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人类诱导多能干细胞重编程的成功:方法与源材料的影响

Human iPSC Reprogramming Success: The Impact of Approaches and Source Materials.

作者信息

Pozner Tatyana, Grandizio Christine, Mitchell Matthew W, Turan Nahid, Scheinfeldt Laura

机构信息

Biobanking Department, Coriell Institute for Medical Research, Camden 08003, New Jersey, USA.

出版信息

Stem Cells Int. 2025 Jan 16;2025:2223645. doi: 10.1155/sci/2223645. eCollection 2025.

DOI:10.1155/sci/2223645
PMID:39850337
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11756937/
Abstract

Since their discovery, human induced pluripotent stem cells (hiPSCs) have been instrumental in biomedical research, particularly in the fields of disease modelling, drug screening and regenerative therapies. Their use has significantly increased over recent years driven by the ability of hiPSCs to provide differentiated cell models without requiring embryonic stem cells. Furthermore, the transition from integrating to non-integrating reprogramming methodologies has contributed to the increase in utilisation. This shift minimises the risk of genomic alterations, enhancing the safety and reliability of hiPSCs. However, the factors that contribute to reprogramming success are still not well understood. In this study, we conducted a comparative analysis of the most prevalent non-integrating reprogramming methods across a range of starting source materials to assess their impact on reprogramming success rates. We found that while source material does not significantly impact success rates, the Sendai virus reprogramming method yields significantly higher success rates relative to the episomal reprogramming method. Our findings offer important insights from a biobanking perspective, for which long-term reliability, integrity and reproducibility of hiPSCs are crucial.

摘要

自人类诱导多能干细胞(hiPSC)被发现以来,它们在生物医学研究中发挥了重要作用,尤其是在疾病建模、药物筛选和再生疗法等领域。近年来,由于hiPSC能够提供无需胚胎干细胞的分化细胞模型,其使用量显著增加。此外,从整合重编程方法向非整合重编程方法的转变也促进了其利用率的提高。这种转变将基因组改变的风险降至最低,提高了hiPSC的安全性和可靠性。然而,促成重编程成功的因素仍未得到很好的理解。在本研究中,我们对一系列起始源材料中最普遍的非整合重编程方法进行了比较分析,以评估它们对重编程成功率的影响。我们发现,虽然源材料对成功率没有显著影响,但相对于游离型重编程方法,仙台病毒重编程方法产生的成功率要高得多。我们的研究结果从生物样本库的角度提供了重要见解,对于hiPSC的长期可靠性、完整性和可重复性而言,这一点至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0beb/11756937/57b2965630a5/SCI2025-2223645.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0beb/11756937/10178bbfa2ec/SCI2025-2223645.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0beb/11756937/a5ac6be0727e/SCI2025-2223645.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0beb/11756937/1b37dc2008f8/SCI2025-2223645.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0beb/11756937/57b2965630a5/SCI2025-2223645.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0beb/11756937/10178bbfa2ec/SCI2025-2223645.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0beb/11756937/a5ac6be0727e/SCI2025-2223645.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0beb/11756937/1b37dc2008f8/SCI2025-2223645.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0beb/11756937/57b2965630a5/SCI2025-2223645.004.jpg

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