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Key Points Methods for and applications of phylogenetic tree inference have proliferated in studies of cancer genomics. Tumour phylogeny methods have become important tools for making sense of the complexity of emerging tumour genomic data sets, providing new methods for identifying the order and timing of driver mutations. This has led to new insights and controversies about the nature of the evolutionary processes involved in cancer, and has driven novel approaches to prognostic prediction. Tumour phylogeny methods can be broadly partitioned into several classes of study design, with variations in data source, evolutionary model, and inference algorithm in each class. Productive use of tumour phylogeny methods requires a sophisticated understanding of how to align genomic data sources, evolutionary models, and phylogeny algorithms with research questions about tumour evolution. Key problems of the field remain unresolved, including how to make use of various novel and heterogeneous data sources, the development of more sophisticated models and algorithms appropriate to specific mechanisms of tumour evolution, and the generation of methods and standards for statistically rigorous planning and analysis of tumour phylogeny studies. The use of phylogenetics in cancer genomics is increasing owing to a growing appreciation of the importance of evolutionary theory to cancer progression. The authors provide guidance on the design and analysis of tumour phylogeny studies by surveying the range of phylogenetic methods and tools available to the cancer researcher and discussing their key applications and the unsolved problems in the field. Rapid advances in high-throughput sequencing and a growing realization of the importance of evolutionary theory to cancer genomics have led to a proliferation of phylogenetic studies of tumour progression. These studies have yielded not only new insights but also a plethora of experimental approaches, sometimes reaching conflicting or poorly supported conclusions. Here, we consider this body of work in light of the key computational principles underpinning phylogenetic inference, with the goal of providing practical guidance on the design and analysis of scientifically rigorous tumour phylogeny studies. We survey the range of methods and tools available to the researcher, their key applications, and the various unsolved problems, closing with a perspective on the prospects and broader implications of this field.

AbstractObjectivesTo 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.DesignTest negative design study.SettingElectronic health records of a large state mandated healthcare organisation, Israel.ParticipantsAdults 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 measuresPositive 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.Results83 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).ConclusionsIn 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.

We aim to evaluate relationships between the locations and success rates of United States oncology clinical trials by analyzing geographic features such as median income and proportion of practicing oncologists by ZIP code. A dataset of 15,658 trials with at least one site in the 50 states or the District of Columbia was collected by integrating trial outcomes curated in Trialtrove, locations from ClinicalTrials.gov, incomes from the U.S. Census, oncologist locations from the Center for Medicare Services and other sources. We found that ZIP codes in which trials are conducted are skewed away from lower median incomes ( p  = 4.05e-08, Kolmogorov-Smirnov test). When ZIP codes were partitioned into lower, middle and upper terciles of median income, success rates by ZIP code were significantly lower in the low-income range relative to the middle- and higher-income ranges (lowest vs. highest p  < 0.0001, OR 1.13 [1.10–1.16]). Trials conducted in more ZIP codes are significantly more likely to succeed than trials conducted in fewer ZIP codes. We identified candidate ZIP codes with sufficient patient populations and practicing oncologists to support clinical oncology trials but have never had a trial previously.

Homozygous mutations in the CARD9 gene, with a premature termination codon, are associated with chronic mucocutaneous candidiasis in an Iranian family. Dysfunction of CARD9 impairs the innate signaling of dectin-1, an antifungal pattern-recognition receptor. Homozygous mutations in the CARD9 gene are associated with chronic mucocutaneous candidiasis in an Iranian family. Dysfunction of CARD9 impairs the innate signaling of dectin-1, an antifungal pattern-recognition receptor. Chronic mucocutaneous candidiasis is characterized by impaired clearance of fungal infections and results in colonization and infections of the mucosa or skin, predominantly with Candida albicans . 1 , 2 A variety of clinical conditions, such as infection with the human immunodeficiency virus or the use of corticosteroids, favor the development of chronic mucocutaneous candidiasis, but the disease may also be a primary immunodeficiency arising from unknown genetic defects. 1 , 3 In chronic mucocutaneous candidiasis, the most common infections are due to C. albicans; however, patients may also have an increased susceptibility to dermatophytes. 1 , 3 Severe complications rarely develop in patients with chronic . . .

Inferring subject ancestry using genetic data is an important step in genetic association studies, required for dealing with population stratification. It has become more challenging to infer subject ancestry quickly and accurately since large amounts of genotype data, collected from millions of subjects by thousands of studies using different methods, are accessible to researchers from repositories such as the database of Genotypes and Phenotypes (dbGaP) at the National Center for Biotechnology Information (NCBI). Study-reported populations submitted to dbGaP are often not harmonized across studies or may be missing. Widely-used methods for ancestry prediction assume that most markers are genotyped in all subjects, but this assumption is unrealistic if one wants to combine studies that used different genotyping platforms. To provide ancestry inference and visualization across studies, we developed a new method, GRAF-pop, of ancestry prediction that is robust to missing genotypes and allows researchers to visualize predicted population structure in color and in three dimensions. When genotypes are dense, GRAF-pop is comparable in quality and running time to existing ancestry inference methods EIGENSTRAT, FastPCA, and FlashPCA2, all of which rely on principal components analysis (PCA). When genotypes are not dense, GRAF-pop gives much better ancestry predictions than the PCA-based methods. GRAF-pop employs basic geometric and probabilistic methods; the visualized ancestry predictions have a natural geometric interpretation, which is lacking in PCA-based methods. Since February 2018, GRAF-pop has been successfully incorporated into the dbGaP quality control process to identify inconsistencies between study-reported and computationally predicted populations and to provide harmonized population values in all new dbGaP submissions amenable to population prediction, based on marker genotypes. Plots, produced by GRAF-pop, of summary population predictions are available on dbGaP study pages, and the software, is available at https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/Software.cgi.

Five children from two consanguineous families were born with severe congenital neutropenia, prominent venous angiectasia, and congenital heart defects, urogenital abnormalities, or both. All five children had the same mutation in the gene for glucose-6-phosphatase, catalytic subunit 3 ( G6PC3 ). Their neutrophils had increased susceptibility to apoptosis, and the mutation abolished the enzymatic activity of glucose-6-phosphatase. Five children from two consanguineous families who were born with severe congenital neutropenia had the same mutation in the gene for glucose-6-phosphatase, catalytic subunit 3 ( G6PC3 ). Their neutrophils had increased susceptibility to apoptosis, and the mutation abolished the enzymatic activity of glucose-6-phosphatase. Severe congenital neutropenia was described more than 50 years ago by Kostmann, 1 , 2 and subsequently the disorder was found to consist of a heterogeneous group of diseases. 3 , 4 In these syndromes, the neutropenia is associated with life-threatening bacterial infections early in life. Most patients respond to treatment with recombinant human granulocyte colony-stimulating factor (rhG-CSF), which increases neutrophil counts and decreases the frequency and severity of infections. 5 Nonetheless, patients may remain at risk for both infectious complications and the development of clonal disorders of hematopoiesis, such as myelodysplastic syndrome and acute myeloid leukemia. 6 Considerable progress has been made in identifying the . . .

Integer linear programs (ILPs) and mixed integer programs (MIPs) often have multiple distinct optimal solutions, yet the widely used Gurobi optimization solver returns certain solutions at disproportionately high frequencies. This behavior is disadvantageous, as, in fields such as biomedicine, the identification and analysis of distinct optima yields valuable domain-specific insights that inform future research directions. In the present work, we introduce MORSE (Multiple Optima via Random Sampling and careful choice of the parameter Epsilon), a randomized, parallelizable algorithm to efficiently generate multiple optima for ILPs. MORSE maps multiplicative perturbations to the coefficients in an instance’s objective function, generating a modified instance that retains an optimum of the original problem. We formalize and prove the above claim in some practical conditions. Furthermore, we prove that for 0/1 selection problems, MORSE finds each distinct optimum with equal probability. We evaluate MORSE using two measures; the number of distinct optima found in r independent runs, and the diversity of the list (with repetitions) of solutions by average pairwise Hamming distance and Shannon entropy. Using these metrics, we provide empirical results demonstrating that MORSE outperforms the Gurobi method and unweighted variations of the MORSE method on a set of 20 Mixed Integer Programming Library (MIPLIB) instances and on a combinatorial optimization problem in cancer genomics.

Autosomal recessive severe congenital neutropenia (SCN) 1 constitutes a primary immunodeficiency syndrome associated with increased apoptosis in myeloid cells 2 , 3 , yet the underlying genetic defect remains unknown. Using a positional cloning approach and candidate gene evaluation, we identified a recurrent homozygous germline mutation in HAX1 in three pedigrees. After further molecular screening of individuals with SCN, we identified 19 additional affected individuals with homozygous HAX1 mutations, including three belonging to the original pedigree described by Kostmann 1 . HAX1 encodes the mitochondrial protein HAX1, which has been assigned functions in signal transduction 4 and cytoskeletal control 5 , 6 . Here, we show that HAX1 is critical for maintaining the inner mitochondrial membrane potential and protecting against apoptosis in myeloid cells. Our findings suggest that HAX1 is a major regulator of myeloid homeostasis and underline the significance of genetic control of apoptosis in neutrophil development.

Identifying the gene that underlies the hyper-IgE immune syndrome — also known as Job's syndrome — has been a challenge. Affected persons typically have extremely high levels of IgE and are susceptible to cold staphylococcal abscesses, pneumonia, and eczema. The cause of this disease is now established: mutations in STAT3. Identifying the gene that underlies the hyper-IgE immune syndrome has been a challenge. The cause of this disease is now established: mutations in STAT3 . The syndrome described as Job's syndrome by Davis et al. in 1966 1 and as hyperimmunoglobulinemia E by Buckley et al. in 1972 2 was originally characterized by recurrent cold staphylococcal abscesses, pneumonia, eczema, hyperextensibility, and extreme elevation of IgE levels. Since then, additional features of the hyper-IgE syndrome have been recognized, including scoliosis, pathologic fractures, pneumatoceles, delayed dental deciduation, 3 , 4 coronary-artery aneurysms, 5 brain lesions, and Chiari's malformations. 6 Pneumonia in patients with the hyper-IgE syndrome is typically caused by infections with Staphylococcus aureus , Haemophilus influenzae , or Streptococcus pneumoniae and leads to pneumatoceles, 3 providing portals for fatal infections with bacteria and . . .

Lysosome-related organelles have versatile functions, including protein and lipid degradation, signal transduction and protein secretion. The molecular elucidation of rare congenital diseases affecting endosomal-lysosomal biogenesis has given insights into physiological functions of the innate and adaptive immune system. Here, we describe a previously unknown human primary immunodeficiency disorder and provide evidence that the endosomal adaptor protein p14, previously characterized as confining mitogen-activated protein kinase (MAPK) signaling to late endosomes, is crucial for the function of neutrophils, B cells, cytotoxic T cells and melanocytes. Combining genetic linkage studies and transcriptional profiling analysis, we identified a homozygous point mutation in the 3′ untranslated region (UTR) of p14 (also known as MAPBPIP ), resulting in decreased protein expression. In p14-deficient cells, the distribution of late endosomes was severely perturbed, suggesting a previously unknown role for p14 in endosomal biogenesis. These findings have implications for understanding endosomal membrane dynamics, compartmentalization of cell signal cascades, and their role in immunity.