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Advances in single-cell RNA sequencing and its applications in cancer research.


ABSTRACT: Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor microenvironment. The emergence and development of single-cell RNA sequencing (scRNA-seq) technologies have provided opportunities to understand subtle changes in tumor biology by identifying distinct cell subpopulations, dissecting the tumor microenvironment, and characterizing cellular genomic mutations. Recently, scRNA-seq technology has been increasingly used in cancer studies to explore tumor heterogeneity and the tumor microenvironment, which has increased the understanding of tumorigenesis and evolution. This review summarizes the basic processes and development of scRNA-seq technologies and their increasing applications in cancer research and clinical practice.

SUBMITTER: Huang D 

PROVIDER: S-EPMC10463514 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Advances in single-cell RNA sequencing and its applications in cancer research.

Huang Dezhi D   Ma Naya N   Li Xinlei X   Gou Yang Y   Duan Yishuo Y   Liu Bangdong B   Xia Jing J   Zhao Xianlan X   Wang Xiaoqi X   Li Qiong Q   Rao Jun J   Zhang Xi X  

Journal of hematology & oncology 20230824 1


Cancers are a group of heterogeneous diseases characterized by the acquisition of functional capabilities during the transition from a normal to a neoplastic state. Powerful experimental and computational tools can be applied to elucidate the mechanisms of occurrence, progression, metastasis, and drug resistance; however, challenges remain. Bulk RNA sequencing techniques only reflect the average gene expression in a sample, making it difficult to understand tumor heterogeneity and the tumor micr  ...[more]

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