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Salivary Glycopatterns as Potential Biomarkers for Screening of Early-Stage Breast Cancer

机译：唾液糖皮质激素作为筛选早期乳腺癌的潜在生物标志物

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Objective We systematically investigated and assessed the alterations of salivary glycopatterns and possibility as biomarkers for diagnosis of early-stage breast cancer. Design Alterations of salivary glycopatterns were probed using lectin microarrays and blotting analysis from 337 patients with breast benign cyst or tumor (BB) or breast cancer (I/II stage) and 110 healthy humans. Their diagnostic models were constructed by a logistic stepwise regression in the retrospective cohort. Then, the performance of the diagnostic models were assessed by ROC analysis in the validation cohort. Finally, a double-blind cohort was tested to confirm the application potential of the diagnostic models. Results The diagnostic models were constructed based on 9 candidate lectins (e.g., PHA-E + L, BS-I, and NPA) that exhibited significant alterations of salivary glycopatterns, which achieved better diagnostic powers with an AUC value > 0.750 (p Conclusions This study could contribute to the screening for patients with early-stage breast cancer based on precise alterations of salivary glycopatterns.
机译：目的我们系统地研究和评估唾液糖模式的变化以及作为诊断早期乳腺癌的生物标志物的可能性。设计使用凝集素微阵列和印迹分析法对337例乳腺良性囊肿或肿瘤（BB）或乳腺癌（I / II期）患者和110名健康人的唾液糖模式进行了研究。他们的诊断模型是通过回顾性队列中的逻辑逐步回归建立的。然后，通过验证队列中的ROC分析评估诊断模型的性能。最后，对双盲队列进行了测试，以确认诊断模型的应用潜力。结果基于9种候选凝集素（例如PHA-E + L，BS-1和NPA）构建了诊断模型，这些凝集素表现出唾液糖模式的显着改变，其AUC值> 0.750时具有更好的诊断能力（p结论这项研究可以基于唾液糖模式的精确改变，有助于筛查早期乳腺癌患者。

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