The International Federation of Adipose Therapeutics (IFATS) and ISCT have established phenotypic and functional criteria for characterization of SVF as well as ASCs. As the IFATS and ISCT have stated, adipose-derived stem cell research takes place in a dynamic field that requires further standardization, and thus, guidance in support of safety and biologic clarifications for clinical practices was provided by IFATS and ISCT (Bourin et al., 2013). The final aim of those instructions is to develop efficacious adipose tissue-derived cell therapies that benefit society in an optimal manner.
The initial cell fraction that is gained after tissue processing is known as the stromal vascular fraction, which is separated from mature adipocytes by differential centrifugation. The SFV contains a heterogeneous mesenchymal cell population, e.g., cells of endothelial, hematopoietic and pericytic origin and many others (Table 2). The adipose tissue collection site and the digestion protocol may affect the heterogeneity of SVF cell types. When SVF cells are seeded into cell culture, a subset of elongated cells begins to adhere to the tissue culture plastic ware that select the ASCs.
Table 2. Cell populations in stromal vascular fraction. Table modified from Bourin et al. (Bourin et al., 2013).
Hematopoietic-lineage cell Stem and progenitor cells <0.1%
Granulocytes 10–15%
Monocytes 5–15%
Lymphocytes 10–15%
Endothelial cells 10–20%
Pericytes 3–5%
Stem cells 15–30%
2.5.1 Surface marker expression of ASCs
No single markers are available for recognition of ASCs, but instead, the use of a multi-color identification panel of several cell surface markers is recommended.
Additionally, a viability marker is also suggested to eliminate dead or apoptotic cells induced by the isolation procedures. According to recommendations by the IFATS and ISCT, ASCs should be negative (<2%) for hematopoietic markers such as CD14 or CD11b, CD45, CD86, and HLA-DR and positive (>90%) for stromal markers such as CD13, CD73, CD90 and CD105. Similar to ASCs, BM-MSCs should be negative for hemopoietic markers CD11b and CD45, and express stromal markers CD13, CD73, CD90 and CD105. To distinguish ASCs from BM-MSC, use of two other markers is proposed, i.e., CD36 (fatty acid translocase) and CD106 (VCAM- 1). In contrast to BM-MSCs it has been reported that ASCs do not express CD106 but are positive for CD34 (Katz et al., 2005; Maumus et al., 2011; Pachon-Pena et al., 2011). However, the expression of CD34 is greatly dependent on the in vitro culture period. It is generally expressed during the early phase of culture, but its expression decreases with continued cell division (Maumus et al., 2011; Mitchell et al., 2006). In contrast to ASCs, BM-MSCs do not express CD34 (Liao and Chen, 2014). Of note,
CD34 is a marker that is generally used for hematopoietic stem and progenitor cells (Bensinger et al., 1993; Trischmann et al., 1993) but is also highly expressed in vascular endothelial cells and their precursors (Asahara et al., 1997; Rafii et al., 1994). Multiple classes of CD34 antibodies exist that recognize unique immunogens. Consequently, the choice of CD34 antibody can substantially influence the signal intensity detected on a given cell population, and therefore the use of class III CD34 antibodies is highly recommended. Moreover, histological analysis of adipose tissue has revealed that CD34 positive cells are widely distributed among adipocytes and are primarily associated with vascular structures (Traktuev et al., 2008). Although small numbers of these cells are probably CD31 positive capillary endothelial cells, a CD34+/CD31- cell population of pericytic origin may be derived from adipose tissue (Johal et al., 2015).
Furthermore, additional markers will still strengthen the characterization. Bourin et al. suggested that CD10, CD26 (DPPIV), CD49d (VLA4), CD49e (VLA5) and CD146 (MUC18) can be added as additional positive markers but with variable expression depending on the donor or culture passage. In contrast, minor expression (<2%) levels can be observed with additional negative markers CD3, CD11b (Mac- 1), CD49f (VLA6) and Podocalyxin-like protein. However, when ASCs are defined using basic surface antigens, it is likely that ASC populations will display heterogeneity for additional surface antigens (Pachon-Pena et al., 2011). In contrast, flow cytometry analysis can be considered as a definition of the relative homogeneity or alternatively, the relative heterogeneity of the ASCs. Guidelines for characterization of ASCs and SVF are collected in Table 3.
Of note, these characterization criteria were originally determined for ASCs cultured in traditional FBS culture medium, but the IFATS and ISCT do not take a stand on the effect of serum conditions on cell surface marker expression. For instance, Bourin et al. stated that one main difference between SVF cell and ASC populations is the high level of CD45+ cells in the SVF cells and a notably low or undetectable level in ASCs. This definition applies to ASC cultures in FBS or HS conditions, but somewhat higher expression of CD45 has been observed in defined XF/SF conditions (Rajala et al., 2010). Overall, cell phenotypes still remain highly similar when cultured in different serum conditions or defined XF/SF conditions (Al-Saqi et al., 2014a; Rajala et al., 2010).
In addition to cell surface markers, the fibroblastoid colony-forming unit (CFU- F) assay is recommended for use in defining the number of progenitor cells. The number of colonies allows for an estimation of the rate of doubling of the population during the primary phase of culture. The information gained from CFU-F could be
particularly useful in enhancing the quality control of any resulting cell therapy product (Bourin et al., 2013).
Table 3. Guidelines for characterization of adipose tissue-derived cells. Modified from Bourin et al.
(Bourin et al., 2013).
Feature Assay Cells of SVF ASCs
Immunophenotype Flow cytometry
Primary stable positive markers for stromal cells: CD13, CD29, CD44, CD73, CD90 (>40%), CD34 (<20%) Primary negative markers for stromal cells: CD31 (<20%), CD45 (<50%).
Primary stable positive markers: CD13, CD29, CD44, CD73, CD90, CD105 (>80% in ASC)
Primary unstable positive marker: CD34 (present at variable levels)
Primary negative markers:
CD31, CD45, CD235a (<2%)
Secondary other positive markers: CD10, CD26, CD36, CD49d, CD49e Secondary other low or negative markers: CD3, CD11b, CD49f, CD106, PODXL
Adipogenic differentiation
Histochemistry, RT- PCR, Western blot immunoblot, ELISA
Histology: oil red O, Nile red or stain specific for lipid inclusions
Biomarkers: adiponectin, C/EBPα, FABP4, leptin, PPARγ
Osteogenic differentiation
Histology: alizarin red or von Kossa
Biomarkers: alkaline phosphatase, bone sialoprotein, osteocalcin, osterix, runx2
Chondrogenic differentiation
Histology: alcian blue or safranin O
Biomarkers: aggrecan, collagen type II, Sox 9 Proliferation and
frequency CFU-F Anticipated frequency:
>1% Anticipated frequency: >5%
2.5.2 Differentiation potential of ASCs
One of the characterization criteria of ASCs is their multipotency and ability to give rise to osteoblastic, chondrocytic and adipocytic lineages (Gimble and Guilak, 2003;
Zuk et al., 2001; Zuk et al., 2002). However, as demonstrated with BM-MSCs, long- term ex vivo culture of MSCs may lead to a loss of osteogenic differentiation capacity (Banfi et al., 2000; Noer et al., 2009). A recent study compared the impact of aging on the regenerative properties of MSCs from different tissue sources and showed that BM-MSCs may display impaired proliferation and chondrogenic response, whereas ASCs exhibited no negative effects on cell differentiation (Beane et al., 2014). This same study also demonstrated that the osteogenic differentiation potential should be retained after long-term ex vivo culture with MSCs from different tissue sources. Nevertheless, protocols that induce cell differentiation have been published extensively. Although a qualitative evaluation of cell differentiation based on histochemistry is helpful, the IFATS and ISCT have stated that it may not be sufficient for comprehensive analysis. A better approach for characterization of differentiation is the use of quantitative methods such as RT-PCR, western blot immunoblot, and ELISA assay. A selection of lineage-specific gene or protein biomarkers can be analyzed based on published data: for adipogenesis adiponectin (GBP-28), aP2, leptin, PPAR-γ, glycerol 3 phosphate dehydrogenase (GPDH); for chondrogenesis, aggrecan (CSPCP), collagen type II, Sox9; for osteogenesis, alkaline phosphatase (ALP), bone sialoprotein (BSP), OC, OPN, osterix (OSX), RUNX-2, and DLX5 (Erickson et al., 2002; Seda Tigli et al., 2009; G. Yu et al., 2010; Zuk et al., 2001; Zuk et al., 2002). These biomarkers analyzed by quantitative methods provide reliable indications of cell differentiation.