Cell-Based Approaches for Therapeutic Selection in Oncology

<br/>Single-cell analysis methods provide information that is not masked by the intrinsic heterogeneity of the bulk population and can therefore be applied to gain insights into heterogeneity among different cell subpopulations with fine resolution. Over the last five years, an explosion in the number of single-cell measurement methods has occurred. However, most of these methods are applicable to pure populations of cultured cells and are not able to handle high levels of phenotypic heterogeneity or a large background of nontarget cells. Our laboratory has developed a new microfluidics-based analytical strategy to meet this unmet need referred to as magnetic ranking cytometry (MagRC). Cells expressing a biomarker of interest are labeled with receptor-coated magnetic nanoparticles and isolated from nontarget cells using a microfluidic device. The device ranks the cells according to the level of bound magnetic nanoparticles, which corresponds to the expression level of a target biomarker. Over the last several years, two generations of MagRC devices have been developed for different applications. The first-generation MagRC devices are powerful tools for the quantitation and analysis of rare cells present in heterogeneous samples, such as CTCs, stem cells, and pathogenic bacteria. The second-generation MagRC devices are compatible with the efficient recovery of cells sorted on the basis of protein expression and can be used to analyse large populations of cells and perform phenotypic CRISPR screens. To improve analytical precision, newer iterations of the first-generation and second-generation MagRC devices have been integrated with electrochemical sensors and Hall effect sensors, respectively. Both generations of MagRC devices permit the isolation of viable cells, which sets the stage for a wide range of applications, such as generating cell lines from rare cells and <i>in vitro</i> screening for effective therapeutic interventions in cancer patients to realize the promise of personalized medicine.