Pathogenic Germline Variants in 10,389 Adult Cancers.

We conducted the largest investigation of predisposition variants in cancer to date, discovering 853 pathogenic or likely pathogenic variants in 8% of 10,389 cases from 33 cancer types. Twenty-one genes showed single or cross-cancer associations, including novel associations of SDHA in melanoma and PALB2 in stomach adenocarcinoma. The 659 predisposition variants and 18 additional large deletions in tumor suppressors, including ATM, BRCA1, and NF1, showed low gene expression and frequent (43%) loss of heterozygosity or biallelic two-hit events. We also discovered 33 such variants in oncogenes, including missenses in MET, RET, and PTPN11 associated with high gene expression. We nominated 47 additional predisposition variants from prioritized VUSs supported by multiple evidences involving case-control frequency, loss of heterozygosity, expression effect, and co-localization with mutations and modified residues. Our integrative approach links rare predisposition variants to functional consequences, informing future guidelines of variant classification and germline genetic testing in cancer.

Prediction of thirty-day morbidity and mortality after duodenal switch using an artificial neural network.

BACKGROUND: Understanding factors that increase risk of both mortality and specific measures of morbidity after duodenal switch (DS) is important in deciding to offer this weight loss operation. Artificial neural networks (ANN) are computational deep learning approaches that model complex interactions among input factors to optimally predict an outcome. Here, a comprehensive national database is examined for patient factors associated with poor outcomes, while comparing the performance of multivariate logistic regression and ANN models in predicting these outcomes. METHODS: 2907 DS patients from the 2019 Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program database were assessed for patient factors associated with the previously validated composite endpoint of 30-day postoperative reintervention, reoperation, readmission, or mortality using bivariate analysis. Variables associated (P ≤ 0.05) with the endpoint were imputed in a multivariate logistic regression model and a three-node ANN with 20% holdback for validation. Goodness-of-fit was assessed using area under receiver operating curves (AUROC). RESULTS: There were 229 DS patients with the composite endpoint (7.9%), and 12 mortalities (0.4%). Associated patient factors on bivariate analysis included advanced age, non-white race, cardiac history, hypertension requiring 3 + medications (HTN), previous foregut/obesity surgery, obstructive sleep apnea (OSA), and higher creatinine (P ≤ 0.05). Upon multivariate analysis, independently associated factors were non-white race (odds ratio 1.40; P = 0.075), HTN (1.55; P = 0.038), previous foregut/bariatric surgery (1.43; P = 0.041), and OSA (1.46; P = 0.018). The nominal logistic regression multivariate analysis (n = 2330; R2 = 0.02, P < 0.001) and ANN (R2 = 0.06; n = 1863 [training set], n = 467 [validation]) models generated AUROCs of 0.619, 0.656 (training set) and 0.685 (validation set), respectively. CONCLUSION: Readily obtainable patient factors were identified that confer increased risk of the 30-day composite endpoint after DS. Moreover, use of an ANN to model these factors may optimize prediction of this outcome. This information provides useful guidance to bariatricians and surgical candidates alike.

Phase transitions in evolutionary dynamics.

Sharp changes in state, such as transitions from survival to extinction, are hallmarks of evolutionary dynamics in biological systems. These transitions can be explored using the techniques of statistical physics and the physics of nonlinear and complex systems. For example, a survival-to-extinction transition can be characterized as a non-equilibrium phase transition to an absorbing state. Here, we review the literature on phase transitions in evolutionary dynamics. We discuss directed percolation transitions in cellular automata and evolutionary models, and models that diverge from the directed percolation universality class. We explore in detail an example of an absorbing phase transition in an agent-based model of evolutionary dynamics, including previously unpublished data demonstrating similarity to, but also divergence from, directed percolation, as well as evidence for phase transition behavior at multiple levels of the model system's evolutionary structure. We discuss phase transition models of the error catastrophe in RNA virus dynamics and phase transition models for transition from chemistry to biochemistry, i.e., the origin of life. We conclude with a review of phase transition dynamics in models of natural selection, discuss the possible role of phase transitions in unraveling fundamental unresolved questions regarding multilevel selection and the major evolutionary transitions, and assess the future outlook for phase transitions in the investigation of evolutionary dynamics.

Regulated Phosphosignaling Associated with Breast Cancer Subtypes and Druggability.

Aberrant phospho-signaling is a hallmark of cancer. We investigated kinase-substrate regulation of 33,239 phosphorylation sites (phosphosites) in 77 breast tumors and 24 breast cancer xenografts. Our search discovered 2134 quantitatively correlated kinase-phosphosite pairs, enriching for and extending experimental or binding-motif predictions. Among the 91 kinases with auto-phosphorylation, elevated EGFR, ERBB2, PRKG1, and WNK1 phosphosignaling were enriched in basal, HER2-E, Luminal A, and Luminal B breast cancers, respectively, revealing subtype-specific regulation. CDKs, MAPKs, and ataxia-telangiectasia proteins were dominant, master regulators of substrate-phosphorylation, whose activities are not captured by genomic evidence. We unveiled phospho-signaling and druggable targets from 113 kinase-substrate pairs and cascades downstream of kinases, including AKT1, BRAF and EGFR. We further identified kinase-substrate-pairs associated with clinical or immune signatures and experimentally validated activated phosphosites of ERBB2, EIF4EBP1, and EGFR. Overall, kinase-substrate regulation revealed by the largest unbiased global phosphorylation data to date connects driver events to their signaling effects.

Militaries and global health: peace, conflict, and disaster response.

Many countries show a growing willingness to use militaries in support of global health efforts. This Series paper summarises the varied roles, responsibilities, and approaches of militaries in global health, drawing on examples and case studies across peacetime, conflict, and disaster response environments. Militaries have many capabilities applicable to global health, ranging from research, surveillance, and medical expertise to rapidly deployable, large-scale assets for logistics, transportation, and security. Despite this large range of capabilities, militaries also have limitations when engaging in global health activities. Militaries focus on strategic, operational, and tactical objectives that support their security and defence missions, which can conflict with humanitarian and global health equity objectives. Guidelines-both within and outside militaries-for military engagement in global health are often lacking, as are structured opportunities for military and civilian organisations to engage one another. We summarise policies that can help close the gap between military and civilian actors to catalyse the contributions of all participants to enhance global health.

GenomeVIP: a cloud platform for genomic variant discovery and interpretation.

Identifying genomic variants is a fundamental first step toward the understanding of the role of inherited and acquired variation in disease. The accelerating growth in the corpus of sequencing data that underpins such analysis is making the data-download bottleneck more evident, placing substantial burdens on the research community to keep pace. As a result, the search for alternative approaches to the traditional "download and analyze" paradigm on local computing resources has led to a rapidly growing demand for cloud-computing solutions for genomics analysis. Here, we introduce the Genome Variant Investigation Platform (GenomeVIP), an open-source framework for performing genomics variant discovery and annotation using cloud- or local high-performance computing infrastructure. GenomeVIP orchestrates the analysis of whole-genome and exome sequence data using a set of robust and popular task-specific tools, including VarScan, GATK, Pindel, BreakDancer, Strelka, and Genome STRiP, through a web interface. GenomeVIP has been used for genomic analysis in large-data projects such as the TCGA PanCanAtlas and in other projects, such as the ICGC Pilots, CPTAC, ICGC-TCGA DREAM Challenges, and the 1000 Genomes SV Project. Here, we demonstrate GenomeVIP's ability to provide high-confidence annotated somatic, germline, and de novo variants of potential biological significance using publicly available data sets.

CharGer: clinical Characterization of Germline variants.

SUMMARY: CharGer (Characterization of Germline variants) is a software tool for interpreting and predicting clinical pathogenicity of germline variants. CharGer gathers evidence from databases and annotations, provided by local tools and files or via ReST APIs, and classifies variants according to ACMG guidelines for assessing variant pathogenicity. User-designed pathogenicity criteria can be incorporated into CharGer's flexible framework, thereby allowing users to create a customized classification protocol. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://github.com/ding-lab/CharGer and is distributed under the GNU GPL-v3.0 license. Software is also distributed through the Python Package Index (PyPI) repository. CharGer is implemented in Python 2.7 and is supported on Unix-based operating systems. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Database of evidence for precision oncology portal.

Summary: A database of curated genomic variants with clinically supported drug therapies and other oncological annotations is described. The accompanying web portal provides a search engine with two modes: one that allows users to query gene, cancer type, variant type or position for druggable mutations, and another to search for and to visualize, on three-dimensional protein structures, putative druggable sites that cluster with known druggable mutations. Availability and implementation: http://dinglab.wustl.edu/depo.

The cost of love: financial consequences of insecure attachment in antisocial youth.

BACKGROUND: Knowing that your parent or caregiver will be there for you in times of emotional need and distress is a core aspect of the human experience of feeling loved and being securely attached. In contrast, an insecure attachment pattern is found in many antisocial youth and is related to less sensitive caregiving. Such youth are often distrustful of adults and authority figures, and are at high risk of poor outcomes. As they become adults, they require extensive health, social and economic support, costing society ten times more than their well-adjusted peers. However, it is not known whether insecure attachment itself is associated with higher costs in at-risk youth, independently of potential confounders, nor whether cost differences are already beginning to emerge early in adolescence. METHODS: Sample: A total of 174 young people followed up aged 9-17 years (mean 12.1, SD 1.8): 85 recruited with moderate antisocial behaviour (80th percentile) from a school screen aged 4-6 years; 89 clinically referred with very high antisocial behaviour (98th percentile) aged 3-7 years. MEASURES: Costs by detailed health economic and service-use interview; attachment security to mother and father from interview; diagnostic interviews for oppositional and conduct problems; self-reported delinquent behaviour. RESULTS: Costs were greater for youth insecurely attached to their mothers (secure £6,743, insecure £10,199, p = .001) and more so to fathers (secure £1,353, insecure £13,978, p < .001). These differences remained significant (mother p = .019, father p < .001) after adjusting for confounders, notably family income and education, intelligence and antisocial behaviour severity. CONCLUSIONS: Attachment insecurity is a significant predictor of public cost in at-risk youth, even after accounting for covariates. Since adolescent attachment security is influenced by caregiving quality earlier in childhood, these findings add support to the public health case for early parenting interventions to improve child outcomes and reduce the financial burden on society.