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Antibody microarray analysis of the serum proteome in primary breast cancer patients

机译:原发性乳腺癌患者血清蛋白质组的抗体微阵列分析

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Noninvasive biomarkers are urgently needed for detecting breast cancer as early as possible since the risk of recurrence, morbidity and mortality is closely related to disease stage at the time of primary surgery. There are currently no such biomarkers in clinical use as a diagnostic tool. Proteomic analysis of protein expression patterns in body fluids has potential for use in identifying biomarkers of breast cancer. The aim of this study was to compare protein expression levels in the sera of primary breast cancer patients and healthy controls. An antibody microarray tool with 23 antibodies immobilized on nitrocellulose slides was used to determine the levels of acute phase proteins, interleukins and complement factors in the sera of 101 study participants (49 women with primary breast cancer and 52 healthy age-matched controls). Statistical analysis of reaction intensities identified six proteins that showed significantly (p < 0.05) different levels in breast cancer patients vs. healthy subjects. The neural network distinguished cancer patients from controls with a sensitivity of 69% and a specificity of 76%. Thus, antibody microarray analysis could be used as a tool for the development of improved diagnostics and biomarker discovery for breast cancer patients. Further validation of the results and de novo screening of new biomarkers could facilitate the early diagnosis of breast cancer.
机译:迫切需要非侵入性生物标记物,以尽早发现乳腺癌,因为复发,发病率和死亡率的风险与初次手术时的疾病阶段密切相关。当前在临床上没有这样的生物标记物作为诊断工具。体液中蛋白质表达模式的蛋白质组学分析具有识别乳腺癌生物标志物的潜力。这项研究的目的是比较原发性乳腺癌患者和健康对照者血清中的蛋白质表达水平。 101位研究参与者(49位患有原发性乳腺癌的女性和52位年龄相匹配的健康对照者)的血清中,使用一种将23种抗体固定在硝酸纤维素玻片上的抗体微阵列工具来确定其急性期蛋白,白介素和补体因子的水平。反应强度的统计分析确定了六种蛋白质,这些蛋白质在乳腺癌患者和健康受试者中显示出显着(p <0.05)的不同水平。该神经网络以69%的敏感性和76%的特异性将癌症患者与对照组区别开来。因此,抗体微阵列分析可以用作开发针对乳腺癌患者的改进的诊断方法和生物标记物发现的工具。对结果的进一步验证和对新的生物标志物的从头筛选可以促进乳腺癌的早期诊断。

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