Melanoma is a heterogeneous neoplasm at the histomorphologic, immunophenotypic, and molecular levels. Melanoma with extreme histomorphologic heterogeneity can pose a diagnostic challenge in which the diagnosis may predominantly rely on its immunophenotypic profile. However, tumor survival and response to therapy are linked to tumor genetic heterogeneity rather than tumor morphology. Therefore, understating the molecular characteristics of such melanomas become indispensable. In this study, DNA was extracted from 11 morphologically distinct regions in eight formalin-fixed, paraffin-embedded melanomas. In each region, mutations in 50 cancer-related genes were tested using next-generation sequencing (NGS). A tumor was considered genetically heterogeneous if at least one non-overlapping mutation was identified either between the histologically distinct regions of the same tumor (intratumor heterogeneity) or among the histologically distinct regions of the paired primary and metastatic tumors within the same patient (intertumor heterogeneity). Our results revealed that genetic heterogeneity existed in all tumors as non-overlapping mutations were detected in every tested tumor (n = 5, 100%; intratumor: n = 2, 40%; intertumor: n = 3, 60%). Conversely, overlapping mutations were also detected in all the tested regions (n = 11, 100%). Melanomas exhibiting histomorphologic heterogeneity are often associated with genetic heterogeneity, which might contribute to tumor survival and poor response to therapy.

Introduction: Hypertrophic cardiomyopathy (HCM) is a heterogeneous disorder of the cardiac sarcomere, resulting in myocyte hypertrophy and disarray, interstitial fibrosis, and cardiac dysfunction. Our aim was to determine whether the amount of fibrosis in HCM correlates with echocardiographic measures of diastolic dysfunction, presence of HCM-susceptibility mutations, or polymorphisms in the renin-angiotensin-aldosterone system (RAAS). Methods: Surgical specimens from patients with obstructive HCM undergoing septal myectomy at the Mayo Clinic (2001-2004) were examined and compared with autopsy-derived tissues from age- and sex-matched normal controls. Digital image analysis was used to quantitate the fibrosis in representative microscopic sections. Genotyping was performed for myofilament-HCM using polymerase chain reaction, high-performance liquid chromatography, and direct DNA sequencing. RAAS polymorphism status was similarly established. Results: The study included 59 HCM cases and 44 controls. Patients with HCM exhibited more fibrosis (mean 17%, range 3-45%) than controls (mean 8%, range 3-17%) (P<.0001). A significant relationship existed between amount of fibrosis and maximum wall thickness (P=.02), left ventricular ejection fraction (P=.02), and peak early/late diastolic mitral annulus velocity (E/A ratio) (P=.002). Although there was no association between amount of fibrosis and myofilament-HCM genotype status or polymorphisms in the RAAS cascade, there was a trend toward more fibrosis in patients with ≥1 C-encoding allele in CYP11B2-encoded aldosterone synthase. Conclusions: Patients with HCM undergoing septal myectomy had significantly more myocardial interstitial fibrosis than controls. The amount of fibrosis in HCM patients correlated with degree of septal hypertrophy and left ventricular systolic and diastolic function. Notably, neither mutations in cardiac myofilament proteins or polymorphisms in RAAS exhibited strong associations with severity of myocardial fibrosis.

Since the genetic code first was determined, many have claimed that it is organized adaptively, so as to assign similar codons to similar amino acids. This claim has proved difficult to establish due to the absence of relevant comparative data on alternative primordial codes and of objective measures of amino acid exchangeability. Here we use a recently developed measure of exchangeability to evaluate a null hypothesis and two alternative hypotheses about the adaptiveness of the genetic code. The null hypothesis that there is no tendency for exchangeable amino acids to be assigned to similar codons can be excluded here as expected from earlier work. The first alternative hypothesis is that any such correlation between codon distance and amino acid distance is due to incremental mechanisms of code evolution, and not to adaptation to reduce deleterious effects of future mutations. More specifically, new codon assignments that occur by ambiguity reduction or by codon capture will tend to give rise to correlations, whether due to the condition of amino acid ambiguity, or to the condition of similarity between a new tRNA synthetase (or tRNA) and its parent. The second alternative hypothesis, the adaptive hypothesis, then may be defined as an excess relative to what may be expected given the incremental nature of evolution, reflecting true adaptation for robustness rather than an incidental effect. The results reported here indicate that most of the nonrandomness in the amino acids to codon assignments can be explained by incremental code evolution, with a small residue of orderliness that may reflect code adaptation.

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The human immunodeficiency virus type 1 (HIV-1) protease (PR) is a critical drug target as it is responsible for virion maturation. Mutations within the active site (1°) of the PR directly interfere with inhibitor binding while mutations distal to the active site (2°) to restore enzymatic fitness. Increasing mutation number is not directly proportional to the severity of resistance, suggesting that resistance is not simply additive but that it is interdependent. The interdependency of both primary and secondary mutations to drive protease inhibitor (PI) resistance is grossly understudied. To structurally and dynamically characterize the direct role of secondary mutations in drug resistance, I selected a panel of single-site mutant protease crystal structures complexed with the PI darunavir (DRV). From these studies, I developed a network hypothesis that explains how mutations outside the active site are able to perpetuate changes to the active site of the protease to disrupt inhibitor binding. I then expanded the panel to include highly mutated multi-drug resistant variants. To elucidate the interdependency between primary and secondary mutations I used statistical and machine-learning techniques to determine which specific mutations underlie the perturbations of key inter-molecular interactions. From these studies, I have determined that mutations distal to the active site are able to perturb the global PR hydrogen bonding patterns, while primary and secondary mutations cooperatively perturb hydrophobic contacts between the PR and DRV. Discerning and exploiting the mechanisms that underlie drug resistance in viral targets could proactively ameliorate both current treatment and inhibitor design for HIV-1 targets.

Thesis advisor: Laura Anne Lowery / Thesis advisor: Sarah McMenamin / Development of the central nervous system (CNS) is a complex process that requires the proper function of many genes in order for neurons to proliferate and divide, differentiate, and subsequently migrate long distances to form connections with one another. Abnormalities in any one of these cellular processes can lead to detrimental developmental defects. Growing evidence suggests that genetic mutations caused by rare copy number variants (CNVs) are associated with neurodevelopmental disorders including intellectual disabilities (ID), Autism spectrum disorder (ASD), and schizophrenia. Additionally, these pathogenic CNVs are characterized by extensive phenotypic heterogeneity, as affected individuals often present with microcephaly, craniofacial and heart defects, growth retardation, and seizures. Despite their strong association as risk factors towards neurodevelopmental disorders, the developmental role of individual CNV-affected genes and disrupted cellular mechanisms underlying these mutations remains poorly understood. Moreover, it is unclear as to how the affected genes both individually and combinatorially contribute to the phenotypes associated with pathogenic CNVs. Thus, in this thesis, we explore the functional basis of phenotypic variability of pathogenic CNVs linked to neurodevelopmental disorders. In particular, we focus on the 3q29 deletion and 16p12.1 deletion, to provide insight towards the convergent cellular, molecular, and developmental mechanisms associated with decreased dosage of the affected gene homologs using two complementary model systems, Xenopus laevis and Drosophila melanogaster. First, we examine the role of individual homologs of several CNV-affected genes at chromosome 3q29 and their interactions towards cellular processes underlying the deletion. We find that multiple 3q29-affected genes, including NCBP2, DLG1, FBXO45, PIGZ, and BDH1, contribute to disruptions in apoptosis and cell cycle pathways, leading to neuronal and developmental defects. We then expand further upon this work by discerning the individual contribution of four CNV-affected genes at chromosome 16p12.1, POLR3E, MOSMO, UQCRC2, and CDR2, towards neurodevelopment and craniofacial morphogenesis. We demonstrate that several of these genes affect multiple phenotypic domains during neurodevelopment leading to brain size alterations, abnormal neuronal morphology, and cellular proliferation defects. We then explore their functions during vertebrate craniofacial morphogenesis and demonstrate that some 16p12.1-affected genes are enriched in migratory neural crest, and contribute to early craniofacial patterning and formation of cartilaginous tissue structures. Together, these data are the first to suggest that signature neurodevelopmental phenotypes demonstrated in the 3q29 deletion and 16p12.1 deletion may stem from convergent cellular mechanisms including aberrations in neuronal proliferation, apoptosis and cell cycle regulation, and neural crest cell development. / Thesis (PhD) — Boston College, 2020. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.

Dans une première partie, je présente le travail que j’ai accompli sur la coévolution moléculaire. Je présente le contexte biologique et les différentes mesures qui permettent de détecter la conservation et la coévolution à l’échelle des acides aminés. Ensuite, je montre une application de ces mesures à la détection des résidus critiques dans la protéine P53 liée au cancer. Dans ce but, j’ai créé une évaluation des différentes méthodes de prédiction. J’utilise ensuite la même méthodologie sur une base de données de mutations liées à des maladies génétiques. Je montre également comment la coévolution au niveau des résidus permet de découvrir des interactions protéine-protéine sur le virus de l’hépatite C. Enfin, je présente l’algorithme PruneTree, qui permet de filtrer des ensembles de séquences utilisés comme entrée par les programmes de détection de coévolution.Dans une deuxième partie, je m’intéresse à l’étude de l’évolution à l’échelle du génome, en particulier aux mécanismes de recombinaison méiotique. Pour cela j’ai considéré le taux de recombinaison le long du génome et sa cause, les cassures double-brin de l’ADN. Je présente alors un modèle de la distribution de ces cassures et de la liaison des différentes protéines liées à la recombinaison. Je présente également une méthode de détection de périodicité le long du génome basée sur les transformées de Fourier.Enfin, dans la dernière partie, je présente un nouvel algorithme pour simuler l’évolution des génomes de façon à évaluer les outils de reconstruction, et le paquet R-CLAG permettant d’utiliser l’algorithme de classification CLAG depuis R. / In a first part, I show the work I have done on molecular evolution. I present the general biological background and the measures that allow us to detect both conservation and coevolution at the amino-acid level. Then, I present an application of these measures to the detection of critical residues in the cancer protein P53. To this end, I have made a benchmark of different prediction methods. I then use the same methodology on a large scale database of pathogenic mutations linked to genetic diseases. After that, I show how residue-level coevolution can help us discover protein-protein interactions in the hepatitis C virus. Finally, I present the PruneTree algorithm, which allows filtering sequence sets used as input for molecular coevolution detection methods. In a second part, I have studied evolution at the genome level, in particular the recombination mechanisms that occur during meiosis. I have looked at the recombination rates along the genomes and its primary cause, the double-strand breaks, but also at the density of other proteins involved in recombination. I also present a method based on Fourier transforms to analyze these genomic signals, and a model for the distribution along the genome of double-strand breaks and recombination proteins. Finally, I present the other tools I have developed. I describe a novel algorithm that can simulate the evolution of genomes in order to benchmark the phylogenetic reconstruction algorithm PhyChro. Finally, I present the R-CLAG package that allows for easy use of the clustering algorithm CLAG.

Indiana University-Purdue University Indianapolis (IUPUI) / While most cases of epilepsy respond well to common antiepileptic drugs, many genetically-driven epilepsies are refractory to conventional antiepileptic drugs. Over 250 mutations in the Nav1.2 gene (SCN2A) have been implicated in otherwise idiopathic cases of epilepsy, many of which are refractory to traditional antiepileptic drugs. Few of these mutations have been studied in vitro to determine their biophysical effects on the channels, which could reveal why the effects of some are refractory to traditional antiepileptic drugs. The goal of this dissertation was to characterize multiple epilepsy mutations in the SCN2A gene, which I hypothesized would have distinct biophysical effects on the channel’s function. I used patch-clamp electrophysiology to determine the biophysical effects of three SCN2A epilepsy mutations (R1882Q, R853Q, and L835F). Wild-type (WT) or mutant human SCN2A cDNAs were expressed in human embryonic kidney (HEK) cells and subjected to a panel of electrophysiological assays. I predicted that the net effect of each of these mutations was enhancement of channel function; my results regarding the L835F and R1882Q mutations supported this hypothesis. Both mutations enhance persistent current, and R1882Q also impairs fast inactivation. However, examination of the same parameters for the R853Q mutation suggested a decrease of channel function. I hypothesized that the R853Q mutation creates a gating pore in the channel structure through which sodium leaks into the cell when the channel is in its resting conformation. This hypothesis was supported by electrophysiological data from Xenopus oocytes, which showed a significant voltage-dependent leak current at negative potentials when they expressed the R853Q mutant channels. This was absent in oocytes expressing WT channels. Overall, these results suggest that individual mutations in the SCN2A gene generate epilepsy via distinct biophysical effects that may require novel and/or tailored pharmacotherapies for effective management.

京都大学 / 0048 / 新制・課程博士 / 博士(薬科学) / 甲第19974号 / 薬科博第65号 / 新制||薬科||7(附属図書館) / 33070 / 京都大学大学院薬学研究科医薬創成情報科学専攻 / (主査)教授 馬見塚 拓, 教授 緒方 博之, 教授 掛谷 秀昭 / 学位規則第4条第1項該当 / Doctor of Pharmaceutical Sciences / Kyoto University / DFAM

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