A method for accurate prediction of prognosis in individual patients with prostatic carcinoma does not exist. The limitations of pathological grading systems may result from the failure of standard pathological examination of fixed dead tissue to accurately assess the biological and metastatic behavior of live tumor cells. Many of the sublines of the Dunning R-3327 rat prostatic adenocarcinoma are histologically similar yet differ in metastatic potential. Cells from the Dunning model were grown in culture and filmed by time-lapse videomicroscopy. These cells exhibited characteristic membrane ruffling, pseudopodal extension, and cellular translation that could be graded with 80% reproducibility. Individual cells from sublines with high metastatic potential were separated from cells from sublines of low metastatic potential in 96% of cases. We have applied our cell motility grading system to prospectively classify the metastatic potential of neoplastic cells. The mean motility grades of sublines of high and low metastatic potential differed significantly (Mann-Whitney-Wilcoxon, P less than 0.0005). Among seven sublines in which the grading system was developed, individual cells were correctly classified as high or low metastatic in 71% of cases by ruffling or pseudopodal extension, 73% of cases by translation, and 75% of cases by motility index, an average of the three parameters of motility. Among four newly tested sublines, cells from a low metastatic and high metastatic sublines were perfectly classified. Cells from two other low metastatic sublines were misclassified. When all 88 cells from the 11 sublines were classified, high metastatic cells were detected with 94% sensitivity and 50% specificity. The predictive value of a determination of low metastatic was 93%, whereas the predictive value of an assignment of high metastatic was 52%. The ability to detect and accurately classify most highly metastatic cells while rarely erring in a classification of low metastatic potential suggests that a grading system of cancer cell motility should be evaluated in human prostatic carcinoma. The motility of live prostatic carcinoma cells may predict patient prognosis better than standard pathological grading systems.