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DOI: 10.4103/2278-330X.179701
Clinical implications of cytosine deletion of exon 5 of P53 gene in non small cell lung cancer patients
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Abstract
Aim: Lung cancer is considered to be the most common cancer in the world. In humans, about 50% or more cancers have a mutated tumor suppressor p53 gene thereby resulting in accumulation of p53 protein and losing its function to activate the target genes that regulate the cell cycle and apoptosis. Extensive research conducted in murine cancer models with activated p53, loss of p53, or p53 missense mutations have facilitated researchers to understand the role of this key protein. Our study was aimed to evaluate the frequency of cytosine deletion in nonsmall cell lung cancer (NSCLC) patients. Methods: One hundred NSCLC patients were genotyped for P53 (exon5, codon168) cytosine deletion leading to loss of its function and activate the target genes by allele-specific polymerase chain reaction. The P53 cytosine deletion was correlated with all the clinicopathological parameters of the patients. Results and Analysis: 59% cases were carrying P53 cytosine deletion. Similarly, the significantly higher incidence of cytosine deletion was reported in current smokers (75%) in comparison to exsmoker and nonsmoker. Significantly higher frequency of cytosine deletion was reported in adenocarcinoma (68.08%) than squamous cell carcinoma (52.83%). Also, a significant difference was reported between p53 cytosine deletion and metastasis (64.28%). Further, the majority of the cases assessed for response carrying P53 cytosine deletion were found to show faster disease progression. Conclusion: The data suggests that there is a significant association of the P53 exon 5 deletion of cytosine in codon 168 with metastasis and staging of the disease.
Key words
Nonsmall cell lung cancer - adeno-carcinoma - squamous cell carcinoma - allele specific oligonucleotide - P53 (exon5,codon168) cytosine deletionPublication History
Article published online:
30 December 2020
© 2016. MedIntel Services Pvt Ltd. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
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