Telomerase Activity in Bladder Cancer Tissue

Overview

Journal Exp Ther Med

Specialty Pathology

Date 2012 Nov 9

PMID 23136598

Citations 3

Authors

Akihiro Morii

Akira Komiya

Akiou Okumura

Hideki Fuse

Affiliations

Soon will be listed here.

Abstract

Telomerase is a ribonucleoprotein enzyme that maintains telomeric DNA repeats at the end of chromosomes. Telomerase activity has been reported in many human cancers. The present study evaluated telomerase activity in bladder cancer tissue and investigated whether this activity is associated with tumor characteristics and prognosis in bladder cancer patients. Telomerase activity was investigated using the telomeric repeat amplification protocol (TRAP) in bladder tissue specimens from 81 patients, including 75 patients with bladder carcinoma and 6 patients with dysplasia or an inflammatory bladder lesion. Forty-nine of the 75 bladder cancer patients were found to be telomerase-positive, while 1 out of the 6 control specimens without carcinoma was telomerase-positive. Telomerase activity was correlated with lower grade and lower stage bladder cancer, but was not significantly associated with cancer-specific survival in the total population of bladder cancer patients. However, telomerase-positive patients among the patients with invasive and grade 3 tumors had an improved prognosis. Telomerase activity was observed in early-stage bladder cancer, and may be an indicator of prognosis in bladder cancer patients with advanced-stage and high-grade tumors.

Citing Articles

Diagnostic Value of Telomerase Activity in Patients With Bladder Cancer: A Meta-Analysis of Diagnostic Test.

Peng L, Li J, Meng C, Li J, Tang D, Guan F Front Oncol. 2020; 10:570127.

PMID: 33344230 PMC: 7744937. DOI: 10.3389/fonc.2020.570127.

Telomerase promoter mutations in cancer: an emerging molecular biomarker?.

Vinagre J, Pinto V, Celestino R, Reis M, Populo H, Boaventura P Virchows Arch. 2014; 465(2):119-33.

PMID: 25048572 DOI: 10.1007/s00428-014-1608-4.

A system-level pathway-phenotype association analysis using synthetic feature random forest.

Pan Q, Hu T, Malley J, Andrew A, Karagas M, Moore J Genet Epidemiol. 2014; 38(3):209-19.

PMID: 24535726 PMC: 4327826. DOI: 10.1002/gepi.21794.

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