MicroRNAs (miRs) are involved in the pathogenesis of several neoplasms; however, there are no data on their expression patterns and possible roles in adrenocortical tumors. Our objective was to study adrenocortical tumors by an integrative bioinformatics analysis involving miR and transcriptomics profiling, pathway analysis, and a novel, tissue-specific miR target prediction approach. Thirty-six tissue samples including normal adrenocortical tissues, benign adenomas, and adrenocortical carcinomas (ACC) were studied by simultaneous miR and mRNA profiling. A novel data-processing software was used to identify all predicted miR–mRNA interactions retrieved from PicTar, TargetScan, and miRBase. Tissue-specific target prediction was achieved by filtering out mRNAs with undetectable expression and searching for mRNA targets with inverse expression alterations as their regulatory miRs. Target sets and significant microarray data were subjected to Ingenuity Pathway Analysis. Six miRs with significantly different expression were found. miR-184 and miR-503 showed significantly higher, whereas miR-511 and miR-214 showed significantly lower expression in ACCs than in other groups. Expression of miR-210 was significantly lower in cortisol-secreting adenomas than in ACCs. By calculating the difference between dCTmiR-511 and dCTmiR-503 (delta cycle threshold), ACCs could be distinguished from benign adenomas with high sensitivity and specificity. Pathway analysis revealed the possible involvement of G2/M checkpoint damage in ACC pathogenesis. To our knowledge, this is the first report describing miR expression patterns and pathway analysis in sporadic adrenocortical tumors. miR biomarkers may be helpful for the diagnosis of adrenocortical malignancy. This tissue-specific target prediction approach may be used in other tumors too.
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Zsófia Tömböl, Peter M Szabó, Viktor Molnár, Zoltán Wiener, Gergely Tölgyesi, János Horányi, Peter Riesz, Peter Reismann, Attila Patócs, István Likó, Rolf-Christian Gaillard, András Falus, Károly Rácz, and Peter Igaz
Birke Bausch, Ulrich Wellner, Dirk Bausch, Francesca Schiavi, Marta Barontini, Gabriela Sanso, Martin K Walz, Mariola Peczkowska, Georges Weryha, Patrizia Dall'Igna, Giovanni Cecchetto, Gianni Bisogno, Lars C Moeller, Detlef Bockenhauer, Attila Patocs, Karoly Rácz, Dmitry Zabolotnyi, Svetlana Yaremchuk, Iveta Dzivite-Krisane, Frederic Castinetti, David Taieb, Angelica Malinoc, Ernst von Dobschuetz, Jochen Roessler, Kurt W Schmid, Giuseppe Opocher, Charis Eng, and Hartmut P H Neumann
A third of patients with paraganglial tumors, pheochromocytoma, and paraganglioma, carry germline mutations in one of the susceptibility genes, RET, VHL, NF1, SDHAF2, SDHA, SDHB, SDHC, SDHD, TMEM127, and MAX. Despite increasing importance, data for long-term prognosis are scarce in pediatric presentations. The European-American-Pheochromocytoma–Paraganglioma-Registry, with a total of 2001 patients with confirmed paraganglial tumors, was the platform for this study. Molecular genetic and phenotypic classification and assessment of gene-specific long-term outcome with second and/or malignant paraganglial tumors and life expectancy were performed in patients diagnosed at <18 years. Of 177 eligible registrants, 80% had mutations, 49% VHL, 15% SDHB, 10% SDHD, 4% NF1, and one patient each in RET, SDHA, and SDHC. A second primary paraganglial tumor developed in 38% with increasing frequency over time, reaching 50% at 30 years after initial diagnosis. Their prevalence was associated with hereditary disease (P=0.001), particularly in VHL and SDHD mutation carriers (VHL vs others, P=0.001 and SDHD vs others, P=0.042). A total of 16 (9%) patients with hereditary disease had malignant tumors, ten at initial diagnosis and another six during follow-up. The highest prevalence was associated with SDHB (SDHB vs others, P<0.001). Eight patients died (5%), all of whom had germline mutations. Mean life expectancy was 62 years with hereditary disease. Hereditary disease and the underlying germline mutation define the long-term prognosis of pediatric patients in terms of prevalence and time of second primaries, malignant transformation, and survival. Based on these data, gene-adjusted, specific surveillance guidelines can help effective preventive medicine.