Jagged2 targeting in lung cancer activates anti-tumor immunity via Notch-induced functional reprogramming of tumor-associated macrophages.

Signaling through Notch receptors intrinsically regulates tumor cell development and growth. Here, we studied the role of the Notch ligand Jagged2 on immune evasion in non-small cell lung cancer (NSCLC). Higher expression of JAG2 in NSCLC negatively correlated with survival. In NSCLC pre-clinical models, deletion of Jag2, but not Jag1, in cancer cells attenuated tumor growth and activated protective anti-tumor T cell responses. Jag2-/- lung tumors exhibited higher frequencies of macrophages that expressed immunostimulatory mediators and triggered T cell-dependent anti-tumor immunity. Mechanistically, Jag2 ablation promoted Nr4a-mediated induction of Notch ligands DLL1/4 on cancer cells. DLL1/4-initiated Notch1/2 signaling in macrophages induced the expression of transcription factor IRF4 and macrophage immunostimulatory functionality. IRF4 expression was required for the anti-tumor effects of Jag2 deletion in lung tumors. Antibody targeting of Jagged2 inhibited tumor growth and activated IRF4-driven macrophage-mediated anti-tumor immunity. Thus, Jagged2 orchestrates immunosuppressive systems in NSCLC that can be overcome to incite macrophage-mediated anti-tumor immunity.

C9orf72 Dipeptide Repeats Impair the Assembly, Dynamics, and Function of Membrane-Less Organelles.

Expansion of a hexanucleotide repeat GGGGCC (G4C2) in C9ORF72 is the most common cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Transcripts carrying (G4C2) expansions undergo unconventional, non-ATG-dependent translation, generating toxic dipeptide repeat (DPR) proteins thought to contribute to disease. Here, we identify the interactome of all DPRs and find that arginine-containing DPRs, polyGly-Arg (GR) and polyPro-Arg (PR), interact with RNA-binding proteins and proteins with low complexity sequence domains (LCDs) that often mediate the assembly of membrane-less organelles. Indeed, most GR/PR interactors are components of membrane-less organelles such as nucleoli, the nuclear pore complex and stress granules. Genetic analysis in Drosophila demonstrated the functional relevance of these interactions to DPR toxicity. Furthermore, we show that GR and PR altered phase separation of LCD-containing proteins, insinuating into their liquid assemblies and changing their material properties, resulting in perturbed dynamics and/or functions of multiple membrane-less organelles.

ULK1 and ULK2 Regulate Stress Granule Disassembly Through Phosphorylation and Activation of VCP/p97.

Disturbances in autophagy and stress granule dynamics have been implicated as potential mechanisms underlying inclusion body myopathy (IBM) and related disorders. Yet the roles of core autophagy proteins in IBM and stress granule dynamics remain poorly characterized. Here, we demonstrate that disrupted expression of the core autophagy proteins ULK1 and ULK2 in mice causes a vacuolar myopathy with ubiquitin and TDP-43-positive inclusions; this myopathy is similar to that caused by VCP/p97 mutations, the most common cause of familial IBM. Mechanistically, we show that ULK1/2 localize to stress granules and phosphorylate VCP, thereby increasing VCP's activity and ability to disassemble stress granules. These data suggest that VCP dysregulation and defective stress granule disassembly contribute to IBM-like disease in Ulk1/2-deficient mice. In addition, stress granule disassembly is accelerated by an ULK1/2 agonist, suggesting ULK1/2 as targets for exploiting the higher-order regulation of stress granules for therapeutic intervention of IBM and related disorders.

Integrative Proteomics and Phosphoproteomics Profiling Reveals Dynamic Signaling Networks and Bioenergetics Pathways Underlying T Cell Activation.

The molecular circuits by which antigens activate quiescent T cells remain poorly understood. We combined temporal profiling of the whole proteome and phosphoproteome via multiplexed isobaric labeling proteomics technology, computational pipelines for integrating multi-omics datasets, and functional perturbation to systemically reconstruct regulatory networks underlying T cell activation. T cell receptors activated the T cell proteome and phosphoproteome with discrete kinetics, marked by early dynamics of phosphorylation and delayed ribosome biogenesis and mitochondrial activation. Systems biology analyses identified multiple functional modules, active kinases, transcription factors and connectivity between them, and mitochondrial pathways including mitoribosomes and complex IV. Genetic perturbation revealed physiological roles for mitochondrial enzyme COX10-mediated oxidative phosphorylation in T cell quiescence exit. Our multi-layer proteomics profiling, integrative network analysis, and functional studies define landscapes of the T cell proteome and phosphoproteome and reveal signaling and bioenergetics pathways that mediate lymphocyte exit from quiescence.

An Epigenomic fingerprint of human cancers by landscape interrogation of super enhancers at the constituent level.

Super enhancers (SE), large genomic elements that activate transcription and drive cell identity, have been found with cancer-specific gene regulation in human cancers. Recent studies reported the importance of understanding the cooperation and function of SE internal components, i.e., the constituent enhancers (CE). However, there are no pan-cancer studies to identify cancer-specific SE signatures at the constituent level. Here, by revisiting pan-cancer SE activities with H3K27Ac ChIP-seq datasets, we report fingerprint SE signatures for 28 cancer types in the NCI-60 cell panel. We implement a mixture model to discriminate active CEs from inactive CEs by taking into consideration ChIP-seq variabilities between cancer samples and across CEs. We demonstrate that the model-based estimation of CE states provides improved functional interpretation of SE-associated regulation. We identify cancer-specific CEs by balancing their active prevalence with their capability of encoding cancer type identities. We further demonstrate that cancer-specific CEs have the strongest per-base enhancer activities in independent enhancer sequencing assays, suggesting their importance in understanding critical SE signatures. We summarize fingerprint SEs based on the cancer-specific statuses of their component CEs and build an easy-to-use R package to facilitate the query, exploration, and visualization of fingerprint SEs across cancers.

The Noncanonical Role of ULK/ATG1 in ER-to-Golgi Trafficking Is Essential for Cellular Homeostasis.

ULK1 and ULK2 are thought to be essential for initiating autophagy, and Ulk1/2-deficient mice die perinatally of autophagy-related defects. Therefore, we used a conditional knockout approach to investigate the roles of ULK1/2 in the brain. Although the mice showed neuronal degeneration, the neurons showed no accumulation of P62(+)/ubiquitin(+) inclusions or abnormal membranous structures, which are observed in mice lacking other autophagy genes. Rather, neuronal death was associated with activation of the unfolded protein response (UPR) pathway. An unbiased proteomics approach identified SEC16A as an ULK1/2 interaction partner. ULK-mediated phosphorylation of SEC16A regulated the assembly of endoplasmic reticulum (ER) exit sites and ER-to-Golgi trafficking of specific cargo, and did not require other autophagy proteins (e.g., ATG13). The defect in ER-to-Golgi trafficking activated the UPR pathway in ULK-deficient cells; both processes were reversed upon expression of SEC16A with a phosphomimetic substitution. Thus, the regulation of ER-to-Golgi trafficking by ULK1/2 is essential for cellular homeostasis.

Summarizing internal dynamics boosts differential analysis and functional interpretation of super enhancers.

Super enhancers (SEs) are broad enhancer domains usually containing multiple constituent enhancers that hold elevated activities in gene regulation. Disruption in one or more constituent enhancers causes aberrant SE activities that lead to gene dysregulation in diseases. To quantify SE aberrations, differential analysis is performed to compare SE activities between cell conditions. The state-of-art strategy in estimating differential SEs relies on overall activities and neglect the changes in length and structure of SEs. Here, we propose a novel computational method to identify differential SEs by weighting the combinatorial effects of constituent-enhancer activities and locations (i.e. internal dynamics). In addition to overall activity changes, our method identified four novel classes of differential SEs with distinct enhancer structural alterations. We demonstrate that these structure alterations hold distinct regulatory impact, such as regulating different number of genes and modulating gene expression with different strengths, highlighting the differentiated regulatory roles of these unexplored SE features. When compared to the existing method, our method showed improved identification of differential SEs that were linked to better discernment of cell-type-specific SE activity and functional interpretation.

PATH-SURVEYOR: pathway level survival enquiry for immuno-oncology and drug repurposing.

Pathway-level survival analysis offers the opportunity to examine molecular pathways and immune signatures that influence patient outcomes. However, available survival analysis algorithms are limited in pathway-level function and lack a streamlined analytical process. Here we present a comprehensive pathway-level survival analysis suite, PATH-SURVEYOR, which includes a Shiny user interface with extensive features for systematic exploration of pathways and covariates in a Cox proportional-hazard model. Moreover, our framework offers an integrative strategy for performing Hazard Ratio ranked Gene Set Enrichment Analysis and pathway clustering. As an example, we applied our tool in a combined cohort of melanoma patients treated with checkpoint inhibition (ICI) and identified several immune populations and biomarkers predictive of ICI efficacy. We also analyzed gene expression data of pediatric acute myeloid leukemia (AML) and performed an inverse association of drug targets with the patient's clinical endpoint. Our analysis derived several drug targets in high-risk KMT2A-fusion-positive patients, which were then validated in AML cell lines in the Genomics of Drug Sensitivity database. Altogether, the tool offers a comprehensive suite for pathway-level survival analysis and a user interface for exploring drug targets, molecular features, and immune populations at different resolutions.

The landscape of coding RNA editing events in pediatric cancer.

BACKGROUND: RNA editing leads to post-transcriptional variation in protein sequences and has important biological implications. We sought to elucidate the landscape of RNA editing events across pediatric cancers. METHODS: Using RNA-Seq data mapped by a pipeline designed to minimize mapping ambiguity, we investigated RNA editing in 711 pediatric cancers from the St. Jude/Washington University Pediatric Cancer Genome Project focusing on coding variants which can potentially increase protein sequence diversity. We combined de novo detection using paired tumor DNA-RNA data with analysis of known RNA editing sites. RESULTS: We identified 722 unique RNA editing sites in coding regions across pediatric cancers, 70% of which were nonsynonymous recoding variants. Nearly all editing sites represented the canonical A-to-I (n = 706) or C-to-U sites (n = 14). RNA editing was enriched in brain tumors compared to other cancers, including editing of glutamate receptors and ion channels involved in neurotransmitter signaling. RNA editing profiles of each pediatric cancer subtype resembled those of the corresponding normal tissue profiled by the Genotype-Tissue Expression (GTEx) project. CONCLUSIONS: In this first comprehensive analysis of RNA editing events in pediatric cancer, we found that the RNA editing profile of each cancer subtype is similar to its normal tissue of origin. Tumor-specific RNA editing events were not identified indicating that successful immunotherapeutic targeting of RNA-edited peptides in pediatric cancer should rely on increased antigen presentation on tumor cells compared to normal but not on tumor-specific RNA editing per se.

H3.3 K27M depletion increases differentiation and extends latency of diffuse intrinsic pontine glioma growth in vivo.

Histone H3 K27M mutation is the defining molecular feature of the devastating pediatric brain tumor, diffuse intrinsic pontine glioma (DIPG). The prevalence of histone H3 K27M mutations indicates a critical role in DIPGs, but the contribution of the mutation to disease pathogenesis remains unclear. We show that knockdown of this mutation in DIPG xenografts restores K27M-dependent loss of H3K27me3 and delays tumor growth. Comparisons of matched DIPG xenografts with and without K27M knockdown allowed identification of mutation-specific effects on the transcriptome and epigenome. The resulting transcriptional changes recapitulate expression signatures from K27M primary DIPG tumors and are strongly enriched for genes associated with nervous system development. Integrated analysis of ChIP-seq and expression data showed that genes upregulated by the mutation are overrepresented in apparently bivalent promoters. Many of these targets are associated with more immature differentiation states. Expression profiles indicate K27M knockdown decreases proliferation and increases differentiation within lineages represented in DIPG. These data suggest that K27M-mediated loss of H3K27me3 directly regulates a subset of genes by releasing poised promoters, and contributes to tumor phenotype and growth by limiting differentiation. The delayed tumor growth associated with knockdown of H3 K27M provides evidence that this highly recurrent mutation is a relevant therapeutic target.

Correction to: H3.3 K27M depletion increases differentiation and extends latency of diffuse intrinsic pontine glioma growth in vivo.

The original article can be found online.

Target-Decoy-Based False Discovery Rate Estimation for Large-Scale Metabolite Identification.

Metabolite identification is a crucial step in mass spectrometry (MS)-based metabolomics. However, it is still challenging to assess the confidence of assigned metabolites. We report a novel method for estimating the false discovery rate (FDR) of metabolite assignment with a target-decoy strategy, in which the decoys are generated through violating the octet rule of chemistry by adding small odd numbers of hydrogen atoms. The target-decoy strategy was integrated into JUMPm, an automated metabolite identification pipeline for large-scale MS analysis and was also evaluated with two other metabolomics tools, mzMatch and MZmine 2. The reliability of FDR calculation was examined by false data sets, which were simulated by altering MS1 or MS2 spectra. Finally, we used the JUMPm pipeline coupled to the target-decoy strategy to process unlabeled and stable-isotope-labeled metabolomic data sets. The results demonstrate that the target-decoy strategy is a simple and effective method for evaluating the confidence of high-throughput metabolite identification.

Isotope Labeling-Assisted Evaluation of Hydrophilic and Hydrophobic Liquid Chromatograph-Mass Spectrometry for Metabolomics Profiling.

High throughput untargeted metabolomics usually relies on complementary liquid chromatography-mass spectrometry (LC-MS) methods to expand the coverage of diverse metabolites, but the integration of those methods is not fully characterized. We systematically investigated the performance of hydrophilic interaction liquid chromatography (HILIC)-MS and nanoflow reverse-phase liquid chromatography (nRPLC)-MS under 8 LC-MS settings, varying stationary phases (HILIC and C18), mobile phases (acidic and basic pH), and MS ionization modes (positive and negative). Whereas nRPLC-MS optimization was previously reported, we found in HILIC-MS (2.1 mm × 150 mm) that the optimal performance was achieved in a 90 min gradient with 100 µL/min flow rate by loading metabolite extracts from 2 mg of cell/tissue samples. Since peak features were highly compromised by contaminants, we used stable isotope labeled yeast to enhance formula identification for comparing different LC-MS conditions. The 8 LC-MS settings enabled the detection of a total of 1050 formulas, among which 78%, 73%, and 62% formulas were recovered by the best combination of 4, 3, and 2 LC-MS settings, respectively. Moreover, these yeast samples were harvested in the presence or absence of nitrogen starvation, enabling quantitative comparisons of altered formulas and metabolite structures, followed by validation with selected synthetic metabolites. The results revealed that nitrogen starvation downregulated amino acid components but upregulated uridine-related metabolism. In summary, this study introduces a thorough evaluation of hydrophilicity and hydrophobicity based LC-MS and provides information for selecting complementary settings to balance throughput and efficiency during metabolomics experiments.

JUMPg: An Integrative Proteogenomics Pipeline Identifying Unannotated Proteins in Human Brain and Cancer Cells.

Proteogenomics is an emerging approach to improve gene annotation and interpretation of proteomics data. Here we present JUMPg, an integrative proteogenomics pipeline including customized database construction, tag-based database search, peptide-spectrum match filtering, and data visualization. JUMPg creates multiple databases of DNA polymorphisms, mutations, splice junctions, partially trypticity, as well as protein fragments translated from the whole transcriptome in all six frames upon RNA-seq de novo assembly. We use a multistage strategy to search these databases sequentially, in which the performance is optimized by re-searching only unmatched high-quality spectra and reusing amino acid tags generated by the JUMP search engine. The identified peptides/proteins are displayed with gene loci using the UCSC genome browser. Then, the JUMPg program is applied to process a label-free mass spectrometry data set of Alzheimer's disease postmortem brain, uncovering 496 new peptides of amino acid substitutions, alternative splicing, frame shift, and "non-coding gene" translation. The novel protein PNMA6BL specifically expressed in the brain is highlighted. We also tested JUMPg to analyze a stable-isotope labeled data set of multiple myeloma cells, revealing 991 sample-specific peptides that include protein sequences in the immunoglobulin light chain variable region. Thus, the JUMPg program is an effective proteogenomics tool for multiomics data integration.

HIV N-linked glycosylation site analyzer and its further usage in anchored alignment.

N-linked glycosylation is a posttranslational modification that has significantly contributed to the rapid evolution of HIV-1. In particular, enrichment of N-linked glycosylation sites can be found within Envelope variable loops, regions that play an essential role in HIV pathogenesis and immunogenicity. The web server described here, the HIV N-linked Glycosylation Site Analyzer, was developed to facilitate study of HIV diversity by tracking gp120 N-linked glycosylation sites. This server provides an automated platform for mapping and comparing variable loop N-linked glycosylation sites across populations of HIV-1 sequences. Furthermore, this server allows for refinement of HIV-1 sequence alignment by using N-linked glycosylation sites in variable loops as alignment anchors. Availability of this web server solves one of the difficult problems in HIV gp120 alignment and analysis imposed by the extraordinary HIV-1 diversity. The HIV N-linked Glycosylation Site Analyzer web server is available at http://hivtools.publichealth.uga.edu/N-Glyco/.

STRAW: Species TRee Analysis Web server.

The coalescent methods for species tree reconstruction are increasingly popular because they can accommodate coalescence and multilocus data sets. Herein, we present STRAW, a web server that offers workflows for reconstruction of phylogenies of species using three species tree methods-MP-EST, STAR and NJst. The input data are a collection of rooted gene trees (for STAR and MP-EST methods) or unrooted gene trees (for NJst). The output includes the estimated species tree, modified Robinson-Foulds distances between gene trees and the estimated species tree and visualization of trees to compare gene trees with the estimated species tree. The web sever is available at http://bioinformatics.publichealth.uga.edu/SpeciesTreeAnalysis/.

Assemblathon 1: a competitive assessment of de novo short read assembly methods.

Low-cost short read sequencing technology has revolutionized genomics, though it is only just becoming practical for the high-quality de novo assembly of a novel large genome. We describe the Assemblathon 1 competition, which aimed to comprehensively assess the state of the art in de novo assembly methods when applied to current sequencing technologies. In a collaborative effort, teams were asked to assemble a simulated Illumina HiSeq data set of an unknown, simulated diploid genome. A total of 41 assemblies from 17 different groups were received. Novel haplotype aware assessments of coverage, contiguity, structure, base calling, and copy number were made. We establish that within this benchmark: (1) It is possible to assemble the genome to a high level of coverage and accuracy, and that (2) large differences exist between the assemblies, suggesting room for further improvements in current methods. The simulated benchmark, including the correct answer, the assemblies, and the code that was used to evaluate the assemblies is now public and freely available from http://www.assemblathon.org/.

Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression.

Immunotherapy with CAR T cells for pediatric solid and brain tumors is constrained by available targetable antigens. Cancer-specific exons (CSE) present a promising reservoir of targets; however, these have not been explored and validated systematically in a pan-cancer fashion. To identify CSE targets, we analyzed 1,532 RNA-seq datasets from 16 types of pediatric solid and brain tumors for comparison with normal tissues using a newly developed workflow. We found 2,933 exons in 157 genes encoding proteins of the surfaceome or matrisome with high cancer specificity either at the gene (n=148) or the alternatively spliced (AS) isoform (n=9) level. Expression of selected AS targets, including the EDB domain of FN1 (EDB), and gene targets, such as COL11A1, were validated in pediatric PDX tumors. We generated CAR T cells specific to EDB or COL11A1 and demonstrated that COL11A1-CAR T-cells have potent antitumor activity. The full target list, explorable via an interactive web portal (https://cseminer.stjude.org/), provides a rich resource for developing immunotherapy of pediatric solid and brain tumors using gene or AS targets with high expression specificity in cancer.

Discovery of immunotherapy targets for pediatric solid and brain tumors by exon-level expression.

Immunotherapy with chimeric antigen receptor T cells for pediatric solid and brain tumors is constrained by available targetable antigens. Cancer-specific exons present a promising reservoir of targets; however, these have not been explored and validated systematically in a pan-cancer fashion. To identify cancer specific exon targets, here we analyze 1532 RNA-seq datasets from 16 types of pediatric solid and brain tumors for comparison with normal tissues using a newly developed workflow. We find 2933 exons in 157 genes encoding proteins of the surfaceome or matrisome with high cancer specificity either at the gene (n = 148) or the alternatively spliced isoform (n = 9) level. Expression of selected alternatively spliced targets, including the EDB domain of fibronectin 1, and gene targets, such as COL11A1, are validated in pediatric patient derived xenograft tumors. We generate T cells expressing chimeric antigen receptors specific for the EDB domain or COL11A1 and demonstrate that these have antitumor activity. The full target list, explorable via an interactive web portal ( https://cseminer.stjude.org/ ), provides a rich resource for developing immunotherapy of pediatric solid and brain tumors using gene or AS targets with high expression specificity in cancer.