Cancer Genetics and Epigenetics 2024, Vol.12, No.1, 55-65 http://medscipublisher.com/index.php/cge 55 Research Report Open Access A New Perspective on Revealing Tumor Heterogeneity through Single Cell RNA Sequencing TaoChen Institute of Life Science, Jiyang College of Zhejiang A&F University, Zhuji, 311800, China Corresponding author email: 2693733238@qq.com Cancer Genetics and Epigenetics, 2024, Vol.12, No.2 doi: 10.5376/cge.2024.12.0007 Received: 29 Dec., 2023 Accepted: 02 Feb., 2024 Published: 15 Feb., 2024 Copyright © 2024 Chen, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Chen T., 2024, Single-cell RNA sequencing reveals new insights into tumor heterogeneity, Cancer Genetics and Epigenetics, 12(1): 55-65 (doi: 10.5376/cge.2024.12.0007) Abstract Study mainly explores the application and prospects of single-cell RNA sequencing technology in the study of tumor heterogeneity. As an important concept in the field of oncology, tumor heterogeneity reveals the diversity and complexity of cells within tumors and has an important impact on the occurrence, development, treatment and prognosis of tumors. However, traditional research methods have limitations in revealing tumor heterogeneity. In recent years, the emergence of single-cell RNA sequencing technology has brought new breakthroughs to the study of tumor heterogeneity. This study first introduces the concept of tumor heterogeneity and its importance, and then outlines the development process and principles of single-cell RNA sequencing technology. Next, the specific application of single-cell RNA sequencing in the study of tumor heterogeneity was highlighted, including identifying cell subpopulations within tumors, analyzing gene expression differences and regulatory networks, and studying interactions between tumor cells. Finally, the contribution of single-cell RNA sequencing in the study of tumor heterogeneity is summarized and future research directions are prospected. Keywords Tumor heterogeneity; Single-cell RNA Sequencing; Cell Subpopulation; Gene Expression; Tumor Cell Interactions Tumor heterogeneity is a core and complex issue in contemporary oncology research. It refers to the significant differences in genetics, epigenetics, metabolism, and cell behavior between different cell populations within the same tumor. This heterogeneity not only affects the growth rate, invasion ability and response to treatment of tumors, but also greatly increases the risk of disease recurrence and metastasis, making precision treatment of tumors facing huge challenges (Stanta and Bonin, 2018). Therefore, a deep understanding of the nature and sources of tumor heterogeneity is crucial for the development of more effective diagnostic and therapeutic strategies. In recent years, with the rapid development of biotechnology, single-cell RNA sequencing (scRNA-seq) technology has emerged and gradually matured. This technology allows researchers to make high-precision measurements of genome-wide transcription at the level of individual cells, revealing heterogeneity within cell populations with unprecedented resolution. Compared with traditional cell population-based sequencing methods, scRNA-seq avoids the interference of population average effects and can more accurately depict the unique status of each cell and its dynamic changes throughout the biological process (Papalexi and Satija, 2018). In the field of oncology, the introduction of scRNA-seq technology provides new opportunities for comprehensive analysis of tumor heterogeneity. By measuring the gene expression profile of individual tumor cells, researchers can not only identify different cell subpopulations within the tumor, but also further analyze the gene expression differences, signaling pathway activation status, and potential intercellular communication between these subpopulations. Mechanism (Ferrall -Fairbank and Meghan, 2019). This information is of great significance for revealing the mechanisms of tumorigenesis, key regulatory networks during development, and mechanisms of response and resistance to treatment strategies.
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