PCaProTreat · Multi-omics molecular treatment targets for Prostate Cancer

Multi-omics molecular treatment targets for Prostate Cancer

Clinical problem: Prostate Cancer (PCa) is the second most commonly diagnosed cancer among men. PCa patients represent a diverse group of individuals, with many presenting indolent disease, (unlikely to progress in the absence of treatment), and others having aggressive, life-threatening disease. Discrimination between these two groups is crucial to prevent over-treatment of patients with indolent disease and under-treatment of those with lethal disease. Lack of effective therapies for advanced disease is reflected in the 5-year survival rate that is decreasing from 100% (for patients with localized stage) to 29% (for patients with advanced stage). Even though, scientific advancements have led to the approval of new drugs for advanced PCa, the low response rate and development of resistance remains a barrier to improve on therapeutic outcomes. Challenges: Progress has been made in understanding biology of PCa progression. However, development of new drugs is hindered by high molecular complexity, heterogeneity and development of resistance, impacting the treatment response. The problem seems to be multifactorial, with “sub-optimal” selection of the drug targets, being a key issue. The latter is to a large extent a result of insufficient knowledge of the molecular pathophysiology, (e.g. cross- linking of the molecular pathways), assessment of biological relevance and underestimation of disease heterogeneity. Societal Implications: PCaProTreat was designed to face existing therapeutic challenges and address pressing needs related to PCa burden. The aim is to improve our understanding of molecular changes associated with PCa progression to define novel drug targets based on the molecular pathophysiology. Thus, PCaProTreat has the potential to revolutionise PCa management, and ultimately improve patient outcome and quality of life. The specific PCaProTreat objectives were: 1. Establishment of PCa knowledgebase with features related to PCa progression. 2. Characterisation of the molecular landscape of PCa progression through the integration of multi-source (tissue, urine, and seminal plasma) and multi-omics data, complemented with literature-mined data. 3. Definition of biological processes/ pathways and their regulatory elements responsible for disease progression (best suited drug targets), followed by their validation. 4. In silico prediction of therapeutic agents based on profiling data sets. Conclusions: PCaProTreat defined molecular-driven drug targets/ potential therapeutic agents that directly targets molecular mechanisms underlying the disease. The research and training activities boosted the IF fellow career in the industry sector.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз