High-Resolution Melting Analysis for Mutation Screening of RGSL1, RGS16, and RGS8 in Breast Cancer

被引:12
|
作者
Wiechec, Emilia [1 ,2 ]
Wiuf, Carsten [3 ]
Overgaard, Jens [2 ]
Hansen, Lise Lotte [1 ]
机构
[1] Univ Aarhus, Inst Human Genet, DK-8000 Aarhus C, Denmark
[2] Aarhus Univ Hosp, Dept Expt Clin Oncol, DK-8000 Aarhus C, Denmark
[3] Univ Aarhus, BiRC, DK-8000 Aarhus C, Denmark
关键词
PROTEIN SIGNALING RGS; PROSTATE-CANCER; GENE; RISK; DNA; REGULATOR; CHROMOSOME-1; POLYMORPHISM; THROUGHPUT; RECEPTORS;
D O I
10.1158/1055-9965.EPI-10-0514
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background: Identification of specific mutation targets in cancer may lead to discovery of the genes modulating cancer susceptibility and/or prognosis. The RGSL1, RGS16, and RGS8 genes within the 1q25.3 region belong to the novel family of regulators of G protein signaling (RGS) genes, which increase the GTPase activity of the G alpha subunit to attenuate signaling from the G protein-coupled receptor. We evaluated the use of high-resolution melting (HRM) to screen for mutations in the genes of interest and assess their clinical significance. Methods: The HRM analysis was used to screen 32 coding exons of RGSL1, RGS16, and RGS8 in tumors from 200 breast cancer patients. All sequence variants detected by HRM resulted in abnormal shape of the melting curves. The identified mutations and known single nucleotide polymorphisms (SNP) were subsequently confirmed by sequencing, and distribution of the SNP genotypes was determined by SNaPshot analysis. A case-control analysis of genotype frequencies was carried out. Results: We identified three tumor specific missense mutations in RGSL1 (ex6 c.664 G>A (Val222Ile), ex13 c.2262 C>G (Asp754Glu), and ex13 c.2316 C>T (Ser772Leu) in three different breast cancer patients. In addition, a total of seven known SNPs were identified in this study. Genotype distributions were not significantly different between breast cancer patients and controls. Conclusions and Impact: Identification of novel mutations within RGSL1 provides a new insight into the pathophysiology of breast cancer. Moreover, the HRM analysis represents a reliable and highly sensitive method for mutation scanning of multiple exons. Cancer Epidemiol Biomarkers Prev; 20(2); 397-407. (C)2010 AACR.
引用
收藏
页码:397 / 407
页数:11
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