APMAdvances in Precision Medicine2424-85922424-9106WHIOCE PUBLISHING PTE. LTD.10.18063/APM.v11i4.1860ArticleSample-level Single-cell Transcriptomic Analysis Identifies Molecular Features Associated with Non-healing Diabetic Foot Ulcershttps://artdesignp.com/journal/APM/11/4/10.18063/APM.v11i4.1860LianJiaqi,RenChunyan,ZouXinyu20261142026-04-26Background: Diabetic foot ulcers (DFUs) frequently fail to heal, but the local cellular programs associated with non-healing remain incompletely resolved. We performed a conservative secondary analysis of public single-cell RNA-seq count matrices to identify sample-level signatures and candidate transcripts associated with non-healing DFU. Methods: Raw count matrices from GSE165816 were summarized at the sample level. The primary analysis focused on 33 foot-skin specimens, including 9 healing DFU, 5 non-healing DFU, 8 diabetic non-DFU, and 11 non-diabetic foot-skin samples. Marker-based signatures representing fibroblast activation, extracellular matrix remodeling, angiogenesis, keratinocyte activation, and immune states were calculated from log2 counts per million. Healing and non-healing DFU samples were compared using Welch statistics at the pseudobulk level. Results: The analyzed foot-skin matrices contained 94,325 cells. Non-healing DFU samples showed broad remodeling of immune- and matrix-associated pseudobulk expression. A compact data-driven marker panel (IGHG3, IGLC2, IGKC, IGHG1, MMP3, IGHA1) separated healing from non-healing DFU samples with an apparent sample-level AUC of 0.89, although this estimate should be interpreted cautiously because of the modest number of independent DFU specimens. Conclusion: Public single-cell DFU data support the presence of distinct sample-level molecular states in non-healing ulcers. The analysis prioritizes transcripts and signatures for low-cost follow-up studies while emphasizing the need for patient-level validation.Diabetic foot ulcer,Single-cell RNA sequencing,Non-healing wound,Pseudobulk,Biomarker,Extracellular matrix

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