Division of Biostatistics and Human Genetics Center, School of Public Health, University of Texas Health Science Center, Houston, Texas, United States of America.
PLoS One. 2012;7(10):e46887. doi: 10.1371/journal.pone.0046887. Epub 2012 Oct 4.
Pancreatic cancer is the fourth leading cause of cancer death in the U.S. and the etiology of this highly lethal disease has not been well defined. To identify genetic susceptibility factors for pancreatic cancer, we conducted pathway analysis of genome-wide association study (GWAS) data in 3,141 pancreatic cancer patients and 3,367 controls with European ancestry.
Using the gene set ridge regression in association studies (GRASS) method, we analyzed 197 pathways identified from the Kyoto Encyclopedia of Genes and Genomes database. We used the logistic kernel machine (LKM) test to identify major contributing genes to each pathway. We conducted functional enrichment analysis of the most significant genes (P<0.01) using the Database for Annotation, Visualization, and Integrated Discovery (DAVID).
Two pathways were significantly associated with risk of pancreatic cancer after adjusting for multiple comparisons (P<0.00025) and in replication testing: neuroactive ligand-receptor interaction, (Ps<0.00002), and the olfactory transduction pathway (P = 0.0001). LKM test identified four genes that were significantly associated with risk of pancreatic cancer after Bonferroni correction (P<1×10(-5)): ABO, HNF1A, OR13C4, and SHH. Functional enrichment analysis using DAVID consistently found the G protein-coupled receptor signaling pathway (including both neuroactive ligand-receptor interaction and olfactory transduction pathways) to be the most significant pathway for pancreatic cancer risk in this study population.
These novel findings provide new perspectives on genetic susceptibility to and molecular mechanisms of pancreatic cancer.
胰腺癌是美国第四大癌症死因，但其病因尚未明确。为了确定胰腺癌的遗传易感性因素，我们对 3141 名胰腺癌患者和 3367 名具有欧洲血统的对照者的全基因组关联研究 (GWAS) 数据进行了途径分析。
我们使用关联研究中的基因集脊回归 (GRASS) 方法，分析了从京都基因与基因组百科全书数据库中确定的 197 个途径。我们使用逻辑核机器 (LKM) 测试来识别每个途径的主要贡献基因。我们使用数据库注释、可视化和综合发现 (DAVID) 对最显著基因 (P<0.01) 进行了功能富集分析。
在调整了多次比较 (P<0.00025) 和复制测试后，有两个途径与胰腺癌风险显著相关：神经活性配体-受体相互作用 (Ps<0.00002) 和嗅觉转导途径 (P = 0.0001)。LKM 测试确定了四个在 Bonferroni 校正后与胰腺癌风险显著相关的基因 (P<1×10(-5))：ABO、HNF1A、OR13C4 和 SHH。使用 DAVID 进行的功能富集分析一致发现 G 蛋白偶联受体信号通路 (包括神经活性配体-受体相互作用和嗅觉转导途径) 是本研究人群中胰腺癌风险的最显著途径。
这些新发现为胰腺癌的遗传易感性和分子机制提供了新的视角。
