Fluoxetine, a selective serotonin re-uptake inhibitor (SSRI) and the active ingredient in Prozac®, is found in the environment and disrupts feeding and metabolism in exposed fish. The objective of this research was to investigate the mechanisms involved in the feeding and metabolism disruption in the model goldfish (Carassius auratus). Two short-term waterborne fluoxetine exposures (7- and 14-days) were performed using two environmentally relevant doses of fluoxetine (0.5 and 1 μg/L) and metabolic effects at the level of the brain, liver, serum and bile in goldfish were investigated. Abundances of mRNA transcripts coding for six feeding neuropeptides were examined to determine which may be involved in the initial neural changes associated with decreased appetite in goldfish. The 7-day fluoxetine exposure at 1 μg/L caused corticotropin-releasing factor (CRF) mRNA levels to increase by 2-fold in female hypothalamus and telencephalon, indicating that CRF may be one of the first of the feeding neuropeptides to be altered. Six hepatic miRNAs were also evaluated in the goldfish liver that were previously associated with fluoxetine exposure in zebrafish (Danio rerio). Following the 7-day exposure at 1 μg/L, miR-22b, miR-140, miR-210, miR-301a and miR-457b levels increased in the female goldfish liver by 4-6 fold. The 14-day fluoxetine exposure at 1 μg/L caused 2-fold increases in miR-210, miR-301a, miR-457b and let-7d in male goldfish liver. These miRNAs were associated with the down-regulation of anabolic metabolic pathways in zebrafish, indicating a conservation of miRNA and fluoxetine effect between fish species. Serum and bile metabolite profiles of fluoxetine exposed goldfish were evaluated using ultra performance liquid chromatography coupled to quadrupole time of flight mass spectrometry. Following the 14-day exposure at 1 μg/L, the bile metabolite profiles of male goldfish were significantly different from controls as detected by cluster analysis and fluoxetine was tentatively identified in the serum. No other discriminant metabolites were identified as of yet. The data presented suggest that fluoxetine causes metabolic disruption in goldfish at multiple organ levels. Because of the widespread detection of fluoxetine and other emerging SSRIs in the aquatic environment, future research is required to firmly establish this pharmaceutical class as a metabolic and endocrine disrupting chemical.

MicroRNAs (miRNAs) are a class of small, single-stranded, non-protein coding RNA molecules that regulate cellular messenger RNA (mRNA) and protein levels by binding to specific mRNAs. Aberrant miRNA expression has been shown to be implicated in several diseases, including cancer. Extracellular miRNAs have been found to circulate in the bloodstream and some of their levels have been associated with different diseases. Furthermore, they hold promise as tissue- and blood-based biomarkers for cancer classification and prognostication. Blood-based biomarkers are attractive for cancer screening due to their minimal invasiveness, relatively low cost and ease of reproducibility. New miRNA analysis techniques will add toward the understanding of their biological functions. In this thesis, I investigate the utility of capillary electrophoresis (CE) and mass spectrometry (MS) for analysis of miRNAs through proof-of-concept experiments. In the fi rst part of this work, we developed a Protein-Facilitated Affinity Capillary Electrophoresis (ProFACE) assay for rapid quantification of miRNA levels in blood serum (see List of publications (6)). We also implemented a capillary electrophoresis with laser induced fluorescence detection (CE-LIF) method with online sample pre-concentration for detection of endogenous microRNAs in human serum and cancer cells. 3' modification of miRNA is a physiological and common post-transcriptional event that shows selectivity for specific miRNAs and is observed across species. Recent studies have shown that post-transcriptional addition of nucleotides to the 3' end of miRNAs is a mechanism for miRNA activity regulation. For example, such modifications in plants and C. elegans influence miRNA stability. In humans, effects on miRNA stability and on mRNA target repression have both been observed. Thus, there is a need for miRNA detection techniques which are direct and multiplexed, require minimal sample preparation and provide qualitative information regarding these modifications. We developed a multiplexed miRNA detection technique based on capillary electrophoresis coupled on line with electrospray ionization mass spectrometry (CE-ESI-MS). This method allowed a label-free, direct detection of multiple miRNAs extracted from cancer serum as well as their post-transcriptional modifications with a high mass accuracy.

Complementary and Alternative Medicine (CAM) is popularly used among breast cancer patients to improve their quality of life. CAM includes dietary supplements such as Active Hexose Correlated Compound (AHCC®), a cultured mushroom extract shown to positively influence the immune system and cancer. Breast cancer recurrence is believed to be caused by cancer stem cells (CSCs). We postulated that AHCC impacts CSCs epigenetically by targeting miRNA pathways. The effects of AHCC on mammosphere growth were observed in MDA-MB-231, MCF-7, and 4T1 cells. Profiling, RT2-qPCR, and western blot analyses were performed to determine AHCC influence on miRNAs and Tenascin C protein in TNBC cell line MDA-MB-231. Balb/c mice were gavaged with AHCC to examine tumorigenesis effects. Our results demonstrated that AHCC reduced mammosphere growth and cell migration, and upregulated tumor suppressor miR-335 expression in different biological settings. Inhibition of miR-335 increased Tenascin C expression. Consequently, AHCC may influence BCSCs through miRNA pathways.

RNA silencing is a cellular mechanism of post-transcriptional gene regulation which is highly conserved among the plant and animal kingdoms of life, and plays a critical part of developmental biology, maintenance of homeostasis, and host-pathogen interactions. The pathway is engaged by small double-stranded (ds)RNA molecules (small RNAs), which effect sequence specific gene silencing by targeting complementary RNA sequences. There are several classes of small RNAs which engage the pathway. MicroRNAs (miRNAs) are expressed in the genome as endogenous regulators of gene expression. Short-interfering RNAs (siRNAs) are usually from exogenous sources such as viral-derived short-interfering RNAs, or synthetic siRNAs which are applied to cells or organisms to inhibit expression of specific genes. The p19 protein is a viral suppressor of RNA silencing (VSRS) endogenous to tombusviruses, which binds small RNA duplexes of any sequence with extremely high affinity. Because of its unique binding properties, recombinant p19 proteins are an excellent platform for tool development surrounding the RNA silencing pathway and are used extensively in novel applications for modulating the activity of small RNAs in living systems and for detecting small RNAs in biological samples. Herein we present work that has increased the breadth of p19’s utility as a biotechnology tool in three distinct realms. First, we present a chemical biology approach which combines p19 and small molecules for potent inhibition of the RNA silencing pathway in human cells. Secondly, we present the development of a novel fusion protein between p19 and a cell penetrating peptide (CPP), which functions as an siRNA delivery agent to allow gene knockdown in human cells. Thirdly, we have improved the utility of p19 for detecting and sequestering human miRNAs through rationally designing the binding surface; we describe mutations which dramatically enhance p19's affinity for human miRNA-122. The work presented here adds to the growing repertoire of engineered RNA binding proteins (RBPs) as tools for studying small RNA molecules and modulating their activity for applications in human therapeutics.

Oncolytic viruses are novel candidates for cancer therapy and their efficacy relies on their capacity to overcome the host’s anti-viral barriers. In mammalian cells, the anti-viral response involves a protein-signaling cascade known as the interferon pathway, which alerts the immune system and limits the propagation of infection. Given that most cancer cells have defects in this pathway, they are susceptible to viral infection and responsive to oncolytic virotherapy. For reasons that remain unknown, many cancers are still refractory to oncolytic viruses, which suggests the existence of additional antiviral mechanisms. In this study, we investigate the potential involvement of an alternative antiviral pathway in cancer cells. Given that insects and plants rely on the RNA silencing pathway for their anti-viral protection, we investigated the presence of a similar mechanism in cancer cells. We found viral genome-derived small RNAs in various cancer cell lines upon infection, which is indicative of an RNA-mediated antiviral response. Also, various viruses encode suppressors of the RNA interference pathway. To determine if an oncolytic virus could benefit from such a factor, we engineered an oncolytic virus variant to encode the Nodamura virus B2 protein, a known inhibitor of RNA silencing-mediated immune responses. Using this virus, we observed enhanced cytotoxicity in 33 out of the 38 human cancer cell lines tested. Furthermore, our results show inhibition of viral genome cleavage and altered microRNA processing by our B2-expressing oncolytic virus. Taken together, our data suggests the blockade of RNA silencing antiviral pathways and/or antiviral microRNA processing improves the efficacy of our B2-encoding virus in a cell-line specific manner. Overall, our results establish the improved potential of our novel virus therapy and demonstrate for the first time the involvement of RNA pathways in the antiviral defense of cancer cells.

Le but de toute étude en biologie évolutive du développement est l’étude des mécanismes développementaux à l’origine des diversifications morphologiques. Dans ce contexte, j’ai décidé de me focaliser sur l’émergence des Vertébrés au cours de l’évolution, par la mise en œuvre d’études comparatives entre différents modèles de Deutérostomiens. Le travail réalisé durant ma thèse est subdivisé en trois projets: (i) j’ai abordé le lien entre l’évolution du cerveau chez les Chordés et les modifications de la signalisation à l’acide rétinoïque (AR) au cours du développement. En particulier, j’ai examiné les rôles de l’AR au cours du développement du cerveau chez la lamproie Lampetra fluviatilis, et j’ai comparé les résultats obtenus chez cette espèce aux mécanismes développementaux agissant chez l’amphioxus, un Chordé invertébré, et chez les modèles gnathostomes classiques. Les données obtenues lors de ces analyses comparatives ont permis une meilleure compréhension de l’évolution de la régionalisation cérébrale chez les Vertébrés. (ii) j’ai étudié l’évolution des séquences régulatrices présentes au sein des clusters de gènes hox, connus pour agir dans la régionalisation du système nerveux des Chordés. L’identification d’éléments non-codants conservés ainsi que d’éléments de réponse à l’AR (RARE) potentiels dans des clusters hox de Chordés, combinée à la caractérisation de RAREs in vivo en cellules murines a permis une vision intégrée de l’évolution du contrôle des gènes hox par l’AR, chez les Chordés. (iii) j’ai analysé l’évolution des microARNs chez les Chordés en comparant les répertoires microARN chez plusieurs espèces de Deutérostomiens. Cette étude a permis d’émettre de nouvelles hypothèses quant à l’émergence des microARNs chez les animaux. Toutes ces analyses ont abordé différents aspects de l’évolution des Chordés avec pour objectif la proposition d’une vision intégrée des mécanismes moléculaires à l’origine de l’émergence des Vertébrés. / The aim of the evolutionary developmental biology is to study the developmental mechanisms at the base of morphological diversification. In this context, I decided to focus my attention on the emergence of vertebrates during evolution by carrying out comparative analyses in several deuterostome models. The work carried out during of my thesis can be subdivided into three major projects: (i) I addressed the link between brain evolution and modifications in retinoic acid (RA) signaling during chordate development. In particular, I investigated the roles of RA signaling in brain development in a jawless vertebrate, the lamprey Lampetra fluviatilis, and compared the results with developmental mechanisms in the invertebrate chordate amphioxus and classical developmental model systems in jawed vertebrates. Data obtained from these comparative studies provided insights into the evolution of brain patterning in vertebrate evolution. (ii) I investigated the evolution of the regulatory landscape of hox gene clusters that are known to be fundamental for the patterning of the chordate central nervous system. The identification of conserved non-coding elements and putative RA response elements (RAREs) in hox clusters of different chordate species combined with the in vivo characterization of functional RAREs in mouse F9 cells provided an integrated view of the evolution of RA-dependent hox cluster regulation in chordates. (iii) I studied the roles of microRNAs (miRNAs) in chordate evolution by comparing the miRNA complements of different deuterostome species. This analysis provided novel insights about the general mechanisms of miRNA emergence in animals and highlighted species-specific miRNA complement amplifications in different deuterostome lineages. In sum, these studies have tackled different aspects of chordate evolution from an evo-devo perspective, aiming at an integrated view of the molecular mechanisms underlying vertebrate diversification.

RNA Sequencing has recently emerged as a breakthrough technology for microRNA (miRNA) discovery. This technology has allowed the discovery of thousands of miRNAs in a large number of species. However, despite the benefits of this technology, it also carries its own limitations, including the need for sequencing read libraries and of the genome. Differently, ab initio computational methods need only the genome as input to search for genonic locus likely to give rise to novel miRNAs. In the core of most of these methods, there are predictive models induced by using data mining techniques able to distinguish between real (positive) and pseudo (negative) miRNA precursors (pre-miRNA). Nevertheless, the applicability of current literature ab initio methods have been compromised by high false detection rates and/or by other computational difficulties. In this work, we investigated how the main aspects involved in the induction of predictive models for pre-miRNA affect the predictive performance. Particularly, we evaluate the discriminant power of feature sets proposed in the literature, whose computational costs and composition vary widely. The computational experiments were carried out using sequence data from 45 species, which covered species from eight phyla. The predictive performance of the classification models induced using large training set sizes (≥ 1; 608) composed of instances extracted from real and pseudo human pre-miRNA sequences did not differ significantly among the feature sets that lead to the maximal accuracies. Moreover, the differences in the predictive performances obtained by these models, due to the learning algorithms, were neglectable. Inspired by these results, we obtained a feature set which can be computed 34 times faster than the less costly among those feature sets, producing the maximal accuracies, albeit the proposed feature set has achieved accuracy within 0.1% of the maximal accuracies. When classification models using the elements previously discussed were induced using small training sets (120) from 45 species, we showed that the feature sets that produced the highest accuracies in the classification of human sequences were also more likely to produce higher accuracies for other species. Nevertheless, we showed that the learning complexity of pre-miRNAs vary strongly among species, even among those from the same phylum. These results showed that the existence of specie specific features indicated in previous studies may be correlated with the learning complexity. As a consequence, the predictive accuracies of models induced with different species and same features and instances spaces vary largely. In our results, we show that the use of training examples from species phylogenetically more complex may increase the predictive performances for less complex species. Finally, by using ensembles of computationally less costly feature sets, we showed alternative ways to increase the predictive performance for many species while keeping the computational costs of the analysis lower than those using the feature sets from the literature. Since in miRNA discovery the number of putative miRNA loci is in the order of millions, the analysis of putative miRNAs using a computationally expensive feature set and or inaccurate models would be wasteful or even unfeasible for large genomes. In this work, we explore most of the learning aspects implemented in current ab initio pre-miRNA prediction tools, which may lead to the development of new efficient ab initio pre-miRNA discovery tools / O sequenciamento de pequenos RNAs surgiu recentemente como uma tecnologia inovadora na descoberta de microRNAs (miRNA). Essa tecnologia tem facilitado a descoberta de milhares de miRNAs em um grande número de espécies. No entanto, apesar dos benefícios dessa tecnologia, ela apresenta desafios, como a necessidade de construir uma biblioteca de pequenos RNAs, além do genoma. Diferentemente, métodos computacionais ab initio buscam diretamente no genoma regiões prováveis de conter miRNAs. A maioria desses métodos usam modelos preditivos capazes de distinguir entre os verdadeiros (positivos) e pseudo precursores de miRNA - pre-miRNA - (negativos), os quais são induzidos utilizando técnicas de mineração de dados. No entanto, a aplicabilidade de métodos ab initio da literatura atual é limitada pelas altas taxas de falsos positivos e/ou por outras dificuldades computacionais, como o elevado tempo necessário para calcular um conjunto de atributos. Neste trabalho, investigamos como os principais aspectos envolvidos na indução de modelos preditivos de pre-miRNA afetam o desempenho preditivo. Particularmente, avaliamos a capacidade discriminatória de conjuntos de atributos propostos na literatura, cujos custos computacionais e a composição variam amplamente. Os experimentos computacionais foram realizados utilizando dados de sequências positivas e negativas de 45 espécies, cobrindo espécies de oito filos. Os resultados mostraram que o desempenho preditivo de classificadores induzidos utilizando conjuntos de treinamento com 1608 ou mais vetores de atributos calculados de sequências humanas não diferiram significativamente, entre os conjuntos de atributos que produziram as maiores acurácias. Além disso, as diferenças entre os desempenhos preditivos de classificadores induzidos por diferentes algoritmos de aprendizado, utilizando um mesmo conjunto de atributos, foram pequenas ou não significantes. Esses resultados inspiraram a obtenção de um conjunto de atributos menor e que pode ser calculado até 34 vezes mais rapidamente do que o conjunto de atributos menos custoso produzindo máxima acurácia, embora a acurácia produzida pelo conjunto proposto não difere em mais de 0.1% das acurácias máximas. Quando esses experimentos foram executados utilizando vetores de atributos calculados de sequências de outras 44 espécies, os resultados mostraram que os conjuntos de atributos que produziram modelos com as maiores acurácias utilizando vetores calculados de sequências humanas também produziram as maiores acurácias quando pequenos conjuntos de treinamento (120) calculados de exemplos de outras espécies foram utilizadas. No entanto, a análise destes modelos mostrou que a complexidade de aprendizado varia amplamente entre as espécies, mesmo entre aquelas pertencentes a um mesmo filo. Esses resultados mostram que a existência de características espécificas em pre-miRNAs de certas espécies sugerida em estudos anteriores pode estar correlacionada com a complexidade de aprendizado. Consequentemente, a acurácia de modelos induzidos utilizando um mesmo conjunto de atributos e um mesmo algoritmo de aprendizado varia amplamente entre as espécies. i Os resultados também mostraram que o uso de exemplos de espécies filogeneticamente mais complexas pode aumentar o desempenho preditivo de espécies menos complexas. Por último, experimentos computacionais utilizando técnicas de ensemble mostraram estratégias alternativas para o desenvolvimento de novos modelos para predição de pre-miRNA com maior probabilidade de obter maior desempenho preditivo do que estratégias atuais, embora o custo computacional dos atributos seja inferior. Uma vez que a descoberta de miRNAs envolve a análise de milhares de regiões genômicas, a aplicação prática de modelos preditivos de baixa acurácia e/ou que dependem de atributos computacionalmente custosos pode ser inviável em análises de grandes genomas. Neste trabalho, apresentamos e discutimos os resultados de experimentos computacionais investigando o potencial de diversas estratégias utilizadas na indução de modelos preditivos para predição ab initio de pre-miRNAs, que podem levar ao desenvolvimento de ferramentas ab initio de maior aplicabilidade prática

Endometrial cancer is the fourth most common cancer in women and the most common gynecological malignancy. While patient outcome has improved for the majority of cancers, the outlook for endometrial cancer has steadily decreased. In order to address this problem, we must better understand the different mechanisms involved in endometrial cancer development and progression. To this end, we quantified expression of 667 miRNAs in four endometrioid adenocarcinoma and four serous adenocarcinoma using Taqman Low Density Arrays (TLDAs). miR-888 was one of the most highly overexpressed miRNAs in both endometrial cancer subtypes. Analysis of miR-888 expression across multiple cancer types using the The Cancer Genome Atlas database revealed that miR-888 was selectively expressed in endometrial cancer, with a significant association to invasive and high grade tumors. In addition, miR-888 was most predominantly expressed in endometrial carcinosarcoma, a rare but deadly form of endometrial cancer. Therefore, we conclude that miR-888 expression marks an aggressive endometrial tumor phenotype. One of the top predicted targets of miR-888 by TargetScan is the progesterone receptor (PR). PR is a potent tumor suppressor of the endometrium whose expression is often lost in advanced endometrial cancers. We quantified PR mRNA expression in a panel of endometrial tumors and found a statistically significant, negative correlation between miR-888 and PR mRNA expression. Furthermore, overexpression of miR-888 in endometrial cancer cell lines was capable of decreasing PR at the protein level. To determine if miR-888 directly targets PR, we cloned each of the four miR-888 binding sites downstream of Renilla luciferase into the psiCHECK2 reporter vector. miR-888 overexpression was capable of decreasing luciferase activity for all four binding sites, with the second and third binding sites producing the most prominent results. Here we describe a novel mechanism by which miR-888 inhibits PR mRNA translation to negatively regulate PR expression in endometrial tumors. To determine the endogenous function of miR-888 in human cells, we quantified miR-888 in a panel of 21 normal human tissues. Interestingly, miR-888 was highly expressed in testes, with minimal or absence of expression in all other tissues investigated. The restricted expression pattern of miR-888 in testes and cancer suggested that miR-888 may qualify as a novel cancer-testis (CT) antigen. CT-antigens are a large class of genes that demonstrate selective expression normally in testes germ cells and abnormally in various types of cancer. Furthermore, CT-antigen genes are predominantly located on the X chromosome and are part of evolutionarily novel multicopy gene families. Indeed, miR-888 is part of a multicopy, primate-specific miRNA gene family located on the X-chromosome. Furthermore, miRNA in situ hybridization localized miR-888 expression to the early stages of spermatogenesis, as is often observed for CT antigens. Together, these data identify miR-888 as the first miRNA CT antigen and expand the CT antigen field to noncoding RNAs.

L’amélioration de la prise en charge personnalisée des cancers de l’ovaire nécessite le développement de nouvelles approches thérapeutiques et d’outils capables de prédire la réponse au traitement et la récidive. L’étude des miARNs cellulaires et circulants représente un champ d’investigation prometteur en oncologie, et ils pourraient rapidement constituer de nouveaux outils diagnostiques, pronostiques, voire thérapeutiques. Suite à la réalisation d’un criblage fonctionnel haut débit d’une banque de miARNs sur des lignées cancéreuses ovariennes, nous avons identifié plusieurs miARNs d’intérêt. Alors que l’utilisation des miARNs en tant qu’agents thérapeutiques n’est pas aujourd’hui envisageable, la caractérisation des cibles «pas-à-pas» de l’un de ces candidats, le miR-3622b-5p, en lien avec son action anti-tumorale au sens large (pro-apoptique, sensibilisation au cisplatine et anti-invasive) sur un panel de lignées cancéreuses ovariennes, a permis de renforcer l’intérêt de l’approche que nous développons qui consiste à reproduire l’effet de miARNs en ciblant les déterminants de leur action à l’aide de molécules inhibitrices, potentiellement utilisables en clinique. En parallèle, afin d’identifier globalement les cibles (leur aspect direct ou indirect vis-à-vis d’un miARN devenant alors secondaire) et réseaux associés des miARNs les plus prometteurs, identifiés lors du du screening, et en se basant initialement sur le premier apoptomiR identifié au laboratoire, le miR-491-5p, pour en faire la preuve de concept, une évaluation de l’approche méthodologique combinant des données d’approches multi-omiques a permis de conclure quant à l’intérêt de coupler les analyses trancriptomique et protéomique pour identifier de nouvelles cibles/voies en lien avec son action pro-apoptotique et ainsi proposer des associations pharmacologiques pertinentes et innovantes pour les cancers de l’ovaire. Par ailleurs, nous avons identifié une signature de miARN sérique capable d’identifier les patients susceptibles de présenter une résistance aux sels de platine et potentiellement aux inhibiteurs de PARP, préalablement à toute chimiothérapie et au moment de la récidive avant la seconde ligne de traitement. En résumé, ces résulats offrent de grandes promesses et placent les miARNs au coeur la médecine de précision de demain dans les cancers de l’ovaire. / Improving the personalized management of ovarian cancer requires the development of new therapeutic approaches and tools able to predict treatment response and recurrence. The study of cellular and circulating miRNAs represents a promising field of investigation in oncology, and they could quickly constitute new diagnostic, prognostic and even therapeutic tools. Following a high-throughput functional screening of a miRNA library on ovarian cancer lines, we identified several miRNAs of interest. While the use of miRNAs as therapeutic agents is not currently possible, the characterization of the targets «step-by-step»of one of these candidates, the miR-3622b-5p, with its broad anti-tumoral activity (pro-apoptic, sensibilisation to cisplatin and anti-invasive) on a panel of ovarian cancer lines, made it possible to reinforce the interest of the approach which we develop which consists in reproducing the effect of miRNAs by targeting the determinants of their action using inhibitory molecules, potentially usable in the clinic. In parallel, in order to globally identify the targets (their direct and indirect aspect next to a miRNA then becoming secondary) and associated networks of the most promising miRNAs, identified during the screening, and initially based on the first laboratory-identified apoptomiR, the miR-491-5p, to provide a proof of concept, an evaluation of the methodological approach combining data from multi-omic strategies led to the conclusion that it is useful to combine the trancriptomic and proteomic analyses to identify new targets/pathways related to its pro-apoptotic action and thus propose relevant and innovative pharmacological associations for ovarian cancers. In addition, we have identified a serum miRNA signature capable of identifying patients who may be resistant to platinum-based chemotherapy and potentially PARP inhibitors, prior to any chemotherapy and at the time of recurrence before the second line of treatment. In summary, these results offer great promise and place miRNAs at the heart of tomorrow's precision medicine in ovarian cancer.

京都大学 / 0048 / 新制・課程博士 / 博士(医科学) / 甲第22378号 / 医科博第108号 / 新制||医科||7(附属図書館) / 京都大学大学院医学研究科医科学専攻 / (主査)教授 萩原 正敏, 教授 羽賀 博典, 教授 松村 由美 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM