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|Title:||A network biology approach to breast and colorectal cancers|
|Author:||Arroyo Sánchez, Rodrigo|
|Director:||Aloy, Patrick, 1972-|
Biologia de sistemes
|Publisher:||Universitat de Barcelona|
|Abstract:||[spa] En este proyecto, caracterizamos sistemáticamente nuevas interacciones entre genes causantes y genes asociados a los cánceres de mama y colorrectal, con el objetivo de dar a conocer los mecanismos moleculares implicados en la biología del tumor. En total, presentamos 599 y 622 nuevas interacciones relacionadas con el cáncer de mama y colorrectal, respectivamente. A continuación, contextualizamos las interacciones descubiertas integrándolas con todos los datos de interacción disponibles en la literatura, construyendo el interactoma más completo asociado a cáncer de mama. Por último, ofrecemos validaciones iniciales sobre la alteración de la respuesta al daño del ADN como consecuencia de interacciones específicas, lo que sugiere nuevos roles de RFN20 y FAM84B, entre otros, como potenciadores de los mecanismos de reparación del ADN. En el segundo capítulo de la tesis precedimos nuevas dianas terapéuticas para el cáncer de mama basándonos en su similitud funcional y topológica con dianas de fármacos ya aprobados. A continuación medimos la redundancia y el solapamiento de vías o rutas de señalización con el fin de predecir nuevas combinaciones de fármacos para el cáncer de mama. Por último, realizamos una validación inicial y comprobamos que, por un lado, la inhibición de seis de las ocho dianas produce una disminución de la supervivencia de las células del cáncer de mama. Por otra parte, un 44% de las 23 nuevas combinaciones predichas interactúan de manera sinérgica entre sí. En conclusión, las estrategias presentadas en esta tesis ofrecen una perspectiva global para explorar los mecanismos moleculares que subyacen en enfermedades complejas, más allá del estudio de genes individuales.|
[eng] Network and systems biology disciplines could revolutionize the study of complex diseases by taking proteins back to their context, considering a much broader perspective of their environment without losing the molecular details. Cancer is an extremely complex disease, as innumerable proteins are involved in its development, thus network and systems biology disciplines could revolutionize its study. The objectives of the current thesis were (1) the systematic characterization of novel interactions between causative and associated breast and colorectal cancer genes to unveil the molecular mechanisms involved in tumor biology and (2) the prediction and initial validation of novel drug targets and drug combinations for breast cancer. We first collected genes related to breast and colorectal cancers onset and development and we selected two groups of genes from our starting pool: (1) driver/causative genes (genes key in breast and colorectal cancers, genes that cause genetic predisposition to the disease or key genes in important cancer pathways), and (2) associated genes (genes related to the disease that do not interact with causative genes and that are poorly studied). Then we performed several high-throughput yeast two-hybrid screenings (a pair-wise and a library screen for each cancer type) to detect novel interactions among these two groups of genes. Overall, we identified 599 non-redundant interactions between 49 drivers and 150 associated proteins in the BC study and 622 novel interactions among 42 drivers and 65 associated proteins for CRC. To contextualize the 599 novel BC-related interactions that our study had revealed, we integrated them with all the interaction data reported in the literature to build a comprehensive interactome associated to BC, obtaining a network of 11,226 interactions among 2,019 proteins. We next studied the structure of this network to detect the presence of potential functional modules, defined as groups of proteins that are densely interconnected and that are functionally homogenous. These modules were merged by similar functions to build subnetworks, so each subnetwork contains all the modules that share a biological function. We next focused our attention in the DNA repair subnetwork and in 15 associated genes that had been never related to this function. To know if these BC candidate genes are indeed regulating DNA repair, we carried out clonogenic assays and foci formation assays. Overall, six genes showed a relationship to cell survival after DNA damage, illustrating the power of our approach to generate novel mechanistic hypothesis. In the second part of the thesis we took into account functional redundancy and pathway crosstalk to predict novel drug targets and drug combinations for breast cancer. We predicted novel putative drug targets that resembled not only the functional but also the topological characteristics of known breast cancer targets. Eight candidate drug targets were experimentally tested by MTT assays and, interestingly, the inhibition of four out of the eight targets tested yielded a clear and consistent effect in the survival of breast cancer cells, while other two were slightly inhibiting the grow of some subtypes of BC cells. Next, we wanted to evaluate the applicability of the crosstalk inhibition metric for inferring novel breast cancer drug combinations. Overall, we predicted hundreds of promising novel drug-drug or novel target-drug combinations that either exceeded the crosstalk inhibition threshold of approved drug combinations or showed a synergistic/additive behavior. We carried out MTT assays to test a selected subset of 10 drug-drug combinations and 13 novel target-drug combinations. Overall, the detailed percentages of the results obtained were (1) 44% of drug combinations were synergistic (DCI50 ≤ 0.85), (2) 39% were of additive nature (0.85 < DCI50 ≤ 1.2) and (3) 17% were antagonistic (DCI50 > 1.2). In conclusion, the strategies presented in this thesis offer a global perspective to explore the molecular mechanisms underlying complex disease beyond individual genes and proteins, and can be easily applied to other cancer types and complex diseases.
|Appears in Collections:||Tesis Doctorals - Facultat - Biologia|
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