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

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.

Fractal dimension of chromatin is an independent prognostic factor for survival in melanoma

“…For this purpose, traditional or new immunohistochemical markers, gene expression arrays, comparative genomic hybridization and mutational profiling have been applied [ 1 , 4 - 9 ]. Most of these techniques are sophisticated and expensive, requiring specially equipped laboratories with a trained staff, Detailed morphological analysis of the nuclei in histological or cytological preparations can give important information on cell physiology and, furthermore, can be of considerable great diagnostic and prognostic importance [ 10 - 22 ]. Physiologic or pathologic changes of the cell accompany changes of the chromatin arrangement [ 21 , 22 ].…”

“…Most of these techniques are sophisticated and expensive, requiring specially equipped laboratories with a trained staff, Detailed morphological analysis of the nuclei in histological or cytological preparations can give important information on cell physiology and, furthermore, can be of considerable great diagnostic and prognostic importance [ 10 - 22 ]. Physiologic or pathologic changes of the cell accompany changes of the chromatin arrangement [ 21 , 22 ]. In particular, neoplastic growth induces important modifications, not only of the DNA, but also of the composition and distribution of the histone and non-histone nuclear proteins, thus provoking alterations of the distribution of heterochromatin in the nucleus.…”

“…In particular, neoplastic growth induces important modifications, not only of the DNA, but also of the composition and distribution of the histone and non-histone nuclear proteins, thus provoking alterations of the distribution of heterochromatin in the nucleus. Nuclear texture features have been studied as prognostic markers in neoplasias [ 11 , 21 , 22 ]. The resources available in commercial softwares are usually restricted to basic morphometric parameters such as diameter, area and perimeter, which cannot adequately measure texture features of nuclei.…”

Análise dos parâmetros morfométricos e textura da cromatina dos mieloblastos nas síndromes mielodisplásicas

“…A dimensão fractal tem sido aplicada com sucesso para classificar tipos de neoplasias hematológicas pela citologia (32,43). A morfometria geométrica, derivadas da matriz de coocorrência e as características de Fourier têm ajudado a estabelecer variáveis prognósticas como, por exemplo, em neoplasias papilares uroteliais e carcinoma oral de células escamosas (44,45). Para a classificação de tipos de neoplasia como, por exemplo, o diagnóstico diferencial do carcinoma folicular da tireóide foi aplicado o estudo de textura nuclear baseada na dimensão fractal pelo metodo de Minkowski (20).…”

“…Na medula óssea normal, a maioria das variáveis estudadas foi capaz de distinguir blastos de promielócitos. Portanto, podemos concluir que as variáveis usadas foram uma ferramenta útil para diferenciar precursores mieloides no início da maturação, como também observados em outros estudos de textura nuclear (23,27,30,35,36,41,(43)(44)(45)47).…”