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γ-Aminobutyrate (GAB), the biochemical form of (GABA) γ-aminobutyric acid, participates in shaping physiological processes, including the immune response. How GAB metabolism is controlled to mediate such functions remains elusive. Here we show that GAB is one of the most abundant metabolites in CD4+ T helper 17 (TH17) and induced T regulatory (iTreg) cells. GAB functions as a bioenergetic and signalling gatekeeper by reciprocally controlling pro-inflammatory TH17 cell and anti-inflammatory iTreg cell differentiation through distinct mechanisms. 4-Aminobutyrate aminotransferase (ABAT) funnels GAB into the tricarboxylic acid (TCA) cycle to maximize carbon allocation in promoting TH17 cell differentiation. By contrast, the absence of ABAT activity in iTreg cells enables GAB to be exported to the extracellular environment where it acts as an autocrine signalling metabolite that promotes iTreg cell differentiation. Accordingly, ablation of ABAT activity in T cells protects against experimental autoimmune encephalomyelitis (EAE) progression. Conversely, ablation of GABAA receptor in T cells worsens EAE. Our results suggest that the cell-autonomous control of GAB on CD4+ T cells is bimodal and consists of the sequential action of two processes, ABAT-dependent mitochondrial anaplerosis and the receptor-dependent signalling response, both of which are required for T cell-mediated inflammation.

Fraction of altered genome density plots

Supplementary Figures S1-S7 with captions and Supplementary Tables

Supplementary Methods

Supplementary Methods

Knockdown of selected genes has modest effects on MOLM13 responses to KPT-9274 treatment.

Purpose:Nicotinamide phosphoribosyltransferase (NAMPT) inhibitors (NAMPTi) are currently in development, but may be limited as single-agent therapy due to compound-specific toxicity and cancer metabolic plasticity allowing resistance development. To potentially lower the doses of NAMPTis required for therapeutic benefit against acute myeloid leukemia (AML), we performed a genome-wide CRISPRi screen to identify rational disease-specific partners for a novel NAMPTi, KPT-9274.Experimental Design:Cell lines and primary cells were analyzed for cell viability, self-renewal, and responses at RNA and protein levels with loss-of-function approaches and pharmacologic treatments. In vivo efficacy of combination therapy was evaluated with a xenograft model.Results:We identified two histone deacetylases (HDAC), HDAC8 and SIRT6, whose knockout conferred synthetic lethality with KPT-9274 in AML. Furthermore, HDAC8-specific inhibitor, PCI-34051, or clinical class I HDAC inhibitor, AR-42, in combination with KPT-9274, synergistically decreased the survival of AML cells in a dose-dependent manner. AR-42/KPT-9274 cotreatment attenuated colony-forming potentials of patient cells while sparing healthy hematopoietic cells. Importantly, combined therapy demonstrated promising in vivo efficacy compared with KPT-9274 or AR-42 monotherapy. Mechanistically, genetic inhibition of SIRT6 potentiated the effect of KPT-9274 on PARP-1 suppression by abolishing mono-ADP ribosylation. AR-42/KPT-9274 cotreatment resulted in synergistic attenuation of homologous recombination and nonhomologous end joining pathways in cell lines and leukemia-initiating cells.Conclusions:Our findings provide evidence that HDAC8 inhibition- or shSIRT6-induced DNA repair deficiencies are potently synergistic with NAMPT targeting, with minimal toxicity toward normal cells, providing a rationale for a novel–novel combination-based treatment for AML.

Software and data citation are emerging best practices in scholarly communication. This article provides structured guidance to the academic publishing community on how to implement software and data citation in publishing workflows. These best practices support the verifiability and reproducibility of scientific results; sharing and reuse of valuable data and software tools, and attribution to the creators of the software and data. While data citation is increasingly well-established, software citation is rapidly maturing. With the current intensive use of software, including specialized tools and models for scientific research problems, the research community has begun to recognize that software, as a key research result and resource, requires the same level of transparency, accessibility, and disclosure as data. Software and data that support scientific results should be preserved and shared in scientific repositories for discovery, transparency, and use by other researchers. These goals can be supported by citing these products in the Reference Section of papers and effectively associating them to the software and data preserved in scientific repositories. Publishers need to mark up these references in a specific way to enable downstream processes, specifically those that enable automated attribution. Academic publishers wishing to stay current with best practices in the field are encouraged to follow the guidance provided here.

Using a genome-wide CRISPR screen, we identified

Integration-technology feature shrink increases computing-system susceptibility to single-event effects (SEE). While modeling SEE faults will be critical, an integrated processor’s scope makes physically correct modeling computationally intractable. Without useful models, presilicon evaluation of fault-tolerance approaches becomes impossible. To incorporate accurate transistor-level effects at a system scope, we present a multiscale simulation framework. Charge collection at the 1) device level determines 2) circuit-level transient duration and state-upset likelihood. Circuit effects, in turn, impact 3) register-transfer-level architecture-state corruption visible at 4) the system level. Thus, the physically accurate effects of SEEs in large-scale systems, executed on a high-performance computing (HPC) simulator, could be used to drive cross-layer radiation hardening by design. We demonstrate the capabilities of this model with two case studies. First, we determine a D flip-flop’s sensitivity at the transistor level on 14-nm FinFet technology, validating the model against published cross sections. Second, we track and estimate faults in a microprocessor without interlocked pipelined stages (MIPS) processor for Adams 90% worst case environment in an isotropic space environment.

Triple modular redundancy (TMR) with repair is a commonly employed mitigation strategy used on SRAM field-programmable gate arrays (FPGAs) to reduce the effects of ionizing radiation and improve a circuit’s sensitive cross section. This article examines TMR circuits, where the I/O ports of the circuit have not been triplicated, but the internal circuitry has. Such circuits introduce single-point failures (SPFs) into the circuit that limit the neutron cross-sectional improvement offered by TMR to only $3\times $ for the b13 benchmark circuit used in this article. This article proposes two different mitigation techniques to address SPFs, which alter the placement and routing of the circuit. These mitigation techniques reduce the neutron cross section by $26\times $ over the unmitigated circuit while minimally affecting the circuit’s maximum clock frequency and resource utilization.

Richter’s Transformation (RT) is a poorly understood and fatal progression of chronic lymphocytic leukemia (CLL) manifesting histologically as diffuse large B-cell lymphoma. Protein arginine methyltransferase 5 (PRMT5) is implicated in lymphomagenesis, but its role in CLL or RT progression is unknown. We demonstrate herein that tumors uniformly overexpress PRMT5 in patients with progression to RT. Furthermore, mice with B-specific overexpression of hPRMT5 develop a B-lymphoid expansion with increased risk of death, and Eµ-PRMT5/TCL1 double transgenic mice develop a highly aggressive disease with transformation that histologically resembles RT; where large-scale transcriptional profiling identifies oncogenic pathways mediating PRMT5-driven disease progression. Lastly, we report the development of a SAM-competitive PRMT5 inhibitor, PRT382, with exclusive selectivity and optimal in vitro and in vivo activity compared to available PRMT5 inhibitors. Taken together, the discovery that PRMT5 drives oncogenic pathways promoting RT provides a compelling rationale for clinical investigation of PRMT5 inhibitors such as PRT382 in aggressive CLL/RT cases.

γ-Aminobutyrate (GAB) is the biochemical form of γ-aminobutyric acid (GABA) at physiological pH and functions as an essential neurotransmitter in the vertebrate’s central nervous system (CNS). Growing evidence suggests that GAB may also mediate intercellular communications to shape various physiological processes, including immune response. Beyond acting as a paracrine signaling molecule, how GAB metabolism is controlled to exert many distinct functions remains elusive. By an integrated analysis of the extracellular metabolome, stable isotope traced metabolic pathway analysis, and metabolic transcriptome, we revealed that GAB is one of the most abundant metabolites produced through glutamine and arginine catabolism in CD4+ T help 17 (TH17) and induced T regulatory (iTreg) cells. GAB functions as a bioenergetic and signaling gatekeeper by reciprocally controlling pro-inflammatory TH17 cell and anti-inflammatory iTreg cell differentiation through distinct mechanisms. The expression of 4-aminobutyrate aminotransferase (ABAT) funnels GAB, as an anaplerotic substrate, into the TCA cycle to maximize carbon allocation in promoting TH17 cell differentiation. By contrast, the absence of ABAT activities in iTreg cells enables GAB exporting to the extracellular environment and acting as an autocrine signaling metabolite to promote iTreg cell differentiation. Accordingly, genetic or pharmacological ablation of ABAT activity in T cells confers protection against experimental autoimmune encephalomyelitis (EAE) pathogenic progression. Conversely, genetic ablation of GABA(A) receptor in T cells deteriorates EAE pathogenic progression. Collectively, our results suggest that the cell-autonomous control exerted by GAB on CD4+ T cell is bimodal and consists of the sequential action of two discrete processes, ABAT–dependent mitochondrial anaplerosis and the receptor-dependent autocrine signaling response, both of which are required for a properly controlled T cell-mediated inflammation.

Global thinning is a technique that enables backside failure analysis and radiation testing. In some devices, it can also lead to increased thresholds for single-event latchup and upset. In this study, we examine the impacts of global thinning on 28 nm node FPGAs. Test devices are thinned to 50, 10, and 3 μm via CNC milling. Lattice damage, in the form of dislocations, extends about 1 μm below the surface, but is removed by polishing with colloidal SiO2. As shown by finite-element modeling, thinning increases compressive global stress in the Si while solder bumps (in flip-chip packages) increase stress locally. The results are confirmed by stress measurements obtained through Raman spectroscopy, although more complex models are needed to account for nonlinear effects in devices thinned to 3 μm and heated to 125°C. Thermal imaging shows that increased local heating occurs with increased thinning, but the maximum temperature difference across the 3-μm die is less than 2°C. Ring oscillators throughout the FPGA fabric slow about 0.5% after thinning and another 0.5% when heated to 125°C, which is attributed to stress changes in the Si.

The in vitro erythrocyte differentiation model remains a strong, clinically relevant tool to model erythroid development in normal and disease related hematopoiesis. This model also has application to developing therapeutics for diseases related to red blood cells such as sickle cell anemia where targeting increased expression of fetal hemoglobin has been a major emphasis. Since the original protocol’s publication in 2002, many groups have published modified methodologies to address issues in efficiency of maturation and terminal enucleation, as well as in scalability. While all reports have merit and show efficient enucleation, the methodologies used vary widely in technique and cytokine content. Additionally, despite the strengths in these methods, reproducibility of efficient differentiation to the point of differentiation is difficult. To address these limitations, we developed a streamlined process where total PBMCs are first primed using the original liquid culture expansion phase (published in 2002) before being differentiated with minimal input via standardized, commercially purchased semi-solid medium culture pre-supplemented with erythropoietin. Our data show this methodology to produce similar levels of CD235/CD71 positivity as previous methods but with enhanced CD235 solo positivity and evidence of enucleated cells in comparison with other widely used methods. Given the difficulty and wide variation in in vitro differentiation techniques, we present this methodology as a streamlined methodology for production of mature erythroid cells with minimal input using easily purchased reagents. Supplementary Information The online version contains supplementary material available at 10.1186/s40164-021-00244-z.

Triple modular redundancy (TMR) with repair has proven to be an effective strategy for mitigating the effects of single-event upsets within the configuration memory of static random access memory field-programmable gate arrays. Applying TMR to the design successfully reduces the design’s neutron cross section by $80\times $ . The effectiveness of TMR, however, is limited by the presence of single bits in the configuration memory which cause more than one TMR domain to fail simultaneously. We present three strategies to mitigate against these failures and improve the effectiveness of TMR: incremental routing, incremental placement, and striping. These techniques were tested using both fault injection and a wide spectrum neutron beam with the best technique offering a $400\times $ reduction to the design’s sensitive neutron cross section. An analysis from the radiation test shows that no single bits caused failure and that multicell upsets were the main cause of failure for these mitigation strategies.

KPT-9274 is a phase 1 first-in-class dual PAK4/NAMPT inhibitor for solid tumor and non-Hodgkin’s lymphoma. It demonstrates pre-clinical efficacy toward a broad spectrum of acute myeloid leukemia (AML) subtypes by inhibiting NAMPT-dependent NAD+ production. NAMPT is the rate-limiting enzyme in the salvage metabolic pathway leading to NAD+ generation. Tumor cells which are deficient in de novo pathway enzyme NAPRT1 are addicted to NAMPT. In clinical trials, treatment with NAMPT inhibitors resulted in dose-limiting toxicities. In order to dissect the mechanism of toxicity, mice were treated with KPT-9274 and resulting toxicities were characterized histopathologically and biochemically. KPT-9274 treatment caused gender-dependent stomach and kidney injuries and anemia. Female mice treated with KPT-9274 had EPO deficiency and associated impaired erythropoiesis. KPT-9274 treatment suppressed SIRT3 expression and concomitantly upregulated acetyl-manganese superoxide dismutase (MnSOD) in IMCD3 cells, providing a mechanistic basis for observed kidney toxicity. Importantly, niacin supplementation mitigated KPT-9274-caused kidney injury and EPO deficiency without affecting its efficacy. Altogether, our study delineated the mechanism of KPT-9274-mediated toxicity and sheds light onto developing strategies to improve the tolerability of this important anti-AML inhibitor. Supplementary Information The online version contains supplementary material available at 10.1186/s13045-021-01107-0.

Purpose: Nicotinamide phosphoribosyltransferase (NAMPT) inhibitors (NAMPTi) are currently in development, but may be limited as single-agent therapy due to compound-specific toxicity and cancer metabolic plasticity allowing resistance development. To potentially lower the doses of NAMPTis required for therapeutic benefit against acute myeloid leukemia (AML), we performed a genome-wide CRISPRi screen to identify rational disease-specific partners for a novel NAMPTi, KPT-9274. Experimental Design: Cell lines and primary cells were analyzed for cell viability, self-renewal, and responses at RNA and protein levels with loss-of-function approaches and pharmacologic treatments. In vivo efficacy of combination therapy was evaluated with a xenograft model. Results: We identified two histone deacetylases (HDAC), HDAC8 and SIRT6, whose knockout conferred synthetic lethality with KPT-9274 in AML. Furthermore, HDAC8-specific inhibitor, PCI-34051, or clinical class I HDAC inhibitor, AR-42, in combination with KPT-9274, synergistically decreased the survival of AML cells in a dose-dependent manner. AR-42/KPT-9274 cotreatment attenuated colony-forming potentials of patient cells while sparing healthy hematopoietic cells. Importantly, combined therapy demonstrated promising in vivo efficacy compared with KPT-9274 or AR-42 monotherapy. Mechanistically, genetic inhibition of SIRT6 potentiated the effect of KPT-9274 on PARP-1 suppression by abolishing mono-ADP ribosylation. AR-42/KPT-9274 cotreatment resulted in synergistic attenuation of homologous recombination and nonhomologous end joining pathways in cell lines and leukemia-initiating cells. Conclusions: Our findings provide evidence that HDAC8 inhibition- or shSIRT6-induced DNA repair deficiencies are potently synergistic with NAMPT targeting, with minimal toxicity toward normal cells, providing a rationale for a novel–novel combination-based treatment for AML.

Software is as integral as a research paper, monograph, or dataset in terms of facilitating the full understanding and dissemination of research. This article provides broadly applicable guidance on software citation for the communities and institutions publishing academic journals and conference proceedings. We expect those communities and institutions to produce versions of this document with software examples and citation styles that are appropriate for their intended audience. This article (and those community-specific versions) are aimed at authors citing software, including software developed by the authors or by others. We also include brief instructions on how software can be made citable, directing readers to more comprehensive guidance published elsewhere. The guidance presented in this article helps to support proper attribution and credit, reproducibility, collaboration and reuse, and encourages building on the work of others to further research.

Osteosarcoma is an aggressive disease that exhibits almost universal p53 inactivation and a high level of genomic complexity. The chaotic genome of most osteosarcomas has led many to assume that this complexity must accumulate under conditions of significant genomic/chromosomal instability. However, such conclusions have been drawn primarily from single-timepoint bulk-tumor analyses. More recent studies have questioned this assumption of chromosomal instability, hypothesizing that genomic complexity could arise from an early catastrophic event followed by faithful propagation of a highly complex, malignancy-promoting genome. To determine whether osteosarcoma tumors show evidence of instability, we performed single-cell whole-genome sequencing of >14,000 osteosarcoma cells obtained from 15 distinct lesions resected from 8 individual patients. Using the CHISEL algorithm, we inferred allele- and haplotype-specific copy numbers from this sequencing data. To evaluate how the SCNA profiles changed during the evolutionary pressures associated with metastatic dissemination and therapy, we compared the single-cell SCNA profiles of paired samples collected from both primary sites and metastases and from pre-treatment and relapsed specimens. We likewise compared profiles of patient tumors propagated orthotopically in mouse tibias to those grown within the lung to evaluate for tissue-dependent emergence of rare subclones. Despite extensive structural variations that give rise to highly complex patterns of SCNA, the cells within each tumor showed remarkably little heterogeneity. We found similar evidence of chromosomal stability when we reconstructed phylogenetic trees to identify the evolutionary relationships of cells collected from metastatic lesions or at relapse. Despite being evolutionarily distant, nearly all variants could be assigned to the trunk of the phylogenetic tree, with only modest changes occurring in the branches. This result suggests that nearly all SCNAs were acquired in an early event, followed by selection of advantageous patterns with subsequent preservation of that particular SCNA pattern. Analysis of bulk whole-genome sequencing from serially collected patient samples supports the preservation of SCNA profiles over time. This work demonstrates the power of combining single-cell DNA sequencing with an allele- and haplotype-specific CNV inference algorithm. Our approach clarifies longstanding questions about the genetics of osteosarcoma initiation and progression, calling into question previous assumptions of genomic instability inferred from single-timepoint bulk sequencing data. These results suggest that an isolated, early catastrophic event, rather than sustained genomic instability, gives rise to the complex genome that characterizes osteosarcoma tumors. Citation Format: Sanjana Rajan, Simone Zaccaria, Matthew Cannon, Maren Cam, Amy Gross, Benjamin Raphael, Ryan D. Roberts. Surprisingly conserved copy numbers from cell to cell within structurally complex tumors challenge the unstable genome hypothesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 801.

Precision oncology is the practice of interpreting the clinical significance of observed molecular changes in patient neoplasms, potentially impacting medical decision making and care. This process is labor-intensive and (among other challenges) involves accurately translating between variation representation conventions from one resource to the next. For example, differences in representations of Copy Number Variation (CNV) from genomic regions, cytogenomic bands, or gene features create challenges in knowledge matching due to lack of standards covering all of these modalities of observed variation.The Global Alliance for Genomics and Health (GA4GH; ga4gh.org) is an international collaborative of genomic data sharing initiatives (Driver Projects) developing genomic data sharing standards within a human rights framework. GA4GH recently published the Variation Representation Specification (VRS; pronounced “verse”), a standard for the computational representation of biomolecular variation. VRS is a terminology, schema, and associated conventions for creating uniquely identifiable and federatable representations of molecular variation. VRS has formal data classes well-suited to differentiating between variation on a single molecule (e.g. tandem duplications) from variation measured at a systemic level (e.g. genome-wide copy number variation). In addition to molecular sequence variation, VRS also supports variation on cytogenetic coordinate systems and genes, making it well-suited to representing variation associated with cancer biomarkers.We demonstrate the use of VRS to model reported gene-associated CNVs from the AACR Project GENIE cohort, to aid in the computational discovery of evidence from clinico-genomic knowledgebases with genomic or cytogenomic CNV representations. We highlight the use case of knowledge matching to the Atlas of Genetics and Cytogenetics in Oncology and Haematology (“the Atlas”; atlasgeneticsoncology.org), a cytogenetics resource historically driven by user website navigation. Using VRS search tools we developed for the Variant Interpretation for Cancer Consortium (VICC; cancervariants.org) GA4GH Driver Project, we found that 64% of GENIE samples with reported CNVs matched clinically relevant knowledge in the Atlas. This work was enabled by programmatic search tools leveraging standard VRS object structures, demonstrating how VRS enables collection of real-world evidence across more resources without manual interpretation or custom normalization methods. We conclude with a survey of open-source tools supporting this analysis as well as search of other clinico-genomic knowledgebases with VRS, including CIViC (civicdb.org), BRCA Exchange (brcaexchange.org), and the Molecular Oncology Almanac (moalmanac.org). Citation Format: Matthew Cannon, Kori Kuzma, James Stevenson, Jiachen Liu, Colin O'Sullivan, Bimal P. Chaudhari, Matthew Brush, Robert R. Freimuth, Tristan Nelson, Michael Baudis, Obi L. Griffith, Malachi Griffith, Lawrence Babb, Melissa S. Cline, Xuelu Liu, Brian Walsh, Alex H. Wagner. Introduction of the GA4GH Variation Representation Specification (VRS) and supporting tools for discovery and exchange of clinical genomic and cytogenomic knowledge in cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1177.

The Drug-Gene Interaction Database (DGIdb, www.dgidb.org) is a publicly accessible resource that aggregates 102,426 gene records and 57,498 drug records from 40 drug-gene interaction data sources to aid both researchers and clinicians in identifying associations between genes of interest and available drugs and therapeutics. By using peer-reviewed data sources and publications, DGIdb represents a stand-alone resource with over 100,000 drug-gene interaction claims across 30 interaction types to drive hypothesis generation in precision medicine and interpretation pipelines. The background process that normalizes drugs to a harmonized ontological concept has been upgraded. These improvements have increased concept normalization for drugs by 20% and are now available as a stand-alone service for use (https://normalize.cancervariants.org/therapy/). Leveraging our platform’s ability to find relationships between disease-critical genes and available therapeutics, DGIdb has been used in clinical interpretation pipelines to find drugs for specific diseases with an emphasis on regulatory approval status. DGIdb now uses annotations from Drugs@FDA as an additional source to provide more accurate descriptors for market and maturity status of drugs, when available. Lastly, to enhance the annotation potential for DGIdb in precision medicine pipelines, we have updated our druggable gene category sources with an additional curated list of 2,217 genes. Used alone or in combination with existing categories-such as the heavily-utilized ‘clinically actionable’ category-this additional source will give precision medicine and interpretation pipelines the power to find concise, actionable annotations for specific diseases including pediatric cancers and epilepsy. These lists are managed and maintained as a publicly-available resource to provide up-to-date annotations on disease-associated genes as they become available. Citation Format: Matthew Cannon, James Stevenson, Kori Kuzma, Colin O'Sullivan, Katherine Miller, Olivia Grischow, Adam Coffman, Susanna Kiwala, Joshua F. McMichael, Dorian Morrissey, Kelsy Cotto, Obi Griffith, Malachi Griffith, Alex Wagner. Refining the drug-gene interaction database for precision medicine pipelines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1197.

Acute myeloid leukemia (AML) is a heterogeneous and complex disease, and treatments for this disease have not been curative for the majority of patients. In younger patients, internal tandem duplication of FLT3 (FLT3-ITD) is a common mutation for which two inhibitors (midostaurin and gilteritinib) with varied potency and specificity for FLT3 are clinically approved. However, the high rate of relapse or failed initial response of AML patients suggests that the addition of a second targeted therapy may be necessary to improve efficacy. Using an unbiased large-scale CRISPR screen, we genetically identified BCL2 knockout as having synergistic effects with an approved FLT3 inhibitor. Here, we provide supportive studies that validate the therapeutic potential of the combination of FLT3 inhibitors with venetoclax in vitro and in vivo against multiple models of FLT3-ITD-driven AML. Our unbiased approach provides genetic validation for co-targeting FLT3 and BCL2 and repurposes CRISPR screening data, utilizing the genome-wide scope toward mechanistic understanding.