Breast tumors are detected by self exam, clinical exam, and mammogram and suspicious lesions are biopsied. The ensuing histological classification plays a determining role in the treatment decision but the associated risk of malignancy, the appropriate treatment, and the risk of reoccurrence are difficult to determine. As a consequence, patient treatment is based on epidemiological findings rather than individual needs. Non- invasive imaging provides some information but early breast cancer detection by routine screening is not currently feasible. However, once a tumor has been detected and biopsied, there is urgent need for novel methods to aid in the detection and classification of sub-classes of lesions. One key epigenetic marker of cell phenotype is the organization of nuclear proteins which direct and reflect normal cell function. Based on the hypothesis that the redistribution of chromatin-related proteins reflects changes in gene expression that accompany alterations in cell phenotype, we have developed image analysis methodologies to quantify the nuclear distribution of specific chromatin-associated proteins from three-dimensional, high-resolution, fluorescently immunostained images. By applying these methods to culture models that mimic normal and malignant breast epithelial tissue, we have demonstrated that the distribution of nuclear mitotic apparatus protein (NuMA) and heterochromatin related protein histone-4 methylated on lysine-20 (H4-K20m) are biomarkers capable of clearly distinguishing non-neoplastic and malignant human mammary epithelial cells. The goal of this project is to quantify the distribution of specific nuclear proteins in culture models that mimic premalignant and malignant tissue to uncover epigenetic characteristics of premalignant disease. Our image-based methodologies will be expanded to produce a novel technique, the phenotype tissue-map, capable of resolving local tissue phenotype at cellular resolution and uncovering subtle differences in tissue morphology and behavior. The technology, which will work alongside the usual H&E staining and histological techniques, will be tested on needle-core biopsies of a variety of premalignant tumors with the aim of defining sub-classes of graded lesions. The results will be correlated with the histopathology of the initial needle-core and the follow-up surgical biopsy with the hope of predicting more aggressive phenotypes missed by the initial screen. The future public health benefit of this research is to aid the treatment decision process of breast cancer patients. By better understanding the organization of molecular components within the cell and how the organization of these components is altered during the progression to cancer, we can develop and provide pathologists with novel image analysis tools to aid and support the histological classification of biopsied breast tissue. ? ? ?
| Long, Fuhui; Peng, Hanchuan; Sudar, Damir et al. (2007) Phenotype clustering of breast epithelial cells in confocal images based on nuclear protein distribution analysis. BMC Cell Biol 8 Suppl 1:S3 |
