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Open AccessJournal ArticleDOI

Applications of single-cell sequencing in cancer research: progress and perspectives

TLDR
The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions, including information related to the landscapes of malignant cells and immune cells, tumor heterogeneity, circulating tumor cells and underlying mechanisms of tumor biological behaviors as mentioned in this paper.
Abstract
Single-cell sequencing, including genomics, transcriptomics, epigenomics, proteomics and metabolomics sequencing, is a powerful tool to decipher the cellular and molecular landscape at a single-cell resolution, unlike bulk sequencing, which provides averaged data. The use of single-cell sequencing in cancer research has revolutionized our understanding of the biological characteristics and dynamics within cancer lesions. In this review, we summarize emerging single-cell sequencing technologies and recent cancer research progress obtained by single-cell sequencing, including information related to the landscapes of malignant cells and immune cells, tumor heterogeneity, circulating tumor cells and the underlying mechanisms of tumor biological behaviors. Overall, the prospects of single-cell sequencing in facilitating diagnosis, targeted therapy and prognostic prediction among a spectrum of tumors are bright. In the near future, advances in single-cell sequencing will undoubtedly improve our understanding of the biological characteristics of tumors and highlight potential precise therapeutic targets for patients.

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Cell death-related biomarker SLC2A1 has a significant role in prognosis prediction and immunotherapy efficacy evaluation in pan-cancer

TL;DR: In this paper , the authors evaluated the role of SLC2A1 in pan-cancer using the GEPIA2.0, TIMER 2.0 and UALCAN databases.
Posted ContentDOI

Identification of muscle-invasive related genes in bladder cancer single-cell sequencing data for constructing patient prognostic model

TL;DR: In this paper , the expression levels of muscle-invasive related genes (MIRGs) in bladder cancer patients and construct a model of MIRG, which can predict patients' prognosis using bioinformatics methods.
References
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Journal ArticleDOI

Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position

TL;DR: The feasibility of analyzing an individual's epigenome on a timescale compatible with clinical decision-making is demonstrated and classes of DNA-binding factors that strictly avoided, could tolerate or tended to overlap with nucleosomes are discovered.
Journal ArticleDOI

Droplet Barcoding for Single-Cell Transcriptomics Applied to Embryonic Stem Cells

TL;DR: This work has developed a high-throughput droplet-microfluidic approach for barcoding the RNA from thousands of individual cells for subsequent analysis by next-generation sequencing, which shows a surprisingly low noise profile and is readily adaptable to other sequencing-based assays.
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