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Estimating residual undifferentiated cells in human chemically induced pluripotent stem cell derived islets using lncRNA as biomarkers.
Wu, Yandan; Zhang, Zhenzhen; Wu, Shuangshuang; Chen, Zhaolong; Pu, Yue.
Afiliación
  • Wu Y; Hangzhou Reprogenix Bioscience Co., Ltd, Hangzhou, 310023, China.
  • Zhang Z; Hangzhou Reprogenix Bioscience Co., Ltd, Hangzhou, 310023, China.
  • Wu S; Hangzhou Reprogenix Bioscience Co., Ltd, Hangzhou, 310023, China.
  • Chen Z; Hangzhou Reprogenix Bioscience Co., Ltd, Hangzhou, 310023, China.
  • Pu Y; Hangzhou Reprogenix Bioscience Co., Ltd, Hangzhou, 310023, China. yue.pu@reprogenix.com.
Sci Rep ; 13(1): 16435, 2023 09 30.
Article en En | MEDLINE | ID: mdl-37777562
Human pluripotent stem cells (hPSCs) can generate insulin-producing beta cells for diabetes treatment, but residual undifferentiated cells may cause tumors. We developed a highly sensitive assay to detect these cells in islet cells derived from human chemically induced pluripotent stem cells (hCiPSCs), which are transgene-free and safer. We used RNA-seq data to find protein-coding and non-coding RNAs that were only expressed in hCiPSCs, not in islet cells. We confirmed these biomarkers by RT-qPCR and ddPCR. We chose long non-coding RNA (lncRNA) markers, which performed better than protein-coding RNA markers. We found that LNCPRESS2, LINC00678 and LOC105370482 could detect 1, 1 and 3 hCiPSCs in 106 islet cells by ddPCR, respectively. We tested our method on several hCiPSC lines, which could quantify 0.0001% undifferentiated cell in 106 islet cells by targeting hCiPSCs-specific lncRNA transcripts, ensuring the safety and quality of hCiPSC-derived islet cells for clinical use.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Islotes Pancreáticos / Células Madre Pluripotentes Inducidas / ARN Largo no Codificante Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Islotes Pancreáticos / Células Madre Pluripotentes Inducidas / ARN Largo no Codificante Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article