Epidermal differentiation complex (locus 1q21) gene expression in head and neck cancer and normal mucosa

Epidermal differentiation complex (EDC) comprises a number of genes associated with human skin diseases including psoriasis, atopic dermatitis and hyperkeratosis. These genes have also been linked to numerous cancers, among them skin, gastric, colorectal, lung, ovarian and renal carcinomas. The involvement of EDC components encoding S100 proteins, small proline-rich proteins (SPRRs) and other genes in the tumorigenesis of head and neck squamous cell cancer (HNSCC) has been previously suggested. The aim of the study was to systematically analyze the expression of EDC components on the transcript level in HNSCC. Tissue specimens from 93 patients with HNC of oral cavity and 87 samples from adjacent or distant grossly normal oral mucosawere analyzed. 48 samples (24 tumor and 24 corresponding surrounding tissue) were hybridized to Affymetrix GeneChip Human 1.0 ST Arrays. For validation by quantitative real-time PCR (QPCR) the total RNA from all 180 samples collected in the study was analyzed with Real-Time PCR system and fluorescent amplicon specific-probes. Additional set of samples from 14 patients with laryngeal carcinoma previously obtained by HG-U133 Plus 2.0 microarray was also included in the analyses. The expression of analyzed EDC genes was heterogeneous. Two transcripts (S100A1 and S100A4) were significantly down-regulated in oral cancer when compared to normal mucosa (0.69 and 0.36-fold change, respectively), showing an opposite pattern of expression to the remaining S100 genes. Significant up-regulation in tumors was found for S100A11, S100A7, LCE3D, S100A3 and S100A2 genes. The increased expression of S100A7 was subsequently validated by QPCR, confirming significant differences. The remaining EDC genes, including all encoding SPRR molecules, did not show any differences between oral cancer and normal mucosa. The observed differences were also assessed in the independent set of laryngeal cancer samples, confirming the role of S100A3 and LCE3D transcripts in HNC. In HNC of oral cavity only one family of EDC genes (S100 proteins) showed significant cancer-related differences. A number of other transcripts which showed altered expression in HNC require further validation.

Częstość występowania mutacji somatycznych RAS w raku rdzeniastym tarczycy — analiza populacji polskiej

Introduction: Somatic RET mutations are detectable in two-thirds of sporadic cases of medullary thyroid cancer (MTC). Recent studies reported a high proportion of RAS somatic mutations in RET negative tumours, which may indicate RAS mutation as a possible alternative genetic event in sporadic MTC tumorigenesis. Thus, the aim of the study was to evaluate the frequency of somatic RAS mutations in sporadic medullary thyroid cancer in the Polish population and to relate the obtained data to the presence of somatic RET mutations.Material and methods: Somatic mutations (RET, RAS genes) were evaluated in 78 snap-frozen MTC samples (57 sporadic and 21 hereditary) by direct sequencing. Next, three randomly selected RET-negative MTC samples were analysed by the next generation sequencing.Results: RAS mutation was detected in 26.5% of 49 sporadic MTC tumours. None of all the analysed samples showed N-RAS mutation. When only RET-negative samples were considered, the prevalence of RAS mutation was 68.7%, compared to 6% observed in RET-positive samples. Most of these mutations were located in H-RAS codon 61 (72%). None of 21 hereditary MTC samples showed any RAS mutations.Conclusions: RAS mutations constitute a frequent molecular event in RET-negative sporadic medullary thyroid carcinoma in Polish patients. However, their role in MTC tumorigenesis remains unclear. (Endokrynol Pol 2015; 66 (2): 121–125)Wstęp: Somatyczne mutacje proto-onkogenu RET wykrywane są w trzech czwartych wszystkich sporadycznych raków rdzeniastych tarczycy (MTC). Ostatnie badania wykazały, że mutacja genu RAS jest również częstym wydarzeniem w sporadycznych guzach MTC, co może oznaczać, że mutacje genów z rodziny RAS są alternatywnym wydarzeniem molekularnym w kancerogezie sporadycznej postaci tego raka. Z tego względu celem niniejszej pracy było oszacowanie częstości występowania mutacji genów RAS w sporadycznym raku rdzeniastym tarczycy w populacji polskiej i odniesieniu częstości ich występowania do obecności mutacji somatycznych proto-onkogenu RET.Materiał i metody: Materiał do badań stanowiło 78 fragmentów guza raka rdzeniastego tarczycy (57 próbek postaci sporadycznej i 21 dziedzicznej MTC). Analizowano mutacje genu RET, H-RAS, K-RAS i N-RAS metodą bezpośredniego sekwencjonowania a także 3 próbki raka sporadycznego, wybrane losowo, zostały zeskwencjonowane metodą głębokiego sekwencjonowania (Illumina).Wyniki: Mutację genów RAS wykryto w 26,5% z 49 przeanalizowanych guzów sporadycznej postaci MTC. Natomiast, gdy tylko brano pod uwagę próbki RET-negatywne, częstość występowania mutacji genów RAS wynosiła 68,7% w porównaniu z 6% obserwowanych w guzach RET-pozytywnych. Nie wykryto, w żadnej z próbek, mutacji genu N-RAS. Najczęściej wykrywaną mutacją była zmiana w kodonie 61 genu H-RAS (72%). Nie wykryto mutacji genów RAS w żadnej z próbek dziedzicznego guza raka tarczycy.Wnioski: Mutacje somatyczne genów RAS są częstym wydarzeniem obserwowanym w RET-negatywnych sporadycznych rakach rdzeniastych tarczycy w populacji polskiej. Jednakże rola tych mutacji w rozwoju rdzeniastego raka tarczycy nie jest do końca poznana. (Endokrynol Pol 2015; 66 (2): 121–125

Gene Expression (mRNA) Markers for Differentiating between Malignant and Benign Follicular Thyroid Tumours

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

BRAFV600E-Associated Gene Expression Profile: Early Changes in the Transcriptome, Based on a Transgenic Mouse Model of Papillary Thyroid Carcinoma

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

Hierarchical clustering of mouse samples.

<p>Thirty-eight mouse samples based on 1020 probe sets significantly differentiating between <i>BRAF</i>(+) and <i>BRAF</i>(−) non-malignant mouse samples (marked with blue and cyan respectively). PTCs (red); borderline thyroid lesions (BL; magenta); benign hyperplastic thyroid lesions (BHL; dark green); asymptomatic thyroid glands (AT; green).</p

Boxplots of 18 genes chosen for validation.

<p>Expression distribution for each gene from our microarray data (on the left), The Cancer Genome Atlas Project data (on the right). The expression levels of analyzed genes are presented in <i>BRAF</i>(+) PTCs, <i>RET</i>(+), <i>RAS</i>(+), PTC(-) and healthy thyroids (HT) from left to right, respectively (as presented at the bottom of the figure). FDR values are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0143688#pone.0143688.t004" target="_blank">Table 4</a>.</p

Microarray-derived dataset- human cohort.

<p>PTC(-)- PTCs without any mutation detected</p><p>Microarray-derived dataset- human cohort.</p