Classifying Medulloblastoma Subgroups Based on Small, Clinically Achievable Gene Sets.

As treatment protocols for medulloblastoma (MB) are becoming subgroup-specific, means for reliably distinguishing between its subgroups are a timely need. Currently available methods include immunohistochemical stains, which are subjective and often inconclusive, and molecular techniques-e.g., NanoString, microarrays, or DNA methylation assays-which are time-consuming, expensive and not widely available. Quantitative PCR (qPCR) provides a good alternative for these methods, but the current NanoString panel which includes 22 genes is impractical for qPCR. Here, we applied machine-learning-based classifiers to extract reliable, concise gene sets for distinguishing between the four MB subgroups, and we compared the accuracy of these gene sets to that of the known NanoString 22-gene set. We validated our results using an independent microarray-based dataset of 92 samples of all four subgroups. In addition, we performed a qPCR validation on a cohort of 18 patients diagnosed with SHH, Group 3 and Group 4 MB. We found that the 22-gene set can be reduced to only six genes (IMPG2, NPR3, KHDRBS2, RBM24, WIF1, and EMX2) without compromising accuracy. The identified gene set is sufficiently small to make a qPCR-based MB subgroup classification easily accessible to clinicians, even in developing, poorly equipped countries.

Differences in RNA and microRNA Expression Between PTCH1- and SUFU-mutated Medulloblastoma.

BACKGROUND/AIM: Germline mutations in PTCH1 or SUFU in the sonic hedgehog (SHH) pathway cause Gorlin's syndrome with increased risk of developing SHH-subgroup medulloblastoma. Gorlin's syndrome precludes the use of radiotherapy (a standard component of treatment) due to the development of multiple basal cell carcinomas. Also, current SHH inhibitors are ineffective against SUFU-mutated medulloblastoma, as they inhibit upstream genes. In this study, we aimed to detect differences in the expression of genes and microRNAs between SUFU- and PTCH1-mutated SHH medulloblastomas which may hint at new treatment directions. PATIENTS AND METHODS: We sequenced RNA and microRNA from tumors of two patients with germline Gorlin's syndrome - one having PTCH1 mutation and one with SUFU mutation - followed by bioinformatics analysis to detect changes in genes and miRNAs expression in these two tumors. Expression changes were validated using qRT-PCR. Ingenuity pathway analysis was performed in search for targetable pathways. RESULTS: Compared to the PTCH1 tumor, the SUFU tumor demonstrated lower expression of miR-301a-3p and miR-181c-5p, matrix metallopeptidase 11 (MMP11) and OTX2, higher expression of miR-7-5p and corresponding lower expression of its targeted gene, connexin 30 (GJB6). We propose mechanisms to explain the phenotypic differences between the two types of tumors, and understand why PTCH1 and SUFU tumors tend to relapse locally (rather than metastatically as in other medulloblastoma subgroups). CONCLUSION: Our results help towards finding new treatable molecular targets for these types of medulloblastomas.

Pathogen Detection Using Frequency Domain Fluorescent Lifetime Measurements.

OBJECTIVE: Inflammation of the meninges is a source of severe morbidity and therefore is an important health concerns worldwide. The conventional clinical microbiology approaches used today to identify pathogens suffer from several drawbacks and frequently provide false results. This research describes a fast method to detect the presence of pathogens using the frequency domain (FD) fluorescence lifetime (FLT) imaging microscopy (FLIM) system. METHODS: The study included 43 individuals divided into 4 groups: 9 diagnosed with different types of bacteria; 16 diagnosed with different types of viruses; 5 healthy samples served as a control; and 12 samples were negative to any pathogen, although presenting related symptoms. All samples contained leukocytes that were extracted from the cerebrospinal fluid (CSF) and were subjected to nuclear staining by 4', 6-diamidino-2-phenylindole (DAPI) and FLT analyses based on phase and amplitude crossing point (CRPO). RESULTS: Using notched boxplots, we found differences in 95% probability between the first three groups through different notch ranges (NR). Pathogen samples presented a longer median FLT (3.28 ns with NR of 3.24-3.32 ns in bacteria and 3.18 ns with NR of 3.16-3.21 ns in viruses) compared to the control median FLT (2.65 ns with NR of 2.63-2.67 ns). Furthermore, we found that the undetected forth group was divided into two types: a relatively normal median FLT (2.72 ns with NR of 2.68-2.76 ns) and a prolonged FLT (3.22 ns with NR of 3.17-3.27 ns). CONCLUSION: FLT measurements can differentiate between control and pathogen by the CRPO method. SIGNIFICANCE: The FD-FLIM system can provide a high throughput diagnostic technique that does not require a physician.

MicroRNA-mRNA expression profiles associated with medulloblastoma subgroup 4.

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.

Fluorescence Lifetime Imaging Microscopy, a Novel Diagnostic Tool for Metastatic Cell Detection in the Cerebrospinal Fluid of Children with Medulloblastoma.

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.

Utilizing fluorescent life time imaging microscopy technology for identify carriers of BRCA2 mutation.

Worldwide, more than one million women are diagnosed with breast cancer every year, making it the most common female malignancy in the developed world. Germline mutations in BRCA1 and BRCA2 genes are estimated to increase the risk for developing breast cancer by up to 87%. From a clinical point of view, identification of BRCA1 and BRCA2 mutation carriers offers an opportunity to early identify or prevent the development of malignancy; therefore the ability to determine which women are more likely to carry BRCA1 or BRCA2 mutations is of great importance. The available diagnostic tests for mutation analysis of BRCA1 and BRCA2 are time- and labor-intensive, expensive, and do not allow the identification of all the functional mutations. We utilized the Fluorescent lifetime (FLT) imaging microscopy method which allows recognizing different cell populations, in order to distinguish between lymphocytes from BRCA1 and BRCA2 mutation carriers and non-carrier women by using easily obtainable lymphocyte cells from peripheral blood. Our results demonstrate that cells originated from BRCA2-mutation carriers have significantly lower FLT values compared with BRCA1 mutation carriers and control cells. This simple, inexpensive and sensitive method may be utilized in the future to detect BRCA2 mutation carriers, particularly those bearing unknown functional mutations.

Elucidating tissue specific genes using the Benford distribution.

BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: These results demonstrate the applicability and potential predictability of the Benford law for gleaning biological insight from simple count data.

Fast closure of N-terminal long loops but slow formation of ß strands precedes the folding transition state of Escherichia coli adenylate kinase.

The nature of the earliest steps of the initiation of the folding pathway of globular proteins is still controversial. To elucidate the role of early closure of long loop structures in the folding transition, we studied the folding kinetics of subdomain structures in Escherichia coli adenylate kinase (AK) using Förster type resonance excitation energy transfer (FRET)-based methods. The overall folding rate of the AK molecule and of several segments that form native ß strands is 0.5 ± 0.3 s(-1), in sharp contrast to the 1000-fold faster closure of three long loop structures in the CORE domain. A FRET-based "double kinetics" analysis revealed complex transient changes in the initially closed N-terminal loop structure that then opens and closes again at the end of the folding pathway. The study of subdomain folding in situ suggests a hierarchic ordered folding mechanism, in which early and rapid cross-linking by hydrophobic loop closure provides structural stabilization at the initiation of the folding pathway.