scholarly journals Identification of Significant Genes and Therapeutic Agents for Breast Cancer by Integrated Bioinformatics

2021 ◽  
Author(s):  
Xiao Sun ◽  
Zhenzhen Luo ◽  
Liuyun Gong ◽  
Xinyue Tan ◽  
Jie Chen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Association Study ◽  
Gene Expression Profile ◽  
Small Molecule ◽  
Expression Profile ◽  
Genome Wide Association Study ◽  
Therapeutic Agents ◽  
Genome Wide Association ◽  
Genome Wide

Abstract Background: Breast cancer is the most commonly diagnosed malignancy in women; thus, more cancer prevention research is urgently needed. The aim of this study was to predict potential therapeutic agents for breast cancer and determine their molecular mechanisms using integrated bioinformatics.Methods: Summary data from a large genome-wide association study of breast cancer was derived from the UK Biobank. The gene expression profile of breast cancer was from the Oncomine database. We performed a network-wide association study and gene set enrichment analysis to identify the significant genes in breast cancer. Then we performed Gene Ontology analysis using the STRING database and conducted Kyoto Encyclopedia of Genes and Genomes pathway analysis using Cytoscape software. We verified our results using the Gene Expression Profile Interactive Analysis, PROgeneV2, and Human Protein Atlas databases. Connectivity map analysis was used to identify small molecule compounds that are potential therapeutic agents for breast cancer.Results: We identified 10 significant genes in breast cancer based on the gene expression profile and genome-wide association study. A total of 65 small molecule compounds were found to be potential therapeutic agents for breast cancer.Conclusion: Combined analyses of network-wide association studies, gene expression profiles, and drug databases are helpful for identifying potential therapeutic agents for diseases. This method is a new paradigm that can guide future research directions.

scholarly journals A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer

2007 ◽  
Vol 39 (7) ◽  
pp. 870-874 ◽  
Author(s):  
David J Hunter ◽  
Peter Kraft ◽  
Kevin B Jacobs ◽  
David G Cox ◽  
Meredith Yeager ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Postmenopausal Breast Cancer ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome

scholarly journals A loop-counting method for covariate-corrected low-rank biclustering of gene-expression and genome-wide association study data

2018 ◽  
Vol 14 (5) ◽  
pp. e1006105 ◽  
Author(s):  
Aaditya V. Rangan ◽  
Caroline C. McGrouther ◽  
John Kelsoe ◽  
Nicholas Schork ◽  
Eli Stahl ◽  
...  
Keyword(s):  
Gene Expression ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Study Data ◽  
Genome Wide Association ◽  
Low Rank ◽  
Counting Method ◽  
Genome Wide

scholarly journals A Pilot Genome-wide Association Study of Breast Cancer Susceptibility Loci in Indonesia

2015 ◽  
Vol 16 (6) ◽  
pp. 2231-2235 ◽  
Author(s):  
Samuel J Haryono ◽  
I Gusti Bagus Datasena ◽  
Wahyu Budi Santosa ◽  
Raymond Mulyarahardja ◽  
Kartika Sari
Keyword(s):  
Breast Cancer ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Cancer Susceptibility ◽  
Breast Cancer Susceptibility ◽  
Genome Wide Association ◽  
Susceptibility Loci ◽  
Genome Wide

scholarly journals Common Susceptibility Loci for Male Breast Cancer

2020 ◽  
Author(s):  
Sarah Maguire ◽  
Eleni Perraki ◽  
Katarzyna Tomczyk ◽  
Michael E Jones ◽  
Olivia Fletcher ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Association Study ◽  
Genetic Correlation ◽  
Male Breast Cancer ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Susceptibility Loci ◽  
Single Nucleotide ◽  
Genome Wide

Abstract Background The etiology of male breast cancer (MBC) is poorly understood. In particular, the extent to which the genetic basis of MBC differs from female breast cancer (FBC) is unknown. A previous genome-wide association study of MBC identified 2 predisposition loci for the disease, both of which were also associated with risk of FBC. Methods We performed genome-wide single nucleotide polymorphism genotyping of European ancestry MBC case subjects and controls in 3 stages. Associations between directly genotyped and imputed single nucleotide polymorphisms with MBC were assessed using fixed-effects meta-analysis of 1380 cases and 3620 controls. Replication genotyping of 810 cases and 1026 controls was used to validate variants with P values less than 1 × 10–06. Genetic correlation with FBC was evaluated using linkage disequilibrium score regression, by comprehensively examining the associations of published FBC risk loci with risk of MBC and by assessing associations between a FBC polygenic risk score and MBC. All statistical tests were 2-sided. Results The genome-wide association study identified 3 novel MBC susceptibility loci that attained genome-wide statistical significance (P < 5 × 10–08). Genetic correlation analysis revealed a strong shared genetic basis with estrogen receptor–positive FBC. Men in the top quintile of genetic risk had a fourfold increased risk of breast cancer relative to those in the bottom quintile (odds ratio = 3.86, 95% confidence interval = 3.07 to 4.87, P = 2.08 × 10–30). Conclusions These findings advance our understanding of the genetic basis of MBC, providing support for an overlapping genetic etiology with FBC and identifying a fourfold high-risk group of susceptible men.

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