Research Paper Volume 16, Issue 8 pp 6883—6897

PROS1 is a crucial gene in the macrophage efferocytosis of diabetic foot ulcers: a concerted analytical approach through the prisms of computer analysis

Hongshuo Shi1, *, , Zhicheng Zhang2, *, , Xin Yuan1, , Guobin Liu1, , Weijing Fan1, , Wenbo Wang3, ,

  • 1 Department of Peripheral Vascular Surgery, Institute of Surgery of Traditional Chinese Medicine, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
  • 2 Dongying People’s Hospital (Dongying Hospital of Shandong Provincial Hospital Group), Dongying, Shandong, China
  • 3 The Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China
* Co-first author

Received: October 26, 2023       Accepted: March 18, 2024       Published: April 10, 2024
How to Cite

Copyright: © 2024 Shi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Background: Diabetic foot ulcers (DFUs) pose a serious long-term threat because of elevated mortality and disability risks. Research on its biomarkers is still, however, very limited. In this paper, we have effectively identified biomarkers linked with macrophage excretion in diabetic foot ulcers through the application of bioinformatics and machine learning methodologies. These findings were subsequently validated using external datasets and animal experiments. Such discoveries are anticipated to offer novel insights and approaches for the early diagnosis and treatment of DFU.

Methods: In this work, we used the Gene Expression Omnibus (GEO) database’s datasets GSE68183 and GSE80178 as the training dataset to build a gene model using machine learning methods. After that, we used the training and validation sets to validate the model (GSE134431). On the model genes, we performed enrichment analysis using both gene set variant analysis (GSVA) and gene set enrichment analysis (GSEA). Additionally, the model genes were subjected to immunological association and immune function analyses.

Results: In this study, PROS1 was identified as a potential key target associated with macrophage efflux in DFU by machine learning and bioinformatics approaches. Subsequently, the key biomarker status of PROS1 in DFU was also confirmed by external datasets. In addition, PROS1 also plays a key role in macrophage exudation in DFU. This gene may be associated with macrophage M1, CD4 memory T cells, naïve B cells, and macrophage M2, and affects IL-17, Rap1, hedgehog, and JAK-STAT signaling pathways.

Conclusions: PROS1 was identified and validated as a biomarker for DFU. This finding has the potential to provide a target for macrophage clearance of DFU.


DFU: Diabetic foot ulcer; GEO: Gene Expression Omnibus; AGEs: Advanced glycation end products; PCA: Principal component analysis; GSVA: Gene Set Variation Analysis; WGCNA: Weighted Gene Co-Expression Network Analysis; GLM: Generalized Linear Model; XGB: Extreme Gradient Boosting; SVM: Support Vector Machine; RF: Random Forest; ROC: Receiver operating characteristic; KEGG: Kyoto Encyclopedia of Genes and Genomes; GO: Gene Ontology; MERGs: Related genes of macrophage efferocytosis; RTK: Receptor tyrosine kinase; TAM: Tyro3/Axl/Mer.