Automated measurement of multiple cancer biomarkers using quantum-dot-based microfluidic immunohistochemistry

We report an automated multiple biomarker measurement method for tissue from cancer patients using quantum dot (QD)-based protein detection combined with reference-based protein quantification and autofluorescence (AF) removal. For multiplexed detection of biomarkers in tissue samples, visualization of QDs on cytokeratin was performed to create a multichannel microfluidic device on sites with dense populations of tumor cells. Three major breast cancer biomarkers (i.e., estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2) were labeled using QDs successively on cancer cells in tissue sections. For the automated measurement of biomarkers, a cytokeratin-based biomarker normalization method was used to measure the averaged expression of proteins. A novel AF-removal algorithm was developed, which normalizes the reference AF spectra reconstructed from unknown AF spectra based on random sampling. For accurate quantification of QDs, we automatically and accurately removed the AF signal from 344 spots of QD-labeled tissue samples using 240 reference AF spectra. Using analytical data with 10 tissue samples from breast cancer patients, the measured biomarker intensities were in good agreement with the results of conventional analyses.