Association study of NAT2 gene polymorphism and risk of oral cancer in Southern Punjab, Pakistan.

OBJECTIVE: To investigate the single nucleotide polymorphic variations of N-acetyltransferase 2, phase-II metabolising enzyme, and associated risk factors for oral cancer. METHODS: The case-control study was conducted from November 2017 to April 2018 after approval from the Institute of Molecular Biology and Biotechnology, Bahauddin Zakariya University, Multan, Pakistan, and comprised oral cancer patients and healthy controls. Single nucleotide polymorphism of the N-acetyltransferase 2 gene associated with oral cancer was analysed. Factors assessed using tetra-primer amplification refractory mutation system polymerase chain reaction included age, smoking, naswar, betel leaves and nuts. RESULTS: Of the 201 subjects, 94(47%) were patients and 107(53%) were controls, while 108(54%) were aged 10-30 years. Single nucleotide polymorphism rs1208 of N-acetyltransferase 2 gene was primarily A803G and Lys268Arg, with allelic frequency of G/A. Age range 51-70 was significantly (p=0.00001) associated with the prevalence of oral cancer in terms of genotypic relationship with A803G. Substantial allelic association was found between the gene and oral cancer (p=0.006895). Smoking increased the cacner risk 7-fold (odds ratio: 7.0). CONCLUSIONS: The genetic variant of N-acetyltransferase 2 rs1208 was found to be significantly associated with oral cancer progression and development of associated risk factors.

Systems-level differential gene expression analysis reveals new genetic variants of oral cancer.

Oral cancer (OC) ranked as eleventh malignancy worldwide, with the increasing incidence among young patients. Limited understanding of complications in cancer progression, its development system, and their interactions are major restrictions towards the progress of optimal and effective treatment strategies. The system-level approach has been designed to explore genetic complexity of the disease and to identify novel oral cancer related genes to detect genomic alterations at molecular level, through cDNA differential analysis. We analyzed 21 oral cancer-related cDNA datasets and listed 30 differentially expressed genes (DEGs). Among 30, we found 6 significant DEGs including CYP1A1, CYP1B1, ADCY2, C7, SERPINB5, and ANAPC13 and studied their functional role in OC. Our genomic and interactive analysis showed significant enrichment of xenobiotics metabolism, p53 signaling pathway and microRNA pathways, towards OC progression and development. We used human proteomic data for post-translational modifications to interpret disease mutations and inter-individual genetic variations. The mutational analysis revealed the sequence predicted disordered region of 14%, 12.5%, 10.5% for ADCY2, CYP1B1, and C7 respectively. The MiRNA target prediction showed functional molecular annotation including specific miRNA-targets hsa-miR-4282, hsa-miR-2052, hsa-miR-216a-3p, for CYP1B1, C7, and ADCY2 respectively associated with oral cancer. We constructed the system level network and found important gene signatures. The drug-gene interaction of OC source genes with seven FDA approved OC drugs help to design or identify new drug target or establishing novel biomedical linkages regarding disease pathophysiology. This investigation demonstrates the importance of system genetics for identifying 6 OC genes (CYP1A1, CYP1B1, ADCY2, C7, SERPINB5, and ANAPC13) as potential drugs targets. Our integrative network-based system-level approach would help to find the genetic variants of OC that can accelerate drug discovery outcomes to develop a better understanding regarding treatment strategies for many cancer types.