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Supplementary tables S1 to S5

Supplementary Figures S1 to S16

Supplemental Figures including additional Kaplan-Meier plots, heatmaps of surface antigen expression and gene expression, and miRNA correlations.

Purpose:A cryptic inv(16)(p13.3q24.3) encoding the CBFA2T3–GLIS2 fusion is associated with poor outcome in infants with acute megakaryocytic leukemia. We aimed to broaden our understanding of the pathogenesis of this fusion through transcriptome profiling.Experimental Design:Available RNA from children and young adults with de novo acute myeloid leukemia (AML; N = 1,049) underwent transcriptome sequencing (mRNA and miRNA). Transcriptome profiles for those with the CBFA2T3–GLIS2 fusion (N = 24) and without (N = 1,025) were contrasted to define fusion-specific miRNAs, genes, and pathways. Clinical annotations defined distinct fusion-associated disease characteristics and outcomes.Results:The CBFA2T3–GLIS2 fusion was restricted to infants P < 0.001), and the presence of this fusion was highly associated with adverse outcome (P < 0.001) across all morphologic classifications. Further, there was a striking paucity of recurrent cooperating mutations, and transduction of cord blood stem cells with this fusion was sufficient for malignant transformation. CBFA2T3–GLIS2 positive cases displayed marked upregulation of genes with cell membrane/extracellular matrix localization potential, including NCAM1 and GABRE. Additionally, miRNA profiling revealed significant overexpression of mature miR-224 and miR-452, which are intronic miRNAs transcribed from the GABRE locus. Gene-set enrichment identified dysregulated Hippo, TGFβ, and hedgehog signaling, as well as NCAM1 (CD56) interaction pathways. Therapeutic targeting of fusion-positive leukemic cells with CD56-directed antibody–drug conjugate caused significant cytotoxicity in leukemic blasts.Conclusions:The CBFA2T3–GLIS2 fusion defines a highly refractory entity limited to infants that appears to be sufficient for malignant transformation. Transcriptome profiling elucidated several highly targetable genes and pathways, including the identification of CD56, providing a highly plausible target for therapeutic intervention.

Supplemental methods that provides additional detail on statistical methods and laboratory protocols and reagents.

Supplemental tables including clinical characteristics and differentially expressed gene lists.

Temporally regulated alternative splicing choices are vital for proper development, yet the wrong splice choice may be detrimental. Here, we highlight a previously unidentified role for the neurotrophin receptor splice variant TrkB.T1 in neurodevelopment, embryogenesis, transformation, and oncogenesis across multiple tumor types in humans and mice. TrkB.T1 is the predominantNTRK2isoform across embryonic organogenesis, and forced overexpression of this embryonic pattern causes multiple solid and nonsolid tumors in mice in the context of tumor suppressor loss. TrkB.T1 also emerges as the predominantNTRKisoform expressed in a wide range of adult and pediatric tumors, including those harboring tropomyosin receptor kinase fusions. Affinity purification–mass spectrometry proteomic analysis reveals distinct interactors with known developmental and oncogenic signaling pathways such as Wnt, transforming growth factor–β, Sonic Hedgehog, and Ras. From alterations in splicing factors to changes in gene expression, the discovery of isoform specific oncogenes with embryonic ancestry has the potential to shape the way we think about developmental systems and oncology.

RNA-sequencing data is widely used to identify disease biomarkers and therapeutic targets using numerical methods such as clustering, classification, regression, and differential expression analysis. Such approaches rely on the assumption that mRNA abundance estimates from RNA-seq are reliable estimates of true expression levels. Here, using data from five RNA-seq processing pipelines applied to 6,690 human tumor and normal tissues, we show that nearly 88% of protein-coding genes have similar gene expression profiles across all pipelines. However, for >12% of protein-coding genes, current best-in-class RNA-seq processing pipelines differ in their abundance estimates by more than four-fold when applied to exactly the same samples and the same set of RNA-seq reads. Expression fold changes are similarly affected. Many of the impacted genes are widely studied disease-associated genes. We show that impacted genes exhibit diverse patterns of discordance among pipelines, suggesting that many inter-pipeline differences contribute to overall uncertainty in mRNA abundance estimates. A concerted, community-wide effort will be needed to develop gold-standards for estimating the mRNA abundance of the discordant genes reported here. In the meantime, our list of discordantly evaluated genes provides an important resource for robust marker discovery and target selection.

Purpose: A cryptic inv(16)(p13.3q24.3) encoding the CBFA2T3–GLIS2 fusion is associated with poor outcome in infants with acute megakaryocytic leukemia. We aimed to broaden our understanding of the pathogenesis of this fusion through transcriptome profiling. Experimental Design: Available RNA from children and young adults with de novo acute myeloid leukemia (AML; N = 1,049) underwent transcriptome sequencing (mRNA and miRNA). Transcriptome profiles for those with the CBFA2T3–GLIS2 fusion (N = 24) and without (N = 1,025) were contrasted to define fusion-specific miRNAs, genes, and pathways. Clinical annotations defined distinct fusion-associated disease characteristics and outcomes. Results: The CBFA2T3–GLIS2 fusion was restricted to infants Conclusions: The CBFA2T3–GLIS2 fusion defines a highly refractory entity limited to infants that appears to be sufficient for malignant transformation. Transcriptome profiling elucidated several highly targetable genes and pathways, including the identification of CD56, providing a highly plausible target for therapeutic intervention.

Summary Multi-omic profiling of human peripheral blood is increasingly utilized to identify biomarkers and pathophysiologic mechanisms of disease. The importance of these platforms in clinical and translational studies led us to investigate the impact of delayed blood processing on the numbers and state of peripheral blood mononuclear cells (PBMC) and on the plasma proteome. Similar to previous studies, we show minimal effects of delayed processing on the numbers and general phenotype of PBMC up to 18 hours. In contrast, profound changes in the single-cell transcriptome and composition of the plasma proteome become evident as early as 6 hours after blood draw. These reflect patterns of cellular activation across diverse cell types that lead to progressive distancing of the gene expression state and plasma proteome from native in vivo biology. Differences accumulating during an overnight rest (18 hours) could confound relevant biologic variance related to many underlying disease states., Graphical abstract, Highlights • Studies of human blood cells and plasma are highly sensitive to process variability • Time variability distorts biology in cutting-edge single-cell and multiplex assays • Longitudinal, multi-modal, and aligned data enable data qualification and exploration • Dataset holds potential novel, multi-modal biological correlations and hypotheses, Molecular Physiology ; Immunology ; Proteomics ; Transcriptomics

BACKGROUND: Despite a rapidly growing body of literature on coronavirus disease 2019 (COVID-19), our understanding of the immune correlates of disease severity, course, and outcome remains poor. METHODS: Using mass cytometry, we assessed the immune landscape in longitudinal whole-blood specimens from 59 patients presenting with acute COVID-19 and classified based on maximal disease severity. Hospitalized patients negative for SARS-CoV-2 were used as controls. RESULTS: We found that the immune landscape in COVID-19 formed 3 dominant clusters, which correlated with disease severity. Longitudinal analysis identified a pattern of productive innate and adaptive immune responses in individuals who had a moderate disease course, whereas those with severe disease had features suggestive of a protracted and dysregulated immune response. Further, we identified coordinate immune alterations accompanying clinical improvement and decline that were also seen in patients who received IL-6 pathway blockade. CONCLUSION: The hospitalized COVID-19 negative cohort allowed us to identify immune alterations that were shared between severe COVID-19 and other critically ill patients. Collectively, our findings indicate that selection of immune interventions should be based in part on disease presentation and early disease trajectory due to the profound differences in the immune response in those with mild to moderate disease and those with the most severe disease. FUNDING: Benaroya Family Foundation, the Leonard and Norma Klorfine Foundation, Glenn and Mary Lynn Mounger, and the National Institutes of Health.

Infant Acute Myeloid Leukemia (AML) is a poorly-addressed, heterogeneous malignancy distinguished by surprisingly few mutations per patient but accompanied by myriad age-specific translocations. These characteristics make treatment of infant AML challenging. While infant AML is a relatively rare disease, it has enormous impact on families, and in terms of life-years-lost and life limiting morbidities. To better understand the mechanisms that drive infant AML, we performed integrative analyses of genome-wide mRNA, miRNA, and DNA-methylation data in diagnosis-stage patient samples. Here, we report the activation of an onco-fetal B-cell developmental gene regulatory network in infant AML. AML in infants is genomically distinct from AML in older children/adults in that it has more structural genomic aberrations and fewer mutations. Differential expression analysis of ~1500 pediatric AML samples revealed a large number of infant-specific genes, many of which are associated with B cell development and function. 18 of these genes form a well-studied B-cell gene regulatory network that includes the epigenetic regulators BRD4 and POU2AF1, and their onco-fetal targets LIN28B and IGF2BP3. All four genes are hypo-methylated in infant AML. Moreover, micro-RNA Let7a-2 is expressed in a mutually exclusive manner with its target and regulator LIN28B. These findings suggest infant AML may respond to bromodomain inhibitors and immune therapies targeting CD19, CD20, CD22, and CD79A.

Independent scientific achievements have led to the discovery of aberrant splicing patterns in oncogenesis, while more recent advances have uncovered novel gene fusions involving neurotrophic tyrosine receptor kinases (NTRKs) in gliomas. The exploration of NTRK splice variants in normal and neoplastic brain provides an intersection of these two rapidly evolving fields. Tropomyosin receptor kinase B (TrkB), encoded NTRK2, is known for critical roles in neuronal survival, differentiation, molecular properties associated with memory, and exhibits intricate splicing patterns and post-translational modifications. Here, we show a role for a truncated NTRK2 splice variant, TrkB.T1, in human glioma. TrkB.T1 enhances PDGF-driven gliomas in vivo, augments PDGF-induced Akt and STAT3 signaling in vitro, while next generation sequencing broadly implicates TrkB.T1 in the PI3K signaling cascades in a ligand-independent fashion. These TrkB.T1 findings highlight the importance of expanding upon whole gene and gene fusion analyses to include splice variants in basic and translational neuro-oncology research., Tropomyosin receptor kinase B (TrkB), encoded by the neurotrophic tyrosine receptor kinase 2 (NTRK2) gene, exhibits intricate splicing patterns and post-translational modifications. Here, the authors perform whole gene and transcript-level analyses and report the TrkB.T1 splice variant enhances PDGF-driven gliomas in vivo and augments PI3K signaling cascades in vitro.

Background Copy number alterations form prognostic molecular subtypes of glioblastoma with clear differences in median overall survival. In this study, we leverage molecular data from several glioblastoma cohorts to define the distribution of copy number subtypes across random cohorts as well as cohorts with selection biases for patients with inherently better outcome. Methods Copy number subtype frequency was established for 4 glioblastoma patient cohorts. Two randomly selected cohorts include The Cancer Genome Atlas (TCGA) and the German Glioma Network (GGN). Two more selective cohorts include the phase II trial ARTE in elderly patients with newly diagnosed glioblastoma and a multi-institutional cohort focused on paired resected initial/recurrent glioblastoma. The paired initial/recurrent cohort also had exome data available, which allowed for evaluation of multidimensional scaling analysis. Results Smaller selective glioblastoma cohorts are enriched for copy number subtypes that are associated with better survival, reflecting the selection of patients who do well enough to enter a clinical trial or who are deemed well enough to undergo resection at recurrence. Adding exome data to copy number data provides additional data reflective of outcome. Conclusions The overall outcome for diffuse glioma patients is predicted by DNA structure at initial tumor resection. Molecular signature shifts across glioblastoma populations reflect the inherent bias of patient selection toward longer survival in clinical trials. Therefore it may be important to include molecular profiling, including copy number, when enrolling patients for clinical trials in order to balance arms and extrapolate relevance to the general glioblastoma population.

SUMMARY The majority of supratentorial ependymomas (ST-ependymomas) have few mutations but frequently display chromothripsis of chromosome 11q that generates a fusion between C11orf95 and RELA (RELAFUS). Neural stem cells transduced with RELAFUS ex vivo form ependymomas when implanted in the brain. These tumors display enhanced NF-κB signaling, suggesting that this aberrant signal is the principal mechanism of oncogenesis. However, it is not known whether RELAFUS is sufficient to drive de novo ependymoma tumorigenesis in the brain and, if so, whether these tumors also arise from neural stem cells. We show that RELAFUS drives ST-ependymoma formation from periventricular neural stem cells in mice and that RELAFUS-induced tumorigenesis is likely dependent on a series of cell signaling pathways in addition to NF-κB., Graphical Abstract, In Brief The C11orf95-RELA fusion (RELAFUS) has been found in a distinct subset of supratentorial ependymomas. Ozawa et al. show that RELAFUS is sufficient to drive ST-ependymoma formation from periventricular neural stem cells in mice. Furthermore, they show that RELAFUS-induced tumorigenesis might depend on other cell signaling pathways in addition to NF-κB.

Temporally regulated alternative splicing choices are vital for proper development yet the wrong splice choice may be detrimental. Here we highlight a novel role for the neurotrophin receptor splice variant TrkB.T1 in neurodevelopment, embryogenesis, transformation, and oncogenesis across multiple tumor types in both humans and mice. TrkB.T1 is the predominant NTRK2 isoform across embryonic organogenesis and is highly expressed in a wide range of adult and pediatric tumors. Further, forced expression of TrkB.T1 causes multiple solid and non-solid tumors in mice in the context of tumor suppressor loss. These results highlight a unique role for the neurotrophin receptor splicing in development and oncogenesis and underscore the need for considering alternative splicing and transcript level data in neuroscience, developmental biology, and oncology research.

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction‐based models and packages that extend the core with features suited to other model types including constraint‐based models, reaction‐diffusion models, logical network models, and rule‐based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single‐cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution., Over the past two decades, scientists from different fields have been developing SBML, a standard format for encoding computational models in biology and medicine. This article summarizes recent progress and gives perspectives on emerging challenges.

PURPOSE: A cryptic inv(16)(p13.3q24.3) encoding the CBFA2T3-GLIS2 fusion is associated with poor outcome in infants with acute megakaryocytic leukemia. We aimed to broaden our understanding of the pathogenesis of this fusion through transcriptome profiling. EXPERIMENTAL DESIGN: Available RNA from children and young adults with de novo AML (N=1,049) underwent transcriptome sequencing (mRNA and miRNA). Transcriptome profiles for those with the CBFA2T3-GLIS2 fusion (N=24) and without (N=1,025) were contrasted to define fusion-specific miRNAs, genes, and pathways. Clinical annotations defined distinct fusion-associated disease characteristics and outcomes. RESULTS: The CBFA2T3-GLIS2 fusion was restricted to infants < 3 years-old (p

Immune checkpoint inhibitor (ICI) treatment has recently become a first-line therapy for many non–small cell lung cancer (NSCLC) patients. Unfortunately, most NSCLC patients are refractory to ICI monotherapy, and initial attempts to address this issue with secondary therapeutics have proven unsuccessful. To identify entities precluding CD8(+) T cell accumulation in this process, we performed unbiased analyses on flow cytometry, gene expression, and multiplexed immunohistochemical data from a NSCLC patient cohort. The results revealed the presence of a myeloid-rich subgroup, which was devoid of CD4(+) and CD8(+) T cells. Of all myeloid cell types assessed, neutrophils were the most highly associated with the myeloid phenotype. Additionally, the ratio of CD8(+) T cells to neutrophils (CD8/PMN) within the tumor mass optimally distinguished between active and myeloid cases. This ratio was also capable of showing the separation of patients responsive to ICI therapy from those with stable or progressive disease in 2 independent cohorts. Tumor-bearing mice treated with a combination of anti-PD1 and SX-682 (CXCR1/2 inhibitor) displayed relocation of lymphocytes from the tumor periphery into a malignant tumor, which was associated with induction of IFN-γ–responsive genes. These results suggest that neutrophil antagonism may represent a viable secondary therapeutic strategy to enhance ICI treatment outcomes.

INTRODUCTION AND OBJECTIVES:Although the genomic landscape of LTUC is well studied, less is known about UTUC, including in the metastatic sites. We evaluated and compared genomic features of metast...

Failure to clear antigens causes CD8+ T cells to become increasingly hypo-functional, a state known as exhaustion. We combined manually extracted information from published literature with gene expression data from diverse model systems to infer a set of molecular regulatory interactions that underpin exhaustion. Topological analysis and simulation modeling of the network suggests CD8+ T cells undergo 2 major transitions in state following stimulation. The time cells spend in the earlier pro-memory/proliferative (PP) state is a fixed and inherent property of the network structure. Transition to the second state is necessary for exhaustion. Combining insights from network topology analysis and simulation modeling, we predict the extent to which each node in our network drives cells towards an exhausted state. We demonstrate the utility of our approach by experimentally testing the prediction that drug-induced interference with EZH2 function increases the proportion of pro-memory/proliferative cells in the early days post-activation.

We present the molecular landscape of pediatric acute myeloid leukemia (AML) and characterize nearly 1,000 participants in Children's Oncology Group (COG) AML trials. The COG-National Cancer Institute (NCI) TARGET AML initiative assessed cases by whole-genome, targeted DNA, mRNA and microRNA sequencing and CpG methylation profiling. Validated DNA variants corresponded to diverse, infrequent mutations, with fewer than 40 genes mutated in2% of cases. In contrast, somatic structural variants, including new gene fusions and focal deletions of MBNL1, ZEB2 and ELF1, were disproportionately prevalent in young individuals as compared to adults. Conversely, mutations in DNMT3A and TP53, which were common in adults, were conspicuously absent from virtually all pediatric cases. New mutations in GATA2, FLT3 and CBL and recurrent mutations in MYC-ITD, NRAS, KRAS and WT1 were frequent in pediatric AML. Deletions, mutations and promoter DNA hypermethylation convergently impacted Wnt signaling, Polycomb repression, innate immune cell interactions and a cluster of zinc finger-encoding genes associated with KMT2A rearrangements. These results highlight the need for and facilitate the development of age-tailored targeted therapies for the treatment of pediatric AML.

BACKGROUND Aberrant expression of microRNA-155 (miR-155) has been implicated in acute myeloid leukemia (AML) and associated with clinical outcome. PROCEDURE We evaluated miR-155 expression in 198 children with normal karyotype AML (NK-AML) enrolled in Children's Oncology Group (COG) AML trial AAML0531 and correlated miR-155 expression levels with disease characteristics and clinical outcome. Patients were divided into quartiles (Q1-Q4) based on miR-155 expression level, and disease characteristics were then evaluated and correlated with miR-155 expression. RESULTS MiR-155 expression varied over 4-log10-fold range relative to its expression in normal marrow with a median expression level of 0.825 (range 0.043-25.630) for the entire study cohort. Increasing miR-155 expression was highly associated with the presence of FLT3/ITD mutations (P < 0.001) and high-risk disease (P < 0.001) and inversely associated with standard-risk (P = 0.008) and low-risk disease (P = 0.041). Patients with highest miR-155 expression had a complete remission (CR) rate of 46% compared with 82% in low expressers (P < 0.001) with a correspondingly lower event-free (EFS) and overall survival (OS) (P < 0.001 and P = 0.002, respectively). In a multivariate model that included molecular risk factors, high miR-155 expression remained a significant independent predictor of OS (P = 0.022) and EFS (0.019). CONCLUSIONS High miR-155 expression is an adverse prognostic factor in pediatric NK-AML patients. Specifically, high miR-155 expression not only correlates with FLT3/ITD mutation status and high-risk disease but it is also an independent predictor of worse EFS and OS.