Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/98485
標題: 建立雌激素及萘醌類代謝物蛋白質胼合物為篩選乳癌高風險族群之生物指標模式
Establishment of a prediction model of breast cancer using estrogen and naphthalene quinone-derived protein adducts as biomarkers
作者: 許碩元
Shuo-Yuan Hsu
關鍵字: 雌激素
萘醌類代謝物蛋白質胼合物
estrogen
naphthalene quinone-derived protein adducts
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摘要: 本研究目的是為建立雌性激素及萘之醌類代謝物所形成血清蛋白胼合物(Albumin adduct, Alb adduct)之背景值為生物指標(biomarker) ,探討其與乳癌風險因子間之相關性,其中雌性激素之代謝物為17β-雌二醇-2,3-醌類代謝物 (E2-2,3-Q) 和 17β-雌二醇-3,4-醌類代謝物(E2-3,4-Q),萘之醌類代謝物包括1,2-naphthoquinone (1,2-NPQ)及1,4-naphthoquinone (1,4-NPQ) 。 這類代謝物所形成血清蛋白胼合物可作為分析正常人血清蛋白胼合物及乳癌病人胼合物背景值之相關性,並建立篩選模式,作為乳癌風險之預測指標。 本研究首先推估(1)雌性激素之醌類活性代謝物包括E2-2,3-Quinone及E2-3,4-Quinone所形成之Alb adducts之背景值之比率;(2)萘之醌類代謝物包括1,2-naphthoquinone及1,4-naphthoquinone所形成之Alb adducts之比率。(3) 雌性激素之醌類活性代謝物與萘之醌類代謝物所形成之Alb adducts之比率,建立一混合模式(Mixed model)篩選乳癌高風險族群。由過去實驗室完成之乳癌病人及正常人背景值混合為一數據庫,求取其算術平均值及標準偏差。以大於平均值之族群歸類為高風險族群 (High risk group),小於背景值平均值歸類為低風險族群 (Low risk group),並計算預測準確百分比值(Predictive value),以及計算模式預測之偽陽性(False positive)及偽陰性(False negative)。 本研究驗證結果顯示,混合模式若以雌性激素之醌類活性代謝物與萘之醌類代謝物所形成之Alb adducts之比率,可以觀察到預測正確值大於99%以上之結果,且偽陽性及偽陰性皆小於2%以下。本研究所建立之生物指標模式,將能作為一高效率篩選乳癌之生物指標,進而提供乳癌風險篩選重要的資訊。
The purpose of this study was to investigate the association of the background levels of albumin adduct (Alb adduct) derived from estrogen and naphthalene quinone metabolites with risk factors of breast cancer. The reactive metabolites of estrogen are 17β-estradiol-2,3-quinone (E2-2,3-Q) and 17β-estradiol-3,4-quinone (E2-3,4-Q) whereas for naphthalene are 1,2-naphthoquinone (1,2-NPQ) and 1,4-naphthoquinone (1,4-NPQ). Background levels of these metabolite-derived albumin adducts may serve as markers to explore the relationship between healthy controls and cancer patients and to establish a prediction model for breast cancer. In this study, we estimated (1) the ratio of Alb adducts between E2-3,4-Q and E2-2,3-Q; (2) the ratio of Alb adducts between 1,2-NPQ and 1,4-NPQ ; (3) the ratio of Alb adducts between naphthalene quinones and estrogen quinones to establish a 'Mixed model' to screen for population with high risk of developing breast cancer.. Based upon our previous analysis of the background values of Alb adducts derived from healthy controls and breast cancer patients, these data were pooled as a data bank. Arithmatic mean and standard deviation were calculated. To those subjects with values greater than the mean were classified as hirisk group and vise versa. The percentage of predictive values, false negative, and false positive were estimated. Results from our analysis indicated that using the ratio of Alb adducts between naphthalene quinones and estrogen quinones as biomarkers, the predictive values of the Mixed model are greater than 99% with less than 2% of false negative, and false positive. This study established a model of biological indicators with high accuracy of screening for individual with high risk of developing breast cancer and provided provide important information of screening for breast cancer risk.
URI: http://hdl.handle.net/11455/98485
文章公開時間: 2021-08-16
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