Alterations in phenotypic biochemical markers in bladder epithelium during tumorigenesis.
- 1 September 1993
- journal article
- Published by Proceedings of the National Academy of Sciences in Proceedings of the National Academy of Sciences
- Vol. 90 (17) , 8287-8291
- https://doi.org/10.1073/pnas.90.17.8287
Abstract
Phenotypic biochemical markers of oncogenesis and differentiation were mapped in bladder biopsies to investigate changes that occur in bladder tumorigenesis and to identify markers for increased bladder cancer risk. Touch preparations from biopsy specimens from 30 patients were obtained from tumors, the adjacent bladder epithelium, and random distant bladder epithelium. Markers, including DNA ploidy, epidermal growth factor receptor (EGFR), and oncoproteins, were quantified in individual cells by using quantitative fluorescence image analysis. Cluster analysis revealed the markers fell into three independent groups: (i) G-actin and EGFR; (ii) ploidy, cytology, and p185 (HER-2/neu oncoprotein) (ERBB2); and (iii) p300, a low-grade tumor antigen. Each marker displayed a gradient of abnormality from distant field to adjacent field to tumor. Different patterns for each marker suggested a developmental sequence of bladder cancer oncogenesis; G-actin was altered in 58% of distant biopsies (vs. 0/6 normals, P < 0.001), ploidy and cytology were altered in < 20% of distant fields and approximately 80% of tumors, and the other markers were intermediate. Patterns of EGFR and p185 suggest low-and high-grade tracks diverge early (P < 0.05 by Mann-Whitney U test for EGFR and ANOVA for p185). In conclusion, this study shows that a sequence of phenotypic changes accompanies development and progression of bladder cancers. Biochemical alterations in cells of the bladder field are often detectable before abnormal pathology, and markers previously thought to be limited to tumors were found in the field. The hierarchy of expression may be useful in identifying high-risk patients, assessing completeness of response to therapy, and monitoring and predicting recurrence.Keywords
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