Advancing precision medicine through single-cell sequencing: Insights and implications

Abstract

Background: Single-cell sequencing (SCS) marks the advent of a transformative period in biomedical studies, enabling unprecedented insight into the cellular intricacies of health and disease.

Methods: By dissecting the genetic, epigenetic and proteomic landscapes at the single-cell level, SCS transcends traditional bulk sequencing methodologies, illuminating the heterogeneity and dynamics of individual cells.

Results: This analytical leap facilitates a deeper understanding of disease mechanisms, offers novel diagnostic and therapeutic targets and underpins the development of precision medicine across diverse fields such as neurology, oncology and immunology.

Conclusions: Despite its profound potential, SCS encounters challenges, including complex sample preparation, sophisticated data analysis and cost considerations. Nevertheless, ongoing advancements promise to overcome these barriers, integrating SCS with other omics data and leveraging machine learning to enhance biological understanding and clinical application. With the advancement of SCS technologies, personalised healthcare might be fundamentally altered, facilitating tailored and efficacious treatment strategies.

References

[1] WangY, NavinNE. Advances and applications of single-cell sequencing technologies. Mol Cell. 2015;58(4):598-609.

[2] FangH, ZengY, ZhangL, Chen C, PowellCA, WangX. Can single-cell RNA sequencing reshape the clinical biochemistry of haematology? New clusters of circulating blood cells. Clin Transl Disc. 2022;2:e19.

[3] YanF, LiZ, PowellCA, Wang X. Forward single-cell sequencing into clinical application: understanding of ageing and rejuvenation from clinical observation to single-cell solution. Clin Transl Disc. 2022;2:e50.

[4] SauraCA, Deprada A, Capilla-LópezMD, Parra-DamasA. Revealing cell vulnerability in Alzheimer's disease by single-cell transcriptomics. Semin Cell Dev Biol. 2023;139:73-83.

[5] ZhangX, LuP, ShenX. Applications of single-cell multi-omics sequencing in deep understanding of brain diseases. Clin Transl Disc. 2022;2:e95.

[6] YangB, SedanoMJ, GadadSS. Single-cell nucleic acid sequencing reinforces to reveal signal-dependent pathways contributing to cellular heterogeneity. Clin Transl Disc. 2022;2:e120.

[7] WangF, LongJ, LiL, et al. Single-cell and spatial transcriptome analysis reveals the cellular heterogeneity of liver metastatic colorectal cancer. Sci Adv. 2023;9(24):eadf5464.

[8] DominguezCX, Müller S, KeerthivasanS, et al. Single-cell RNA sequencing reveals stromal evolution into LRRC15+ myofibroblasts as a determinant of patient response to cancer immunotherapy. Cancer Discov. 2020;10(2):232-253.

[9] ChenD, LuoY, ChengG. Single cell and immunity: better understanding immune cell heterogeneities with single-cell sequencing. Clin Transl Disc. 2022;2:e162.

[10] LiuX, ZhuZ, WangX. Specificity and function of T cell subset identities using single-cell sequencing. Clin Transl Disc. 2023;3:e199.

[11] LiuX, WangDC, PowellCA, Wang X. Challenges of clinical translation from single-cell sequencing to measures in clinical biochemistry of haematology: definition of immune cell identities. Clin Transl Med. 2023;13:e1401.

[12] LiuF, LiuX, PowellCA, et al. Initiative of clinical single-cell biomedicine in clinical and translational medicine. Clin Transl Med. 2023;13:e1173.

[13] WangDC, WangX. Discovery in clinical and translational medicine. Clin Transl Med. 2021;11(10):e568.

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2024 The Authors. Clinical and Translational Discovery published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.