Author(s): Olivieri EH, da Silva SD, Mendona FF, Urata YN, Vidal DO,
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Abstract Head and neck squamous cell carcinoma (HNSCC) is associated with environmental factors, especially tobacco and alcohol consumption. Most of the carcinogens present in tobacco smoke are converted into DNA-reactive metabolites by cytochrome P450 (CYPs) enzymes and detoxification of these substances is performed by glutathione S-transferases (GSTs). It has been suggested that genetic alterations, such as polymorphisms, play an important role in tumorigenesis and HNSCC progression. The aim of this study was to investigate CYP1A1, CYP1A2, CYP2E1, GSTM1, and GSTT1 polymorphisms as risk factors in HNSCC and their association with clinicopathologic data. The patients comprised 153 individuals with HNSCC (cases) and 145 with no current or previous diagnosis of cancer (controls). Genotyping of the single nucleotide polymorphisms (SNPs) of the CYP1A1, CYP1A2, and CYP2E1 genes was performed by PCR-RFLP and the GSTM1 and GSTT1 copy number polymorphisms (CNPs) were analyzed by PCR-multiplex. As expected, a significant difference was detected for tobacco and alcohol consumption between cases and controls (P<0.001). It was observed that the CYP1A2*1D (OR=16.24) variant and GSTM1 null alleles (OR=0.02) confer increased risk of HNSCC development (P<0.001). In addition, head and neck cancer alcohol consumers were more frequently associated with the CYP2E1*5B variant allele than control alcohol users (P<0.0001, OR=190.6). The CYP1A2*1C polymorphism was associated with tumor recurrence (log-rank test, P=0.0161). The CYP2E1*5B and GSTM1 null alleles were significantly associated with advanced clinical stages (T3+T4; P=0.022 and P=0.028, respectively). Overall, the findings suggested that the genetic polymorphisms studied are predictors of risk and are also associated with tumor recurrence, since they are important for determining the parameters associated with tumor progression and poor outcomes in HNSCC.
This article was published in Oral Oncol
and referenced in Journal of Theoretical and Computational Science