Gene expression profiles for in vitro human stem cell differentiation into osteoblasts and osteoclasts: a systematic review

Background There have been promising results published regarding the potential of stem cells in regenerative medicine. However, the vast variety of choices of techniques and the lack of a standard approach to analyse human osteoblast and osteoclast differentiation may reduce the utility of stem cell...

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Main Authors: Shahrul Hisham Zainal Ariffin, Ker Wei Lim, Rohaya Megat Abdul Wahab, Zaidah Zainal Ariffin, Rus Dina Rus Din, Muhammad Ashraf Shahidan, Anis Nabilah Johari, Intan Zarina Zainol Abidin
Format: Article
Language:English
Published: PeerJ Inc. 2022-10-01
Series:PeerJ
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Online Access:https://peerj.com/articles/14174.pdf
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author Shahrul Hisham Zainal Ariffin
Ker Wei Lim
Rohaya Megat Abdul Wahab
Zaidah Zainal Ariffin
Rus Dina Rus Din
Muhammad Ashraf Shahidan
Anis Nabilah Johari
Intan Zarina Zainol Abidin
author_facet Shahrul Hisham Zainal Ariffin
Ker Wei Lim
Rohaya Megat Abdul Wahab
Zaidah Zainal Ariffin
Rus Dina Rus Din
Muhammad Ashraf Shahidan
Anis Nabilah Johari
Intan Zarina Zainol Abidin
author_sort Shahrul Hisham Zainal Ariffin
collection DOAJ
description Background There have been promising results published regarding the potential of stem cells in regenerative medicine. However, the vast variety of choices of techniques and the lack of a standard approach to analyse human osteoblast and osteoclast differentiation may reduce the utility of stem cells as a tool in medical applications. Therefore, this review aims to systematically evaluate the findings based on stem cell differentiation to define a standard gene expression profile approach. Methods This review was performed following the PRISMA guidelines. A systematic search of the study was conducted by retrieving articles from the electronic databases PubMed and Web of Science to identify articles focussed on gene expression and approaches for osteoblast and osteoclast differentiation. Results Six articles were included in this review; there were original articles of in vitro human stem cell differentiation into osteoblasts and osteoclasts that involved gene expression profiling. Quantitative polymerase chain reaction (qPCR) was the most used technique for gene expression to detect differentiated human osteoblasts and osteoclasts. A total of 16 genes were found to be related to differentiating osteoblast and osteoclast differentiation. Conclusion Qualitative information of gene expression provided by qPCR could become a standard technique to analyse the differentiation of human stem cells into osteoblasts and osteoclasts rather than evaluating relative gene expression. RUNX2 and CTSK could be applied to detect osteoblasts and osteoclasts, respectively, while RANKL could be applied to detect both osteoblasts and osteoclasts. This review provides future researchers with a central source of relevant information on the vast variety of gene expression approaches in analysing the differentiation of human osteoblast and osteoclast cells. In addition, these findings should enable researchers to conduct accurately and efficiently studies involving isolated human stem cell differentiation into osteoblasts and osteoclasts.
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spelling doaj.art-68d99370a17449fe84c8d107c45ef1602023-12-02T21:55:34ZengPeerJ Inc.PeerJ2167-83592022-10-0110e1417410.7717/peerj.14174Gene expression profiles for in vitro human stem cell differentiation into osteoblasts and osteoclasts: a systematic reviewShahrul Hisham Zainal Ariffin0Ker Wei Lim1Rohaya Megat Abdul Wahab2Zaidah Zainal Ariffin3Rus Dina Rus Din4Muhammad Ashraf Shahidan5Anis Nabilah Johari6Intan Zarina Zainol Abidin7Department of Biological Sciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, MalaysiaDepartment of Biological Sciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, MalaysiaCentre of Family Dental Health, Faculty of Dentistry, Universiti Kebangsaan Malaysia, Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, MalaysiaSchool of Biology, Faculty of Applied Sciences, Universiti Teknologi MARA, Shah Alam, Selangor, MalaysiaForensic Science Programme, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Bangi, Selangor, MalaysiaDepartment of Biological Sciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, MalaysiaDepartment of Biological Sciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, MalaysiaCentre for Research and Graduate Studies, University of Cyberjaya, Cyberjaya, Selangor, MalaysiaBackground There have been promising results published regarding the potential of stem cells in regenerative medicine. However, the vast variety of choices of techniques and the lack of a standard approach to analyse human osteoblast and osteoclast differentiation may reduce the utility of stem cells as a tool in medical applications. Therefore, this review aims to systematically evaluate the findings based on stem cell differentiation to define a standard gene expression profile approach. Methods This review was performed following the PRISMA guidelines. A systematic search of the study was conducted by retrieving articles from the electronic databases PubMed and Web of Science to identify articles focussed on gene expression and approaches for osteoblast and osteoclast differentiation. Results Six articles were included in this review; there were original articles of in vitro human stem cell differentiation into osteoblasts and osteoclasts that involved gene expression profiling. Quantitative polymerase chain reaction (qPCR) was the most used technique for gene expression to detect differentiated human osteoblasts and osteoclasts. A total of 16 genes were found to be related to differentiating osteoblast and osteoclast differentiation. Conclusion Qualitative information of gene expression provided by qPCR could become a standard technique to analyse the differentiation of human stem cells into osteoblasts and osteoclasts rather than evaluating relative gene expression. RUNX2 and CTSK could be applied to detect osteoblasts and osteoclasts, respectively, while RANKL could be applied to detect both osteoblasts and osteoclasts. This review provides future researchers with a central source of relevant information on the vast variety of gene expression approaches in analysing the differentiation of human osteoblast and osteoclast cells. In addition, these findings should enable researchers to conduct accurately and efficiently studies involving isolated human stem cell differentiation into osteoblasts and osteoclasts.https://peerj.com/articles/14174.pdfMolecular analysisStem cellDifferentiation OsteoblastOsteoclastHuman
spellingShingle Shahrul Hisham Zainal Ariffin
Ker Wei Lim
Rohaya Megat Abdul Wahab
Zaidah Zainal Ariffin
Rus Dina Rus Din
Muhammad Ashraf Shahidan
Anis Nabilah Johari
Intan Zarina Zainol Abidin
Gene expression profiles for in vitro human stem cell differentiation into osteoblasts and osteoclasts: a systematic review
PeerJ
Molecular analysis
Stem cell
Differentiation
Osteoblast
Osteoclast
Human
title Gene expression profiles for in vitro human stem cell differentiation into osteoblasts and osteoclasts: a systematic review
title_full Gene expression profiles for in vitro human stem cell differentiation into osteoblasts and osteoclasts: a systematic review
title_fullStr Gene expression profiles for in vitro human stem cell differentiation into osteoblasts and osteoclasts: a systematic review
title_full_unstemmed Gene expression profiles for in vitro human stem cell differentiation into osteoblasts and osteoclasts: a systematic review
title_short Gene expression profiles for in vitro human stem cell differentiation into osteoblasts and osteoclasts: a systematic review
title_sort gene expression profiles for in vitro human stem cell differentiation into osteoblasts and osteoclasts a systematic review
topic Molecular analysis
Stem cell
Differentiation
Osteoblast
Osteoclast
Human
url https://peerj.com/articles/14174.pdf
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