Influence of surgical manipulation on prostate gene expression: implications for molecular correlates of treatment effects and disease prognosis.

Purpose: Measurements of tissue gene expression are increasingly used for disease stratification, clinical trial eligibility, and assessment of neoadjuvant therapy response. However, the method of tissue acquisition alone could significantly influence the expression of specific transcripts or proteins. This study examines whether there are transcript alterations associated with surgical resection of the prostate gland by radical retropubic prostatectomy.

Materials And Methods: Twelve patients with clinically localized prostate cancer underwent immediate in situ prostate biopsy after induction of anesthesia for radical prostatectomy. Ex vivo prostate biopsies were performed immediately after surgical removal. Prostate epithelium was acquired by laser-capture microdissection, and transcript abundance levels were quantitated by cDNA microarray hybridization and confirmed by quantitative polymerase chain reaction. Data were analyzed by paired, two-sample t test using Statistical Analysis of Microarray algorithms, and linear models were fit as a function of clinical characteristics.

Results: Of 5,753 cDNAs with measurable expression in prostate epithelium, 88 (1.5%) were altered as a result of surgery (false-discovery rate < or = 10%), representing 62 unique genes. These included transcripts encoding acute phase response proteins, IER2 and JUNB, and regulators of cell proliferation, p21Cip1 and KLF6. Of the clinical characteristics examined, including patient age, prostate volume, serum prostate-specific antigen, blood loss, and operative time, only gland volume was significantly and negatively associated with the magnitude of gene expression difference between pre- and postsurgical specimens.

Conclusion: Surgical manipulation results in significant gene expression changes. Molecular analyses of surgical samples should recognize that transcript alterations occur rapidly, and these results are important when designing and analyzing molecular correlates of clinical studies.