Published in:
Open Access 01-12-2014 | Research
Immunohistochemical assessment of a unique basal pattern of p53 expression in ulcerative-colitis-associated neoplasia using computer-assisted cytometry
Published in: Diagnostic Pathology | Issue 1/2014
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Background
The basal pattern of p53 expression, defined as its immunoreactivity confined to the basal half of the glands, is associated with early neoplastic lesions in ulcerative colitis (UC). However, their clinical utility of this finding is limited by the use of “visual estimation” (approximate immunoreactivity on the basis of scanning the stained slide, without formal counting). This study was designed to analyze the basal pattern of p53 using computer-assisted cytometry and to identify the optimal cutoff value for discriminating between UC-associated early-stage neoplasia and regenerative atypia.
Methods
The specimens were obtained from eight UC patients undergoing colectomy and were classified according to the criteria by the Research Committee of Inflammatory Bowel Disease of the Ministry of Health and Welfare in Japan. Patients with classes UC-IIa (indefinite for dysplasia, probably regenerative), UC-IIb (indefinite for dysplasia, probably dysplastic), and UC-III (definitive dysplasia) were enrolled in the study. Based on the percentage of immunoreactive cells in the basal half of the crypt with visual estimation, basal positivity of p53 was classified into three categories: grade 1 (1 - 9%), grade 2 (10 - 19%), and grade 3 (≥20%). Next, crypts classified as grade 3 by visual estimation were analyzed by computer-assisted image analysis.
Results
Using visual estimation, grade-3 p53 basal positivity was observed in 46.0% of UC-IIa crypts (128 of 278), 61.9% of UC-IIb crypts (39 of 63), and 94.2% of UC-III crypts (81 of 86). Using image analysis, the median p53 basal positivities were 30.3% in UC-IIa, 52.3% in UC-IIb, and 65.4% in UC-III (P ≤0.002). A receiver operating characteristics curve was generated to determine the method’s diagnostic utility in differentiating UC-IIa from UC-III. In this cohort, the sensitivity was 0.78; the specificity was 0.98; the negative predictive value was 87.4%; the positive predictive value was 95.5%, and the accuracy was 90.2% with a cutoff value for p53 basal positivity of 46.1%.
Conclusions
Our findings indicate that assessing p53 basal positivity by image analysis with an optimal threshold represents an alternative to visual estimation for the accurate diagnosis of UC-associated early-stage neoplasia.
Virtual Slides
The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/3588120501252608