Differential Marker Expression between Keratinocyte Stem Cells and Their Progeny Generated from a Single Colony.

Dema Ali, Dana Majed Alhattab, Hanan Jafar, Malak Alzubide, Nour Sharar, Salwa Bdour, Abdalla Awidi

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


The stemness in keratinocyte stem cells (KSCs) is determined by their gene expression patterns. KSCs are crucial in maintaining epidermal homeostasis and wound repair and are widely used candidates for therapeutic applications. Although several studies have reported their positive identifiers, unique biomarkers for KSCs remain elusive. Here, we aim to identify potential candidate stem cell markers. Human epidermal keratinocytes (HEKs) from neonatal foreskin tissues were isolated and cultured. Single-cell clonal analysis identified and characterized three types of cells: KSCs (holoclones), transient amplifying cells (TACs; meroclones), and differentiated cells (DSCs; paraclones). The clonogenic potential of KSCs demonstrated the highest proliferation potential of KSCs, followed by TACs and DSCs, respectively. Whole-transcriptome analysis using microarray technology unraveled the molecular signatures of these cells. These results were validated by quantitative real-time polymerase chain reaction and flow cytometry analysis. A total of 301 signature upregulated and 149 downregulated differentially expressed genes (DEGs) were identified in the KSCs, compared to TACs and DSCs. Furthermore, DEG analyses revealed new sets of genes related to cell proliferation, cell adhesion, surface makers, and regulatory factors. In conclusion, this study provides a useful source of information for the identification of potential SC-specific candidate markers.
Original languageEnglish (US)
Pages (from-to)10810
JournalInternational journal of molecular sciences
Issue number19
StatePublished - Oct 13 2021

ASJC Scopus subject areas

  • Organic Chemistry
  • Spectroscopy
  • Molecular Biology
  • Catalysis
  • Physical and Theoretical Chemistry
  • Inorganic Chemistry
  • Computer Science Applications


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