In pediatric brain tumours, dissemination of malignant cells within the central nervous system confers poor prognosis and determines treatment intensity, but is often undetectable by imaging or cytology. This study describes the use of fluorescence lifetime (FLT) imaging microscopy (FLIM), a novel diagnostic tool, for detection of metastatic spread. The study group included 15 children with medulloblastoma and 2 with atypical teratoid/rhabdoid tumour. Cells extracted from the tumour and the cerebrospinal fluid (CSF) 2 weeks postoperatively and repeatedly during chemo/radiotherapy were subjected to nuclear staining followed by FLT measurement and cytological study. Control CSF samples were collected from patients with infectious/inflammatory disease attending the same hospital. Median FLT was prolonged in tumour cells (4.27 ± 0.28 ns;P < 2.2*10⁻¹⁶) and CSF metastatic cells obtained before chemo/radiotherapy (6.28 ± 0.22 ns;P < 2.2*10⁻¹⁶); normal in inflammatory control cells (2.6 ± 0.04 ns) and cells from children without metastasis before chemo/radiotherapy (2.62 ± 0.23 ns;P = 0.858) and following treatment (2.62 ± 0.21 ns;P = 0.053); and short in CSF metastatic cells obtained after chemo/radiotherapy (2.40 ± 0.2 ns;P < 2.2*10⁻¹⁶). FLIM is a simple test that can potentially identify CSF spread of brain tumours. FLT changes in accordance with treatment, with significant prolonged median values in tumours and metastases. More accurate detection of metastatic cells may guide personalised treatment and improve the therapeutic outcome.

Purpose: Medulloblastoma (MB), the most common malignant brain tumor in children, is divided into four tumor subgroups: wingless-type (WNT), sonic hedgehog (SHH), Group 3, and Group 4. ­Ideally, clinical practice and treatment design should be subgroup specific. While WNT and SHH subgroups have well-defined biomarkers, distinguishing Group 3 from Group 4 is not straightforward. MicroRNAs (miRNAs), which regulate posttranscriptional gene expression, are involved in MB tumorigenesis. However, the miRNA–messenger RNA (mRNA) regulatory network in MB is far from being fully understood. Our aims were to investigate miRNA expression regulation in MB subgroups, to assess miRNA target relationships, and to identify miRNAs that can distinguish Group 3 from Group 4.
Patients and methods: With these aims, integrated transcriptome mRNA and miRNA expression analysis was performed on primary tumor samples collected from 18 children with MB, using miRNA sequencing (miRNA-seq), RNA sequencing (RNA-seq), and quantitative PCR. Results: Of all the expressed miRNAs, 19 appeared to be significantly differentially expressed (DE) between Group 4 and non-Group 4 subgroups (false discovery rate [FDR] <0.05), including 10 miRNAs, which, for the first time, are reported to be in conjunction with MB. RNA-seq analysis identified 165 genes that were DE between Group 4 and the other subgroups (FDR <0.05), among which seven are predicted targets of five DE miRNAs and exhibit inverse expression pattern. Conclusion: This study identified miRNA molecules that may be involved in Group 4 etiology, in general, and can distinguish between Group 3 and Group 4, in particular. In addition, understanding the involvement of miRNAs and their targets in MB may improve diagnosis and advance the development of targeted treatment for MB.

The RNA-seq technique is applied for the investigation of transcriptional behaviour. The reduction in sequencing costs has led to an unprecedented trove of gene expression data from diverse biological systems. Subsequently, principles from other disciplines such as the Benford law, which can be properly judged only in data-rich systems, can now be examined on this high-throughput transcriptomic information. The Benford law, states that in many count-rich datasets the distribution of the first significant digit is not uniform but rather logarithmic. All tested digital gene expression datasets showed a Benford-like distribution when observing an entire gene set. This phenomenon was conserved in development and does not demonstrate tissue specificity. However, when obedience to the Benford law is calculated for individual expressed genes across thousands of cells, genes that best and least adhere to the Benford law are enriched with tissue specific or cell maintenance descriptors, respectively. Surprisingly, a positive correlation was found between the obedience a gene exhibits to the Benford law and its expression level, despite the former being calculated solely according to first digit frequency while totally ignoring the expression value itself. Nevertheless, genes with low expression that exhibit Benford behavior demonstrate tissue specific associations. These observations were extended to predict the likelihood of tissue specificity based on Benford behaviour in a supervised learning approach. These results demonstrate the applicability and potential predictability of the Benford law for gleaning biological insight from simple count data.

Brain tumors are the second leading cause of cancer-related deaths in children, after leukemia. Patients with cancer in the central nervous system have a very low recovery rate. Today known imaging and cytology techniques are not always sensitive enough for an early detection of both tumor and its metastatic spread, moreover the detection is generally limited, reviewer dependent and takes a relatively long time. Medulloblastoma (MB) is the most common malignant brain tumor in children. The aim of our talk is to present the frequency domain fluorescence lifetime imaging microscopy system as a possible method for an early detection of MB and its metastatic spread in the cerebrospinal fluids within the pediatric population. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.