In an era of personalised medicine and considering the high level of PCa heterogeneity that results in low response rates to available treatments, more efficient combinatorial therapies and biomarkers to guide intervention are needed. PROMOTE is a training network that applies -omics and advanced computational methods to introduce novel drug targets for advanced PCa and guide intervention according to patients’ individual molecular and medical profiles. 

Prostate cancer is the most common malignancy affecting men worldwide, with approximately 1.4 million diagnoses worldwide in 2020 [1]. Almost 45% of PCa patients experience slow-growing indolent cancer forms that are unlikely to progress rapidly, also related to a 5-year survival rate of >90% [2]. Many of these patients’ tumours would never become clinically significant (csPCa), thus as a result, a significant proportion of men are overtreated. Following this existing clinical need, and according to the new EC council recommendation (2022/0290, replacing 2003/878/EC), which encourages the establishment of cancer programmes that include stratification tools in order to avoid harms (overdiagnosis and overtreatment of indolent disease), in PROMOTE we propose quantitative omics-based biomarker scores and imaging metrics (pathomics and/or radiomics) to improve on risk stratification for csPCa in guiding biopsies in patients at risk and also those under AS with the goals to reduce unnecessary biopsies and to predict PCa aggressiveness. 

At the same time, some PCa tumours present in an advanced stage are related to poor prognosis (median survival 33-60 months)2. As highlighted by EC Commission priorities and the EAU guidelines2, quality of life and personalised care go hand in hand. Treating PCa can affect an individual both physically and mentally, personally and professionally. As such, although several treatments appear in advanced settings (particularly metastatic) they are frequently associated with acquisition of resistance and not all patients respond well. Thus, better characterization at the molecular level in order to introduce novel more effective therapies and/or treatment combinations, is highly required to improve efficiency towards a more personalised medicine approach. As tissue omics studies mainly focus on the comparisons between non-malignant and all cancer types, better characterization of advanced disease, particularly metastatic hormone sensitive setting (mHSPC) could be of value. 

As evident from these facts, clinical management of PCa is not optimal, as patients who do not require treatment are overtreated, while for those with advanced PCa, efficient management of treatment options is challenging. What is therefore needed, in order to go beyond the state-of-the art in terms of PCa management is: 

1. novel non-invasive stratification tools (-omics and AI imaging/radiomics models) for accurate discrimination between slow-growing and csPCa that would prevent overtreatment in patients at risk and those under AS, 
2. novel more efficient drug candidates and/ or combinatorial therapies for advanced metastatic PCa, driven by molecular characterisation of the disease phenotypes.

References

[1] Culp, M. B., et al. (2020). Eur Urol 77(1): 38-52. 

[2] Mottet, N., et al. (2021). Eur Urol 79(2): 243-262.