AHR Over-Expression in Papillary Thyroid Carcinoma: Clinical and Molecular Assessments in a Series of Italian Acromegalic Patients with a Long-Term Follow-Up

Aim

Acromegaly reportedly carries an increased risk of malignant and benign thyroid tumors, with a prevalence of thyroid cancer of around 3–7%. Germline mutations in the aryl-hydrocarbon receptor (AHR) interacting protein (AIP) have been identified in familial forms of acromegaly. The molecular and endocrine relationships between follicular thyroid growth and GH-secreting pituitary adenoma have yet to be fully established. Our aim was to study the prevalence of differentiated thyroid cancer (DTC) in acromegaly, focusing on the role of genetic events responsible for the onset of thyroid cancer.

Methods

Germline mutations in the AIP gene were assessed in all patients; BRAF and H-N-K RAS status was analyzed by direct sequencing in thyroid specimens, while immunohistochemistry was used to analyze the protein expression of AIP and AHR. A set of PTCs unrelated to acromegaly was also studied.

Results

12 DTCs (10 papillary and 2 follicular carcinomas) were identified in a cohort of 113 acromegalic patients. No differences in GH/IGF-1 levels or disease activity emerged between patients with and without DTC, but the former were older and more often female. BRAF V600E was found in 70% of the papillary thyroid cancers; there were no RAS mutations. AIP protein expression was similar in neoplastic and normal cells, while AHR protein was expressed more in PTCs carrying BRAF mutations than in normal tissue, irrespective of acromegaly status.

Conclusions

The prevalence of DTC in acromegaly is around 11% and endocrinologists should bear this in mind, especially when examining elderly female patients with uninodular goiter. The DTC risk does not seem to correlate with GH/IGF-1 levels, while it may be associated with BRAF mutations and AHR over-expression. Genetic or epigenetic events probably play a part in promoting thyroid carcinoma.     

Sonographic Features Of Multifocal Papillary Thyroid Carcinomas

Objective: It is uncertain whether papillary thyroid carcinomas (PTCs) of the same subtype display similar sonographic features. This retrospective analysis of pre-operative sonographic and pathologic findings aimed to assess whether PTCs of the same subtype share sonographic features.Methods: Before undergoing thyroid surgery, 137 patients underwent ultrasound (US) examination. A single radiologist used a picture archiving and communication system and pathologic reports to investigate all sonographic features of the largest and second largest PTCs. Additionally, the radiologist evaluated the similarity of sonographic features between primary (largest), secondary (second largest), and daughter (secondary with same subtype as the primary) PTCs.Results: Of the 137 PTC patients, 48 (35.0%) had multiple PTCs; however, 5 had no US images of the secondary PTC. Of the 43 secondary PTCs with US images, 9 (20.9%) secondary PTCs were of a different subtype than the primary PTC and revealed sonographic features that differed from those of the primary PTC. Of the 48 patients with multiple PTCs, the subtype was the same in the primary and secondary PTCs in 34 (70.8%) patients. Of the 34 daughter PTCs, 32 (94.1%) had sonographic features similar to those of the primary PTC, whereas 2 (5.9%) showed different sonographic features than the primary PTC. There was no significant difference between primary and daughter PTCs in the size, location, sonographic features, or Korean Thyroid Imaging Reporting and Data System category (P>.05).Conclusion: Daughter PTCs show similar sonographic features as the primary PTC.Abbreviations: K-TIRADS = Korean Thyroid Imaging Reporting and Data System; PTC = papillary thyroid carcinoma; US = ultrasound     

Comprehensive gene expression analysis reveals multiple signal pathways associated with prostate cancer

Prostate cancer (PC) depends on androgenic signaling for growth and survival. To data, the exact molecular mechanism of hormone controlling proliferation and tumorigenesis in the PC remains unclear. Therefore, in this study, we explored the differentially expressed genes (DEGs) and identified featured genes related to hormone stimulus from PC. Two sets of gene expression data, including PC and normal control sample, were downloaded from Gene Expression Omnibus (GEO) database. The t-test was used to identify DEGs between PC and controls. Gene ontology (GO) functional annotation was applied to analyze the function of DEGs and screen hormone-related DEGs. Then these hormone-related DEGs were further analyzed in constructed cancer network and Human Protein Reference Database to screen important signaling pathways they participated in. A total of 912 DEGs were obtained which included 326 up-regulated genes and 586 down-regulated genes. GO functional enrichment analysis identified 50 hormone-related DEGs associated with PC. After pathway and PPI network analysis, we found these hormone-related DEGs participated in several important signaling pathways including TGF-β (TGFB2, TGFB3 and TGFBR2), MAPK (TGFB2, TGFB3 and TGFBR2), insulin (PIK3R3, SHC1 and EIF4EBP1), and p53 signaling pathways (CCND2 and CDKN1A). In addition, a total of five hormone-related DEGs (SHC1, CAV1, RXRA, CDKN1A and SRF) were located in the center of PPI network and 12 hormone-related DEGs formed six protein modules. These important signal pathways and hormone-related DEGs may provide potential therapeutic targets for PC.     

Identification and validation of key genes associated with non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is one of the main causes of death induced by cancer globally. However, the molecular aberrations in NSCLC patients remain unclearly. In the present study, four messenger RNA microarray datasets (GSE18842, GSE40275, GSE43458, and GSE102287) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between NSCLC tissues and adjacent lung tissues were obtained from GEO2R and the overlapping DEGs were identified. Moreover, functional and pathway enrichment were performed by Funrich, while the protein–protein interaction (PPI) network construction were obtained from STRING and hub genes were visualized and identified by Cytoscape software. Furthermore, validation, overall survival (OS) and tumor staging analysis of selected hub genes were performed by GEPIA. A total of 367 DEGs (95 upregulated and 272 downregulated) were obtained through gene integration analysis. The PPI network consisted of 94 nodes and 1036 edges in the upregulated DEGs and 272 nodes and 464 edges in the downregulated DEGs, respectively. The PPI network identified 46 upregulated and 27 downregulated hub genes among the DEGs, and six (such as CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M) of that have not been identified to be associated with NSCLC so far. Moreover, the expression differences of the mentioned hub genes were consistent with that in lung adenocarcinoma and lung squamous cell carcinoma in the TCGA database. Further analysis showed that all the six hub genes were associated with tumor staging except MYH11, while only the upregulated DEG CENPE was associated with the worse OS of patients with NSCLC. In conclusion, the current study showed that CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M might be the key genes contributed to tumorigenesis or tumor progression in NSCLC, further functional study is needed to explore the involved mechanisms.     

Expression Profiling of Mitochondrial Voltage-Dependent Anion Channel-1 Associated Genes Predicts Recurrence-Free Survival in Human Carcinomas

Background

Mitochondrial voltage-dependent anion channels (VDACs) play a key role in mitochondria-mediated apoptosis. Both in vivo and in vitro evidences indicate that VDACs are actively involved in tumor progression. Specifically, VDAC-1, one member of the VDAC family, was thought to be a potential anti-cancer therapeutic target. Our previous study demonstrated that the human gene VDAC1 (encoding the VDAC-1 isoform) was significantly up-regulated in lung tumor tissue compared with normal tissue. Also, we found a significant positive correlation between the gene expression of VDAC1 and histological grade in breast cancer. However, the prognostic power of VDAC1 and its associated genes in human cancers is largely unknown.

Methods

We systematically analyzed the expression pattern of VDAC1 and its interacting genes in breast, colon, liver, lung, pancreatic, and thyroid cancers. The genes differentially expressed between normal and tumor tissues in human carcinomas were identified.

Results

The expression level of VDAC1 was uniformly up-regulated in tumor tissue compared with normal tissue in breast, colon, liver, lung, pancreatic, and thyroid cancers. Forty-four VDAC1 interacting genes were identified as being commonly differentially expressed between normal and tumor tissues in human carcinomas. We designated VDAC1 and the 44 dysregulated interacting genes as the VDAC1 associated gene signature (VAG). We demonstrate that the VAG signature is a robust prognostic biomarker to predict recurrence-free survival in breast, colon, and lung cancers, and is independent of standard clinical and pathological prognostic factors.

Conclusions

VAG represents a promising prognostic biomarker in human cancers, which may enhance prediction accuracy in identifying patients at higher risk for recurrence. Future therapies aimed specifically at VDAC1 associated genes may lead to novel agents in the treatment of cancer.     

BRAF mutation and RASSF1A expression in thyroid carcinoma of southern Italy

Aim of this work is to provide a detailed comparison of clinical‐pathologic features between well‐differentiated and poorly differentiated tumors according to their BRAF and RASSF1A status. We analyzed RASSF1A methylation by MSP and BRAF mutation by LCRT‐PCR with LightMix® kit BRAF V600E in neoplastic thyroid tissues. Immunohistochemical evaluation of RASSF1A expression was also performed by standard automated LSAB‐HRP technique. An overall higher degree of RASSF1A over‐expression than normal thyroid parenchyma surrounding tumors (P < 0.05) has been found in all malignant well‐differentiated lesions. Moreover, statistically significant higher levels of RASSF1A expression were observed in differentiated cancers associated to an inflammatory autoimmune background (P = 0.01). Amplifiable DNA for LC PCR with LightMix® kit BRAF V600E was obtained in nine PTCs, four FVPTCs, five ATCs, and one control. The V600E mutation was found in 13 of 18 (72%) tumors. BRAF was mutated in 6 of 9 (66%) classical PTC, in 2 of 4 (50%) follicular variant PTC and in all ACs (100%). The overall frequency of RASSF1A promoter methylation observed was 20.5% (9 cases out 44). Hypermethylation of RASSF1A in primary tumors was variable according to histotypes ranging from100% (5/5) in ACs to only 12.5% (4/32) in PTCs. We show a correlation between RASSF1A methylation status and RASSF1A protein expression. Finally, we conclude that BRAF V600E mutation and RASSF1A methylation were pathogenetic event restricted to a subgroup of PTC/FVPTCs in early stage and to clinically aggressive ATCs. J. Cell. Biochem. 114: 1174–1182, 2013. © 2012 Wiley Periodicals, Inc.     

Uncovering the pathogenesis and identifying novel targets of pancreatic cancer using bioinformatics approach

Pancreatic cancer is a uniformly lethal disease that can be difficult to diagnose at its early stage. Thus, our present study aimed to explore the underlying mechanism and identify new targets for this disease. The data GSE16515, including 36 tumor and 16 normal samples were available from Gene Expression Omnibus. Differentially expressed genes (DEGs) were screened out using Robust Multichip Averaging and LIMMA package. Moreover, gene ontology and pathway enrichment analyses were performed to DEGs. Followed with protein–protein interaction (PPI) network construction by STRING and Cytoscape, module analysis was conducted using ClusterONE. Finally, based on PubMed, text mining about these DEGs was carried out. Total 274 up-regulated and 93 down-regulated genes were identified as the common DEGs and these genes were discovered significantly enriched in cell adhesion and extracellular region terms, as well as ECM-receptor interaction pathway. In addition, five modules were screened out from the up-regulated PPI network with none in down-regulated network. Finally, the up-regulated genes, including MIA, MET and CEACAMS, and down-regulated genes, such as FGF, INS and LAPP, had the most references in text mining analysis. Our findings demonstrate that the up- and down-regulated genes play important roles in pancreatic cancer development and might be new targets for the therapy.     

The Role of Podoplanin in the Biology of Differentiated Thyroid Cancers

Podoplanin (PDPN), a mucin-type transmembrane glycoprotein specific to the lymphatic system is expressed in a variety of human cancers, and is regarded as a factor promoting tumor progression. The purpose of this study was to elucidate the molecular role of PDPN in the biology of thyroid cancer cells. PDPN expression was evaluated in primary thyroid carcinomas and thyroid carcinoma cell lines by RT-qPCR, Western blotting, IF and IHC. To examine the role of podoplanin in determining a cell''s malignant potential (cellular migration, invasion, proliferation, adhesion, motility, apoptosis), a thyroid cancer cell line with silenced PDPN expression was used. We observed that PDPN was solely expressed in the cancer cells of 40% of papillary thyroid carcinoma (PTC) tissues. Moreover, PDPN mRNA and protein were highly expressed in PTC-derived TPC1 and BcPAP cell lines but were not detected in follicular thyroid cancer derived cell lines. PDPN knock-down significantly decreased cellular invasion, and modestly reduced cell migration, while proliferation and adhesion were not affected. Our results demonstrate that PDPN mediates the invasive properties of cells derived from papillary thyroid carcinomas, suggesting that podoplanin might promote PTC progression.     

Notch Pathway Is Activated by MAPK Signaling and Influences Papillary Thyroid Cancer Proliferation

Mutually exclusive genetic alterations in the RET, RAS, or BRAF genes, which result in constitutively active mitogen-activated protein kinase (MAPK) signaling, are present in about 70% of papillary thyroid carcinomas (PTCs). However, the effect of MAPK activation on other signaling pathways involved in oncogenic transformation, such as Notch, remains unclear. In this study, we tested the hypothesis that the MAPK pathway regulates Notch signaling and that Notch signaling plays a role in PTC cell proliferation. Conditional induction of MAPK signaling oncogenes RET/PTC3 or BRAF^T1799A in normal rat thyroid cell line mediated activation of Notch signaling, upregulating Notch1 receptor and Hes1, the downstream effector of Notch pathway. Conversely, pharmacological inhibition of MAPK reduced Notch signaling in PTC cell. Thyroid tumor samples from transgenic mice expressing BRAF^T1799A and primary human PTC samples showed high levels of Notch1 expression. Down-regulation of Notch signaling by γ-secretase inhibitor (GSI) or NOTCH1 RNA interference reduces PTC cell proliferation. Moreover, the combination of GSI with a MAPK inhibitor enhanced the growth suppression in PTC cells. This study revealed that RET/PTC and BRAF^T1799A activate Notch signaling and promote tumor growth in thyroid follicular cell. Taken together, these data suggest that Notch signaling may be explored as an adjuvant therapy for thyroid papillary cancer.     

MiR-20a Is Upregulated in Anaplastic Thyroid Cancer and Targets LIMK1

Background

There have been conflicting reports regarding the function of miR-20a in a variety of cancer types and we previously found it to be dysregulated in sporadic versus familial papillary thyroid cancer. In this study, we studied the expression of miR-20a in normal, benign and malignant thyroid samples, and its effect on thyroid cancer cells in vitro and in vivo.

Methodology/Principal Findings

The expression of miR-20a in normal, benign and malignant thyroid tissue was determined by quantitative RT-PCR. Thyroid cancer cells were transfected with miR-20a and the effect on cellular proliferation, tumor spheroid formation, and invasion was evaluated. Target genes of miR-20 were determined by genome-wide mRNA expression analysis with miR-20a overexpression in thyroid cancer cells and target prediction database. Target genes were validated by quantitative PCR and immunoblotting, and luciferase assays. MiR-20a expression was significantly higher in anaplastic thyroid cancer than in differentiated thyroid cancer, and benign and normal thyroid tissues. MiR-20a significantly inhibited thyroid cancer cell proliferation in vitro (p<0.01) and in vivo (p<0.01), tumor spheroid formation (p<0.05) and invasion (p<0.05) in multiple thyroid cancer cell lines. We found that LIMK1 was a target of miR-20a in thyroid cancer cell lines and direct knockdown of LIMK1 recapitulated the effect of miR-20a in thyroid cancer cells.

Conclusions/Significance

To our knowledge, this is the first study to demonstrate that miR-20a plays a role as a tumor suppressor in thyroid cancer cells and targets LIMK1. Our findings suggest the upregulated expression of miR-20a in anaplastic thyroid cancer counteracts thyroid cancer progression and may have therapeutic potential.     

Identification of drug target candidates of the swine pathogen <Emphasis Type="Italic">Actinobacillus pleuropneumoniae</Emphasis> by construction of protein–protein interaction network

Porcine pleuropneumonia caused by Actinobacillus pleuropneumoniae has led to severe economic losses in the pig industry worldwide. A. pleuropneumoniae displays various levels of antimicrobial resistance, leading to the dire need to identify new drug targets. Protein–protein interaction (PPI) network can aid the identification of drug targets by discovering essential proteins during the life of bacteria. The aim of this study is to identify drug target candidates of A. pleuropneumoniae from essential proteins in PPI network. The homologous protein mapping method (HPM) was utilized to construct A. pleuropneumoniae PPI network. Afterwards, the subnetwork centered with H-NS was selected to verify the PPI network using bacterial two-hybrid assays. Drug target candidates were identified from the hub proteins by analyzing the topology of the network using interaction degree and homologous comparison with the pig proteome. An A. pleuropneumoniae PPI network containing 2737 non-redundant interaction pairs among 533 proteins was constructed. These proteins were distributed in 21 COG functional categories and 28 KEGG metabolic pathways. The A. pleuropneumoniae PPI network was scale free and the similar topological tendencies were found when compared with other bacteria PPI network. Furthermore, 56.3% of the H-NS subnetwork interactions were validated. 57 highly connected proteins (hub proteins) were identified from the A. pleuropneumoniae PPI network. Finally, 9 potential drug targets were identified from the hub proteins, with no homologs in swine. This study provides drug target candidates, which are promising for further investigations to explore lead compounds against A. pleuropneumoniae.