Background Our objective was to develop and validate a multi-feature nuclear score based on image analysis of direct DNA staining, and to test its association with field effects and subsequent detection of prostate cancer (PCa) in benign biopsies. Methods Tissue sections from 39 prostatectomies were Feulgen-stained and digitally scanned (400×), providing maps of DNA content per pixel. PCa and benign epithelial nuclei were randomly selected for measurement of 52 basic morphometric features. Logistic regression models discriminating benign from PCa nuclei, and benign from malignant nuclear populations, were built and cross-validated by AUC analysis. Nuclear populations were randomly collected <1 mm or >5 mm from cancer foci, and from cancer-free prostates, HGPIN, and PCa Gleason grade 3–5. Nuclei also were collected from negative biopsy subjects who had a subsequent diagnosis of PCa and age-matched cancer-free controls (20 pairs). Results A multi-feature nuclear score discriminated cancer from benign cell populations with AUCs of 0.91 and 0.79, respectively, in training and validation sets of patients. In prostatectomy samples, both nuclear- and population-level models revealed cancer-like features in benign nuclei adjacent to PCa, compared to nuclei that were more distant or from PCa-free glands. In negative biopsies, a validated model with 5 variance features yielded significantly higher scores in cases than controls (P = 0.026). Conclusions A multifeature nuclear morphometric score, obtained by automated digital analysis, was validated for discrimination of benign from cancer nuclei. This score demonstrated field effects in benign epithelial nuclei at varying distance from PCa lesions, and was associated with subsequent PCa detection in negative biopsies. Impact This nuclear score shows promise as a risk predictor among men with negative biopsies and as an intermediate biomarker in Phase II chemoprevention trials. The results also suggest that subvisual disturbances in nuclear structure precede the development of pre-neoplastic lesions.
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