Neuronal cell adhesion molecule (NRCAM) variant defined by microexon skipping is an essential, antigenically distinct, and targetable proteoform in high-grade glioma.

Unlabelled: To overcome the paucity of known tumor-specific surface antigens in pediatric high-grade glioma (pHGG), we contrasted splicing patterns in pHGGs and normal brain samples. Among alternative splicing events affecting extracellular protein domains, the most pervasive alteration was the skipping of ≤30 nucleotide-long microexons. Several of these skipped microexons mapped to L1-IgCAM family members, such as .

Genetic ancestry superpopulations show distinct prevalence and outcomes across pediatric central nervous system tumors from the PBTA and PNOC.

Background: Central nervous system (CNS) tumors lead to cancer-related mortality in children. Genetic ancestry-associated cancer prevalence and outcomes have been studied, but is limited.

Methods: We performed genetic ancestry prediction in 1,452 pediatric patients with paired normal and tumor whole genome sequencing from the Open Pediatric Cancer (OpenPedCan) project to evaluate the influence of reported race and ethnicity and ancestry-based genetic superpopulations on tumor histology, molecular subtype, survival, and treatment.

Characterization of aberrant splicing in pediatric central nervous system tumors reveals as a candidate oncogenic dependency.

Pediatric brain cancer is the leading cause of disease-related mortality in children, and many aggressive tumors still lack effective treatment strategies. We characterized aberrant alternative splicing across pediatric brain tumors, identifying pediatric high-grade gliomas (HGGs) among the most heterogeneous. Annotating these events with UniProt, we identified 11,940 splice events in 5,368 genes leading to potential protein function changes.

AutoGVP: a dockerized workflow integrating ClinVar and InterVar germline sequence variant classification.

Summary: With the increasing rates of exome and whole genome sequencing, the ability to classify large sets of germline sequencing variants using up-to-date American College of Medical Genetics-Association for Molecular Pathology (ACMG-AMP) criteria is crucial. Here, we present Automated Germline Variant Pathogenicity (AutoGVP), a tool that integrates germline variant pathogenicity annotations from ClinVar and sequence variant classifications from a modified version of InterVar (PVS1 strength adjustments, removal of PP5/BP6). This tool facilitates large-scale, clinically focused classification of germline sequence variants in a research setting.

AutoGVP: a dockerized workflow integrating ClinVar and InterVar germline sequence variant classification.

With the increasing rates of exome and whole genome sequencing, the ability to classify large sets of germline sequencing variants using up-to-date American College of Medical Genetics - Association for Molecular Pathology (ACMG-AMP) criteria is crucial. Here, we present Automated Germline Variant Pathogenicity (AutoGVP), a tool that integrates germline variant pathogenicity annotations from ClinVar and sequence variant classifications from a modified version of InterVar (PVS1 strength adjustments, removal of PP5/BP6). This tool facilitates large-scale, clinically-focused classification of germline sequence variants in a research setting.

FBXW7β isoform drives transcriptional activation of the proinflammatory TNF cluster in human pro-B cells.

Noncanonical exon usage plays many important roles in cellular phenotypes, but its contribution to human B-cell development remains sketchily understood. To fill this gap, we collected various B-cell fractions from bone marrow (BM) and tonsil donors, performed RNA sequencing, and examined transcript variants. We identified 150 genes that harbor local splicing variations in all pairwise comparisons.

Targeting CD123 in blastic plasmacytoid dendritic cell neoplasm using allogeneic anti-CD123 CAR T cells.

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare hematologic malignancy with poor outcomes with conventional therapy. Nearly 100% of BPDCNs overexpress interleukin 3 receptor subunit alpha (CD123). Given that CD123 is differentially expressed on the surface of BPDCN cells, it has emerged as an attractive therapeutic target.

Modulation of CD22 Protein Expression in Childhood Leukemia by Pervasive Splicing Aberrations: Implications for CD22-Directed Immunotherapies.

Unlabelled: Downregulation of surface epitopes causes postimmunotherapy relapses in B-lymphoblastic leukemia (B-ALL). Here we demonstrate that mRNA encoding CD22 undergoes aberrant splicing in B-ALL. We describe the plasma membrane-bound CD22 Δex5-6 splice isoform, which is resistant to chimeric antigen receptor (CAR) T cells targeting the third immunoglobulin-like domain of CD22.

annoFuse: an R Package to annotate, prioritize, and interactively explore putative oncogenic RNA fusions.

Background: Gene fusion events are significant sources of somatic variation across adult and pediatric cancers and are some of the most clinically-effective therapeutic targets, yet low consensus of RNA-Seq fusion prediction algorithms makes therapeutic prioritization difficult. In addition, events such as polymerase read-throughs, mis-mapping due to gene homology, and fusions occurring in healthy normal tissue require informed filtering, making it difficult for researchers and clinicians to rapidly discern gene fusions that might be true underlying oncogenic drivers of a tumor and in some cases, appropriate targets for therapy.

Results: We developed annoFuse, an R package, and shinyFuse, a companion web application, to annotate, prioritize, and explore biologically-relevant expressed gene fusions, downstream of fusion calling.

A transcriptome-based classifier to determine molecular subtypes in medulloblastoma.

Medulloblastoma is a highly heterogeneous pediatric brain tumor with five molecular subtypes, Sonic Hedgehog TP53-mutant, Sonic Hedgehog TP53-wildtype, WNT, Group 3, and Group 4, defined by the World Health Organization. The current mechanism for classification into these molecular subtypes is through the use of immunostaining, methylation, and/or genetics. We surveyed the literature and identified a number of RNA-Seq and microarray datasets in order to develop, train, test, and validate a robust classifier to identify medulloblastoma molecular subtypes through the use of transcriptomic profiling data.

The Msi Family of RNA-Binding Proteins Function Redundantly as Intestinal Oncoproteins.

Members of the Msi family of RNA-binding proteins have recently emerged as potent oncoproteins in a range of malignancies. MSI2 is highly expressed in hematopoietic cancers, where it is required for disease maintenance. In contrast to the hematopoietic system, colorectal cancers can express both Msi family members, MSI1 and MSI2.

Age-driven modulation of tRNA-derived fragments in Drosophila and their potential targets.

Background: Development of sequencing technologies and supporting computation enable discovery of small RNA molecules that previously escaped detection or were ignored due to low count numbers. While the focus in the analysis of small RNA libraries has been primarily on microRNAs (miRNAs), recent studies have reported findings of fragments of transfer RNAs (tRFs) across a range of organisms.

Results: Here we describe Drosophila melanogaster tRFs, which appear to have a number of structural and functional features similar to those of miRNAs but are less abundant.

Visualization of nucleotide substitutions in the (micro)transcriptome.

Background: RNA-related applications of the next-generation sequencing (NGS) technologies require context-specific interpretations: e.g., sequence mismatches may indicate sites of RNA editing, or uneven read coverage often points to mature form of microRNA.

Impact of age-associated increase in 2'-O-methylation of miRNAs on aging and neurodegeneration in Drosophila.

MicroRNAs (miRNAs) are 20- to ∼24-nucleotide (nt) small RNAs that impact a variety of biological processes, from development to age-associated events. To study the role of miRNAs in aging, studies have profiled the levels of miRNAs with time. However, evidence suggests that miRNAs show heterogeneity in length and sequence in different biological contexts.

Colonic microbiome is altered in alcoholism.

Several studies indicate the importance of colonic microbiota in metabolic and inflammatory disorders and importance of diet on microbiota composition. The effects of alcohol, one of the prominent components of diet, on colonic bacterial composition is largely unknown. Mounting evidence suggests that gut-derived bacterial endotoxins are cofactors for alcohol-induced tissue injury and organ failure like alcoholic liver disease (ALD) that only occur in a subset of alcoholics.

The exoribonuclease Nibbler controls 3' end processing of microRNAs in Drosophila.

MicroRNAs (miRNAs) are endogenous noncoding small RNAs with important roles in many biological pathways; their generation and activity are under precise regulation [1-3]. Emerging evidence suggests that miRNA pathways are precisely modulated with controls at the level of transcription [4-8], processing [9-11], and stability [12, 13], with miRNA deregulation linked with diseases [14] and neurodegenerative disorders [15]. In the Drosophila miRNA biogenesis pathway, long primary miRNA transcripts undergo sequential cleavage [16-18] to release the embedded miRNAs.

Deep annotation of Drosophila melanogaster microRNAs yields insights into their processing, modification, and emergence.

Since the initial annotation of miRNAs from cloned short RNAs by the Ambros, Tuschl, and Bartel groups in 2001, more than a hundred studies have sought to identify additional miRNAs in various species. We report here a meta-analysis of short RNA data from Drosophila melanogaster, aggregating published libraries with 76 data sets that we generated for the modENCODE project. In total, we began with more than 1 billion raw reads from 187 libraries comprising diverse developmental stages, specific tissue- and cell-types, mutant conditions, and/or Argonaute immunoprecipitations.

Analysis of multitag pyrosequence data from human cervical lavage samples.

We have been using the Roche GS-FLX sequencing platform to produce tens of thousands of sequencing reads from samples of both bacterial communities (microbiome) and fungal communities (mycobiome) of stool, gut mucosa, vaginal washes, and oral washes from a large number of subjects. This vast volume of data from diverse sources has necessitated the development of an analysis pipeline in order to systematically and rapidly identify the taxa within the samples and to correlate the sample data with clinical and environmental features. Specifically, we have developed automated analytical tools for data tracking, taxonomical analysis, and feature clustering of bacteria in the human microbiome and demonstrate the pipeline using Cervical Vaginal Lavage (CVL) samples.

Network-based modeling of the human gut microbiome.

In this article, we used a network-based approach to characterize the microflora abundance in colonic mucosal samples and correlate potential interactions between the identified species with respect to the healthy and diseased states. We analyzed the modelled network by computing several local and global network statistics, identified recurring patterns or motifs, fit the network models to a family of well-studied graph models. This study has demonstrated, for the first time, an approach that differentiated the gut microbiota in alcoholic subjects and healthy subjects using topological network analysis of the gut microbiome.