Quantitative Approaches to the Genomics of Clonal Evolution

Many problems in the biological sciences reduce to questions of genetic evolution. Entire classes of medical pathology, such as malignant neoplasia or infectious disease, can be viewed in the light of Darwinian competition of genomes. With the benefit of today's maturing sequencing technologies we can observe and quantify genetic evolution with nucleotide resolution. This provides a molecular view of genetic material that has adapted, or is in the process of adapting, to its local selection pressures. A series of problems will be discussed in this thesis, all involving the mathematical modeling of genomic data derived from clonally evolving populations. We use a variety of computational approaches to characterize over-represented features in the data, with the underlying hypothesis that we may be detecting fitness-conferring features of the biology. In Part I we consider the cross-sectional sampling of human tumors via RNA-sequencing, and devise computational pipelines for detecting oncogenic gene fusions and oncovirus infections. Genomic translocation and oncovirus infection can each be a highly penetrant alteration in a tumor's evolutionary history, with famous examples of both populating the cancer biology literature. In order to exert a transforming influence over the host cell, gene fusions and viral genetic programs need to be expressed and thus can be detected via whole transcriptome sequencing of a malignant cell population. We describe our approaches to predicting oncogenic gene fusions (Chapter 2) and quantifying host-viral interactions (Chapter 3) in large panels of human tumor tissue. The alterations that we characterize prompt the larger question of how the genetics of tumors and viruses might vary in time, leading us to the study of serially sampled populations. In Part II we consider longitudinal sampling of a clonally evolving population. Phylogenetic trees are the standard representation of a clonal process, an evolutionary picture as old as Darwin's voyages on the Beagle. Chapter 4 first reviews phylogenetic inference and then introduces a certain phylogenetic tree space that forms the starting point of our work on the topic. Specifically, Chapter 4 describes the construction of our projective tree space along with an explicit implementation for visualizing point clouds of rescaled trees. The Chapter finishes by defining a method for stable dimensionality reduction of large phylogenies, which is useful for analyzing long genomic time series. In Chapter 5 we consider medically relevant instances of clonal evolution and the longitudinal genetic data sets to which they give rise. We analyze data from (i) the sequencing of cancers along their therapeutic course, (ii) the passaging of a xenografted tumor through a mouse model, and (iii) the seasonal surveillance of H3N2 influenza's hemagglutinin segment. A novel approach to predicting influenza vaccine effectiveness is demonstrated using statistics of point clouds in tree spaces. Our investigations into clonal processes may be extended beyond naturally occurring genomes. In Part III we focus on the directed clonal evolution of populations of synthetic RNAs in vitro. Analogous to the selection pressures exerted upon malignant cells or viral particles, these synthetic RNA genomes can be evolved against a desired fitness objective. We investigate fitness objectives related to reprogramming ribosomal translation. Chapter 6 identifies high fitness RNA pseudoknot geometries capable of inducing ribosomal frameshift, while Chapter 7 takes an unbiased approach to evolving sequence and structural elements that promote stop codon readthrough

Crisis Management and the Public Sector: Key Trends and Perspectives

A crisis is a situation approaching a dangerous phase, which requires urgent intervention to avoid harmful effects on the body of an organization in order to return to normal situation. It is a decisive and critical time for the organization, where the wrong decision can even cost its viability. This situation can shape political, legal, economic, and governmental impact on its activities. From different definitions of crisis, we seek to underscore key elements of a crisis that may threat a public organization and, also, to highlight both the elements of management responsiveness resulting in the loss of control in the organization, regarding the short time demand for decision-making. The key purpose of this chapter is to illustrate the basis available in the international literature, upon which public risk mechanisms can be reviewed and chosen in public sector organizations under the scope of their applicability

The Impact of the COVID-19 Pandemic on the Expenditures of Hellenic Supermarket Customers Spending Clusters: An Econometric Analysis

Purpose: Given the severity and the length of the crisis caused by the COVID-19 pandemic, information on the financial impact of the pandemic becomes useful to enterprises who wish to arm themselves with strategies and policies, designed to combat the effects of similar crises. Such information is particularly useful to grocery retailers, who may need to know the effects of the pandemic on spending behaviour of different spending power classes of consumers. To that end, the study explores the configuration of (supermarket) consumer spending in Greece in relation to the number of: a) reported COVID-19 infections; b) admissions in hospital intensive care units, and: c) number of COVID-19 reported deaths, for the period betweenFebruary the 26th, 2020 to April 30th, 2021. Design/methodology/approach: Methodologically, the paper focuses on an econometric analysis of daily spending reactions of six distinct spending clustersof consumersof Greek nation -wide supermarket chain, measured against official numbers of COVID-19 related metrics in Greece during the period of February 2020- April 2021. The data used, emerged from daily sales records of a national chain of supermarkets in Greece, consisting of 60 stores. Proven econometric causality techniques were used to analyse the data by applying Hsiao's Optimizing Procedure via the “Stepwise Granger Causality”, for the statistical tests of possible interactions between variables. Findings: The study found a phenomenal effect of the number of reported COVID-19 related deaths on consumers’ supermarket spending in Greece. The study revealed the statistically significant effects of the COVID-19 variables on the 6 buyers’ clusters. These statistically significant effects have a diachronic behaviour which is varied in relation to the covid variables. The findings indicate that the biggest fluctuations in daily consumer reactions (on reported COVID-19 related variables) occurred in lower spending clusters of consumers, diminished over a period of about 15 days. The study also revealed that consumers’ spending reaction on infection case is minimal compared to that of reported deaths, signalling a relative apathy to the number of reported infection cases. Research limitations/implications: One basic constraint was the lack of spending data over a longer period of time which would have included the entire pandemic era. Ideally the researchers would prefer to compare customer spending data of several supermarket chains, yet the availability of such data was scarce. The findings also imply that lower spending clusters react more intensively to COVID-19 outcomes and as such marketing efforts to serve these target markets may need to be customized. Originality/value: The interpretation of the results reveals that the level of panic that drives reactionary spending appears to be lower in higher spending consumers. This study contributes to theory by appreciating the Greek supermarket customers’ psychological reaction to COVID-19 related variables, by not relying on self-reported data. Although the study was not designed to reveal the reasons for this occurrence, the results demonstrated variability in the reaction of customer clusters as outcomes of severely negative COVID -19 related reports. The data used were objective and the adopted analysis method was appropriate to the purpose of the study. The paper further suggests that future research could build on this study by: (a) examining causality of variability of customer spending during various phases of the pandemic by applying non-linear and possibly chaotic causality tests on daily data; and (b) identifying the exact threshold of change in consumers’ spending patterns on specific product categories, as influenced by reports of COVID-19 related factors

Association of the 894G>T polymorphism in the endothelial nitric oxide synthase gene with risk of acute myocardial infarction

Background: This study was designed to investigate the association of the 894G>T polymorphism in the eNOS gene with risk of acute myocardial infarction (AMI), extent of coronary artery disease (CAD) on coronary angiography, and in-hospital mortality after AMI. Methods: We studied 1602 consecutive patients who were enrolled in the GEMIG study. The control group was comprised by 727 individuals, who were randomly selected from the general adult population. Results: The prevalence of the Asp298 variant of eNOS was not found to be significantly and independently associated with risk of AMI (RR = 1.08, 95%CI = 0.77–1.51, P = 0.663), extent of CAD on angiography (OR = 1.18, 95%CI = 0.63–2.23, P = 0.605) and in-hospital mortality (RR = 1.08, 95%CI = 0.29–4.04, P = 0.908). Conclusion: In contrast to previous reports, homozygosity for the Asp298 variant of the 894G>T polymorphism in the eNOS gene was not found to be associated with risk of AMI, extent of CAD and in-hospital mortality after AM

Activating mutations and translocations in the guanine exchange factor VAV1 in peripheral T-cell lymphomas.

Peripheral T-cell lymphomas (PTCLs) are a heterogeneous group of non-Hodgkin lymphomas frequently associated with poor prognosis and for which genetic mechanisms of transformation remain incompletely understood. Using RNA sequencing and targeted sequencing, here we identify a recurrent in-frame deletion (VAV1 Δ778-786) generated by a focal deletion-driven alternative splicing mechanism as well as novel VAV1 gene fusions (VAV1-THAP4, VAV1-MYO1F, and VAV1-S100A7) in PTCL. Mechanistically these genetic lesions result in increased activation of VAV1 catalytic-dependent (MAPK, JNK) and non-catalytic-dependent (nuclear factor of activated T cells, NFAT) VAV1 effector pathways. These results support a driver oncogenic role for VAV1 signaling in the pathogenesis of PTCL