Integrative Transcriptomic Analysis of Long Intergenic Non-Coding RNAs in Cancer.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Opportunities and obstacles for deep learning in biology and medicine

Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems-patient classification, fundamental biological processes and treatment of patients-and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges. Following from an extensive literature review, we find that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art. Even though improvements over previous baselines have been modest in general, the recent progress indicates that deep learning methods will provide valuable means for speeding up or aiding human investigation. Though progress has been made linking a specific neural network\u27s prediction to input features, understanding how users should interpret these models to make testable hypotheses about the system under study remains an open challenge. Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine

Genome-scale hypomethylation in the cord blood DNAs associated with early onset preeclampsia

Background: Preeclampsia is one of the leading causes of fetal and maternal morbidity and mortality worldwide. Preterm babies of mothers with early onset preeclampsia (EOPE) are at higher risks for various diseases later on in life, including cardiovascular diseases. We hypothesized that genome-wide epigenetic alterations occur in cord blood DNAs in association with EOPE and conducted a case control study to compare the genome-scale methylome differences in cord blood DNAs between 12 EOPE-associated and 8 normal births. Results: Bioinformatics analysis of methylation data from the Infinium HumanMethylation450 BeadChip shows a genome-scale hypomethylation pattern in EOPE, with 51,486 hypomethylated CpG sites and 12,563 hypermethylated sites (adjusted P <0.05). A similar trend also exists in the proximal promoters (TSS200) associated with protein-coding genes. Using summary statistics on the CpG sites in TSS200 regions, promoters of 643 and 389 genes are hypomethylated and hypermethylated, respectively. Promoter-based differential methylation (DM) analysis reveals that genes in the farnesoid X receptor and liver X receptor (FXR/LXR) pathway are enriched, indicating dysfunction of lipid metabolism in cord blood cells. Additional biological functional alterations involve inflammation, cell growth, and hematological system development. A two-way ANOVA analysis among coupled cord blood and amniotic membrane samples shows that a group of genes involved in inflammation, lipid metabolism, and proliferation are persistently differentially methylated in both tissues, including IL12B, FAS, PIK31, and IGF1. Conclusions: These findings provide, for the first time, evidence of prominent genome-scale DNA methylation modifications in cord blood DNAs associated with EOPE. They may suggest a connection between inflammation and lipid dysregulation in EOPE-associated newborns and a higher risk of cardiovascular diseases later in adulthood

Alternative Splicing Promotes Tumour Aggressiveness and Drug Resistance in African American Prostate Cancer.

linical challenges exist in reducing prostate cancer (PCa) disparities. The RNA splicing landscape of PCa across racial populations has not been fully explored as a potential molecular mechanism contributing to race-related tumour aggressiveness. Here, we identify novel genome-wide, race-specific RNA splicing events as critical drivers of PCa aggressiveness and therapeutic resistance in African American (AA) men. AA-enriched splice variants of PIK3CD, FGFR3, TSC2 and RASGRP2 contribute to greater oncogenic potential compared with corresponding European American (EA)-expressing variants. Ectopic overexpression of the newly cloned AA-enriched variant, PIK3CD-S, in EA PCa cell lines enhances AKT/mTOR signalling and increases proliferative and invasive capacity in vitro and confers resistance to selective PI3Kδ inhibitor, CAL-101 (idelalisib), in mouse xenograft models. High PIK3CD-S expression in PCa specimens associates with poor survival. These results highlight the potential of RNA splice variants to serve as novel biomarkers and molecular targets for developmental therapeutics in aggressive PCa

Alternative Splicing Promotes Tumour Aggressiveness and Drug Resistance in African American Prostate Cancer.

linical challenges exist in reducing prostate cancer (PCa) disparities. The RNA splicing landscape of PCa across racial populations has not been fully explored as a potential molecular mechanism contributing to race-related tumour aggressiveness. Here, we identify novel genome-wide, race-specific RNA splicing events as critical drivers of PCa aggressiveness and therapeutic resistance in African American (AA) men. AA-enriched splice variants of PIK3CD, FGFR3, TSC2 and RASGRP2 contribute to greater oncogenic potential compared with corresponding European American (EA)-expressing variants. Ectopic overexpression of the newly cloned AA-enriched variant, PIK3CD-S, in EA PCa cell lines enhances AKT/mTOR signalling and increases proliferative and invasive capacity in vitro and confers resistance to selective PI3Kδ inhibitor, CAL-101 (idelalisib), in mouse xenograft models. High PIK3CD-S expression in PCa specimens associates with poor survival. These results highlight the potential of RNA splice variants to serve as novel biomarkers and molecular targets for developmental therapeutics in aggressive PCa

Alternative Splicing Promotes Tumour Aggressiveness and Drug Resistance in African American Prostate Cancer.

linical challenges exist in reducing prostate cancer (PCa) disparities. The RNA splicing landscape of PCa across racial populations has not been fully explored as a potential molecular mechanism contributing to race-related tumour aggressiveness. Here, we identify novel genome-wide, race-specific RNA splicing events as critical drivers of PCa aggressiveness and therapeutic resistance in African American (AA) men. AA-enriched splice variants of PIK3CD, FGFR3, TSC2 and RASGRP2 contribute to greater oncogenic potential compared with corresponding European American (EA)-expressing variants. Ectopic overexpression of the newly cloned AA-enriched variant, PIK3CD-S, in EA PCa cell lines enhances AKT/mTOR signalling and increases proliferative and invasive capacity in vitro and confers resistance to selective PI3Kδ inhibitor, CAL-101 (idelalisib), in mouse xenograft models. High PIK3CD-S expression in PCa specimens associates with poor survival. These results highlight the potential of RNA splice variants to serve as novel biomarkers and molecular targets for developmental therapeutics in aggressive PCa

The core-independent promoter-specific interaction of primary sigma factor

Previous studies have led to a model in which the promoter-specific recognition of prokaryotic transcription initiation factor, sigma (σ), is core dependent. Most σ functions were studied on the basis of this tenet. Here, we provide in vitro evidence demonstrating that the intact Bacillus subtilis primary sigma, σA, by itself, is able to interact specifically with promoter deoxyribonucleic acid (DNA), albeit with low sequence selectivity. The core-independent promoter-specific interaction of the σA is −10 specific. However, the promoter −10 specific interaction is unable to allow the σA to discern the optimal promoter spacing. To fulfill this goal, the σA requires assistance from core RNA polymerase (RNAP). The ability of σ, by itself, to interact specifically with promoter might introduce a critical new dimension of study in prokaryotic σ function

Working group on ecosystem assessment of Western European shelf seas (WGEAWESS)

The ICES Working Group on Ecosystem Assessment of Western European Shelf Seas (WGEA-WESS) aims to provide high quality science in support to holistic, adaptive, evidence-based man-agement in the Celtic seas, Bay of Biscay and Iberian coast regions. The group works towards developing integrated ecosystem assessments for both the (i) Celtic Seas and (ii) Bay of Biscay and Iberian Coast which are summarized in the Ecosystem Overviews (EOs) advice products that were recently updated. Integrated Trend Analysis (ITA) were performed for multiple sub-ecoregions and used to develop an understanding of ecosystem responses to pressures at varying spatial scales. Ecosystem models (primarily Ecopath with Ecosim; EwE) were developed and identified for fisheries and spatial management advice. The updated Celtic Seas EO represents a large step forward for EOs, with the inclusion of novel sections on climate change, foodweb and productivity, the first application of the new guidelines for building the conceptual diagram, inclusion of socio-economic indicators, and progress made toward complying with the Transparent Assessment Framework (TAF). We highlight ongoing issues relevant to the development and communication of EO conceptual diagrams. A common methodology using dynamic factor analysis (DFA) was used to perform ITA in a comparable way for seven subregions. This was supported by the design and compilation of the first standardized cross-regional dataset. A comparison of the main trends evidenced among subregions over the period 1993–2020 was conducted and will be published soon. A list of available and developing EWE models for the region was also generated. Here, we re-port on the advances in temporal and spatial ecosystem modelling, such as their capacity to model the impacts of sector activities (e.g. renewables and fisheries) and quantify foodweb indi-cators. We also reflect on model quality assessment with the key run of the Irish sea EwE model. The group highlighted the hurdles and gaps in current models in support of EBM, such as the choice of a relevant functional, spatial, and temporal scales and the impacts of model structure on our capacity to draw comparisons from models of different regions. The group aims to ad-dress these issues in coming years and identify routes for ecosystem model derived information into ICES advice.info:eu-repo/semantics/publishedVersio