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Original Articles

Functional Polymorphisms of JWA Gene are Associated with Risk of Bladder Cancer

, , , , , , , , & show all
Pages 876-884 | Published online: 04 May 2007
 

Abstract

The JWA gene is a novel cell differentiation-related gene thought to be a responsive gene in response to DNA damage and repair induced by environmental stressors. Recently, a novel single nucleotide polymorphism (SNP) was identified in the promoter of the JWA gene (−76G→C) that may alter the transcription activity and thus play a role in increased risk of bladder cancer. Further, studies were conducted to screen for more novel variants in the JWA exons by using PCR-SSCP (polymerase chain reaction–single-strand conformation polymorphism) followed by PCR-RFLP (PCR restriction fragment length polymorphism) methods. Finally, the functional relevance of the newly identified genetic variants in a hospital-based case-control study of 215 bladder cancer patients and 250 cancer-free controls was evaluated. In addition to the −76G→C polymorphism, another novel SNP (454C→A in exon2 and 723T→G in exon 3) of JWA was identified. The −76G→C allele and genotype frequencies were found to vary in different ethnic groups. The −76C allele and 454A allele were both associated with significantly increased risk of bladder cancer. In contrast, the 723GG genotype was associated with a decreased risk of bladder cancer. Furthermore, −76C and 454A together increased the risk of bladder caner using haplotype and stratification analysis. In conclusion, the three novel functional genetic polymorphisms of JWA gene, −76G→C, 454C→A, and 723T→G, appear to contribute to the etiology of bladder cancer.

Chunping Li and Yujie Zhu contributed equally to this work.

This study was supported by the National Natural Science Foundation of China (30170812, 30471430, 30271105 and 30571583), Doctoral Program Funding of National Education Ministry (20040312008), and National Key Basic Research and Development Project (973) (2002CB512900). We thank Fengye Wang and Jianfeng Shao for their assistance in recruiting the subjects, and we are grateful to all the study participants. We also thank Dr. Renzheng Zhao for her technical and laboratory support, Dr. Feng Chen for his statistical support, Dr. Hongbing Shen for scientific inputs, Dr. Zuofeng Zhang of University of California at Los Angeles, and Dr. Ruiwen Zhang of University of Alabama at Birmingham for scientific editing.

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