Abstract
Background. Diabetes mellitus (DM) affects approximately 550 million individuals worldwide, with an estimated 18.6 million developing diabetic foot ulcers (DFU) annually due to poor vascularization and limited healing capacity. These ulcers present significant treatment challenges, exhibiting high recurrence rates and susceptibility to secondary infections, ultimately leading to amputation in approximately 20% of affected patients. The intricate ulcer microenvironment, which requires coordination among multiple cell types, complicates the identification of a single therapeutic target to enhance healing outcomes.
Aim. The purpose of this research was to identify potential multicellular reprogramming factors to induce healing in diabetic patients with non-healing DFU.
Materials and Methods. This research used single-cell RNA sequencing (scRNA-seq) datasets (GEO accession number GSE165816) to analyze gene expression alterations, biological processes, and cell-cell interactions in DFU with divergent healing outcomes. A cell type-specific gene regulatory network was leveraged to identify transcription factors (TF) with differential activity between healing and non-healing DFU. Subsequently, in silico TF overexpression simulations were conducted to identify TF combinations that maximize targeting upregulated genes in healing DFU across multiple cell types, with the goal of inducing cell state transitions from non-healing to healing states. Additional scRNA-seq and Visium transcriptomics datasets (GSE167406, GSE142471, GSE178758, GSE153596, and GSE241124) were analyzed to assess the similarity between the identified cell states in this research and their identified cell ones. Finally, spatial transcriptomics validation was performed using Xenium 10xGenomics technology to confirm the differential expression of the identified TFs in healing and non-healing DFU human skin samples.
Results. Comparative gene expression analysis between healing and non-healing DFU across various cell types identified 902 differentially expressed genes (log2FC ≥ 0.5). Several biological processes were significantly downregulated in the non-healing group, including vasculature development in vascular endothelial cells, endoderm formation in fibroblasts, and antimicrobial responses in immune cells. A healing-specific subset of myeloid cells (FPR1+) was found to receive signals from the ligand ANXA1, promoting healing, whereas TLR4+ myeloid cells were more abundant in the non-healing group, potentially contributing to impaired healing. Additionally, a healing-specific fibroblast subset was identified, exhibiting a gene signature associated with angiogenic potential, similar to an identified fibroblast subset in multiple other studies that support angiogenesis. Both the healing-specific myeloid and fibroblast subsets showed elevated expression of VEGFA, a key factor in blood vessel development. TF activity estimation revealed 387 TFs with altered activity in at least one cell type between healing and non-healing DFUs. Notably, NR3C1, encoding the glucocorticoid receptor, exhibited increased activity in the non-healing group, suggesting its involvement in healing impairment. In silico TF overexpression simulations identified a combination of TFs—FOSL2, CREB3L1, ETS1, and XBP1—that collectively targeted 66.5% of upregulated genes in healing DFU while affecting only 12.5% of downregulated genes. This TF combination effectively covered 95%, 90%, and 77% of upregulated genes involved in vasculature development (vascular endothelial cells), endoderm formation (fibroblasts), and antimicrobial response (myeloid cells), respectively. Spatial transcriptomics using Xenium confirmed the elevated expression of ETS1 and the reduced expression of NR3C1 in healing DFU samples. Furthermore, Visium-based spatial transcriptomics revealed that CREB3L1 and ETS1 exhibited the highest positive correlation with vasculature development, while XBP1 demonstrated the strongest correlation with antimicrobial response. Notably, ETS1 expression was upregulated in multiple cell types, including vascular endothelial cells, fibroblasts, and keratinocytes, highlighting its broader role in wound healing beyond vasculature development.
Conclusion. This study emphasizes the critical role of coordinated interactions among vascular endothelial cells, fibroblasts, and immune cells in the impaired revascularization observed in non-healing DFUs. Four TFs—FOSL2, CREB3L1, ETS1, and XBP1—were identified as potential reprogramming factors capable of restoring healing in non-healing DFUs by shifting the transcriptional states of key cell types. Upregulation of these TFs may facilitate the transition from non-healing to healing states. Further experimental validation is warranted to assess the therapeutic potential of these TF combinations in promoting DFU healing. This study provides novel insights into shared and cell type-specific transcriptional activities underlying DFU healing, paving the way for targeted interventions through TF-based therapies to improve patient outcomes.
School
School of Sciences and Engineering
Department
Biotechnology Program
Degree Name
PhD in Applied Science
Graduation Date
Winter 1-31-2025
Submission Date
1-30-2025
First Advisor
Hassan Azzazy
Second Advisor
Hossam Sharara
Third Advisor
Ahmed Abdellatif
Committee Member 1
Hassan El-Fawal
Committee Member 2
Asma Amleh
Committee Member 3
Ramy Aziz
Extent
124 p.
Document Type
Doctoral Dissertation
Institutional Review Board (IRB) Approval
Not necessary for this item
Recommended Citation
APA Citation
Abouhashem, A. S.
(2025).Identification of Skin Multicellular Reprogramming Factors as Potential Treatment for Non-Healing Diabetic Foot Ulcer [Doctoral Dissertation, the American University in Cairo]. AUC Knowledge Fountain.
https://fount.aucegypt.edu/etds/2483
MLA Citation
Abouhashem, Ahmed S.. Identification of Skin Multicellular Reprogramming Factors as Potential Treatment for Non-Healing Diabetic Foot Ulcer. 2025. American University in Cairo, Doctoral Dissertation. AUC Knowledge Fountain.
https://fount.aucegypt.edu/etds/2483
Supplementary tables
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