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. 2011 Jan;178(1):79-87.
doi: 10.1016/j.ajpath.2010.09.042. Epub 2010 Dec 23.

Determining prostate cancer-specific death through quantification of stromogenic carcinoma area in prostatectomy specimens

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Determining prostate cancer-specific death through quantification of stromogenic carcinoma area in prostatectomy specimens

Gustavo E Ayala et al. Am J Pathol. 2011 Jan.

Abstract

We previously reported that reactive stroma grading in prostate cancer (PCa) is predictive of biochemical recurrence in prostatectomies and biopsies. In this study, we tested whether quantifying the percentage of reactive stromal grade 3 (RSG 3; stromogenic carcinoma pattern) in the entire tumor is predictive of PCa-specific death. Whole-mount prostatectomies operated by a single surgeon obtained between 1983 and 1998 were reviewed. Reactive stroma was evaluated as described previously, and areas of RSG 3 in the entire tumor were registered as percentages of total tumor. Statistical analysis was performed using Spearman, Kaplan-Meier, and Cox analyses. In all, 872 cases were evaluable. Quantification of RSG 3 percentage was an independent predictor of biochemical recurrence, analyzed as a continuous or grouped variable. Patients with higher RSG 3 percentages (larger tumor areas with RSG 3) had a significantly decreased biochemical recurrence-free survival than those with a lower RSG 3 percentage, even within the Gleason score 7 subset of patients. A nomogram introduced this new variable to the model. Furthermore, quantification of RSG 3 percentage was significantly predictive of PCa-specific death. Quantification of the RSG 3 (stromogenic carcinoma) area in PCa provides additional novel information on prognosis. These data substantiate the concept that the tumor microenvironment holds significant predictive information, as well as biological significance.

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Figures

Figure 1
Figure 1
Whole-mount section of a radical prostatectomy, with different areas in the tumor marked with different symbols for four different reactive stromal grades (RSGs) (center) and the corresponding higher magnification images (corners), depending on the percentage of area of reactive stroma (RS) in the tumor: RSG 0, ≤5%; RSG 1, 6%– 15%; RSG 2, 16%–50%; RSG 3, at least a 1:1 ratio between reactive stroma and epithelial cancer.
Figure 2
Figure 2
Whole-mount slides of prostates with tumors delineated in black and areas of RSG 3 marked in blue. Varying percentages of RSG 3 are noted in the tumors. The tumor on the left has a larger area of the tumor with RSG 3 than the one on the right. Note that only one of the two tumors on the right section has RSG 3.
Figure 3
Figure 3
Time to biochemical recurrence in major groups with similar risk, based on the percentage of RSG 3 area in prostate cancer. Patients with small areas of RSG 3 in their tumors had a better survival than those with larger RSG 3 areas. The analysis groups RSG 3 percentages into five ranges (from ≤5% to >85%).
Figure 4
Figure 4
Time to biochemical recurrence in patients affected with a Gleason 7 prostate cancer but differing in percentage of RSG 3 area in the tumor. The analysis groups RSG 3 percentages into just two ranges (centered on 40%).
Figure 5
Figure 5
Kaplan Meier curves for prostate cancer (PCa)-specific mortality for percentage of RSG 3. Blue (None) indicates no intratumoral RSG 3; green (Low) indicates <15% of the tumor with RSG 3; red (High) indicates ≥15% of the tumor with RSG 3. Mean time to prostate cancer-specific death: 218 months (N = 463) for None, 20 months (N = 356) for Low, 143 months (N = 53) for High.
Figure 6
Figure 6
The postoperative nomogram includes the quantification of RSG and perineural invasion (PNI) diameter, both demonstrated to be independent predictors of biochemical recurrence-free survival. The points scored are obtained from each predictor [ie, log preoperative PSA, lymph node status (LN), surgical margin, extracapsular extension (ECE), seminal vesicle invasion (SVI), Gleason sum, stroma percentage (quantification of RSG 3 area), and PNI diameter] for a given patient and then are manually added up to obtain a total point count before reading the predicted recurrence-free probability.

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