Breast cancer-associated high-order SNP-SNP interaction of CXCL12/CXCR4-related genes by an improved multifactor dimensionality reduction (MDR-ER)

  • Authors:
    • Ou‑Yang Fu
    • Hsueh‑Wei Chang
    • Yu‑Da Lin
    • Li‑Yeh Chuang
    • Ming‑Feng Hou
    • Cheng‑Hong Yang
  • View Affiliations

  • Published online on: July 21, 2016     https://doi.org/10.3892/or.2016.4956
  • Pages: 1739-1747
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Abstract

In association studies, the combined effects of single nucleotide polymorphism (SNP)-SNP interactions and the problem of imbalanced data between cases and controls are frequently ignored. In the present study, we used an improved multifactor dimensionality reduction (MDR) approach namely MDR-ER to detect the high order SNP‑SNP interaction in an imbalanced breast cancer data set containing seven SNPs of chemokine CXCL12/CXCR4 pathway genes. Most individual SNPs were not significantly associated with breast cancer. After MDR‑ER analysis, six significant SNP‑SNP interaction models with seven genes (highest cross‑validation consistency, 10; classification error rates, 41.3‑21.0; and prediction error rates, 47.4‑55.3) were identified. CD4 and VEGFA genes were associated in a 2‑loci interaction model (classification error rate, 41.3; prediction error rate, 47.5; odds ratio (OR), 2.069; 95% bootstrap CI, 1.40‑2.90; P=1.71E‑04) and it also appeared in all the best 2‑7‑loci models. When the loci number increased, the classification error rates and P‑values decreased. The powers in 2‑7‑loci in all models were >0.9. The minimum classification error rate of the MDR‑ER‑generated model was shown with the 7‑loci interaction model (classification error rate, 21.0; OR=15.282; 95% bootstrap CI, 9.54‑23.87; P=4.03E‑31). In the epistasis network analysis, the overall effect with breast cancer susceptibility was identified and the SNP order of impact on breast cancer was identified as follows: CD4 = VEGFA > KITLG > CXCL12 > CCR7 = MMP2 > CXCR4. In conclusion, the MDR‑ER can effectively and correctly identify the best SNP‑SNP interaction models in an imbalanced data set for breast cancer cases.

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September-2016
Volume 36 Issue 3

Print ISSN: 1021-335X
Online ISSN:1791-2431

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Copy and paste a formatted citation
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Spandidos Publications style
Fu OY, Chang HW, Lin YD, Chuang LY, Hou MF and Yang CH: Breast cancer-associated high-order SNP-SNP interaction of CXCL12/CXCR4-related genes by an improved multifactor dimensionality reduction (MDR-ER). Oncol Rep 36: 1739-1747, 2016
APA
Fu, O., Chang, H., Lin, Y., Chuang, L., Hou, M., & Yang, C. (2016). Breast cancer-associated high-order SNP-SNP interaction of CXCL12/CXCR4-related genes by an improved multifactor dimensionality reduction (MDR-ER). Oncology Reports, 36, 1739-1747. https://doi.org/10.3892/or.2016.4956
MLA
Fu, O., Chang, H., Lin, Y., Chuang, L., Hou, M., Yang, C."Breast cancer-associated high-order SNP-SNP interaction of CXCL12/CXCR4-related genes by an improved multifactor dimensionality reduction (MDR-ER)". Oncology Reports 36.3 (2016): 1739-1747.
Chicago
Fu, O., Chang, H., Lin, Y., Chuang, L., Hou, M., Yang, C."Breast cancer-associated high-order SNP-SNP interaction of CXCL12/CXCR4-related genes by an improved multifactor dimensionality reduction (MDR-ER)". Oncology Reports 36, no. 3 (2016): 1739-1747. https://doi.org/10.3892/or.2016.4956