Translational Traits of Non-Small-Cell Lung Carcinoma with Drug Resistances by Dual mRNA and Protein Quantification at the Single Cell Level

Abstract

Translation in eukaryotic cells is a fundamental biological process that has been investigated widely for understanding gene expression. To comprehensively understand gene expression, single cell level observation of both transcript and protein is desirable for translational analysis. The simultaneous observation of both transcript and protein, however, remains challenging due to the requirements of a highly sensitive and multi-modal platform. Here, we report a robust microdevice enabling both transcript and protein quantification from a single cell with a large number of cells per assay. Using 25600 microwells, we quarantined single cells for observing protein expression through immunostaining and sequentially mRNA expression via single cell reverse transcription polymerase chain reaction. Based on this correlation between transcript and protein, 2-dimensional cytometric representation from single cells is possible. The relationship between transcript and proteome of three NSCLC cell lines (HCC827, H1650 and H1975) with different levels of drug resistances to epidermal growth factor tyrosine kinase inhibitors clearly indicates unique translational traits of each cell line. Our data demonstrated that the most drug resistant cell line, H1975, showed least translational efficiency in cMET whereas the least drug resistant cell line, HCC827, showed most translational efficiency. Cytometric platforms, like the one introduced here, may ultimately allow researchers to quantify the evolution of cancerous tissues enabling detailed monitoring of tumor progression.