BTC patients, as well as in plasma samples from an independent prospective cohort of 20 cholangiocarcinoma patients and 100 control patients. Receiver operating characteristic (ROC) curve analyses were performed to probe the diagnostic ability of both methylation markers. DNA methylation was correlated to clinicopathological data and to overall survival.

RESULTS

SHOX2 methylation was significantly higher in tumor tissue than in NAT irrespective of tumor localization (p < 0.001) and correctly identified 71% of BTC specimens with 100% specificity (AUC = 0.918; 95% CI 0.865-0.971). SEPT9 hypermethylation was significantly more frequent in gallbladder carcinomas compared to cholangiocarcinomas (p = 0.01) and was associated with large primary tumors (p = 0.01) as well as age (p = 0.03). Cox proportional hazard analysis confirmed microscopic residual tumor at the surgical margin (R1-resection) as an independent prognostic factor, while SHOX2 and SEPT9 methylation showed no correlation with overall survival. Elevated DNA methylation levels were also found in plasma derived from cholangiocarcinoma patients. SHOX2 and SEPT9 methylation as a marker panel achieved a sensitivity of 45% and a specificity of 99% in differentiating between samples from patients with and without cholangiocarcinoma (AUC = 0.752; 95% CI 0.631-0.873).

CONCLUSIONS

SHOX2 and SEPT9 are frequently methylated in biliary tract cancers. Promoter hypermethylation of SHOX2 and SEPT9 may therefore serve as a minimally invasive biomarker supporting diagnosis finding and therapy monitoring in clinical specimens.

Gene expression profiling in undifferentiated thyroid carcinoma induced by high-dose radiation

Published gene expression studies for radiation-induced thyroid carcinogenesis have used various methodologies. In this study, we identified differential gene expression in a human thyroid epithelial cell line after exposure to high-dose γ-radiation. HTori-3 cells were exposed to 5 or 10 Gy of ionizing radiation using two dose rates (high-dose rate: 4.68 Gy/min, and low-dose rate: 40 mGy/h) and then implanted into the backs of BALB/c nude mice after 4 (10 Gy) or 5 weeks (5 Gy). Decreases in cell viability, increases in giant cell frequency, anchorage-independent growth in vitro, and tumorigenicity in vivo were observed. Particularly, the cells irradiated with 5 Gy at the high-dose rate or 10 Gy at the low-dose rate demonstrated more prominent tumorigenicity. Gene expression profiling was analyzed via microarray. Numerous genes that were significantly altered by a fold-change of >50% following irradiation were identified in each group. Gene expression analysis identified six commonly misregulated genes, including CRYAB, IL-18, ZNF845, CYP24A1, OR4N4 and VN1R4, at all doses. These genes involve apoptosis, the immune response, regulation of transcription, and receptor signaling pathways. Overall, the altered genes in high-dose rate (HDR) 5 Gy and low-dose rate (LDR) 10 Gy were more than those of LDR 5 Gy and HDR 10 Gy. Thus, we investigated genes associated with aggressive tumor development using the two dosage treatments. In this study, the identified gene expression profiles reflect the molecular response following high doses of external radiation exposure and may provide helpful information about radiation-induced thyroid tumors in the high-dose range.

A novel analysis strategy for integrating methylation and expression data reveals core pathways for thyroid cancer aetiology

Background

Recently, a wide range of diseases have been associated with changes in DNA methylation levels, which play a vital role in gene expression regulation. With ongoing developments in technology, attempts to understand disease mechanism have benefited greatly from epigenetics and transcriptomics studies. In this work, we have used expression and methylation data of thyroid carcinoma as a case study and explored how to optimally incorporate expression and methylation information into the disease study when both data are available. Moreover, we have also investigated whether there are important post-translational modifiers which could drive critical insights on thyroid cancer genetics.

Results

In this study, we have conducted a threshold analysis for varying methylation levels to identify whether setting a methylation level threshold increases the performance of functional enrichment. Moreover, in order to decide on best-performing analysis strategy, we have performed data integration analysis including comparison of 10 different analysis strategies. As a result, combining methylation with expression and using genes with more than 15% methylation change led to optimal detection rate of thyroid-cancer associated pathways in top 20 functional enrichment results. Furthermore, pooling the data from different experiments increased analysis confidence by improving the data range. Consequently, we have identified 207 transcription factors and 245 post-translational modifiers with more than 15% methylation change which may be important in understanding underlying mechanisms of thyroid cancer.

Conclusion

While only expression or only methylation information would not reveal both primary and secondary mechanisms involved in disease state, combining expression and methylation led to a better detection of thyroid cancer-related genes and pathways that are found in the recent literature. Moreover, focusing on genes that have certain level of methylation change improved the functional enrichment results, revealing the core pathways involved in disease development such as; endocytosis, apoptosis, glutamatergic synapse, MAPK, ErbB, TGF-beta and Toll-like receptor pathways. Overall, in addition to novel analysis framework, our study reveals important thyroid-cancer related mechanisms, secondary molecular alterations and contributes to better knowledge of thyroid cancer aetiology.

Mutation Profile of Well-Differentiated Thyroid Cancer in Asians

Recent advances in molecular diagnostics have led to significant insights into the genetic basis of thyroid tumorigenesis. Among the mutations commonly seen in thyroid cancers, the vast majority are associated with the mitogen-activated protein kinase pathway. B-Raf proto-oncogene (BRAF) mutations are the most common mutations observed in papillary thyroid cancers (PTCs), followed by RET/PTC rearrangements and RAS mutations, while follicular thyroid cancers are more likely to harbor RAS mutations or PAX8/peroxisome proliferator-activated receptor γ (PPARγ) rearrangements. Beyond these more common mutations, alterations in the telomerase reverse transcriptase (TERT) promoter have recently been associated with clinicopathologic features, disease prognosis, and tumorigenesis in thyroid cancer. While the mutations underlying thyroid tumorigenesis are well known, the frequency of these mutations is strongly associated with geography, with clear differences reported between Asian and Western countries. Of particular interest is the prevalence of BRAF mutations, with Korean patients exhibiting the highest rate of BRAF-associated thyroid cancers in the world. Here, we review the prevalence of each of the most common mutations in Asian and Western countries, and identify the characteristics of well-differentiated thyroid cancer in Asians.

Chromatin Memory in the Development of Human Cancers

Cancer is a complex disease with acquired genomic and epigenomic alterations that affect cell proliferation, viability and invasiveness. Almost all the epigenetic mechanisms including cytosine methylation and hydroxymethylation, chromatin remodeling and non-coding RNAs have been found associate with carcinogenesis and cancer specific expression profile. Altered histone modification as an epigenetic hallmark is frequently found in tumors. Understanding the epigenetic alterations induced by carcinogens or infectious agents may help us understand early epigenetic changes prior to the development of cancer. In this review, we focus on chromatin remodeling and the associated histone modifiers in the development of cancer; the application of these modifiers as a cancer therapy target in different clinical trial phases is also discussed.