Cathepsin D and chromogranin A as predictors of long term disease specific survival after radical prostatectomy for localized carcinoma of the prostate.
The accumulation of chromogranin A (Chr A) and cathepsin D (Cath D) gene products may be important in prostate carcinoma progression. This study assessed whether the levels of immunoreactivity for Chr A and Cath D are better predictors of disease specific survival than conventional pathologic parameters of the primary tumor such as Gleason score, capsular penetration, seminal vesicle invasion, and percent tumor in the specimen for patients with clinically localized prostate carcinoma managed by radical prostatectomy. Seventy-one patients with modified Jewett clinical stages A1 to B2 adenocarcinoma of the prostate underwent a radical prostatectomy after a negative metastatic workup. No neoadjuvant or adjuvant treatments were given and all disease recurrences and causes of death were recorded. Analysis of prostatectomy specimens was undertaken to determine the conventional pathologic parameters of the primary tumor and Chr A and Cath D immunohistochemical staining. Univariate and multivariate analyses were performed to determine the independent contributions of Chr A and Cath D in predicting survival. On univariate analysis Chr A was the only variable that reached statistical significance for disease specific survival (P = 0.035). Cath D nearly reached significance with a P value of 0.079 for disease specific survival. On multivariate analysis, the only independent factor predicting disease specific survival was the Chr A staining score (P < 0.05). In patients with unequivocal foci of Chr A immunoreactivity, the 14-year disease specific survival was 50% compared with 68% for patients lacking such foci. The level of Chr A immunohistochemical staining is a strong predictor of disease specific survival and is superior to standard pathologic prognostic factors. Such findings lay the groundwork for future prospective study of the utility of such markers on biopsy specimens to predict patient outcome.