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.

NF-κB Signaling is Required for X-Chromosome Inactivation Maintenance Following T cell Activation.

X Chromosome Inactivation (XCI) is a female-specific process which balances X-linked gene dosage between sexes. Unstimulated T cells lack cytological enrichment of Xist RNA and heterochromatic modifications on the inactive X chromosome (Xi), and these modifications become enriched at the Xi after cell stimulation. Here, we examined allele-specific gene expression and the epigenomic profiles of the Xi following T cell stimulation. We found that the Xi in unstimulated T cells is largely dosage compensated and is enriched with the repressive H3K27me3 modification, but not the H2AK119-ubiquitin (Ub) mark, even at promoters of XCI escape genes. Upon CD3/CD28-mediated T cell stimulation, the Xi accumulates H2AK119-Ub and H3K27me3 across the Xi. Next, we examined the T cell signaling pathways responsible for Xist RNA localization to the Xi and found that T cell receptor (TCR) engagement, specifically NF-κB signaling downstream of TCR, is required. Disruption of NF-κB signaling, using inhibitors or genetic deletions, in mice and patients with immunodeficiencies prevents Xist/XIST RNA accumulation at the Xi and alters expression of some X-linked genes. Our findings reveal a novel connection between NF-κB signaling pathways which impact XCI maintenance in female T cells.

Biochemical progression free and overall survival among Black men with stage IV prostate cancer in South Africa: Results from a prospective cohort study.

BACKGROUND: Men of African descent are disproportionately affected by prostate cancer (PCa), and many have metastatic disease at presentation. In South Africa (SA), androgen deprivation therapy (ADT) is the first-line treatment for stage IV PCa. OBJECTIVE: To identify predictors of overall survival (OS) in Black South African men with stage IV PCa treated with ADT. DESIGN, SETTING, AND PARTICIPANTS: Men diagnosed with prostate cancer (3/22/2016-10/30/2020) at Chris Hani Baragwanath Academic Hospital in Soweto, Johannesburg, were recruited for the Men of African Descent with Cancer of the Prostate study. We included men with newly diagnosed stage IV PCa treated with ADT who had a prostate-specific antigen (PSA) level drawn prior to initiation of ADT and had ≥1 PSA drawn ≥12 weeks after ADT start. OUTCOMES MEASURES AND STATISTICAL ANALYSIS: We used Kaplan-Meier statistics to estimate OS and Cox regression models to identify predictors of OS. RESULTS AND LIMITATIONS: Of the 1097 men diagnosed with prostate cancer, we included 153 men with stage IV PCa who received ADT and met PSA requirements. The median age was 68.0 years (interquartile range 64-73 years). Median OS from time of ADT initiation was 3.39 years (95% confidence interval (CI): 3.14%-noncalculable), while biochemical progression-free survival was 2.36 years (95% CI: 2.03%-3.73%). Biochemical progression (HR 3.52, 95% CI: 1.85%-6.70%), PSA nadir level >4 ng/mL (HR 3.77, 95% CI: 1.86%-7.62%), alkaline phosphatase level at diagnosis >150 IU/dL (HR 3.09, 95% CI: 1.64%-5.83%), and hemoglobin at diagnosis <13.5 g/dL (HR 2.90, 95% CI: 1.28%-6.56%) were associated with worse OS. CONCLUSIONS: In this study, we identified factors associated with poor OS among Black South African men with stage IV PCa treated with ADT. These factors may be useful in identifying patients for upfront treatment escalation, including the use of docetaxel chemotherapy or escalation of therapy at the time of biochemical progression. PATIENT SUMMARY: In this study, we found that high alkaline phosphatase level, anemia at diagnosis, and high PSA nadir after initiation of androgen deprivation therapy are associated with worse overall survival among Black South African men treated with androgen deprivation therapy for metastatic prostate cancer.

Chemotherapy and Immune Checkpoint Blockade for Gastric and Gastroesophageal Junction Adenocarcinoma.

Importance: Combining immune checkpoint blockade (ICB) with chemotherapy improves outcomes in patients with metastatic gastric and gastroesophageal junction (G/GEJ) adenocarcinoma; however, whether this combination has activity in the perioperative setting remains unknown. Objective: To evaluate the safety and preliminary activity of perioperative chemotherapy and ICB followed by maintenance ICB in resectable G/GEJ adenocarcinoma. Design, Setting, and Participants: This investigator-initiated, multicenter, open-label, single-stage, phase 2 nonrandomized controlled trial screened 49 patients and enrolled 36 patients with resectable G/GEJ adenocarcinoma from February 10, 2017, to June 17, 2021, with a median (range) follow-up of 35.2 (17.4-73.0) months. Thirty-four patients were deemed evaluable for efficacy analysis, with 28 (82.4%) undergoing curative resection. This study was performed at 4 referral institutions in the US. Interventions: Patients received 3 cycles of capecitabine, 625 mg/m2, orally twice daily for 21 days; oxaliplatin, 130 mg/m2, intravenously and pembrolizumab, 200 mg, intravenously with optional epirubicin, 50 mg/m2, every 3 weeks before and after surgery with an additional cycle of pembrolizumab before surgery. Patients received 14 additional doses of maintenance pembrolizumab. Main Outcomes and Measures: The primary end point was pathologic complete response (pCR) rate. Secondary end points included overall response rate, disease-free survival (DFS), overall survival (OS), and safety. Results: A total of 34 patients (median [range] age, 65.5 [25-90] years; 23 [67.6%] male) were evaluable for efficacy. Of these patients, 28 (82.4%) underwent curative resection, 7 (20.6%; 95% CI, 10.1%-100%) achieved pCR, and 6 (17.6%) achieved a pathologic near-complete response. Of the 28 patients who underwent resection, 4 (14.3%) experienced disease recurrence. The median DFS and OS were not reached. The 2-year DFS was 67.8% (95% CI, 0.53%-0.87%) and the OS was 80.6% (95% CI, 0.68%-0.96%). Treatment-related grade 3 or higher adverse events for evaluable patients occurred in 20 patients (57.1%), and 12 (34.3%) experienced immune-related grade 3 or higher adverse events. Conclusion and Relevance: In this trial of unselected patients with resectable G/GEJ adenocarcinoma, capecitabine, oxaliplatin, and pembrolizumab resulted in a pCR rate of 20.6% and was well tolerated. This trial met its primary end point and supports the development of checkpoint inhibition in combination with perioperative chemotherapy in locally advanced G/GEJ adenocarcinoma. Trial Registration: ClinicalTrials.gov Identifier: NCT02918162.

Prognostic and therapeutic impact of the KRAS G12C mutation in colorectal cancer.

KRAS G12C mutations are critical in the pathogenesis of multiple cancer types, including non-small cell lung (NSCLC), pancreatic ductal adenocarcinoma (PDAC), and colorectal (CRC) cancers. As such, they have increasingly become a target of novel therapies in the management of these malignancies. However, the therapeutic success of KRAS G12C inhibitors to date has been far more limited in CRC and PDAC than NSCLC. In this review, we briefly summarize the biochemistry of KRAS targeting and treatment resistance, highlight differences in the epidemiology of various G12C-mutated cancers, and provide an overview of the published data on KRAS G12C inhibitors for various indications. We conclude with a summary of ongoing clinical trials in G12C-mutant CRC and a discussion of future directions in the management of this disease. KRAS G12C mutation, targeted therapies, colorectal cancer, non-small cell lung cancer, pancreatic cancer, drug development.

The prospect of universal coronavirus immunity: characterization of reciprocal and non-reciprocal T cell responses against SARS-CoV2 and common human coronaviruses.

T cell immunity plays a central role in clinical outcomes of Coronavirus Infectious Disease 2019 (COVID-19) and T cell-focused vaccination or cellular immunotherapy might provide enhanced protection for some immunocompromised patients. Pre-existing T cell memory recognizing SARS-CoV-2 antigens antedating COVID-19 infection or vaccination, may have developed as an imprint of prior infections with endemic non-SARS human coronaviruses (hCoVs) OC43, HKU1, 229E, NL63, pathogens of "common cold". In turn, SARS-CoV-2-primed T cells may recognize emerging variants or other hCoV viruses and modulate the course of subsequent hCoV infections. Cross-immunity between hCoVs and SARS-CoV-2 has not been well characterized. Here, we systematically investigated T cell responses against the immunodominant SARS-CoV-2 spike, nucleocapsid and membrane proteins and corresponding antigens from α- and ß-hCoVs among vaccinated, convalescent, and unexposed subjects. Broad T cell immunity against all tested SARS-CoV-2 antigens emerged in COVID-19 survivors. In convalescent and in vaccinated individuals, SARS-CoV-2 spike-specific T cells reliably recognized most SARS-CoV-2 variants, however cross-reactivity against the omicron variant was reduced by approximately 47%. Responses against spike, nucleocapsid and membrane antigens from endemic hCoVs were significantly more extensive in COVID-19 survivors than in unexposed subjects and displayed cross-reactivity between α- and ß-hCoVs. In some, non-SARS hCoV-specific T cells demonstrated a prominent non-reciprocal cross-reactivity with SARS-CoV-2 antigens, whereas a distinct anti-SARS-CoV-2 immunological repertoire emerged post-COVID-19, with relatively limited cross-recognition of non-SARS hCoVs. Based on this cross-reactivity pattern, we established a strategy for in-vitro expansion of universal anti-hCoV T cells for adoptive immunotherapy. Overall, these results have implications for the future design of universal vaccines and cell-based immune therapies against SARS- and non-SARS-CoVs.

Phylogenies increase power to detect highly transmissible viral genome variants.

As demonstrated by the SARS-CoV-2 pandemic, the emergence of novel viral strains with increased transmission rates poses a significant threat to global health. Viral genome sequences, combined with statistical models of sequence evolution, may provide a critical tool for early detection of these strains. Using a novel statistical model that links transmission rates to the entire viral genome sequence, we study the power of phylogenetic methods-using a phylogenetic tree relating viral samples-and count-based methods-using case-counts of variants over time-to detect increased transmission rates, and to identify causative mutations. We find that phylogenies in particular can detect novel variants very soon after their origin, and may facilitate the development of early detection systems for outbreak surveillance.

Using mechanistic models and machine learning to design single-color multiplexed nascent chain tracking experiments.

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Our simulation results show that with careful application this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. We conclude that the proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell Signaling applications requiring simultaneous study of multiple mRNAs.

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.

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].

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.

Using Mechanistic Models and Machine Learning to Design Single-Color Multiplexed Nascent Chain Tracking Experiments.

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Through simulation, we show that with careful application, this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. The proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell signalling applications requiring simultaneous study of multiple mRNAs.

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.

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/.

The prospect of universal coronavirus immunity: a characterization of reciprocal and non-reciprocal T cell responses against SARS-CoV2 and common human coronaviruses.

T cell immunity plays a central role in clinical outcomes of Coronavirus Infectious Disease 2019 (COVID-19). Therefore, T cell-focused vaccination or cellular immunotherapy might provide enhanced protection for immunocompromised patients. Pre-existing T cell memory recognizing SARS-CoV2 antigens antedating COVID-19 infection or vaccination, may have developed as an imprint of prior infections with endemic non-SARS human coronaviruses (hCoVs) OC43, HKU1, 229E, NL63, pathogens of "common cold". In turn, SARS-CoV2-primed T cells may recognize emerging variants or other hCoV viruses and modulate the course of subsequent hCoV infections. Cross-immunity between hCoVs and SARS-CoV2 has not been well characterized. Here, we systematically investigated T cell responses against the immunodominant SARS-CoV2 spike, nucleocapsid and membrane proteins and corresponding antigens from α- and ß-hCoVs among vaccinated, convalescent, and unexposed subjects. Broad T cell immunity against all tested SARS-CoV2 antigens emerged in COVID-19 survivors. In convalescent and in vaccinated individuals, SARS-CoV2 spike-specific T cells reliably recognized most SARS-CoV2 variants, however cross-reactivity against the omicron variant was reduced by approximately 50%. Responses against spike, nucleocapsid and membrane antigens from endemic hCoVs were more extensive in COVID-19 survivors than in unexposed subjects and displayed cross-reactivity between α- and ß-hCoVs. In some, non-SARS hCoVspecific T cells demonstrated a prominent non-reciprocal cross-reactivity with SARS-CoV2 antigens, whereas a distinct anti-SARS-CoV2 immunological repertoire emerged post-COVID-19, with relatively limited cross-recognition of non-SARS hCoVs. Based on this cross-reactivity pattern, we established a strategy for in-vitro expansion of universal anti-hCoV T cells for adoptive immunotherapy. Overall, these results have implications for the future design of universal vaccines and cell-based immune therapies against SARS- and non-SARS-CoVs.

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.].

Cancer genetic mutation prevalence in sub-Saharan Africa: A review of existing data.

BACKGROUND: Cancer represents a leading cause of death worldwide. Germline mutations in several genes increase the risk of developing several cancers, including cancers of the breast, ovary, pancreas, colorectum, and melanoma. An understanding of the population prevalence of pathogenic germline variants can be helpful in the design of public health interventions, such as genetic testing, which has downstream implications for cancer screening, prevention, and treatment. While population-based studies of pathogenic germline variants exist, most such studies have been conducted in White populations. Limited data exist regarding the prevalence of germline mutations within sub-Saharan African populations. MATERIALS AND METHODS: We identified countries defined as sub-Saharan Africa by the World Bank and conducted a scoping literature review using PubMed. For each country, we identified and summarized studies that focused on the prevalence of germline genetic mutations with sample sizes >10 and in a population directly from sub-Saharan Africa, either with or without diseases associated with the relevant genetic mutations. Studies that evaluated the prevalence of somatic or likely benign variants were excluded. RESULTS: Within the 48 countries in sub-Saharan Africa, we identified 34 studies which meet the inclusion criteria. Twenty studies were conducted in South Africa, Nigeria, or Burkina Faso; four countries had more than two published papers. We found that 33 of 48 countries in sub-Saharan Africa lacked any genetic studies. Notably, there has been an increase in relevant studies starting in 2020. Importantly, of the 34 studies identified, 29 included data on BRCA1 or BRCA2. Data on the prevalence of mutations contributing to familial cancer syndromes other than BRCA1 and BRCA2 was limited. CONCLUSIONS: While some progress has been made towards understanding the prevalence of germline mutations in cancer susceptibility genes, the characterization of genetic mutations among sub-Saharan African populations remains strikingly incomplete. Given the genetic diversity in the region, there remains a great need for large-scale, population-based studies to understand the prevalence of germline pathogenic variants and adequately capture all the subpopulations in this part of the world.

Cytotoxic chemotherapy potentiates the immune response and efficacy of combination CXCR4/PD-1 inhibition in models of pancreatic ductal adenocarcinoma.

Purpose: The CXCL12-CXCR4 chemokine axis plays a significant role in modulating T-cell infiltration into the pancreatic tumor microenvironment. Despite promising preclinical findings, clinical trials combining inhibitors of CXCR4 (AMD3100/BL-8040) and anti-programmed death 1/ligand1 (anti-PD1/PD-L1) have failed to improve outcomes. Experimental Design: We utilized a novel ex vivo autologous patient-derived immune/organoid (PDIO) co-culture system using human peripheral blood mononuclear cells and patient derived tumor organoids, and in vivo the autochthonous LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx-1-Cre (KPC) pancreatic cancer mouse model to interrogate the effects of either monotherapy or all combinations of gemcitabine, AMD3100, and anit-PD1 on CD8+ T cell activation and survival. Results: We demonstrate that disruption of the CXCL12-CXCR4 axis using AMD3100 leads to increased migration and activation of CD8+ T-cells. In addition, when combined with the cytotoxic chemotherapy gemcitabine, CXCR4 inhibition further potentiated CD8+ T-cell activation. We next tested the combination of gemcitabine, CXCR4 inhibition, and anti-PD1 in the KPC pancreatic cancer mouse model and demonstrate that this combination markedly impacted the tumor immune microenvironment by increasing infiltration of natural killer cells, the ratio of CD8+ to regulatory T-cells, and tumor cell death while decreasing tumor cell proliferation. Moreover, this combination extended survival in KPC mice. Conclusions: These findings suggest that combining gemcitabine with CXCR4 inhibiting agents and anti-PD1 therapy controls tumor growth by reducing immunosuppression and potentiating immune cell activation and therefore may represent a novel approach to treating pancreatic cancer.

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.