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优化新鲜标本染色,以在手术期间快速鉴定肿瘤生物标志物。

Optimizing fresh specimen staining for rapid identification of tumor biomarkers during surgery.

机构信息

Biomedical Engineering Department.

Thayer School of Engineering, Dartmouth College, Hanover, NH 03755.

出版信息

Theranostics. 2017 Oct 17;7(19):4722-4734. doi: 10.7150/thno.21527. eCollection 2017.

Abstract

RATIONALE

Positive margin status due to incomplete removal of tumor tissue during breast conserving surgery (BCS) is a prevalent diagnosis usually requiring a second surgical procedure. These follow-up procedures increase the risk of morbidity and delay the use of adjuvant therapy; thus, significant efforts are underway to develop new intraoperative strategies for margin assessment to eliminate re-excision procedures. One strategy under development uses topical application of dual probe staining and a fluorescence imaging strategy termed dual probe difference specimen imaging (DDSI). DDSI uses a receptor-targeted fluorescent probe and an untargeted, spectrally-distinct fluorescent companion imaging agent topically applied to fresh resected specimens, where the fluorescence from each probe is imaged and a normalized difference image is computed to identify tumor-target distribution in the specimen margins. While previous reports suggested this approach is a promising new tool for surgical guidance, advancing the approach into the clinic requires methodical protocol optimization and further validation.

METHODS

In the present study, we used breast cancer xenografts and receiver operator characteristic (ROC) curve analysis to evaluate a wide range of staining and imaging parameters, and completed a prospective validation study on multiple tumor phenotypes with different target expression. Imaging fluorophore-probe pair, concentration, and incubation times were systematically optimized using n=6 tissue specimen replicates per staining condition. Resulting tumor vs. normal adipose tissue diagnostic performance were reported and staining patterns were validated via receptor specific immunohistochemistry colocalization. Optimal staining conditions were tested in receptor positive and receptor negative cohorts to confirm specificity.

RESULTS

The optimal staining conditions were found to be a one minute stain in a 200 nM probe solution (area under the curve (AUC) = 0.97), where the choice of fluorescent label combination did not significantly affect the diagnostic performance. Using an optimal threshold value determined from ROC curve analysis on a training data set, a prospective study on xenografts resulted in an AUC=0.95 for receptor positive tumors and an AUC = 0.50 for receptor negative (control) tumors, confirming the diagnostic performance of this novel imaging technique.

CONCLUSIONS

DDSI provides a robust, molecularly specific imaging methodology for identifying tumor tissue over benign mammary adipose tissue. Using a dual probe imaging strategy, nonspecific accumulation of targeted probe was corrected for and tumor vs. normal tissue diagnostic potential was improved, circumventing difficulties with tissue specimen staining and allowing for rapid clinical translation of this promising technology for tumor margin detection during BCS procedures.

摘要

背景

保乳手术(BCS)中由于肿瘤组织切除不完整而导致的阳性切缘状态是一种常见的诊断,通常需要进行第二次手术。这些后续手术增加了发病率的风险,并延迟了辅助治疗的使用;因此,正在努力开发新的术中切缘评估策略,以消除再次切除手术。一种正在开发的策略是使用双探针染色和一种称为双探针差异标本成像(DDSI)的荧光成像策略。DDSI 使用受体靶向荧光探针和一种非靶向、光谱上不同的荧光伴随成像剂,将其局部应用于新鲜切除的标本,其中每个探针的荧光被成像,并计算归一化差异图像以识别标本切缘中的肿瘤靶标分布。虽然之前的报告表明这种方法是一种有前途的新手术指导工具,但将该方法推进临床需要有条不紊的方案优化和进一步验证。

方法

在本研究中,我们使用乳腺癌异种移植物和接收者操作特征(ROC)曲线分析来评估广泛的染色和成像参数,并在具有不同靶表达的多种肿瘤表型上完成了前瞻性验证研究。使用 n=6 个组织标本重复进行每个染色条件的成像荧光团-探针对、浓度和孵育时间的系统优化。报告了肿瘤与正常脂肪组织的诊断性能,并通过受体特异性免疫组织化学共定位验证了染色模式。在受体阳性和受体阴性队列中测试了最佳染色条件以确认特异性。

结果

发现最佳染色条件为 200 nM 探针溶液中一分钟染色(曲线下面积(AUC)=0.97),其中荧光标记组合的选择并未显著影响诊断性能。使用在训练数据集上通过 ROC 曲线分析确定的最佳阈值值,对异种移植物进行的前瞻性研究得出受体阳性肿瘤的 AUC=0.95,受体阴性(对照)肿瘤的 AUC=0.50,证实了这种新的成像技术的诊断性能。

结论

DDSI 为识别肿瘤组织与良性乳腺脂肪组织提供了一种强大的、分子特异性的成像方法。使用双探针成像策略,校正了靶向探针的非特异性积累,提高了肿瘤与正常组织的诊断潜力,避免了组织标本染色的困难,并允许快速将这项有前途的技术转化为 BCS 手术中肿瘤切缘检测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22f1/5706095/65c6537849f1/thnov07p4722g001.jpg

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