- 期刊
- OpenAccess
Novel Integrative Genomics Approach for Associating GWAS Information with Intrinsic Subtypes of Breast Cancer
並列摘要
Genome-wide association studies (GWAS) have achieved great success in identifying common variants associated with increased risk of developing breast cancer. However, GWAS do not typically provide information about the broader context in which genetic variants operate in different subtypes of breast cancer. The objective of this study was to determine whether genes containing single nucleotide polymorphisms (SNPs, herein called genetic variants) are associated with different subtypes of breast cancer. Additionally, we sought to identify gene regulator networks and biological pathways enriched for these genetic variants. Using supervised analysis, we identified 201 genes that were significantly associated with the six intrinsic subtypes of breast cancer. The results demonstrate that integrative genomics analysis is a powerful approach for linking GWAS information to distinct disease states and provide insights about the broader context in which genetic variants operate in different subtypes of breast cancer.
延伸閱讀
- Hicks, C., Kumar, R., Pannuti, A., Backus, K., Brown, A., Monico, J., & Miele, L. (2013). An Integrative Genomics Approach for Associating GWAS Information with Triple-Negative Breast Cancer. Cancer Informatics, (2013), 1-20. https://doi.org/10.4137/CIN.S10413
- Cerliani, M. B., & Richard, S. M. (2013). Polymorphism Analysis of Genes Involved in Xenobiotic Metabolism and Circadian Rhythm in Human Breast Cancer. International Journal of Advance in Medical Science, 1(4), 57-64. https://www.airitilibrary.com/Article/Detail?DocID=P20150529008-201311-201510130017-201510130017-57-64
- Chen, C. (2001). A study of genomic imprinting and DNA methylation in gynecological cancers [doctoral dissertation, The University of Hong Kong]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0029-1812201200007828
- Hicks, C., Koganti, T., Giri, S., Tekere, M., Ramani, R., Amorn, J. S., & Vijayakumar, S. (2014). Integrative Genomic Analysis for the Discovery of Biomarkers in Prostate Cancer. Biomarker Insights, 2014(), 39-51. https://doi.org/10.4137/BMI.S13729
- Ting, L. S. (2015). Identification of novel CSC predictive biomarkers in breast cancer: a systems biology approach [master's thesis, National Tsing Hua University]. Airiti Library. https://doi.org/10.6843/NTHU.2015.00562