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卵巢癌患者生存的基因集分析提示大环内酯结合和细胞内信号基因的作用。

Gene set analysis of survival following ovarian cancer implicates macrolide binding and intracellular signaling genes.

机构信息

Departments of Health Sciences Research, Mayo Clinic, Rochester, Minnesota 55905, USA.

出版信息

Cancer Epidemiol Biomarkers Prev. 2012 Mar;21(3):529-36. doi: 10.1158/1055-9965.EPI-11-0741. Epub 2012 Feb 2.

Abstract

BACKGROUND

Genome-wide association studies (GWAS) for epithelial ovarian cancer (EOC), the most lethal gynecologic malignancy, have identified novel susceptibility loci. GWAS for survival after EOC have had more limited success. The association of each single-nucleotide polymorphism (SNP) individually may not be well suited to detect small effects of multiple SNPs, such as those operating within the same biologic pathway. Gene set analysis (GSA) overcomes this limitation by assessing overall evidence for association of a phenotype with all measured variation in a set of genes.

METHODS

To determine gene sets associated with EOC overall survival, we conducted GSA using data from two large GWAS (N cases = 2,813, N deaths = 1,116), with a novel Principal Component-Gamma GSA method. Analysis was completed for all cases and then separately for high-grade serous histologic subtype.

RESULTS

Analysis of the high-grade serous subjects resulted in 43 gene sets with P < 0.005 (1.7%); of these, 21 gene sets had P < 0.10 in both GWAS, including intracellular signaling pathway (P = 7.3 × 10(-5)) and macrolide binding (P = 6.2 × 10(-4)) gene sets. The top gene sets in analysis of all cases were meiotic mismatch repair (P = 6.3 × 10(-4)) and macrolide binding (P = 1.0 × 10(-3)). Of 18 gene sets with P < 0.005 (0.7%), eight had P < 0.10 in both GWAS.

CONCLUSION

This research detected novel gene sets associated with EOC survival.

IMPACT

Novel gene sets associated with EOC survival might lead to new insights and avenues for development of novel therapies for EOC and pharmacogenomic studies.

摘要

背景

全基因组关联研究(GWAS)已鉴定出新型上皮性卵巢癌(EOC)易感性基因座,EOC 是最致命的妇科恶性肿瘤。但 GWAS 对 EOC 患者生存的研究结果较为有限。每个单核苷酸多态性(SNP)的关联可能并不适合检测多个 SNP 的微小效应,例如在同一生物学途径中发挥作用的 SNP。基因集分析(GSA)通过评估表型与一组基因中所有测量变异之间关联的总体证据来克服这一局限性。

方法

为了确定与 EOC 总体生存相关的基因集,我们使用来自两项大型 GWAS 的数据(病例数=2813,死亡数=1116),使用新型主成分-γ GSA 方法进行 GSA。分析针对所有病例进行,然后针对高级别浆液性组织学亚型分别进行。

结果

高级别浆液性受试者的分析产生了 43 个 P<0.005(1.7%)的基因集;其中,21 个基因集在两项 GWAS 中 P<0.10,包括细胞内信号通路(P=7.3×10(-5)) 和大环内酯结合(P=6.2×10(-4)) 基因集。所有病例分析中排名最高的基因集是减数分裂错配修复(P=6.3×10(-4)) 和大环内酯结合(P=1.0×10(-3))。在 P<0.005(0.7%)的 18 个基因集中,有 8 个基因集在两项 GWAS 中 P<0.10。

结论

本研究检测到与 EOC 生存相关的新基因集。

影响

与 EOC 生存相关的新基因集可能为 EOC 生存和药物基因组学研究的新型治疗方法提供新的见解和途径。

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