Patterns in the tapestry of chromatin-bound RB.

The retinoblastoma protein (RB)-mediated regulation of E2F is a component of a highly conserved cell cycle machine. However, RB's tumor suppressor activity, like RB's requirement in animal development, is tissue-specific, context-specific, and sometimes appears uncoupled from cell proliferation. Detailed new information about RB's genomic distribution provides a new perspective on the complexity of RB function, suggesting that some of its functional specificity results from context-specific RB association with chromatin. Here we summarize recent evidence showing that RB targets different types of chromatin regulatory elements at different cell cycle stages. RB controls traditional RB/E2F targets prior to S-phase, but, when cells proliferate, RB redistributes to cell type-specific chromatin loci. We discuss the broad implications of the new data for RB research.

Translocation of nuclear chromatin distribution to the periphery reflects dephosphorylated threonine-821/826 of the retinoblastoma protein (pRb) in T24 cells treated with Bacillus Calmette-Guérin.

The standard treatment for non-muscle-invasive bladder cancer is intravesical Bacillus Calmette-Guérin (BCG) therapy, which is considered the only intravesical therapy that reduces the risk of progression to muscle-invasive cancer. BCG unresponsiveness, in which intravesical BCG therapy is ineffective, has become a problem. It is thus important to evaluate the effectiveness of BCG treatment for patients as soon as possible in order to identify the optimal therapy. Urine cytology is a noninvasive, easy, and cost-effective method that has been used during BCG treatment, but primarily only to determine benign or malignant status; findings concerning the efficacy of BCG treatment based on urine cytology have not been reported. We investigated the relationship between BCG exposure and nuclear an important criterion in urine cytology, i.e., nuclear chromatin patterns. We used three types of cultured cells to evaluate nuclear chromatin patterns and the cell cycle, and we used T24 cells to evaluate the phosphorylation of retinoblastoma protein (pRb) in six-times of BCG exposures. The results revealed that after the second BCG exposure, (i) nuclear chromatin is distributed predominantly at the nuclear periphery and (ii) the dephosphorylation of threonine-821/826 in pRb occurs. This is the first report of a dynamic change in the nuclear chromatin pattern induced by exposure to BCG. Molecular findings also suggested a relationship between this phenomenon and cell-cycle proteins. Although these results are preliminary, they contribute to our understanding of the cytomorphological changes that occur with BCG exposure.

Discriminant analysis and interpretation of nuclear chromatin distribution and coarseness using gray-level co-occurrence matrix features for lobular endocervical glandular hyperplasia.

BACKGROUND: Lobular endocervical glandular hyperplasia (LEGH) is a disease considered to be the origin of tumorigenesis of minimal deviation adenocarcinoma, which has characteristic expression in the gastric pyloric mucosa. It is difficult to diagnose by nuclear findings because of lower nuclear atypia. In this study, nuclei of endocervical (EC) and LEGH cells were digitized, and nuclear information was quantified from nuclear images and objectively evaluated using a computer. We examined whether it is possible to distinguish between EC and LEGH cells, which is difficult by human eyes. METHODS: Signal intensity, morphological features, Otsu thresholding technique and gray-level co-occurrence matrix (GLCM) features were calculated from nuclei of EC and LEGH cells on cytology microscopic images. Then, discriminant analysis was performed using the significant difference test and linear support vector machine (LSVM). RESULTS: GLCM features in LEGH cells were higher than those in EC cells. The nuclei of LEGH cells had a higher frequency of signal value pairs with a larger signal value difference than that of EC cells. Therefore, LEGH cell nuclei are thought to have more chromatin granules, and the chromatin is coarse and granular. Moreover, in the LSVM discriminant analysis, the accuracy of GLCM calculated using these features was 85.4%. CONCLUSION: In this study, GLCM accurately demonstrated the nuclear chromatin distribution and coarseness. Discriminant analysis of EC and LEGH cells using GLCM features is useful.

Morphology, morphometry and chromatin distribution in llama sperm nuclei.

The objectives of this study were as follows: (i) to describe and evaluate the frequencies of different morphologies of llama sperm nuclei, (ii) to determine morphometric values of nuclear parameters, (iii) to describe and estimate the frequencies of different classes of chromatin distribution and (iv) to measure haploid DNA content and analyse its nuclear distribution. The study was performed using ejaculates collected from seven males, and sperm nuclei were stained with the Feulgen reaction. Normal morphology ranged from 78.36% to 93.92%, and abnormalities included short, small, large, pyriform, narrow, micro and round nuclei. Important differences in nuclei considered normal were found between some males. The following average values were obtained for each sperm nuclear morphometric parameter analysed: area 11.64 µm2 , perimeter 13.16 µm, length 5.12 µm, width 2.81 µm, ellipticity 1.85 and form 0.83. Differences between males were significant for all the parameters (p < .01). Light microscope observations and cytophotometric determinations allowed discriminating between three classes of chromatin distribution: homogeneous, diffuse and showing a clear band. Significant differences between males were found for the frequencies of the three classes (p < .01). Cluster analysis methods were used to estimate the resemblance between males according to the characteristics of their sperm nuclei. A great intermale variability was found for morphological, morphometric and chromatin distribution data. These parameters would have low dependence between them.

Feature analysis of cell nuclear chromatin distribution in support of cervical cytology.

Cytology, a method of estimating cancer or cellular atypia from microscopic images of scraped specimens, is used according to the pathologist's experience to diagnose cases based on the degree of structural changes and atypia. Several methods of cell feature quantification, including nuclear size, nuclear shape, cytoplasm size, and chromatin texture, have been studied. We focus on chromatin distribution in the cell nucleus and propose new feature values that indicate the chromatin complexity, spreading, and bias, including convex hull ratio on multiple binary images, intensity distribution from the gravity center, and tangential component intensity and texture biases. The characteristics and cellular classification accuracies of the proposed features were verified through experiments using cervical smear samples, for which clear nuclear morphologic diagnostic criteria are available. In this experiment, we also used a stepwise support vector machine to create a machine learning model and a cross-validation algorithm with which to derive identification accuracy. Our results demonstrate the effectiveness of our proposed feature values.

Detection of malignant mesothelioma using nuclear structure of mesothelial cells in effusion cytology specimens.

Mesothelioma is a form of cancer generally caused from previous exposure to asbestos. Although it was considered a rare neoplasm in the past, its incidence is increasing worldwide due to extensive use of asbestos. In the current practice of medicine, the gold standard for diagnosing mesothelioma is through a pleural biopsy with subsequent histologic examination of the tissue. The diagnostic tissue should demonstrate the invasion by the tumor and is obtained through thoracoscopy or open thoracotomy, both being highly invasive surgical operations. On the other hand, thoracocentesis, which is removal of effusion fluid from the pleural space, is a far less invasive procedure that can provide material for cytological examination. In this study, we aim at detecting and classifying malignant mesothelioma based on the nuclear chromatin distribution from digital images of mesothelial cells in effusion cytology specimens. Accordingly, a computerized method is developed to determine whether a set of nuclei belonging to a patient is benign or malignant. The quantification of chromatin distribution is performed by using the optimal transport-based linear embedding for segmented nuclei in combination with the modified Fisher discriminant analysis. Classification is then performed through a k-nearest neighborhood approach and a basic voting strategy. Our experiments on 34 different human cases result in 100% accurate predictions computed with blind cross validation. Experimental comparisons also show that the new method can significantly outperform standard numerical feature-type methods in terms of agreement with the clinical diagnosis gold standard. According to our results, we conclude that nuclear structure of mesothelial cells alone may contain enough information to separate malignant mesothelioma from benign mesothelial proliferations.