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Updated: Dec 30, 2025

Semi-quantitative Detection of RNA-dependent RNA Polymerase Activity of Human Telomerase Reverse Transcriptase Protein
Published on: June 12, 2018
Immunohistochemical expression of human telomerase reverse transcriptase in oral cancer and precancer: A case-control
Namrata Mishra1, Nishi Tandon1, Naseem Fatima1
1Department of Pathology, Era's Lucknow Medical College and Hospital, Lucknow, Uttar Pradesh, India.
Introduction:
Telomere Length is critically important in normal cells and telomere shortening in combination with other oncogenic changes- promotes genome instability, potentially stimulating initiation of the early stages of cancer.
Aim:
The present study was carried out to detect human telomerase reverse transcriptase expression in oral cancer and pre-cancerous lesions by immunohistochemistry.
Materials And Methods:
An observational study was planned in which a total of 45 biopsy specimen of oral mucosa was obtained. Of these, 15 (33.3%) belonged to normal subjects, 15 (33.3%) to subjects found to have Oral submucousal fibrosis and 15 (33.3%) subjects with Oral squamous cell carcinoma.
Results:
Among cases of OSCC, majority was of well differentiated grade (80.0%), only 1 (6.7%) case was poorly differentiated and rest was of moderately differentiated (13.3%) Labelling intensity of OSCC (78.07 ± 22.31) was maximum followed by that of Normal (44.47 ± 6.32) and minimum of OSMF (26.67 ± 15.05) and intergroup difference and between group differences were also found to be significant. Labelling score of OSCC (154.47 ± 94.74) was maximum followed by that of Normal (84.73 ± 51.51) and minimum of OSMF (46.73 ± 44.25) and intergroup difference and between groups differences (Normal vs OSCC, and OSMF and OSCC) were found to be statistically significant.
Conclusion:
The present study highlights only the discriminating ability of hTERT for differentiating the malignant condition from premalignant and normal mucosa. Hence, further studies on a larger sample size, with inclusion of other premalignant conditions too are recommended in order to understand the pattern of hTERT expression changes.
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