Chromatin phenotype karyometry can predict recurrence in papillary urothelial neoplasms of low malignant potential

Rodolfo Montironi, Marina Scarpelli, Antonio Lopez-Beltran, Roberta Mazzucchelli, David S Alberts, James Ranger-Moore, Hubert G. Bartels, Peter W. Hamilton, Janine G Einspahr, Peter H. Bartels

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)47-58
Number of pages12
JournalCellular Oncology
Volume29
Issue number1
StatePublished - 2007

Fingerprint

Karyometry
Chromatin
Phenotype
Recurrence
Neoplasms
Sample Size
Validation Studies
Hematoxylin
Eosine Yellowish-(YS)
Biomarkers
Learning
Technology

Keywords

  • Papillary urothelial neoplasm of low malignant potential
  • Recurrence
  • Urothelium

ASJC Scopus subject areas

  • Cell Biology
  • Pathology and Forensic Medicine
  • Oncology

Cite this

Montironi, R., Scarpelli, M., Lopez-Beltran, A., Mazzucchelli, R., Alberts, D. S., Ranger-Moore, J., ... Bartels, P. H. (2007). Chromatin phenotype karyometry can predict recurrence in papillary urothelial neoplasms of low malignant potential. Cellular Oncology, 29(1), 47-58.

Chromatin phenotype karyometry can predict recurrence in papillary urothelial neoplasms of low malignant potential. / Montironi, Rodolfo; Scarpelli, Marina; Lopez-Beltran, Antonio; Mazzucchelli, Roberta; Alberts, David S; Ranger-Moore, James; Bartels, Hubert G.; Hamilton, Peter W.; Einspahr, Janine G; Bartels, Peter H.

In: Cellular Oncology, Vol. 29, No. 1, 2007, p. 47-58.

Research output: Contribution to journalArticle

Montironi, R, Scarpelli, M, Lopez-Beltran, A, Mazzucchelli, R, Alberts, DS, Ranger-Moore, J, Bartels, HG, Hamilton, PW, Einspahr, JG & Bartels, PH 2007, 'Chromatin phenotype karyometry can predict recurrence in papillary urothelial neoplasms of low malignant potential', Cellular Oncology, vol. 29, no. 1, pp. 47-58.
Montironi R, Scarpelli M, Lopez-Beltran A, Mazzucchelli R, Alberts DS, Ranger-Moore J et al. Chromatin phenotype karyometry can predict recurrence in papillary urothelial neoplasms of low malignant potential. Cellular Oncology. 2007;29(1):47-58.
Montironi, Rodolfo ; Scarpelli, Marina ; Lopez-Beltran, Antonio ; Mazzucchelli, Roberta ; Alberts, David S ; Ranger-Moore, James ; Bartels, Hubert G. ; Hamilton, Peter W. ; Einspahr, Janine G ; Bartels, Peter H. / Chromatin phenotype karyometry can predict recurrence in papillary urothelial neoplasms of low malignant potential. In: Cellular Oncology. 2007 ; Vol. 29, No. 1. pp. 47-58.
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abstract = "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.",
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AU - Alberts, David S

AU - Ranger-Moore, James

AU - Bartels, Hubert G.

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AU - Einspahr, Janine G

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