Genetic variation in the Hippo pathway and breast cancer risk in women of African ancestry.
Shengfeng WangDezheng HuoTemidayo O OgundiranOladosu OjengbedeWei ZhengKatherine L NathansonBarbara NemesureStefan AmbsOlufunmilayo I OlopadeYonglan ZhengPublished in: Molecular carcinogenesis (2018)
Gene expression changes within the Hippo pathway were found to be associated with large tumor size and metastasis in breast cancer. The combined effect of genetic variants in genes of this pathway may have a causal role in breast cancer development. We examined 7086 SNPs that were not highly correlated (r2 < 0.8) in 35 Hippo pathway genes using data from the genome-wide association study of breast cancer from the Root Consortium, which includes 3686 participants of African ancestry from Nigeria, United States of America, and Barbados: 1657 cases (403 estrogen receptor-positive [ER+], 374 ER-) and 2029 controls. Gene-level analyses were conducted using improved AdaJoint test for large-scale genetic association studies adjusting for age, study site and the first four eigenvectors from the principal component analysis. SNP-level analyses were conducted with logistic regression. The Hippo pathway was significantly associated with risk of ER+ breast cancer (pathway-level P = 0.019), with WWC1 (Padj = 0.04) being the leading gene. The pathway-level significance was lost without WWC1 (P = 0.12). rs147106204 in the WWC1 gene was the most statistically significant SNP after gene-level adjustment for multiple comparisons (OR = 0.53, 95%CI = 0.41-0.70, Padj = 0.025). We found evidence of an association between genetic variations in the Hippo pathway and ER+ breast cancer. Moreover, WWC1 was identified as the most important genetic susceptibility locus highlighting the importance of genetic epidemiology studies of breast cancer in understudied populations.
Keyphrases
- genome wide
- estrogen receptor
- breast cancer risk
- gene expression
- copy number
- dna methylation
- genome wide association study
- genome wide identification
- pregnant women
- breast cancer cells
- risk factors
- insulin resistance
- type diabetes
- artificial intelligence
- skeletal muscle
- adipose tissue
- endoplasmic reticulum
- transcription factor
- young adults
- genome wide analysis
- electronic health record
- big data