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As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1–3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Supplementary Table 1. Loci associated with tumor site of origin. Supplementary Table 2. GWAS Cancer Associations Re-tested in TCGA. Supplementary Table 3. Loci associated with somatic status of a cancer gene. Supplementary Table 4. TCGA Samples used for Discovery and Validation Tests. Supplementary Table 5. TCGA Samples Used for Alternative Splicing Analysis.

Supplementary Figure S1. Description of the TCGA data. Supplementary Figure S2. Flow chart describing data preprocessing, association testing and validation testing stages of the study. Supplementary Figure S3. QQ-plots and genomic inflation (G.I.) estimates for germlines associations with tumor site of origin. Supplementary Figure S4. Odds ratios for published cancer-associated markers from the NHGRI GWAS Catalog were compared to odds ratios for the same markers when testing for associations with tumor site of origin. Supplementary Figure S5. Power analysis and comparison of effect sizes between discovery and validation phases. Supplementary Figure S6. QQ-plots for germline associations with somatic status of cancer genes with validated associations. Supplementary Figure S7. Western blots.

Supplementary Figure, Table Legends

Correlations between the expression of DOCK5 variant and clinicopathological parameters in TCGA HPV negative HNSCC data

Figure S1:Distribution of ASEs present within each tumor in TCGA HPV negative HNSCC cohort. Figure S2: Expression of DOCK5 variant within different head and neck regions. Figure S3: Relationship between DOCK5 variant expression and gene mutation. Figure S4: DOCK5 variant expression in HPV negative HNSCC cell lines. Figure S5: Differentially expressed gene and pathway analysis.

Purpose: Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers worldwide, and alternative splicing is considered to play important roles in tumor progression. Our study is designed to identify alternative splicing events (ASEs) in human papillomavirus (HPV)–negative HNSCC.Experimental Design: RNA sequencing data of 407 HPV-negative HNSCC and 38 normal samples were obtained from The Cancer Genome Atlas (TCGA), and splice junctions were discovered using MapSplice. Outlier analysis was used to identify significant splicing junctions between HPV-negative HNSCC and normal samples. To explore the functional role of the identified DOCK5 variant, we checked its expression with qRT-PCR in a separate primary tumor validation set and performed proliferation, migration, and invasion assays.Results: A total of 580 significant splicing events were identified in HPV-negative HNSCC, and the most common type of splicing events was an alternative start site (33.3%). The prevalence of a given individual ASE among the tumor cohort ranged from 9.8% and 64.4%. Within the 407 HPV-negative HNSCC samples in TCGA, the number of significant ASEs differentially expressed in each tumor ranged from 17 to 290. We identified a novel candidate oncogenic DOCK5 variant confirmed using qRT-PCR in a separate primary tumor validation set. Loss- and gain-of-function experiments indicated that DOCK5 variant promoted proliferation, migration, and invasion of HPV-negative HNSCC cells, and patients with higher expression of DOCK5 variant showed decreased overall survival.Conclusions: Analysis of ASEs in HPV-negative HNSCC identifies multiple alterations likely related to carcinogenesis, including an oncogenic DOCK5 variant. Clin Cancer Res; 24(20); 5123–32. ©2018 AACR.

Pediatric acute myeloid leukemia (pAML) is typified by high relapse rates and a relative paucity of somatic DNA mutations. Although seminal studies show that splicing factor mutations and mis-splicing fuel therapy-resistant leukemia stem cell (LSC) generation in adults, splicing deregulation has not been extensively studied in pAML. Herein, we describe single-cell proteogenomics analyses, transcriptome-wide analyses of FACS-purified hematopoietic stem and progenitor cells followed by differential splicing analyses, dual-fluorescence lentiviral splicing reporter assays, and the potential of a selective splicing modulator, Rebecsinib, in pAML. Using these methods, we discover transcriptomic splicing deregulation typified by differential exon usage. In addition, we discover downregulation of splicing regulator RBFOX2 and CD47 splice isoform upregulation. Importantly, splicing deregulation in pAML induces a therapeutic vulnerability to Rebecsinib in survival, self-renewal, and lentiviral splicing reporter assays. Taken together, the detection and targeting of splicing deregulation represent a potentially clinically tractable strategy for pAML therapy.

SummaryThe maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of SARS-CoV-2 lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of ‘local’ when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

BackgroundThe objective of this study is to develop predictive models for persistent opioid use following lower extremity joint arthroplasty and determine if ensemble learning and an oversampling technique may improve model performance.MethodsWe compared various predictive models to identify at-risk patients for persistent postoperative opioid use using various preoperative, intraoperative, and postoperative data, including surgical procedure, patient demographics/characteristics, past surgical history, opioid use history, comorbidities, lifestyle habits, anesthesia details, and postoperative hospital course. Six classification models were evaluated: logistic regression, random forest classifier, simple-feedforward neural network, balanced random forest classifier, balanced bagging classifier, and support vector classifier. Performance with Synthetic Minority Oversampling Technique (SMOTE) was also evaluated. Repeated stratified k-fold cross-validation was implemented to calculate F1-scores and area under the receiver operating characteristics curve (AUC).ResultsThere were 1042 patients undergoing elective knee or hip arthroplasty in which 242 (23.2%) reported persistent opioid use. Without SMOTE, the logistic regression model has an F1 score of 0.47 and an AUC of 0.79. All ensemble methods performed better, with the balanced bagging classifier having an F1 score of 0.80 and an AUC of 0.94. SMOTE improved performance of all models based on F1 score. Specifically, performance of the balanced bagging classifier improved to an F1 score of 0.84 and an AUC of 0.96. The features with the highest importance in the balanced bagging model were postoperative day 1 opioid use, body mass index, age, preoperative opioid use, prescribed opioids at discharge, and hospital length of stay.ConclusionsEnsemble learning can dramatically improve predictive models for persistent opioid use. Accurate and early identification of high-risk patients can play a role in clinical decision making and early optimization with personalized interventions.

A longstanding goal of biomedicine is to understand how alterations in molecular and cellular networks give rise to the spectrum of human diseases. For diseases with shared etiology, understanding the common causes allows for improved diagnosis of each disease, development of new therapies and more comprehensive identification of disease genes. Accordingly, this protocol describes how to evaluate the extent to which two diseases, each characterized by a set of mapped genes, are colocalized in a reference gene interaction network. This procedure uses network propagation to measure the network “distance” between gene sets. For colocalized diseases, the network can be further analyzed to extract common gene communities at progressive granularities. In particular, we show how to: (i) obtain input gene sets and a reference gene interaction network, (ii) identify common subnetworks of genes that encompass or are in close proximity to all gene sets, (iii) use multiscale community detection to identify systems and pathways represented by each common subnetwork to generate a network colocalized systems map, (iv) validate identified genes and systems using a mouse variant database, and (v) visualize and further investigate select genes, interactions and systems for relevance to phenotype(s) of interest. We demonstrate the utility of this approach by identifying shared biological mechanisms underlying autism and congenital heart disease. However, this protocol is general and can be applied to any gene sets attributed to diseases or other phenotypes with suspected joint association. A typical NetColoc run takes less than an hour. Software and documentation are available at https://github.com/ucsd-ccbb/NetColoc.

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E–09 and 4.10E–18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

Current approaches for studying pathologic changes in the retina associated with Alzheimer’s Disease (AD) remain heterogeneous, limiting the use of retinal amyloid-beta as a viable biomarker for AD. Transcriptomic profiling of the retina has provided cell-specific insight into AD progression in the brain yet is lacking in the retina. In this study, we implemented a non-biased approach through next generation sequencing to profile frozen archived retinal tissues from autopsy/pathologically confirmed AD and non-diagnosed cases (NonAD). A total of 37,211 nuclei were isolated from frozen retinal tissue punches originating from AD, and 31,326 were isolated from non-diagnosed cases. Gene expression patterns specific to the retinal region and major retinal cell types were represented in both tissue groups. AD-associated genes were differentially expressed in AD retinal glial cells, including microglia. A greater percentage of microglial nuclei from AD retinal nuclei expressed TYRO protein tyrosine kinase-binding protein (TYROBP) compared to nonAD retinal nuclei. However, compared to microglia from single retinal cell datasets from elderly non-diseased individuals, TYROBP expression is highly expressed in the single cell data set, indicating TYROBP transcripts reside within the cytoplasm. However, other AD-associated genes were differentially expressed in AD nuclei such as DOCK2, PICALM, and PLCG2 compared to non-diseased single-cell microglia, implicating a role of these genes in the AD retina. To summarize, we extracted a high number of nuclei from frozen retinal tissue that retain specific gene markers for cell classification and highlighted candidate AD-associated genes in retinal microglia that may be viable in future AD retinal studies.

Nucleotide-binding oligomerization domain-like receptor-family pyrin domain-containing 3 (NLRP3) inflammasome activation has been shown to result in liver fibrosis. Mechanisms and downstream signaling remain incompletely understood. Here, we studied the role of IL-18 in hepatic stellate cells (HSCs), and its impact on liver fibrosis.We observed significantly increased serum levels of IL-18 (128.4 pg/ml vs. 74.9 pg/ml) and IL-18 binding protein (BP; 46.50 ng/ml vs. 15.35 ng/ml) in patients with liver cirrhosis compared with healthy controls. Single cell RNA sequencing data showed that an immunoregulatory subset of murine HSCs highly expresses Il18 and Il18r1. Treatment of cultured primary murine HSC with recombinant mouse IL-18 accelerated their transdifferentiation into myofibroblasts. In vivo, IL-18 receptor-deficient mice had reduced liver fibrosis in a model of fibrosis induced by HSC-specific NLRP3 overactivation. Whole liver RNA sequencing analysis from a murine model of severe NASH-induced fibrosis by feeding a choline-deficient, L-amino acid-defined, high fat diet showed that genes related to IL-18 and its downstream signaling were significantly upregulated, and Il18Our study highlights the role of IL-18 in the development of liver fibrosis by its direct effect on HSC activation identifying IL-18 as a target to treat liver fibrosis.

While best known for its role in oxidative DNA damage repair, apurinic-apyrimidinic endonuclease-1 (APE1) is a multifunctional protein that regulates multiple host responses during oxidative stress including the reductive activation of transcription factors. As knockout of the APE1-encoding gene, Apex1, is embryonically lethal, we sought to create a viable model with generalized inhibition of APE1 expression.

Our current knowledge of the cellular and molecular mechanisms of placental epithelial cells, trophoblast, primarily came from the use of mouse trophoblast stem cells and tumor-derived or immortalized human trophoblast cell lines. This was mainly due to the difficulties in maintaining primary trophoblast in culture and establishing human trophoblast stem cell (hTSC) lines. However, in-depth characterization of these cellular models and in vivo human trophoblast have revealed significant discrepancies. For the past two decades, multiple groups have shown that human pluripotent stem cells (hPSCs) can be differentiated into trophoblast, and thus could be used as a model for normal and disease trophoblast differentiation. During this time, trophoblast differentiation protocols have evolved, enabling researchers to study cellular characteristics at trophectoderm (TE), trophoblast stem cells (TSC), syncytiotrophoblast (STB), and extravillous trophoblast (EVT) stages. Recently, several groups reported methods to derive hTSC from pre-implantation blastocyst or early gestation placenta, and trophoblast organoids from early gestation placenta, drastically changing the landscape of trophoblast research. These culture conditions have been rapidly applied to generate hPSC-derived TSC and trophoblast organoids. As a result of these technological advancements, the field's capacity to better understand trophoblast differentiation and their involvement in pregnancy related disease has greatly expanded. Here, we present in vitro models of human trophoblast differentiation, describing both primary and hPSC-derived TSC, maintained as monolayers and 3-dimensional trophoblast organoids, as a tool to study early placental development and disease in multiple settings.

Trophoblast stem cells (TSCs) have recently been derived from human embryos and early-first-trimester placenta; however, aside from ethical challenges, the unknown disease potential of these cells limits their scientific utility. We have previously established a bone morphogetic protein 4 (BMP4)-based two-step protocol for differentiation of primed human pluripotent stem cells (hPSCs) into functional trophoblasts; however, those trophoblasts could not be maintained in a self-renewing TSC-like state. Here, we use the first step from this protocol, followed by a switch to newly developed TSC medium, to derive bona fide TSCs. We show that these cells resemble placenta- and naive hPSC-derived TSCs, based on their transcriptome as well as their invitro and invivo differentiation potential. We conclude that primed hPSCs can be used to generate functional TSCs through a simple protocol, which can be applied to a widely available set of existing hPSCs, including induced pluripotent stem cells, derived from patients with known birth outcomes.

NAFLD is the most common chronic liver disease in children. Large pediatric studies identifying single nucleotide polymorphisms (SNPs) associated with risk and histologic severity of NAFLD are limited. Study aims included investigating SNPs associated with risk for NAFLD using family trios and association of candidate alleles with histologic severity.Children with biopsy-confirmed NAFLD were enrolled from the NASH Clinical Research Network. The Expert Pathology Committee reviewed liver histology. Genotyping was conducted with allele-specific primers for 60 candidate SNPs. Parents were enrolled for trio analysis. To assess risk for NAFLD, the transmission disequilibrium test was conducted in trios. Among cases, regression analysis assessed associations with histologic severity. A total of 822 children with NAFLD had mean age 13.2 years (SD 2.7) and mean ALT 101 U/L (SD 90). PNPLA3 (rs738409) demonstrated the strongest risk (p = 2.24 × 10This study demonstrated disease-associated SNPs in children with NAFLD. In particular, rs6006473 was highly associated with severity of fibrosis. These hypothesis-generating results support future mechanistic studies of development of adverse outcomes such as fibrosis and generation of therapeutic targets for NAFLD in children.

ObjectiveThis study examined the host-microbe changes underpinning treatment response to hyperbaric oxygen therapy (HBOT) in ulcerative colitis.DesignPre- and post-intervention mucosal tissue and fecal samples from two clinical trials, along with fecal samples from healthy controls and fecal and mucosal tissue from disease severity matched UC controls. Mucosal tissue bulk-RNA sequencing, digital spatial profiling (DSP) for single-cell RNA and protein analysis, and immunohistochemistry was performed, in addition to 16S rRNA, shotgun metagenomics, metabolomics, and metaproteomics of fecal samples. Fecal colonization experiments in IL10-/- germ-free mice were performed to confirm observations.ResultsProteomics identified associations between HBOT response status and neutrophil degranulation, with specificity of effect for azurophilic granules. DSP identified a specific HBOT effect on reducing neutrophil STAT3, which was confirmed by immunohistochemistry. HBOT decreased microbial diversity with an accompanying proportional increase in Firmicutes and a secondary bile acid lithocholic acid. The reduction in diversity was due to reductions in mucinophiles, with differences in Akkermansia muciniphila strains being associated with HBOT response status. Proteomics observed an accompanying effect for HBOT on MUC2. Colonization of IL10-/- with stool obtained from HBOT responders resulted in lower colitis activity compared to stool obtained from HBOT non-responders, with no differences in STAT3 expression, suggesting complementary but independent host and microbial responses.ConclusionHBOT reduces host neutrophil STAT3 and azurophilic granule activity in UC patients, and changes in microbial composition and metabolism in ways that improve colitis activity. Intestinal microbiota, especially strain level variations in A. muciniphila, may contribute to HBOT non-response.

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA- boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric=1.28E- 09 and 4.10E-18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.

SummaryAs SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Immaturity of alveolar macrophages (AMs) around birth contributes to the susceptibility of newborns to lung disease. However, the molecular features differentiating neonatal and mature, adult AMs are poorly understood. In this study, we identify the unique transcriptomes and enhancer landscapes of neonatal and adult AMs in mice. Although the core AM signature was similar, murine adult AMs expressed higher levels of genes involved in lipid metabolism, whereas neonatal AMs expressed a largely proinflammatory gene profile. Open enhancer regions identified by an assay for transposase-accessible chromatin followed by high-throughput sequencing (ATAC-seq) contained motifs for nuclear receptors, MITF, and STAT in adult AMs and AP-1 and NF-κB in neonatal AMs. Intranasal LPS activated a similar innate immune response in both neonatal and adult mice, with higher basal expression of inflammatory genes in neonates. The lung microenvironment drove many of the distinguishing gene expression and open chromatin characteristics of neonatal and adult AMs. Neonatal mouse AMs retained high expression of some proinflammatory genes, suggesting that the differences in neonatal AMs result from both inherent cell properties and environmental influences.

Purpose: Human papillomavirus (HPV) plays a major role in oncogenesis and circular extrachromosomal DNA (ecDNA) is found in many cancers. However, the relationship between HPV and circular ecDNA in human cancer is not understood. Experimental Design: Forty-four primary tumor tissue samples were obtained from a cohort of patients with HPV-positive oropharynx squamous cell carcinoma (OPSCC). Twenty-eight additional HPV oropharyngeal cancer (HPVOPC) tumors from The Cancer Genome Atlas (TCGA) project were analyzed as a separate validation cohort. Genomic, transcriptomic, proteomic, computational, and functional analyses of HPVOPC were applied to these datasets. Results: Our analysis revealed circular, oncogenic DNA in nearly all HPVOPC, with circular human and human–viral hybrid ecDNA present in over a third of HPVOPC and viral circular DNA in remaining tumors. Hybrid ecDNA highly express fusion transcripts from HPV promoters and HPV oncogenes linked to downstream human transcripts that drive oncogenic transformation and immune evasion, and splice multiple, diverse human acceptors to a canonical SA880 viral donor site. HPVOPC have high E6*I expression with specific viral oncogene expression pattern related to viral or hybrid ecDNA composition. Conclusions: Nonchromosomal circular oncogenic DNA is a dominant feature of HPVOPC, revealing an unanticipated link between HPV and ecDNA that leverages the power of extrachromosomal inheritance to drive HPV and somatic oncogene expression.

Currently, the limited capacity of pediatric acute myeloid leukemia (AML) therapies to prevent recurrence has contributed to high mortality rates. While dormant self-renewing leukemia stem cells (LSCs) contribute to adult AML relapse, their role in pediatric AML therapeutic resistance has not been clearly elucidated and thus was investigated in the context of this study. Through whole transcriptome sequencing (RNA-seq) analyses of FACS-purified human hematopoietic stem cells (HSCs; CD34 +CD38 -Lineage -) and progenitor cells (HPCs; CD34 +CD38 + Lineage -) from pediatric AML (n=10) compared with adult de novo (n=5) and secondary AML (n=6) as well as non-leukemic pediatric bone marrow samples (n=6), we identified widespread splicing alterations in pediatric AML compared to non-leukemic donors, indicative of a disruption in splicing regulation. In this study, we identified 2,000 exon skipping events in pediatric AML HSCs and HPCs. Moreover, we detected increased exon skipping and intron retention in stem cell self-renewal and survival transcripts in pediatric AML stem and progenitor cells. Specifically, the pro-survival isoform of MCL1, MCL1 long, was significantly increased in comparison to its pro-apoptotic counterpart, MCL1 short. In addition, self-renewal, RNA editing and splice isoform altering adenosine deaminase RNA specific 1 (ADAR1) p150 isoform levels were significantly (p=0.05) upregulated in pediatric AML progenitors suggesting that splicing and RNA editing deregulation could fuel pediatric AML stem and progenitor cell propagation. After successful completion of pre-IND development of a pharmacologically stable, potent, and selective small molecule splicing modulator, Rebecsinib (17S-FD-895) (Crews, Balain et al Cell Stem Cell 2016; Chan et al Cell Reports 2020), we developed a dual fluorescence lentiviral splicing reporter that assays the on target anti-leukemic efficacy of Rebcsinib and to assess the therapeutic index between LSCs and normal hematopoietic stem and progenitor cells. In hematopoietic progenitor assays, we observed a dose-dependent reduction in clonogenicity and replating of CD34 + cells isolated from pediatric AML samples following treatment with Rebecsinib. While pediatric AML samples were more sensitive to splicing modulation than adult de novo or adult secondary AML samples, normal cord blood progenitor samples were unaffected by splicing modulator treatment. In addition, we identified dose-dependent alterations in lentiviral splicing reporter activity in pediatric leukemia cells engrafted in a humanized AML mouse xenograft model following intravenous treatment with one dose of 10mg/kg and 20mg/kg of Rebecsinib. Finally, we observed a reduction in ADAR1 p150 transcripts by RNA-seq analysis of hematopoietic tissues in serially transplanted patient derived AML xenografts after Rebecsinib treatment suggesting that inhibition of ADAR1 splicing prevents LSC self-renewal. Cumulatively, these data demonstrate that stem and progenitor cell specific deregulation of pre-mRNA splicing and ADAR1 activation represent a therapeutic vulnerability to splicing modulation, which provides a strong rationale for developing Rebecsinib for preventing pediatric AML recurrence. Disclosures Cloos: Astellas: Speakers Bureau; DC-One: Other, Research Funding; Genentech: Research Funding; Helsinn: Other; Janssen: Research Funding; Merus: Other, Research Funding; Navigate: Patents & Royalties; Novartis: Consultancy, Other, Research Funding; Takeda: Research Funding. Crews: Ionis Pharmaceuticals: Research Funding. Burkart: Algenesis: Other: Co-founder. Jamieson: Forty Seven Inc.: Patents & Royalties.

Throughout the COVID-19 pandemic, massive sequencing and data sharing efforts enabled the real-time surveillance of novel SARS-CoV-2 strains throughout the world, the results of which provided public health officials with actionable information to prevent the spread of the virus. However, with great sequencing comes great computation, and while cloud computing platforms bring high-performance computing directly into the hands of all who seek it, optimal design and configuration of a cloud compute cluster requires significant system administration expertise. We developed ViReflow, a user-friendly viral consensus sequence reconstruction pipeline enabling rapid analysis of viral sequence datasets leveraging Amazon Web Services (AWS) cloud compute resources and the Reflow system. ViReflow was developed specifically in response to the COVID-19 pandemic, but it is general to any viral pathogen. Importantly, when utilized with sufficient compute resources, ViReflow can trim, map, call variants, and call consensus sequences from amplicon sequence data from 1000 SARS-CoV-2 samples at 1000X depth in

Abnormal numerical and structural chromosome content is frequently found in human cancer. To test the role of aneuploidy in tumor initiation and progression, we generated mice with random aneuploidies by transient induction of polo-like kinase 4 (Plk4), a master regulator of centrosome number. Short-term chromosome instability (CIN) from transient Plk4 induction resulted in formation of aggressive T-cell lymphomas in mice with heterozygous inactivation of one p53 allele and accelerated tumor development in the absence of p53. Transient CIN increased the frequency of lymphoma-initiating cells with a specific karyotype profile, including trisomy of chromosomes 4, 5, 14, and 15 occurring early in tumorigenesis. Tumor development in mice with chronic CIN induced by an independent mechanism (through inactivation of the spindle assembly checkpoint) gradually trended toward a similar karyotypic profile, as determined by single-cell whole-genome DNA sequencing. Overall, we show how transient CIN generates cells with random aneuploidies from which ones that acquire a karyotype with specific chromosome gains are sufficient to drive cancer formation, and that distinct CIN mechanisms can lead to similar karyotypic cancer-causing outcomes.