Cancer Genetics and Epigenetics 2024, Vol.12, No.1, 55-65 http://medscipublisher.com/index.php/cge 63 4.2 Impact and contribution to the study of tumor heterogeneity Tumor heterogeneity has always been a core problem in cancer research. It refers to the existence of multiple different cell subpopulations within the same tumor. These subpopulations vary in terms of gene expression, proliferation rate, invasion ability, and response to treatment. There are significant differences. The emergence of single-cell RNA sequencing technology has brought revolutionary breakthroughs to the study of tumor heterogeneity (Ma et al., 2020). This technology can reveal the gene expression profiles of different cell subpopulations within tumors with unprecedented resolution, and can study tumor heterogeneity at the single-cell level. The application of this technology can not only more accurately identify and classify cell subpopulations within tumors, but also enable in-depth analysis of gene expression differences and regulatory networks between these subpopulations. Through these studies, we can gain a deeper understanding of the pathogenesis of tumors, predict patients' treatment response and prognosis, and even guide the development of personalized treatment strategies. In addition, by simultaneously sequencing and analyzing multiple cell types in tumor samples, single-cell RNA sequencing technology can reveal the communication mechanisms and regulatory relationships between different cell types, further deepening the understanding of the tumor ecosystem. These studies will provide new ideas for developing treatment strategies targeting specific cell subpopulations or tumor microenvironments, and promote the development of precision medicine and personalized treatment of tumors. Jamal-Hanjani et al. (2015) highlighted the potential impact of tumor heterogeneity in treatment response and resistance, cancer progression and risk of disease recurrence, but the significance of subclonal mutations, particularly in driver genes, and their subsequent The evolution over time, as well as the response to cancer treatment, remains to be determined. Single-cell RNA sequencing technology has had a profound impact on the study of tumor heterogeneity, providing a powerful tool to reveal the pathogenesis of tumors, develop new treatment strategies, and improve treatment effects. 4.3 Prospects and suggestions for future research directions Looking to the future, with the continuous advancement of science and technology and the deepening of medical research, artificial intelligence and single-cell RNA sequencing technology will present broader development prospects in the fields of drug design and tumor heterogeneity research. McGranahan and Swanton (2017) review data and techniques on intra-tumor heterogeneity across different cancer types, as well as the intrinsic dynamics of tumor evolution, constraints, and contingency, highlighting macroevolutionary transitions, often involving large-scale chromosomal changes, Importance in driving tumor evolution and metastasis. 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 tumor heterogeneity. The importance of sex in developing effective treatments. Single-cell RNA sequencing technology is a powerful tool for studying tumor heterogeneity, but its resolution and accuracy still have room for improvement. Future research should be devoted to improving sequencing technology, reducing experimental costs, and improving data analysis capabilities so that it can be more widely used in the analysis of clinical samples. In addition, combining other omics technologies, such as single-cell proteomics and metabolomics, will provide more comprehensive information on tumor heterogeneity (Peng et al., 2019). Interdisciplinary collaboration is key to advancing both fields. It is recommended to strengthen exchanges and cooperation between computer science, bioinformatics, pharmacy, clinical medicine and other disciplines to jointly promote the application of artificial intelligence and single-cell sequencing technology in the medical field.
RkJQdWJsaXNoZXIy MjQ4ODYzNQ==