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.

MitoScape: A big-data, machine-learning platform for obtaining mitochondrial DNA from next-generation sequencing data.

The growing number of next-generation sequencing (NGS) data presents a unique opportunity to study the combined impact of mitochondrial and nuclear-encoded genetic variation in complex disease. Mitochondrial DNA variants and in particular, heteroplasmic variants, are critical for determining human disease severity. While there are approaches for obtaining mitochondrial DNA variants from NGS data, these software do not account for the unique characteristics of mitochondrial genetics and can be inaccurate even for homoplasmic variants. We introduce MitoScape, a novel, big-data, software for extracting mitochondrial DNA sequences from NGS. MitoScape adopts a novel departure from other algorithms by using machine learning to model the unique characteristics of mitochondrial genetics. We also employ a novel approach of using rho-zero (mitochondrial DNA-depleted) data to model nuclear-encoded mitochondrial sequences. We showed that MitoScape produces accurate heteroplasmy estimates using gold-standard mitochondrial DNA data. We provide a comprehensive comparison of the most common tools for obtaining mtDNA variants from NGS and showed that MitoScape had superior performance to compared tools in every statistically category we compared, including false positives and false negatives. By applying MitoScape to common disease examples, we illustrate how MitoScape facilitates important heteroplasmy-disease association discoveries by expanding upon a reported association between hypertrophic cardiomyopathy and mitochondrial haplogroup T in men (adjusted p-value = 0.003). The improved accuracy of mitochondrial DNA variants produced by MitoScape will be instrumental in diagnosing disease in the context of personalized medicine and clinical diagnostics.

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.

Ancestry and frequency of genetic variants in the general population are confounders in the characterization of germline variants linked to cancer.

BACKGROUND: Pediatric high-grade gliomas (pHGGs) are incurable malignant brain cancers. Clear somatic genetic drivers are difficult to identify in the majority of cases. We hypothesized that this may be due to the existence of germline variants that influence tumor etiology and/or progression and are filtered out using traditional pipelines for somatic mutation calling. METHODS: In this study, we analyzed whole-genome sequencing (WGS) datasets of matched germlines and tumor tissues to identify recurrent germline variants in pHGG patients. RESULTS: We identified two structural variants that were highly recurrent in a discovery cohort of 8 pHGG patients. One was a ~ 40 kb deletion immediately upstream of the NEGR1 locus and predicted to remove the promoter region of this gene. This copy number variant (CNV) was present in all patients in our discovery cohort (n = 8) and in 86.3% of patients in our validation cohort (n = 73 cases). We also identified a second recurrent deletion 55.7 kb in size affecting the BTNL3 and BTNL8 loci. This BTNL3-8 deletion was observed in 62.5% patients in our discovery cohort, and in 17.8% of the patients in the validation cohort. Our single-cell RNA sequencing (scRNA-seq) data showed that both deletions result in disruption of transcription of the affected genes. However, analysis of genomic information from multiple non-cancer cohorts showed that both the NEGR1 promoter deletion and the BTNL3-8 deletion were CNVs occurring at high frequencies in the general population. Intriguingly, the upstream NEGR1 CNV deletion was homozygous in ~ 40% of individuals in the non-cancer population. This finding was immediately relevant because the affected genes have important physiological functions, and our analyses showed that NEGR1 expression levels have prognostic value for pHGG patient survival. We also found that these deletions occurred at different frequencies among different ethnic groups. CONCLUSIONS: Our study highlights the need to integrate cancer genomic analyses and genomic data from large control populations. Failure to do so may lead to spurious association of genes with cancer etiology. Importantly, our results showcase the need for careful evaluation of differences in the frequency of genetic variants among different ethnic groups.

A pilot precision medicine trial for children with diffuse intrinsic pontine glioma-PNOC003: A report from the Pacific Pediatric Neuro-Oncology Consortium.

This clinical trial evaluated whether whole exome sequencing (WES) and RNA sequencing (RNAseq) of paired normal and tumor tissues could be incorporated into a personalized treatment plan for newly diagnosed patients (<25 years of age) with diffuse intrinsic pontine glioma (DIPG). Additionally, whole genome sequencing (WGS) was compared to WES to determine if WGS would further inform treatment decisions, and whether circulating tumor DNA (ctDNA) could detect the H3K27M mutation to allow assessment of therapy response. Patients were selected across three Pacific Pediatric Neuro-Oncology Consortium member institutions between September 2014 and January 2016. WES and RNAseq were performed at diagnosis and recurrence when possible in a CLIA-certified laboratory. Patient-derived cell line development was attempted for each subject. Collection of blood for ctDNA was done prior to treatment and with each MRI. A specialized tumor board generated a treatment recommendation including up to four FDA-approved agents based upon the genomic alterations detected. A treatment plan was successfully issued within 21 business days from tissue collection for all 15 subjects, with 14 of the 15 subjects fulfilling the feasibility criteria. WGS results did not significantly deviate from WES-based therapy recommendations; however, WGS data provided further insight into tumor evolution and fidelity of patient-derived cell models. Detection of the H3F3A or HIST1H3B K27M (H3K27M) mutation using ctDNA was successful in 92% of H3K27M mutant cases. A personalized treatment recommendation for DIPG can be rendered within a multicenter setting using comprehensive next-generation sequencing technology in a clinically relevant timeframe.

The Open Pediatric Cancer Project.

Background: In 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 extend the OpenPBTA to create 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). Findings: We 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 NCI's 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. Conclusions: OpenPedCan 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.

Transcriptional immunogenomic analysis reveals distinct immunological clusters in paediatric nervous system tumours.

BACKGROUND: Cancer immunotherapies including immune checkpoint inhibitors and Chimeric Antigen Receptor (CAR) T-cell therapy have shown variable response rates in paediatric patients highlighting the need to establish robust biomarkers for patient selection. While the tumour microenvironment in adults has been widely studied to delineate determinants of immune response, the immune composition of paediatric solid tumours remains relatively uncharacterized calling for investigations to identify potential immune biomarkers. METHODS: To inform immunotherapy approaches in paediatric cancers with embryonal origin, we performed an immunogenomic analysis of RNA-seq data from 925 treatment-naïve paediatric nervous system tumours (pedNST) spanning 12 cancer types from three publicly available data sets. RESULTS: Within pedNST, we uncovered four broad immune clusters: Paediatric Inflamed (10%), Myeloid Predominant (30%), Immune Neutral (43%) and Immune Desert (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. CONCLUSIONS: Given the heterogeneity of immune infiltration within pedNST, our findings suggest personalized immunogenomic profiling is needed to guide selection of immunotherapeutic strategies.

OpenPBTA: The Open Pediatric Brain Tumor Atlas.

Pediatric brain and spinal cancers are collectively the leading disease-related cause of death in children; thus, we urgently need curative therapeutic strategies for these tumors. To accelerate such discoveries, the Children's Brain Tumor Network (CBTN) and Pacific Pediatric Neuro-Oncology Consortium (PNOC) created a systematic process for tumor biobanking, model generation, and sequencing with immediate access to harmonized data. We leverage these data to establish OpenPBTA, an open collaborative project with over 40 scalable analysis modules that genomically characterize 1,074 pediatric brain tumors. Transcriptomic classification reveals universal TP53 dysregulation in mismatch repair-deficient hypermutant high-grade gliomas and TP53 loss as a significant marker for poor overall survival in ependymomas and H3 K28-mutant diffuse midline gliomas. Already being actively applied to other pediatric cancers and PNOC molecular tumor board decision-making, OpenPBTA is an invaluable resource to the pediatric oncology community.

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.

Transcriptome signatures associated with meningioma progression.

Meningiomas are the most common primary brain tumor of adults. The majority are benign (WHO grade I), with a mostly indolent course; 20% of them (WHO grade II and III) are, however, considered aggressive and require a more complex management. WHO grade II and III tumors are heterogeneous and, in some cases, can develop from a prior lower grade meningioma, although most arise de novo. Mechanisms leading to progression or implicated in de novo grade II and III tumorigenesis are poorly understood. RNA-seq was used to profile the transcriptome of grade I, II, and III meningiomas and to identify genes that may be involved in progression. Bioinformatic analyses showed that grade I meningiomas that progress to a higher grade are molecularly different from those that do not. As such, we identify GREM2, a regulator of the BMP pathway, and the snoRNAs SNORA46 and SNORA48, as being significantly reduced in meningioma progression. Additionally, our study has identified several novel fusion transcripts that are differentially present in meningiomas, with grade I tumors that did not progress presenting more fusion transcripts than all other tumors. Interestingly, our study also points to a difference in the tumor immune microenvironment that correlates with histopathological grade.

Intratumoral Genetic and Functional Heterogeneity in Pediatric Glioblastoma.

Pediatric glioblastoma (pGBM) is a lethal cancer with no effective therapies. To understand the mechanisms of tumor evolution in this cancer, we performed whole-genome sequencing with linked reads on longitudinally resected pGBM samples. Our analyses showed that all diagnostic and recurrent samples were collections of genetically diverse subclones. Clonal composition rapidly evolved at recurrence, with less than 8% of nonsynonymous single-nucleotide variants being shared in diagnostic-recurrent pairs. To track the origins of the mutational events observed in pGBM, we generated whole-genome datasets for two patients and their parents. These trios showed that genetic variants could be (i) somatic, (ii) inherited from a healthy parent, or (iii) de novo in the germlines of pGBM patients. Analysis of variant allele frequencies supported a model of tumor growth involving slow-cycling cancer stem cells that give rise to fast-proliferating progenitor-like cells and to nondividing cells. Interestingly, radiation and antimitotic chemotherapeutics did not increase overall tumor burden upon recurrence. These findings support an important role for slow-cycling stem cell populations in contributing to recurrences, because slow-cycling cell populations are expected to be less prone to genotoxic stress induced by these treatments and therefore would accumulate few mutations. Our results highlight the need for new targeted treatments that account for the complex functional hierarchies and genomic heterogeneity of pGBM. SIGNIFICANCE: This work challenges several assumptions regarding the genetic organization of pediatric GBM and highlights mutagenic programs that start during early prenatal development.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/79/9/2111/F1.large.jpg.

High-Performance Ultraviolet Photodetector Based on Graphene Quantum Dots Decorated ZnO Nanorods/GaN Film Isotype Heterojunctions.

A novel isotype heterojunction ultraviolet photodetector was fabricated by growing n-ZnO nanorod arrays on n-GaN thin films and then spin-coated with graphene quantum dots (GQDs). Exposed to UV illumination with a wavelength of 365 nm, the time-dependent photoresponse of the hybrid detectors manifests high sensitivity and consistent transients with a rise time of 100 ms and a decay time of 120 ms. Meanwhile, an ultra-high specific detectivity (up to ~ 1012 Jones) and high photoresponsivity (up to 34 mA W-1) are obtained at 10 V bias. Compared to the bare heterojunction detectors, the excellent performance of the GQDs decorated n-ZnO/n-GaN heterostructure is attributed to the efficient immobilization of GQDs on the ZnO nanorod arrays. GQDs were exploited as a light absorber and act like an electron donor to effectively improve the effective carrier concentration in interfacial junction. Moreover, appropriate energy band alignment in GQDs decorated ZnO/GaN hybrids can also be a potential factor in facilitating the UV-induced photocurrent and response speed.

New Understanding on Photocatalytic Mechanism of Nitrogen-Doped Graphene Quantum Dots-Decorated BiVO4 Nanojunction Photocatalysts.

Bismuth vanadate (BiVO4) is a promising candidate as a visible-light-driven photocatalyst in the aspect of practical applications. To investigate the origin of active species from BiVO4 and understand the influence of the variations of the photocatalytic process, comparative studies on zero-dimensional nitrogen-doped graphene quantum dot (NGQD)-decorated BiVO4 have been carried out for methylene blue photodegradation. It was found that the hydroxyl group-rich NGQD surface and the established heterojunction structure between NGQDs and BiVO4 were greatly beneficial for the conversion of the •OH radical. With NGQD decoration, the dominant oxidant species for NGQDs/BiVO4 were confirmed to be •OH and H2O2, rather than holes originating from the valence band of unmodified BiVO4. The synergistic photocatalytic mechanism with respect to the interfacial charge transport and the conversion of active species was proposed. The achievement of the controllable active species significantly altering the activity may be applied for different photocatalytic reactions.

Overcoming resistance to single-agent therapy for oncogenic BRAF gene fusions via combinatorial targeting of MAPK and PI3K/mTOR signaling pathways.

Pediatric low-grade gliomas (PLGGs) are frequently associated with activating BRAF gene fusions, such as KIAA1549-BRAF, that aberrantly drive the mitogen activated protein kinase (MAPK) pathway. Although RAF inhibitors (RAFi) have been proven effective in BRAF-V600E mutant tumors, we have previously shown how the KIAA1549-BRAF fusion can be paradoxically activated by RAFi. While newer classes of RAFi, such as PLX8394, have now been shown to inhibit MAPK activation by KIAA1549-BRAF, we sought to identify alternative MAPK pathway targeting strategies using clinically relevant MEK inhibitors (MEKi), along with potential escape mechanisms of acquired resistance to single-agent MAPK pathway therapies. We demonstrate effectiveness of multiple MEKi against diverse BRAF-fusions with novel N-terminal partners, with trametinib being the most potent. However, resistance to MEKi or PLX8394 develops via increased RTK expression causing activation of PI3K/mTOR pathway in BRAF-fusion expressing resistant clones. To circumvent acquired resistance, we show potency of combinatorial targeting with trametinib and everolimus, an mTOR inhibitor (mTORi) against multiple BRAF-fusions. While single-agent mTORi and MEKi PLGG clinical trials are underway, our study provides preclinical rationales for using MEKi and mTORi combinatorial therapy to stave off or prevent emergent drug-resistance in BRAF-fusion driven PLGGs.

Controllable Growth of Ultrathin P-doped ZnO Nanosheets.

Ultrathin phosphor (P)-doped ZnO nanosheets with branched nanowires were controllably synthesized, and the effects of oxygen and phosphor doping on the structural and optical properties were systematically studied. The grown ZnO nanosheet exhibits an ultrathin nanoribbon backbone with one-side-aligned nanoteeth. For the growth of ultrathin ZnO nanosheets, both oxygen flow rate and P doping are essential, by which the morphologies and microstructures can be finely tuned. P doping induces strain relaxation to change the growth direction of ZnO nanoribbons, and oxygen flow rate promotes the high supersaturation degree to facilitate the growth of nanoteeth and widens the nanoribbons. The growth of P-doped ZnO in this work provides a new progress towards the rational control of the morphologies for ZnO nanostructures.

Layer-by-layer thinning of two-dimensional MoS2 films by using a focused ion beam.

A layer-controlled two-dimensional (2D) molybdenum disulfide (MoS2) film with tunable bandgaps is highly desired for the fabrication of electronic/photoelectronic devices. In this work, we demonstrate that a focused ion beam (FIB) can be applied to thin MoS2 films layer-by-layer. The layer number can be controlled by simply changing the Ga(+) beam exposure time and the thinning speed is about half a layer per second. OM, AFM, PL and Raman spectra were used to monitor the change of layer numbers and characterize the morphology, thickness, and homogeneity of MoS2 films. The FIB layer-by-layer thinning technology will establish a new methodology for rationally thinning all kinds of 2D layered materials.

MYB-QKI rearrangements in angiocentric glioma drive tumorigenicity through a tripartite mechanism.

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.

Evaluation of electromechanical coupling parameters of piezoelectric materials by using piezoelectric cantilever with coplanar electrode structure in quasi-stasis.

Based on Timoshenko beam theory, a principle model is proposed to establish the relationship between electric charge and excitation acceleration, and in quasi-stasis we apply the direct piezoelectric effect of multilayer cantilever with coplanar electrode structure to evaluate the piezoelectric strain coefficient d15 and electromechanical coupling coefficient k15. They are measured as 678 pC/N and 0.74 for the commercial piezoelectric ceramic lead zirconate titanate (PZT-51) bulk specimen and 656 pC/N and 0.63 for the lead magnesium niobate (PMN) bulk specimen, and they are in agreement with the calibration and simulation values. The maximum of relative errors is less than 4.2%, so the proposed method is reliable and convenient.