Systematic transcriptomic analysis of childhood medulloblastoma identifies N6- methyladenosine-dependent lncRNA signatures associated with molecular subtype, immune cell infiltration, and prognosis.

Medulloblastoma, the most common malignant pediatric brain tumor, is classified into four main molecular subgroups, but group 3 and group 4 tumors are difficult to subclassify and have a poor prognosis. Rapid point-of-care diagnostic and prognostic assays are needed to improve medulloblastoma risk stratification and management. N6-methyladenosine (m6A) is a common RNA modification and long non-coding RNAs (lncRNAs) play a central role in tumor progression, but their impact on gene expression and associated clinical outcomes in medulloblastoma are unknown. Here we analyzed 469 medulloblastoma tumor transcriptomes to identify lncRNAs co-expressed with m6A regulators. Using LASSO-Cox analysis, we identified a five-gene m6A-associated lncRNA signature (M6LSig) significantly associated with overall survival, which was combined in a prognostic clinical nomogram. Using expression of the 67 m6A-associated lncRNAs, a subgroup classification model was generated using the XGBoost machine learning algorithm, which had a classification accuracy > 90%, including for group 3 and 4 samples. All M6LSig genes were significantly correlated with at least one immune cell type abundance in the tumor microenvironment, and the risk score was positively correlated with CD4+ naïve T cell abundance and negatively correlated with follicular helper T cells and eosinophils. Knockdown of key m6A writer genes METTL3 and METTL14 in a group 3 medulloblastoma cell line (D425-Med) decreased cell proliferation and upregulated many M6LSig genes identified in our in silico analysis, suggesting that the signature genes are functional in medulloblastoma. This study highlights a crucial role for m6A-dependent lncRNAs in medulloblastoma prognosis and immune responses and provides the foundation for practical clinical tools that can be rapidly deployed in clinical settings.

Systematic transcriptomic analysis of childhood medulloblastoma identifies N6-methyladenosine-dependent lncRNA signatures associated with molecular subtype, immune cell infiltration, and prognosis.

Medulloblastoma, the most common malignant pediatric brain tumor, is classified into four main molecular subgroups, but group 3 and group 4 tumors are difficult to subclassify and have a poor prognosis. Rapid point-of-care diagnostic and prognostic assays are needed to improve medulloblastoma risk stratification and management. N6-methyladenosine (m6A) is a common RNA modification and long non-coding RNAs (lncRNAs) play a central role in tumor progression, but their impact on gene expression and associated clinical outcomes in medulloblastoma are unknown. Here we analyzed 469 medulloblastoma tumor transcriptomes to identify lncRNAs co-expressed with m6A regulators. Using LASSO-Cox analysis, we identified a five-gene m6A-associated lncRNA signature (M6LSig) significantly associated with overall survival, which was combined in a prognostic clinical nomogram. Using expression of the 67 m6A-associated lncRNAs, a subgroup classification model was generated using the XGBoost machine learning algorithm, which had a classification accuracy > 90%, including for group 3 and 4 samples. All M6LSig genes were significantly correlated with at least one immune cell type abundance in the tumor microenvironment, and the risk score was positively correlated with CD4+ naïve T cell abundance and negatively correlated with follicular helper T cells and eosinophils. Knockdown of key m6A writer genes METTL3 and METTL14 in a group 3 medulloblastoma cell line (D425-Med) decreased cell proliferation and upregulated many M6LSig genes identified in our in silico analysis, suggesting that the signature genes are functional in medulloblastoma. This study highlights a crucial role for m6A-dependent lncRNAs in medulloblastoma prognosis and immune responses and provides the foundation for practical clinical tools that can be rapidly deployed in clinical settings.

A therapeutically targetable positive feedback loop between lnc-HLX-2-7, HLX, and MYC that promotes group 3 medulloblastoma.

Recent studies suggest that long non-coding RNAs (lncRNAs) contribute to medulloblastoma (MB) formation and progression. We have identified an lncRNA, lnc-HLX-2-7, as a potential therapeutic target in group 3 (G3) MBs. lnc-HLX-2-7 RNA specifically accumulates in the promoter region of HLX, a sense-overlapping gene of lnc-HLX-2-7, which activates HLX expression by recruiting multiple factors, including enhancer elements. RNA sequencing and chromatin immunoprecipitation reveal that HLX binds to and activates the promoters of several oncogenes, including TBX2, LIN9, HOXM1, and MYC. Intravenous treatment with cerium-oxide-nanoparticle-coated antisense oligonucleotides targeting lnc-HLX-2-7 (CNP-lnc-HLX-2-7) inhibits tumor growth by 40%-50% in an intracranial MB xenograft mouse model. Combining CNP-lnc-HLX-2-7 with standard-of-care cisplatin further inhibits tumor growth and significantly prolongs mouse survival compared with CNP-lnc-HLX-2-7 monotherapy. Thus, the lnc-HLX-2-7-HLX-MYC axis is important for regulating G3 MB progression, providing a strong rationale for using lnc-HLX-2-7 as a therapeutic target for G3 MBs.

epidecodeR: a functional exploration tool for epigenetic and epitranscriptomic regulation.

Recent technological advances in sequencing DNA and RNA modifications using high-throughput platforms have generated vast epigenomic and epitranscriptomic datasets whose power in transforming life science is yet fully unleashed. Currently available in silico methods have facilitated the identification, positioning and quantitative comparisons of individual modification sites. However, the essential challenge to link specific 'epi-marks' to gene expression in the particular context of cellular and biological processes is unmet. To fast-track exploration, we generated epidecodeR implemented in R, which allows biologists to quickly survey whether an epigenomic or epitranscriptomic status of their interest potentially influences gene expression responses. The evaluation is based on the cumulative distribution function and the statistical significance in differential expression of genes grouped by the number of 'epi-marks'. This tool proves useful in predicting the role of H3K9ac and H3K27ac in associated gene expression after knocking down deacetylases FAM60A and SDS3 and N6-methyl-adenosine-associated gene expression after knocking out the reader proteins. We further used epidecodeR to explore the effectiveness of demethylase FTO inhibitors and histone-associated modifications in drug abuse in animals. epidecodeR is available for downloading as an R package at https://bioconductor.riken.jp/packages/3.13/bioc/html/epidecodeR.html.

miRNA-211 maintains metabolic homeostasis in medulloblastoma through its target gene long-chain acyl-CoA synthetase 4.

The prognosis of childhood medulloblastoma (MB) is often poor, and it usually requires aggressive therapy that adversely affects quality of life. microRNA-211 (miR-211) was previously identified as an important regulator of cells that descend from neural cells. Since medulloblastomas primarily affect cells with similar ontogeny, we investigated the role and mechanism of miR-211 in MB. Here we showed that miR-211 expression was highly downregulated in cell lines, PDXs, and clinical samples of different MB subgroups (SHH, Group 3, and Group 4) compared to normal cerebellum. miR-211 gene was ectopically expressed in transgenic cells from MB subgroups, and they were subjected to molecular and phenotypic investigations. Monoclonal cells stably expressing miR-211 were injected into the mouse cerebellum. miR-211 forced expression acts as a tumor suppressor in MB both in vitro and in vivo, attenuating growth, promoting apoptosis, and inhibiting invasion. In support of emerging regulatory roles of metabolism in various forms of cancer, we identified the acyl-CoA synthetase long-chain family member (ACSL4) as a direct miR-211 target. Furthermore, lipid nanoparticle-coated, dendrimer-coated, and cerium oxide-coated miR-211 nanoparticles were applied to deliver synthetic miR-211 into MB cell lines and cellular responses were assayed. Synthesizing nanoparticle-miR-211 conjugates can suppress MB cell viability and invasion in vitro. Our findings reveal miR-211 as a tumor suppressor and a potential therapeutic agent in MB. This proof-of-concept paves the way for further pre-clinical and clinical development.

Next-Generation Sequencing Technology: Current Trends and Advancements.

The advent of next-generation sequencing (NGS) has brought about a paradigm shift in genomics research, offering unparalleled capabilities for analyzing DNA and RNA molecules in a high-throughput and cost-effective manner. This transformative technology has swiftly propelled genomics advancements across diverse domains. NGS allows for the rapid sequencing of millions of DNA fragments simultaneously, providing comprehensive insights into genome structure, genetic variations, gene expression profiles, and epigenetic modifications. The versatility of NGS platforms has expanded the scope of genomics research, facilitating studies on rare genetic diseases, cancer genomics, microbiome analysis, infectious diseases, and population genetics. Moreover, NGS has enabled the development of targeted therapies, precision medicine approaches, and improved diagnostic methods. This review provides an insightful overview of the current trends and recent advancements in NGS technology, highlighting its potential impact on diverse areas of genomic research. Moreover, the review delves into the challenges encountered and future directions of NGS technology, including endeavors to enhance the accuracy and sensitivity of sequencing data, the development of novel algorithms for data analysis, and the pursuit of more efficient, scalable, and cost-effective solutions that lie ahead.

Diagnostic and therapeutic potential of circular RNA in brain tumors.

Circular RNAs (circRNAs) are a class of RNA with a stable cyclic structure. They are expressed in various tissues and cells with conserved, specific characteristics. CircRNAs have been found to play critical roles in a wide range of cellular processes by regulating gene expression at the epigenetic, transcriptional, and posttranscriptional levels. There is an accumulation of evidence on newly discovered circRNAs, their molecular interactions, and their roles in the development and progression of human brain tumors, including cell proliferation, cell apoptosis, invasion, and chemoresistance. Here we summarize the current state of knowledge of the circRNAs that have been implicated in brain tumor pathogenesis, particularly in gliomas and medulloblastomas. In providing a comprehensive overview of circRNA studies, we highlight how different circRNAs have oncogenic or tumor-suppressive roles in brain tumors, making them attractive therapeutic targets and biomarkers for personalized therapy and precision diagnostics. This review article discusses circRNAs' functional roles and the prospect of using them as diagnostic biomarkers and therapeutic targets in patients with brain tumors.

Hepatic RNA adduction derived from metabolic activation of retrorsine in vitro and in vivo.

Pyrrolizidine alkaloids (PAs) are among the most significant hepatotoxins widely distributed in plant species. Incidence of liver injuries caused by PAs has been reported worldwide, and the reactive metabolites of PAs are known to play a critical role in causing the hepatotoxicity. To better understand the toxicity-induction mechanisms, we explored the interactions of PA metabolites with cellular RNA molecules, and examined their effects on the biochemical and metabolic properties of hepatic RNAs. After exposure to retrorsine, adduction on adenosine and guanosine were detected in mouse liver microsomal incubations, cultured mouse primary hepatocytes, and mouse liver tissues. NMR analysis showed that the exocyclic amino group participated in the adduction. We found drastically altered properties and metabolism of the adducted RNA such as reverse-transcriptability, translatability, and RNase-susceptibility. In addition, endogenous modification of N6-methyladenosine (m6A) was remarkably reduced.

Systematic pharmacogenomics analysis of a Malay whole genome: proof of concept for personalized medicine.

BACKGROUND: With a higher throughput and lower cost in sequencing, second generation sequencing technology has immense potential for translation into clinical practice and in the realization of pharmacogenomics based patient care. The systematic analysis of whole genome sequences to assess patient to patient variability in pharmacokinetics and pharmacodynamics responses towards drugs would be the next step in future medicine in line with the vision of personalizing medicine. METHODS: Genomic DNA obtained from a 55 years old, self-declared healthy, anonymous male of Malay descent was sequenced. The subject's mother died of lung cancer and the father had a history of schizophrenia and deceased at the age of 65 years old. A systematic, intuitive computational workflow/pipeline integrating custom algorithm in tandem with large datasets of variant annotations and gene functions for genetic variations with pharmacogenomics impact was developed. A comprehensive pathway map of drug transport, metabolism and action was used as a template to map non-synonymous variations with potential functional consequences. PRINCIPAL FINDINGS: Over 3 million known variations and 100,898 novel variations in the Malay genome were identified. Further in-depth pharmacogenetics analysis revealed a total of 607 unique variants in 563 proteins, with the eventual identification of 4 drug transport genes, 2 drug metabolizing enzyme genes and 33 target genes harboring deleterious SNVs involved in pharmacological pathways, which could have a potential role in clinical settings. CONCLUSIONS: The current study successfully unravels the potential of personal genome sequencing in understanding the functionally relevant variations with potential influence on drug transport, metabolism and differential therapeutic outcomes. These will be essential for realizing personalized medicine through the use of comprehensive computational pipeline for systematic data mining and analysis.