Clustering of temporal gene expression data with mixtures of mixed effects models

While time-dependent processes are important to biological functions, methods to leverage temporal information from large data have remained computationally challenging. In temporal gene-expression data, clustering can be used to identify genes with shared function in complex processes. Algorithms like K-Means and standard Gaussian mixture-models (GMM) fail to account for variability in replicated data or repeated measures over time and require a priori cluster number assumptions, evaluating many cluster numbers to select an optimal result. An improved penalized-GMM offers a computationally-efficient algorithm to simultaneously optimize cluster number and labels. The work presented in this dissertation was motivated by mice bone-fracture models interested in determining patterns of temporal gene-expression during bone-healing progression. To solve this, an extension to the penalized-GMM was proposed to account for correlation between replicated data and repeated measures over time by introducing random-effects using a mixture of mixed-effects polynomial regression models and an entropy-penalized EM-Algorithm (EPEM). First, performance of EPEM for different mixed-effects models were assessed with simulation studies and applied to the fracture-healing study. Second, modifications to address the high computational cost of EPEM were considered that either clustered subsets of data determined by predicted polynomial-order (S-EPEM) or used modified-initialization to decrease the initial burden (I-EPEM). Each was compared to EPEM and applied to the fracture-healing study. Lastly, as varied rates of fracture-healing were observed for mice with different genetic-backgrounds (strains), a new analysis strategy was proposed to compare patterns of temporal gene-expression between different mice-strains and assessed with simulation studies. Expression-profiles for each strain were treated as separate objects to cluster in order to determine genes clustered into different groups across strain. We found that the addition of random-effects decreased accuracy of predicted cluster labels compared to K-Means, GMM, and fixed-effects EPEM. Polynomial-order optimization with BIC performed with highest accuracy, and optimization on subspaces obtained with singular-value-decomposition performed well. Computation time for S-EPEM was much reduced with a slight decrease in accuracy. I-EPEM was comparable to EPEM with similar accuracy and decrease in computation time. Application of the new analysis strategy on fracture-healing data identified several distinct temporal gene-expression patterns for the different strains.2021-02-27T00:00:00

Human uterine leiomyoma-derived fibroblasts stimulate uterine leiomyoma cell proliferation and collagen type I production, and activate RTKs and TGF beta receptor signaling in coculture

BACKGROUND: Uterine leiomyomas (fibroids) are benign smooth muscle tumors that often contain an excessive extracellular matrix (ECM). In the present study, we investigated the interactions between human uterine leiomyoma (UtLM) cells and uterine leiomyoma-derived fibroblasts (FB), and their importance in cell growth and ECM protein production using a coculture system. RESULTS: We found enhanced cell proliferation, and elevated levels of ECM collagen type I and insulin-like growth factor-binding protein-3 after coculturing. There was also increased secretion of vascular endothelial growth factor, epidermal growth factor, fibroblast growth factor-2, and platelet derived growth factor A and B in the media of UtLM cells cocultured with FB. Protein arrays revealed increased phosphorylated receptor tyrosine kinases (RTKs) of the above growth factor ligands, and immunoblots showed elevated levels of the RTK downstream effector, phospho-mitogen activated protein kinase 44/42 in cocultured UtLM cells. There was also increased secretion of transforming growth factor-beta 1 and 3, and immunoprecipitated transforming growth factor-beta receptor I from cocultured UtLM cells showed elevated phosphoserine expression. The downstream effectors phospho-small mothers against decapentaplegic -2 and -3 protein (SMAD) levels were also increased in cocultured UtLM cells. However, none of the above effects were seen in normal myometrial cells cocultured with FB. The soluble factors released by tumor-derived fibroblasts and/or UtLM cells, and activation of the growth factor receptors and their pathways stimulated the proliferation of UtLM cells and enhanced the production of ECM proteins. CONCLUSIONS: These data support the importance of interactions between fibroid tumor cells and ECM fibroblasts in vivo, and the role of growth factors, and ECM proteins in the pathogenesis of uterine fibroids

Census-derived migration data as a tool for informing malaria elimination policy

Background: Numerous countries around the world are approaching malaria elimination. Until global eradication is achieved, countries that successfully eliminate the disease will contend with parasite reintroduction through international movement of infected people. Human-mediated parasite mobility is also important within countries near elimination, as it drives parasite flows that affect disease transmission on a subnational scale.Methods: Movement patterns exhibited in census-based migration data are compared with patterns exhibited in a mobile phone data set from Haiti to quantify how well migration data predict short-term movement patterns. Because short-term movement data were unavailable for Mesoamerica, a logistic regression model fit to migration data from three countries in Mesoamerica is used to predict flows of infected people between subnational administrative units throughout the region.Results: Population flows predicted using census-based migration data correlated strongly with mobile phone-derived movements when used as a measure of relative connectivity. Relative population flows are therefore predicted using census data across Mesoamerica, informing the areas that are likely exporters and importers of infected people. Relative population flows are used to identify community structure, useful for coordinating interventions and elimination efforts to minimize importation risk. Finally, the ability of census microdata inform future intervention planning is discussed in a country-specific setting using Costa Rica as an example.Conclusions: These results show long-term migration data can effectively predict the relative flows of infected people to direct malaria elimination policy, a particularly relevant result because migration data are generally easier to obtain than short-term movement data such as mobile phone records. Further, predicted relative flows highlight policy-relevant population dynamics, such as major exporters across the region, and Nicaragua and Costa Rica’s strong connection by movement of infected people, suggesting close coordination of their elimination efforts. Country-specific applications are discussed as well, such as predicting areas at relatively high risk of importation, which could inform surveillance and treatment strategies.<br/

Dynamics of Immune Reconstitution and Activation Markers in HIV+ Treatment-Naïve Patients Treated with Raltegravir, Tenofovir Disoproxil Fumarate and Emtricitabine

Background: The dynamics of CD4+ T cell reconstitution and changes in immune activation and inflammation in HIV-1 disease following initiation of antiretroviral therapy (ART) are incompletely defined and their underlying mechanisms poorly understood. Methods: Thirty-nine treatment-naïve patients were treated with raltegravir, tenofovir DF and emtricitabine. Immunologic and inflammatory indices were examined in persons with sustained virologic control during 48 weeks of therapy. Results: Initiation of ART increased CD4+ T cell numbers and decreased activation and cell cycle entry among CD4+ and CD8+ T cell subsets, and attenuated markers of coagulation (D-dimer levels) and inflammation (IL-6 and TNFr1). These indices decayed at different rates and almost all remained elevated above levels measured in HIV-seronegatives through 48 weeks of viral control. Greater first and second phase CD4+ T cell restoration was related to lower T cell activation and cell cycling at baseline, to their decay with treatment, and to baseline levels of selected inflammatory indices, but less so to their changes on therapy. Conclusions: ART initiation results in dynamic changes in viral replication, T cell restoration, and indices of immune activation, inflammation, and coagulation. These findings suggest that determinants of T cell activation/cycling and inflammation/coagulation may have distinguishable impact on immune homeostasis. Trial Registration Clinicaltrials.gov NCT0066097

Boceprevir and Antiretroviral Pharmacokinetic Interactions in HIV/HCV Co-infected Persons: AIDS Clinical Trials Group Study A5309s

Objective: The objective of this study was to determine the magnitude of drug interactions between the hepatitis C virus (HCV) protease inhibitor boceprevir (BOC) and antiretroviral (ARV) agents in persons with HIV/HCV co-infection. Methods: Participants taking two nucleos(t)ide analogs with either efavirenz, raltegravir, or ritonavir-boosted atazanavir, darunavir, or lopinavir underwent intensive pharmacokinetic (PK) sampling for ARV 2 weeks before (week 2) and 2 weeks after initiating BOC (week 6) and for BOC at week 6. Geometric mean ratios (GMRs) and 90% confidence intervals (CIs) were used to compare ARV PK at weeks 2 and 6 and BOC PK at week 6 to historical data (HD) in healthy volunteers and HCV mono-infected patients. Results: ARV PK was available for 55 participants. BOC reduced atazanavir and darunavir exposures by 30 and 42%, respectively. BOC increased raltegravir maximum concentration (C max) by 71%. BOC did not alter efavirenz PK. BOC PK was available for 53 participants. BOC exposures were similar in these HIV/HCV co-infected participants compared with HD in healthy volunteers, but BOC minimum concentrations (C min) were lower with all ARV agents (by 34–73%) compared with HD in HCV mono-infected patients. Conclusions: Effects of BOC on ARV PK in these HIV/HCV co-infected individuals were similar to prior studies in healthy volunteers. However, some differences in the effects of ARV on BOC PK were observed, indicating the magnitude of interactions may differ in HCV-infected individuals versus healthy volunteers. Findings highlight the need to conduct interaction studies with HCV therapies in the population likely to receive the combination

Virologic Response, Early HIV-1 Decay, and Maraviroc Pharmacokinetics With the Nucleos(t)ide-Free Regimen of MaravIroc Plus Darunavir/Ritonavir in a Pilot Study

To address the need for nucleos(t)ide reverse transcriptase inhibitor (NRTI)-sparing regimens, we explored the virologic and pharmacokinetic characteristics of maraviroc plus ritonavir-boosted darunavir in a single-arm, open-label, 96-week study

Histopathologic changes in the uterus, cervix and vagina of immature CD-1 mice exposed to low doses of perfluorooctanoic acid (PFOA) in a uterotrophic assay

The estrogenic and antiestrogenic potential of perfluorooctanoic acid (PFOA) was assessed using an immature mouse uterotrophic assay and by histologic evaluation of the uterus, cervix and vagina following treatment. Female offspring of CD-1 dams were weaned at 18 days old and assigned to groups of equal weight, and received 0, 0.01, 0.1, or 1 mg PFOA/kg BW/d by gavage with or without 17-β estradiol (E2, 500 μg/kg/d) from PND18-20 (n=8/treatment/block). At 24 hr after the third dose (PND 21), uteri were removed and weighed. Absolute and relative uterine weights were significantly increased in the 0.01 mg/kg PFOA only group. Characteristic estrogenic changes were present in all E2-treated mice; however, they were minimally visible in the 0.01 PFOA only mice. These data suggest that at a low dose PFOA produces minimal histopathologic changes in the reproductive tract of immature female mice, and does not antagonize the cellular effects of E2

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin