» Articles » PMID: 33766554

Single-cell Sequencing Technology in Tumor Research

Overview
Journal Clin Chim Acta
Specialty Biochemistry
Date 2021 Mar 26
PMID 33766554
Citations 15
Authors
Affiliations
Soon will be listed here.
Abstract

Tumor heterogeneity is a key characteristic of malignant tumors and a significant obstacle in cancer treatment and research. Although bulk tissue sequencing has wide coverage and high accuracy, it can only represent the dominant cell signal information of each sample, while masking the unique gene expression of rare cells; therefore it cannot represent genes that are unstable within a subgroup, but unchanged in a majority of cells. With the progress of genomic technology, the emergence of single-cell sequencing (SCS) has effectively solved the above problem. Genetic, transcriptomic and epigenetic sequencing at the single-cell level provides an important basis for us to correctly classify the cell subsets of heterogeneous tumor populations and to reveal the process of complex changes in tumor cells at the molecular level. Single-cell sequencing technology has been applied to the field of cancer, revealing exciting discoveries in the potential mechanisms of tumor driver gene mutation, clonal evolution, invasion and metastasis. It also provides favorable conditions for developing new tumor biomarkers and providing more accurate and individualized targeted tumor therapy. Herein, we review the steps and methods of single-cell sequencing and highlight the application of SCS in tumor diagnosis and clinical treatment.

Citing Articles

Single-Cell RNA Sequencing in Unraveling Acquired Resistance to EGFR-TKIs in Non-Small Cell Lung Cancer: New Perspectives.

Peng L, Deng S, Li J, Zhang Y, Zhang L Int J Mol Sci. 2025; 26(4).

PMID: 40003951 PMC: 11855476. DOI: 10.3390/ijms26041483.


Research trends and hotspots of the applications of single-cell RNA sequencing in cardiovascular diseases: a bibliometric and visualized study.

Yu Y, Ye J, Wang R, Wang J, Wang J, Xu Q Ann Med Surg (Lond). 2024; 86(12):7164-7177.

PMID: 39649887 PMC: 11623828. DOI: 10.1097/MS9.0000000000002681.


Application of single cell sequencing technology in ovarian cancer research (review).

Yuan Q, Lv N, Chen Q, Shen S, Wang Y, Tong J Funct Integr Genomics. 2024; 24(5):144.

PMID: 39196391 PMC: 11358195. DOI: 10.1007/s10142-024-01432-w.


Integration of single-cell sequencing and bulk RNA-seq to identify and develop a prognostic signature related to colorectal cancer stem cells.

Wu J, Li W, Su J, Zheng J, Liang Y, Lin J Sci Rep. 2024; 14(1):12270.

PMID: 38806611 PMC: 11133358. DOI: 10.1038/s41598-024-62913-3.


Identification and Validation of T-Cell Exhaustion Signature for Predicting Prognosis and Immune Response in Pancreatic Cancer by Integrated Analysis of Single-Cell and Bulk RNA Sequencing Data.

Zhu Y, Tan L, Luo D, Wang X Diagnostics (Basel). 2024; 14(6).

PMID: 38535087 PMC: 10968840. DOI: 10.3390/diagnostics14060667.