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Cellular Oncology
Volume 29 (2007), Issue 1, Pages 47-58

Chromatin Phenotype Karyometry Can Predict Recurrence in Papillary Urothelial Neoplasms of Low Malignant Potential

Rodolfo Montironi,1 Marina Scarpelli,1 Antonio Lopez-Beltran,2 Roberta Mazzucchelli,1 David Alberts,3 James Ranger-Moore,3 Hubert G. Bartels,3 Peter W. Hamilton,4 Janine Einspahr,3 and Peter H. Bartels3

1Section of Pathological Anatomy and Histopathology, Polytechnic University of the Marche Region, Ancona, Italy
2Unit of Anatomic Pathology, Cordoba University Medical School, Cordoba, Spain
3College of Public Health, Arizona Cancer Center, University of Arizona, USA
4The Queen’s University, Belfast, Northern Ireland, UK

Copyright © 2007 Hindawi Publishing Corporation and the authors. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background: A preceding exploratory study (J. Clin. Pathol. 57(2004), 1201–1207) had shown that a karyometric assessment of nuclei from papillary urothelial neoplasms of low malignant potential (PUNLMP) revealed subtle differences in phenotype which correlated with recurrence of disease. Aim of the Study: To validate the results from the exploratory study on a larger sample size. Materials: 93 karyometric features were analyzed on haematoxylin and eosin-stained sections from 85 cases of PUNLMP. 45 cases were from patients who had a solitary PUNLMP lesion and were disease-free during a follow-up period of at least 8 years. The other 40 were from patients with a unifocal PUNLMP, with one or more recurrences in the follow-up. A combination of the previously defined classification functions together with a new P-index derived classification method was used in an attempt to classify cases and identify a biomarker of recurrence in PUNLMP lesions. Results: Validation was pursued by a number of separate approaches. First, the exact procedure from the exploratory study was applied to the large validation set. Second, since the discriminant function 2 of the exploratory study had been based on a small sample size, a new discriminant function was derived. The case classification showed a correct classification of 61% for non-recurrent and 74% for recurrent cases, respectively. Greater success was obtained by applying unsupervised learning technologies to take advantage of phenotypical composition (correct classification of 92%). This approach was validated by dividing the data into training and test sets with 2/3 of the cases assigned to the training sets, and 1/3 to the test sets, on a rotating basis, and validation of the classification rate was thus tested on three separate data sets by a leave-k-out process. The average correct classification was 92.8% (training set) and 84.6% (test set). Conclusions: Our validation study detected subvisual differences in chromatin organization state between non-recurrent and recurrent PUNLMP, thus allowing a very stable method of predicting recurrence of papillary urothelial neoplasms of low malignant potential by karyometry.