Tissue Source and Cell Expansion Condition Influence Phenotypic Changes of Adipose-Derived Stem Cells.
Lauren H MangumShanmugasundaram NatesanRandolph StoneNicole L WriceDavid A LarsonKyle F FlorellBarbara A ChristyMaryanne C HerzigAndrew P CapRobert J ChristyPublished in: Stem cells international (2017)
Stem cells derived from the subcutaneous adipose tissue of debrided burned skin represent an appealing source of adipose-derived stem cells (ASCs) for regenerative medicine. Traditional tissue culture uses fetal bovine serum (FBS), which complicates utilization of ASCs in human medicine. Human platelet lysate (hPL) is one potential xeno-free, alternative supplement for use in ASC culture. In this study, adipogenic and osteogenic differentiation in media supplemented with 10% FBS or 10% hPL was compared in human ASCs derived from abdominoplasty (HAP) or from adipose associated with debrided burned skin (BH). Most (95-99%) cells cultured in FBS were stained positive for CD73, CD90, CD105, and CD142. FBS supplementation was associated with increased triglyceride content and expression of adipogenic genes. Culture in hPL significantly decreased surface staining of CD105 by 31% and 48% and CD142 by 27% and 35% in HAP and BH, respectively (p < 0.05). Culture of BH-ASCs in hPL also increased expression of markers of osteogenesis and increased ALP activity. These data indicate that application of ASCs for wound healing may be influenced by ASC source as well as culture conditions used to expand them. As such, these factors must be taken into consideration before ASCs are used for regenerative purposes.
Keyphrases
- wound healing
- endothelial cells
- stem cells
- adipose tissue
- poor prognosis
- induced pluripotent stem cells
- mesenchymal stem cells
- pluripotent stem cells
- cell therapy
- induced apoptosis
- soft tissue
- type diabetes
- nk cells
- nlrp inflammasome
- electronic health record
- bone marrow
- gene expression
- signaling pathway
- binding protein
- dna methylation
- cell proliferation
- deep learning
- skeletal muscle
- long non coding rna
- climate change
- single cell
- cell cycle arrest
- artificial intelligence