Abstract
Background
Epithelial cell adhesion molecule (EpCAM) is a promising biomarker for squamous cell carcinoma (SCC) of the uterine cervix, because it is over-expressed in various cancers of epithelial origin. However, EpCAM expression reported in previous immunohistochemistry (IHC) studies was inconsistent. We hypothesize that the membrane-distal part of EpCAM may be lost during tissue preparation, leaving only the membrane-proximal part of EpCAM available for antibody binding and IHC staining.
Methods
Two new anti-EpCAM MAbs to the membrane-proximal part (WC-2) and the membrane-distal part (WC-1) of EpCAM were generated and characterized. WC-2 was selected for its ability to detect EpCAM in cervical tissues by IHC. One hundred thirty-five archival paraffin-embedded tissues previously diagnosed as cervical SCC (n=44), high-grade (HSIL) (n=43), or low-grade (LSIL) (n=48) squamous intraepithelial lesions were examined. IHC score was collected, recorded, and analyzed for distribution, intensity, and percentage of cancer cells stained for EpCAM.
Results
EpCAM expression was consistently detected on cervical tissues by WC-2, but not by WC-1. EpCAM was expressed with high IHC score in the majority of cervical SCC (37/44), but not in normal epithelial area adjacent to SCC. EpCAM was also highly expressed on precancerous lesion of the cervix, particularly in HSIL. More importantly, EpCAM expression could be used to distinguish between HSIL and LSIL, according to staining distribution. HSIL tissues displayed EpCAM expression in two-thirds to full thickness of the epithelium, while in LSIL the staining was limited to the lower one-third of the thickness. The IHC score of EpCAM expression was strongly correlated with cervical cancer and grades of precancerous lesions (r=0.875, p<0.001).
Conclusion
Only the anti-EpCAM MAb to the membrane-proximal part is able to detect EpCAM on paraffin-embedded cervical cancer tissues. A strong positive correlation between EpCAM expression level and the grades of SILs provides the possibility that EpCAM can be used to predict prognosis and severity in these patients.
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