Abstract 4720: Genome-wide copy number variation and breast cancer risk: Preliminary report

2010 ◽  
Author(s):  
Kyoung-Mu Lee ◽  
Miey Park ◽  
Sang-Hoon Moon ◽  
Hyung-Chol Kim ◽  
Ji-Young Lee ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Copy Number Variation ◽  
Copy Number ◽  
Preliminary Report ◽  
Genome Wide ◽  
Number Variation

Abstract 2616: Association ofUGT2B17gene copy number variation with breast cancer risk: The Nashville Breast Health Study

2012 ◽  
Author(s):  
Guoliang Li ◽  
Sandra L. Deming ◽  
Qiuyin Cai ◽  
Alecia M. Fair ◽  
Martha J. Shrubsole ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Copy Number Variation ◽  
Copy Number ◽  
Health Study ◽  
Breast Health ◽  
Number Variation

Genome-wide analysis of DNA copy number variation in breast cancer using DNA microarrays

10.1038/14385 ◽  
1999 ◽  
Vol 23 (S3) ◽  
pp. 69-69 ◽  
Author(s):  
Jonathan R. Pollack ◽  
Charles M. Perou ◽  
Therese Sorlie ◽  
Ash A. Alizadeh ◽  
Christian Rees ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Copy Number Variation ◽  
Copy Number ◽  
Dna Microarrays ◽  
Dna Copy Number ◽  
Genome Wide Analysis ◽  
Dna Copy Number Variation ◽  
Genome Wide ◽  
Number Variation

scholarly journals Genome-wide analysis of the role of copy-number variation in pancreatic cancer risk

2014 ◽  
Vol 5 ◽  
Author(s):  
Jason A. Willis ◽  
Semanti Mukherjee ◽  
Irene Orlow ◽  
Agnes Viale ◽  
Kenneth Offit ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Risk ◽  
Copy Number Variation ◽  
Copy Number ◽  
Genome Wide Analysis ◽  
Pancreatic Cancer Risk ◽  
Genome Wide ◽  
Number Variation

scholarly journals Genome-wide Analysis of Common Copy Number Variation and Epithelial Ovarian Cancer Risk

2019 ◽  
Vol 28 (7) ◽  
pp. 1117-1126 ◽  
Author(s):  
Brett M. Reid ◽  
Jennifer B. Permuth ◽  
Y. Ann Chen ◽  
Brooke L. Fridley ◽  
Edwin S. Iversen ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cancer Risk ◽  
Copy Number Variation ◽  
Epithelial Ovarian Cancer ◽  
Copy Number ◽  
Ovarian Cancer Risk ◽  
Genome Wide Analysis ◽  
Genome Wide ◽  
Number Variation

scholarly journals Pro-inflammatory cytokine polymorphisms and interactions with dietary alcohol and estrogen, risk factors for invasive breast cancer using a post genome-wide analysis for gene–gene and gene–lifestyle interaction

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Su Yon Jung ◽  
Jeanette C. Papp ◽  
Eric M. Sobel ◽  
Matteo Pellegrini ◽  
Herbert Yu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Visceral Obesity ◽  
Cumulative Exposure ◽  
Environment Interaction ◽  
Dependent Manner ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Reduction Methods

AbstractMolecular and genetic immune-related pathways connected to breast cancer and lifestyles in postmenopausal women are not fully characterized. In this study, we explored the role of pro-inflammatory cytokines such as C-reactive protein (CRP) and interleukin-6 (IL-6) in those pathways at the genome-wide level. With single-nucleotide polymorphisms (SNPs) in the biomarkers and lifestyles together, we further constructed risk profiles to improve predictability for breast cancer. Our earlier genome-wide association gene-environment interaction study used large cohort data from the Women’s Health Initiative Database for Genotypes and Phenotypes Study and identified 88 SNPs associated with CRP and IL-6. For this study, we added an additional 68 SNPs from previous GWA studies, and together with 48 selected lifestyles, evaluated for the association with breast cancer risk via a 2-stage multimodal random survival forest and generalized multifactor dimensionality reduction methods. Overall and in obesity strata (by body mass index, waist, waist-to-hip ratio, exercise, and dietary fat intake), we identified the most predictive genetic and lifestyle variables. Two SNPs (SALL1 rs10521222 and HLA-DQA1 rs9271608) and lifestyles, including alcohol intake, lifetime cumulative exposure to estrogen, and overall and visceral obesity, are the most common and strongest predictive markers for breast cancer across the analyses. The risk profile that combined those variables presented their synergistic effect on the increased breast cancer risk in a gene–lifestyle dose-dependent manner. Our study may contribute to improved predictability for breast cancer and suggest potential interventions for the women with the risk genotypes and lifestyles to reduce their breast cancer risk.

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