Tumor Microenvironment: Bioinformatics and Systems Biology Approaches

Cancers develop in complex microenvironments whose importance was emerging during last years. In fact, cancer microenvironment influences tumor progression and leads to the raising of chemotherapics resistance. Thus, a shift of the focus from cancer cells to cancer cells in their environment is crucial for studying the molecular and metabolic features of tumors in physiological contexts. Within the microenvironment, cancer associated fibroblasts (CAF) are attracting the attention of scientific community since, up to date, it is clear that they are the main component involved in the organization of tumor tissue and that they interact with cancer cells and affect their behavior. Importantly, stromal cell types within the microenvironment are genetically stable, contrary to the tumor counterpart that frequently shows genetic instability and seriously altered physiological mechanisms. Accordingly, they represent a valuable therapeutic target. For these reasons, in this work we investigated the interplay between prostate cancer cells and tumor microenvironment, focusing on CAFs' role and on alterations of cancer cells occurring due their presence. In the first part of the study we collected expression profile data from cultures and co-cultures as well as metabolic data in order to characterize prostate cancer cells (PC3), CAFs and normal fibroblasts and alterations occurring in these cells n co-culture conditions. We found deregulated genes, strictly related to activation of processes which ease conditions favoring tumor progression in PC3 cells and in CAFs. More, we found deregulated genes in CAFs which usually are described as deregulated in transformed cells from patients and studied in PC3s, highlighting the importance of considering the stromal component as playing a major role in driving tumor progression. Through analyses of metabolic data we shed light on metabolic needs of PC3s and CAFs and on the metabolic behavior adopted by CAFs to enhance PC3s' growth. In the second part of the study, the retrieved data were used to build a metabolic model which in turn was used to validate an algorithm we developed, Metpath, designed toto improvestudies of unknown pathways' alterations. The models we built, a single cell model for PC3 and S9 and one model representing interacting PC3 and CAF cells, showed to be able to recapitulate the main metabolic reactions occurring in the corresponding conditions and represent a valid starting ground on which refined models for further studies could be developed. Moreover, MetPathrevealed altered metabolic pathways in PC3 and in CAF, which deserve further studies to deepen the knowledge about the way they can confer advantages to tumor. Taken together, all the results obtained in this work demonstrate the importance of considering and studying the tumors not only as a set of cancer cells but as part ofa complex microenvironment which influences tumor's progression. Importantly, this workhighlights the importance of the modern approaches to cancer study. In fact, simulation studies on --omics integrated models, like the ones elaborated in this work, can really push forward research in the multidisciplinary field of cancer research