Abstract
Microfluidics-based single-cell study is an emerging approach in personalized treatment or precision medicine studies. Single-cell gene expression holds a potential to provide treatment selections with maximized efficacy to help cancer patients based on a genetic understanding of their disease. This work presents a multi-layer microchip for single-cell multiplexed gene expression profiling and genotoxicity detection. Treated by three drug reagents (i.e., methyl methanesulfonate, docetaxel and colchicine) with varied concentrations and time lengths, individual human cancer cells (MDA-MB-231) are lysed on-chip, and the released mRNA templates are captured and reversely transcribed into single strand DNA. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), cyclin-dependent kinase inhibitor 1A (CDKN1A), and aurora kinase A (AURKA) genes from single cells are amplified and real-time quantified through multiplex polymerase chain reaction. The microchip is capable of integrating all steps of single-cell multiplexed gene expression profiling, and providing precision detection of drug induced genotoxic stress. Throughput has been set to be 18, and can be further increased following the same approach. Numerical simulation of on-chip single cell trapping and heat transfer has been employed to evaluate the chip design and operation.
Highlights
As a leading cause of death worldwide, cancer has been widely recognized as a disease from patient-specific mutations [1]
Single-cell gene expression profiling promises to address the issues in cancer research, including unveiling intra-tumor heterogeneity [8], tracing cell lineages [9], interpreting rare tumor cell populations [10], and quantifying mutation rates [11]
A typical mammalian cell contains about 10–30 pg RNA and messenger RNA (mRNA) accounts for 1%–5% of the total cellular RNA depending on the cell type and physiological state [13]
Summary
As a leading cause of death worldwide, cancer has been widely recognized as a disease from patient-specific mutations [1]. Fueled by cutting-edge cellular and molecular technologies, the data of single cancer cells has transformed from qualitative microscopic readouts to quantitative genomic datasets. Single-cell gene expression profiling promises to address the issues in cancer research, including unveiling intra-tumor heterogeneity [8], tracing cell lineages [9], interpreting rare tumor cell populations [10], and quantifying mutation rates [11]. Such assays have been technically challenging due to the low quantity and degradation of messenger RNA (mRNA) from an individual cell [12]. A typical mammalian cell contains about 10–30 pg RNA and mRNA accounts for 1%–5% of the total cellular RNA depending on the cell type and physiological state [13]
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