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

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 ex vivo tissue specimen staining and allowing for rapid clinical translation of this promising technology for tumor margin detection during BCS procedures.

Topical dual-probe staining using quantum dot-labeled antibodies for identifying tumor biomarkers in fresh specimens

“…Consistent with our prior studies investigating tissue staining protocols for tumor diagnosis [20,37], ROC analysis of the targeted QDAC probe alone showed no capacity to identify tumor and normal tissues. Thus, these results add to the expanding experimental evidence emphasizing the importance of incorporating the untargeted counterpart for fresh tissue staining.…”

“…Temperature is known to affect the rate of antibody-antigen binding [41], and this effect seems to be a primary driver of the QDAC probe kinetics in our protocol. Interestingly, this temperature sensitivity has not been observed in our extensive prior work which showed very high diagnostic performance using standard fluorophore labels [20,37] for tissue staining at room temperature.…”

“…A schematic of the tissue staining and imaging protocol is provided in Fig 1(a), and similar protocols for non-quantum dot DDSI have been described previously [20,37]. In this study, specimens were first submerged in a blocking solution consisting of 5% bovine serum albumin (BSA) for 10 minutes.…”

“…After normalization, the DDSI value ((targeteduntargeted)/untargeted) was calculated to produce the DDSI image maps, as illustrated in Fig 1(c). As previously reported [37], ROC curves were determined using the perfcurve function in Matlab on a pixel-by-pixel basis, with truth defined by manually tracking harvested tumor and normal specimens through the staining process. Area under the curve (AUC) were values extracted to compare diagnostic performance of each condition.…”

“…These normalization/correction procedures can involve simple subtraction, ratio calculation, or more sophisticated model-based methods to provide quantitative information about receptor engagement [34][35][36]. Experimentally, dual-probe techniques have been applied using antibody-labeled surfaceenhanced Raman spectroscopy particles, which allow multiplexing of multiple targets of interest due to the fine spectral features of the Raman signatures [19,31,32], or antibodies labeled with conventional organic fluorophores [20,37].…”