Abstract

ObjectiveThe carcinogenesis role of PARP1 in lung cancer is still not clear. Analysis at allelic levels cannot fully explain the function of PARP1 on lung cancer. Our study aims to further explore the relation between PARP1 haplotypes and lung cancer.Materials and methodsDNA and RNA were extracted from non-small cell lung cancer (NSCLC) tumor and adjacent normal fresh frozen tissue. Five PARP1-SNPs were genotyped and PARP1-specific SNPs were imputed using IMPUTE and SHAPEIT software. The SNPs were subjected to allelic, haplotype and SNP-SNP interaction analyses. Correlation between SNPs and mRNA/protein expressions were performed.ResultsSNP imputation inferred the ungenotyped SNPs and increased the power for association analysis. Tumor tissue samples are more likely to carry rs1805414 (OR = 1.85; 95% CI: 1.12–3.06; P-value: 0.017) and rs1805404 (OR = 2.74; 95%CI 1.19–6.32; P-value: 0.015) compared to normal tissues. Our study is the first study to show that haplotypes comprising of 5 SNPs on PARP1 (rs1136410, rs3219073, rs1805414, rs1805404, rs1805415) is able to differentiate the NSCLC tumor from normal tissues. Interaction between rs3219073, rs1805415, and rs1805414 were significantly associated with the NSCLC tumor with OR ranging from 3.61–6.75; 95%CI from 1.82 to 19.9; P-value<0.001.ConclusionPARP1 haplotypes may serve as a better predictor in lung cancer development and prognosis compared to single alleles.

Highlights

  • Lung cancer patients have the highest mortality rate among all cancer patients [1]

  • Interaction between rs3219073, rs1805415, and rs1805414 were significantly associated with the Non-small cell lung cancer (NSCLC) tumor with OR ranging from 3.61–6.75; 95%CI from 1.82 to 19.9; P-value

  • Poly (ADP-ribose) polymerase 1 (PARP1) haplotypes may serve as a better predictor in lung cancer development and prognosis compared to single alleles

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Summary

Introduction

Lung cancer patients have the highest mortality rate among all cancer patients [1]. In 2020, there would be around 228,820 new cases of lung cancer, and 135,720 deaths from lung cancer in the United States [2]. The five-year survival rate of lung cancer is around 56% for early-stage cases [4]. Only 16% of lung cancer patients can be detected at an early stage [4]. While multiple known environmental factors are associated with lung cancer [7], genetic mutations have been shown to have important roles. Genetic variations in genes like the TP53, EGFR, and KRAS have been identified and are currently used as biomarkers in clinical practice, but are only effective for selected lung cancer patients [8,9,10,11,12]. Unexplored gene mutations could help explain the poor prognosis of lung cancer [13], and further the treatment effectiveness for specific subtypes of lung cancer [14]. The heterogeneity and complexity of the lung cancer disease require more efforts in investigating the potential role of novel genes that are associated with lung cancer development

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