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Chitinase-3-like protein 1 (CHI3L1/YKL-40) has long been known as a biomarker for early detection of neuroinflammation and disease diagnosis of Alzheimer’s disease (AD). In the brain, CHI3L1 is primarily provided by astrocytes and heralds the reactive, neurotoxic state triggered by inflammation and other stress signals. However, how CHI3L1 acts in neuroinflammation or how it contributes to AD and relevant neurodegenerative conditions remains unknown. In peripheral tissues, our group and others have uncovered that CHI3L1 is a master regulator for a wide range of injury and repair events, including the innate immunity pathway that resembles the neuroinflammation process governed by microglia and astrocytes. Based on assessment of current knowledge regarding CHI3L1 biology, we hypothesize that CHI3L1 functions as a signaling molecule mediating distinct neuroinflammatory responses in brain cells and dysfunctions to precipitate the neurodegeneration. We also recommend future research directions to validate such assertions for better understanding of disease mechanism.

Pediatric high-grade gliomas (pHGGs), encompassing hemispheric and diffuse midline gliomas (DMGs), remain a devastating disease. The last decade has revealed oncogenic drivers including single nucleotide variants (SNVs) in histones. However, the contribution of structural variants (SVs) to gliomagenesis has not been systematically explored due to limitations in early SV analysis approaches. Using SV algorithms, we recently created, we analyzed SVs in whole-genome sequences of 179 pHGGs including a novel cohort of treatment naïve samples–the largest WGS cohort assembled in adult or pediatric glioma. The most recurrent SVs targeted MYC isoforms and receptor tyrosine kinases, including a novel SV amplifying a MYC enhancer in the lncRNA CCDC26 in 12% of DMGs and revealing a more central role for MYC in these cancers than previously known. Applying de novo SV signature discovery, we identified five signatures including three (SVsig1-3) involving primarily simple SVs, and two (SVsig4-5) involving complex, clustered SVs. These SV signatures associated with genetic variants that differed from what was observed for SV signatures in other cancers, suggesting different links to underlying biology. Tumors with simple SV signatures were TP53 wild-type but were enriched with alterations in TP53 pathway members PPM1D and MDM4. Complex signatures were associated with direct aberrations in TP53, CDKN2A, and RB1 early in tumor evolution, and with extrachromosomal amplicons that likely occurred later. All pHGGs exhibited at least one simple SV signature but complex SV signatures were primarily restricted to subsets of H3.3K27M DMGs and hemispheric pHGGs. Importantly, DMGs with the complex SV signatures SVsig4-5 were associated with shorter overall survival independent of histone type and TP53 status. These data inform the role and impact of SVs in gliomagenesis and mechanisms that shape them.

Pediatric high-grade gliomas (pHGGs), encompassing hemispheric and diffuse midline gliomas (DMGs), remain a devastating disease. The last decade has revealed oncogenic drivers including single nucleotide variants (SNVs) in histones. However, the contribution of structural variants (SVs) to gliomagenesis has not been systematically explored due to limitations in early SV analysis approaches. Using SV algorithms, we recently created, we analyzed SVs in whole-genome sequences of 179 pHGGs including a novel cohort of treatment naïve samples–the largest WGS cohort assembled in adult or pediatric glioma. The most recurrent SVs targeted MYC isoforms and receptor tyrosine kinases, including a novel SV amplifying a MYC enhancer in the lncRNA CCDC26 in 12% of DMGs and revealing a more central role for MYC in these cancers than previously known. Applying de novo SV signature discovery, we identified five signatures including three (SVsig1-3) involving primarily simple SVs, and two (SVsig4-5) involving complex, clustered SVs. These SV signatures associated with genetic variants that differed from what was observed for SV signatures in other cancers, suggesting different links to underlying biology. Tumors with simple SV signatures were TP53 wild-type but were enriched with alterations in TP53 pathway members PPM1D and MDM4. Complex signatures were associated with direct aberrations in TP53, CDKN2A, and RB1 early in tumor evolution, and with extrachromosomal amplicons that likely occurred later. All pHGGs exhibited at least one simple SV signature but complex SV signatures were primarily restricted to subsets of H3.3K27M DMGs and hemispheric pHGGs. Importantly, DMGs with the complex SV signatures SVsig4-5 were associated with shorter overall survival independent of histone type and TP53 status. These data inform the role and impact of SVs in gliomagenesis and mechanisms that shape them.

Background Many biological processes, such as cancer metastasis, organismal development, and acquisition of resistance to cytotoxic therapy, rely on the emergence of rare sub-clones from a larger population. Understanding how the genetic and epigenetic features of diverse clones affect clonal fitness provides insight into molecular mechanisms underlying selective processes. While large-scale barcoding with NGS readout has facilitated cellular fitness assessment at the population level, this approach does not support characterization of clones prior to selection. Single-cell genomics methods provide high biological resolution, but are challenging to scale across large populations to probe rare clones and are destructive, limiting further functional analysis of important clones. Results Here, we develop CloneSifter, a methodology for tracking and enriching rare clones throughout their response to selection. CloneSifter utilizes a CRISPR sgRNA-barcode library that facilitates the isolation of viable cells from specific clones within the barcoded population using a sequence-specific retrieval reporter. We demonstrate that CloneSifter can measure clonal fitness of cancer cell models in vitro and retrieve targeted clones at abundance as low as 1 in 1883 in a heterogeneous cell population. Conclusions CloneSifter provides a means to track and access specific and rare clones of interest across dynamic changes in population structure to comprehensively explore the basis of these changes.

In Alzheimer's disease (AD) and other neurodegenerative disorders, oligodendroglial failure is a common early pathological feature, but how it contributes to disease development and progression, particularly in the gray matter of the brain, remains largely unknown. The dysfunction of oligodendrocyte lineage cells is hallmarked by deficiencies in myelination and impaired self-renewal of oligodendrocyte precursor cells (OPCs). These two defects are caused at least in part by the disruption of interactions between neuron and oligodendrocytes along the buildup of pathology. OPCs give rise to myelinating oligodendrocytes during CNS development. In the mature brain cortex, OPCs are the major proliferative cells (comprising ~5% of total brain cells) and control new myelin formation in a neural activity-dependent manner. Such neuron-to-oligodendrocyte communications are significantly understudied, especially in the context of neurodegenerative conditions such as AD, due to the lack of appropriate tools. In recent years, our group and others have made significant progress to improve currently available protocols to generate functional neurons and oligodendrocytes individually from human pluripotent stem cells. In this manuscript, we describe our optimized procedures, including the establishment of a co-culture system to model the neuron-oligodendrocyte connections. Our illustrative results suggest an unexpected contribution from OPCs/oligodendrocytes to the brain amyloidosis and synapse integrity and highlight the utility of this methodology for AD research. This reductionist approach is a powerful tool to dissect the specific hetero-cellular interactions out of the inherent complexity inside the brain. The protocols we describe here are expected to facilitate future studies on oligodendroglial defects in the pathogenesis of neurodegeneration.

The extent of genetic and epigenetic diversity between and within patient tumors is being mapped in ever more detail. It is clear that cancer is an evolutionary process in which tumor cell intrinsic and extrinsic forces shape clonal selection. The pre-clinical oncology pipeline uses model systems of human cancer - including mouse models, cell lines, patient-derived organoids and patient-derived xenografts - to study tumor biology and assess the efficacy of putative therapeutic agents. Model systems cannot completely replicate the environment of human tumors and, even within the same cancer model, data are often irreproducible between laboratories. One hypothesis is that ongoing evolutionary processes remain relevant in laboratory models, leading to divergence over time. In a recent edition of Nature, Ben-David and colleagues showed that different stocks of widely used cancer cell lines - a staple of cancer research over many decades - are highly heterogeneous in terms of their genetics, transcriptomics and responses to therapies. The authors find compelling evidence of positive selection based on ongoing mutational processes and chromosomal instability. Thus, the origin, culture conditions and cumulative number of population doublings of cell lines likely influence experimental outcomes. Here, we summarize the key findings of this important study and discuss the practical implications of this work for researchers using cell lines in the laboratory.

Structural variants (SVs), including small insertion and deletion variants (indels), are challenging to detect through standard alignment-based variant calling methods. Sequence assembly offers a powerful approach to identifying SVs, but is difficult to apply at scale genome-wide for SV detection due to its computational complexity and the difficulty of extracting SVs from assembly contigs. We describe SvABA, an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements. We evaluated SvABA's performance on the NA12878 human genome and in simulated and real cancer genomes. SvABA demonstrates superior sensitivity and specificity across a large spectrum of SVs and substantially improves detection performance for variants in the 20–300 bp range, compared with existing methods. SvABA also identifies complex somatic rearrangements with chains of short (

BackgroundMany biological processes, such as cancer metastasis, organismal development, and development of resistance to cytotoxic therapy, rely on the emergence of rare sub-clones from a larger population. Understanding how the genetic and epigenetic features of diverse clones affect clonal fitness provides insight into molecular mechanisms underlying selective processes. However, identifying causal drivers of clonal fitness remains challenging. Population-level analysis has limited resolution to characterize clones prior to selection, while high-resolution single-cell methods are destructive and challenging to scale across large populations, limiting further functional analysis of relevant clones.ResultsHere, we develop CloneRetriever, a methodology for tracking and retrieving rare clones throughout their response to selection. CloneRetriever utilizes a CRISPR sgRNA-barcode library that allows isolation of viable cells from specific clones within the barcoded population using a sequence-specific retrieval reporter. We demonstrated that CloneRetriever can measure clonal fitness of cancer cell modelsin vitroand retrieve targeted clones at abundance as low as 1 in 1,883 in a heterogeneous cell population.ConclusionsCloneRetriever provides a means to track and access specific and rare clones of interest across dynamic changes in population structure to comprehensively explore the basis of these changes.

BACKGROUND: BET-bromodomain proteins bind to H3K27ac enhancers and recruit transcriptional proteins to facilitate the expression of genes. Inhibition of BET-bromodomain proteins shows preclinical promise for MYC-driven tumors such as medulloblastoma (MB), however the mechanism of action and means of resistance are not well described. We hypothesized that genes required for MB cell growth and were sufficient to rescue the effects of BET-bromodomain inhibition (BETi) would signify key downstream effectors of this class of inhibitors. METHODS: We applied an integrative genomics approach: expression profiling of genes suppressed following BETi with JQ1, genome-scale CRISPR/Cas9 screens to determine which of the suppressed genes are also essential for cell viability, and a near-genome scale open reading frame (ORF) rescue screen to determine which of the suppressed genes are also sufficient to drive resistance to BETi. Genes that were nominated by all three data sets were considered BETi transcriptional targets responsible for BET-induced reduced cell viability. RESULTS: BETi in MYC-driven MB cell lines generated widespread changes in gene expression. Genes suppressed by BETi had the tendency to be essential to cell survival. The most frequently included pathways were cell-cycle, DNA replication, and RNA processing/transcription. In each cell line, we identified ORF constructs that significantly rescued cells from BETi which included BCL2 family proteins, which also represented genetic dependencies in treatment naïve cell. Overexpression of BCL2 family member BCL2L1 attenuated both apoptosis and JQ1 mediated cell cycle arrest and expression of the pro-apoptotic genes BAX and BAK were required for BETi response. BCL2 family genes were also validated in drug-tolerant cell lines as having been suppressed by BETi and re-expressed in drug-tolerant cells thus demonstrating their relevance in resistance. CONCLUSION: Integrative genomic analysis identifies BCL2 family members as key mediators of response of MB cells to BET-bromodomain inhibition and also mediate resistance to BETi.

BET-bromodomain inhibition (BETi) has shown pre-clinical promise for MYC-amplified medulloblastoma. However, the mechanisms for its action, and ultimately of resistance, have not been fully defined. Using a combination of expression profiling, genome-scale CRISPR/Cas9-mediated loss of function and ORF/cDNA-driven rescue screens, and cell-based models of spontaneous resistance, we identified bHLH/homeobox transcription factors including NEUROD1, NEUROG1 and NEUROG3, and cell-cycle regulators CCND2 and CCND3 as key gene mediators of BETi’s response. Furthermore, these genes also mediated resistance, and were re-expressed in cells that acquire resistance to BETi through chronic dosing. Cells that acquired drug tolerance exhibit altered cell state, with an increase in neuronally differentiated cell-state and expression of lineage-specific bHLH/homeobox transcription factors. However, they did not terminally differentiate, maintaining the expression of SOX2 and the capacity to cycle through S-phase, re-instating expression of CCND2. Analysis of human medulloblastomas revealed heterogeneous populations of cell states, including those that expressed both neuronal and stem markers, and would be predicted to be less sensitive to BETi. Barcoding techniques to track evolution of cells through treatment indicated the existence of cells that are predetermined to acquire resistance to BETi. Finally, we found inhibition of cell-cycling with CDK4/CKD6 inhibition to delay acquisition of resistance, providing a rationale for combination treatments. These findings provide insights into the mechanisms of action of BETi as a therapeutic strategy for MYC-driven medulloblastoma that can be leveraged to increase efficacy in the clinical setting.

BACKGROUND Driver single nucleotide variants (SNV) and somatic copy number aberrations (SCNA) of pediatric high-grade glioma (pHGGs), including Diffuse Midline Gliomas (DMGs) are characterized. However, structural variants (SVs) in pHGGs and the mechanisms through which they contribute to glioma formation have not been systematically analyzed genome-wide. METHODS Using SvABA for SVs as well as the latest pipelines for SCNAs and SNVs we analyzed whole-genome sequencing from 174 patients. This includes 60 previously unpublished samples, 43 of which are DMGs. Signature analysis allowed us to define pHGG groups with shared SV characteristics. Significantly recurring SV breakpoints and juxtapositions were identified with algorithms we recently developed and the findings were correlated with RNAseq and H3K27ac ChIPseq. RESULTS The SV characteristics in pHGG showed three groups defined by either complex, intermediate or simple signature activities. These associated with distinct combinations of known driver oncogenes. Our statistical analysis revealed recurring SVs in the topologically associating domains of MYCN, MYC, EGFR, PDGFRA & MET. These correlated with increased mRNA expression and amplification of H3K27ac peaks. Complex recurring amplifications showed characteristics of extrachromosomal amplicons and were enriched in coding SVs splitting protein regulatory from effector domains. Integrative analysis of all SCNAs, SNVs & SVs revealed patterns of characteristic combinations between potential drivers and signatures. This included two distinct groups of H3K27M DMGs with either complex or simple signatures and different combinations of associated variants. CONCLUSION Recurrent SVs associate with signatures shaped by an underlying process, which can lead to distinct mechanisms to activate the same oncogene.

INTRODUCTION: Children with MYC-amplified medulloblastoma face a dismal prognosis. We have previously found BET-bromodomain inhibition to have preclinical promise as a therapeutic strategy for MYC-amplified medulloblastoma. However, the mechanisms of action of these inhibitors have not been fully elucidated. In addition, the development of resistance is likely to impact their clinical efficacy. To address this, we characterized cancer cell evolution in response to BET-bromodomain inhibition in MYC-amplified medulloblastoma models. METHODS: We applied genome wide over-expression (ORF) and CRISPR-cas9 screens to identify pathways which, when altered, rescue cells from the phenotypic effects of BET-bromodomain inhibition in MYC-amplified medulloblastoma cell lines. Candidate genes were validated as resistance drivers in medulloblastoma cell lines chronically passaged with BET-bromodomain inhibitors until the acquisition of resistance. These lines were also subjected to whole-exome sequencing to uncover genomic alterations that confer resistance. RESULTS: Altered expression of the anti-apoptosis pathway, cell cycle activation and PI3-kinase signaling, in addition to several lineage-specific transcription factors, rescued MYC-amplified cells from BET-bromodomain inhibition. Cell-lines that had acquired resistance to BET-bromodomain inhibitors exhibited altered cell-state and increased expression of candidate resistance proteins. These lines were resistant to structurally distinct BET-bromodomain inhibitors, and whole-exome sequencing did not reveal mutations in BRD2, BRD3 or BRD4. Resistant cell-lines were sensitive to inhibitors targeting candidate resistance drivers. CONCLUSIONS: MYC-amplified medulloblastoma cell-lines evolve to increase expression of candidate resistant pathways to acquire resistance to BET-bromodomain inhibition. These represent potential therapeutic targets for combination therapies to increase the clinical efficacy of BET-bromodomain inhibitors for children with MYC-amplified medulloblastoma.

INTRODUCTION: Diffuse intrinsic pontine glioma (DIPG) remains a devastating and incurable disease. The DIPG-BATs clinical trial incorporates diagnostic biopsy with molecularly determined treatment stratification. Here we present the initial genomic analysis of the DIPG-BATs cohort. METHODS: Children enrolled on the DIPG-BATs clinical trial underwent upfront diagnostic biopsies prior to commencement of therapy. RNA and DNA were extracted from single core biopsies and subjected to whole-genome sequencing (WGS) and RNA-sequencing. Tumor samples were also collected at autopsy if there was parental consent. RESULTS: Fifty-three patients were enrolled on study, of whom 50 underwent biopsy. There were no biopsy-related deaths. A mean of 5ug of RNA and 10ug of DNA were extracted from single frozen cores. WGS on 41 DIPG samples (including eight autopsy samples) revealed a mean mutation rate of 0.753 mutations per Mb. We confirmed TP53, PIK3CA, H3F3A, ACVR1, PPM1D, and HIST1H3B to be recurrently mutated in DIPG. Additional mutations were found in epigenetic modifiers including ASXL1. Copy-number analysis revealed PDGFRA to meet statistical significance as a recurrent amplification peak in DIPG (q

Structural variants (SVs), including small insertion and deletion variants (indels), are challenging to detect through standard alignment-based variant calling methods. Sequence assembly offers a powerful approach to identifying SVs, but is difficult to apply at-scale genome-wide for SV detection due to its computational complexity and the difficulty of extracting SVs from assembly contigs. We describe SvABA, an efficient and accurate method for detecting SVs from short-read sequencing data using genome-wide local assembly with low memory and computing requirements. We evaluated SvABA’s performance on the NA12878 human genome and in simulated and real cancer genomes. SvABA demonstrates superior sensitivity and specificity across a large spectrum of SVs, and substantially improved detection performance for variants in the 20-300 bp range, compared with existing methods. SvABA also identifies complex somatic rearrangements with chains of short (< 1,000 bp) templated-sequence insertions copied from distant genomic regions. We applied SvABA to 344 cancer genomes from 11 cancer types, and found that templated-sequence insertions occur in ~4% of all somatic rearrangements. Finally, we demonstrate that SvABA can identify sites of viral integration and cancer driver alterations containing medium-sized SVs.

Background Clinical genomics platforms are needed to identify targetable alterations, but implementation of these technologies and best practices in routine clinical pediatric oncology practice are not yet well established. Methods Profile is an institution-wide prospective clinical research initiative that uses targeted sequencing to identify targetable alterations in tumors. OncoPanel, a multiplexed targeted exome-sequencing platform that includes 300 cancer-causing genes, was used to assess single nucleotide variants and rearrangements/indels. Alterations were annotated (Tiers 1-4) based on clinical significance, with Tier 1 alterations having well-established clinical utility. OncoCopy, a clinical genome-wide array comparative genomic hybridization (aCGH) assay, was also performed to evaluate copy number alterations and better define rearrangement breakpoints. Results Cancer genomes of 203 pediatric brain tumors were profiled across histological subtypes, including 117 samples analyzed by OncoPanel, 146 by OncoCopy, and 60 tumors subjected to both methodologies. OncoPanel revealed clinically relevant alterations in 56% of patients (44 cancer mutations and 20 rearrangements), including BRAF alterations that directed the use of targeted inhibitors. Rearrangements in MYB-QKI, MYBL1, BRAF, and FGFR1 were also detected. Furthermore, while copy number profiles differed across histologies, the combined use of OncoPanel and OncoCopy identified subgroup-specific alterations in 89% (17/19) of medulloblastomas. Conclusion The combination of OncoPanel and OncoCopy multiplex genomic assays can identify critical diagnostic, prognostic, and treatment-relevant alterations and represents an effective precision medicine approach for clinical evaluation of pediatric brain tumors.

Angiocentric gliomas are pediatric low-grade gliomas (PLGGs) without known recurrent genetic drivers. We performed genomic analysis of new and published data from 249 PLGGs, including 19 angiocentric gliomas. We identified MYB-QKI fusions as a specific and single candidate driver event in angiocentric gliomas. In vitro and in vivo functional studies show that MYB-QKI rearrangements promote tumorigenesis through three mechanisms: MYB activation by truncation, enhancer translocation driving aberrant MYB-QKI expression and hemizygous loss of the tumor suppressor QKI. To our knowledge, this represents the first example of a single driver rearrangement simultaneously transforming cells via three genetic and epigenetic mechanisms in a tumor.

INTRODUCTION: Clinical genomics platforms identify targetable alterations for precision medicine in pediatric neuro-oncology, allowing both the genomic profiling of tumors to inform clinical care and facilitating the potential discovery of novel driver alterations. METHODS: We applied two clinical genomic platforms (OncoPanel and OncoCopy) to profile pediatric brain tumors in a clinical setting. OncoPanel, a multiplexed targeted exome-sequencing platform that includes 300 cancer causing genes, was used to assess single nucleotide variants and rearrangements/indels. OncoCopy, a high-resolution genome-wide array comparative genomic hybridization (aCGH) assay, was used to evaluate copy number alterations and refine rearrangement breakpoints. RESULTS: Cancer genomes of 203 pediatric brain tumors were profiled across histological subtypes including 117 analyzed by OncoPanel, 146 by OncoCopy, and 60 evaluated using both methodologies. OncoPanel revealed clinically relevant alterations in 56% of patients (44 cancer mutations and 20 rearrangements), including BRAF alterations that directed the use of targeted inhibitors. EWSRa rearrangements were observed unexpectedly in two patients; one with a Atypical Teratoid Rhabdoid Tumor with loss of INI-1 (SMARCB1), and the second in an ependymoma. Whole Genome Sequencing of the rhabdoid tumor confirmed a rearrangement involving EWSR1 and PLAGL1.CONCLUSIONS: The combined deployment of OncoPanel and OncoCopy multiplex genomic assays can identify clinically relevant genomic alterations in pediatric brain tumors and facilitate the discovery of novel driver alterations. *equal contribution