Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA.
Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia.
Nat Genet. 2018 Jul;50(7):968-978. doi: 10.1038/s41588-018-0132-x. Epub 2018 Jun 18.
The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.
在全基因组关联研究中鉴定的乳腺癌风险变异仅能解释家族相对风险的一小部分，而与这些关联相关的基因在很大程度上仍然未知。为了确定新的风险位点和可能的因果基因，我们进行了一项转录组全基因组关联研究，评估了在 122977 例欧洲裔乳腺癌病例和 105974 例对照中，遗传预测的基因表达与乳腺癌风险的关联。我们使用来自基因-组织表达项目的数据来建立预测乳腺组织中基因表达的遗传模型，并使用癌症基因组图谱的数据来评估模型性能。在所评估的 8597 个基因中，有 48 个在经过 Bonferroni 校正的 P 值 < 5.82×10 时达到显著关联，其中包括 14 个在乳腺癌中尚未报道过的基因座的基因。我们沉默了 13 个基因，并发现其中 11 个基因对细胞增殖和/或集落形成效率有影响。我们的研究为乳腺癌遗传学和生物学提供了新的见解。
