Genomic and Functional Technologies for Studying Cancer Stem Cell Dynamics, Metastasis, and Therapy Resistance

Cancer stem cells (CSCs) are a functionally defined and plastic subpopulation of tumor cells. While the precise definition of CSCs is still debated, studies demonstrate that CSCs are capable of driving recurrence, metastases, and therapeutic resistance. Genomic studies of CSCs are critical to understanding how these cells exert their effects within the tumor microenvironment and while under therapeutic pressure. Prior reviews on the genomic characterization of CSCs have primarily focused upon biological mechanisms, therapeutic categories, or the leverage of a single experimental platform. However, no prior reviews have provided a cross-platform comparison of the methodologies used to characterize CSC dynamics, metastasis and therapy resistance. In this manuscript, we review methodologies to study CSCs: spatial transcriptomics, CRISPR functional screens, nanoparticle-based tools, and single-cell omics. We provide the mechanistic basis, application to CSC dynamics, advantages and limitations, and methods of integration among these complementary approaches, including the leveraging of new artificial intelligence tools. While we describe the details of each individual platform, ultimately, we show that the integration of techniques is critical to future studies of CSCs.