A multi-ethnic breast cancer case–control study in New Zealand: evidence of differential risk patterns

Background Breast cancer has a major disease burden in the female population, and it is a highly genome-associated human disease. However, in genetic studies of complex diseases, modern geneticists face challenges in detecting interactions among loci. Objective This study aimed to investigate whether variations of single-nucleotide polymorphisms (SNPs) are associated with histopathological tumor characteristics in breast cancer patients. Methods A hybrid Taguchi-genetic algorithm (HTGA) was proposed to identify the high-order SNP barcodes in a breast cancer case-control study. A Taguchi method was used to enhance a genetic algorithm (GA) for identifying high-order SNP barcodes. The Taguchi method was integrated into the GA after the crossover operations in order to optimize the generated offspring systematically for enhancing the GA search ability. Results The proposed HTGA effectively converged to a promising region within the problem space and provided excellent SNP barcode identification. Regression analysis was used to validate the association between breast cancer and the identified high-order SNP barcodes. The maximum OR was less than 1 (range 0.870-0.755) for two- to seven-order SNP barcodes. Conclusions We systematically evaluated the interaction effects of 26 SNPs within growth factor–related genes for breast carcinogenesis pathways. The HTGA could successfully identify relevant high-order SNP barcodes by evaluating the differences between cases and controls. The validation results showed that the HTGA can provide better fitness values as compared with other methods for the identification of high-order SNP barcodes using breast cancer case-control data sets.

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The importance of replication in gene-gene interaction studies: multifactor dimensionality reduction applied to a two-stage breast cancer case-control study

Carcinogenesis ◽

10.1093/carcin/bgn120 ◽

2008 ◽

Vol 29 (6) ◽

pp. 1215-1218 ◽

Cited By ~ 16

Author(s):

R. L. Milne ◽

R. Fagerholm ◽

H. Nevanlinna ◽

J. Benitez

Keyword(s):

Breast Cancer ◽

Dimensionality Reduction ◽

Multifactor Dimensionality Reduction ◽

Case Control Study ◽

Breast Cancer Case ◽

Gene Interaction ◽

Case Control ◽

Cancer Case ◽

Two Stage ◽

Control Study

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Sex hormone measurements using mass spectrometry and sensitive extraction radioimmunoassay and risk of estrogen receptor negative and positive breast cancer: Case control study in UK Collaborative Cancer Trial of Ovarian Cancer Screening (UKCTOCS)

Steroids ◽

10.1016/j.steroids.2016.04.003 ◽

2016 ◽

Vol 110 ◽

pp. 62-69 ◽

Cited By ~ 7

Author(s):

Evangelia-Ourania Fourkala ◽

Oleg Blyuss ◽

Helen Field ◽

Richard Gunu ◽

Andy Ryan ◽

...

Keyword(s):

Breast Cancer ◽

Case Control Study ◽

Breast Cancer Case ◽

Case Control ◽

Cancer Case ◽

Ovarian Cancer Screening ◽

Cancer Trial ◽

Estrogen Receptor Negative ◽

Control Study ◽

Positive Breast Cancer

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Identification of High-Order Single-Nucleotide Polymorphism Barcodes in Breast Cancer Using a Hybrid Taguchi-Genetic Algorithm: Case-Control Study (Preprint)

10.2196/preprints.16886 ◽

2019 ◽

Author(s):

Li-Yeh Chuang ◽

Cheng-San Yang ◽

Huai-Shuo Yang ◽

Cheng-Hong Yang

Keyword(s):

Breast Cancer ◽

Genetic Algorithm ◽

Taguchi Method ◽

Case Control Study ◽

Breast Cancer Case ◽

Case Control ◽

High Order ◽

Cancer Case ◽

Single Nucleotide ◽

Control Study

BACKGROUND Breast cancer has a major disease burden in the female population, and it is a highly genome-associated human disease. However, in genetic studies of complex diseases, modern geneticists face challenges in detecting interactions among loci. OBJECTIVE This study aimed to investigate whether variations of single-nucleotide polymorphisms (SNPs) are associated with histopathological tumor characteristics in breast cancer patients. METHODS A hybrid Taguchi-genetic algorithm (HTGA) was proposed to identify the high-order SNP barcodes in a breast cancer case-control study. A Taguchi method was used to enhance a genetic algorithm (GA) for identifying high-order SNP barcodes. The Taguchi method was integrated into the GA after the crossover operations in order to optimize the generated offspring systematically for enhancing the GA search ability. RESULTS The proposed HTGA effectively converged to a promising region within the problem space and provided excellent SNP barcode identification. Regression analysis was used to validate the association between breast cancer and the identified high-order SNP barcodes. The maximum OR was less than 1 (range 0.870-0.755) for two- to seven-order SNP barcodes. CONCLUSIONS We systematically evaluated the interaction effects of 26 SNPs within growth factor–related genes for breast carcinogenesis pathways. The HTGA could successfully identify relevant high-order SNP barcodes by evaluating the differences between cases and controls. The validation results showed that the HTGA can provide better fitness values as compared with other methods for the identification of high-order SNP barcodes using breast cancer case-control data sets.

Download Full-text