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Home > 정보광장 > ddPCR
Droplet Digital polymerase chain reaction

[ Title ]

- Germline copy number variations associated with breast cancer susceptibility in a Japanese population

[ Journal ]

- Tumor Biology

[ Author ]

- Y. Suehiro, T. Okada, N. Shikamoto, Y. B. Zhan, K. Sakai, N. Okayama, M. Nishioka, T. Furuya, A. Oga, S. Kawauchi, N. Maeda, M. Tamesa, Y. Nagashima, S. Yamamoto, M. Oka, Y. Hinoda and K. Sasaki

[ Year ]

- 2013

[ Volume ]

- 34

[ Pages ]

- 947-952

[ Abstract ]

- Although copy number variations (CNVs) are expected to affect various diseases, little is known about the association between CNVs and breast cancer susceptibility. Therefore, we investigated this relation. Array comparative genomic hybridization was performed to search for candidate CNVs related to breast cancer susceptibility. Subsequent quantitative real-time polymerase chain reaction was carried out for confirmation. We found seven CNV markers associated with breast cancer risk. The means of the relative copy numbers of patients with a history of breast cancer and women in the control group were 0.8 and 1.8 for Hs06535529_cn on 1p36.12 (P < 0.0001), 2.9 and 2.2 for Hs03103056_cn on 3q26.1 (P < 0.0001), 1.2 and 1.8 for Hs03899300_cn on 15q26.3 (P < 0.0001), 1.0 and 1.5 for Hs03908783_cn on 15q26.3 (P < 0.0001), and 1.1 and 1.7 for Hs03898338_cn on 15q26.3 (P < 0.0001), respectively. Interestingly, nine or more copies of Hs04093415_cn on 22q12.3 were found only in 8/193 (4.1 %) patients with a history of breast cancer and in none of the controls (P = 0.0081). Similarly, 12 or more copies of Hs040908898_cn on 22q12.3 were found only in 7/193 (3.6 %) patients with a history of breast cancer and in none of the controls (P = 0.016). A combination of two CNVs resulted in 80.3 % sensitivity, 80.6 % specificity, 82.4 % positive predictive value, and 78.3 % negative predictive value for the prediction of breast cancer susceptibility. These findings may lead to a new means of risk assessment for breast cancer. Confirmatory studies using independent data sets are needed to support our findings.

[ URL ]

- ://WOS:000316364500040