Multi-antigen Vaccination With Simultaneous Engagement of the OX40 Receptor Delays Malignant Mesothelioma Growth and Increases Survival in Animal Models

Malignant Mesothelioma (MM) is a rare and highly aggressive cancer that develops from mesothelial cells lining the pleura and other internal cavities, and is often associated with asbestos exposure. To date, no effective treatments have been made available for this pathology. Herein, we propose a novel immunotherapeutic approach based on a unique vaccine targeting a series of antigens that we found expressed in different MM tumors, but largely undetectable in normal tissues. This vaccine, that we term p-Tvax, is comprised of a series of immunogenic peptides presented by both MHC-I and -II to generate robust immune responses. The peptides were designed using in silico algorithms that discriminate between highly immunogenic T cell epitopes and other harmful epitopes, such as suppressive regulatory T cell epitopes and autoimmune epitopes. Vaccination of mice with p-Tvax led to antigen-specific immune responses that involved both CD8+ and CD4+ T cells, which exhibited cytolytic activity against MM cells in vitro. In mice carrying MM tumors, p-Tvax increased tumor infiltration of CD4+ T cells. Moreover, combining p-Tvax with an OX40 agonist led to decreased tumor growth and increased survival. Mice treated with this combination immunotherapy displayed higher numbers of tumor-infiltrating CD8+ and CD4+ T cells and reduced T regulatory cells in tumors. Collectively, these data suggest that the combination of p-Tvax with an OX40 agonist could be an effective strategy for MM treatment

Complementary feeding: a Global Network cluster randomized controlled trial

Background: Inadequate and inappropriate complementary feeding are major factors contributing to excess morbidity and mortality in young children in low resource settings. Animal source foods in particular are cited as essential to achieve micronutrient requirements. The efficacy of the recommendation for regular meat consumption, however, has not been systematically evaluated. Methods/Design: A cluster randomized efficacy trial was designed to test the hypothesis that 12 months of daily intake of beef added as a complementary food would result in greater linear growth velocity than a micronutrient fortified equi-caloric rice-soy cereal supplement. The study is being conducted in 4 sites of the Global Network for Women\u27s and Children\u27s Health Research located in Guatemala, Pakistan, Democratic Republic of the Congo (DRC) and Zambia in communities with toddler stunting rates of at least 20%. Five clusters per country were randomized to each of the food arms, with 30 infants in each cluster. The daily meat or cereal supplement was delivered to the home by community coordinators, starting when the infants were 6 months of age and continuing through 18 months. All participating mothers received nutrition education messages to enhance complementary feeding practices delivered by study coordinators and through posters at the local health center. Outcome measures, obtained at 6, 9, 12, and 18 months by a separate assessment team, included anthropometry, dietary variety and diversity scores, biomarkers of iron, zinc and Vitamin B(12) status (18 months), neurocognitive development (12 and 18 months), and incidence of infectious morbidity throughout the trial. The trial was supervised by a trial steering committee, and an independent data monitoring committee provided oversight for the safety and conduct of the trial. Discussion: Findings from this trial will test the efficacy of daily intake of meat commencing at age 6 months and, if beneficial, will provide a strong rationale for global efforts to enhance local supplies of meat as a complementary food for young children

Riociguat treatment in patients with chronic thromboembolic pulmonary hypertension: Final safety data from the EXPERT registry

Objective: The soluble guanylate cyclase stimulator riociguat is approved for the treatment of adult patients with pulmonary arterial hypertension (PAH) and inoperable or persistent/recurrent chronic thromboembolic pulmonary hypertension (CTEPH) following Phase

Multi-genome annotation of genome fragments using hidden Markov model profiles

Thesis (M.S.)--University of Hawaii at Manoa, 2007.Includes bibliographical references (leaves 78-80).xv, 80 leaves, bound : ill. ; 29 cm

Kernel-based empirical bayesian classification methods with applications to protein phosphorylation and non-coding RNA

Ph.D. University of Hawaii at Manoa 2014.Includes bibliographical references.With the advancement of high-throughput sequencing technologies, a new era of "big data" biological research has dawned. However, the abundance of biological data presents many challenges in their analysis and it has proven very difficult to extract important information out of the data. One approach to this problem is to use the methods of machine learning. In this dissertation, we describe novel probabilistic kernel-based learning methods and demonstrate their practical applicability by solving major bioinformatics problems at the transcriptome and proteome levels where the resulting tools are expected to help biologists further elucidate the important information contained in their data. The proposed binary classification method, the Classification Relevance Units Machine (CRUM), employs the theory of kernel and empirical Bayesian methods to achieve non-linear classification and high generalization. We demonstrate the practical applicability of CRUM by applying it to the prediction of protein phosphorylation sites, which helps explain the mechanisms that control many biochemical processes. Then we develop an extension of CRUM to solve multiclass problems, called the Multiclass Relevance Units Machine (McRUM). McRUM uses the error correcting output codes framework to decompose a multiclass problem into a set of binary problems. We devise a linear-time algorithm to aggregate the results into the final probabilistic multiclass prediction to allow for predictions in large scale applications. We demonstrate the practical applicability of McRUM through a solution to the identification of mature microRNA (miRNA) and piwi-interacting RNA (piRNA) in small RNA sequencing datasets. This provides biologists a tool to help discover novel miRNA and piRNA to further understand the molecular processes of the organisms they study

Prediction of Mature MicroRNA and Piwi-Interacting RNA without a Genome Reference or Precursors

The discovery of novel microRNA (miRNA) and piwi-interacting RNA (piRNA) is an important task for the understanding of many biological processes. Most of the available miRNA and piRNA identification methods are dependent on the availability of the organism’s genome sequence and the quality of its annotation. Therefore, an efficient prediction method based solely on the short RNA reads and requiring no genomic information is highly desirable. In this study, we propose an approach that relies primarily on the nucleotide composition of the read and does not require reference genomes of related species for prediction. Using an empirical Bayesian kernel method and the error correcting output codes framework, compact models suitable for large-scale analyses are built on databases of known mature miRNAs and piRNAs. We found that the usage of an L1-based Gaussian kernel can double the true positive rate compared to the standard L2-based Gaussian kernel. Our approach can increase the true positive rate by at most 60% compared to the existing piRNA predictor based on the analysis of a hold-out test set. Using experimental data, we also show that our approach can detect about an order of magnitude or more known miRNAs than the mature miRNA predictor, miRPlex

Development of somatic mutation signatures for risk stratification and prognosis in lung and colorectal adenocarcinomas

Abstract Background Prognostic signatures are vital to precision medicine. However, development of somatic mutation prognostic signatures for cancers remains a challenge. In this study we developed a novel method for discovering somatic mutation based prognostic signatures. Results Somatic mutation and clinical data for lung adenocarcinoma (LUAD) and colorectal adenocarcinoma (COAD) from The Cancer Genome Atlas (TCGA) were randomly divided into training (n = 328 for LUAD and 286 for COAD) and validation (n = 167 for LUAD and 141 for COAD) datasets. A novel method of using the log2 ratio of the tumor mutation frequency to the paired normal mutation frequency is computed for each patient and missense mutation. The missense mutation ratios were mean aggregated into gene-level somatic mutation profiles. The somatic mutations were assessed using univariate Cox analysis on the LUAD and COAD training sets separately. Stepwise multivariate Cox analysis resulted in a final gene prognostic signature for LUAD and COAD. Performance was compared to gene prognostic signatures generated using the same pipeline but with different somatic mutation profile representations based on tumor mutation frequency, binary calls, and gene-gene network normalization. Signature high-risk LUAD and COAD cases had worse overall survival compared to the signature low-risk cases in the validation set (log-rank test p-value = 0.0101 for LUAD and 0.0314 for COAD) using mutation tumor frequency ratio (MFR) profiles, while all other methods, including gene-gene network normalization, have statistically insignificant stratification (log-rank test p-value ≥0.05). Most of the genes in the final gene signatures using MFR profiles are cancer-related based on network and literature analysis. Conclusions We demonstrated the robustness of MFR profiles and its potential to be a powerful prognostic tool in cancer. The results are robust according to validation testing and the selected genes are biologically relevant

Adaptive Thermogenesis in a Mouse Model Lacking Selenoprotein Biosynthesis in Brown Adipocytes

Selenoproteins are a class of proteins with the selenium-containing amino acid selenocysteine (Sec) in their primary structure. Sec is incorporated into selenoproteins via recoding of the stop codon UGA, with specific cis and trans factors required during translation to avoid UGA recognition as a stop codon, including a Sec-specific tRNA, tRNA[Ser]Sec, encoded in mice by the gene Trsp. Whole-body deletion of Trsp in mouse is embryonically lethal, while targeted deletion of Trsp in mice has been used to understand the role of selenoproteins in the health and physiology of various tissues. We developed a mouse model with the targeted deletion of Trsp in brown adipocytes (Trspf/f-Ucp1-Cre+/−), a cell type predominant in brown adipose tissue (BAT) controlling energy expenditure via activation of adaptive thermogenesis, mostly using uncoupling protein 1 (Ucp1). At room temperature, Trspf/f-Ucp1-Cre+/− mice maintain oxygen consumption and Ucp1 expression, with male Trspf/f-Ucp1-Cre+/− mice accumulating more triglycerides in BAT than both female Trspf/f-Ucp1-Cre+/− mice or Trspf/f controls. Acute cold exposure neither reduced core body temperature nor changed the expression of selenoprotein iodothyronine deiodinase type II (Dio2), a marker of adaptive thermogenesis, in Trspf/f-Ucp1-Cre+/− mice. Microarray analysis of BAT from Trspf/f-Ucp1-Cre+/− mice revealed glutathione S-transferase alpha 3 (Gsta3) and ELMO domain containing 2 (Elmod2) as the transcripts most affected by the loss of Trsp. Male Trspf/f-Ucp1-Cre+/− mice showed mild hypothyroidism while downregulating thyroid hormone-responsive genes Thrsp and Tshr in their BATs. In summary, modest changes in the BAT of Trspf/f-Ucp1-Cre +/− mice implicate a mild thyroid hormone dysfunction in brown adipocytes