Abstract 5181: Detecting multiplexed biomarkers for predicting lymph node metastasis by using quantum dots technology
Authors: Xu Jing , Huang Donghai , Wang Yuxiang , Hoyt Clifford C , Peng Xianghong , Wang Dongsheng , Zhang Hongzheng , Shin Dong M , Chen Zhuo (Georgia) 
Published: June 2012

Abstract
Current molecular prediction of lymph node metastasis (LNM) mainly utilizes gene profiling by DNA microarray with RT-PCR validation. Major concerns limiting the application of this technique in the clinic include reproducibility, particularly between different sample cohorts, and costs of these methods. In this study, we used quantum dot (QD)-based immunohistofluorescence (IHF) to select multiplexed biomarkers for predicting LNM in patients with squamous cell carcinoma of the head and neck (SCCHN). Quantification of multiplexed biomarkers was achieved by linking QDs emitted at different wavelengths to the secondary antibodies. In our previous study, we found that epidermal growth factor receptor (EGFR), E-cadherin (E-cad) and aldehyde dehydrogenase1A1 (ALDH1A1) were highly associated with LNM. Therefore, we used QD-based IHF to quantify these three biomarkers simultaneously. Five values can be obtained from the same cells, including expression levels of EGFR, E-cad, and ALDH1A1, and percentage of co-localized EGFR and E-cad versus total EGFR (CO-EGFR) and total E-cad (CO-E-cad). Tissue samples from 100 patients with SCCHN, including 50 N0 and 50 N+ patients, were collected from Emory University hospital, and were used as a training set. 80 additional samples obtained two years later, including 42 N0 patients and 38 N+ patients, were used as a validation set. In the training set, the five values were significantly correlated with LNM (for N+ vs N0, EGFR: 4.66+0.92 vs 1.89+0.41, p = 0.001; ALDHA1: 4.99+0.84 vs 1.79+0.44, p &lt; 0.0001; E-cad: 0.2+0.06 vs 0.84+0.19, p &lt; 0.0001; CO-EGFR(%) : 10.38+1.82 vs 28.72+2.69, p &lt; 0.0001 and CO-E-cad (%): 45.26+3.78 VS 58.2+3.38, p = 0.01). Using a receiver operator characteristic (ROC) model, we found that CO-EGFR+ALDH1A1 was the best biomarker signature for predicting LNM, with a maximum sensitivity of 94% and specificity of 74%. Using the same cut off values, the validation set was tested for the predicting power. It was found that the single biomarker ALDH1A1 could achieve 89% sensitivity and 12% specificity, double biomarker CO-EGFR achieved 76% sensitivity and 62% specificity, and the three biomarker combination, CO-EGFR+ALDH1A1 resulted in higher predicting power than both single and double biomarkers with sensitivity 84% and specificity 62%. Our results suggest that due to the simple nature of the method, quantification of multiplexed biomarkers by using QD-based IHF has significant potential and should be further developed and standardized for predicting metastasis in clinical applications. (Supported by grants NIH R21 CA125062 and GCC Distinguished Scholar Award to ZC).
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5181. doi:10.1158/1538-7445.AM2011-5181