Duration of androgen deprivation therapy with maximum androgen blockade for localized prostate cancer

<p>Abstract</p> <p>Background</p> <p>Primary androgen deprivation therapy (ADT) is a treatment option not only for advanced but also for localized prostate cancer. However, the appropriate duration for primary ADT for localized prostate cancer has not been defined and few studies have addressed this issue. In this study, we aimed to determine the appropriate duration of ADT for localized prostate cancer.</p> <p>Methods</p> <p>Sixty-eight consecutive patients with localized prostate cancer who underwent a prostatectomy following neoadjuvant ADT were retrospectively reviewed. Factors associated with pT0, which is regarded as serious cancer cell damage or elimination, were investigated.</p> <p>Results</p> <p>Of the 68 males, 24 (35.3%) were classified as pT0. The median duration of neoadjuvant ADT in the pT0 and non-pT0 groups was 9 months and 7.5 months, respectively (p = 0.022). The duration of neoadjuvant ADT from when PSA reached < 0.2 ng/ml to surgery was longer in the pT0 group than that in the non-pT0 group (median 5 months against 3 months, p = 0.011). pT0 was achieved in 5 of 6 patients (83.3%) who received ADT for ≥10 months after PSA reached < 0.2 ng/ml. No other clinical characteristics predicted conversion to pT0.</p> <p>Conclusions</p> <p>Continuous ADT for ≥10 months after PSA reached < 0.2 ng/ml induced serious prostate cancer cell damage in most patients (> 80%) and may be sufficient to treat localized prostate cancer.</p

Epidermal Growth Factor Receptor (EGFR) mutation analysis, gene expression profiling and EGFR protein expression in primary prostate cancer

<p>Abstract</p> <p>Background</p> <p>Activating mutations of the epidermal growth factor receptor (<it>EGFR</it>) confer sensitivity to the tyrosine kinase inhibitors (TKi), gefitinib and erlotinib. We analysed EGFR expression, EGFR mutation status and gene expression profiles of prostate cancer (PC) to supply a rationale for EGFR targeted therapies in this disease.</p> <p>Methods</p> <p>Mutational analysis of EGFR TK domain (exons from 18 to 21) and immunohistochemistry for EGFR were performed on tumour tissues derived from radical prostatectomy from 100 PC patients. Gene expression profiling using oligo-microarrays was also carried out in 51 of the PC samples.</p> <p>Results</p> <p>EGFR protein overexpression (EGFR_high) was found in 36% of the tumour samples, and mutations were found in 13% of samples. Patients with EGFR_hightumours experienced a significantly increased risk of biochemical relapse (hazard ratio-HR 2.52, p=0.02) compared with patients with tumours expressing low levels of EGFR (EGFR_low). Microarray analysis did not reveal any differences in gene expression between EGFR_highand EGFR_lowtumours. Conversely, in EGFR_hightumours, we were able to identify a 79 gene signature distinguishing mutated from non-mutated tumours. Additionally, 29 genes were found to be differentially expressed between mutated/EGFR_high(n=3) and mutated/EGFR_lowtumours (n=5). Four of the down-regulated genes, U19/EAF2, ABCC4, KLK3 and ANXA3 and one of the up-regulated genes, FOXC1, are involved in PC progression.</p> <p>Conclusions</p> <p>Based on our findings, we hypothesize that accurate definition of the EGFR status could improve prognostic stratification and we suggest a possible role for EGFR-directed therapies in PC patients. Having been generated in a relatively small sample of patients, our results warrant confirmation in larger series.</p

Identification of Clinically Relevant Protein Targets in Prostate Cancer with 2D-DIGE Coupled Mass Spectrometry and Systems Biology Network Platform

Prostate cancer (PCa) is the most common type of cancer found in men and among the leading causes of cancer death in the western world. In the present study, we compared the individual protein expression patterns from histologically characterized PCa and the surrounding benign tissue obtained by manual micro dissection using highly sensitive two-dimensional differential gel electrophoresis (2D-DIGE) coupled with mass spectrometry. Proteomic data revealed 118 protein spots to be differentially expressed in cancer (n = 24) compared to benign (n = 21) prostate tissue. These spots were analysed by MALDI-TOF-MS/MS and 79 different proteins were identified. Using principal component analysis we could clearly separate tumor and normal tissue and two distinct tumor groups based on the protein expression pattern. By using a systems biology approach, we could map many of these proteins both into major pathways involved in PCa progression as well as into a group of potential diagnostic and/or prognostic markers. Due to complexity of the highly interconnected shortest pathway network, the functional sub networks revealed some of the potential candidate biomarker proteins for further validation. By using a systems biology approach, our study revealed novel proteins and molecular networks with altered expression in PCa. Further functional validation of individual proteins is ongoing and might provide new insights in PCa progression potentially leading to the design of novel diagnostic and therapeutic strategies