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Background: Telomerase reverse transcriptase promoter (TERTp) mutations are related to a worse prognosis in various malignancies, including papillary thyroid carcinoma (PTC). Since mechanisms responsible for the poorer outcome of TERTp(+) patients are still unknown, searching for molecular consequences of TERTp mutations in PTC was the aim of our study. Methods: The studied cohort consisted of 54 PTCs, among them 24 cases with distant metastases. BRAF V600E, RAS, and TERTp mutational status was evaluated in all cases. Differences in gene expression profile between TERTp(+) and TERTp(&minus, ) PTCs were examined using microarrays. The evaluation of signaling pathways and gene ontology was based on the Gene Set Enrichment Analysis. Results: Fifty-nine percent (32/54) of analyzed PTCs were positive for at least one mutation: 27 were BRAF(+), among them eight were TERTp(+), and 1 NRAS(+), whereas five other samples harbored RAS mutations. Expression of four genes significantly differed in BRAF(+)TERTp(+) and BRAF(+)TERTp(&minus, ) PTCs. Deregulation of pathways involved in key cell processes was observed. Conclusions: TERTp mutations are related to higher PTC aggressiveness. CRABP2 gene was validated as associated with TERTp mutations. However, its potential use in diagnostics or risk stratification in PTC patients needs further studies.

Papillary thyroid carcinoma (PTC) is most common among all thyroid cancers. Multiple genomic alterations occur in PTC, and gene rearrangements are one of them. Here we screened 14 tumors for novel fusion transcripts by RNA-Seq. Two samples harboring RET/PTC1 and RET/PTC3 rearrangements were positive controls whereas the remaining ones were negative regarding the common PTC alterations. We used Sanger sequencing to validate potential fusions. We detected 2 novel potentially oncogenic transcript fusions: TG-FGFR1 and TRIM33-NTRK1. We detected 4 novel fusion transcripts of unknown significance accompanying the TRIM33-NTRK1 fusion: ZSWIM5-TP53BP2, TAF4B-WDR1, ABI2-MTA3, and ARID1B-PSMA1. Apart from confirming the presence of RET/PTC1 and RET/PTC3 in positive control samples, we also detected known oncogenic fusion transcripts in remaining samples: TFG-NTRK1, ETV6-NTRK3, MKRN1-BRAF, EML4-ALK, and novel isoform of CCDC6-RET.

Transcriptome of papillary thyroid cancer (PTC) is well characterized and correlates with some prognostic and genotypic factors, but data addressing the interaction between PTC and tumor microenvironment (TME) are scarce. Therefore, in the present study, we aimed to assess the impact of TME on gene expression profile in PTC. We evaluated the gene expression profile in PTC and normal thyroid cells isolated by laser capture microdissection and in whole tissue slides corresponding to the entire tumor. We included 26 microdissected samples for gene expression analysis (HG-U133 PLUS 2.0, Affymetrix, currently Thermo Fisher Scientific USA): 15 PTC samples, 11 samples of normal thyrocytes, and 30 whole slides (15 PTC and 15 normal thyroid). Transcripts were divided into three groups: differentially expressed both in microdissected and whole slides, transcripts differently expressed in microdissected samples and not changed in whole slides, and transcripts differentially expressed in whole slides and not changed in microdissected samples. Eleven genes were selected for validation in an independent set of samples; among them, four genes differentiated only microdissected PTC and normal cells. Two genes (PTCSC and CTGF) were confirmed. One gene (FOS) was not confirmed by the validation, whereas EGR1 was also significant in whole slide analysis. The other seven genes (TFF3, FN1, MPPED2, MET, KCNJ2, TACSTD2, and GALE) showed differentiated expression in microdissected thyrocytes and in whole tumor slides. Most of identified genes were related to the tumor-microenvironment interaction and confirmed the crosstalk between TME and cancer cells.

There are 5 main histological types of thyroid cancers (TCs): papillary, follicular (also known as differentiated), poorly differentiated, anaplastic (the most aggressive form), and medullary TC, and only the latter arises from thyroid C cells. These different forms of TCs show significant variability, both among and within tumours. This great variation is particularly notable among the first 4 types, which all originate from thyroid follicular cells. Importantly, this heterogeneity is not limited to histopathological diversity only but is also manifested as variation in several genetic and/or epigenetic alterations, the numbers of interactions between the tumour and surrounding microenvironment, and interpatient differences, for example. All these factors contribute to the great complexity in the development of a tumour from cancer cells. In the present review, we summarise the knowledge accumulated about the heterogeneity of TCs. Further research in this direction should help to gain a better understanding of the underlying mechanisms contributing to the development and diversity of TCs, paving the way toward more effective treatment strategies.

The molecular etiology of follicular thyroid tumors is largely unknown, rendering the diagnostics of these tumors challenging. The somatic alterations present in these tumors apart from RAS gene mutations and PAX8/PPARG translocations are not well described. To evaluate the profile of somatic alteration in follicular thyroid tumors, a total of 82 thyroid tissue samples derived from 48 patients were subjected to targeted Illumina HiSeq next generation sequencing of 372 cancer-related genes. New somatic alterations were identified in oncogenes (MDM2, FLI1), transcription factors and repressors (MITF, FLI1, ZNF331), epigenetic enzymes (KMT2A, NSD1, NCOA1, NCOA2), and protein kinases (JAK3, CHEK2, ALK). Single nucleotide and large structural variants were most and least frequently identified, respectively. A novel translocation in DERL/COX6C was detected. Many somatic alterations in non-coding gene regions with high penetrance were observed. Thus, follicular thyroid tumor somatic alterations exhibit complex patterns. Most tumors contained distinct somatic alterations, suggesting previously unreported heterogeneity.

Molecular mechanisms of distant metastases (M1) in papillary thyroid cancer (PTC) are poorly understood. We attempted to analyze the gene expression profile in PTC primary tumors to seek the genes associated with M1 status and characterize their molecular function. One hundred and twenty-three patients, including 36 M1 cases, were subjected to transcriptome oligonucleotide microarray analyses: (set A&mdash, U133, set B&mdash, HG 1.0 ST) at transcript and gene group level (limma, gene set enrichment analysis (GSEA)). An additional independent set of 63 PTCs, including 9 M1 cases, was used to validate results by qPCR. The analysis on dataset A detected eleven transcripts showing significant differences in expression between metastatic and non-metastatic PTC. These genes were validated on microarray dataset B. The differential expression was positively confirmed for only two genes: IGFBP3, (most significant) and ECM1. However, when analyzed on an independent dataset by qPCR, the IGFBP3 gene showed no differences in expression. Gene group analysis showed differences mainly among immune-related transcripts, indicating the potential influence of tumor immune infiltration or signal within the primary tumor. The differences in gene expression profile between metastatic and non-metastatic PTC, if they exist, are subtle and potentially detectable only in large datasets.

Distinguishing between follicular thyroid cancer (FTC) and follicular thyroid adenoma (FTA) constitutes a long-standing diagnostic problem resulting in equivocal histopathological diagnoses. There is therefore a need for additional molecular markers. To identify molecular differences between FTC and FTA, we analyzed the gene expression microarray data of 52 follicular neoplasms. We also performed a meta-analysis involving 14 studies employing high throughput methods (365 follicular neoplasms analyzed). Based on these two analyses, we selected 18 genes differentially expressed between FTA and FTC. We validated them by quantitative real-time polymerase chain reaction (qRT-PCR) in an independent set of 71 follicular neoplasms from formaldehyde-fixed paraffin embedded (FFPE) tissue material. We confirmed differential expression for 7 genes (CPQ, PLVAP, TFF3, ACVRL1, ZFYVE21, FAM189A2, and CLEC3B). Finally, we created a classifier that distinguished between FTC and FTA with an accuracy of 78%, sensitivity of 76%, and specificity of 80%, based on the expression of 4 genes (CPQ, PLVAP, TFF3, ACVRL1). In our study, we have demonstrated that meta-analysis is a valuable method for selecting possible molecular markers. Based on our results, we conclude that there might exist a plausible limit of gene classifier accuracy of approximately 80%, when follicular tumors are discriminated based on formalin-fixed postoperative material.

Wstep: Rak pecherzykowy tarczycy (FTC) jest nowotworem ktorego podloze molekularne jest malo zbadane. W podjetej analizie transkryptomu oceniono mozliwośc dyskryminacji raka i gruczolaka pecherzykowego tarczycy (FTA) na podstawie badan profilu ekspresji genow metodą tzw. nienadzorowaną (tzn. na podstawie dominujących źrodel zmienności). Analize te prowadzono by sprawdzic czy zlośliwośc guza jest rzeczywiście czynnikiem dominującym dla profilu ekspresji genow w nowotworach pecherzykowych. Material i metody: Podstawowy zbior guzow pecherzykowych obejmowal 52 probki (27 FTC i 25 FTA), z ktorych wyizolowano calkowity RNA i poddano badaniu na mikromacierzach HG-U133 Plus 2.0. Otrzymany zbior normalizowano za pomocą RMA i GC-RMA. Identyfikacji glownych źrodel zmienności dokonano metodą analizy glownych skladowych (PCA). Wyniki: Analize funkcji biologicznej genow przeprowadzono dla pierwszych 6 skladowych glownych. Geny skorelowane z pierwszą skladową pozwalaly wyodrebnic 2 klastry probek: jeden zlozony glownie z gruczolakow, z wysoką ekspresją miedzy innymi transkryptow tarczycowo-swoistych, drugi zaś, zawierający wiekszośc rakow, wykazywal zwiekszoną, ale heterogenną ekspresje genow związanych z odpowiedzią immunologiczną, a obnizoną ekspresje genow tarczycowych. Geny odpowiedzi immunologicznej stwierdzono wśrod transkryptow skorelowanych przebiegiem pierwszej, trzeciej i szostej glownej skladowej; w istotny sposob wplywaly one na rozroznienie miedzy FTC i FTA. Wnioski: W analizie nienadzorowanej stwierdzono, ze zlośliwośc (inwazyjnośc) nowotworu pecherzykowego moze byc jednym z glownych źrodel zmienności w transkryptomie tych guzow. Jednak, genomiczna odleglośc miedzy grupami FTC i FTA jest niewielka, a wyodrebnione w analizie nienadzorowanej klastry nakladają sie, stąd sama analiza nienadzorowana nie jest wystarczającym narzedziem do celow klasyfikacji tych guzow. (Endokrynol Pol 2013; 64 (5): 329–334)

Medullary thyroid cancer (MTC) can be caused by germline mutations of the RET proto-oncogene or occurs as a sporadic form. It is well known that RET mutations affecting the cysteine-rich region of the protein (MEN2A-like mutations) are correlated with different phenotypes than those in the kinase domain (MEN2B-like mutations). Our aim was to analyse the whole-gene expression profile of MTC with regard to the type of RET gene mutation and the cancer genetic background (hereditary vs sporadic). We studied 86 MTC samples. We demonstrated that there were no distinct differences in the gene expression profiles of hereditary and sporadic MTCs. This suggests a homogeneous nature of MTC. We also noticed that the site of the RET gene mutation slightly influenced the gene expression profile of MTC. We found a significant association between the localization of RET mutations and the expression of three genes: NNAT (suggested to be a tumour suppressor gene), CDC14B (involved in cell cycle control) and NTRK3 (tyrosine receptor kinase that undergoes rearrangement in papillary thyroid cancer). This study suggests that these genes are significantly deregulated in tumours with MEN2A-like and MEN2B-like mutations; however, further investigations are necessary to demonstrate any clinical impact of these findings.

Triple-negative breast cancer (TNBC) lacks expression of steroid hormone receptors (estrogen receptor α and progesterone) and epidermal growth factor receptor type 2. This phenotype shows high metastatic potential, with particular predilection to lungs and brain. Determination of TNBC transcriptomic profiles associated with high risk of brain metastasis (BM) might identify patients requiring alternative, more aggressive, or specific preventive and therapeutic approaches.Using a cDNA-mediated annealing, selection, extension, and ligation assay, we investigated expression of 29,369 gene transcripts in primary TNBC tumor samples from 119 patients-71 in discovery cohort A and 48 in independent cohort B-that included best discriminating genes. Expression of mRNA was correlated with the occurrence of symptomatic BM.In cohort A, the difference at the noncorrected P .005 was found for 64 transcripts (P = .23 for global test), but none showed significant difference at a preset level of false-discovery rate of 10%. Of the 30 transcripts with the largest differences between patients with and without BM in cohort A, none was significantly associated with BM in cohort B.Analysis based on the primary tumor gene transcripts alone is unlikely to predict BM development in advanced TNBC. Despite its negative findings, the study adds to the knowledge on the biology of TNBC and paves the way for future projects using more advanced molecular assays.

Background Infinium HumanMethylation 450 BeadChip Arrays by Illumina (Illumina HM450K) are among the most popular CpG microarray platforms widely used in biological and medical research. Several recent studies highlighted the potentially confounding impact of the genomic variation on the results of methylation studies performed using Illumina’s Infinium methylation probes. However, the complexity of SNPs impact on the methylation level measurements (β values) has not been comprehensively described. Results In our comparative study of European and Asian populations performed using Illumina HM450K, we found that the majority of Infinium probes, which differentiated two examined groups, had SNPs in their target sequence. Characteristic tri-modal or bi-modal patterns of β values distribution among individual samples were observed for CpGs with SNPs in the first and second position, respectively. To better understand how SNPs affect methylation readouts, we investigated their impact in the context of SNP position and type, and of the Illumina probe type (Infinium I or II). Conclusions Our study clearly demonstrates that SNP variation existing in the genome, if not accounted for, may lead to false interpretation of the methylation signal differences suggested by some of the Illumina Infinium probes. In addition, it provides important practical clues for discriminating between differences due to the methylation status and to the genomic polymorphisms, based on the inspection of methylation readouts in individual samples. This approach is of special importance when Illumina Infinium assay is used for any comparative population studies, whether related to cancer, disease, ethnicity where SNP frequencies differentiate the studied groups.

Background The molecular mechanisms driving the papillary thyroid carcinoma (PTC) are still poorly understood. The most frequent genetic alteration in PTC is the BRAFV600E mutation–its impact may extend even beyond PTC genomic profile and influence the tumor characteristics and even clinical behavior. Methods In order to identify BRAF-dependent signature of early carcinogenesis in PTC, a transgenic mouse model with BRAFV600E-induced PTC was developed. Mice thyroid samples were used in microarray analysis and the data were referred to a human thyroid dataset. Results Most of BRAF(+) mice developed malignant lesions. Nevertheless, 16% of BRAF(+) mice displayed only benign hyperplastic lesions or apparently asymptomatic thyroids. After comparison of non-malignant BRAF(+) thyroids to BRAF(−) ones, we selected 862 significantly deregulated genes. When the mouse BRAF-dependent signature was transposed to the human HG-U133A microarray, we identified 532 genes, potentially indicating the BRAF signature (representing early changes, not related to developed malignant tumor). Comparing BRAF(+) PTCs to healthy human thyroids, PTCs without BRAF and RET alterations and RET(+), RAS(+) PTCs, 18 of these 532 genes displayed significantly deregulated expression in all subgroups. All 18 genes, among them 7 novel and previously not reported, were validated as BRAFV600E-specific in the dataset of independent PTC samples, made available by The Cancer Genome Atlas Project. Conclusion The study identified 7 BRAF-induced genes that are specific for BRAF V600E-driven PTC and not previously reported as related to BRAF mutation or thyroid carcinoma: MMD, ITPR3, AACS, LAD1, PVRL3, ALDH3B1, and RASA1. The full signature of BRAF-related 532 genes may encompass other BRAF-related important transcripts and require further study.

Introduction: As far as pathogenesis of the atopic dermatitis (AD) is concerned, the roles of an impaired epidermal barrier and cornified cell envelope are widely emphasized. Aim : The assessment of mutations of the filaggrin gene and their connection with the clinical picture of AD as well as selected allergological and environmental indicators. Material and methods: 105 patients with diagnosed AD on the basis of diagnostic criteria were included. For every patient of the examined group, quantitative determination of the total concentration of IgE and the concentration of IgE antibodies to selected allergens were examined. For all patients, studies were performed by means of analysis of two genomic gene variants of profilaggrin (FLG) – R501X and 2282del4. Results : Loss-of-function mutations in the filaggrin gene were shown in 12 (11.4%) patients in the examined group. All patients in the study group who developed one of the tested loss-of-function mutations in the filaggrin gene demonstrated an extrinsic, allergic form of atopic dermatitis. A significant association (p = 0.0002) between the presence of one of the tested loss-of-function mutations in the filaggrin gene and elevated levels of total concentration of immunoglobulin E was shown. Conclusions : Patients with AD of null mutations in the filaggrin gene demonstrate a relationship with the total and specific concentration of immunoglobulin E, specifically higher concentrations of IgE against aeroallergens and alimentary allergens as well as elevated levels of total immunoglobulin E.

Background Differential diagnosis between malignant follicular thyroid cancer (FTC) and benign follicular thyroid adenoma (FTA) is a great challenge for even an experienced pathologist and requires special effort. Molecular markers may potentially support a differential diagnosis between FTC and FTA in postoperative specimens. The purpose of this study was to derive molecular support for differential post-operative diagnosis, in the form of a simple multigene mRNA-based classifier that would differentiate between FTC and FTA tissue samples. Methods A molecular classifier was created based on a combined analysis of two microarray datasets (using 66 thyroid samples). The performance of the classifier was assessed using an independent dataset comprising 71 formalin-fixed paraffin-embedded (FFPE) samples (31 FTC and 40 FTA), which were analysed by quantitative real-time PCR (qPCR). In addition, three other microarray datasets (62 samples) were used to confirm the utility of the classifier. Results Five of 8 genes selected from training datasets (ELMO1, EMCN, ITIH5, KCNAB1, SLCO2A1) were amplified by qPCR in FFPE material from an independent sample set. Three other genes did not amplify in FFPE material, probably due to low abundance. All 5 analysed genes were downregulated in FTC compared to FTA. The sensitivity and specificity of the 5-gene classifier tested on the FFPE dataset were 71% and 72%, respectively. Conclusions The proposed approach could support histopathological examination: 5-gene classifier may aid in molecular discrimination between FTC and FTA in FFPE material.