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.

Comprehensive genomic analysis reveals molecular heterogeneity in pediatric ALK-positive anaplastic large cell lymphoma

Anaplastic large cell lymphoma (ALCL) is a mature T-cell lymphoma that accounts for for 10-15% of childhood lymphomas. Despite the observation that more than 90% of pediatric cases harbor the anaplastic lymphoma kinase (ALK) rearrangement resulting in aberrant ALK kinase expression, there is significant clinical, morphologic, and biological heterogeneity. To gain insights into the genomic aberrations and molecular heterogeneity within ALK-positive ALCL(ALK+ ALCL), we analyzed 46 pediatric ALK+ ALCLs by whole-exome sequencing, RNA-sequencing, and DNA methylation profiling. Whole-exome sequencing found on average 25 SNV/Indel events per sample with recurring genetic events in regulators of DNA damage (TP53, MDM4), transcription (JUNB), and epigenetic regulators (TET1, KMT2B, KMT2A, KMT2C, KMT2E). Gene expression and methylation profiling consistently subclassified ALK+ ALCLs into two groups characterized by diferential ALK expression levels. The ALK-low group showed enrichment of pathways associated with immune response, cytokine signaling, and a hypermethylated predominant pattern compared to the ALK- high group, which had more frequent copy number changes, and was enriched with pathways associated with cell growth, proliferation, metabolic pathways, and. Taken together, these findings suggest that there is molecular heterogeneity within pediatric ALK+ALCL, predicting distinct biological mechanisms that may provide novel insights into disease pathogenesis and represent prognostic markers.

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.

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.

Genetic and epigenetic features of bilateral Wilms tumor predisposition in patients from the Children's Oncology Group AREN18B5-Q

Developing synchronous bilateral Wilms tumor suggests an underlying (epi)genetic predisposition. Here, we evaluate this predisposition in 68 patients using whole exome or genome sequencing (n = 85 tumors from 61 patients with matched germline blood DNA), RNA-seq (n = 99 tumors), and DNA methylation analysis (n = 61 peripheral blood, n = 29 non-diseased kidney, n = 99 tumors). We determine the predominant events for bilateral Wilms tumor predisposition: 1)pre-zygotic germline genetic variants readily detectable in blood DNA [WT1 (14.8%), NYNRIN (6.6%), TRIM28 (5%), and BRCA-related genes (5%)] or 2)post-zygotic epigenetic hypermethylation at 11p15.5 H19/ICR1 that may require analysis of multiple tissue types for diagnosis. Of 99 total tumor specimens, 16 (16.1%) have 11p15.5 normal retention of imprinting, 25 (25.2%) have 11p15.5 copy neutral loss of heterozygosity, and 58 (58.6%) have 11p15.5 H19/ICR1 epigenetic hypermethylation (loss of imprinting). Here, we ascertain the epigenetic and genetic modes of bilateral Wilms tumor predisposition.

CBFA2T3-GLIS2-dependent pediatric acute megakaryoblastic leukemia is driven by GLIS2 and sensitive to navitoclax

Pediatric acute megakaryoblastic leukemia (AMKL) is an aggressive blood cancer associated with poor therapeutic response and high mortality. Here we describe the development of CBFA2T3-GLIS2-driven mouse models of AMKL that recapitulate the phenotypic and transcriptional signatures of the human disease. We show that an activating Ras mutation that occurs in human AMKL increases the penetrance and decreases the latency of CBF2AT3-GLIS2-driven AMKL. CBFA2T3-GLIS2 and GLIS2 modulate similar transcriptional networks. We identify the dominant oncogenic properties of GLIS2 that trigger AMKL in cooperation with oncogenic Ras. We find that both CBFA2T3-GLIS2 and GLIS2 alter the expression of a number of BH3-only proteins, causing AMKL cell sensitivity to the BCL2 inhibitor navitoclax both in vitro and in vivo, suggesting a potential therapeutic option for pediatric patients suffering from CBFA2T3-GLIS2-driven AMKL.

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.

Long Noncoding RNA Expression Independently Predicts Outcome in Pediatric Acute Myeloid Leukemia

PURPOSE

Optimized strategies for risk classification are essential to tailor therapy for patients with biologically distinctive disease. Risk classification in pediatric acute myeloid leukemia (pAML) relies on detection of translocations and gene mutations. Long noncoding RNA (lncRNA) transcripts have been shown to associate with and mediate malignant phenotypes in acute myeloid leukemia (AML) but have not been comprehensively evaluated in pAML.

METHODS

To identify lncRNA transcripts associated with outcomes, we evaluated the annotated lncRNA landscape by transcript sequencing of 1,298 pediatric and 96 adult AML specimens. Upregulated lncRNAs identified in the pAML training set were used to establish a regularized Cox regression model of event-free survival (EFS), yielding a 37 lncRNA signature (lncScore). Discretized lncScores were correlated with initial and postinduction treatment outcomes using Cox proportional hazards models in validation sets. Predictive model performance was compared with standard stratification methods by concordance analysis.

RESULTS

Training set cases with positive lncScores had 5-year EFS and overall survival rates of 26.7% and 42.7%, respectively, compared with 56.9% and 76.3% with negative lncScores (hazard ratio, 2.48 and 3.16; P < .001). Pediatric validation cohorts and an adult AML group yielded comparable results in magnitude and significance. lncScore remained independently prognostic in multivariable models, including key factors used in preinduction and postinduction risk stratification. Subgroup analysis suggested that lncScores provide additional outcome information in heterogeneous subgroups currently classified as indeterminate risk. Concordance analysis showed that lncScore adds to overall classification accuracy with at least comparable predictive performance to current stratification methods that rely on multiple assays.

CONCLUSION

Inclusion of the lncScore enhances predictive power of traditional cytogenetic and mutation-defined stratification in pAML with potential, as a single assay, to replace these complex stratification schemes with comparable predictive accuracy.

Bcl11b sustains multipotency and restricts effector programs of intestinal-resident memory CD8+ T cells

The networks of transcription factors (TFs) that control intestinal-resident memory CD8⁺ T (T_RM) cells, including multipotency and effector programs, are poorly understood. In this work, we investigated the role of the TF Bcl11b in T_RM cells during infection with Listeria monocytogenes using mice with post-activation, conditional deletion of Bcl11b in CD8⁺ T cells. Conditional deletion of Bcl11b resulted in increased numbers of intestinal T_RM cells and their precursors as well as decreased splenic effector and circulating memory cells and precursors. Loss of circulating memory cells was in part due to increased intestinal homing of Bcl11b^-/- circulating precursors, with no major alterations in their programs. Bcl11b^-/- T_RM cells had altered transcriptional programs, with diminished expression of multipotent/multifunctional (MP/MF) program genes, including Tcf7, and up-regulation of the effector program genes, including Prdm1. Bcl11b also limits the expression of Ahr, another TF with a role in intestinal CD8⁺ T_RM cell differentiation. Deregulation of T_RM programs translated into a poor recall response despite T_RM cell accumulation in the intestine. Reduced expression of MP/MF program genes in Bcl11b^-/- T_RM cells was linked to decreased chromatin accessibility and a reduction in activating histone marks at these loci. In contrast, the effector program genes displayed increased activating epigenetic status. These findings demonstrate that Bcl11b is a frontrunner in the tissue residency program of intestinal memory cells upstream of Tcf1 and Blimp1, promoting multipotency and restricting the effector program.

Etiology of oncogenic fusions in 5,190 childhood cancers and its clinical and therapeutic implication

Oncogenic fusions formed through chromosomal rearrangements are hallmarks of childhood cancer that define cancer subtype, predict outcome, persist through treatment, and can be ideal therapeutic targets. However, mechanistic understanding of the etiology of oncogenic fusions remains elusive. Here we report a comprehensive detection of 272 oncogenic fusion gene pairs by using tumor transcriptome sequencing data from 5190 childhood cancer patients. We identify diverse factors, including translation frame, protein domain, splicing, and gene length, that shape the formation of oncogenic fusions. Our mathematical modeling reveals a strong link between differential selection pressure and clinical outcome in CBFB-MYH11. We discover 4 oncogenic fusions, including RUNX1-RUNX1T1, TCF3-PBX1, CBFA2T3-GLIS2, and KMT2A-AFDN, with promoter-hijacking-like features that may offer alternative strategies for therapeutic targeting. We uncover extensive alternative splicing in oncogenic fusions including KMT2A-MLLT3, KMT2A-MLLT10, C11orf95-RELA, NUP98-NSD1, KMT2A-AFDN and ETV6-RUNX1. We discover neo splice sites in 18 oncogenic fusion gene pairs and demonstrate that such splice sites confer therapeutic vulnerability for etiology-based genome editing. Our study reveals general principles on the etiology of oncogenic fusions in childhood cancer and suggests profound clinical implications including etiology-based risk stratification and genome-editing-based therapeutics.

Abstract 5704: An integrated immune signature predictive of adjuvant immunotherapeutic benefits for high-risk melanoma

Introduction CTLA4 blockade with ipilimumab was more favorable than interferon-α2b (IFN) in high-risk melanoma in phase adjuvant III trial E1609. Characterization of the pretreatment tumor immune biomarkers and clinical covariates may inform the likelihood of response to ipilimumab and other immune checkpoint inhibitors (ICI), and guide future development of this and other modalities in this patient population.

Methods We utilized PATH-SURVEIOR, a bioinformatics framework developed in-house for associating genes and pathway signatures with clinical endpoints, to perform survival analysis of gene expression levels of 31 candidate immune-related biomarkers based on previous preliminary data. We analyzed microarray gene expression data from 471 melanoma patients treated with ipilimumab (ipi) and 248 melanoma patients treated with IFN as part of E1609. We then developed a LASSO Cox regression model and validated our model in 22 patients treated with neoadjuvant ipi in a separate clinical trial.

Results Using PATH-SURVEIOR, we evaluated 31 candidate immune biomarkers and their association with patient outcome by including treatment group (ipi and IFN) as a multiplicative covariate interaction in the Cox hazard model. Our analysis identified CXCL9, CD8A, CXCL10, and INPP5D as Tier 1 biomarkers (HR &gt; 1 and P &lt; 0.05) and IDO1, IGKC, and IL2RB as Tier 2 biomarkers (HR &gt; 1 and P &lt; 0.1). Next, we developed an ipilimumab immune-based risk score using LASSO Cox regression (L-IPI7) based on these 7 aggregate biomarkers. We then split our 471 ipi-treated cohort into training (310, 66%) and testing (161, 33%) cohorts and assessed our model for its ability to predict overall survival (OS) and relapse-free survival (RFS). Our risk score was capable of stratifying ipi-treated patients into High-Risk and Low-Risk populations, which correlated with OS. As a negative control, we assessed our risk score in 248 IFN-treated patients and found no significant association with OS. As validation, we applied our L-IPI7 score to a cohort of 22 patients treated with neoadjuvant ipi and determined that the score was able to predict patients with a high risk of relapse. Interestingly, when we developed an interactive Cox-regression model with colitis status (grade 0-1 vs grade 2+), we found that neoadjuvant ipi patients with low-grade colitis were associated with a higher L-IPI7 risk score for disease relapse. In addition, we determined that: i) higher age and higher L-IPI7 risk score identified patients with the worst OS and RFS And ii) female patients with a low L-IPI7 risk scores had a better OS and RFS.

Conclusions We developed a broadly applicable model based on LASSO Cox Regression predictive of adjuvant ipi treatment outcomes in melanoma. Our L-IPI7 score based on expression of CXCL9, CD8A, CXCL10, INPP5D, IDO1, IGKC, IL2RB effectively predicts survival, with interactions with age, gender and on-treatment development of colitis.

Citation Format: Alyssa N. Obermayer, Timothy I. Shaw, Sandra J. Lee, F. Stephen Hodi, William A. LaFramboise, Walter Storkus, Arivarasan D. Karunamurthy, Patrick Hwu, Howard Streicher, Dung-Tsa Chen, John M. Kirkwood, Ahmad A. Tarhini. An integrated immune signature predictive of adjuvant immunotherapeutic benefits for high-risk melanoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5704.

The Genetic and Epigenetic Features of Bilateral Wilms Tumor Predisposition: A Report from the Children's Oncology Group AREN18B5-Q Study

This study comprehensively evaluated the landscape of genetic and epigenetic events that predispose to synchronous bilateral Wilms tumor (BWT). We performed whole exome or whole genome sequencing, total-strand RNA-seq, and DNA methylation analysis using germline and/or tumor samples from 68 patients with BWT from St. Jude Children's Research Hospital and the Children's Oncology Group. We found that 25/61 (41%) of patients evaluated harbored pathogenic or likely pathogenic germline variants, with WT1 (14.8%), NYNRIN (6.6%), TRIM28 (5%) and the BRCA-related genes (5%) BRCA1, BRCA2, and PALB2 being most common. Germline WT1 variants were strongly associated with somatic paternal uniparental disomy encompassing the 11p15.5 and 11p13/WT1 loci and subsequent acquired pathogenic CTNNB1 variants. Somatic coding variants or genome-wide copy number alterations were almost never shared between paired synchronous BWT, suggesting that the acquisition of independent somatic variants leads to tumor formation in the context of germline or early embryonic, post-zygotic initiating events. In contrast, 11p15.5 status (loss of heterozygosity, loss or retention of imprinting) was shared among paired synchronous BWT in all but one case. The predominant molecular events for BWT predisposition include pathogenic germline variants or post-zygotic epigenetic hypermethylation at the 11p15.5 H19/ICR1 locus (loss of imprinting). This study demonstrates that post-zygotic somatic mosaicism for 11p15.5 hypermethylation/loss of imprinting is the single most common initiating molecular event predisposing to BWT. Evidence of somatic mosaicism for 11p15.5 loss of imprinting was detected in leukocytes of a cohort of BWT patients and long-term survivors, but not in unilateral Wilms tumor patients and long-term survivors or controls, further supporting the hypothesis that post-zygotic 11p15.5 alterations occurred in the mesoderm of patients who go on to develop BWT. Due to the preponderance of BWT patients with demonstrable germline or early embryonic tumor predisposition, BWT exhibits a unique biology when compared to unilateral Wilms tumor and therefore warrants continued refinement of its own treatment-relevant biomarkers which in turn may inform directed treatment strategies in the future.

Malignant Progression of an Ancestral Bone Marrow Clone Harboring a CIC-NUTM2A Fusion in Isolated Myeloid Sarcoma

Myeloid sarcoma is a rare condition consisting of extramedullary myeloid blasts found in association with acute myeloid leukemia or, in the absence of bone marrow involvement. We identified an infant with isolated myeloid sarcoma whose bone marrow was negative for involvement by flow cytometry. Sequencing revealed the fusion oncogene CIC-NUTM2A and identified the sarcoma to be clonally evolved from the bone marrow, which carried the fusion despite the absence of pathology. Murine modeling confirmed the ability of the fusion to transform hematopoietic cells and identified receptor tyrosine kinase (RTK) signaling activation consistent with disruption of the CIC transcriptional repressor. These findings extend the definition of CIC-rearranged malignancies to include hematologic disease, provide insight into the mechanism of oncogenesis, and demonstrate the importance of molecular analysis and tracking of bone marrow involvement over the course of treatment in myeloid sarcoma, including patients that lack flow cytometric evidence of leukemia at diagnosis.

IMPLICATIONS

This study illustrates molecular involvement of phenotypically normal bone marrow in myeloid sarcoma, which has significant implications in clinical care. Further, it extends the definition of CIC-rearrangements to include hematologic malignancies and shows evidence of RTK activation that may be exploited therapeutically in cancer(s) driven by these fusions.

Multi-omics approach to identifying isoform variants as therapeutic targets in cancer patients

Cancer-specific alternatively spliced events (ASE) play a role in cancer pathogenesis and can be targeted by immunotherapy, oligonucleotide therapy, and small molecule inhibition. However, identifying actionable ASE targets remains challenging due to the uncertainty of its protein product, structure impact, and proteoform (protein isoform) function. Here we argue that an integrated multi-omics profiling strategy can overcome these challenges, allowing us to mine this untapped source of targets for therapeutic development. In this review, we will provide an overview of current multi-omics strategies in characterizing ASEs by utilizing the transcriptome, proteome, and state-of-art algorithms for protein structure prediction. We will discuss limitations and knowledge gaps associated with each technology and informatics analytics. Finally, we will discuss future directions that will enable the full integration of multi-omics data for ASE target discovery.

Ablation of the endoplasmic reticulum stress kinase PERK induces paraptosis and type I interferon to promote anti-tumor T cell responses

Activation of unfolded protein responses (UPRs) in cancer cells undergoing endoplasmic reticulum (ER) stress promotes survival. However, how UPR in tumor cells impacts anti-tumor immune responses remains poorly described. Here, we investigate the role of the UPR mediator pancreatic ER kinase (PKR)-like ER kinase (PERK) in cancer cells in the modulation of anti-tumor immunity. Deletion of PERK in cancer cells or pharmacological inhibition of PERK in melanoma-bearing mice incites robust activation of anti-tumor T cell immunity and attenuates tumor growth. PERK elimination in ER-stressed malignant cells triggers SEC61β-induced paraptosis, thereby promoting immunogenic cell death (ICD) and systemic anti-tumor responses. ICD induction in PERK-ablated tumors stimulates type I interferon production in dendritic cells (DCs), which primes CCR2-dependent tumor trafficking of common-monocytic precursors and their intra-tumor commitment into monocytic-lineage inflammatory Ly6C+CD103+ DCs. These findings identify how tumor cell-derived PERK promotes immune evasion and highlight the potential of PERK-targeting therapies in cancer immunotherapy.

Alzheimer's disease-associated U1 snRNP splicing dysfunction causes neuronal hyperexcitability and cognitive impairment

Recent proteome and transcriptome profiling of Alzheimer's disease (AD) brains reveals RNA splicing dysfunction and U1 small nuclear ribonucleoprotein (snRNP) pathology containing U1-70K and its N-terminal 40-KDa fragment (N40K). Here we present a causative role of U1 snRNP dysfunction to neurodegeneration in primary neurons and transgenic mice (N40K-Tg), in which N40K expression exerts a dominant-negative effect to downregulate full-length U1-70K. N40K-Tg recapitulates N40K insolubility, erroneous splicing events, neuronal degeneration and cognitive impairment. Specifically, N40K-Tg shows the reduction of GABAergic synapse components (e.g., the GABA receptor subunit of GABRA2), and concomitant postsynaptic hyperexcitability that is rescued by a GABA receptor agonist. Crossing of N40K-Tg and the 5xFAD amyloidosis model indicates that the RNA splicing defect synergizes with the amyloid cascade to remodel the brain transcriptome and proteome, deregulate synaptic proteins, and accelerate cognitive decline. Thus, our results support the contribution of U1 snRNP-mediated splicing dysfunction to AD pathogenesis.

Integrated stem cell signature and cytomolecular risk determination in pediatric acute myeloid leukemia

Relapsed or refractory pediatric acute myeloid leukemia (AML) is associated with poor outcomes and relapse risk prediction approaches have not changed significantly in decades. To build a robust transcriptional risk prediction model for pediatric AML, we perform RNA-sequencing on 1503 primary diagnostic samples. While a 17 gene leukemia stem cell signature (LSC17) is predictive in our aggregated pediatric study population, LSC17 is no longer predictive within established cytogenetic and molecular (cytomolecular) risk groups. Therefore, we identify distinct LSC signatures on the basis of AML cytomolecular subtypes (LSC47) that were more predictive than LSC17. Based on these findings, we build a robust relapse prediction model within a training cohort and then validate it within independent cohorts. Here, we show that LSC47 increases the predictive power of conventional risk stratification and that applying biomarkers in a manner that is informed by cytomolecular profiling outperforms a uniform biomarker approach.

Relapsed pediatric acute myeloid leukemia is associated with poor prognosis. Here, the authors use RNA-seq data from 1503 primary samples to create a combined transcriptional and cytomolecular signature to improve relapse risk prediction.

Tumor Expression Quantitative Trait Methylation Screening Reveals Distinct CpG Panels for Deconvolving Cancer Immune Signatures

DNA methylation signatures in tumors could serve as reliable biomarkers that are accessible in archival tissues for tracking the epigenetic dynamics shaped by both cancer cells and the tumor microenvironment. However, given the ultrahigh dimensionality and noncollapsible nature of the data, it remains challenging to screen all CpG sites to identify the most promising marker panels. In this article, we introduce the concept of tumor-based expression quantitative trait methylation (eQTM) for the prioritization and systematic mining of predictive biomarkers. In melanoma as a disease model, eQTM CpGs and genes represent new and efficient candidate targets to be investigated for both prognostic and immune status monitoring purposes. Three cis-eQTM CpGs (cg07786657, cg12446199, and cg00027570) were strongly associated with and can serve as surrogate biomarkers for the tumor immune cytolytic activity score (CYT). In addition, multiple eQTM genes could be further exploited for predicting immunoregulatory phenotypes. A targeted gene panel analysis identified one eQTM in TCF7 (cg25947408) as a novel candidate biomarker for uncoupling overall T-cell differentiation and exhaustion status in a tumor. The prognostic significance of this eQTM as an independent signature to CYT was validated by both The Cancer Genome Atlas and Moffitt melanoma cohort data. Overall, eQTMs represent a mechanistically distinct class of potential biomarkers that can be used to predict patient prognosis and immune status.

SIGNIFICANCE

This study provides a novel and promising approach to identify targeted epigenetic biomarkers in cancer and will spur further analysis in tumor immune phenotyping.

DRPPM-EASY: A Web-Based Framework for Integrative Analysis of Multi-Omics Cancer Datasets

High-throughput transcriptomic and proteomic analyses are now routinely applied to study cancer biology. However, complex omics integration remains challenging and often time-consuming. Here, we developed DRPPM-EASY, an R Shiny framework for integrative multi-omics analysis. We applied our application to analyze RNA-seq data generated from a USP7 knockdown in T-cell acute lymphoblastic leukemia (T-ALL) cell line, which identified upregulated expression of a TAL1-associated proliferative signature in T-cell acute lymphoblastic leukemia cell lines. Next, we performed proteomic profiling of the USP7 knockdown samples. Through DRPPM-EASY-Integration, we performed a concurrent analysis of the transcriptome and proteome and identified consistent disruption of the protein degradation machinery and spliceosome in samples with USP7 silencing. To further illustrate the utility of the R Shiny framework, we developed DRPPM-EASY-CCLE, a Shiny extension preloaded with the Cancer Cell Line Encyclopedia (CCLE) data. The DRPPM-EASY-CCLE app facilitates the sample querying and phenotype assignment by incorporating meta information, such as genetic mutation, metastasis status, sex, and collection site. As proof of concept, we verified the expression of TP53 associated DNA damage signature in TP53 mutated ovary cancer cells. Altogether, our open-source application provides an easy-to-use framework for omics exploration and discovery.

OUP accepted manuscript

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.

Chromatin architecture at susceptible gene loci in cerebellar Purkinje cells characterizes DNA damage-induced neurodegeneration

The pathogenesis of inherited genome instability neurodegenerative syndromes remains largely unknown. Here, we report new disease-relevant murine models of genome instability–driven neurodegeneration involving disabled ATM and APTX that develop debilitating ataxia. We show that neurodegeneration and ataxia result from transcriptional interference in the cerebellum via aberrant messenger RNA splicing. Unexpectedly, these splicing defects were restricted to only Purkinje cells, disrupting the expression of critical homeostatic regulators including ITPR1, GRID2, and CA8. Abundant genotoxic R loops were also found at these Purkinje cell gene loci, further exacerbating DNA damage and transcriptional disruption. Using ATAC-seq to profile global chromatin accessibility in the cerebellum, we found a notably unique chromatin conformation specifically in Purkinje chromatin at the affected gene loci, thereby promoting susceptibility to DNA damage. These data reveal the pathogenic basis of DNA damage in the nervous system and suggest chromatin conformation as a feature in directing genome instability–associated neuropathology.

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

With recent advances in mass spectrometry-based proteomics technologies, deep profiling of hundreds of proteomes has become increasingly feasible. However, deriving biological insights from such valuable datasets is challenging. Here we introduce a systems biology-based software JUMPn, and its associated protocol to organize the proteome into protein co-expression clusters across samples and protein-protein interaction (PPI) networks connected by modules (e.g., protein complexes). Using the R/Shiny platform, the JUMPn software streamlines the analysis of co-expression clustering, pathway enrichment, and PPI module detection, with integrated data visualization and a user-friendly interface. The main steps of the protocol include installation of the JUMPn software, the definition of differentially expressed proteins or the (dys)regulated proteome, determination of meaningful co-expression clusters and PPI modules, and result visualization. While the protocol is demonstrated using an isobaric labeling-based proteome profile, JUMPn is generally applicable to a wide range of quantitative datasets (e.g., label-free proteomics). The JUMPn software and protocol thus provide a powerful tool to facilitate biological interpretation in quantitative proteomics.

Genome instability independent of type I interferon signaling drives neuropathology caused by impaired ribonucleotide excision repair

Aicardi-Goutières syndrome (AGS) is a monogenic type I interferonopathy characterized by neurodevelopmental defects and upregulation of type I interferon signaling and neuroinflammation. Mutations in genes that function in nucleic acid metabolism, including RNASEH2, are linked to AGS. Ribonuclease H2 (RNASEH2) is a genome surveillance factor critical for DNA integrity by removing ribonucleotides incorporated into replicating DNA. Here we show that RNASEH2 is necessary for neurogenesis and to avoid activation of interferon-responsive genes and neuroinflammation. Cerebellar defects after RNASEH2B inactivation are rescued by p53 but not cGAS deletion, suggesting that DNA damage signaling, not neuroinflammation, accounts for neuropathology. Coincident inactivation of Atm and Rnaseh2 further affected cerebellar development causing ataxia, which was dependent upon aberrant activation of non-homologous end-joining (NHEJ). The loss of ATM also markedly exacerbates cGAS-dependent type I interferon signaling. Thus, DNA damage-dependent signaling rather than type I interferon signaling underlies neurodegeneration in this class of neurodevelopmental/neuroinflammatory disease.

Metabolomic and transcriptomic analysis reveals endogenous substrates and metabolic adaptation in rats lacking Abcg2 and Abcb1a transporters

Abcg2/Bcrp and Abcb1a/Pgp are xenobiotic efflux transporters limiting substrate permeability in the gastrointestinal system and brain, and increasing renal and hepatic drug clearance. The systemic impact of Bcrp and Pgp ablation on metabolic homeostasis of endogenous substrates is incompletely understood. We performed untargeted metabolomics of cerebrospinal fluid (CSF) and plasma, transcriptomics of brain, liver and kidney from male Sprague Dawley rats (WT) and Bcrp/Pgp double knock-out (dKO) rats, and integrated metabolomic/transcriptomic analysis to identify putative substrates and perturbations in canonical metabolic pathways. A predictive Bayesian machine learning model was used to predict in silico those metabolites with greater substrate-like features for either transporters. The CSF and plasma levels of 169 metabolites, nutrients, signaling molecules, antioxidants and lipids were significantly altered in dKO rats, compared to WT rats. These metabolite changes suggested alterations in histidine, branched chain amino acid, purine and pyrimidine metabolism in the dKO rats. Levels of methylated and sulfated metabolites and some primary bile acids were increased in dKO CSF or plasma. Elevated uric acid levels appeared to be a primary driver of changes in purine and pyrimidine biosynthesis. Alterations in Bcrp/Pgp dKO CSF levels of antioxidants, precursors of neurotransmitters, and uric acid suggests the transporters may contribute to the regulation of a healthy central nervous system in rats. Microbiome-generated metabolites were found to be elevated in dKO rat plasma and CSF. The altered dKO metabolome appeared to cause compensatory transcriptional change in urate biosynthesis and response to lipopolysaccharide in brain, oxidation-reduction processes and response to oxidative stress and porphyrin biosynthesis in kidney, and circadian rhythm genes in liver. These findings present insight into endogenous functions of Bcrp and Pgp, the impact that transporter substrates, inhibitors or polymorphisms may have on metabolism, how transporter inhibition could rewire drug sensitivity indirectly through metabolic changes, and identify functional Bcrp biomarkers.

Abstract 1543: Mining cancer-specific isoforms as CAR T-cell therapy targets for pediatric solid and brain tumors

Immunotherapy with T-cells expressing chimeric antigen receptors (CARs) holds the promise to improve outcomes for children with solid and brain tumors. However, at present, there is a limited array of targetable antigens. We posit here that targets generated by alternative splicing events (ASEs) in cancer cells present an untapped class of CAR targets since many of these are tumor-specific and overexpressed in malignant cells. Thus, we developed Cancer-Specific Isoform Miner (CSI-Miner), a pipeline to perform a comprehensive ASE analysis of pediatric cancers to discover CSIs as CAR T-cell therapy targets. We analyzed 1,938 solid and brain tumor samples collected from PCGP, TARGET, and St. Jude's real-time clinical sequencing data sets. In addition, 7,527 GTEx RNAseq samples across 31 human tissues were harmonized to prioritize exon candidates with minimal expression in normal tissue. Through CSI-Miner, we identified 40,748 highly expressed exons from the tumor's surfaceome and secretome, of which 185 were unannotated novel exons. Taking advantage of available mass-spectrometry proteome data from the Clinical Proteomic Tumor Analysis Consortium and St. Jude's proteomics facility, we validated the presence of peptides encoded by these novel exons for rhabdomyosarcoma, medulloblastoma, high-grade glioma, low-grade glioma, and ependymoma. Moreover, non-malignant mass-spectrometry data from muscle and brain samples were incorporated as negative controls. Several secretome targets were identified that adhered to the surface of cancer cells, including EDB, an oncofetal splice variant of fibronectin. EDB was expressed in a broad range of pediatric solid and brain tumors, including Ewing sarcoma and high-grade glioma. We generated T-cells expressing a 2nd generation EDB-CAR (EDB-CAR T-cells) by standard retroviral transduction. EDB-CAR T-cells recognized and killed EDB+ cancer cells in vitro and had potent antitumor activity in xenograft models, resulting in improved overall survival compared to control mice. Importantly, EDB-CAR T-cells did not induce ‘on target/off cancer' toxicities in mice, which is encouraging since EDB is identical in mice and humans. c-MET was also identified as a candidate surfaceome CAR target for rhabdomyosarcoma and melanoma. In summary, we developed CSI-Miner, an integrative analysis pipeline to discover CSIs as CAR T-cell therapy targets, comprised of 248 surfaceome and 51 secretome candidates, for pediatric solid and brain tumors. At present we have validated these CSIs by mass-spectrometry and successfully generated CAR T-cells for one of the candidates. Collectively, CSIs present an untapped class of immunotherapy targets that hold the promise to improve current CAR T-cell therapy approaches for a wide range of pediatric solid and brain tumors. A web portal has been developed supporting access and visualization of this data set to the research community.

Citation Format: Timothy I. Shaw, Jessica Wagner, Elizabeth Wickman, Liqing Tian, Dong Li, Suresh Poudel, Elizabeth Stewart, Yuxin Li, Hong Wang, Mingming Niu, Robin Paul, Colleen Reilly, Xin Zhou, Michael Dyer, Suzanne Baker, Junmin Peng, Jiyang Yu, Paulina Velasquez, Chris DeRenzo, Giedre Krenciute, Jinghui Zhang, Stephen Gottschalk. Mining cancer-specific isoforms as CAR T-cell therapy targets for pediatric solid and brain tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1543.

Cell-surface antigen profiling of pediatric brain tumors: B7-H3 is consistently expressed and can be targeted via local or systemic CAR T-cell delivery

BACKGROUND

Immunotherapy with chimeric antigen receptor (CAR) T cells is actively being explored for pediatric brain tumors in preclinical models and early phase clinical studies. At present, it is unclear which CAR target antigens are consistently expressed across different pediatric brain tumor types. In addition, the extent of HLA class I expression is unknown, which is critical for tumor recognition by conventional αβTCR T cells.

METHODS

We profiled 49 low- and high-grade pediatric brain tumor patient-derived orthotopic xenografts (PDOX) by flow analysis for the expression of 5 CAR targets (B7-H3, GD2, IL-13Rα2, EphA2, and HER2), and HLA class I. In addition, we generated B7-H3-CAR T cells and evaluated their antitumor activity in vitro and in vivo.

RESULTS

We established an expression hierarchy for the analyzed antigens (B7-H3 = GD2 >> IL-13Rα2 > HER2 = EphA2) and demonstrated that antigen expression is heterogenous. All high-grade gliomas expressed HLA class I, but only 57.1% of other tumor subtypes had detectable expression. We then selected B7-H3 as a target for CAR T-cell therapy. B7-H3-CAR T cells recognized tumor cells in an antigen-dependent fashion. Local or systemic administration of B7-H3-CAR T cells induced tumor regression in PDOX and immunocompetent murine glioma models resulting in a significant survival advantage.

CONCLUSIONS

Our study highlights the importance of studying target antigen and HLA class I expression in PDOX samples for the future design of immunotherapies. In addition, our results support active preclinical and clinical exploration of B7-H3-targeted CAR T-cell therapies for a broad spectrum of pediatric brain tumors.

Integrative network analysis reveals USP7 haploinsufficiency inhibits E-protein activity in pediatric T-lineage acute lymphoblastic leukemia (T-ALL)

USP7, which encodes a deubiquitylating enzyme, is among the most frequently mutated genes in pediatric T-ALL, with somatic heterozygous loss-of-function mutations (haploinsufficiency) predominantly affecting the subgroup that has aberrant TAL1 oncogene activation. Network analysis of > 200 T-ALL transcriptomes linked USP7 haploinsufficiency with decreased activities of E-proteins. E-proteins are also negatively regulated by TAL1, leading to concerted down-regulation of E-protein target genes involved in T-cell development. In T-ALL cell lines, we showed the physical interaction of USP7 with E-proteins and TAL1 by mass spectrometry and ChIP-seq. Haploinsufficient but not complete CRISPR knock-out of USP7 showed accelerated cell growth and validated transcriptional down-regulation of E-protein targets. Our study unveiled the synergistic effect of USP7 haploinsufficiency with aberrant TAL1 activation on T-ALL, implicating USP7 as a haploinsufficient tumor suppressor in T-ALL. Our findings caution against a universal oncogene designation for USP7 while emphasizing the dosage-dependent consequences of USP7 inhibitors currently under development as potential cancer therapeutics.

Toxicoproteomic Profiling of hPXR Transgenic Mice Treated with Rifampicin and Isoniazid

Tuberculosis is a global health threat that affects millions of people every year, and treatment-limiting toxicity remains a considerable source of treatment failure. Recent reports have characterized the nature of hPXR-mediated hepatotoxicity and the systemic toxicity of antitubercular drugs. The antitubercular drug isoniazid plays a role in such pathologic states as acute intermittent porphyria, anemia, hepatotoxicity, hypercoagulable states (deep vein thrombosis, pulmonary embolism, or ischemic stroke), pellagra (vitamin B₃ deficiency), peripheral neuropathy, and vitamin B₆ deficiency. However, the mechanisms by which isoniazid administration leads to these states are unclear. To elucidate the mechanism of rifampicin- and isoniazid-induced liver and systemic injury, we performed tandem mass tag mass spectrometry-based proteomic screening of mPxr^-/- and hPXR mice treated with combinations of rifampicin and isoniazid. Proteomic profiling analysis suggested that the hPXR liver proteome is affected by antitubercular therapy to disrupt [Fe-S] cluster assembly machinery, [2Fe-2S] cluster-containing proteins, cytochrome P450 enzymes, heme biosynthesis, homocysteine catabolism, oxidative stress responses, vitamin B₃ metabolism, and vitamin B₆ metabolism. These novel findings provide insight into the etiology of some of these processes and potential targets for subsequent investigations. Data are available via ProteomeXchange with identifier PXD019505.

JUMPm: A Tool for Large-Scale Identification of Metabolites in Untargeted Metabolomics

Metabolomics is increasingly important for biomedical research, but large-scale metabolite identification in untargeted metabolomics is still challenging. Here, we present Jumbo Mass spectrometry-based Program of Metabolomics (JUMPm) software, a streamlined software tool for identifying potential metabolite formulas and structures in mass spectrometry. During database search, the false discovery rate is evaluated by a target-decoy strategy, where the decoys are produced by breaking the octet rule of chemistry. We illustrated the utility of JUMPm by detecting metabolite formulas and structures from liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) analyses of unlabeled and stable-isotope labeled yeast samples. We also benchmarked the performance of JUMPm by analyzing a mixed sample from a commercially available metabolite library in both hydrophilic and hydrophobic LC-MS/MS. These analyses confirm that metabolite identification can be significantly improved by estimating the element composition in formulas using stable isotope labeling, or by introducing LC retention time during a spectral library search, which are incorporated into JUMPm functions. Finally, we compared the performance of JUMPm and two commonly used programs, Compound Discoverer 3.1 and MZmine 2, with respect to putative metabolite identifications. Our results indicate that JUMPm is an effective tool for metabolite identification of both unlabeled and labeled data in untargeted metabolomics.

Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer's Disease Progression

Alzheimer's disease (AD) displays a long asymptomatic stage before dementia. We characterize AD stage-associated molecular networks by profiling 14,513 proteins and 34,173 phosphosites in the human brain with mass spectrometry, highlighting 173 protein changes in 17 pathways. The altered proteins are validated in two independent cohorts, showing partial RNA dependency. Comparisons of brain tissue and cerebrospinal fluid proteomes reveal biomarker candidates. Combining with 5xFAD mouse analysis, we determine 15 Aβ-correlated proteins (e.g., MDK, NTN1, SMOC1, SLIT2, and HTRA1). 5xFAD shows a proteomic signature similar to symptomatic AD but exhibits activation of autophagy and interferon response and lacks human-specific deleterious events, such as downregulation of neurotrophic factors and synaptic proteins. Multi-omics integration prioritizes AD-related molecules and pathways, including amyloid cascade, inflammation, complement, WNT signaling, TGF-β and BMP signaling, lipid metabolism, iron homeostasis, and membrane transport. Some Aβ-correlated proteins are colocalized with amyloid plaques. Thus, the multilayer omics approach identifies protein networks during AD progression.

Adapterama II: universal amplicon sequencing on Illumina platforms (TaggiMatrix)

Next-generation sequencing (NGS) of amplicons is used in a wide variety of contexts. In many cases, NGS amplicon sequencing remains overly expensive and inflexible, with library preparation strategies relying upon the fusion of locus-specific primers to full-length adapter sequences with a single identifying sequence or ligating adapters onto PCR products. In Adapterama I, we presented universal stubs and primers to produce thousands of unique index combinations and a modifiable system for incorporating them into Illumina libraries. Here, we describe multiple ways to use the Adapterama system and other approaches for amplicon sequencing on Illumina instruments. In the variant we use most frequently for large-scale projects, we fuse partial adapter sequences (TruSeq or Nextera) onto the 5' end of locus-specific PCR primers with variable-length tag sequences between the adapter and locus-specific sequences. These fusion primers can be used combinatorially to amplify samples within a 96-well plate (8 forward primers + 12 reverse primers yield 8 × 12 = 96 combinations), and the resulting amplicons can be pooled. The initial PCR products then serve as template for a second round of PCR with dual-indexed iTru or iNext primers (also used combinatorially) to make full-length libraries. The resulting quadruple-indexed amplicons have diversity at most base positions and can be pooled with any standard Illumina library for sequencing. The number of sequencing reads from the amplicon pools can be adjusted, facilitating deep sequencing when required or reducing sequencing costs per sample to an economically trivial amount when deep coverage is not needed. We demonstrate the utility and versatility of our approaches with results from six projects using different implementations of our protocols. Thus, we show that these methods facilitate amplicon library construction for Illumina instruments at reduced cost with increased flexibility. A simple web page to design fusion primers compatible with iTru primers is available at: http://baddna.uga.edu/tools-taggi.html. A fast and easy to use program to demultiplex amplicon pools with internal indexes is available at: https://github.com/lefeverde/Mr_Demuxy.

Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes

High throughput omics approaches provide an unprecedented opportunity for dissecting molecular mechanisms in cancer biology. Here we present deep profiling of whole proteome, phosphoproteome and transcriptome in two high-grade glioma (HGG) mouse models driven by mutated RTK oncogenes, PDGFRA and NTRK1, analyzing 13,860 proteins and 30,431 phosphosites by mass spectrometry. Systems biology approaches identify numerous master regulators, including 41 kinases and 23 transcription factors. Pathway activity computation and mouse survival indicate the NTRK1 mutation induces a higher activation of AKT downstream targets including MYC and JUN, drives a positive feedback loop to up-regulate multiple other RTKs, and confers higher oncogenic potency than the PDGFRA mutation. A mini-gRNA library CRISPR-Cas9 validation screening shows 56% of tested master regulators are important for the viability of NTRK-driven HGG cells, including TFs (Myc and Jun) and metabolic kinases (AMPKa1 and AMPKa2), confirming the validity of the multiomics integrative approaches, and providing novel tumor vulnerabilities.

A Key Role for the Ubiquitin Ligase UBR4 in Myofiber Hypertrophy in Drosophila and Mice

Skeletal muscle cell (myofiber) atrophy is a detrimental component of aging and cancer that primarily results from muscle protein degradation via the proteasome and ubiquitin ligases. Transcriptional upregulation of some ubiquitin ligases contributes to myofiber atrophy, but little is known about the role that most other ubiquitin ligases play in this process. To address this question, we have used RNAi screening in Drosophila to identify the function of > 320 evolutionarily conserved ubiquitin ligases in myofiber size regulation in vivo. We find that whereas RNAi for some ubiquitin ligases induces myofiber atrophy, loss of others (including the N-end rule ubiquitin ligase UBR4) promotes hypertrophy. In Drosophila and mouse myofibers, loss of UBR4 induces hypertrophy via decreased ubiquitination and degradation of a core set of target proteins, including the HAT1/RBBP4/RBBP7 histone-binding complex. Together, this study defines the repertoire of ubiquitin ligases that regulate myofiber size and the role of UBR4 in myofiber hypertrophy.

Abstract 3652: USP7 heterozygous loss-of-function affects T-cell differentiation in pediatric T-ALL

Ubiquitin-specific-processing protease 7 (USP7), a protein deubiquitinase, is one of the most frequently mutated genes (33%) in the TAL1 subtype of pediatric T-lineage acute lymphoblastic leukemia (T-ALL). However, the functional effect of USP7 haploinsufficiency on T-ALL pathogenesis remains elusive. To understand USP7 haploinsufficiency’s impact on T-ALL, we performed gene expression analysis on 42 non-early T-cell precursor T-ALL RNAseq samples downloaded from phs000218. The gene expression analysis suggested that USP7 haploinsufficiency (USP7-mut N = 12; USP7-wt N = 30) down-regulated the expression of T-cell maturation markers (e.g. RAG1, RAG2, and CD1B), which were negatively regulated by TAL1 [1]. RNAseq on a T-ALL cell line with USP7 knocked down by shRNA also found the same TAL1 negatively regulated gene set, further supporting an increase of TAL1 activity in the USP7 mutated T-ALLs. To examine whether the T-cell maturation was affected by USP7 heterozygous knockout, we generated a conditional knockout (cKO) mouse model by cross-breeding the transgenic vav1-cre mice with the USP7fl/fl mice to obtain heterozygous USP7fl/wt-vav1-cre. Thymocytes isolated from cKO mice were co-cultured with the OP9-Δ1 cells in the medium supplied with cytokines. The cell surface differentiation markers, CD4 and CD8 were stained for flow cytometry detection, and we observed an increase of double-negative cells and a decrease of double-positive cells in USP7-het-KO mice versus control (N = 4 in each group; p-value &lt; 0.05), consolidating the disrupted T-cell development ex vivo. To further understand USP7’s mechanism to regulate TAL1, we analyzed proteins that interacted with USP7 by affinity purification-mass spectrometry (AP-MS) and immune-precipitated followed by western-blotting (IP/WB). AP-MS with the anti-USP7 antibody revealed that USP7 directly interacts with TAL1 in Jurkat cells; AP-MS with the anti-TAL1 antibody also reciprocated the USP7-TAL1 interactions. Whole proteome analysis, through tandem-mass-tag and two-dimensional liquid chromatography-tandem mass spectrometry, revealed that USP7 knockdown down-regulated TRIM27, a deubiquitin target of USP7. IP/WB further confirmed the interaction between USP7, TRIM27, and TAL1, suggesting a possible synergistic relationship between USP7 and TRIM27 to regulate TAL1. In conclusion, our finding demonstrates heterozygous loss of function of USP7 dysregulates T-cell maturation by enhancing TAL1 activity. Future work on TRIM27 could further shed light on the mechanism underlying USP7’s ability to regulate TAL1. Reference: [1] Sanda et al. Cancer Cell 22, 209 (2012).

Citation Format: Timothy I. Shaw, Li Dong, Anthony High, Yu Liu, Bensheng Ju, Kanisha Kavdia, Vishwajeeth Pagala, Bridget Shaner, John Easton, Chenxi Qian, Jiyang Yu, Janke Janke, John Kim Choi, Junmin Peng, Wei Gu, James R. Downing, Jinghui Zhang. USP7 heterozygous loss-of-function affects T-cell differentiation in pediatric T-ALL [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3652.

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.

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.

Histone H3.3 K27M Accelerates Spontaneous Brainstem Glioma and Drives Restricted Changes in Bivalent Gene Expression

Diffuse intrinsic pontine gliomas (DIPGs) are incurable childhood brainstem tumors with frequent histone H3 K27M mutations and recurrent alterations in PDGFRA and TP53. We generated genetically engineered inducible mice and showed that H3.3 K27M enhanced neural stem cell self-renewal while preserving regional identity. Neonatal induction of H3.3 K27M cooperated with activating platelet-derived growth factor receptor α (PDGFRα) mutant and Trp53 loss to accelerate development of diffuse brainstem gliomas that recapitulated human DIPG gene expression signatures and showed global changes in H3K27 posttranslational modifications, but relatively restricted gene expression changes. Genes upregulated in H3.3 K27M tumors were enriched for those associated with neural development where H3K27me3 loss released the poised state of apparently bivalent promoters, whereas downregulated genes were enriched for those encoding homeodomain transcription factors.

Identification of Therapeutic Targets in Rhabdomyosarcoma through Integrated Genomic, Epigenomic, and Proteomic Analyses

Personalized cancer therapy targeting somatic mutations in patient tumors is increasingly being incorporated into practice. Other therapeutic vulnerabilities resulting from changes in gene expression due to tumor specific epigenetic perturbations are progressively being recognized. These genomic and epigenomic changes are ultimately manifest in the tumor proteome and phosphoproteome. We integrated transcriptomic, epigenomic, and proteomic/phosphoproteomic data to elucidate the cellular origins and therapeutic vulnerabilities of rhabdomyosarcoma (RMS). We discovered that alveolar RMS occurs further along the developmental program than embryonal RMS. We also identified deregulation of the RAS/MEK/ERK/CDK4/6, G₂/M, and unfolded protein response pathways through our integrated analysis. Comprehensive preclinical testing revealed that targeting the WEE1 kinase in the G₂/M pathway is the most effective approach in vivo for high-risk RMS.

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.

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.

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.

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.

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.

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.

Rapid Microbiome Changes in Freshly Deposited Cow Feces under Field Conditions

Although development of next generation sequencing (NGS) has substantially improved our understanding of the microbial ecology of animal feces, previous studies have mostly focused on freshly excreted feces. There is still limited understanding of the aging process dynamics of fecal microbiomes in intact cowpats exposed to natural environments. Fresh cowpats were sampled at multiple time points for 57 days under field conditions; half the samples were exposed to sunlight (unshaded) while the other half was protected from sunlight (shaded). The 16SRNA hypervariable region 4 was amplified from each sample and sequenced on an Illumina MiSeq Platform. While Clostridia, Bacteroidia, and Sphingobacteria were dominant classes of bacteria in fresh cowpats, Alphaproteobacteria, Betaproteobacteria, Actinobacteria, and Bacilli were the dominant classes by the end of the study, indicating a general shift from anaerobic to aerobic bacterial populations. This change was most likely influenced by the shift from cattle gut (anaerobic) to pasture ground (aerobic). Reduced moisture in cowpats may also contribute to the community shift since air can penetrate the dryer cowpat more easily. Twelve genera consisting pathogenic bacteria were detected, with Mycobacterium, Bacillus, and Clostridium being the most abundant; their combined abundance accounts for 90% of the total pathogenic genera. Taxonomic richness and diversity increased throughout the study for most samples, which could be due to bacteria regrowth and colonization of bacteria from the environment. In contrast to the high taxonomic diversity, the changes of PICRUSt inferred function profile were minimal for all cowpats throughout the study, which suggest that core functions predicted by PICRUSt may be too conserved to distinguish differences between aerobe and anaerobe. To the best of our knowledge, this is the first study demonstrating that cowpat exposure to air and sunlight can cause drastic microbiome changes soon after deposition in natural environments. Our findings offer important insights for future research characterizing the microbiome of feces collected in natural environments and the impact of cattle fecal contamination on water resources.

Assemblathon 2: evaluating de novo methods of genome assembly in three vertebrate species

BACKGROUND

The process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly.

RESULTS

In Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies.

CONCLUSIONS

Many current genome assemblers produced useful assemblies, containing a significant representation of their genes and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another.

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/.