Integrated Proteogenomic Characterization across Major Histological Types of Pediatric Brain Cancer.

We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.

Human CLP1 mutations alter tRNA biogenesis, affecting both peripheral and central nervous system function.

CLP1 is a RNA kinase involved in tRNA splicing. Recently, CLP1 kinase-dead mice were shown to display a neuromuscular disorder with loss of motor neurons and muscle paralysis. Human genome analyses now identified a CLP1 homozygous missense mutation (p.R140H) in five unrelated families, leading to a loss of CLP1 interaction with the tRNA splicing endonuclease (TSEN) complex, largely reduced pre-tRNA cleavage activity, and accumulation of linear tRNA introns. The affected individuals develop severe motor-sensory defects, cortical dysgenesis, and microcephaly. Mice carrying kinase-dead CLP1 also displayed microcephaly and reduced cortical brain volume due to the enhanced cell death of neuronal progenitors that is associated with reduced numbers of cortical neurons. Our data elucidate a neurological syndrome defined by CLP1 mutations that impair tRNA splicing. Reduction of a founder mutation to homozygosity illustrates the importance of rare variations in disease and supports the clan genomics hypothesis.

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. AVAILABILITY AND IMPLEMENTATION: AutoGVP is an open source dockerized workflow implemented in R and freely available on GitHub at https://github.com/diskin-lab-chop/AutoGVP.

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. We validated annoFuse using a random cohort of TCGA RNA-Seq samples (N = 160) and achieved a 96% sensitivity for retention of high-confidence fusions (N = 603). annoFuse uses FusionAnnotator annotations to filter non-oncogenic and/or artifactual fusions. Then, fusions are prioritized if previously reported in TCGA and/or fusions containing gene partners that are known oncogenes, tumor suppressor genes, COSMIC genes, and/or transcription factors. We applied annoFuse to fusion calls from pediatric brain tumor RNA-Seq samples (N = 1028) provided as part of the Open Pediatric Brain Tumor Atlas (OpenPBTA) Project to determine recurrent fusions and recurrently-fused genes within different brain tumor histologies. annoFuse annotates protein domains using the PFAM database, assesses reciprocality, and annotates gene partners for kinase domain retention. As a standard function, reportFuse enables generation of a reproducible R Markdown report to summarize filtered fusions, visualize breakpoints and protein domains by transcript, and plot recurrent fusions within cohorts. Finally, we created shinyFuse for algorithm-agnostic interactive exploration and plotting of gene fusions. CONCLUSIONS: annoFuse provides standardized filtering and annotation for gene fusion calls from STAR-Fusion and Arriba by merging, filtering, and prioritizing putative oncogenic fusions across large cancer datasets, as demonstrated here with data from the OpenPBTA project. We are expanding the package to be widely-applicable to other fusion algorithms and expect annoFuse to provide researchers a method for rapidly evaluating, prioritizing, and translating fusion findings in patient tumors.

Comparative RNA-sequencing analysis of myocardial and circulating small RNAs in human heart failure and their utility as biomarkers.

Heart failure (HF) is associated with high morbidity and mortality and its incidence is increasing worldwide. MicroRNAs (miRNAs) are potential markers and targets for diagnostic and therapeutic applications, respectively. We determined myocardial and circulating miRNA abundance and its changes in patients with stable and end-stage HF before and at different time points after mechanical unloading by a left ventricular assist device (LVAD) by small RNA sequencing. miRNA changes in failing heart tissues partially resembled that of fetal myocardium. Consistent with prototypical miRNA-target-mRNA interactions, target mRNA levels were negatively correlated with changes in abundance for highly expressed miRNAs in HF and fetal hearts. The circulating small RNA profile was dominated by miRNAs, and fragments of tRNAs and small cytoplasmic RNAs. Heart- and muscle-specific circulating miRNAs (myomirs) increased up to 140-fold in advanced HF, which coincided with a similar increase in cardiac troponin I (cTnI) protein, the established marker for heart injury. These extracellular changes nearly completely reversed 3 mo following initiation of LVAD support. In stable HF, circulating miRNAs showed less than fivefold differences compared with normal, and myomir and cTnI levels were only captured near the detection limit. These findings provide the underpinning for miRNA-based therapies and emphasize the usefulness of circulating miRNAs as biomarkers for heart injury performing similar to established diagnostic protein biomarkers.

Comprehensive profiling of circulating microRNA via small RNA sequencing of cDNA libraries reveals biomarker potential and limitations.

We profiled microRNAs (miRNAs) in cell-free serum and plasma samples from human volunteers using deep sequencing of barcoded small RNA cDNA libraries. By introducing calibrator synthetic oligonucleotides during library preparation, we were able to calculate the total as well as specific concentrations of circulating miRNA. Studying trios of samples from newborn babies and their parents we detected placental-specific miRNA in both maternal and newborn circulations and quantitated the relative contribution of placental miRNAs to the circulating pool of miRNAs. Furthermore, sequence variation in the placental miRNA profiles could be traced to the specific placenta of origin. These deep sequencing profiles, which may serve as a model for tumor or disease detection, allow us to define the repertoire of miRNA abundance in the circulation and potential uses as biomarkers.

Identification of mRNAs bound and regulated by human LIN28 proteins and molecular requirements for RNA recognition.

Human LIN28A and LIN28B are RNA-binding proteins (RBPs) conserved in animals with important roles during development and stem cell reprogramming. We used Photoactivatable-Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation (PAR-CLIP) in HEK293 cells and identified a largely overlapping set of ∼3000 mRNAs at ∼9500 sites located in the 3' UTR and CDS. In vitro and in vivo, LIN28 preferentially bound single-stranded RNA containing a uridine-rich element and one or more flanking guanosines and appeared to be able to disrupt base-pairing to access these elements when embedded in predicted secondary structure. In HEK293 cells, LIN28 protein binding mildly stabilized target mRNAs and increased protein abundance. The top targets were its own mRNAs and those of other RBPs and cell cycle regulators. Alteration of LIN28 protein levels also negatively regulated the abundance of some but not all let-7 miRNA family members, indicating sequence-specific binding of let-7 precursors to LIN28 proteins and competition with cytoplasmic miRNA biogenesis factors.

A genome-wide view of the expression and processing patterns of Thermus thermophilus HB8 CRISPR RNAs.

The CRISPR-Cas system represents an RNA-based adaptive immune response system in prokaryotes and archaea. CRISPRs (clustered regularly interspaced short palindromic repeats) consist of arrays of short repeat-sequences interspaced by nonrepetitive short spacers, some of which show sequence similarity to foreign phage genetic elements. Their cistronic transcripts are processed to produce the mature CRISPR RNAs (crRNAs), the elements that confer immunity by base-pairing with exogenous nucleic acids. We characterized the expression and processing patterns of Thermus thermophilus HB8 CRISPRs by using differential deep-sequencing, which differentiates between 5' monophosphate and 5' non-monophosphate-containing RNAs and/or between 3' hydroxyl and 3' non-hydroxyl-containing RNAs. The genome of T. thermophilus HB8 encodes 11 CRISPRs, classified into three distinct repeat-sequence types, all of which were constitutively expressed without deliberately infecting the bacteria with phage. Analysis of the differential deep sequencing data suggested that crRNAs are generated by endonucleolytic cleavage, leaving fragments with 5' hydroxyl and 3' phosphate or 2',3'-cyclic phosphate termini. The 5' ends of all crRNAs are generated by site-specific cleavage 8 nucleotides upstream of the spacer first position; however, the 3' ends are generated by two alternative, repeat-sequence-type-dependent mechanisms. These observations are consistent with the operation of multiple crRNA processing systems within a bacterial strain.

A proteogenomic surfaceome study identifies DLK1 as an immunotherapeutic target in neuroblastoma.

Cancer immunotherapies have produced remarkable results in B-cell malignancies; however, optimal cell surface targets for many solid cancers remain elusive. Here, we present an integrative proteomic, transcriptomic, and epigenomic analysis of tumor specimens along with normal tissues to identify biologically relevant cell surface proteins that can serve as immunotherapeutic targets for neuroblastoma, an often-fatal childhood cancer of the developing nervous system. We apply this approach to human-derived cell lines (N=9) and cell/patient-derived xenograft (N=12) models of neuroblastoma. Plasma membrane-enriched mass spectrometry identified 1,461 cell surface proteins in cell lines and 1,401 in xenograft models, respectively. Additional proteogenomic analyses revealed 60 high-confidence candidate immunotherapeutic targets and we prioritized Delta-like canonical notch ligand 1 (DLK1) for further study. High expression of DLK1 directly correlated with the presence of a super-enhancer spanning the DLK1 locus. Robust cell surface expression of DLK1 was validated by immunofluorescence, flow cytometry, and immunohistochemistry. Short hairpin RNA mediated silencing of DLK1 in neuroblastoma cells resulted in increased cellular differentiation. ADCT-701, a DLK1-targeting antibody-drug conjugate (ADC), showed potent and specific cytotoxicity in DLK1-expressing neuroblastoma xenograft models. Moreover, DLK1 is highly expressed in several adult cancer types, including adrenocortical carcinoma (ACC), pheochromocytoma/paraganglioma (PCPG), hepatoblastoma, and small cell lung cancer (SCLC), suggesting potential clinical benefit beyond neuroblastoma. Taken together, our study demonstrates the utility of comprehensive cancer surfaceome characterization and credentials DLK1 as an immunotherapeutic target. Highlights: Plasma membrane enriched proteomics defines surfaceome of neuroblastomaMulti-omic data integration prioritizes DLK1 as a candidate immunotherapeutic target in neuroblastoma and other cancersDLK1 expression is driven by a super-enhancer DLK1 silencing in neuroblastoma cells results in cellular differentiation ADCT-701, a DLK1-targeting antibody-drug conjugate, shows potent and specific cytotoxicity in DLK1-expressing neuroblastoma preclinical models.

RNA-ligase-dependent biases in miRNA representation in deep-sequenced small RNA cDNA libraries.

Sequencing of small RNA cDNA libraries is an important tool for the discovery of new RNAs and the analysis of their mutational status as well as expression changes across samples. It requires multiple enzyme-catalyzed steps, including sequential oligonucleotide adapter ligations to the 3' and 5' ends of the small RNAs, reverse transcription (RT), and PCR. We assessed biases in representation of miRNAs relative to their input concentration, using a pool of 770 synthetic miRNAs and 45 calibrator oligoribonucleotides, and tested the influence of Rnl1 and two variants of Rnl2, Rnl2(1-249) and Rnl2(1-249)K227Q, for 3'-adapter ligation. The use of the Rnl2 variants for adapter ligations yielded substantially fewer side products compared with Rnl1; however, the benefits of using Rnl2 remained largely obscured by additional biases in the 5'-adapter ligation step; RT and PCR steps did not have a significant impact on read frequencies. Intramolecular secondary structures of miRNA and/or miRNA/3'-adapter products contributed to these biases, which were highly reproducible under defined experimental conditions. We used the synthetic miRNA cocktail to derive correction factors for approximation of the absolute levels of individual miRNAs in biological samples. Finally, we evaluated the influence of 5'-terminal 5-nt barcode extensions for a set of 20 barcoded 3' adapters and observed similar biases in miRNA read distribution, thereby enabling cost-saving multiplex analysis for large-scale miRNA profiling.

Bioinformatic analysis of barcoded cDNA libraries for small RNA profiling by next-generation sequencing.

The characterization of post-transcriptional gene regulation by small regulatory RNAs of 20-30 nt length, particularly miRNAs and piRNAs, has become a major focus of research in recent years. A prerequisite for the characterization of small RNAs is their identification and quantification across different developmental stages, normal and diseased tissues, as well as model cell lines. Here we present a step-by-step protocol for the bioinformatic analysis of barcoded cDNA libraries for small RNA profiling generated by Illumina sequencing, thereby facilitating miRNA and other small RNA profiling of large sample collections.

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.

The children's brain tumor network (CBTN) - Accelerating research in pediatric central nervous system tumors through collaboration and open science.

Pediatric brain tumors are the leading cause of cancer-related death in children in the United States and contribute a disproportionate number of potential years of life lost compared to adult cancers. Moreover, survivors frequently suffer long-term side effects, including secondary cancers. The Children's Brain Tumor Network (CBTN) is a multi-institutional international clinical research consortium created to advance therapeutic development through the collection and rapid distribution of biospecimens and data via open-science research platforms for real-time access and use by the global research community. The CBTN's 32 member institutions utilize a shared regulatory governance architecture at the Children's Hospital of Philadelphia to accelerate and maximize the use of biospecimens and data. As of August 2022, CBTN has enrolled over 4700 subjects, over 1500 parents, and collected over 65,000 biospecimen aliquots for research. Additionally, over 80 preclinical models have been developed from collected tumors. Multi-omic data for over 1000 tumors and germline material are currently available with data generation for > 5000 samples underway. To our knowledge, CBTN provides the largest open-access pediatric brain tumor multi-omic dataset annotated with longitudinal clinical and outcome data, imaging, associated biospecimens, child-parent genomic pedigrees, and in vivo and in vitro preclinical models. Empowered by NIH-supported platforms such as the Kids First Data Resource and the Childhood Cancer Data Initiative, the CBTN continues to expand the resources needed for scientists to accelerate translational impact for improved outcomes and quality of life for children with brain and spinal cord tumors.

Genome-wide annotation and analysis of zebra finch microRNA repertoire reveal sex-biased expression.

BACKGROUND: MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression post-transcriptionally in a wide range of biological processes. The zebra finch (Taeniopygia guttata), an oscine songbird with characteristic learned vocal behavior, provides biologists a unique model system for studying vocal behavior, sexually dimorphic brain development and functions, and comparative genomics. RESULTS: We deep sequenced small RNA libraries made from the brain, heart, liver, and muscle tissues of adult male and female zebra finches. By mapping the sequence reads to the zebra finch genome and to known miRNAs in miRBase, we annotated a total of 193 miRNAs. Among them, 29 (15%) are avian specific, including three novel zebra finch specific miRNAs. Many of the miRNAs exhibit sequence heterogeneity including length variations, untemplated terminal nucleotide additions, and internal substitution events occurring at the uridine nucleotide within a GGU motif. We also identified seven Z chromosome-encoded miRNAs. Among them, miR-2954, an avian specific miRNA, is expressed at significantly higher levels in males than in females in all tissues examined. Target prediction analysis reveals that miR-2954, but not other Z-linked miRNAs, preferentially targets Z chromosome-encoded genes, including several genes known to be expressed in a sexually dimorphic manner in the zebra finch brain. CONCLUSIONS: Our genome-wide systematic analysis of mature sequences, genomic locations, evolutionary sequence conservation, and tissue expression profiles of the zebra finch miRNA repertoire provides a valuable resource to the research community. Our analysis also reveals a miRNA-mediated mechanism that potentially regulates sex-biased gene expression in avian species.

Modulation of single-cell IgG secretion frequency and rates in human memory B cells by CpG DNA, CD40L, IL-21, and cell division.

During the recall response by CD27(+) IgG class-switched human memory B cells, total IgG secreted is a function of the following: 1) the number of IgG-secreting cells (IgG-SC), and 2) the secretion rate of each cell. In this study, we report the quantitative ELISPOT method for simultaneous estimation of single-cell IgG secretion rates and secreting cell frequencies in human B cell populations. We found that CD27(+) IgM(-) memory B cells activated with CpG and cytokines had considerable heterogeneity in the IgG secretion rates, with two major secretion rate subpopulations. BCR cross-linking reduced the frequency of cells with high per-cell IgG secretion rates, with a parallel decrease in CD27(high) B cell blasts. Increased cell death may account for the BCR-stimulated reduction in high-rate IgG-SC CD27(high) B cell blasts. In contrast, the addition of IL-21 to CD40L plus IL-4-activated human memory B cells induced a high-rate IgG-SC population in B cells with otherwise low per-cell IgG secretion rates. The profiles of human B cell IgG secretion rates followed the same biphasic distribution and range irrespective of division class. This, along with the presence of non-IgG-producing, dividing B cells in CpG plus cytokine-activated B memory B cell populations, is suggestive of an on/off switch regulating IgG secretion. Finally, these data support a mixture model of IgG secretion in which IgG secreted over time is modulated by the frequency of IgG-SC and the distribution of their IgG secretion rates.

Detection of circulating extracellular mRNAs by modified small-RNA-sequencing analysis.

Extracellular mRNAs (ex-mRNAs) potentially supersede extracellular miRNAs (ex-miRNAs) and other RNA classes as biomarkers. We performed conventional small-RNA-sequencing (sRNA-seq) and sRNA-seq with T4 polynucleotide kinase (PNK) end-treatment of total exRNA isolated from serum and platelet-poor EDTA, ACD, and heparin plasma to study the effect on ex-mRNA capture. Compared to conventional sRNA-seq PNK-treatment increased the detection of informative ex-mRNAs reads up to 50-fold. The exRNA pool was dominated by hematopoietic cells and platelets, with additional contribution from the liver. About 60% of the 15- to 42-nt reads originated from the coding sequences, in a pattern reminiscent of ribosome-profiling. Blood sample type had a considerable influence on the exRNA profile. On average approximately 350 to 1,100 distinct ex-mRNA transcripts were detected depending on plasma type. In serum, additional transcripts from neutrophils and hematopoietic cells increased this number to near 2,300. EDTA and ACD plasma showed a destabilizing effect on ex mRNA and non-coding RNA ribonucleoprotein complexes compared to other plasma types. In a proof-of-concept study, we investigated differences between the exRNA profiles of patients with acute coronary syndrome (ACS) and healthy controls. The improved tissue resolution of ex mRNAs after PNK-treatment enabled us to detect a neutrophil-signature in ACS that escaped detection by ex miRNA analysis.

Human Organoids Share Structural and Genetic Features with Primary Pancreatic Adenocarcinoma Tumors.

Patient-derived pancreatic ductal adenocarcinoma (PDAC) organoid systems show great promise for understanding the biological underpinnings of disease and advancing therapeutic precision medicine. Despite the increased use of organoids, the fidelity of molecular features, genetic heterogeneity, and drug response to the tumor of origin remain important unanswered questions limiting their utility. To address this gap in knowledge, primary tumor- and patient-derived xenograft (PDX)-derived organoids, and 2D cultures for in-depth genomic and histopathologic comparisons with the primary tumor were created. Histopathologic features and PDAC representative protein markers (e.g., claudin 4 and CA19-9) showed strong concordance. DNA- and RNA-sequencing (RNAseq) of single organoids revealed patient-specific genomic and transcriptomic consistency. Single-cell RNAseq demonstrated that organoids are primarily a clonal population. In drug response assays, organoids displayed patient-specific sensitivities. In addition, the in vivo PDX response to FOLFIRINOX and gemcitabine/abraxane treatments were examined, which was recapitulated in vitro with organoids. This study has demonstrated that organoids are potentially invaluable for precision medicine as well as preclinical drug treatment studies because they maintain distinct patient phenotypes and respond differently to drug combinations and dosage. IMPLICATIONS: The patient-specific molecular and histopathologic fidelity of organoids indicate that they can be used to understand the etiology of the patient's tumor and the differential response to therapies and suggests utility for predicting drug responses.

Author Correction: Integrated molecular subtyping defines a curable oligometastatic state in colorectal liver metastasis.

In the originally published version of this Article, the affiliation details for Kevin P. White inadvertently omitted 'Tempus Labs, Chicago, IL, 60654, USA'. This has now been corrected in both the PDF and HTML versions of the Article.

Integrated molecular subtyping defines a curable oligometastatic state in colorectal liver metastasis.

The oligometastasis hypothesis suggests a spectrum of metastatic virulence where some metastases are limited in extent and curable with focal therapies. A subset of patients with metastatic colorectal cancer achieves prolonged survival after resection of liver metastases consistent with oligometastasis. Here we define three robust subtypes of de novo colorectal liver metastasis through integrative molecular analysis. Patients with metastases exhibiting MSI-independent immune activation experience the most favorable survival. Subtypes with adverse outcomes demonstrate VEGFA amplification in concert with (i) stromal, mesenchymal, and angiogenic signatures, or (ii) exclusive NOTCH1 and PIK3C2B mutations with E2F/MYC activation. Molecular subtypes complement clinical risk stratification to distinguish low-risk, intermediate-risk, and high-risk patients with 10-year overall survivals of 94%, 45%, and 19%, respectively. Our findings provide a framework for integrated classification and treatment of metastasis and support the biological basis of curable oligometastatic colorectal cancer. These concepts may be applicable to many patients with metastatic cancer.

Characterizing Expression and Processing of Precursor and Mature Human tRNAs by Hydro-tRNAseq and PAR-CLIP.

The participation of tRNAs in fundamental aspects of biology and disease necessitates an accurate, experimentally confirmed annotation of tRNA genes and curation of tRNA sequences. This has been challenging because RNA secondary structure, nucleotide modifications, and tRNA gene multiplicity complicate sequencing and mapping efforts. To address these issues, we developed hydro-tRNAseq, a method based on partial alkaline RNA hydrolysis that generates fragments amenable for sequencing. To identify transcribed tRNA genes, we further complemented this approach with photoactivatable crosslinking and immunoprecipitation (PAR-CLIP) of SSB/La, a conserved protein involved in pre-tRNA processing. Our results show that approximately half of all predicted tRNA genes are transcribed in human cells. We also report nucleotide modification sites and their order of introduction, and we identify tRNA leaders, trailers, and introns. By using complementary sequencing-based methodologies, we present a human tRNA atlas and determine expression levels of mature and processing intermediates of tRNAs in human cells.