Prostate cancer is the most prevalent cancer disease and the third most common cancer-related cause of death in European men . Clinical behavior of localized prostate cancer is highly variable. Some men have aggressive cancer leading to death but many others have indolent cancers that are cured with initial therapy or may be safely observed. Patients often face unnecessary surgery because clinical and histopathological risk factors, as well as biomarkers and their according classification models, lack discrimination accuracy. Hence, there is a high clinical demand of biomarkers for the early prognosis of prostate cancer.
To address this, we strive for a better understanding of the molecular dysregulation in PCa. We conducted whole-transcriptome variation studies to detect gene signatures of prognostic value comprising protein and non-protein coding genes in fresh frozen radical prostatectomy samples and confirmed them in routine clinical materials of formalin-fixed and paraffin-embedded (FFPE) radical prostatectomy or biopsy samples.
We assessed the transcriptional landscape of more than two hundred tissue specimens of prostate cancer patients with long-term clinical follow up. For an unbiased assessment of transcriptional changes, we used analytical methods like custom expression microarrays and transcriptome-wide next-generation sequencing. We applied survival models to the expression values of each gene and combined evidence from different types of samples via a statistical meta-analysis. We combined all selected genes in a gene expression prognostic score per patient. The combined score showed a strong prognostic effect and correlates with time to death because of the disease. We could confirm the prognostic score in an independent testing cohort of a representative sample size and showed that the score also correlates with time to biochemical recurrence.
We developed a transcriptome-based score that predicts aggressive types of prostate cancer in cohorts of prostate cancer patients treated by radical prostatectomy. We further confirmed the score in an independent cohort of tissue specimens. The score is suitable to support treatment stratification and clinical decision-making for patients diagnosed with prostate cancer. We are currently confirming the score in tissue specimens that represent hands-on clinical material.