Model misspecification misleads inference of the spatial dynamics of disease outbreaks.

Epidemiology has been transformed by the advent of Bayesian phylodynamic models that allow researchers to infer the geographic history of pathogen dispersal over a set of discrete geographic areas [1, 2]. These models provide powerful tools for understanding the spatial dynamics of disease outbreaks, but contain many parameters that are inferred from minimal geographic information (i.e., the single area in which each pathogen was sampled). Consequently, inferences under these models are inherently sensitive to our prior assumptions about the model parameters. Here, we demonstrate that the default priors used in empirical phylodynamic studies make strong and biologically unrealistic assumptions about the underlying geographic process. We provide empirical evidence that these unrealistic priors strongly (and adversely) impact commonly reported aspects of epidemiological studies, including: 1) the relative rates of dispersal between areas; 2) the importance of dispersal routes for the spread of pathogens among areas; 3) the number of dispersal events between areas, and; 4) the ancestral area in which a given outbreak originated. We offer strategies to avoid these problems, and develop tools to help researchers specify more biologically reasonable prior models that will realize the full potential of phylodynamic methods to elucidate pathogen biology and, ultimately, inform surveillance and monitoring policies to mitigate the impacts of disease outbreaks.

A Somatic BRCA2-Mutated Pancreatic Adenocarcinoma With Sustained Exceptional Response to Modified FOLFIRINOX.

Homologous recombination repair (HRR) pathway deficiency opens multiple therapeutic avenues within pancreatic cancer. Patients with HRR deficiency-associated gene mutations such as BRCA1, BRCA2, and PALB2 are more susceptible to platinum-based chemotherapies and in those with somatic BRCA mutations, PARP inhibitor therapy prolongs progression-free survival. The case discussed herein illustrates the therapeutic opportunities offered through the identification of HRR deficiency in pancreatic cancer, as well as the challenges associated with treatment and prevention of central nervous system metastases in long-term survivors of pancreatic cancer.

PrioriTree: a utility for improving phylodynamic analyses in BEAST.

SUMMARY: Phylodynamic methods are central to studies of the geographic and demographic history of disease outbreaks. Inference under discrete-geographic phylodynamic models-which involve many parameters that must be inferred from minimal information-is inherently sensitive to our prior beliefs about the model parameters. We present an interactive utility, PrioriTree, to help researchers identify and accommodate prior sensitivity in discrete-geographic inferences. Specifically, PrioriTree provides a suite of functions to generate input files for-and summarize output from-BEAST analyses for performing robust Bayesian inference, data-cloning analyses and assessing the relative and absolute fit of candidate discrete-geographic (prior) models to empirical datasets. AVAILABILITY AND IMPLEMENTATION: PrioriTree is distributed as an R package available at https://github.com/jsigao/prioritree, with a comprehensive user manual provided at https://bookdown.org/jsigao/prioritree_manual/.

Diversification Models Conflate Likelihood and Prior, and Cannot be Compared Using Conventional Model-Comparison Tools.

Time-calibrated phylogenetic trees are a tremendously powerful tool for studying evolutionary, ecological, and epidemiological phenomena. Such trees are predominantly inferred in a Bayesian framework, with the phylogeny itself treated as a parameter with a prior distribution (a "tree prior"). However, we show that the tree "parameter" consists, in part, of data, in the form of taxon samples. Treating the tree as a parameter fails to account for these data and compromises our ability to compare among models using standard techniques (e.g., marginal likelihoods estimated using path-sampling and stepping-stone sampling algorithms). Since accuracy of the inferred phylogeny strongly depends on how well the tree prior approximates the true diversification process that gave rise to the tree, the inability to accurately compare competing tree priors has broad implications for applications based on time-calibrated trees. We outline potential remedies to this problem, and provide guidance for researchers interested in assessing the fit of tree models. [Bayes factors; Bayesian model comparison; birth-death models; divergence-time estimation; lineage diversification].

Unearthing Modes of Climatic Adaptation in Underground Storage Organs Across Liliales.

Testing adaptive hypotheses about how continuous traits evolve in association with developmentally structured discrete traits, while accounting for the confounding influence of other, hidden, evolutionary forces, remains a challenge in evolutionary biology. For example, geophytes are herbaceous plants-with underground buds-that use underground storage organs (USOs) to survive extended periods of unfavorable conditions. Such plants have evolved multiple times independently across all major vascular plant lineages. Even within closely related lineages, however, geophytes show impressive variation in the morphological modifications and structures (i.e.,"types" of USOs) that allow them to survive underground. Despite the developmental and structural complexity of USOs, the prevailing hypothesis is that they represent convergent evolutionary "solutions" to a common ecological problem, though some recent research has drawn this conclusion into question. We extend existing phylogenetic comparative methods to test for links between the hierarchical discrete morphological traits associated with USOs and adaptation to environmental variables, using a phylogeny of 621 species in Liliales. We found that plants with different USO types do not differ in climatic niche more than expected by chance, with the exception of root morphology, where modified roots are associated with lower temperature seasonality. These findings suggest that root tubers may reflect adaptations to different climatic conditions than those represented by other types of USOs. Thus, the tissue type and developmental origin of the USO structure may influence the way it mediates ecological relationships, which draws into question the appropriateness of ascribing broad ecological patterns uniformly across geophytic taxa. This work provides a new framework for testing adaptive hypotheses and for linking ecological patterns across morphologically varying taxa while accounting for developmental (non-independent) relationships in morphological data. [Climatic niche evolution; geophytes; imperfect correspondence; macroevolution.].

Lymph node formation and B cell homeostasis require IKK-α in distinct endothelial cell-derived compartments.

Global inactivation of IκB kinase (IKK)-α results in defective lymph node (LN) formation and B cell maturation, and loss of IKK-α-dependent noncanonical NF-κB signaling in stromal organizer and hematopoietic cells is thought to underlie these distinct defects. We previously demonstrated that this pathway is also activated in vascular endothelial cells (ECs). To determine the physiologic function of EC-intrinsic IKK-α, we crossed IkkαF/F mice with Tie2-cre or Cdh5-cre mice to ablate IKK-α in ECs. Notably, the compound defects of global IKK-α inactivation were recapitulated in IkkαTie2 and IkkαCdh5 mice, as both lacked all LNs and mature follicular and marginal zone B cell numbers were markedly reduced. However, as Tie2-cre and Cdh5-cre are expressed in all ECs, including blood forming hemogenic ECs, IKK-α was also absent in hematopoietic cells (HC). To determine if loss of HC-intrinsic IKK-α affected LN development, we generated IkkαVav mice lacking IKK-α in only the hematopoietic compartment. While mature B cell numbers were significantly reduced in IkkαVav mice, LN formation was intact. As lymphatic vessels also arise during development from blood ECs, we generated IkkαLyve1 mice lacking IKK-α in lymphatic ECs (LECs) to determine if IKK-α in lymphatic vessels impacts LN development. Strikingly, while mature B cell numbers were normal, LNs were completely absent in IkkαLyve1 mice. Thus, our findings reveal that IKK-α in distinct EC-derived compartments is uniquely required to promote B cell homeostasis and LN development, and we establish that LEC-intrinsic IKK-α is absolutely essential for LN formation.

New Phylogenetic Models Incorporating Interval-Specific Dispersal Dynamics Improve Inference of Disease Spread.

Phylodynamic methods reveal the spatial and temporal dynamics of viral geographic spread, and have featured prominently in studies of the COVID-19 pandemic. Virtually all such studies are based on phylodynamic models that assume-despite direct and compelling evidence to the contrary-that rates of viral geographic dispersal are constant through time. Here, we: (1) extend phylodynamic models to allow both the average and relative rates of viral dispersal to vary independently between pre-specified time intervals; (2) implement methods to infer the number and timing of viral dispersal events between areas; and (3) develop statistics to assess the absolute fit of discrete-geographic phylodynamic models to empirical datasets. We first validate our new methods using simulations, and then apply them to a SARS-CoV-2 dataset from the early phase of the COVID-19 pandemic. We show that: (1) under simulation, failure to accommodate interval-specific variation in the study data will severely bias parameter estimates; (2) in practice, our interval-specific discrete-geographic phylodynamic models can significantly improve the relative and absolute fit to empirical data; and (3) the increased realism of our interval-specific models provides qualitatively different inferences regarding key aspects of the COVID-19 pandemic-revealing significant temporal variation in global viral dispersal rates, viral dispersal routes, and the number of viral dispersal events between areas-and alters interpretations regarding the efficacy of intervention measures to mitigate the pandemic.

Smoking is Not Associated with Lung Metastasis in Pancreatic Cancer.

Smoking is a risk factor for pulmonary metastasis in various malignancies. We investigated this association for pancreatic ductal adenocarcinoma (PDAC). We conducted a retrospective 1:2 case-control study of consecutive patients who underwent PDAC resection (2011-2021). Cases ultimately developed lung metastases and controls did not. Of 744 patients we identified 53 cases and 106 matched controls. Twenty-five (47%) cases and 50 (47%) matched controls had a history of smoking (p = 1.0). This indicates that smoking is not associated with increased risk of pulmonary metastasis in resectable PDAC. Further research is needed to elucidate tumor and parenchymal factors influencing metastatic site.

Improved maize reference genome with single-molecule technologies.

Complete and accurate reference genomes and annotations provide fundamental tools for characterization of genetic and functional variation. These resources facilitate the determination of biological processes and support translation of research findings into improved and sustainable agricultural technologies. Many reference genomes for crop plants have been generated over the past decade, but these genomes are often fragmented and missing complex repeat regions. Here we report the assembly and annotation of a reference genome of maize, a genetic and agricultural model species, using single-molecule real-time sequencing and high-resolution optical mapping. Relative to the previous reference genome, our assembly features a 52-fold increase in contig length and notable improvements in the assembly of intergenic spaces and centromeres. Characterization of the repetitive portion of the genome revealed more than 130,000 intact transposable elements, allowing us to identify transposable element lineage expansions that are unique to maize. Gene annotations were updated using 111,000 full-length transcripts obtained by single-molecule real-time sequencing. In addition, comparative optical mapping of two other inbred maize lines revealed a prevalence of deletions in regions of low gene density and maize lineage-specific genes.

A hierarchical Bayesian mixture model for inferring the expression state of genes in transcriptomes.

Transcriptomes are key to understanding the relationship between genotype and phenotype. The ability to infer the expression state (active or inactive) of genes in the transcriptome offers unique benefits for addressing this issue. For example, qualitative changes in gene expression may underly the origin of novel phenotypes, and expression states are readily comparable between tissues and species. However, inferring the expression state of genes is a surprisingly difficult problem, owing to the complex biological and technical processes that give rise to observed transcriptomic datasets. Here, we develop a hierarchical Bayesian mixture model that describes this complex process and allows us to infer expression state of genes from replicate transcriptomic libraries. We explore the statistical behavior of this method with analyses of simulated datasets-where we demonstrate its ability to correctly infer true (known) expression states-and empirical-benchmark datasets, where we demonstrate that the expression states inferred from RNA-sequencing (RNA-seq) datasets using our method are consistent with those based on independent evidence. The power of our method to correctly infer expression states is generally high and remarkably, approaches the maximum possible power for this inference problem. We present an empirical analysis of primate-brain transcriptomes, which identifies genes that have a unique expression state in humans. Our method is implemented in the freely available R package zigzag.

Advances in Liquid Biopsy Technology and Implications for Pancreatic Cancer.

Pancreatic cancer is a highly aggressive malignancy with a climbing incidence. The majority of cases are detected late, with incurable locally advanced or metastatic disease. Even in individuals who undergo resection, recurrence is unfortunately very common. There is no universally accepted screening modality for the general population and diagnosis, evaluation of treatment response, and detection of recurrence relies primarily on the use of imaging. Identification of minimally invasive techniques to help diagnose, prognosticate, predict response or resistance to therapy, and detect recurrence are desperately needed. Liquid biopsies represent an emerging group of technologies which allow for non-invasive serial sampling of tumor material. Although not yet approved for routine use in pancreatic cancer, the increasing sensitivity and specificity of contemporary liquid biopsy platforms will likely change clinical practice in the near future. In this review, we discuss the recent technological advances in liquid biopsy, focusing on circulating tumor DNA, exosomes, microRNAs, and circulating tumor cells.

Inferring the Total-Evidence Timescale of Marattialean Fern Evolution in the Face of Model Sensitivity.

Phylogenetic divergence-time estimation has been revolutionized by two recent developments: 1) total-evidence dating (or "tip-dating") approaches that allow for the incorporation of fossils as tips in the analysis, with their phylogenetic and temporal relationships to the extant taxa inferred from the data and 2) the fossilized birth-death (FBD) class of tree models that capture the processes that produce the tree (speciation, extinction, and fossilization) and thus provide a coherent and biologically interpretable tree prior. To explore the behavior of these methods, we apply them to marattialean ferns, a group that was dominant in Carboniferous landscapes prior to declining to its modest extant diversity of slightly over 100 species. We show that tree models have a dramatic influence on estimates of both divergence times and topological relationships. This influence is driven by the strong, counter-intuitive informativeness of the uniform tree prior, and the inherent nonidentifiability of divergence-time models. In contrast to the strong influence of the tree models, we find minor effects of differing the morphological transition model or the morphological clock model. We compare the performance of a large pool of candidate models using a combination of posterior-predictive simulation and Bayes factors. Notably, an FBD model with epoch-specific speciation and extinction rates was strongly favored by Bayes factors. Our best-fitting model infers stem and crown divergences for the Marattiales in the mid-Devonian and Late Cretaceous, respectively, with elevated speciation rates in the Mississippian and elevated extinction rates in the Cisuralian leading to a peak diversity of ${\sim}$2800 species at the end of the Carboniferous, representing the heyday of the Psaroniaceae. This peak is followed by the rapid decline and ultimate extinction of the Psaroniaceae, with their descendants, the Marattiaceae, persisting at approximately stable levels of diversity until the present. This general diversification pattern appears to be insensitive to potential biases in the fossil record; despite the preponderance of available fossils being from Pennsylvanian coal balls, incorporating fossilization-rate variation does not improve model fit. In addition, by incorporating temporal data directly within the model and allowing for the inference of the phylogenetic position of the fossils, our study makes the surprising inference that the clade of extant Marattiales is relatively young, younger than any of the fossils historically thought to be congeneric with extant species. This result is a dramatic demonstration of the dangers of node-based approaches to divergence-time estimation, where the assignment of fossils to particular clades is made a priori (earlier node-based studies that constrained the minimum ages of extant genera based on these fossils resulted in much older age estimates than in our study) and of the utility of explicit models of morphological evolution and lineage diversification. [Bayesian model comparison; Carboniferous; divergence-time estimation; fossil record; fossilized birth-death; lineage diversification; Marattiales; models of morphological evolution; Psaronius; RevBayes.].

Stereotactic radiosurgery for melanoma brain metastases: dose-size response relationship in the era of immunotherapy.

PURPOSE/OBJECTIVE(S): To determine, for intact melanoma brain metastases (MBM) treated with single-fraction stereotactic radiosurgery (SRS), whether planning parameter peripheral dose per lesion diameter (PDLDm, Gy/mm) and lesion control (LC) differs with versus without immunotherapy (IO). MATERIALS/METHODS: We performed a retrospective analysis of patients with intact MBM treated with SRS from 2008 to 2019. Cox-frailty models were constructed to include confounders selected by penalized Cox regression models with a LASSO selector. Interaction effect testing was used to determine whether a significant effect between IO and PDLDm could be demonstrated with respect to LC. RESULTS: The study cohort comprised 67 patients with 244 MBMs treated with SRS (30 patients with 122 lesions treated with both SRS and IO) were included. The logarithm of PDLDm was selected as a predictor of LC (HR 0.307, 95% CI 0.098-0.441), adjusting for IO receipt (HR 0.363, 95% CI 0.108-1.224). Interaction effect testing demonstrated a differential effect of PDLDm by IO receipt, with respect to LC (p = 0.048). Twelve-month LC rates for a 7.5 mm lesion receiving SRS (18 Gy) with IO versus without IO were 87.8% (95% CI 69.0-98.3%) versus 79.8% (95% CI 55.1-93.8%) respectively. CONCLUSION: PDLDm predicted LC in patients with small MBMs treated with single-fraction SRS. We found a differential effect of dose per lesion size and LC by immunotherapy receipt. Future studies are needed to determine whether lower doses of single-fraction SRS afford similarly effective LC for patients with small MBMs receiving immunotherapy.

Limited Utility of Procalcitonin in Identifying Community-Associated Bacterial Infections in Patients Presenting with Coronavirus Disease 2019.

The role of procalcitonin in identifying community-associated bacterial infections among patients with coronavirus disease 2019 is not yet established. In 2,443 patients of whom 148 had bacterial coinfections, mean procalcitonin levels were significantly higher with any bacterial infection (13.16 ± 51.19 ng/ml; P = 0.0091) and with bacteremia (34.25 ± 85.01 ng/ml; P = 0.0125) than without infection (2.00 ± 15.26 ng/ml). Procalcitonin (cutoff, 0.25 or 0.50 ng/ml) did not reliably identify bacterial coinfections but may be useful in excluding bacterial infection.

Prolonged Response to HER2-Directed Therapy in Three Patients with HER2-Amplified Metastatic Carcinoma of the Biliary System: Case Study and Review of the Literature.

HER2 amplification, which results in overexpression of the receptor tyrosine kinase HER2, has been described in a wide variety of malignancies. HER2-targeting agents have been incorporated into the treatment paradigms for HER2-overexpressing breast and gastric cancer. More recently, these agents have shown promise in other gastrointestinal malignancies, such as colon cancer and biliary tract tumors. This study discusses two patients with gallbladder carcinoma and a third with ampullary carcinoma who were able to achieve marked responses to HER2-directed therapy. These cases underscore the importance of molecular analysis for HER2 amplification/HER2 overexpression, irrespective of tumor histology, and highlight a need for further investigation of HER2-directed therapy beyond breast and gastroesophageal cancers. KEY POINTS: Current guidelines recommend molecular assessment for HER2 overexpression exclusively in breast and gastric adenocarcinoma. The focus of this report is on three cases (two biliary tract and one ampullary carcinoma) in which amplification of HER2 or overexpression of HER2 was detected and treatment with HER2-directed therapy resulted in robust responses. These cases exemplify responsiveness of non-breast/gastric histologies to HER2-directed therapies, highlighting several promising new settings for these agents. Testing for amplification of HER2 or overexpression of HER2 should be considered especially in rare diseases with limited treatment options.

A Bayesian Approach for Inferring the Impact of a Discrete Character on Rates of Continuous-Character Evolution in the Presence of Background-Rate Variation.

Understanding how and why rates of character evolution vary across the Tree of Life is central to many evolutionary questions; for example, does the trophic apparatus (a set of continuous characters) evolve at a higher rate in fish lineages that dwell in reef versus nonreef habitats (a discrete character)? Existing approaches for inferring the relationship between a discrete character and rates of continuous-character evolution rely on comparing a null model (in which rates of continuous-character evolution are constant across lineages) to an alternative model (in which rates of continuous-character evolution depend on the state of the discrete character under consideration). However, these approaches are susceptible to a "straw-man" effect: the influence of the discrete character is inflated because the null model is extremely unrealistic. Here, we describe MuSSCRat, a Bayesian approach for inferring the impact of a discrete trait on rates of continuous-character evolution in the presence of alternative sources of rate variation ("background-rate variation"). We demonstrate by simulation that our method is able to reliably infer the degree of state-dependent rate variation, and show that ignoring background-rate variation leads to biased inferences regarding the degree of state-dependent rate variation in grunts (the fish group Haemulidae). [Bayesian phylogenetic comparative methods; continuous-character evolution; data augmentation; discrete-character evolution.].

Computational design and interpretation of single-RNA translation experiments.

Advances in fluorescence microscopy have introduced new assays to quantify live-cell translation dynamics at single-RNA resolution. We introduce a detailed, yet efficient sequence-based stochastic model that generates realistic synthetic data for several such assays, including Fluorescence Correlation Spectroscopy (FCS), ribosome Run-Off Assays (ROA) after Harringtonine application, and Fluorescence Recovery After Photobleaching (FRAP). We simulate these experiments under multiple imaging conditions and for thousands of human genes, and we evaluate through simulations which experiments are most likely to provide accurate estimates of elongation kinetics. Finding that FCS analyses are optimal for both short and long length genes, we integrate our model with experimental FCS data to capture the nascent protein statistics and temporal dynamics for three human genes: KDM5B, ß-actin, and H2B. Finally, we introduce a new open-source software package, RNA Sequence to NAscent Protein Simulator (rSNAPsim), to easily simulate the single-molecule translation dynamics of any gene sequence for any of these assays and for different assumptions regarding synonymous codon usage, tRNA level modifications, or ribosome pauses. rSNAPsim is implemented in Python and is available at: https://github.com/MunskyGroup/rSNAPsim.git.

Tumor infiltrating lymphocyte grade in Merkel cell carcinoma: relationships with clinical factors and independent prognostic value.

INTRODUCTION: Surrogate markers of the host immune response are not currently included in AJCC staging for Merkel cell carcinoma (MCC), and have not been consistently associated with clinical outcomes. We performed an analysis of a large national database to investigate tumor infiltrating lymphocyte (TIL) grade as an independent predictor of overall survival (OS) for patients with MCC and to characterize the relationship between TIL grade and other clinical prognostic factors. MATERIAL AND METHODS: The NCDB was queried for patients with resected, non-metastatic MCC with known TIL grade (absent, non-brisk and brisk). Multivariable Cox regression modeling was performed to define TIL grade as a predictor of OS adjusting for other relevant clinical factors. Multinomial, multivariable logistic regression was performed to characterize the relationship between TIL grade and other clinical prognostic factors. Multiple imputation was performed to account for missing data bias. RESULTS: Both brisk (HR 0.55, CI 0.36-0.83) and non-brisk (HR 0.77, CI 0.60-0.98) were associated with decreased adjusted hazard of death relative to absent TIL grade. Adverse clinical factors such as 1-3 positive lymph nodes, lymphovascular invasion (LVI) and immunosuppression were associated with increased likelihood of non-brisk TIL relative to absent TIL grade (p values <.05). Extracapsular extension (ECS) was associated with decreased likelihood of brisk TIL relative to absent TIL grade (p<.05). DISCUSSION: Histopathologic TIL grade was independently predictive for OS in this large national cohort. Significant differences in the likelihood of non-brisk or brisk TIL relative to absent grade were present with regards to LVI, ECS and immune status. TIL grade may be a useful prognostic factor to consider in addition to more granular characterization of TIL morphology and immunophenotype.

Signet ring cell carcinoma of the Ampulla of Vater: outcomes of patients in the United States.

BACKGROUND: Signet ring cell carcinoma (SRCC) of the ampulla of Vater is poorly understood, with approximately 22 reported cases. Our study sought to create a comprehensive review of cases in the United States. METHODS: We used the Surveillance, Epidemiology, and End Results Program to collect all cases of ampullary adenocarcinoma diagnosed between 2010 and 2015. RESULTS: The age-adjusted incidence rate of SRCC of the ampulla of Vater was 1.2 cases per 10,000,000 persons per year, with 50% more cases in males than females. We identified 3448 cases of adenocarcinoma of the ampulla of Vater, 81 of which were SRCC (2.3%). SRCC tended to present a later stage than other ampullary cancers, with median survival times of 17 vs. 25 months, (p = 0.07). Survival was significantly worse for SRCC when accounting for other clinical features (HR 1.46, p = 0.01). Factors portending worse prognosis in SRCC of the ampulla of Vater were advanced age, late stage and lack of surgical intervention. CONCLUSION: Our study represents the largest study of SRCC of the ampulla of Vater to date. SRCC has a poorer prognosis compared with other ampullary cancers. Optimal treatment regimen is the most important future area of study.

Critically evaluating the theory and performance of Bayesian analysis of macroevolutionary mixtures.

Bayesian analysis of macroevolutionary mixtures (BAMM) has recently taken the study of lineage diversification by storm. BAMM estimates the diversification-rate parameters (speciation and extinction) for every branch of a study phylogeny and infers the number and location of diversification-rate shifts across branches of a tree. Our evaluation of BAMM reveals two major theoretical errors: (i) the likelihood function (which estimates the model parameters from the data) is incorrect, and (ii) the compound Poisson process prior model (which describes the prior distribution of diversification-rate shifts across branches) is incoherent. Using simulation, we demonstrate that these theoretical issues cause statistical pathologies; posterior estimates of the number of diversification-rate shifts are strongly influenced by the assumed prior, and estimates of diversification-rate parameters are unreliable. Moreover, the inability to correctly compute the likelihood or to correctly specify the prior for rate-variable trees precludes the use of Bayesian approaches for testing hypotheses regarding the number and location of diversification-rate shifts using BAMM.