Ki‐67 immunoquantitation in cervical intraepithelial neoplasia (CIN): a sensitive marker for grading

Abstract

The aim of this study was to assess the value of Ki-67 immunoquantitation with a computerized image analysis system for grading support in cervical intraepithelial neoplasia (CIN). Sixty-five 'blind' consensus biopsies (23 CIN 1, 22 CIN 2, and 20 CIN 3) were used as a learning set. Measurements were done in the carefully selected most severely dysplastic part of the epithelium of each CIN case. The resulting discriminating combination of quantitative features was then prospectively applied on 121 new biopsies (test set) and compared with the classical CIN grade assessed routinely by six different pathologists and with the blind review grades assessed by two experienced pathologists. In the learning set of 65 cases, a jack-knifed stepwise discriminant analysis showed that the 90th percentile of the stratification index and the number of positive nuclei per 100 microm basal membrane are the best discriminating set of features to distinguish the three CIN grades at the same time. With these features, two CIN 1 cases were 'misclassified' as CIN 2 and nine CIN 2 cases as CIN 3. Overall agreement, therefore, was only 83%. However, recut of the paraffin blocks in the two 'misclassified' CIN 1 cases revealed CIN 2 in the first and CIN 3 in the other, while the other CIN 1 cases that were correctly classified with Ki-67 quantitation remained CIN 1. Likewise, nine CIN 2 cases were misclassified as CIN 3, but in two of these nine cases histological follow-up clearly indicated CIN 3. Agreement may thus be higher than the 83% in the learning set suggests. In the subsequent prospective evaluation on 121 routine CIN cases (test set), agreement between routine CIN grades (by six independent different pathologists) and quantitative Ki-67 classification was 78%. However, when compared with the blind review CIN grades of two expert pathologists, agreement was 97% and sensitivity, specificity, and positive and negative predictive value were very high. It is concluded that Ki-67 immunoquantitation is a useful diagnostic adjunct to distinguish different CIN grades and may also be a sensitive biological indicator of progression of seemingly low-grade CIN.

p16INK4a Expression Correlates with Degree of Cervical Neoplasia: A Comparison with Ki-67 Expression and Detection of High-Risk HPV Types

“…Although Ki-67 has been shown in several studies to be useful in diagnosing cervical neoplasia, our study shows that whereas Ki-67 expression is a sensitive marker of cervical neoplasia, overexpression is linked to both inflammation and reactive/atypical changes; p16 INK4a showed no such association (7,10,14,22). This is to be expected as inflammation is associated with increased cell turnover and reactive cervical squamous metaplasia has been shown to overexpress Ki-67 (10).…”

“…Wispy weak cytoplasmic staining present in rare cells (Ͻ5%) was considered Ϯ, and for analysis was grouped into the negative category. For Ki-67, the results were also reported in a semiquantitative fashion as cells in the lower 1/3 of the epithelium staining (i.e., usually basilar cell staining), cells in the middle 1/3-2/3 staining, or cells in the upper 1/3 staining (14). Strong nuclear staining was considered a positive reaction.…”

Diagnostic role of p16/INK4A protein in Human Papillomavirus (HPV) induced cervical dysplasia

“…A frequently used immunohistochemical marker in intraepithelial cervical dysplasia (CIN/SIL) is the Ki-67 protein that occurs in the nuclei of proliferating and/ or repeatedly dividing (immortalized) cells, including dysplastic cells [55]. The decreased availability of the functioning Rb protein due to the over-expression of E7 polypeptide, not only leads to p16 overexpression, but also explains the higher expression Ki-67 protein [56].…”

MIB1 expression in basal cell layer: a diagnostic tool to identify premalignancies of the vulva

“…13,14 In many (pre)malignant lesions, qualitative MIB1 expression is used for grading and estimating prognosis. 10,[15][16][17][18] Bulten et al 15 used a method in which epithelial MIB1 expression patterns in cervical lesions were digitally quantified. The method proved to be an objective, reproducible and reliable method of classification for dysplastic changes in cervical epithelium.…”