Assessing telomerase and Ki-67 protein expression in pre-invasive lesions and invasive cervical neoplasia with correlation to clinico-pathological parameters

Background and purpose: Cervical carcinoma, exhibits distinctive hallmarks, including sustained proliferation and replicative immortality. Ki-67 is a well-established marker of cell proliferation, while the presence of telomerase, particularly its catalytic subunit human Telomerase Reverse Transcriptase (hTERT), is associated with the uncontrolled proliferation seen in many cancers. Method: The expression of Ki-67 and the hTERT component of telomerase was investigated in various cervical lesions. Tissue microarray blocks were prepared from a total of 586 paraffin-embedded cervical tissue specimens received at Sultan Qaboos University Hospital and Royal Hospital between January 2010 and December 2018. Immunohistochemistry was performed to assess the expression of both markers. Results: The results showed that Ki-67 expression increased significantly with the severity of cervical lesions (p < 0.05), with SCC displaying high Ki-67 expression in more than 50% of tumor cells. However, statistical analysis revealed no significant correlation between Ki-67 expression and lesion prognosis. On the other hand, hTERT showed a significantly higher expression in low-grade LSIL (p < 0.05), whereas high-grade squamous intraepithelial lesions and SCC predominantly showed negative hTERT expression. hTERT staining was mainly localized to the nucleus across all cervical lesions, with some cytoplasmic and combined expressions, and it was generally of mild intensity; however, this correlation was not statistically significant. Additionally, the percentage of hTERT-positive cells was mostly below 10% in all lesion types, with no statistically significant differences observed. Conclusion: Our findings suggest that the use of Ki-67 and hTERT component of telomerase combination might not be sufficient to predict the prognosis of cervical lesions. Nonetheless, the observed expression patterns of each biomarker indicate a potential role in early carcinogenesis.