# MicroRNA-133b Inhibition Restores EGFR Expression and Accelerates Diabetes-Impaired Wound Healing

Authors: Haobo Zhong; Jin Qian; Zhihong Xiao; Yan Chen; Xiangchun He; Chunhan Sun; Zhiming Zhao
Journal: Oxidative Medicine and Cellular Longevity
 (2021)

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## Abstract

Diabetic foot ulcers (DFUs) are caused by impairments in peripheral blood vessel angiogenesis and represent a great clinical challenge. Although various innovative techniques and drugs have been developed for treating DFUs, therapeutic outcomes remain unsatisfactory. Using the GEO database, we obtained transcriptomic microarray data for DFUs and control wounds and detected a significant downregulation of epidermal growth factor receptor (EGFR) in DFUs. We cultured human umbilical vein endothelial cells (HUVECs) and noted downregulated EGFR expression following high-glucose exposure in vitro. Further, we observed decreased HUVEC proliferation and migration and increased apoptosis after shRNA-mediated EGFR silencing in these cells. In mice, EGFR inhibition via focal EGFR-shRNA injection delayed wound healing. Target prediction analysis followed by dual-luciferase reporter assays indicated that microRNA-133b (miR-133b) is a putative upstream regulator of EGFR expression. Increased miR-133b expression was observed in both glucose-treated HUVECs and wounds from diabetes patients, but no such change was observed in controls. miR-133b suppression enhanced the proliferation and angiogenic potential of cultured HUVECs and also accelerated wound healing. Although angiogenesis is not the sole mechanism affected in DFU, these findings suggest that the miR-133b-induced downregulation of EGFR may contribute to delayed wound healing in diabetes. Hence, miR-133b inhibition may be a useful strategy for treating diabetic wounds.


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## Body

## 1. Introduction

Diabetic wounds cause serious economic, physical, and psychosocial burdens among diabetes patients and often show poor healing due to underlying vascular lesions [1, 2]. Diabetic foot ulcers (DFUs) are a major health problem, affecting 9.1–26.1 million individuals with diabetes globally every year. DFUs are characterized by impairments in angiogenesis—a key step in wound healing [3–5]. Given how critical the vascular endothelium is for wound healing, the identification of mechanisms preventing a normal angiogenic response in DFUs is crucial for developing effective treatments.The epidermal growth factor (EGF) receptor (EGFR; ErbB-1; HER1 in humans) is primarily expressed in epithelial cells and promotes cellular proliferation, migration, and survival [6, 7]. Moreover, the interaction between EGFR and its main ligand EGF results in EGFR signaling, which can also promote angiogenesis [7, 8]. There is robust evidence that angiogenesis is also modulated by several miRNAs that influence gene expression in endothelial cells [9–13]. For instance, a study showed that exosomal miR-21-5p acts on endothelial cells to promote vascular repair by suppressing the expression of thrombospondin-1, an angiogenesis inhibitor [14].In the present study, we analyzed available microarray data and detected a significant downregulation ofEGFR expression in DFUs. Based on this finding, we explored miRNA databases to identify putative upstream regulators of EGFR expression. Further, we conducted experiments in human vascular endothelial cells (HUVECs) and diabetic wounds in mice to assess how miR-133b affects endothelial cell function and wound healing.


## 2. Materials and Methods

### 2.1. Microarray and Bioinformatics

Microarray data for six and three individuals with and without diabetes, respectively, were obtained from a microRNA database in the Gene Expression Omnibus repository (GEO,http://www.ncbi.nlm.nih.gov/geo;GSE80178). The identification of differentially expressed genes (DEGs) was performed using the inbuilt GEO2R function at default settings based on a threshold of p<0.05. Changes in mRNA expression were visualized using heatmaps created with the R package pheatmap. Subsequently, a protein-protein interaction (PPI) network was created after importing DEGs into the STRING database. Cytoscape 3.7.2 was used to calculate the degree, betweenness, and closeness of PPI genes with the help of the CentiScaPe 2.2. plugin. Finally, GO and KEGG pathway enrichment analyses were performed using DAVID [15], and the top three terms within each GO category and KEGG pathways were identified. The top ten genes (highest degree values) were visualized with ggplot2 on R [16] and considered hub genes. GOplot was used to visualize enrichment analysis results [17]. Chromosomal locations and the degree of connectivity for the top 50 DEGs were illustrated using the circlize package in R [18].


### 2.2. Ethics Approval

Both human and animal studies were conducted after approval from the Committees of Clinical Ethics of Huizhou First Hospital. All human studies were performed after obtaining informed consent from each participant.


### 2.3. Blood and Skin Samples

Peripheral blood samples were collected from patients at the Huizhou First Hospital (12 healthy volunteers and 12 with DFUs) between September 2016 and October 2018. Skin samples were also collected from patients at this center during the same period (6 DFU patients and 6 emergency foot trauma patients without diabetes). mRNA expression was examined in all blood and skin samples.


### 2.4. Murine Wound Model

Male C57BL/6J mice (age, 6–7 weeks; weight, 25–30 g) and male db/db mice (BKS.Cg-Dock7m +/+ Leprdb/J strain) were procured. All db/db mice were examined and found to be mildly to severely diabetic.Before the induction of the wound model, all animals were anesthetized using pentobarbital sodium (50 mg/kg i.p.; Sigma-Aldrich, MO, USA). After shaving, full-thickness excisional skin wounds (diameter, 10 mm) were induced on their upper back. The mice were subsequently randomized into four groups (n=6 mice/group) and received subcutaneous injections of EGFR shRNA, negative control (NC) shRNA, or mi-133b agonist/antagonist mimics at four sites surrounding the wound (25 μL/site). The injections were administered on days 0, 3, 5, 7, 9, and 11 postwound induction. On days 0, 3, 5, 7, 10, and 14, the wounds were imaged and measured using a caliper rule.


### 2.5. Wound Closure

The wound closure rate was calculated on days 0, 3, 5, 7, 10, and 14 postwound induction using digital photographs, which were then analyzed using ImageJ software (NIH, USA).


### 2.6. Cell Culture and Transfection

HUVECs (Cell Bank of the Chinese Academy of Sciences, Shanghai, China) were cultured in RPMI 1640 medium (Thermo Fisher Sci., Inc., MA, USA) containing 10% FBS (Gibco, New York, USA). Transfection was performed using Lipofectamine 3000 (Thermo Fisher Sci., Inc.) based on the manufacturer’s instructions in cultured cells (37°C; 5% CO2 and 95% humidity). The agomiR-133b and antagomiR-133b constructs (100 nM) were obtained from GenePharma (Shanghai, China) and transfected into cells. EGFR-specific shRNA (shEGFR) was cloned into pSicoR vectors. For glucose stimulation assays, HUVECs were cultured in 20 mM D-glucose for 72 h.


### 2.7. CCK-8 Assay

HUVECs (5×103) were cultured for 24, 48, or 72 h in 96-well plates. Subsequently, CCK-8 reagent (#96992, Sigma-Aldrich, MO, USA) was added to each well containing serum-free medium for 2 h. Absorbance was measured at 450 nm.


### 2.8. Transwell Migration Assay

Transwell inserts (#140629, Thermo Fisher Sci.) with 8μm pore filters were used to examine transwell migration. HUVECs in low serum (5% FBS) medium were added to the upper chamber (1×104 cells per insert). Complete medium (500 μL; containing 10% FBS) supplemented with different treatment agents was added to the lower chamber. After 12 h of incubation, cells adhering to the upper membrane surface were expunged using cotton swabs. Cells showing migration onto the lower surface were stained using 0.5% crystal violet, and counts were obtained from three random fields.


### 2.9. Luciferase Assay

Positions 50–56 in the 3′UTR of EGFR mRNA that contained the putative miR-133b target site were identified using TargetScan. Subsequently, using cDNA obtained from HUVECs, this region was PCR-amplified and ligated into a pGL3-basic vector (Promega, Madison, WI, USA). The pGL3-EGFR 3′UTR-mutant (Mut) construct was synthesized by inserting two site mutations within the potential target sequence of miR-133b using the QuickChange Site-Directed Mutagenesis kit (Agilent Technologies, Inc., CA, USA). These two constructs were independently transfected into HUVECs (200 ng) along with the Renilla plasmid using Lipofectamine 3000 (Thermo Fisher Sci., Inc.). Subsequently, miR-NC mimic, agomiR-133b, or antagomiR-133b (48 h at 37°C; 10 nM) were transfected into cells using kits supplied by Shanghai GenePharma Co., Ltd. Relative luciferase activity was evaluated based on the firefly/Renilla activity ratio using a dual-luciferase reporter assay system (Promega).


### 2.10. qRT-PCR Analysis

First, total RNA was isolated from cells and tissues using the TRIzol reagent (Thermo Fisher Sci., Inc.) and then reverse transcribed into cDNA using the ReverTra Ace qPCR RT Master Mix (Toyobo Life Science, Tokyo, Japan) based on the manufacturer’s instructions (15 min at 42°C, followed by 5 min at 98°C; reactionvolume=20 μL). The qPCR thermocycling conditions were as follows: initial denaturation, 95°C for 30 s; 40 cycles at 95°C for 5 s, and 60°C for 30 s (reaction volume=25 μL). GAPDH was selected as the internal control. Relative miRNA expression was calculated using the 2-△△Ct method. The primer sequences used were as follows:miR-133b: F, GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACTAGCTG, R, CCGTTTGGTCCCCTTCAAC;Bcl-2: F, GATAACGGAGGCTGGGATGC, R, TCACTTGTGGCCCAGATAGG; Bax: F, CCCTTTTGCTTCAGGGTTTC, R, GAGACACTCGCTCAGCTTCTTG; Cyclin D1: F, TTGCCCTCTGTGCCACAGAT, R, TCAGGTTCAGGCCTTGCACT; Cyclin D3: F, CTGGCCATGAACTACCTGGA, R, CCAGCAAATCATGTGCAATC; EGFR: F, GGTCTT GAAGGCTGTCCAACG, R, CCTCAAGAGAGCTTGGTTGGG; GAPDH: F, CCGTTGAATTTGCCGTGA, R, TGATGACCCTTTTGGCTCCC.


### 2.11. Statistical Analyses

All experiments were conducted in triplicate. Data are presented as themean±SD. Student’s t-tests or one-way ANOVAs with Tukey’s post hoc test were applied for comparing two or more than two groups, respectively. GraphPad Prism 8.0 was used for all analyses. p values < 0.05 were considered significant (∗p<0.05, ∗∗p<0.01, and ∗∗∗p<0.001).


## 2.1. Microarray and Bioinformatics

Microarray data for six and three individuals with and without diabetes, respectively, were obtained from a microRNA database in the Gene Expression Omnibus repository (GEO,http://www.ncbi.nlm.nih.gov/geo;GSE80178). The identification of differentially expressed genes (DEGs) was performed using the inbuilt GEO2R function at default settings based on a threshold of p<0.05. Changes in mRNA expression were visualized using heatmaps created with the R package pheatmap. Subsequently, a protein-protein interaction (PPI) network was created after importing DEGs into the STRING database. Cytoscape 3.7.2 was used to calculate the degree, betweenness, and closeness of PPI genes with the help of the CentiScaPe 2.2. plugin. Finally, GO and KEGG pathway enrichment analyses were performed using DAVID [15], and the top three terms within each GO category and KEGG pathways were identified. The top ten genes (highest degree values) were visualized with ggplot2 on R [16] and considered hub genes. GOplot was used to visualize enrichment analysis results [17]. Chromosomal locations and the degree of connectivity for the top 50 DEGs were illustrated using the circlize package in R [18].


## 2.2. Ethics Approval

Both human and animal studies were conducted after approval from the Committees of Clinical Ethics of Huizhou First Hospital. All human studies were performed after obtaining informed consent from each participant.


## 2.3. Blood and Skin Samples

Peripheral blood samples were collected from patients at the Huizhou First Hospital (12 healthy volunteers and 12 with DFUs) between September 2016 and October 2018. Skin samples were also collected from patients at this center during the same period (6 DFU patients and 6 emergency foot trauma patients without diabetes). mRNA expression was examined in all blood and skin samples.


## 2.4. Murine Wound Model

Male C57BL/6J mice (age, 6–7 weeks; weight, 25–30 g) and male db/db mice (BKS.Cg-Dock7m +/+ Leprdb/J strain) were procured. All db/db mice were examined and found to be mildly to severely diabetic.Before the induction of the wound model, all animals were anesthetized using pentobarbital sodium (50 mg/kg i.p.; Sigma-Aldrich, MO, USA). After shaving, full-thickness excisional skin wounds (diameter, 10 mm) were induced on their upper back. The mice were subsequently randomized into four groups (n=6 mice/group) and received subcutaneous injections of EGFR shRNA, negative control (NC) shRNA, or mi-133b agonist/antagonist mimics at four sites surrounding the wound (25 μL/site). The injections were administered on days 0, 3, 5, 7, 9, and 11 postwound induction. On days 0, 3, 5, 7, 10, and 14, the wounds were imaged and measured using a caliper rule.


## 2.5. Wound Closure

The wound closure rate was calculated on days 0, 3, 5, 7, 10, and 14 postwound induction using digital photographs, which were then analyzed using ImageJ software (NIH, USA).


## 2.6. Cell Culture and Transfection

HUVECs (Cell Bank of the Chinese Academy of Sciences, Shanghai, China) were cultured in RPMI 1640 medium (Thermo Fisher Sci., Inc., MA, USA) containing 10% FBS (Gibco, New York, USA). Transfection was performed using Lipofectamine 3000 (Thermo Fisher Sci., Inc.) based on the manufacturer’s instructions in cultured cells (37°C; 5% CO2 and 95% humidity). The agomiR-133b and antagomiR-133b constructs (100 nM) were obtained from GenePharma (Shanghai, China) and transfected into cells. EGFR-specific shRNA (shEGFR) was cloned into pSicoR vectors. For glucose stimulation assays, HUVECs were cultured in 20 mM D-glucose for 72 h.


## 2.7. CCK-8 Assay

HUVECs (5×103) were cultured for 24, 48, or 72 h in 96-well plates. Subsequently, CCK-8 reagent (#96992, Sigma-Aldrich, MO, USA) was added to each well containing serum-free medium for 2 h. Absorbance was measured at 450 nm.


## 2.8. Transwell Migration Assay

Transwell inserts (#140629, Thermo Fisher Sci.) with 8μm pore filters were used to examine transwell migration. HUVECs in low serum (5% FBS) medium were added to the upper chamber (1×104 cells per insert). Complete medium (500 μL; containing 10% FBS) supplemented with different treatment agents was added to the lower chamber. After 12 h of incubation, cells adhering to the upper membrane surface were expunged using cotton swabs. Cells showing migration onto the lower surface were stained using 0.5% crystal violet, and counts were obtained from three random fields.


## 2.9. Luciferase Assay

Positions 50–56 in the 3′UTR of EGFR mRNA that contained the putative miR-133b target site were identified using TargetScan. Subsequently, using cDNA obtained from HUVECs, this region was PCR-amplified and ligated into a pGL3-basic vector (Promega, Madison, WI, USA). The pGL3-EGFR 3′UTR-mutant (Mut) construct was synthesized by inserting two site mutations within the potential target sequence of miR-133b using the QuickChange Site-Directed Mutagenesis kit (Agilent Technologies, Inc., CA, USA). These two constructs were independently transfected into HUVECs (200 ng) along with the Renilla plasmid using Lipofectamine 3000 (Thermo Fisher Sci., Inc.). Subsequently, miR-NC mimic, agomiR-133b, or antagomiR-133b (48 h at 37°C; 10 nM) were transfected into cells using kits supplied by Shanghai GenePharma Co., Ltd. Relative luciferase activity was evaluated based on the firefly/Renilla activity ratio using a dual-luciferase reporter assay system (Promega).


## 2.10. qRT-PCR Analysis

First, total RNA was isolated from cells and tissues using the TRIzol reagent (Thermo Fisher Sci., Inc.) and then reverse transcribed into cDNA using the ReverTra Ace qPCR RT Master Mix (Toyobo Life Science, Tokyo, Japan) based on the manufacturer’s instructions (15 min at 42°C, followed by 5 min at 98°C; reactionvolume=20 μL). The qPCR thermocycling conditions were as follows: initial denaturation, 95°C for 30 s; 40 cycles at 95°C for 5 s, and 60°C for 30 s (reaction volume=25 μL). GAPDH was selected as the internal control. Relative miRNA expression was calculated using the 2-△△Ct method. The primer sequences used were as follows:miR-133b: F, GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACTAGCTG, R, CCGTTTGGTCCCCTTCAAC;Bcl-2: F, GATAACGGAGGCTGGGATGC, R, TCACTTGTGGCCCAGATAGG; Bax: F, CCCTTTTGCTTCAGGGTTTC, R, GAGACACTCGCTCAGCTTCTTG; Cyclin D1: F, TTGCCCTCTGTGCCACAGAT, R, TCAGGTTCAGGCCTTGCACT; Cyclin D3: F, CTGGCCATGAACTACCTGGA, R, CCAGCAAATCATGTGCAATC; EGFR: F, GGTCTT GAAGGCTGTCCAACG, R, CCTCAAGAGAGCTTGGTTGGG; GAPDH: F, CCGTTGAATTTGCCGTGA, R, TGATGACCCTTTTGGCTCCC.


## 2.11. Statistical Analyses

All experiments were conducted in triplicate. Data are presented as themean±SD. Student’s t-tests or one-way ANOVAs with Tukey’s post hoc test were applied for comparing two or more than two groups, respectively. GraphPad Prism 8.0 was used for all analyses. p values < 0.05 were considered significant (∗p<0.05, ∗∗p<0.01, and ∗∗∗p<0.001).


## 3. Results and Discussion

### 3.1.EGFR Expression Is Decreased in Diabetic Foot Ulcers

To search for DEGs in DFUs, the GSE80178 dataset, containing information on six DFUs and three nondiabetic foot skin samples, was retrieved from the GEO database. In total, there were 326 DEGs (88 upregulated and 238 downregulated in the DFU specimens) (Figures1(a) and 1(b)). The degree centrality for the top 50 degree-filtered genes in the PPI network, as well as their chromosomal positions, is shown in Figure 1(c). The top 10 hub genes were EGFR, CD44, HGF, TFRC, LAMA4, FAS, LAMB3, CLCA2, DSG3, and PKP1 (Figure 1(d)), of which the first three had the highest degree, betweenness, and closeness (EGFR, CD44, and HGF). The genes involved in the top three modules showing the highest MCODE scores were subjected to enrichment analysis. The DEGs were enriched under the following terms in the GO analysis: biological process: “cell adhesion,” “biological adhesion,” and “cell-cell adhesion”; molecular function: “receptor binding,” “protein complex binding,” and “intermediate filament binding”; and cellular component: “extracellular region,” “cell junction,” and “anchoring junction.” In turn, the top three KEGG pathways enriched in these DEGs were “proteoglycans in cancer pathway,” “pathway in cancer,” and “PI3K-Akt signaling pathway.” Results of enrichment analyses for the top hub genes are shown in Figure 1(e). The qRT-PCR results showed lower EGFR mRNA levels in DFU patients than in those without diabetes (Figure 1(f)).Figure 1
EGFR expression is decreased in DFUs. (a) Hierarchical clustering heat map constructed using GSE80178 data. (b) Volcano plot based on GSE80178 data. (c) Degree centrality analysis of the top 50 degree-filtered genes from the DEG PPI network and corresponding chromosomal positions. The top 10 hub genes are highlighted in red. (d) Distribution of degree, betweenness, and closeness of the top 10 hub genes. (e) Enrichment analysis findings for the top 10 genes in the PPI network. (f) Expression of EGFR in skin tissues from non-DFU (n=6) and DFU patients (n=6) measured using qRT-PCR analysis.
(a)(b)(c)(d)(e)(f)


### 3.2. High-Glucose Stimulation ReducesEGFR mRNA Expression in HUVECs

To validate the above findings, blood samples from 12 DFU patients and 12 healthy volunteers were analyzed using qRT-PCR. Results showed lowerEGFR mRNA levels in DFU patients than in those without diabetes (Figure 2(a)). To understand if EGFR expression in HUVECs is altered in response to diabetic stimuli, qRT-PCR was performed on RNA extracted from cells exposed to hyperglycemic conditions (20 mM D-glucose). Results revealed that EGFR expression was decreased at 4 and 24 h after exposure to a high-glucose environment (Figure 2(b)). Moreover, EGFR expression was significantly lower in excisional wounds in diabetic mice than in nondiabetic controls at 3 and 7 d postwound induction (Figures 2(c) and 2(d)).Figure 2
High-glucose exposure decreases EGFR expression in HUVECs. (a) RelativeEGFR mRNA levels in peripheral blood from control volunteers and DFU patients (n=12 per group). (b) Changes in relative EGFR mRNA levels in HUVECs, 4 and 24 h following exposure to 20 mM D-glucose. (c, d) Relative EGFR mRNA levels in wounds from nondiabetic (c) and diabetic mice (d) at 0, 3, and 7 d postwound induction.
(a)(b)(c)(d)


### 3.3.EGFR Inhibition Impairs HUVEC Functions

To understand howEGFR affects HUVEC activity in vitro, we transfected HUVECs with EGFR-specific shRNAs or a NC. We confirmed EGFR silencing using qRT-PCR analysis (Figure 3(a)). HUVEC proliferation was assessed using the CCK-8 assay, which indicated that EGFR knockdown decreased the proliferative capacity of cells (Figure 3(b)). Further, qRT-PCR assay showed that the expression of the proliferation-related genes Cyclin D1 and Cyclin D3 was decreased in EGFR-shRNA-treated cells (Figure 3(c)). Moreover, EGFR silencing also caused a change in the expression of the apoptosis-related genes Bcl-2 and Bax, which were downregulated and upregulated, respectively, following transfection with EGFR-shRNA (Figure 3(d)). Finally, transwell migration assays also indicated that EGFR silencing weakened the migratory ability of HUVECs (Figures 3(e) and 3(f)).Figure 3
EGFR inhibition impairs HUVEC functions. (a) RelativeEGFR mRNA expression in control, shNC, and shEGFR HUVECs. (b) Effect of EGFR shRNA treatment on HUVEC proliferation (CCK-8 assay). (c) qRT-PCR results showing Cyclin D1 and Cyclin D3 expression in HUVECs treated with EGFR shRNA. (d) qRT-PCR results showing Bcl-2 and Bax expression in HUVECs treated with EGFR shRNA. (e, f) Transwell migration assay findings depicting the effect of EGFR shRNA on HUVEC migration. Scale bar: 100 μm.
(a)(b)(c)(d)(e)(f)


### 3.4. EGFR Inhibition Delays Wound HealingIn Vivo

In nondiabetic mice (Figure4(a)), closure rate measurements revealed a significant delay in the healing of full-thickness back wounds after focal EGFR-shRNA injection (Figure 4(b)).Figure 4
EGFR inhibition delays wound healingin vivo. (a) Wound closure at various time points after different treatments. (b) Wound closure rates for the three experimental treatments.
(a)(b)


### 3.5. miR-133b Is a Potential Upstream Regulator ofEGFR Expression

Using three different miRNA databases (miRTarBase, TargetScan, and miRWalk), we identified miR-133b as a putativeEGFR partner and regulator (Figure 5(a)). Next, we verified the association between miR-133b and EGFR using a dual-luciferase assay in HUVECs transfected with 3′UTR-wild-type or 3′UTR-mutant sequences of EGFR mRNA. The results confirmed that miR-133b specifically binds to the predicted target site of EGFR mRNA (Figures 5(b) and 5(c)). Furthermore, agomiR-mediated miR-133b overexpression clearly suppressed the expression of EGFR (Figures 5(d) and 5(e)). To explore whether miR-133b expression is altered in response to a prodiabetic milieu, we examined EGFR levels in glucose-treated HUVECs using qRT-PCR. The results revealed increased miR-133b expression at 4 and 24 h after exposure to high-glucose conditions (Figure 5(f)). Similarly, miR-133b expression was also found to be significantly higher at 3 and 7 d postwound induction in diabetic mice than in nondiabetic animals (Figures 5(g) and 5(h)).Figure 5
miR-133b is a potential regulator ofEGFR expression. (a) Identification of miR-133b as a putative regulator of EGFR expression based on miRTarBase, TargetScan, and miRWalk target prediction analyses. (b, c) Luciferase reporter assay demonstrating that miR-133b binds to the 3′UTR of the EGFR mRNA. (d) Relative miR-133b levels in control and agomiR-NC-, agomiR-133b-, antagomiR-NC-, and antagomiR-133b-transfected HUVECs (qRT-PCR). (e) qRT-PCR for assessing the effect of miR-133b on EGFR expression. (f) Changes in relative miR-133b levels following exposure of HUVECs to 20 mM D-glucose for 4 and 24 h. (g, h) Relative miR-133b expression in wounds from nondiabetic (g) and diabetic mice (h) at 0, 3, and 7 d postwound induction.
(a)(b)(c)(d)(e)(f)(g)(h)


### 3.6. miR-133b Suppression Enhances HUVEC Functions

After verifying the modulatory effects of the specific miRNA agonist (agomiR-133b) and antagonist (antagomiR-133b) mimics on miR-133b expression (Figure6(a)) using qRT-PCR, we evaluated how miR-133b affects HUVEC activity in vitro. CCK-8 assays showed that HUVEC proliferation was enhanced following transfection with antagomiR-133b (Figure 6(b)). In addition, qRT-PCR analyses for Cyclin D1, Cyclin D3, Bcl-2, and Bax revealed an increase in proliferation and reduction in apoptosis in HUVECs transfected with antagomiR-133b (Figures 6(c) and 6(d)). Furthermore, HUVECs transfected with a miR-133b antagonist showed an improved migration ability (Figures 6(e) and 6(f)).Figure 6
Suppression of miR-133b enhances HUVEC functions. (a) qRT-PCR for miR-133b expression in HUVECs transfected with miR-133b agonist and antagonist mimics. (b) CCK-8 proliferation assay showing HUVECs with enhanced and suppressed miR-133b expression. (c, d) Analysis ofBcl-2 and Bax expression (c) and Cyclin D1 and Cyclin D3 expression (d) using qRT-PCR. (e) Transwell migration assay illustrating the effect of miR-133b inhibition on cell migration. Scale bar: 100 μm.
(a)(b)(c)(d)(e)


### 3.7. miR-133b Suppression Accelerates Wound HealingIn Vivo

The effect of miR-133b inhibition on wound repair was assessed by injecting equal volumes of PBS (control group), agomiR-133b, or antagomiR-133b into the back wounds of control C57BL/6J mice and db/db mice. Wound closure analyses revealed that the antagomiR-133b group showed better wound healing than the other two groups (Figures7(a) and 7(b)). miR-133b levels showed an obvious decrease in wounds only in mice treated with antagomiR-133b, suggesting that the enhancement of wound closure was indeed related to miR-133b suppression (Figure 7(c)).Figure 7
Administration of antagomiR-133b accelerates wound healingin vivo. (a) General condition of wounds after treatment with PBS (control), agomiR-133b, and antagomiR-133b. (b) Wound closure rates. (c) Expression of miR-133b in wound samples.
(a)(b)(c)Microarrays are widely used to investigate the pathogenic mechanisms mediating disease progression. Hence, they are extremely useful for functional genomic research [19, 20]. Studies have used microarrays to detect genetic contributors to diabetes-impaired wound healing. Consequently, several relevant genes such as CD44, CCL5, and IL-6 [21, 22]—which play vital structural and functional roles in the regulation of diabetic wound progression—have been identified. Based on transcriptomic microarray data from DFUs and nondiabetic foot skin samples and subsequent DEG identification and GO and KEGG enrichment analyses, we identified EGFR as a potentially critical player in delayed wound healing in DFUs. After confirming that EGFR is downregulated in DFU patients, we performed thorough in vitro and in vivo experiments to provide confirmatory evidence showing that EGFR downregulation is a significant contributor to DFU progression.Angiogenesis allows oxygen and nutrients to reach wound sites and is therefore vital for facilitating wound repair [23]. Endothelial cell dysfunction is closely linked to impaired angiogenesis, an important hallmark of diabetes and a key cause of impaired DFU healing [4, 24, 25]. EGFR signaling is involved in several biological processes and influences angiogenesis via the regulation of endothelial cell proliferation, apoptosis, and migration [26]. A previous study demonstrated that high-glucose levels impair EGFR signaling and attenuate ex vivo corneal epithelial wound healing [27]. Consistent with this finding, the present study showed that EGFR downregulation occurred in both high-glucose-treated HUVECs and skin wounds from diabetic mice.miRNAs are noncoding, single-stranded RNAs that modulate gene expression. Interestingly, recent research has shown that miRNAs can be released by cells into the blood. These miRNAs can be taken up by other cells, leading to gene modulation in these cells [28]. Because endothelial vascular cells are exposed to large amounts of circulating miRNAs, they are especially susceptible to their regulatory effects. A recent study performed in a rat model of aortic balloon injury showed that endothelial progenitor cells release exosomes containing miR-21-5p, which—upon internalization by endothelial cells—mediate vascular repair by suppressing thrombospondin-1, an angiogenesis inhibitor [10]. Previous research has also shown that EGFR expression is regulated by several miRNAs in different tumors [29, 30]. For example, a study showed that miR-522-3p overexpression could mediate acquired resistance against EGFR-tyrosine kinase inhibitors in NSCLC [31]. Therefore, we searched for potential regulators of EGFR expression by screening for miRNAs that could bind to EGFR mRNA. Using several online predicting tools, we identified five candidates—miR-133b, miR-16, miR-223, miR-133bp, and miR-337. Given the recently reported link between miR-133b and EGFR in squamous cell carcinoma [32], in our study, we examined how miR-133b affects both EGFR expression and wound healing. We found that this miRNA has detrimental effects on both vascular endothelial cell function and wound repair. When a miR-133b agonist was transfected into HUVECs, we observed a significant reduction in their proliferation, migration, and tube-forming ability and an increase in their rate of apoptosis. Accordingly, we observed reduced wound perfusion and delayed wound healing after the treatment of wounds in mice with miR-133b mimics. It is worth noting that angiogenesis is not the only mechanism affected in DFU and that miR-133b can regulate other processes, such as inflammation and fibrosis [33, 34]. However, our findings indicate that miR-133b inhibition can restore EGFR expression and accelerate diabetes-impaired wound healing.


## 3.1.EGFR Expression Is Decreased in Diabetic Foot Ulcers

To search for DEGs in DFUs, the GSE80178 dataset, containing information on six DFUs and three nondiabetic foot skin samples, was retrieved from the GEO database. In total, there were 326 DEGs (88 upregulated and 238 downregulated in the DFU specimens) (Figures1(a) and 1(b)). The degree centrality for the top 50 degree-filtered genes in the PPI network, as well as their chromosomal positions, is shown in Figure 1(c). The top 10 hub genes were EGFR, CD44, HGF, TFRC, LAMA4, FAS, LAMB3, CLCA2, DSG3, and PKP1 (Figure 1(d)), of which the first three had the highest degree, betweenness, and closeness (EGFR, CD44, and HGF). The genes involved in the top three modules showing the highest MCODE scores were subjected to enrichment analysis. The DEGs were enriched under the following terms in the GO analysis: biological process: “cell adhesion,” “biological adhesion,” and “cell-cell adhesion”; molecular function: “receptor binding,” “protein complex binding,” and “intermediate filament binding”; and cellular component: “extracellular region,” “cell junction,” and “anchoring junction.” In turn, the top three KEGG pathways enriched in these DEGs were “proteoglycans in cancer pathway,” “pathway in cancer,” and “PI3K-Akt signaling pathway.” Results of enrichment analyses for the top hub genes are shown in Figure 1(e). The qRT-PCR results showed lower EGFR mRNA levels in DFU patients than in those without diabetes (Figure 1(f)).Figure 1
EGFR expression is decreased in DFUs. (a) Hierarchical clustering heat map constructed using GSE80178 data. (b) Volcano plot based on GSE80178 data. (c) Degree centrality analysis of the top 50 degree-filtered genes from the DEG PPI network and corresponding chromosomal positions. The top 10 hub genes are highlighted in red. (d) Distribution of degree, betweenness, and closeness of the top 10 hub genes. (e) Enrichment analysis findings for the top 10 genes in the PPI network. (f) Expression of EGFR in skin tissues from non-DFU (n=6) and DFU patients (n=6) measured using qRT-PCR analysis.
(a)(b)(c)(d)(e)(f)


## 3.2. High-Glucose Stimulation ReducesEGFR mRNA Expression in HUVECs

To validate the above findings, blood samples from 12 DFU patients and 12 healthy volunteers were analyzed using qRT-PCR. Results showed lowerEGFR mRNA levels in DFU patients than in those without diabetes (Figure 2(a)). To understand if EGFR expression in HUVECs is altered in response to diabetic stimuli, qRT-PCR was performed on RNA extracted from cells exposed to hyperglycemic conditions (20 mM D-glucose). Results revealed that EGFR expression was decreased at 4 and 24 h after exposure to a high-glucose environment (Figure 2(b)). Moreover, EGFR expression was significantly lower in excisional wounds in diabetic mice than in nondiabetic controls at 3 and 7 d postwound induction (Figures 2(c) and 2(d)).Figure 2
High-glucose exposure decreases EGFR expression in HUVECs. (a) RelativeEGFR mRNA levels in peripheral blood from control volunteers and DFU patients (n=12 per group). (b) Changes in relative EGFR mRNA levels in HUVECs, 4 and 24 h following exposure to 20 mM D-glucose. (c, d) Relative EGFR mRNA levels in wounds from nondiabetic (c) and diabetic mice (d) at 0, 3, and 7 d postwound induction.
(a)(b)(c)(d)


## 3.3.EGFR Inhibition Impairs HUVEC Functions

To understand howEGFR affects HUVEC activity in vitro, we transfected HUVECs with EGFR-specific shRNAs or a NC. We confirmed EGFR silencing using qRT-PCR analysis (Figure 3(a)). HUVEC proliferation was assessed using the CCK-8 assay, which indicated that EGFR knockdown decreased the proliferative capacity of cells (Figure 3(b)). Further, qRT-PCR assay showed that the expression of the proliferation-related genes Cyclin D1 and Cyclin D3 was decreased in EGFR-shRNA-treated cells (Figure 3(c)). Moreover, EGFR silencing also caused a change in the expression of the apoptosis-related genes Bcl-2 and Bax, which were downregulated and upregulated, respectively, following transfection with EGFR-shRNA (Figure 3(d)). Finally, transwell migration assays also indicated that EGFR silencing weakened the migratory ability of HUVECs (Figures 3(e) and 3(f)).Figure 3
EGFR inhibition impairs HUVEC functions. (a) RelativeEGFR mRNA expression in control, shNC, and shEGFR HUVECs. (b) Effect of EGFR shRNA treatment on HUVEC proliferation (CCK-8 assay). (c) qRT-PCR results showing Cyclin D1 and Cyclin D3 expression in HUVECs treated with EGFR shRNA. (d) qRT-PCR results showing Bcl-2 and Bax expression in HUVECs treated with EGFR shRNA. (e, f) Transwell migration assay findings depicting the effect of EGFR shRNA on HUVEC migration. Scale bar: 100 μm.
(a)(b)(c)(d)(e)(f)


## 3.4. EGFR Inhibition Delays Wound HealingIn Vivo

In nondiabetic mice (Figure4(a)), closure rate measurements revealed a significant delay in the healing of full-thickness back wounds after focal EGFR-shRNA injection (Figure 4(b)).Figure 4
EGFR inhibition delays wound healingin vivo. (a) Wound closure at various time points after different treatments. (b) Wound closure rates for the three experimental treatments.
(a)(b)


## 3.5. miR-133b Is a Potential Upstream Regulator ofEGFR Expression

Using three different miRNA databases (miRTarBase, TargetScan, and miRWalk), we identified miR-133b as a putativeEGFR partner and regulator (Figure 5(a)). Next, we verified the association between miR-133b and EGFR using a dual-luciferase assay in HUVECs transfected with 3′UTR-wild-type or 3′UTR-mutant sequences of EGFR mRNA. The results confirmed that miR-133b specifically binds to the predicted target site of EGFR mRNA (Figures 5(b) and 5(c)). Furthermore, agomiR-mediated miR-133b overexpression clearly suppressed the expression of EGFR (Figures 5(d) and 5(e)). To explore whether miR-133b expression is altered in response to a prodiabetic milieu, we examined EGFR levels in glucose-treated HUVECs using qRT-PCR. The results revealed increased miR-133b expression at 4 and 24 h after exposure to high-glucose conditions (Figure 5(f)). Similarly, miR-133b expression was also found to be significantly higher at 3 and 7 d postwound induction in diabetic mice than in nondiabetic animals (Figures 5(g) and 5(h)).Figure 5
miR-133b is a potential regulator ofEGFR expression. (a) Identification of miR-133b as a putative regulator of EGFR expression based on miRTarBase, TargetScan, and miRWalk target prediction analyses. (b, c) Luciferase reporter assay demonstrating that miR-133b binds to the 3′UTR of the EGFR mRNA. (d) Relative miR-133b levels in control and agomiR-NC-, agomiR-133b-, antagomiR-NC-, and antagomiR-133b-transfected HUVECs (qRT-PCR). (e) qRT-PCR for assessing the effect of miR-133b on EGFR expression. (f) Changes in relative miR-133b levels following exposure of HUVECs to 20 mM D-glucose for 4 and 24 h. (g, h) Relative miR-133b expression in wounds from nondiabetic (g) and diabetic mice (h) at 0, 3, and 7 d postwound induction.
(a)(b)(c)(d)(e)(f)(g)(h)


## 3.6. miR-133b Suppression Enhances HUVEC Functions

After verifying the modulatory effects of the specific miRNA agonist (agomiR-133b) and antagonist (antagomiR-133b) mimics on miR-133b expression (Figure6(a)) using qRT-PCR, we evaluated how miR-133b affects HUVEC activity in vitro. CCK-8 assays showed that HUVEC proliferation was enhanced following transfection with antagomiR-133b (Figure 6(b)). In addition, qRT-PCR analyses for Cyclin D1, Cyclin D3, Bcl-2, and Bax revealed an increase in proliferation and reduction in apoptosis in HUVECs transfected with antagomiR-133b (Figures 6(c) and 6(d)). Furthermore, HUVECs transfected with a miR-133b antagonist showed an improved migration ability (Figures 6(e) and 6(f)).Figure 6
Suppression of miR-133b enhances HUVEC functions. (a) qRT-PCR for miR-133b expression in HUVECs transfected with miR-133b agonist and antagonist mimics. (b) CCK-8 proliferation assay showing HUVECs with enhanced and suppressed miR-133b expression. (c, d) Analysis ofBcl-2 and Bax expression (c) and Cyclin D1 and Cyclin D3 expression (d) using qRT-PCR. (e) Transwell migration assay illustrating the effect of miR-133b inhibition on cell migration. Scale bar: 100 μm.
(a)(b)(c)(d)(e)


## 3.7. miR-133b Suppression Accelerates Wound HealingIn Vivo

The effect of miR-133b inhibition on wound repair was assessed by injecting equal volumes of PBS (control group), agomiR-133b, or antagomiR-133b into the back wounds of control C57BL/6J mice and db/db mice. Wound closure analyses revealed that the antagomiR-133b group showed better wound healing than the other two groups (Figures7(a) and 7(b)). miR-133b levels showed an obvious decrease in wounds only in mice treated with antagomiR-133b, suggesting that the enhancement of wound closure was indeed related to miR-133b suppression (Figure 7(c)).Figure 7
Administration of antagomiR-133b accelerates wound healingin vivo. (a) General condition of wounds after treatment with PBS (control), agomiR-133b, and antagomiR-133b. (b) Wound closure rates. (c) Expression of miR-133b in wound samples.
(a)(b)(c)Microarrays are widely used to investigate the pathogenic mechanisms mediating disease progression. Hence, they are extremely useful for functional genomic research [19, 20]. Studies have used microarrays to detect genetic contributors to diabetes-impaired wound healing. Consequently, several relevant genes such as CD44, CCL5, and IL-6 [21, 22]—which play vital structural and functional roles in the regulation of diabetic wound progression—have been identified. Based on transcriptomic microarray data from DFUs and nondiabetic foot skin samples and subsequent DEG identification and GO and KEGG enrichment analyses, we identified EGFR as a potentially critical player in delayed wound healing in DFUs. After confirming that EGFR is downregulated in DFU patients, we performed thorough in vitro and in vivo experiments to provide confirmatory evidence showing that EGFR downregulation is a significant contributor to DFU progression.Angiogenesis allows oxygen and nutrients to reach wound sites and is therefore vital for facilitating wound repair [23]. Endothelial cell dysfunction is closely linked to impaired angiogenesis, an important hallmark of diabetes and a key cause of impaired DFU healing [4, 24, 25]. EGFR signaling is involved in several biological processes and influences angiogenesis via the regulation of endothelial cell proliferation, apoptosis, and migration [26]. A previous study demonstrated that high-glucose levels impair EGFR signaling and attenuate ex vivo corneal epithelial wound healing [27]. Consistent with this finding, the present study showed that EGFR downregulation occurred in both high-glucose-treated HUVECs and skin wounds from diabetic mice.miRNAs are noncoding, single-stranded RNAs that modulate gene expression. Interestingly, recent research has shown that miRNAs can be released by cells into the blood. These miRNAs can be taken up by other cells, leading to gene modulation in these cells [28]. Because endothelial vascular cells are exposed to large amounts of circulating miRNAs, they are especially susceptible to their regulatory effects. A recent study performed in a rat model of aortic balloon injury showed that endothelial progenitor cells release exosomes containing miR-21-5p, which—upon internalization by endothelial cells—mediate vascular repair by suppressing thrombospondin-1, an angiogenesis inhibitor [10]. Previous research has also shown that EGFR expression is regulated by several miRNAs in different tumors [29, 30]. For example, a study showed that miR-522-3p overexpression could mediate acquired resistance against EGFR-tyrosine kinase inhibitors in NSCLC [31]. Therefore, we searched for potential regulators of EGFR expression by screening for miRNAs that could bind to EGFR mRNA. Using several online predicting tools, we identified five candidates—miR-133b, miR-16, miR-223, miR-133bp, and miR-337. Given the recently reported link between miR-133b and EGFR in squamous cell carcinoma [32], in our study, we examined how miR-133b affects both EGFR expression and wound healing. We found that this miRNA has detrimental effects on both vascular endothelial cell function and wound repair. When a miR-133b agonist was transfected into HUVECs, we observed a significant reduction in their proliferation, migration, and tube-forming ability and an increase in their rate of apoptosis. Accordingly, we observed reduced wound perfusion and delayed wound healing after the treatment of wounds in mice with miR-133b mimics. It is worth noting that angiogenesis is not the only mechanism affected in DFU and that miR-133b can regulate other processes, such as inflammation and fibrosis [33, 34]. However, our findings indicate that miR-133b inhibition can restore EGFR expression and accelerate diabetes-impaired wound healing.


## 4. Conclusions

Given the limited success of current treatments for DFUs, novel strategies that consider the underlying angiopathy are urgently required. Our findings suggest that exposure to circulating miR-133b may lead to negative effects in endothelial cells by impairing EGFR signaling and contribute to delayed wound healing in diabetic patients. Therefore, the inhibition of miR-133b could represent a potential therapeutic strategy for promoting the healing of diabetic wounds.



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*Source: 9306760-2021-11-27.xml*