Nano-bio-chip sensor platform for examination of oral exfoliative cytology.
Nano-bio-chip sensor platform for examination of oral exfoliative cytology.
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DOI：
10.1158/1940-6207.capr-09-0139
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发表时间：
2010-04
期刊：
影响因子：
--
通讯作者：
McDevitt JT
中科院分区：
文献类型：
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作者：
Weigum SE;Floriano PN;Redding SW;Yeh CK;Westbrook SD;McGuff HS;Lin A;Miller FR;Villarreal F;Rowan SD;Vigneswaran N;Williams MD;McDevitt JT
口腔癌是一种致命的毁容性疾病，可以从早期发现的新诊断方法中受益匪浅。在这项试点研究中，我们描述了一种纳米生物芯片（NBC）传感器技术，用于分析脱落细胞学标本中的口腔癌生物标志物，目标是与早期口腔肿瘤发生相关的生物化学和形态学变化。在这里，口腔病变从41名牙科患者，沿着与正常上皮从11名健康志愿者，采用非侵入性刷活检技术采样。根据先前建立的EGFR生物标志物和细胞形态测定法，在NBC传感器中对样本进行富集、免疫标记和成像。使用自定义图像分析宏提取了总共51个测量参数，包括EGFR标记强度、细胞和核大小以及核质比。与健康口腔上皮相比，异型增生和恶性病变中的四个关键参数显著升高，包括核面积和直径（p < 0.0001）、核质比（p < 0.0001）和EGFR生物标志物表达（p < 0.03）。使用逻辑回归和受试者操作特征（ROC）曲线分析的进一步检查将形态学特征单独确定为疾病的最佳预测因子（AUC ≤ 0.93），而所有特征的组合进一步增强了口腔癌和癌前疾病的区分（AUC = 0.94），具有高灵敏度和特异性。进一步的临床试验是必要的，以验证回归模型和评估其他潜在的生物标志物，但这项初步研究支持NBC传感器技术作为一种有前途的新的诊断工具，用于早期检测口腔癌，这可以提高患者的护理和生存。
Oral cancer is a deadly and disfiguring disease which could greatly benefit from new diagnostic approaches enabling early detection. In this pilot study, we describe a nano-bio-chip (NBC) sensor technique for analysis of oral cancer biomarkers in exfoliative cytology specimens, targeting both biochemical and morphologic changes associated with early oral tumorigenesis. Here, oral lesions from 41 dental patients, along with normal epithelium from 11 healthy volunteers, were sampled using a non-invasive brush biopsy technique. Specimens were enriched, immunolabeled, and imaged in the NBC sensor according to previously established assays for the EGFR biomarker and cytomorphometry. A total of 51 measurement parameters were extracted using custom image analysis macros including EGFR labeling intensity, cell and nuclear size, and the nuclear-to-cytoplasmic ratio. Four key parameters were significantly elevated in both dysplastic and malignant lesions relative to healthy oral epithelium, including the nuclear area and diameter (p < 0.0001), the nuclear-to-cytoplasmic ratio (p < 0.0001), and EGFR biomarker expression (p < 0.03). Further examination using logistic regression and receiver operating characteristic (ROC) curve analysis identified morphologic features as the best predictors of disease (AUC ≤ 0.93) individually, while a combination of all features further enhanced discrimination of oral cancer and pre-cancerous conditions (AUC = 0.94) with high sensitivity and specificity. Further clinical trials are necessary to validate the regression model and evaluate other potential biomarkers, but this pilot study supports the NBC sensor technique as a promising new diagnostic tool for early detection of oral cancer, which could enhance patient care and survival.