Paper
8 January 2024 Integrating single-cell genomics for specific guidance of iPSCs fate commitment in adoptive cell therapy
Hongji Li, Jinpeng Hu
Author Affiliations +
Proceedings Volume 12924, Third International Conference on Biological Engineering and Medical Science (ICBioMed2023); 129240C (2024) https://doi.org/10.1117/12.3012932
Event: 3rd International Conference on Biological Engineering and Medical Science (ICBioMed2023), 2023, ONLINE, United Kingdom
Abstract
Induced pluripotent stem cells (iPSCs) have immense potential for regenerative medicine, particularly as a main source of adoptive immune cells. However, due to the variation of genetic and epigenetic factors on the differentiation of iPSCs cells, the final desired outcome is often impure. Therefore, fully harnessing the capabilities of iPSCs requires precise control over their fate commitment, ensuring the generation of desired cell lineages with functional properties. In recent years, the integration of single-cell genomics has emerged as a powerful approach for guiding iPSCs fate commitment with unparalleled resolution and specificity. In this paper, we aim to discuss the methodologies and technologies utilized in single-cell genomics, specifically focusing on single-cell RNA sequencing, T cell receptor sequencing, and advanced computational analysis methods. We further explore how these techniques have been applied to uncover the genetic and epigenetic changes involved in iPSCs fate commitment, identify important regulators, and track lineage trajectories at the single-cell level. Additionally, we also provide a concise pipeline to guide iPSCs differentiation by integrating single-cell genomic approaches.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Hongji Li and Jinpeng Hu "Integrating single-cell genomics for specific guidance of iPSCs fate commitment in adoptive cell therapy", Proc. SPIE 12924, Third International Conference on Biological Engineering and Medical Science (ICBioMed2023), 129240C (8 January 2024); https://doi.org/10.1117/12.3012932
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KEYWORDS
Genomics

Tumors

Genetics

Supercontinuum generation

In vitro testing

Algorithm development

Biological research

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