A glycolytic metabolite bypasses "two-hit" tumor suppression by BRCA2.

Knudson's "two-hit" paradigm posits that carcinogenesis requires inactivation of both copies of an autosomal tumor suppressor gene. Here, we report that the glycolytic metabolite methylglyoxal (MGO) transiently bypasses Knudson's paradigm by inactivating the breast cancer suppressor protein BRCA2 to elicit a cancer-associated, mutational single-base substitution (SBS) signature in nonmalignant mammary cells or patient-derived organoids. Germline monoallelic BRCA2 mutations predispose to these changes. An analogous SBS signature, again without biallelic BRCA2 inactivation, accompanies MGO accumulation and DNA damage in Kras-driven, Brca2-mutant murine pancreatic cancers and human breast cancers. MGO triggers BRCA2 proteolysis, temporarily disabling BRCA2's tumor suppressive functions in DNA repair and replication, causing functional haploinsufficiency. Intermittent MGO exposure incites episodic SBS mutations without permanent BRCA2 inactivation. Thus, a metabolic mechanism wherein MGO-induced BRCA2 haploinsufficiency transiently bypasses Knudson's two-hit requirement could link glycolysis activation by oncogenes, metabolic disorders, or dietary challenges to mutational signatures implicated in cancer evolution.

Activity of pemetrexed in pre-clinical chordoma models and humans.

Chordomas are rare slow growing tumors, arising from embryonic remnants of notochord with a close predilection for the axial skeleton. Recurrence is common and no effective standard medical therapy exists. Thymidylate synthase (TS), an intracellular enzyme, is a key rate-limiting enzyme of DNA biosynthesis and repair which is primarily active in proliferating and metabolically active cells. Eighty-four percent of chordoma samples had loss of TS expression which may predict response to anti-folates. Pemetrexed suppresses tumor growth by inhibiting enzymes involved in folate metabolism, resulting in decreased availability of thymidine which is necessary for DNA synthesis. Pemetrexed inhibited growth in a preclinical mouse xenograft model of human chordoma. We report three cases of metastatic chordoma that had been heavily treated previously with a variety of standard therapies with poor response. In two cases, pemetrexed was added and objective responses were observed on imaging with one patient on continuous treatment for > 2 years with continued shrinkage. One case demonstrated tumor growth after treatment with pemetrexed. The two cases which had a favorable response had a loss of TS expression, whereas the one case with progressive disease had TS present. These results demonstrate the activity of pemetrexed in recurrent chordoma and warrant a prospective clinical trial which is ongoing (NCT03955042).

Exploring the role of cerebrospinal fluid as analyte in neurologic disorders.

The cerebrospinal fluid (CSF) is a clear ultrafiltrate of blood that envelopes and protects the central nervous system while regulating neuronal function through the maintenance of interstitial fluid homeostasis in the brain. Due to its anatomic location and physiological functions, the CSF can provide a reliable source of biomarkers for the diagnosis and treatment monitoring of different neurological diseases, including neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and primary and secondary brain malignancies. The incorporation of CSF biomarkers into the drug discovery and development can improve the efficiency of drug development and increase the chances of success. This review aims to consolidate the current use of CSF biomarkers in clinical practice and explore future perspectives for the field.

Cerebrospinal fluid (CSF) is a clear fluid that protects our brain and spinal cord, and can help diagnose and monitor neurological diseases like Alzheimer's and Parkinson's. Biomarkers in CSF are like clues that help doctors and researchers better understand these diseases. By using CSF biomarkers, doctors can diagnose and monitor patients more accurately, while researchers can develop more effective treatments. This review looks at how we use CSF biomarkers in medicine and how they might help us in the future. Better understanding of CSF biomarkers can improve the lives of people living with neurological diseases.

MTAP loss: a possible therapeutic approach for glioblastoma.

Glioblastoma is the most lethal form of brain tumor with a recurrence rate of almost 90% and a survival time of only 15 months post-diagnosis. It is a highly heterogeneous, aggressive, and extensively studied tumor. Multiple studies have proposed therapeutic approaches to mitigate or improve the survival for patients with glioblastoma. In this article, we review the loss of the 5'-methylthioadenosine phosphorylase (MTAP) gene as a potential therapeutic approach for treating glioblastoma. MTAP encodes a metabolic enzyme required for the metabolism of polyamines and purines leading to DNA synthesis. Multiple studies have explored the loss of this gene and have shown its relevance as a therapeutic approach to glioblastoma tumor mitigation; however, other studies show that the loss of MTAP does not have a major impact on the course of the disease. This article reviews the contrasting findings of MTAP loss with regard to mitigating the effects of glioblastoma, and also focuses on multiple aspects of MTAP loss in glioblastoma by providing insights into the known findings and some of the unexplored areas of this field where new approaches can be imagined for novel glioblastoma therapeutics.

Anomaly Detection Framework for Wearables Data: A Perspective Review on Data Concepts, Data Analysis Algorithms and Prospects.

Wearable devices use sensors to evaluate physiological parameters, such as the heart rate, pulse rate, number of steps taken, body fat and diet. The continuous monitoring of physiological parameters offers a potential solution to assess personal healthcare. Identifying outliers or anomalies in heart rates and other features can help identify patterns that can play a significant role in understanding the underlying cause of disease states. Since anomalies are present within the vast amount of data generated by wearable device sensors, identifying anomalies requires accurate automated techniques. Given the clinical significance of anomalies and their impact on diagnosis and treatment, a wide range of detection methods have been proposed to detect anomalies. Much of what is reported herein is based on previously published literature. Clinical studies employing wearable devices are also increasing. In this article, we review the nature of the wearables-associated data and the downstream processing methods for detecting anomalies. In addition, we also review supervised and un-supervised techniques as well as semi-supervised methods that overcome the challenges of missing and un-annotated healthcare data.

A Functional Variant on 9p21.3 Related to Glioma Risk Affects Enhancer Activity and Modulates Expression of CDKN2B-AS1.

Genome-wide association studies have identified SNPs associated with glioma risk on 9p21.3, but biological mechanisms underlying this association are unknown. We tested the hypothesis that a functional SNP on 9p21.3 affects activity of an enhancer, causing altered expression of nearby genes. We considered all SNPs in linkage disequilibrium with the 9p21.3 sentinel SNP rs634537 that mapped to putative enhancers. An enhancer containing rs1537372 exhibited allele-specific effects on luciferase activity. Deletion of this enhancer in GBM cell lines correlated with decreased expression of CDKN2B-AS1. Expression quantitative trait loci analysis using non-diseased brain samples showed rs1537372 to be a consistently significant eQTL for CDKN2B-AS1. Additionally, our analysis of Hi-C data generated in neural progenitor cells showed that the bait region containing rs1537372 interacted with the CDKN2B-AS1 promoter. These data suggest rs1537372, a SNP at the 9p21.3 risk locus, is a functional variant that modulates expression of CDKN2B-AS1.

Meta-Analyses of Splicing and Expression Quantitative Trait Loci Identified Susceptibility Genes of Glioma.

BACKGROUND: The functions of most glioma risk alleles are unknown. Very few studies had evaluated expression quantitative trait loci (eQTL), and insights of susceptibility genes were limited due to scarcity of available brain tissues. Moreover, no prior study had examined the effect of glioma risk alleles on alternative RNA splicing. OBJECTIVE: This study explored splicing quantitative trait loci (sQTL) as molecular QTL and improved the power of QTL mapping through meta-analyses of both cis eQTL and sQTL. METHODS: We first evaluated eQTLs and sQTLs of the CommonMind Consortium (CMC) and Genotype-Tissue Expression Project (GTEx) using genotyping, or whole-genome sequencing and RNA-seq data. Alternative splicing events were characterized using an annotation-free method that detected intron excision events. Then, we conducted meta-analyses by pooling the eQTL and sQTL results of CMC and GTEx using the inverse variance-weighted model. Afterward, we integrated QTL meta-analysis results (Q < 0.05) with the Glioma International Case Control Study (GICC) GWAS meta-analysis (case:12,496, control:18,190), using a summary statistics-based mendelian randomization (SMR) method. RESULTS: Between CMC and GTEx, we combined the QTL data of 354 unique individuals of European ancestry. SMR analyses revealed 15 eQTLs in 11 loci and 32 sQTLs in 9 loci relevant to glioma risk. Two loci only harbored sQTLs (1q44 and 16p13.3). In seven loci, both eQTL and sQTL coexisted (2q33.3, 7p11.2, 11q23.3 15q24.2, 16p12.1, 20q13.33, and 22q13.1), but the target genes were different for five of these seven loci. Three eQTL loci (9p21.3, 20q13.33, and 22q13.1) and 4 sQTL loci (11q23.3, 16p13.3, 16q12.1, and 20q13.33) harbored multiple target genes. Eight target genes of sQTLs (C2orf80, SEC61G, TMEM25, PHLDB1, RP11-161M6.2, HEATR3, RTEL1-TNFRSF6B, and LIME1) had multiple alternatively spliced transcripts. CONCLUSION: Our study revealed that the regulation of transcriptome by glioma risk alleles is complex, with the potential for eQTL and sQTL jointly affecting gliomagenesis in risk loci. QTLs of many loci involved multiple target genes, some of which were specific to alternative splicing. Therefore, quantitative trait loci that evaluate only total gene expression will miss many important target genes.

A functional variant on 20q13.33 related to glioma risk alters enhancer activity and modulates expression of multiple genes.

Genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) associated with glioma risk on 20q13.33, but the biological mechanisms underlying this association are unknown. We tested the hypothesis that a functional SNP on 20q13.33 impacted the activity of an enhancer, leading to an altered expression of nearby genes. To identify candidate functional SNPs, we identified all SNPs in linkage disequilibrium with the risk-associated SNP rs2297440 that mapped to putative enhancers. Putative enhancers containing candidate functional SNPs were tested for allele-specific effects in luciferase enhancer activity assays against glioblastoma multiforme (GBM) cell lines. An enhancer containing SNP rs3761124 exhibited allele-specific effects on activity. Deletion of this enhancer by CRISPR-Cas9 editing in GBM cell lines correlated with an altered expression of multiple genes, including STMN3, RTEL1, RTEL1-TNFRSF6B, GMEB2, and SRMS. Expression quantitative trait loci (eQTL) analyses using nondiseased brain samples, isocitrate dehydrogenase 1 (IDH1) wild-type glioma, and neurodevelopmental tissues showed STMN3 to be a consistent significant eQTL with rs3761124. RTEL1 and GMEB2 were also significant eQTLs in the context of early CNS development and/or in IDH1 wild-type glioma. We provide evidence that rs3761124 is a functional variant on 20q13.33 related to glioma/GBM risk that modulates the expression of STMN3 and potentially other genes across diverse cellular contexts.

STAT3 Regulates Mouse Neural Progenitor Proliferation and Differentiation by Promoting Mitochondrial Metabolism.

The proliferation and differentiation of neural progenitor lay the foundation for brain development. In neural progenitors, activation of Signal Transducer and Activator of Transcription 3 (STAT3) has been found to promote proliferation and astrocytogenesis while suppressing neurogenesis. However, our study found that Stat3 conditional knockout in neural progenitors (Stat3 cKO) also results in increased proliferation and suppressed neurogenesis. To investigate how STAT3 regulates these processes, we attempted to identify potential STAT3 target genes by RNA-seq profiling of the control (CTL) and Stat3 cKO neural progenitors. We found that STAT3 promotes the expression of genes involved in the mitochondrial oxidative phosphorylation (OXPHOS), and thereby promotes mitochondrial respiration and negatively regulates reactive oxygen species (ROS) production. In addition, we demonstrated that Stat3 loss-of-function promotes proliferation via regulation of mitochondrial metabolism and downstream signaling pathways. Our study provides novel insights into the relation between STAT3, mitochondrial metabolism and the process of embryonic neurogenesis.

Human cytomegalovirus may promote tumour progression by upregulating arginase-2.

BACKGROUND: Both arginase (ARG2) and human cytomegalovirus (HCMV) have been implicated in tumorigenesis. However, the role of ARG2 in the pathogenesis of glioblastoma (GBM) and the HCMV effects on ARG2 are unknown. We hypothesize that HCMV may contribute to tumorigenesis by increasing ARG2 expression. RESULTS: ARG2 promotes tumorigenesis by increasing cellular proliferation, migration, invasion and vasculogenic mimicry in GBM cells, at least in part due to overexpression of MMP2/9. The nor-NOHA significantly reduced migration and tube formation of ARG2-overexpressing cells. HCMV immediate-early proteins (IE1/2) or its downstream pathways upregulated the expression of ARG2 in U-251 MG cells. Immunostaining of GBM tissue sections confirmed the overexpression of ARG2, consistent with data from subsets of Gene Expression Omnibus. Moreover, higher levels of ARG2 expression tended to be associated with poorer survival in GBM patient by analyzing data from TCGA. METHODS: The role of ARG2 in tumorigenesis was examined by proliferation-, migration-, invasion-, wound healing- and tube formation assays using an ARG2-overexpressing cell line and ARG inhibitor, N (omega)-hydroxy-nor-L-arginine (nor-NOHA) and siRNA against ARG2 coupled with functional assays measuring MMP2/9 activity, VEGF levels and nitric oxide synthase activity. Association between HCMV and ARG2 were examined in vitro with 3 different GBM cell lines, and ex vivo with immunostaining on GBM tissue sections. The viral mechanism mediating ARG2 induction was examined by siRNA approach. Correlation between ARG2 expression and patient survival was extrapolated from bioinformatics analysis on data from The Cancer Genome Atlas (TCGA). CONCLUSIONS: ARG2 promotes tumorigenesis, and HCMV may contribute to GBM pathogenesis by upregulating ARG2.

STATdb: a specialised resource for the STATome.

Signal transducers and activators of transcription (STAT) proteins are key signalling molecules in metazoans, implicated in various cellular processes. Increased research in the field has resulted in the accumulation of STAT sequence and structure data, which are scattered across various public databases, missing extensive functional annotations, and prone to effort redundancy because of the dearth of community sharing. Therefore, there is a need to integrate the existing sequence, structure and functional data into a central repository, one that is enriched with annotations and provides a platform for community contributions. Herein, we present STATdb (publicly available at http://statdb.bic.nus.edu.sg/), the first integrated resource for STAT sequences comprising 1540 records representing the known STATome, enriched with existing structural and functional information from various databases and literature and including manual annotations. STATdb provides advanced features for data visualization, analysis and prediction, and community contributions. A key feature is a meta-predictor to characterise STAT sequences based on a novel classification that integrates STAT domain architecture, lineage and function. A curation policy workflow has been devised for regulated and structured community contributions, with an update policy for the seamless integration of new data and annotations.

Simple re-instantiation of small databases using cloud computing.

BACKGROUND: Small bioinformatics databases, unlike institutionally funded large databases, are vulnerable to discontinuation and many reported in publications are no longer accessible. This leads to irreproducible scientific work and redundant effort, impeding the pace of scientific progress. RESULTS: We describe a Web-accessible system, available online at http://biodb100.apbionet.org, for archival and future on demand re-instantiation of small databases within minutes. Depositors can rebuild their databases by downloading a Linux live operating system (http://www.bioslax.com), preinstalled with bioinformatics and UNIX tools. The database and its dependencies can be compressed into an ".lzm" file for deposition. End-users can search for archived databases and activate them on dynamically re-instantiated BioSlax instances, run as virtual machines over the two popular full virtualization standard cloud-computing platforms, Xen Hypervisor or vSphere. The system is adaptable to increasing demand for disk storage or computational load and allows database developers to use the re-instantiated databases for integration and development of new databases. CONCLUSIONS: Herein, we demonstrate that a relatively inexpensive solution can be implemented for archival of bioinformatics databases and their rapid re-instantiation should the live databases disappear.