Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/11721
Title: Frequencies of EGFR single nucleotide polymorphisms in non-small cell lung cancer patients and healthy individuals in the Republic of Serbia: a preliminary study
Authors: Obradović, Jasmina
Djordjević, Nataša
Tosic, Nataša
Mrdjanovic, Jasminka
Stanković, BIljana
Stanic, Jelena
Zarić, Bojan
Perin, Branislav
Pavlovic, Sonja
Jurišić, Vladimir
Issue Date: 2016
Abstract: © 2016, International Society of Oncology and BioMarkers (ISOBM). The purpose of this study was to determine the frequencies of EGFR −216G>T, −191C>A, and 181946C>T in Serbian non-small cell lung cancer (NSCLC) patients, as well as to compare it with healthy individuals, in order to assess their potential importance for lung cancer in Serbia. The study involved 56 NSCLC patients and 53 unrelated healthy volunteers, and genotyping was performed on DNA samples obtained from formalin-fixed paraffin-embedded lung tumor tissue and blood, respectively. This was the first time to show genotype frequencies of those single nucleotide polymorphisms for this study group from the territory of the Republic of Serbia. There was very strong evidence of association between age and death due to lung cancer (Pearson chi-square = 43.439, df = 2, p < 0,001), as well as between ever smoking and death due to lung cancer (Pearson chi-square = 31.727, df = 1, p < 0.001). When dominant genetic model (GG vs. GT+TT) was used for −216G>T, we have found significant association (p = 0.012) between −216GG genotype and NSCLC patients within smokers’ subgroup. So, carriers of −216GG genotype had higher risk (OR = 4.33, 95 % CI = 1.324–14.179) than noncarriers (GT and TT) for developing non-small cell lung cancer in our patients.
URI: https://scidar.kg.ac.rs/handle/123456789/11721
Type: article
DOI: 10.1007/s13277-016-4930-4
ISSN: 1010-4283
SCOPUS: 2-s2.0-84957550590
Appears in Collections:Faculty of Medical Sciences, Kragujevac
Institute for Information Technologies, Kragujevac

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