Applications of quantitative digital image analysis to breast cancer research.
Our studies of radiogenic carcinogenesis in mouse and human models of breast cancer are based on the view that cell phenotype, microenvironment composition, communication between cells and within the microenvironment are important factors in the development of breast cancer. This is complicated in the mammary gland by its postnatal development, cyclic evolution via pregnancy and involution, and dynamic remodeling of epithelial-stromal interactions, all of which contribute to breast cancer susceptibility. Microscopy is the tool of choice to examine cells in context. Specific features can be defined using probes, antibodies, immunofluorescence, and image analysis to measure protein distribution, cell composition, and genomic instability in human and mouse models of breast cancer. We discuss the integration of image acquisition, analysis, and annotation to efficiently analyze large amounts of image data. In the future, cell and tissue image-based studies will be facilitated by a bioinformatics strategy that generates multidimensional databases of quantitative information derived from molecular, immunological, and morphological probes at multiple resolutions. This approach will facilitate the construction of an in vivo phenotype database necessary for understanding when, where, and how normal cells become cancer.
Ortiz De Solórzano
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C
Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.
Costes
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Callahan
D E
DE
Parvin
B
B
Barcellos-Hoff
M H
MH
D000818:Animals; D001943:Breast Neoplasms / Q000473:pathology*; D019295:Computational Biology; D004195:Disease Models, Animal; D004847:Epithelial Cells / Q000473:pathology; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D051379:Mice