Solving the Glucocorticoid Paradox in Cancer Using Expression Data

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Solving the Glucocorticoid Paradox in Cancer Using Expression Data ADVERTIMENT. Lʼaccés als continguts dʼaquesta tesi queda condicionat a lʼacceptació de les condicions dʼús establertes per la següent llicència Creative Commons: http://cat.creativecommons.org/?page_id=184 ADVERTENCIA. El acceso a los contenidos de esta tesis queda condicionado a la aceptación de las condiciones de uso establecidas por la siguiente licencia Creative Commons: http://es.creativecommons.org/blog/licencias/ WARNING. The access to the contents of this doctoral thesis it is limited to the acceptance of the use conditions set by the following Creative Commons license: https://creativecommons.org/licenses/?lang=en Solving The Glucocorticoid Paradox In Cancer Using Expression Data Mario Huerta Casado 2016 Solving the Glucocorticoid Paradox In Cancer Using Expression Data Mario Huerta Casado 2016 Submitted for the Degree of Doctor of Philosophy in Biotechnology by Mario Huerta Casado The work was supervised by Dr. Enric Querol Murillo of the Institut de Biotecnologia i de Biomedicina- Universitat Autònoma de Barcelona and Dr. Juan Cedano Rodriguez of CENUR Litoral Norte-Salto, Universidad de la República, Uruguay Mario Huerta Casado Enric Querol Murillo Juan Cedano Rodriguez Universitat Autònoma de Barcelona, 2016 Don’t let the trees stop you from seeing the forest. Unknown author Abstract Glucocorticoids are commonly used as an adjuvant treatment for side-effects and have anti- proliferative activity in several tumours. Inspite of this fact, there has been reported a proliferative effect in several studies, that some of them involving the spread of cancer. These paradoxes are common in cancer research. Usually the same genes seem to be promoter and inhibitor of cancer. We shall attempt to reconcile these incongruities from the transcriptomic and tissue-physiology perspectives with our procedures and findings. An accurate phenotype analysis of expression data can help to solve multiple paradoxes derived from tumour-progression models. We have developed several strategies, tools and databases to facilitate the study of interdependences among the phenotypes hidden inside expression data. These phenotypes can be identified by the sample clusters obtained by common clustering methods (HC, SOTA, SOM, PAM), but clustering methods do not provide information about their interdependence. We study these interdependences by the detection of non-linear expression- relationships where each fluctuation in the relationship implies a phenotype change and each relationship typology implies specific phenotype interdependence. In this way different strategies and tools have been developed to study phenotypic changes and the paradoxes subjected to them. Using the tools developed we have studied the non-linear expression relationships related to glucocorticoid activity. The result is that we have found the possible reason for opposite effects of some stressor agents like dexamethasone on tumour progression as it has been confirmed by literature. This hidden reason has resulted in being linked with the type of tumour progression of the tissues. In the first type of tumour progression found, new cells can be stressed during proliferation and stressor agents increase tumour proliferation. In the second type, cell stress and tumour proliferation are antagonists so, therefore, stressor agents stop tumour proliferation in order to stress the cells. Resum Els glucocorticoides s'utilitzen comunament com a tractament adjuvant per tractar efectes secundaris i tenen una activitat antiproliferativa en diversos tumors però, d'altra banda, el seu efecte proliferatiu s’ha documentat en diversos estudis i en alguns d'ells implica la propagació del càncer. Aquestes paradoxes són comuns en l’investigació del càncer. Molt sobint, els mateixos gens semblen ser a l’hora promotors i inhibidors del càncer. Amb el present treball pretenem conciliar aquestes incongruències des de la perspectiva de la genética i de la fisiologia del teixit amb els nostres procediments i troballes. Un anàlisi precís dels fenotips presents a les dades d'expressió gènica pot ajudar a resoldre múltiples paradoxes derivades dels models de progressió de tumors. En aquest sentit hem desenvolupat diverses estratègies, eines i bases de dades, per facilitar l'estudi de les interdependències entre els fenotips ocults dins de les dades d'expressió. Aquests fenotips poden ser identificats pels grups de mostres obtinguts mitjançant mètodes comuns d'agrupament (HC, SOTA, SOM, PAM), però els mètodes d'agrupament no proporcionen informació sobre la seva interdependència. Nosaltres estudiem aquestes interdependències per la detecció de relacions d'expressió no lineals, on cada fluctuació en la relació implica un canvi fenotípic i cada tipolologia de la relació diferent implica una interdependència fenotípica específica. D'aquesta manera, s'han desenvolupat diferents estratègies i eines per estudiar els canvis fenotípics i les paradoxes sotmeses a ells. Utilitzant les eines desenvolupades s'han estudiat les relacions d'expressió no lineals relacionades amb l'activitat dels glucocorticoides. Estudiant-les, hem trobat la possible raó dels efectes oposats d'alguns agents estressants com la dexametasona sobre la progressió tumoral, com ha estat confirmat per la literatura. Aquesta raó oculta ha resultat estar vinculada amb el tipus de progressió del tumor en cada teixit. En el primer tipus de progressió tumoral trobat, les noves cèl·lules poden ser estressades durant la proliferació i els agents estressants augmenten la proliferació tumoral. En el segon tipus, l'estrès cel·lular i la proliferació del tumor són antagonistes així, per tant, els agents estressants aturen la proliferació tumoral amb la finalitat d’estressar les cèl·lules. Resumen Los glucocorticoides se utilizan comúnmente como tratamiento adyuvante para tratar efectos secundarios y tienen una actividad antiproliferativa en varios tumores, pero, por otra parte, su efecto proliferativo se ha documentado en varios estudios que en algunos de ellos implica la propagación del cáncer. Estas paradojas son comunes en la investigación del cáncer. A menudo los mismos genes parecen ser promotores e inhibidores del cáncer. En el presente trabajo vamos a tratar de conciliar estas incongruencias desde la perspectiva genética y de la fisiologicaa del tejido con nuestros procedimientos y hallazgos. Un análisis preciso de los fenotipos presentes en los datos de expresión génica puede ayudar a resolver múltiples paradojas derivadas de los modelos de progresión de tumores. Con ese fin hemos desarrollado diversas estrategias, herramientas y bases de datos para facilitar el estudio de las interdependencias entre los fenotipos ocultos dentro de los datos de expresión. Estos fenotipos pueden ser identificados por los grupos de muestras obtenidos mediante métodos comunes de agrupación (HC, SO, SOM, PAM), pero los métodos de agrupación no proporcionan información sobre su interdependencia. Estudiamos estas interdependencias mediante la detección de relaciones de expresión no lineales, dónde cada fluctuación en la relación implica un cambio fenotípico y cada tipología de la relación implica una interdependencia fenotípica específica. De este modo, se han desarrollado diferentes estrategias y herramientas para estudiar los cambios fenotípicos y las paradojas sometidas a ellos. Utilizando las herramientas desarrolladas se han estudiado las relaciones de expresión no lineales relacionadas con la actividad de los glucocorticoides. Estudiándolas, hemos encontrado la posible razón de los efectos opuestos de algunos agentes estresantes como la dexametasona sobre la progresión tumoral, como ha sido confirmado por la literatura. Esta razón oculta resultó estar vinculada con el tipo de progresión del tumor de los diferentes tejidos. En el primer tipo de progresión tumoral encontrado, las nuevas células pueden ser estresadas durante la proliferación y los agentes estresantes aumentan la proliferación tumoral. En el segundo tipo, el estrés celular y la proliferación del tumor son antagonistas así, por tanto, los agentes estresantes detienen la proliferación tumoral con el fin de estresar las células. Table of Contents 1. Background ........................................................................................................................................................................... 21 1.1. The glucocorticoid paradox .................................................................................................................................................................................... 24 1.2. What is the hidden reason for this dual behaviour of glucocorticoids? ............................................................................................................... 24 1.3. To search for the hidden reason for glucocorticoids' dual behaviour we need tools to study dual behaviours in cancer findings................. 25 1.4. Studying phenotypes from expression data using sample clustering ................................................................................................................. 26 1.5. Studying phenotypic changes from expression data ............................................................................................................................................ 29 1.6. Using non-linear expression relationships to study phenotypes and phenotypic changes ............................................................................... 30 2. Objectives ............................................................................................................................................................................
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