Elaboración de una batería de modelos multiclónicos tumorales como estrategia de medicina personalizada

Abstract

Colorectal cancer (CRC) is the second most common form of cancer and the second cause of cancer-related death in Spain. Some of the evidence found in the last decade appoint cancer as a stem cell disease and despite having good treatments, some patients suffer a relapse. It is thought that the primary tumour can be treated properly, and the relapse may be caused by this stem-like cells, called cancer stem cells (CSCs). As normal stem cells, CSCs undergo asymmetric division, which provides self-renewal and generates a population of cells that forms the tumour bulk while procuring CSCs maintenance. Moreover, CSCs are more chemoresistant due to their slower division rate. This way, the population remains in the body, suffering epithelial-mesenchymal transition, invading distant niche and causing the relapse. Prior to relapse, the model here presented proposes using CRC immortalized cell lines to create a free-access data base of molecular signatures related to a certain behaviour. To achieve this goal, CRC cell lines were mixed to create multiclonic models and analysed to obtain their molecular signature, growth speed and treatment response. This data base is a preliminary work that will provide the best treatment for a patient’s tumour before its appearance. The origin of CSCs is still unknown, but if we manage to identify the tumour molecular signature through its molecular markers, we might be able to relate it to its growth speed and treatment response. This data base be the starting point to develop a personalised and precision medicine strategies for each patient relapse.