4.6 Review

Single-Cell Sequencing: Current Applications in Precision Onco-Genomics and Cancer Therapeutics

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CANCERS
卷 14, 期 3, 页码 -

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MDPI
DOI: 10.3390/cancers14030657

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single-cell sequencing; large integrated databases; immunotherapy; personalized medicine; cancer

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Single-cell sequencing technologies have become increasingly important in cancer research, allowing scientists to analyze the genome, transcriptome, epigenome, and proteome of individual cells. This review summarizes the various techniques used in single-cell sequencing and provides examples of recent high-impact findings. It also discusses the translational relevance of these technologies and their potential use in clinical trials.
Simple Summary Single-cell sequencing technologies are growing, advancing, and supporting new opportunities to better understand cancer. A variety of technologies are available that analyze the human transcriptome, genome, epigenome, and proteome, enabling integrated datasets. As a result, these integrated datasets contribute to new mechanistic insights and areas with therapeutic potential. This review summarizes the various single-cell sequencing techniques and provides examples of recent high-impact findings from the utilization of these technologies. Additionally, the translational relevance of these technologies and their use in clinical trials is described, along with the future potential for novel findings using these innovative methods. Single-cell sequencing encompasses a variety of technologies that evaluate cells at the genomic, transcriptomic, epigenomic, and proteomic levels. Each of these levels can be split into additional techniques that enable specific and optimized sequencing for a specialized purpose. At the transcriptomic level, single-cell sequencing has been used to understand immune-malignant cell networks, as well as differences between primary versus metastatic tumors. At the genomic and epigenomic levels, single-cell sequencing technology has been used to study genetic mutations involved in tumor evolution or the reprogramming of regulatory elements present in metastasized disease, respectively. Lastly, at the proteomic level, single-cell sequencing has been used to identify biomarkers important for predicting patient prognosis, as well as biomarkers essential for evaluating optimal treatment strategies. Integrated databases and atlases, as a result of large sequencing experiments, provide a vast array of information that can be applied to various studies and accessed by researchers to further answer scientific questions. This review summarizes recent, high-impact literature covering these aspects, as well as single-cell sequencing in the translational setting. Specifically, we review the potential that single-cell sequencing has in the clinic and its implementation in current clinical studies.

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