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The study of the tumor microbiome has been garnering increased attention. We developed a computational pipeline (CSI-Microbes) for identifying microbial reads from single-cell RNA sequencing (scRNA-seq) data and for analyzing differential abundance of taxa. Using a series of controlled experiments and analyses, we performed the first systematic evaluation of the efficacy of recovering microbial unique molecular identifiers by multiple scRNA-seq technologies, which identified the newer 10x chemistries (3' v3 and 5') as the best suited approach. We analyzed patient esophageal and colorectal carcinomas and found that reads from distinct genera tend to co-occur in the same host cells, testifying to possible intracellular polymicrobial interactions. Microbial reads are disproportionately abundant within myeloid cells that up-regulate proinflammatory cytokines like IL1 Β and CXCL8 , while infected tumor cells up-regulate antigen processing and presentation pathways. These results show that myeloid cells with bacteria engulfed are a major source of bacterial RNA within the tumor microenvironment (TME) and may inflame the TME and influence immunotherapy response.

Tailoring optimal treatment for individual cancer patients remains a significant challenge. To address this issue, we developed PERCEPTION (PERsonalized Single-Cell Expression-Based Planning for Treatments In ONcology), a precision oncology computational pipeline. Our approach uses publicly available matched bulk and single-cell (sc) expression profiles from large-scale cell-line drug screens. These profiles help build treatment response models based on patients' sc-tumor transcriptomics. PERCEPTION demonstrates success in predicting responses to targeted therapies in cultured and patient-tumor-derived primary cells, as well as in two clinical trials for multiple myeloma and breast cancer. It also captures the resistance development in patients with lung cancer treated with tyrosine kinase inhibitors. PERCEPTION outperforms published state-of-the-art sc-based and bulk-based predictors in all clinical cohorts. PERCEPTION is accessible at https://github.com/ruppinlab/PERCEPTION . Our work, showcasing patient stratification using sc-expression profiles of their tumors, will encourage the adoption of sc-omics profiling in clinical settings, enhancing precision oncology tools based on sc-omics., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Identifying sex differences in outcomes and toxicity between males and females in oncology clinical trials is important and has also been mandated by National Institutes of Health policies. Here we analyze the Trialtrove database, finding that, strikingly, only 472/89,221 oncology clinical trials (0.5%) had curated post-treatment sex comparisons. Among 288 trials with comparisons of survival, outcome, or response, 16% report males having statistically significant better survival outcome or response, while 42% reported significantly better survival outcome or response for females. The strongest differences are in trials of EGFR inhibitors in lung cancer and rituximab in non-Hodgkin's lymphoma (both favoring females). Among 44 trials with side effect comparisons, more trials report significantly lesser side effects in males (N = 22) than in females (N = 13). Thus, while statistical comparisons between sexes in oncology trials are rarely reported, important differences in outcome and toxicity exist. These considerable outcome and toxicity differences highlight the need for reporting sex differences more thoroughly going forward., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Background: Synthetic lethality (SL) denotes a genetic interaction between two genes whose co-inactivation is detrimental to cells. Because more than 25 years have passed since SL was proposed as a promising way to selectively target cancer vulnerabilities, it is timely to comprehensively assess its impact so far and discuss its future., Methods: We systematically analyzed the literature and clinical trial data from the PubMed and Trialtrove databases to portray the preclinical and clinical landscape of SL oncology., Findings: We identified 235 preclinically validated SL pairs and found 1,207 pertinent clinical trials, and the number keeps increasing over time. About one-third of these SL clinical trials go beyond the typically studied DNA damage response (DDR) pathway, testifying to the recently broadening scope of SL applications in clinical oncology. We find that SL oncology trials have a greater success rate than non-SL-based trials. However, about 75% of the preclinically validated SL interactions have not yet been tested in clinical trials., Conclusions: Dissecting the recent efforts harnessing SL to identify predictive biomarkers, novel therapeutic targets, and effective combination therapy, our systematic analysis reinforces the hope that SL may serve as a key driver of precision oncology going forward., Funding: Funded by the Samsung Research Funding & Incubation Center of Samsung Electronics, the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Republic of Korea government (MSIT), the Kwanjeong Educational Foundation, the Intramural Research Program of the National Institutes of Health (NIH), National Cancer Institute (NCI), and Center for Cancer Research (CCR)., Competing Interests: Declaration of interests E.R. is a co-founder of Medaware, Ltd.; Metabomed, Ltd.; and Pangea Biomed, Ltd. (divested from the latter). E.R. serves as a non-paid scientific consultant to Pangea Biomed, Ltd., a company developing a precision oncology SL-based multiomics approach. J.S.L. is a scientific consultant at Pangea Biomed, Ltd., and a founder of NGen Biointelligence, Inc., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

The 2015 American College of Medical Genetics and Genomics and the Association for Molecular Pathology variant classification publication established a standard employed internationally to guide laboratories in variant assessment. Those recommendations included both pathogenic (PP1) and benign (BS4) criteria for evaluating the inheritance patterns of variants, but details of how to apply those criteria at appropriate evidence levels were sparse. Several publications have since attempted to provide additional guidance, but anecdotally, this issue is still challenging. Additionally, it is not clear that those prior efforts fully distinguished disease-gene identification considerations from variant pathogenicity considerations nor did they address autosomal-recessive and X-linked inheritance. Here, we have taken a mixed inductive and deductive approach to this problem using real diseases as examples. We have developed a practical heuristic for genetic co-segregation evidence and have also determined that the specific phenotype criterion (PP4) is inseparably coupled to the co-segregation criterion. We have also determined that negative evidence at one locus constitutes positive evidence for other loci for disorders with locus heterogeneity. Finally, we provide a points-based system for evaluating phenotype and co-segregation as evidence types to support or refute a locus and show how that can be integrated into the Bayesian framework now used for variant classification and consistent with the 2015 guidelines., Competing Interests: Declaration of interests L.G.B. is a member of the Illumina Medical Ethics Advisory Committee and receives research support from Merck, Inc. and honoraria from Cold Spring Harbor Laboratory Press and Wolters-Kluwer. H.L.R. receives funding from Illumina and Microsoft for rare disease research., (Copyright © 2023. Published by Elsevier Inc.)

Chimeric antigen receptor (CAR) T cell therapies have yielded transformative clinical successes for patients with blood tumors, but their full potential remains to be unleashed against solid tumors. One challenge is finding selective targets, which we define intuitively to be cell surface proteins that are expressed widely by cancer cells but minimally by healthy cells in the tumor microenvironment and other normal tissues. Analyzing patient tumor single-cell transcriptomics data, we first defined and quantified selectivity and safety scores of existing CAR targets for indications in which they are in clinical trials or approved. We then sought new candidate cell surface CAR targets that have better selectivity and safety scores than those currently being tested. Remarkably, in almost all cancer types, we could not find such better targets, testifying to the near optimality of the current target space. However, in human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSC), for which there is currently a dearth of existing CAR targets, we identified a total of twenty candidate novel CAR targets, five of which have both superior selectivity and safety scores. These newly identified cell surface targets lay a basis for future investigations that may lead to better CAR treatments in HNSC.

Introduction: Glucose-6-phosphate dehydrogenase (G6PD) deficiency is an X-linked enzymatic disorder that is particularly prevalent in Africa, Asia, and the Middle East. This study aimed to assess the long-term health risks associated with G6PD deficiency., Methods: A retrospective cohort study was conducted using data from a national healthcare provider in Israel (Leumit Health Services). A total of 7,473 G6PD-deficient individuals were matched with 29,892 control subjects in a 1:4 ratio, based on age, gender, socioeconomic status, and ethnic groups. The exposure of interest was recorded G6PD diagnosis or positive G6PD diagnostic test. The main outcomes and measures included rates of infectious diseases, allergic conditions, and autoimmune disorders between 2002 and 2022., Results: Significantly increased rates were observed for autoimmune disorders, infectious diseases, and allergic conditions in G6PD-deficient individuals compared to the control group. Specifically, notable increases were observed for rheumatoid arthritis (odds ratio [OR] 2.41, p<0.001), systemic lupus erythematosus (OR 4.56, p<0.001), scleroderma (OR 6.87, p<0.001), pernicious anemia (OR 18.70, p<0.001), fibromyalgia (OR 1.98, p<0.001), Graves' disease (OR 1.46, p=0.001), and Hashimoto's thyroiditis (OR 1.26, p=0.001). These findings were supported by elevated rates of positive autoimmune serology and higher utilization of medications commonly used to treat autoimmune conditions in the G6PD-deficient group., Discussion: In conclusion, individuals with G6PD deficiency are at a higher risk of developing autoimmune disorders, infectious diseases, and allergic conditions. This large-scale observational study provides valuable insights into the comprehensive association between G6PD deficiency and infectious and immune-related diseases. The findings emphasize the importance of considering G6PD deficiency as a potential risk factor in clinical practice and further research is warranted to better understand the underlying mechanisms of these associations., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Israel, Schäffer, Berkovitch, Ozeri, Merzon, Green, Golan-Cohen, Ruppin, Vinker and Magen.)

Recent studies exploring the impact of methylation in tumor evolution suggest that although the methylation status of many of the CpG sites are preserved across distinct lineages, others are altered as the cancer progresses. Because changes in methylation status of a CpG site may be retained in mitosis, they could be used to infer the progression history of a tumor via single-cell lineage tree reconstruction. In this work, we introduce the first principled distance-based computational method, Sgootr, for inferring a tumor's single-cell methylation lineage tree and for jointly identifying lineage-informative CpG sites that harbor changes in methylation status that are retained along the lineage. We apply Sgootr on single-cell bisulfite-treated whole-genome sequencing data of multiregionally sampled tumor cells from nine metastatic colorectal cancer patients, as well as multiregionally sampled single-cell reduced-representation bisulfite sequencing data from a glioblastoma patient. We show that the tumor lineages constructed reveal a simple model underlying tumor progression and metastatic seeding. A comparison of Sgootr against alternative approaches shows that Sgootr can construct lineage trees with fewer migration events and with more in concordance with the sequential-progression model of tumor evolution, with a running time a fraction of that used in prior studies. Lineage-informative CpG sites identified by Sgootr are in inter-CpG island (CGI) regions, as opposed to intra-CGIs, which have been the main regions of interest in genomic methylation-related analyses., (© 2023 Liu et al.; Published by Cold Spring Harbor Laboratory Press.)

Identifying patients that are likely to respond to cancer immunotherapy is an important, yet highly challenging clinical need. Using 3139 patients across 17 different cancer types, we comprehensively studied the ability of two common copy-number alteration (CNA) scores-the tumor aneuploidy score (AS) and the fraction of genome single nucleotide polymorphism encompassed by copy-number alterations (FGA)-to predict survival following immunotherapy in both pan-cancer and individual cancer types. First, we show that choice of cutoff during CNA calling significantly influences the predictive power of AS and FGA for patient survival following immunotherapy. Remarkably, by using proper cutoff during CNA calling, AS and FGA can predict pan-cancer survival following immunotherapy for both high-TMB and low-TMB patients. However, at the individual cancer level, our data suggest that the use of AS and FGA for predicting immunotherapy response is currently limited to only a few cancer types. Therefore, larger sample sizes are needed to evaluate the clinical utility of these measures for patient stratification in other cancer types. Finally, we propose a simple, non-parameterized, elbow-point-based method to help determine the cutoff used for calling CNAs., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Background: Gingivobuccal complex oral squamous cell carcinoma (GBC-OSCC) is an aggressive malignancy with high mortality often preceded by premalignant lesions, including leukoplakia. Previous studies have reported genomic drivers in OSCC, but much remains to be elucidated about DNA methylation patterns across different stages of oral carcinogenesis., Results: There is a serious lack of biomarkers and clinical application of biomarkers for early detection and prognosis of gingivobuccal complex cancers. Hence, in search of novel biomarkers, we measured genome-wide DNA methylation in 22 normal oral tissues, 22 leukoplakia, and 74 GBC-OSCC tissue samples. Both leukoplakia and GBC-OSCC had distinct methylation profiles as compared to normal oral tissue samples. Aberrant DNA methylation increases during the different stages of oral carcinogenesis, from premalignant lesions to carcinoma. We identified 846 and 5111 differentially methylated promoters in leukoplakia and GBC-OSCC, respectively, with a sizable fraction shared between the two sets. Further, we identified potential biomarkers from integrative analysis in gingivobuccal complex cancers and validated them in an independent cohort. Integration of genome, epigenome, and transcriptome data revealed candidate genes with gene expression synergistically regulated by copy number and DNA methylation changes. Regularised Cox regression identified 32 genes associated with patient survival. In an independent set of samples, we validated eight genes (FAT1, GLDC, HOXB13, CST7, CYB5A, MLLT11, GHR, LY75) from the integrative analysis and 30 genes from previously published reports. Bisulfite pyrosequencing validated GLDC (P = 0.036), HOXB13 (P < 0.0001) promoter hypermethylation, and FAT1 (P < 0.0001) hypomethylation in GBC-OSCC compared to normal controls., Conclusions: Our findings identified methylation signatures associated with leukoplakia and gingivobuccal complex cancers. The integrative analysis in GBC-OSCC identified putative biomarkers that enhance existing knowledge of oral carcinogenesis and may potentially help in risk stratification and prognosis of GBC-OSCC., (© 2023. The Author(s).)

About 15% of human cancer cases are attributed to viral infections. To date, virus expression in tumor tissues has been mostly studied by aligning tumor RNA sequencing reads to databases of known viruses. To allow identification of divergent viruses and rapid characterization of the tumor virome, we develop viRNAtrap, an alignment-free pipeline to identify viral reads and assemble viral contigs. We utilize viRNAtrap, which is based on a deep learning model trained to discriminate viral RNAseq reads, to explore viral expression in cancers and apply it to 14 cancer types from The Cancer Genome Atlas (TCGA). Using viRNAtrap, we uncover expression of unexpected and divergent viruses that have not previously been implicated in cancer and disclose human endogenous viruses whose expression is associated with poor overall survival. The viRNAtrap pipeline provides a way forward to study viral infections associated with different clinical conditions., (© 2023. The Author(s).)

Introduction: Alzheimer's disease (AD) is a neurodegenerative disorder involving interactions between different cell types in the brain. Previous single-cell and bulk expression Alzheimer's studies have reported conflicting findings about the key cell types and cellular pathways whose expression is primarily altered in this disease. We re-analyzed these data in a uniform, coherent manner aiming to resolve and extend past findings. Our analysis sheds light on the observation that females have higher AD incidence than males., Methods: We re-analyzed three single-cell transcriptomics datasets. We used the software Model-based Analysis of Single-cell Transcriptomics (MAST) to seek differentially expressed genes comparing AD cases to matched controls for both sexes together and each sex separately. We used the GOrilla software to search for enriched pathways among the differentially expressed genes. Motivated by the male/female difference in incidence, we studied genes on the X-chromosome, focusing on genes in the pseudoautosomal region (PAR) and on genes that are heterogeneous across individuals or tissues for X-inactivation. We validated findings by analyzing bulk AD datasets from the cortex in the Gene Expression Omnibus., Results: Our results resolve a contradiction in the literature, showing that by comparing AD patients to unaffected controls, excitatory neurons have more differentially expressed genes than do other cell types. Synaptic transmission and related pathways are altered in a sex-specific analysis of excitatory neurons. PAR genes and X-chromosome heterogeneous genes, including, for example, BEX1 and ELK1 , may contribute to the difference in sex incidence of Alzheimer's disease. GRIN1 , stood out as an overexpressed autosomal gene in cases versus controls in all three single-cell datasets and as a functional candidate gene contributing to pathways upregulated in cases., Discussion: Taken together, these results point to a potential linkage between two longstanding questions concerning AD pathogenesis, involving which cell type is the most important and why females have a higher incidence than males., Highlights: By reanalyzing three, published, single-cell RNAseq datasets, we resolved a contradiction in the literature and showed that when comparing AD patients to unaffected controls, excitatory neurons have more differentially expressed genes than do other cell types.Further analysis of the published single-cell datasets showed that synaptic transmission and related pathways are altered in a sex-specific analysis of excitatory neurons.Combining analysis of single-cell datasets and publicly available bulk transcriptomics datasets revealed that X-chromosome genes, such as BEX1 , ELK1 , and USP11 , whose X-inactivation status is heterogeneous may contribute to the higher incidence in females of Alzheimer's disease., Competing Interests: E.R. is a co‐founder of MedAware, Metabomed, and Pangea Biomed (divested), and an unpaid member of Pangea Biomed's scientific advisory board. The other authors have no competing interests. Author disclosures are available in the supporting information., (© 2023 The Authors. Alzheimer's & Dementia: Translational Research & Clinical Interventions published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Precision oncology is gradually advancing into mainstream clinical practice, demonstrating significant survival benefits. However, eligibility and response rates remain limited in many cases, calling for better predictive biomarkers., Methods: We present ENLIGHT, a transcriptomics-based computational approach that identifies clinically relevant genetic interactions and uses them to predict a patient's response to a variety of therapies in multiple cancer types without training on previous treatment response data. We study ENLIGHT in two translationally oriented scenarios: personalized oncology (PO), aimed at prioritizing treatments for a single patient, and clinical trial design (CTD), selecting the most likely responders in a patient cohort., Findings: Evaluating ENLIGHT's performance on 21 blinded clinical trial datasets in the PO setting, we show that it can effectively predict a patient's treatment response across multiple therapies and cancer types. Its prediction accuracy is better than previously published transcriptomics-based signatures and is comparable with that of supervised predictors developed for specific indications and drugs. In combination with the interferon-γ signature, ENLIGHT achieves an odds ratio larger than 4 in predicting response to immune checkpoint therapy. In the CTD scenario, ENLIGHT can potentially enhance clinical trial success for immunotherapies and other monoclonal antibodies by excluding non-responders while overall achieving more than 90% of the response rate attainable under an optimal exclusion strategy., Conclusions: ENLIGHT demonstrably enhances the ability to predict therapeutic response across multiple cancer types from the bulk tumor transcriptome., Funding: This research was supported in part by the Intramural Research Program, NIH and by the Israeli Innovation Authority., Competing Interests: Declaration of interests G.D., E.D.S., E. Elis, D.S.B.-Z., O.T., E.M., E. Elalouf, B.T., P.V., T.B., and R.A. are employees of Pangea Biomed. I.M. is a paid consultant of Pangea Biomed. E.S. is the Chairman of the Board of Pangea Biomed. E.R. is a co-founder of MedAware, Metabomed, and Pangea Biomed (divested) and an unpaid member of Pangea Biomed’s scientific advisory board. Z.R. is a co-founder of Pangea Biomed and an unpaid member of its scientific advisory board. R.B. is a member of Pangea Biomed’s scientific advisory board., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Nonalcoholic steatohepatitis (NASH)-induced hepatocellular carcinoma (HCC) and its precursor, nonalcoholic fatty liver disease (NAFLD) are an unmet health issue due to widespread obesity. We assessed copy number changes of genes associated with hepatocarcinogenesis and oxidative pathways at a single-cell level. Eleven patients with NASH-HCC and 11 patients with NAFLD were included. Eight probes were analyzed using multiplex interphase fluorescence in situ hybridization (miFISH), single-cell imaging and phylogenetic tree modelling: Telomerase reverse transcriptase (TERT), C-Myc (MYC), hepatocyte growth factor receptor tyrosine kinase (MET), tumor protein 53 (TP53), cyclin D1 (CCND1), human epidermal growth factor receptor 2 (HER2), the fragile histidine triad gene (FHIT) and FRA16D oxidoreductase (WWOX). Each NASH-HCC tumor had up to 14 distinct clonal signal patterns indicating multiclonality, which correlated with high tumor grade. Changes frequently observed were TP53 losses, 45%; MYC gains, 36%; WWOX losses, 36%; and HER2 gains, 18%. Whole-genome duplications were frequent (82%) with aberrant tetraploid cells evolving from diploid ancestors. Non-tumorous NAFLD/NASH biopsies did not harbor clonal copy number changes. Fine mapping of NASH-HCC using single-cell multiplex FISH shows that branched tumor evolution involves genome duplication and that multiclonality increases with tumor grade. The loss of oxidoreductase WWOX and HER2 gains could be potentially associated with NASH-induced hepatocellular carcinoma., (© 2022. The Author(s).)

Cancer occurs more frequently in men while autoimmune diseases (AIDs) occur more frequently in women. To explore whether these sex biases have a common basis, we collected 167 AID incidence studies from many countries for tissues that have both a cancer type and an AID that arise from that tissue. Analyzing a total of 182 country-specific, tissue-matched cancer-AID incidence rate sex bias data pairs, we find that, indeed, the sex biases observed in the incidence of AIDs and cancers that occur in the same tissue are positively correlated across human tissues. The common key factor whose levels across human tissues are most strongly associated with these incidence rate sex biases is the sex bias in the expression of the 37 genes encoded in the mitochondrial genome.

Importance: The recent successes of poly-ADP ribose polymerase (PARP) inhibitors and belzutifan support germline genetic data as an exciting, accessible source for biomarkers in cancer treatment. This study hypothesizes, however, that most oncology clinical trials using germline data largely prioritize BRCA1/2 as biomarkers and PARP inhibitors as therapy., Objective: To characterize past and ongoing oncology trials that use germline data., Design, Setting, and Participants: This retrospective cross-sectional study of oncology trials used the Informa Trialtrove database to evaluate trial attributes. Trials using germline information (including the terms germline, hereditary, or inherited in the title, treatment plan, interventions, end points, objectives, results, or notes) and conducted globally between December 1, 1990, and April 4, 2022 (data freeze date), were included., Main Outcomes and Measures: Trials by cancer type, phase, participants, sponsor type, end points, outcomes, and locations were described. Associated biomarkers and mechanisms of action for studied therapeutic interventions were counted. How germline data in trial inclusion and exclusion criteria are associated with end points, outcomes, and enrollment were also examined., Results: A total of 887 of 84 297 (1.1%) oncology clinical trials in the Trialtrove database that use germline data were identified. Most trials were conducted in cancer types where PARP inhibitors are already approved. A total of 74.8% (672) of trials were performed in the phase 2 setting or above. Trials were primarily sponsored by industry (523 trials [59.0%]), academia (382 trials [43.1%]), and the government (274 trials [30.9%]), where trials may have multiple sponsor types. Among 343 trials using germline data with outcomes in Trialtrove, 180 (52.5%) reported meeting primary end points. Although BRCA1/2 are the most frequent biomarkers seen (BRCA1, 224 trials [25.3%]; BRCA2, 228 trials [25.7%]), trials also examine pharmacogenomic variants and germline mediators of somatic biomarkers. PARP inhibitors or immunotherapy were tested in 69.9% of trials; PARP inhibition was the most frequently studied mechanism (367 trials [41.4%]). An overwhelming number of trials using germline data were conducted in the US, Canada, and Europe vs other countries, mirroring disparities in cancer genetics data. Germline data in inclusion and exclusion criteria are associated with altered end point, outcomes, and enrollment compared with oncology trials with no germline data use. Examples of inclusion and exclusion criteria regarding germline data that may unintentionally exclude patients were identified., Conclusions and Relevance: These findings suggest that for germline biomarkers to gain clinical relevance, trials must expand biomarkers, therapies, and populations under study.

Computational identification and quantification of distinct microbes from high throughput sequencing data is crucial for our understanding of human health. Existing methods either use accurate but computationally expensive alignment-based approaches or less accurate but computationally fast alignment-free approaches, which often fail to correctly assign reads to genomes. Here we introduce CAMMiQ, a combinatorial optimization framework to identify and quantify distinct genomes (specified by a database) in a metagenomic dataset. As a key methodological innovation, CAMMiQ uses substrings of variable length and those that appear in two genomes in the database, as opposed to the commonly used fixed-length, unique substrings. These substrings allow to accurately decouple mixtures of highly similar genomes resulting in higher accuracy than the leading alternatives, without requiring additional computational resources, as demonstrated on commonly used benchmarking datasets. Importantly, we show that CAMMiQ can distinguish closely related bacterial strains in simulated metagenomic and real single-cell metatranscriptomic data., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Vaccines have allowed for a significant decrease in COVID-19 risk, and new antiviral medications can prevent disease progression if given early in the course of the disease. The rapid and accurate estimation of the risk of severe disease in new patients is needed to prioritize the treatment of high-risk patients and maximize lives saved. We used electronic health records from 101,039 individuals infected with SARS-CoV-2, since the beginning of the pandemic and until 30 November 2021, in a national healthcare organization in Israel to build logistic models estimating the probability of subsequent hospitalization and death of newly infected patients based on a few major risk factors (age, sex, body mass index, hemoglobin A1C, kidney function, and the presence of hypertension, pulmonary disease, and malignancy) and the number of BNT162b2 mRNA vaccine doses received. The model's performance was assessed by 10-fold cross-validation: the area under the curve was 0.889 for predicting hospitalization and 0.967 for predicting mortality. A total of 50%, 80%, and 90% of death events could be predicted with respective specificities of 98.6%, 95.2%, and 91.2%. These models enable the rapid identification of individuals at high risk for hospitalization and death when infected, and they can be used to prioritize patients to receive scarce medications or booster vaccination. The calculator is available online.

The FDA has recently approved a high tumor mutational burden (TMB-high) biomarker, defined by ≥10 mutations/Mb, for the treatment of solid tumors with pembrolizumab, an immune checkpoint inhibitor (ICI) that targets PD1. However, recent studies have shown that this TMB-high biomarker is only able to stratify ICI responders in a subset of cancer types, and the mechanisms underlying this observation have remained unknown. The tumor immune microenvironment (TME) may modulate the stratification power of TMB (termed TMB power), determining if it will be predictive of ICI response in a given cancer type. To systematically study this hypothesis, we inferred the levels of 31 immune-related factors characteristic of the TME of different cancer types in The Cancer Genome Atlas. Integration of this information with TMB and response data of 2,277 patients treated with anti-PD1 identified key immune factors that determine TMB power across 14 different cancer types. We find that high levels of M1 macrophages and low resting dendritic cells in the TME characterized cancer types with high TMB power. A model based on these two immune factors strongly predicted TMB power in a given cancer type during cross-validation and testing (Spearman Rho = 0.76 and 1, respectively). Using this model, we predicted the TMB power in nine additional cancer types, including rare cancers, for which TMB and ICI response data are not yet publicly available. Our analysis indicates that TMB-high may be highly predictive of ICI response in cervical squamous cell carcinoma, suggesting that such a study should be prioritized., Significance: This study uncovers immune-related factors that may modulate the relationship between high tumor mutational burden and ICI response, which can help prioritize cancer types for clinical trials., (©2022 The Authors; Published by the American Association for Cancer Research.)

Objective: Hepatocellular carcinoma (HCC) represents a typical inflammation-associated cancer. Tissue resident innate lymphoid cells (ILCs) have been suggested to control tumour surveillance. Here, we studied how the local cytokine milieu controls ILCs in HCC., Design: We performed bulk RNA sequencing of HCC tissue as well as flow cytometry and single-cell RNA sequencing of enriched ILCs from non-tumour liver, margin and tumour core derived from 48 patients with HCC. Simultaneous measurement of protein and RNA expression at the single-cell level (AbSeq) identified precise signatures of ILC subgroups. In vitro culturing of ILCs was used to validate findings from in silico analysis. Analysis of RNA-sequencing data from large HCC cohorts allowed stratification and survival analysis based on transcriptomic signatures., Results: RNA sequencing of tumour, non-tumour and margin identified tumour-dependent gradients, which were associated with poor survival and control of ILC plasticity. Single-cell RNA sequencing and flow cytometry of ILCs from HCC livers identified natural killer (NK)-like cells in the non-tumour tissue, losing their cytotoxic profile as they transitioned into tumour ILC1 and NK-like-ILC3 cells. Tumour ILC composition was mediated by cytokine gradients that directed ILC plasticity towards activated tumour ILC2s. This was liver-specific and not seen in ILCs from peripheral blood mononuclear cells. Patients with high ILC2/ILC1 ratio expressed interleukin-33 in the tumour that promoted ILC2 generation, which was associated with better survival., Conclusion: Our results suggest that the tumour cytokine milieu controls ILC composition and HCC outcome. Specific changes of cytokines modify ILC composition in the tumour by inducing plasticity and alter ILC function., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Immune protection following either vaccination or infection with SARS-CoV-2 decreases over time. Objective: We aim to describe clinical and sociodemographic characteristics associated with COVID-19 infection at least 14 days after booster vaccination in the Israeli population. Methods: We conducted a population-based study among adult members of Leumit Health Services (LHS) in Israel. Nasopharyngeal swabs were examined for SARS-CoV-2 by real-time RT-PCR. The hematological and biochemical parameters in the peripheral blood before booster vaccination were evaluated. Results: Between 1 February 2021 and 30 November 2021, 136,683 individuals in LHS were vaccinated with a booster (third dose) of the BNT162b2 vaccine. Of these, 1171 (0.9%) were diagnosed with COVID-19 by testing positive for SARS-CoV-2 RT-PCR at least >14 days after the booster vaccination. The COVID-19-positive group was characterized by higher rates of chronic kidney disease than the matched COVID-19-negative group (43 (3.7%) vs. 3646 (2.7%); p = 0.039). Anemia, lower peripheral blood lymphocytes, monocytes, basophils, C3 Complement, cholesterol, and prothrombin time were also associated with COVID-19 after booster vaccination. Conclusion: People with chronic kidney disease and anemia should be included in possible future annual SARS-CoV-2 vaccination recommendations.

The tumor microenvironment (TME) is a complex mixture of cell types whose interactions affect tumor growth and clinical outcome. To discover such interactions, we developed CODEFACS (COnfident DEconvolution For All Cell Subsets), a tool deconvolving cell type-specific gene expression in each sample from bulk expression, and LIRICS (Ligand-Receptor Interactions between Cell Subsets), a statistical framework prioritizing clinically relevant ligand-receptor interactions between cell types from the deconvolved data. We first demonstrate the superiority of CODEFACS versus the state-of-the-art deconvolution method CIBERSORTx. Second, analyzing The Cancer Genome Atlas, we uncover cell type-specific ligand-receptor interactions uniquely associated with mismatch-repair deficiency across different cancer types, providing additional insights into their enhanced sensitivity to anti-programmed cell death protein 1 (PD-1) therapy compared with other tumors with high neoantigen burden. Finally, we identify a subset of cell type-specific ligand-receptor interactions in the melanoma TME that stratify survival of patients receiving anti-PD-1 therapy better than some recently published bulk transcriptomics-based methods., Significance: This work presents two new computational methods that can deconvolve a large collection of bulk tumor gene expression profiles into their respective cell type-specific gene expression profiles and identify cell type-specific ligand-receptor interactions predictive of response to immune-checkpoint blockade therapy. This article is highlighted in the In This Issue feature, p. 873., (©2022 American Association for Cancer Research.)

Mining a large cohort of single-cell transcriptomics data, here we employ combinatorial optimization techniques to chart the landscape of optimal combination therapies in cancer. We assume that each individual therapy can target any one of 1269 genes encoding cell surface receptors, which may be targets of CAR-T, conjugated antibodies or coated nanoparticle therapies. We find that in most cancer types, personalized combinations composed of at most four targets are then sufficient for killing at least 80% of tumor cells while sparing at least 90% of nontumor cells in the tumor microenvironment. However, as more stringent and selective killing is required, the number of targets needed rises rapidly. Emerging individual targets include PTPRZ1 for brain and head and neck cancers and EGFR in multiple tumor types. In sum, this study provides a computational estimate of the identity and number of targets needed in combination to target cancers selectively and precisely., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Immune protection following either vaccination or infection with SARS-CoV-2 is thought to decrease over time. We designed a retrospective study, conducted at Leumit Health Services in Israel, to determine the kinetics of SARS-CoV-2 IgG antibodies following administration of two doses of BNT162b2 vaccine, or SARS-CoV-2 infection in unvaccinated individuals. Antibody titers were measured between 31 January 2021, and 31 July 2021 in two mutually exclusive groups: (i) vaccinated individuals who received two doses of BNT162b2 vaccine and had no history of previous infection with COVID-19 and (ii) SARS-CoV-2 convalescents who had not received the vaccine. A total of 2653 individuals fully vaccinated by two doses of vaccine during the study period and 4361 convalescent patients were included. Higher SARS-CoV-2 IgG antibody titers were observed in vaccinated individuals (median 1581 AU/mL IQR [533.8-5644.6]) after the second vaccination than in convalescent individuals (median 355.3 AU/mL IQR [141.2-998.7]; p < 0.001). In vaccinated subjects, antibody titers decreased by up to 38% each subsequent month while in convalescents they decreased by less than 5% per month. Six months after BNT162b2 vaccination 16.1% subjects had antibody levels below the seropositivity threshold of <50 AU/mL, while only 10.8% of convalescent patients were below <50 AU/mL threshold after 9 months from SARS-CoV-2 infection. This study demonstrates individuals who received the Pfizer-BioNTech mRNA vaccine have different kinetics of antibody levels compared to patients who had been infected with the SARS-CoV-2 virus, with higher initial levels but a much faster exponential decrease in the first group.

Motivation: Computational reconstruction of clonal evolution in cancers has become a crucial tool for understanding how tumors initiate and progress and how this process varies across patients. The field still struggles, however, with special challenges of applying phylogenetic methods to cancers, such as the prevalence and importance of copy number alteration (CNA) and structural variation events in tumor evolution, which are difficult to profile accurately by prevailing sequencing methods in such a way that subsequent reconstruction by phylogenetic inference algorithms is accurate., Results: In this work, we develop computational methods to combine sequencing with multiplex interphase fluorescence in situ hybridization to exploit the complementary advantages of each technology in inferring accurate models of clonal CNA evolution accounting for both focal changes and aneuploidy at whole-genome scales. By integrating such information in an integer linear programming framework, we demonstrate on simulated data that incorporation of FISH data substantially improves accurate inference of focal CNA and ploidy changes in clonal evolution from deconvolving bulk sequence data. Analysis of real glioblastoma data for which FISH, bulk sequence and single cell sequence are all available confirms the power of FISH to enhance accurate reconstruction of clonal copy number evolution in conjunction with bulk and optionally single-cell sequence data., Availability and Implementation: Source code is available on Github at https://github.com/CMUSchwartzLab/FISH&#95;deconvolution., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objectives: To determine whether time elapsed since the second injection of the Pfizer-BioNTech BNT162b2 mRNA vaccine was significantly associated with the risk of covid-19 infection after vaccination in people who received two vaccine injections., Design: Test negative design study., Setting: Electronic health records of a large state mandated healthcare organisation, Israel., Participants: Adults aged ≥18 years who had received a reverse transcription polymerase chain reaction (RT-PCR) test between 15 May 2021 and 17 September 2021, at least three weeks after their second vaccine injection, had not received a third vaccine injection, and had no history of covid-19 infection., Main Outcome Measures: Positive result for the RT-PCR test. Individuals who tested positive for SARS-CoV-2 and controls were matched for week of testing, age category, and demographic group (ultra-orthodox Jews, individuals of Arab ancestry, and the general population). Conditional logistic regression was adjusted for age, sex, socioeconomic status, and comorbid conditions., Results: 83 057 adults received an RT-PCR test for SARS-CoV-2 during the study period and 9.6% had a positive result. Time elapsed since the vaccine injection was significantly longer in individuals who tested positive (P<0.001). Adjusted odds ratio for infection at time intervals >90 days since vaccination were significantly increased compared with the reference of <90 days: 2.37 (95% confidence interval 1.67 to 3.36) for 90-119 days, 2.66 (1.94 to 3.66) for 120-149 days, 2.82 (2.07 to 3.84) for 150-179 days, and 2.82 (2.07 to 3.85) for ≥180 days (P<0.001 for each 30 day interval)., Conclusions: In this large population of adults tested for SARS-CoV-2 by RT-PCR after two doses of mRNA BNT162b2 vaccine, a gradual increase in the risk of infection was seen for individuals who received their second vaccine dose after at least 90 days., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: support from Leumit Health Services and the Intramural Research Program, National Institutes of Health, National Cancer Institute, Centre for Cancer Research for the submitted work; the authors declare no competing interests; AI, EMe, AAS, YS, IG, AG-C, EMa,and SV are employees of Leumit Health Services; all authors declare that they have no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Engineered versions of adeno-associated virus (AAV) are commonly used in gene therapy but evidence revealing a potential oncogenic role of natural AAV in hepatocellular carcinoma (HCC) has raised concerns. The frequency of potentially oncogenic integrations has been reported in only a few populations. AAV infection and host genome integration in another type of liver cancer, cholangiocarcinoma (CCA), has been studied only in one cohort. All reported oncogenic AAV integrations in HCC come from strains resembling the fully sequenced AAV2 and partly sequenced AAV13. When AAV integration occurs, only a fragment of the AAV genome is detectable in later DNA or RNA sequencing. The integrated fragment is typically from the 3' end of the AAV genome, and this positional bias has been only partly explained. Three research groups searched for evidence of AAV integration in HCC RNAseq samples in the Cancer Genome Atlas (TCGA) but reported conflicting results., Results: We collected and analyzed whole transcriptome and viral capture DNA sequencing in paired tumor and non-tumor samples from two liver cancer Asian cohorts from Thailand (N = 147, 47 HCC and 100 intrahepatic cholangiocarcinoma (iCCA)) and Mongolia (N = 70, all HCC). We found only one HCC patient with a potentially oncogenic integration of AAV, in contrast to higher frequency reported in European patients. There were no oncogenic AAV integrations in iCCA patients. AAV genomic segments are present preferentially in the non-tumor samples of Thai patients. By analyzing the AAV genome positions of oncogenic and non-oncogenic integrated fragments, we found that almost all the putative oncogenic integrations overlap the X gene, which is present and functional only in the strain AAV2 among all fully sequenced strains. This gene content difference could explain why putative oncogenic integrations from other AAV strains have not been reported. We resolved the discrepancies in previous analyses of AAV presence in TCGA HCC samples and extended it to CCA. There are 12 TCGA samples with an AAV segment and none are in Asian patients. AAV segments are present in preferentially in TCGA non-tumor samples, like what we observed in the Thai patients., Conclusions: Our findings suggest a minimal AAV risk of hepatocarcinogenesis in Asian liver cancer patients. The partial genome presence and positional bias of AAV integrations into the human genome has complicated analysis of possible roles of AAV in liver cancer., (© 2021. The Author(s).)

Competing Interests: Eytan RuppinStock and Other Ownership Interests: Medaware Ltd, Metabomed LtdPatents, Royalties, Other Intellectual Property: Patent applications have been submitted by Tel-Aviv University, University of Maryland, and NCI for synthetic lethality and expression of deconvolution computational analysis approachesUncompensated Relationships: Pangea TherapeuticsNo other potential conflicts of interest were reported.

Background: The DNA sequences encoding ribosomal RNA genes (rRNAs) are commonly used as markers to identify species, including in metagenomics samples that may combine many organismal communities. The 16S small subunit ribosomal RNA (SSU rRNA) gene is typically used to identify bacterial and archaeal species. The nuclear 18S SSU rRNA gene, and 28S large subunit (LSU) rRNA gene have been used as DNA barcodes and for phylogenetic studies in different eukaryote taxonomic groups. Because of their popularity, the National Center for Biotechnology Information (NCBI) receives a disproportionate number of rRNA sequence submissions and BLAST queries. These sequences vary in quality, length, origin (nuclear, mitochondria, plastid), and organism source and can represent any region of the ribosomal cistron., Results: To improve the timely verification of quality, origin and loci boundaries, we developed Ribovore, a software package for sequence analysis of rRNA sequences. The ribotyper and ribosensor programs are used to validate incoming sequences of bacterial and archaeal SSU rRNA. The ribodbmaker program is used to create high-quality datasets of rRNAs from different taxonomic groups. Key algorithmic steps include comparing candidate sequences against rRNA sequence profile hidden Markov models (HMMs) and covariance models of rRNA sequence and secondary-structure conservation, as well as other tests. Nine freely available blastn rRNA databases created and maintained with Ribovore are used for checking incoming GenBank submissions and used by the blastn browser interface at NCBI. Since 2018, Ribovore has been used to analyze more than 50 million prokaryotic SSU rRNA sequences submitted to GenBank, and to select at least 10,435 fungal rRNA RefSeq records from type material of 8350 taxa., Conclusion: Ribovore combines single-sequence and profile-based methods to improve GenBank processing and analysis of rRNA sequences. It is a standalone, portable, and extensible software package for the alignment, classification and validation of rRNA sequences. Researchers planning on submitting SSU rRNA sequences to GenBank are encouraged to download and use Ribovore to analyze their sequences prior to submission to determine which sequences are likely to be automatically accepted into GenBank., (© 2021. The Author(s).)

Background: Until coronavirus disease 2019 (COVID-19) drugs specifically developed to treat COVID-19 become more widely accessible, it is crucial to identify whether existing medications have a protective effect against severe disease. Toward this objective, we conducted a large population study in Clalit Health Services (CHS), the largest healthcare provider in Israel, insuring over 4.7 million members., Methods: Two case-control matched cohorts were assembled to assess which medications, acquired in the last month, decreased the risk of COVID-19 hospitalization. Case patients were adults aged 18 to 95 hospitalized for COVID-19. In the first cohort, five control patients, from the general population, were matched to each case (n=6202); in the second cohort, two non-hospitalized SARS-CoV-2 positive control patients were matched to each case (n=6919). The outcome measures for a medication were: odds ratio (OR) for hospitalization, 95% confidence interval (CI), and the p-value, using Fisher's exact test. False discovery rate was used to adjust for multiple testing., Results: Medications associated with most significantly reduced odds for COVID-19 hospitalization include: ubiquinone (OR=0.185, 95% CI [0.058 to 0.458], p<0.001), ezetimibe (OR=0.488, 95% CI [0.377 to 0.622], p<0.001), rosuvastatin (OR=0.673, 95% CI [0.596 to 0.758], p<0.001), flecainide (OR=0.301, 95% CI [0.118 to 0.641], p<0.001), and vitamin D (OR=0.869, 95% CI [0.792 to 0.954], p<0.003). Remarkably, acquisition of artificial tears, eye care wipes, and several ophthalmological products were also associated with decreased risk for hospitalization., Conclusions: Ubiquinone, ezetimibe, and rosuvastatin, all related to the cholesterol synthesis pathway were associated with reduced hospitalization risk. These findings point to a promising protective effect which should be further investigated in controlled, prospective studies., Funding: This research was supported in part by the Intramural Research Program of the National Institutes of Health, NCI., Competing Interests: AI, AS, AC, KC, SS, ES, IF, AT, GL, ER No competing interests declared

In this work we develop a novel algorithm for reconstructing the genomes of ancestral individuals, given genotype or sequence data from contemporary individuals and an extended pedigree of family relationships. A pedigree with complete genomes for every individual enables the study of allele frequency dynamics and haplotype diversity across generations, including deviations from neutrality such as transmission distortion. When studying heritable diseases, ancestral haplotypes can be used to augment genome-wide association studies and track disease inheritance patterns. The building blocks of our reconstruction algorithm are segments of Identity-By-Descent (IBD) shared between two or more genotyped individuals. The method alternates between identifying a source for each IBD segment and assembling IBD segments placed within each ancestral individual. Unlike previous approaches, our method is able to accommodate complex pedigree structures with hundreds of individuals genotyped at millions of SNPs. We apply our method to an Old Order Amish pedigree from Lancaster, Pennsylvania, whose founders came to North America from Europe during the early 18th century. The pedigree includes 1338 individuals from the past 12 generations, 394 with genotype data. The motivation for reconstruction is to understand the genetic basis of diseases segregating in the family through tracking haplotype transmission over time. Using our algorithm thread, we are able to reconstruct an average of 224 ancestral individuals per chromosome. For these ancestral individuals, on average we reconstruct 79% of their haplotypes. We also identify a region on chromosome 16 that is difficult to reconstruct-we find that this region harbors a short Amish-specific copy number variation and the gene HYDIN. thread was developed for endogamous populations, but can be applied to any extensive pedigree with the recent generations genotyped. We anticipate that this type of practical ancestral reconstruction will become more common and necessary to understand rare and complex heritable diseases in extended families., Competing Interests: The authors have declared that no competing interests exist.

Modifier genes are believed to account for the clinical variability observed in many Mendelian disorders, but their identification remains challenging due to the limited availability of genomics data from large patient cohorts. Here, we present GENDULF (GENetic moDULators identiFication), one of the first methods to facilitate prediction of disease modifiers using healthy and diseased tissue gene expression data. GENDULF is designed for monogenic diseases in which the mechanism is loss of function leading to reduced expression of the mutated gene. When applied to cystic fibrosis, GENDULF successfully identifies multiple, previously established disease modifiers, including EHF, SLC6A14, and CLCA1. It is then utilized in spinal muscular atrophy (SMA) and predicts U2AF1 as a modifier whose low expression correlates with higher SMN2 pre-mRNA exon 7 retention. Indeed, knockdown of U2AF1 in SMA patient-derived cells leads to increased full-length SMN2 transcript and SMN protein expression. Taking advantage of the increasing availability of transcriptomic data, GENDULF is a novel addition to existing strategies for prediction of genetic disease modifiers, providing insights into disease pathogenesis and uncovering novel therapeutic targets., (© 2020 The Authors. Published under the terms of the CC BY 4.0 license.)

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Prognosis in young patients with breast cancer is generally poor, yet considerable differences in clinical outcomes between individual patients exist. To understand the genetic basis of the disparate clinical courses, tumors were collected from 34 younger women, 17 with good and 17 with poor outcomes, as determined by disease-specific survival during a follow-up period of 17 years. The clinicopathologic parameters of the tumors were complemented with DNA image cytometry profiles, enumeration of copy numbers of eight breast cancer genes by multicolor fluorescence in situ hybridization, and targeted sequence analysis of 563 cancer genes. Both groups included diploid and aneuploid tumors. The degree of intratumor heterogeneity was significantly higher in aneuploid versus diploid cases, and so were gains of the oncogenes MYC and ZNF217. Significantly more copy number alterations were observed in the group with poor outcome. Almost all tumors in the group with long survival were classified as luminal A, whereas triple-negative tumors predominantly occurred in the short survival group. Mutations in PIK3CA were more common in the group with good outcome, whereas TP53 mutations were more frequent in patients with poor outcomes. This study shows that TP53 mutations and the extent of genomic imbalances are associated with poor outcome in younger breast cancer patients and thus emphasize the central role of genomic instability vis-a-vis tumor aggressiveness., (Copyright © 2020 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Carpal tunnel syndrome (CTS) is the most common peripheral nerve entrapment syndrome, affecting a large proportion of the general population. Genetic susceptibility has been implicated in CTS, but the causative genes remain elusive. Here, we report the identification of two mutations in cartilage oligomeric matrix protein (COMP) that segregate with CTS in two large families with or without multiple epiphyseal dysplasia (MED). Both mutations impair the secretion of COMP by tenocytes, but the mutation associated with MED also perturbs its secretion in chondrocytes. Further functional characterization of the CTS-specific mutation reveals similar histological and molecular changes of tendons/ligaments in patients' biopsies and the mouse models. The mutant COMP fails to oligomerize properly and is trapped in the ER, resulting in ER stress-induced unfolded protein response and cell death, leading to inflammation, progressive fibrosis and cell composition change in tendons/ligaments. The extracellular matrix (ECM) organization is also altered. Our studies uncover a previously unrecognized mechanism in CTS pathogenesis.

Motivation: Recent advances in single-cell sequencing (SCS) offer an unprecedented insight into tumor emergence and evolution. Principled approaches to tumor phylogeny reconstruction via SCS data are typically based on general computational methods for solving an integer linear program, or a constraint satisfaction program, which, although guaranteeing convergence to the most likely solution, are very slow. Others based on Monte Carlo Markov Chain or alternative heuristics not only offer no such guarantee, but also are not faster in practice. As a result, novel methods that can scale up to handle the size and noise characteristics of emerging SCS data are highly desirable to fully utilize this technology., Results: We introduce PhISCS-BnB (phylogeny inference using SCS via branch and bound), a branch and bound algorithm to compute the most likely perfect phylogeny on an input genotype matrix extracted from an SCS dataset. PhISCS-BnB not only offers an optimality guarantee, but is also 10-100 times faster than the best available methods on simulated tumor SCS data. We also applied PhISCS-BnB on a recently published large melanoma dataset derived from the sublineages of a cell line involving 20 clones with 2367 mutations, which returned the optimal tumor phylogeny in <4 h. The resulting phylogeny agrees with and extends the published results by providing a more detailed picture on the clonal evolution of the tumor., Availability and Implementation: https://github.com/algo-cancer/PhISCS-BnB., Supplementary Information: Supplementary data are available at Bioinformatics online., (Published by Oxford University Press 2020.)

The COVID-19 pandemic caused by SARS-CoV-2 has is a global health challenge. Angiotensin-converting enzyme 2 (ACE2) is the host receptor for SARS-CoV-2 entry. Recent studies have suggested that patients with hypertension and diabetes treated with ACE inhibitors (ACEIs) or angiotensin receptor blockers have a higher risk of COVID-19 infection as these drugs could upregulate ACE2, motivating the study of ACE2 modulation by drugs in current clinical use. Here, we mined published datasets to determine the effects of hundreds of clinically approved drugs on ACE2 expression. We find that ACEIs are enriched for ACE2-upregulating drugs, while antineoplastic agents are enriched for ACE2-downregulating drugs. Vorinostat and isotretinoin are the top ACE2 up/downregulators, respectively, in cell lines. Dexamethasone, a corticosteroid used in treating severe acute respiratory syndrome and COVID-19, significantly upregulates ACE2 both in vitro and in vivo. Further top ACE2 regulators in vivo or in primary cells include erlotinib and bleomycin in the lung and vancomycin, cisplatin, and probenecid in the kidney. Our study provides leads for future work studying ACE2 expression modulators., (© 2020 The Authors. Published under the terms of the CC BY 4.0 license.)

Background: GenBank contains over 3 million viral sequences. The National Center for Biotechnology Information (NCBI) previously made available a tool for validating and annotating influenza virus sequences that is used to check submissions to GenBank. Before this project, there was no analogous tool in use for non-influenza viral sequence submissions., Results: We developed a system called VADR (Viral Annotation DefineR) that validates and annotates viral sequences in GenBank submissions. The annotation system is based on the analysis of the input nucleotide sequence using models built from curated RefSeqs. Hidden Markov models are used to classify sequences by determining the RefSeq they are most similar to, and feature annotation from the RefSeq is mapped based on a nucleotide alignment of the full sequence to a covariance model. Predicted proteins encoded by the sequence are validated with nucleotide-to-protein alignments using BLAST. The system identifies 43 types of "alerts" that (unlike the previous BLAST-based system) provide deterministic and rigorous feedback to researchers who submit sequences with unexpected characteristics. VADR has been integrated into GenBank's submission processing pipeline allowing for viral submissions passing all tests to be accepted and annotated automatically, without the need for any human (GenBank indexer) intervention. Unlike the previous submission-checking system, VADR is freely available (https://github.com/nawrockie/vadr) for local installation and use. VADR has been used for Norovirus submissions since May 2018 and for Dengue virus submissions since January 2019. Since March 2020, VADR has also been used to check SARS-CoV-2 sequence submissions. Other viruses with high numbers of submissions will be added incrementally., Conclusion: VADR improves the speed with which non-flu virus submissions to GenBank can be checked and improves the content and quality of the GenBank annotations. The availability and portability of the software allow researchers to run the GenBank checks prior to submitting their viral sequences, and thereby gain confidence that their submissions will be accepted immediately without the need to correspond with GenBank staff. Reciprocally, the adoption of VADR frees GenBank staff to spend more time on services other than checking routine viral sequence submissions.

Characterizing intratumor heterogeneity (ITH) is crucial to understanding cancer development, but it is hampered by limits of available data sources. Bulk DNA sequencing is the most common technology to assess ITH, but involves the analysis of a mixture of many genetically distinct cells in each sample, which must then be computationally deconvolved. Single-cell sequencing is a promising alternative, but its limitations-for example, high noise, difficulty scaling to large populations, technical artifacts, and large data sets-have so far made it impractical for studying cohorts of sufficient size to identify statistically robust features of tumor evolution. We have developed strategies for deconvolution and tumor phylogenetics combining limited amounts of bulk and single-cell data to gain some advantages of single-cell resolution with much lower cost, with specific focus on deconvolving genomic copy number data. We developed a mixed membership model for clonal deconvolution via non-negative matrix factorization balancing deconvolution quality with similarity to single-cell samples via an associated efficient coordinate descent algorithm. We then improve on that algorithm by integrating deconvolution with clonal phylogeny inference, using a mixed integer linear programming model to incorporate a minimum evolution phylogenetic tree cost in the problem objective. We demonstrate the effectiveness of these methods on semisimulated data of known ground truth, showing improved deconvolution accuracy relative to bulk data alone.

To improve our understanding of longstanding disparities in incidence and mortality in lung cancer across ancestry, we performed a systematic comparative analysis of molecular features in tumors from African Americans (AAs) and European Americans (EAs). We find that lung squamous cell carcinoma tumors from AAs exhibit higher genomic instability-the proportion of non-diploid genome-aggressive molecular features such as chromothripsis and higher homologous recombination deficiency (HRD). In The Cancer Genome Atlas, we demonstrate that high genomic instability, HRD and chromothripsis among tumors from AAs is found across many cancer types. The prevalence of germline HRD (that is, the total number of pathogenic variants in homologous recombination genes) is higher in tumors from AAs, suggesting that the somatic differences observed have genetic ancestry origins. We also identify AA-specific copy-number-based arm-, focal- and gene-level recurrent features in lung cancer, including higher frequencies of PTEN deletion and KRAS amplification. These results highlight the importance of including under-represented populations in genomics research., (© 2020. The Author(s), under exclusive licence to Springer Nature America, Inc.)

The phenotypic effect of perturbing a gene's activity depends on the activity level of other genes, reflecting the notion that phenotypes are emergent properties of a network of functionally interacting genes. In the context of cancer, contemporary investigations have primarily focused on just one type of functional relationship between two genes-synthetic lethality (SL). Here, we define the more general concept of "survival-associated pairwise gene expression states" (SPAGEs) as gene pairs whose joint expression levels are associated with survival. We describe a data-driven approach called SPAGE-finder that when applied to The Cancer Genome Atlas (TCGA) data identified 71,946 SPAGEs spanning 12 distinct types, only a minority of which are SLs. The detected SPAGEs explain cancer driver genes' tissue specificity and differences in patients' response to drugs and stratify breast cancer tumors into refined subtypes. These results expand the scope of cancer SPAGEs and lay a conceptual basis for future studies of SPAGEs and their translational applications., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Background: A single variant in NAA10 (c.471+2T>A), the gene encoding N-acetyltransferase 10, has been associated with Lenz microphthalmia syndrome. In this study, we aimed to identify causative variants in families with syndromic X-linked microphthalmia., Methods: Three families, including 15 affected individuals with syndromic X-linked microphthalmia, underwent analyses including linkage analysis, exome sequencing and targeted gene sequencing. The consequences of two identified variants in NAA10 were evaluated using quantitative PCR and RNAseq., Results: Genetic linkage analysis in family 1 supported a candidate region on Xq27-q28, which included NAA10 . Exome sequencing identified a hemizygous NAA10 polyadenylation signal (PAS) variant, chrX:153,195,397T>C, c.*43A>G, which segregated with the disease. Targeted sequencing of affected males from families 2 and 3 identified distinct NAA10 PAS variants, chrX:g.153,195,401T>C, c.*39A>G and chrX:g.153,195,400T>C, c.*40A>G. All three variants were absent from gnomAD. Quantitative PCR and RNAseq showed reduced NAA10 mRNA levels and abnormal 3' UTRs in affected individuals. Targeted sequencing of NAA10 in 376 additional affected individuals failed to identify variants in the PAS., Conclusion: These data show that PAS variants are the most common variant type in NAA10 -associated syndromic microphthalmia, suggesting reduced RNA is the molecular mechanism by which these alterations cause microphthalmia/anophthalmia. We reviewed recognised variants in PAS associated with Mendelian disorders and identified only 23 others, indicating that NAA10 harbours more than 10% of all known PAS variants. We hypothesise that PAS in other genes harbour unrecognised pathogenic variants associated with Mendelian disorders. The systematic interrogation of PAS could improve genetic testing yields., Competing Interests: Competing interests: LGB receives royalties from Genentech Corp, is an advisor to the Illumina Corp, received honoraria from Wiley-Blackwell and receives honoraria from Cold Spring Harbor Press. DNC is in receipt of funding from Qiagen Inc through a License Agreement with Cardiff University. AMS receives honoraria from Wiley-Blackwell, Inc, Oxford University Press and UptoDate, Inc., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Caspase activation and recruitment domain 11 (CARD11) encodes a scaffold protein in lymphocytes that links antigen receptor engagement with downstream signaling to nuclear factor κB, c-Jun N-terminal kinase, and mechanistic target of rapamycin complex 1. Germline CARD11 mutations cause several distinct primary immune disorders in human subjects, including severe combined immune deficiency (biallelic null mutations), B-cell expansion with nuclear factor κB and T-cell anergy (heterozygous, gain-of-function mutations), and severe atopic disease (loss-of-function, heterozygous, dominant interfering mutations), which has focused attention on CARD11 mutations discovered by using whole-exome sequencing., Objectives: We sought to determine the molecular actions of an extended allelic series of CARD11 and to characterize the expanding range of clinical phenotypes associated with heterozygous CARD11 loss-of-function alleles., Methods: Cell transfections and primary T-cell assays were used to evaluate signaling and function of CARD11 variants., Results: Here we report on an expanded cohort of patients harboring novel heterozygous CARD11 mutations that extend beyond atopy to include other immunologic phenotypes not previously associated with CARD11 mutations. In addition to (and sometimes excluding) severe atopy, heterozygous missense and indel mutations in CARD11 presented with immunologic phenotypes similar to those observed in signal transducer and activator of transcription 3 loss of function, dedicator of cytokinesis 8 deficiency, common variable immunodeficiency, neutropenia, and immune dysregulation, polyendocrinopathy, enteropathy, X-linked-like syndrome. Pathogenic variants exhibited dominant negative activity and were largely confined to the CARD or coiled-coil domains of the CARD11 protein., Conclusion: These results illuminate a broader phenotypic spectrum associated with CARD11 mutations in human subjects and underscore the need for functional studies to demonstrate that rare gene variants encountered in expected and unexpected phenotypes must nonetheless be validated for pathogenic activity., (Published by Elsevier Inc.)