Sensitive detection of FGFR1 N546K mosaic mutation in patient with encephalocraniocutaneous lipomatosis and pilocytic astrocytoma.

Encephalocraniocutaneous lipomatosis (ECCL) is a rare neurocutaneous disorder, with only about 100 cases reported worldwide. It is characterized by congenital lesions of the eye, skin, and central nervous system. Only recently, potential causative FGFR1 point mutations have been identified in brain tumors and cultured skin biopsies from patients with this condition. Here, we analyzed the molecular status of a patient with ECCL and a coexisting pilocytic astrocytoma with detected FGFR1 N546K mutation. The presence of the alteration in both affected and unaffected tissues has been evaluated using Sanger sequencing and droplet digital polymerase chain reaction (ddPCR) technique. The ddPCR analysis showed differential distribution of the alteration in all specimens, including unaffected and untreated samples. Therefore, we confirm that FGFR1 N546K is a plausible causative mutation of ECCL patients and could be associated with a risk of brain tumor development. We also show the usefulness of sensitive ddPCR method for detection of low levels of autosomal mosaic mutation in blood or swabs. We suggest that utilization of this method may improve the diagnostic process, especially when targeted therapies are considered.

Expression-based decision tree model reveals distinct microRNA expression pattern in pediatric neuronal and mixed neuronal-glial tumors.

BACKGROUND: The understanding of the molecular biology of pediatric neuronal and mixed neuronal-glial brain tumors is still insufficient due to low frequency and heterogeneity of those lesions which comprise several subtypes presenting neuronal and/or neuronal-glial differentiation. Important is that the most frequent ganglioglioma (GG) and dysembryoplastic neuroepithelial tumor (DNET) showed limited number of detectable molecular alterations. In such cases analyses of additional genomic mechanisms seem to be the most promising. The aim of the study was to evaluate microRNA (miRNA) profiles in GGs, DNETs and pilocytic asytrocytomas (PA) and test the hypothesis of plausible miRNA connection with histopathological subtypes of particular pediatric glial and mixed glioneronal tumors. METHODS: The study was designed as the two-stage analysis. Microarray testing was performed with the use of the miRCURY LNA microRNA Array technology in 51 cases. Validation set comprised 107 samples used during confirmation of the profiling results by qPCR bioinformatic analysis. RESULTS: Microarray data was compared between the groups using an analysis of variance with the Benjamini-Hochberg procedure used to estimate false discovery rates. After filtration 782 miRNAs were eligible for further analysis. Based on the results of 10 × 10-fold cross-validation J48 algorithm was identified as the most resilient to overfitting. Pairwise comparison showed the DNETs to be the most divergent with the largest number of miRNAs differing from either of the two comparative groups. Validation of array analysis was performed for miRNAs used in the classification model: miR-155-5p, miR-4754, miR-4530, miR-628-3p, let-7b-3p, miR-4758-3p, miRPlus-A1086 and miR-891a-5p. Model developed on their expression measured by qPCR showed weighted AUC of 0.97 (95% CI for all classes ranging from 0.91 to 1.00). A computational analysis was used to identify mRNA targets for final set of selected miRNAs using miRWalk database. Among genomic targets of selected molecules ZBTB20, LCOR, PFKFB2, SYNJ2BP and TPD52 genes were noted. CONCLUSIONS: Our data showed the existence of miRNAs which expression is specific for different histological types of tumors. miRNA expression analysis may be useful in in-depth molecular diagnostic process of the tumors and could elucidate their origins and molecular background.