Objective
In the developed countries, prostate cancer is the second leading cause of cancer-associated death in men, with a predicted rate of 10.9/100.000 men in Europe in 2016. Mortality results when prostate cancer has spread to other organs (metastasis, particularly to the bone). Prostate cancer prognosis and follow-up is mainly performed with routine blood test (prostate specific antigen levels). However, the low/high risk of metastasis for individual patients cannot always be accurately assessed due to tumor heterogeneity and differential rate of tumor progression. Thus, a more thorough understanding of the metastatic processes is needed.
Complex molecular interactions and cellular processes between the cancer (stem) cells and the surrounding tissue microenvironment (supportive stroma) are required for tumor growth and metastasis. Cancer cells hijack the normal microenvironment to orchestrate metastatic events and acquisition of resistance to drug treatments. To increase our understanding of the metastatic mechanisms we sought to identify and modulate the molecular properties of aggressive tumor cells and the reciprocal supportive stroma in unique xenograft models and eventually assess the prognostic value of the identified parameters.
We propose to investigate the following objectives:
1) identify the molecular signature of tumor and supportive stroma in metastatic patient-derived xenografts
2) elucidate the molecular mechanisms of the tumor- supportive stroma
3) determine their prognostic value in clinical blood samples as predictors of disease progression and metastasis risk.
Understanding the mechanisms of prostate cancer (re)initiation will provide the foundation for proper prognostic tool development for the identification of high risk patient groups.
Fields of science
- medical and health sciencesclinical medicineoncologyprostate cancer
- social sciencessociologydemographymortality
- medical and health sciencesmedical biotechnologytissue engineering
- natural sciencesmathematicspure mathematicsmathematical analysisfunctional analysis
- engineering and technologymedical engineeringmedical laboratory technologylaboratory samples analysis
Programme(s)
Funding Scheme
MSCA-IF-EF-ST - Standard EFCoordinator
3012 Bern
Switzerland