Cancer Genetics and Epigenetics 2024, Vol.12, No.1, 55-65 http://medscipublisher.com/index.php/cge 58 Traditional methods are difficult to dynamically track changes in tumor cells in time and space (Heinrich et al., 2021). Tumor heterogeneity is a dynamic process, and with tumor development and therapeutic intervention, cell subpopulations may change, with new subpopulations appearing or old subpopulations disappearing. However, traditional methods often only provide static information and fail to reflect these dynamic changes, thus limiting a comprehensive understanding of tumor heterogeneity. Traditional methods also have difficulties in identifying and isolating different cell subpopulations within tumors. Due to technical limitations, these methods are often unable to accurately identify different cell types within tumors, let alone further isolate and study the biological properties of these cell subpopulations. This severely limits our understanding of the sources and maintenance mechanisms of tumor heterogeneity. Dagogo-Jack and Shaw (2018) discussed how tumor heterogeneity increases with disease progression, and tumors may contain subpopulations of cells with different molecular characteristics and different sensitivities to treatments. They emphasized the accurate assessment of tumors. The importance of heterogeneity in developing effective treatments. 2 Principles and Advantages of Single-cell RNA Sequencing Technology 2.1 Principles of single-cell RNA sequencing technology Single-cell RNA sequencing technology (Figure 2), as a major breakthrough in the field of bioinformatics in recent years, its principle integrates cutting-edge technologies in multiple fields such as molecular biology, microfluidic technology, and high-throughput sequencing. This technology aims to solve the bottleneck of traditional RNA sequencing methods that cannot be accurate to individual cells, and provides life science researchers with a new perspective to gain insight into the differences and complexities between cells. Figure 2 A Diagram of Single-cell Sequencing (Zheng et al., 2019) In the initial stages of single-cell RNA sequencing, single cells need to be efficiently isolated from complex biological samples. This is usually achieved with the help of microfluidic chips or droplet generation systems, ensuring that each processing unit contains only one cell. These isolated individual cells are then lysed, releasing the intracellular RNA molecules.
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