Biology subjects

Resnick, A. C.

Publications and source records attributed to Resnick, A. C..

12 recordsLinked to original sources

bioRxiv2025

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

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 exons. Several of these skipped microexons mapped to L1-IgCAM family members, such as NRCAM. Bulk and single-nuclei short- and long-read RNA-seq revealed uniform skipping of NRCAM microexons 5 and 19 in virtually every pHGG sample. Importantly, the {Delta}ex5{Delta}ex19 (but not the full-length) NRCAM proteoform was essential for pHGG cell migration and invasion in vitro and tumor growth in vivo. We developed a monoclonal antibody selective for {Delta}ex5{Delta}ex19 NRCAM and demonstrated that "painting" of pHGG cells with this antibody enables killing by T cells armed with an FcRI-based universal immune receptor. Thus, pHGG-specific NRCAM and possibly other L1-IgCAM proteoforms are promising and highly selective targets for adoptive immunotherapies.

cancer biology↗

bioRxiv2024

The splicing modulator CLK1 is a candidate oncogenic dependency in pediatric high-grade gliomas

BackgroundPediatric brain tumors are the leading cause of disease-related mortality in children, yet many aggressive tumors lack effective therapies. RNA splicing is a hallmark of cancer, but it has not yet been systematically studied in pediatric brain tumors. MethodsWe analyzed 729 pediatric brain tumors spanning histologies and molecular subtypes to quantify differential tumor splicing. We developed the Splicing Burden Index (SBI) to enable cross-sample comparisons and performed hierarchical clustering of highly variable splice events to define splicing-informed tumor groups. These were integrated with clinical outcomes, pathway activity, and proteogenomic data. Recurrent splice events were prioritized for predicted functional impact, and in vitro perturbation studies were performed targeting the splicing kinase CDC-like kinase 1 (CLK1). ResultsSBI revealed substantial inter- and intra-histology heterogeneity. Clusters were enriched for histologies and molecular subtypes, several of which were independently associated with survival beyond histology and clinical covariates. Spliceosome pathway activity varied across clusters and was associated with worse survival, yet was not correlated with SBI, indicating distinct dimensions of splicing dysregulation. Functional prioritization identified a recurrent in CLK1 exon 4, required for canonical kinase activity. CLK1 exon 4 inclusion followed an oncofetal pattern and showed context-dependent associations with outcome distinct from total CLK1 expression. Pharmacologic inhibition and exon 4-specific perturbation of CLK1 reduced tumor cell viability and disrupted cancer-relevant splicing and transcriptional programs. ConclusionsThis study systematically characterizes splicing in pediatric brain tumors, identifies splicing-informed subgroups, and prioritizes CLK1 exon 4 as an oncofetal tumor-specific event, motivating further preclinical exploration. Key Points[bullet] Splicing analysis of 729 pediatric CNS tumors identifies splicing-defined clusters. [bullet]CLK1 exon 4 inclusion is widespread and developmentally regulated. [bullet]Exon-level CLK1 regulation shows context-dependent links to prognosis in aggressive CNS tumors.

genomics↗

bioRxiv2024

The Open Pediatric Cancer Project

BackgroundIn 2019, the Open Pediatric Brain Tumor Atlas (OpenPBTA) was created as a global, collaborative open-science initiative to genomically characterize 1,074 pediatric brain tumors and 22 patient-derived cell lines. Here, we present an extension of the OpenPBTA called the Open Pediatric Cancer (OpenPedCan) Project, a harmonized open-source multi-omic dataset from 6,112 pediatric cancer patients with 7,096 tumor events across more than 100 histologies. Combined with RNA-Seq from the Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA), OpenPedCan contains nearly 48,000 total biospecimens (24,002 tumor and 23,893 normal specimens). FindingsWe utilized Gabriella Miller Kids First (GMKF) workflows to harmonize WGS, WXS, RNA-seq, and Targeted Sequencing datasets to include somatic SNVs, InDels, CNVs, SVs, RNA expression, fusions, and splice variants. We integrated summarized CPTAC whole cell proteomics and phospho-proteomics data, miRNA-Seq data, and have developed a methylation array harmonization workflow to include m-values, beta-vales, and copy number calls. OpenPedCan contains reproducible, dockerized workflows in GitHub, CAVATICA, and Amazon Web Services (AWS) to deliver harmonized and processed data from over 60 scalable modules which can be leveraged both locally and on AWS. The processed data are released in a versioned manner and accessible through CAVATICA or AWS S3 download (from GitHub), and queryable through PedcBioPortal and the NCIs pediatric Molecular Targets Platform. Notably, we have expanded PBTA molecular subtyping to include methylation information to align with the WHO 2021 Central Nervous System Tumor classifications, allowing us to create research-grade integrated diagnoses for these tumors. ConclusionsOpenPedCan data and its reproducible analysis module framework are openly available and can be utilized and/or adapted by researchers to accelerate discovery, validation, and clinical translation.

genomics↗

bioRxiv2024

Playbook Workflow Builder: Interactive Construction of Bioinformatics Workflows from a Network of Microservices

Many biomedical research projects produce large-scale datasets that may serve as resources for the research community for hypothesis generation, facilitating diverse use cases. Towards the goal of developing infrastructure to support the findability, accessibility, interoperability, and reusability (FAIR) of biomedical digital objects and maximally extracting knowledge from data, complex queries that span across data and tools from multiple resources are currently not easily possible. By utilizing existing FAIR application programming interfaces (APIs) that serve knowledge from many repositories and bioinformatics tools, different types of complex queries and workflows can be created by using these APIs together. The Playbook Workflow Builder (PWB) is a web-based platform that facilitates interactive construction of workflows by enabling users to utilize an ever-growing network of input datasets, semantically annotated API endpoints, and data visualization tools contributed by an ecosystem. Via a user-friendly web-based user interface (UI), workflows can be constructed from contributed building-blocks without technical expertise. The output of each step of the workflows are provided in reports containing textual descriptions, as well as interactive and downloadable figures and tables. To demonstrate the ability of the PWB to generate meaningful hypotheses that draw knowledge from across multiple resources, we present several use cases. For example, one of these use cases sieves novel targets for individual cancer patients using data from the GTEx, LINCS, Metabolomics, GlyGen, and the ExRNA Communication Consortium (ERCC) Common Fund (CF) Data Coordination Centers (DCCs). The workflows created with the PWB can be published and repurposed to tackle similar use cases using different inputs. The PWB platform is available from: https://playbook-workflow-builder.cloud/.

bioinformatics↗

bioRxiv2024

A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma

Pediatric high-grade glioma (pHGG) is an incurable central nervous system malignancy that is a leading cause of pediatric cancer death. While pHGG shares many similarities to adult glioma, it is increasingly recognized as a molecularly distinct, yet highly heterogeneous disease. In this study, we longitudinally profiled a molecularly diverse cohort of 16 pHGG patients before and after standard therapy through single-nucleus RNA and ATAC sequencing, whole-genome sequencing, and CODEX spatial proteomics to capture the evolution of the tumor microenvironment during progression following treatment. We found that the canonical neoplastic cell phenotypes of adult glioblastoma are insufficient to capture the range of tumor cell states in a pediatric cohort and observed differential tumor-myeloid interactions between malignant cell states. We identified key transcriptional regulators of pHGG cell states and did not observe the marked proneural to mesenchymal shift characteristic of adult glioblastoma. We showed that essential neuromodulators and the interferon response are upregulated post-therapy along with an increase in non-neoplastic oligodendrocytes. Through in vitro pharmacological perturbation, we demonstrated novel malignant cell-intrinsic targets. This multiomic atlas of longitudinal pHGG captures the key features of therapy response that support distinction from its adult counterpart and suggests therapeutic strategies which are targeted to pediatric gliomas.

cancer biology↗

bioRxiv2023

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

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

bioinformatics↗

bioRxiv2022

Transcriptional immunogenomic analysis reveals distinct immunological clusters in pediatric nervous system tumours

To inform immunotherapy approaches in children, we performed an immunogenomic analysis of RNA-seq data from 925 treatment-naive pediatric nervous system tumours (pedNST) spanning 12 cancer types from three public data sets. Within pedNST, we uncovered four broad immune clusters: Pediatric Inflamed (10%), Myeloid Predominant (30%), Immune Neutral (43%) and Immune Excluded (17%). We validated these clusters using immunohistochemistry, methylation immune inference, and segmentation analysis of tissue images. We report shared biology of these immune clusters within and across cancer types, and characterization of specific immune-cell frequencies as well as T- and B-cell repertoires. We found no associations between immune infiltration levels and tumour mutational burden, although molecular cancer entities were enriched within specific immune clusters. Given the heterogeneity within pedNST, our findings suggest personalized immunogenomic profiling is needed to guide selection of immunotherapeutic strategies.

genomics↗

bioRxiv2022

ALT in Pediatric Brain Tumors Can Occur without ATRX Mutation and is Enriched in Patients with Pathogenic Germline MMR Variants

BackgroundTo achieve replicative immortality, most cancers develop a telomere maintenance mechanism, such as reactivation of telomerase or alternative lengthening of telomeres (ALT). There are limited data on the prevalence and clinical significance of ALT in pediatric brain tumors, and ALT-directed therapy is not available. MethodsWe performed C-circle analysis (CCA) on 579 pediatric brain tumors that had corresponding tumor/normal whole genome sequencing through the Open Pediatric Brain Tumor Atlas (OpenPBTA). We detected ALT in 6.9% (n=40/579) of these tumors and completed additional validation by ultrabright telomeric foci in situ on a subset of these tumors. We used CCA to validate TelomereHunter for computational prediction of ALT status and focus subsequent analyses on pediatric high-grade glioma (pHGG) Finally, we examined whether ALT is associated with recurrent somatic or germline alterations. ResultsALT is common in pHGG (n=24/63, 38.1%), but occurs infrequently in other pediatric brain tumors (<3%). Somatic ATRX mutations occur in 50% of ALT+ pHGG and in 30% of ALT-pHGG. Rare pathogenic germline variants in mismatch repair (MMR) genes are significantly associated with an increased occurrence of ALT. Conclusions: We demonstrate that ATRX is mutated in only a subset of ALT+ pHGG, suggesting other mechanisms of ATRX loss of function or alterations in other genes may be associated with the development of ALT in these patients. We show that germline variants in MMR are associated with development of ALT in patients with pHGG. Key PointsATRX alterations are frequent, but not required, for an ALT phenotype in pHGGs pHGG patients with germline mismatch repair variants have higher rate of ALT + tumors TelomereHunter is validated to predict ALT in pHGGs Importance of the StudyWe performed orthogonal molecular and computational analyses to detect the presence of alternative lengthening of telomeres in a highly characterized cohort of pediatric brain tumors. We demonstrate that many pHGG utilize ALT without a mutation in ATRX, suggesting either loss of function of ATRX via an alternative mechanism or an alternate means of development of ALT. We show that germline variants in MMR genes are significantly associated with ALT in pHGG. Our work adds to the biological understanding of the development of ALT and provides an approach to stratify patients who may benefit from future ALT-directed therapies in this patient population.

cancer biology↗

bioRxiv2021

Development of GPC2-directed chimeric antigen receptors using mRNA for pediatric brain tumors

Pediatric brain tumors are the leading cause of cancer death in children with an urgent need for innovative therapies. Here we show that the cell surface oncoprotein glypican 2 (GPC2) is highly expressed on multiple lethal pediatric brain tumors, including medulloblastomas, embryonal tumors with multi-layered rosettes, other CNS embryonal tumors, as well as definable subsets of highly malignant gliomas. To target GPC2 on these pediatric brain tumors with adoptive cellular therapies and mitigate potential inflammatory neurotoxicity, we developed four mRNA chimeric antigen receptor (CAR) T cell constructs using the highly GPC2-specific fully human D3 single chain variable fragment. First, we validated and prioritized these CARs using in vitro cytotoxicity and T cell degranulation assays with GPC2-expressing neuroblastoma cells. Next, we expanded the testing of the two most potent GPC2-directed CAR constructs prioritized from these studies to GPC2-expressing medulloblastoma and high-grade glioma cell lines, showing significant GPC2-specific cell death in multiple models. Finally, locoregional delivery bi-weekly of two to four million GPC2-directed mRNA CAR T cells induced significant and sustained tumor regression in two orthotopic medulloblastoma models, and significantly prolonged survival in an aggressive orthotopic thalamic diffuse midline glioma model. No GPC2-directed CAR T cell related neurologic or systemic toxicity was observed. Taken together, these data show that GPC2 is a highly differentially expressed cell surface protein on multiple malignant pediatric brain tumors that can be targeted safely with local delivery of mRNA CAR T cells. One Sentence SummaryGlypican 2 is expressed on the surface of multiple pediatric brain tumors and can be successfully targeted with mRNA chimeric antigen receptor T cells.

cancer biology↗

bioRxiv2020

Novel BRAF gene fusions in pediatric histiocytic neoplasms define distinct therapeutic responsiveness to RAF paradox breakers

Pediatric histiocytic neoplasms are clonal hematopoietic disorders driven by mutations activating the mitogen-activated protein kinase (MAPK) pathway, such as BRAF-V600E. In non-BRAFV600E cases, we investigated alternative MAPK mutations and found two novel BRAF gene fusions. We investigated the distinct responsiveness of novel BRAF fusions to RAFi therapies and explored the mechanistic basis of such differential responses compared to other BRAF fusions. Two histiocytic patient tumors were analyzed using the CHOP Comprehensive Next-Gen Sequencing Solid Tumor Panel and a targeted RNA-seq panel for 106 fusion partner genes. In the two M- and L-type histiocytic neoplasms assessed, we found novel and rare BRAF gene fusions, MTAP-BRAF and MS4A6A-BRAF, respectively. Both BRAF fusions activated the MAPK/ PI3K pathways and showed homo- and hetero-dimerization with BRAF and the respective N-terminal fusion partner. In contrast to common BRAF fusions, MTAP-BRAF and MS4A6A-BRAF did not respond to PLX8394 due to a lack of disruption of active fusion homo- and hetero-dimers, which was in turn due to the untargeted, stable dimerization mediated by the N-terminal fusion partners. Conversely, we observed robust suppression with LY3009120 that bound fusion dimers and kept them in an inactivate confirmation. MEKi were found to successfully suppress fusion driven signaling and oncogenic phenotypes. Our finding that PLX8394 does not disrupt MTAP-BRAF or MS4A6A-BRAF dimerization due to contribution of N-terminal partners defines a novel paradigm for the distinct mechanisms sought by BRAF fusions in response to RAFi therapy. Overall, this study highlights the unique and differential biology hijacked by BRAF fusions in response to RAFi and further warrants detailed mechanistic classification of BRAF fusions based on their responsiveness to targeted agents.

cancer biology↗

bioRxiv2019

annoFuse: an R Package to annotate and prioritize putative oncogenic RNA fusions

BackgroundGene fusion events are a significant source 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. ResultsWe 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 = 1,028) 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. ConclusionsannoFuse provides standardized filtering and annotation for gene fusion calls from STARFusion 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.

bioinformatics↗

bioRxiv2019

Pediatric High Grade Glioma Resources From the Children’s Brain Tumor Tissue Consortium (CBTTC) and Pediatric Brain Tumor Atlas (PBTA)

BackgroundPediatric high grade glioma (pHGG) remains a fatal disease. Increased access to richly annotated biospecimens and patient derived tumor models will accelerate pHGG research and support translation of research discoveries. This work describes the pediatric high grade glioma set of the Childrens Brain Tumor Tissue Consortium (CBTTC) from the first release (October 2018) of the Pediatric Brain Tumor Atlas (PBTA).\n\nMethodspHGG tumors with associated clinical data and imaging were prospectively collected through the CBTTC and analyzed as the Pediatric Brain Tumor Atlas (PBTA) with processed genomic data deposited into PedcBioPortal for broad access and visualization. Matched tumor was cultured to create high grade glioma cell lines analyzed by targeted and WGS and RNA-seq. A tissue microarray (TMA) of primary pHGG tumors was also created.\n\nResultsThe pHGG set included 87 collection events (73 patients, 60% at diagnosis, median age of 9 yrs, 55% female, 46% hemispheric). Analysis of somatic mutations and copy number alterations of known glioma genes were of expected distribution (36% H3.3, 47% TP53, 24% ATRX and 7% BRAF V600E variants). A pHGG TMA (n=77), includes 36 (53%) patient tumors with matched sequencing. At least one established glioma cell line was generated from 23 patients (32%). Unique reagents include those derived from a H3.3 G34R glioma and from tumors with mismatch repair deficiency.\n\nConclusionThe CBTTC and PBTA have created an openly available integrated resource of over 2,000 tumors, including a rich set of pHGG primary tumors, corresponding cell lines and archival fixed tissue to advance translational research for pHGG.\n\nIMPORTANCE OF STUDYHigh-grade gliomas (HGG) remain the leading cause of cancer death in children. Since molecularly heterogeneous, preclinical studies of pediatric HGG will be most informative if able to compare across groups. Given their relatively rarity, there are few readily available biospecimens and cellular models to inform preclinical laboratory and genomic translational research. Therefore, the aim of this CBTTC study was to highlight the panel of pediatric HGG cases whose primary tumors have undergone extensive genomic analysis, have clinical data, available imaging and additional biospecimens, including tumor, nucleic acids, cell lines and FFPE tissue on a tissue microarray (TMA).

cancer biology↗