Abstract

   Lidocaine, a local anesthetic widely used in dentistry, is esteemed for
   its efficacy and safety. Recent research reveals its additional role in
   modulating the immune system, and particularly in reducing inflammation
   crucial for protecting tooth-supporting tissues. Notably, monocytes and
   macrophages, essential cellular components overseeing various
   physiological and pathological processes, stand as potential mediators
   of lidocaine’s effects. Therefore, this study aimed to investigate how
   lidocaine influences cell behavior using RNA sequencing. To investigate
   the effect of lidocaine on THP-1 cells’ behavior, we performed an MTT
   assay and RNA-Seq along with qPCR analyses to evaluate the
   transcriptomic and proteomic changes in THP-1 cells. Our results showed
   that a high dose of lidocaine (>1 mM) had a significant cytotoxic
   effect on THP-1 cells. However, a lidocaine dose lower than 0.5 mM
   induced a mixed anti-inflammatory profile by significantly upregulating
   tissue remodeling (GDF15, FGF7, HGF, COL4A3, COL8A2, LAMB2, LAMC2,
   PDGFRA, and VEGFA) and through the resolution of inflammation (Cpeb4,
   Socs1, Socs2, Socs3, Dusp1, Tnfaip3, and Gata3) gene cassettes. This
   study explores the effect of lidocaine on the THP-1 in the M2-like
   healing phenotype and provides potential applications of lidocaine’s
   therapeutic effectiveness in dental tissue repair.

   Keywords: local anesthetic, anti-inflammation, macrophage polarization,
   resolution of inflammation, wound healing

1. Introduction

   Achieving profound local anesthesia is pivotal for successful
   dentoalveolar extraction. A fundamental principle in local anesthesia
   is to ensure deep numbness with minimal medication and tissue
   penetration, thereby reducing the risk of complications and patient
   anxiety [[32]1,[33]2]. These anesthetic agents function by reversibly
   binding to sodium channels, blocking sodium’s entry into cells and
   consequently impeding nerve impulse propagation [[34]3]. This prevents
   nociceptive impulses from reaching the brain, effectively eliminating
   pain perception. Local anesthesia refers to the loss of sensation in a
   specific body area due to nerve ending depression or peripheral nerve
   conduction inhibition. Lidocaine, the first amide-linked anesthesia
   agent, synthesized in 1943, has undergone extensive evaluation for its
   efficacy and safety [[35]1].

   When necessitating tooth extraction, dentists commonly administer local
   anesthetics to enhance patient comfort during the procedure while
   ensuring procedural ease [[36]2,[37]4]. After tooth removal, the
   incurred wound initiates an inflammation process, pivotal in combating
   foreign pathogens and advancing wound healing [[38]5,[39]6]. However,
   uncontrolled inflammation may hinder the healing process if it becomes
   excessive [[40]7]. This condition could potentially advance to
   cellulitis if unaddressed [[41]8]. Past research underscores the
   significance of macrophage engagement in wound healing. Its pivotal
   function encompasses inflammation mitigation, cellular debris
   clearance, and the expediting of wound repair [[42]9,[43]10,[44]11].

   Macrophages, immune cells traced back to monocyte transformation via
   signal stimulation [[45]12], showcase remarkable versatility in
   numerous physiological roles such as antigen–antibody uptake,
   phagocytosis, wound healing, bone resorption, antimicrobial defense,
   and antigen presentation [[46]12]. They can be polarized into two major
   subtypes: pro-inflammatory M1 and healing M2. M1 macrophages drive
   pathogen phagocytosis and provoke inflammation, while M2 macrophages
   foster anti-inflammatory actions and tissue repair. Further subdivision
   leads to M2a (wound healing), M2b (immune regulation, tumorigenesis),
   M2c (immune suppression), and M2d (tumor angiogenesis) types [[47]10].
   Positioned as early responders at injury sites, macrophages critically
   regulate inflammatory processes. If modulating macrophage polarization,
   guiding pro-inflammatory macrophages towards the M2 subtype for repair
   becomes feasible; it could control diseases by reducing excess
   inflammation and facilitate tissue regeneration.

   Lidocaine, initially developed as a local anesthetic and antiarrhythmic
   agent, distinguishes itself from its precursor, cocaine, by omitting
   the hallucinogenic and addictive components [[48]13]. Originally
   employed for cardiac arrhythmias, lidocaine’s analgesic potential
   emerged later [[49]1]. Recent pharmacological and clinical advances
   have uncovered its immunoregulatory capabilities, notably inhibiting
   anti-inflammatory responses and mitigating acute lung injury
   [[50]14,[51]15]. A noteworthy sensitization to anticancer drugs has
   also been documented [[52]16,[53]17]. Contemporary research underscores
   lidocaine’s efficacy in suppressing inflammation within
   lipopolysaccharide-activated macrophages [[54]18]. As previously
   mentioned, macrophage phenotypes can be classified into four subtypes,
   and there is currently no research investigating which specific subtype
   of M2 macrophages lidocaine treatment leads to. This study aimed to
   discover the phenotypic transition and transcriptomic changes in
   macrophages upon lidocaine stimulation. This investigation’s outcomes
   stand to unravel the molecular dynamics of lidocaine’s involvement in
   tissue repair, explore the possibility of repurposing an existing drug,
   and expedite the drug development process.

2. Materials and Methods

2.1. THP-1 Cell Culture

   Cells from the human monocytic cell line THP-1 (BCRC, Hsinchu, Taiwan)
   were cultured in RPMI 1640 medium with 2 mM L-glutamine adjusted to
   contain 1.5 g/L sodium bicarbonate, 4.5 g/L glucose, 10 mM HEPES, 1.0
   mM sodium pyruvate, 90% fetal bovine serum, 10% supplemented with 0.05
   mM 2-mercaptoethanol (Sigma-Aldrich, St. Louis, MO, USA). Cells with a
   density of 1 × 10^6 cells/mL were stimulated using 25 nM of
   phorbol-12-myristate-13-acetate (Sigma-Aldrich) for 48 h and another 24
   h of resting before lidocaine treatments.

2.2. Cell Viability

   THP-1 cells were seeded at 150,000 cells/well in 24-well plates and
   cultured as described earlier. Various concentrations of lidocaine
   (from 0 mM (untreated) to 10 mM (lidocaine-treated)) were used to
   stimulate cells at 0, 6, 12, and 24 h. After incubation with lidocaine,
   the supernatant was removed, and cells were rinsed prior to adding MTT
   (Sigma-Aldrich) to develop color. The media were then removed and 1 mL
   of lysis buffer (SDS 30%/N,N-dimethyl-formamide at ratio 2:1, pH 4.7)
   was added to each well. Plates were then incubated at 37 °C and gently
   agitated at 70 rpm for 1 h. The absorbance was then measured at 570 nm.
   For microscopic observations, the THP-1 cells at various treatment
   conditions were imaged with a Nikon E200 LED microscope (Nikon, Tokyo,
   Japan).

2.3. RNA Sequencing

   THP-1 cells treated with 0 and 0.5 mM lidocaine for 12 h were analyzed
   with RNA-sequencing. Total RNA was isolated from lidocaine induced and
   non-induced control cells using TRIzol reagent (Thermo Fisher, Waltham,
   MA, USA). RNA purity was checked using the NanoPhotometer^®
   spectrophotometer (IMPLEN, München, Germany) and RNA integrity was
   assessed using the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100
   system (Agilent Technologies, Santa Clara, CA, USA). Then, RNA samples
   with three replicates were delivered to a company (Genomics, New Taipei
   City, Taiwan) for RNA-sequencing on an Illumina Hiseq 2500 platform and
   150 bp paired-end reads were generated.

2.4. Bioinformatic Analysis

   SeqPrep was used to perform quality control for the sequences after
   RNA-seq. After adapters were removed, sequences with lengths below 25
   bp were discarded, followed by the trimming of low-quality bases and
   the deletion of sequences with N ratios higher than 10%. The read
   depth, error rate (%), Q20 and Q30 values, and GC-content (%) of the
   resulting high-quality clean reads were then evaluated. DEG
   (Differentially Expressed Gene) analysis was performed using DESeq2 and
   edgeR [[55]19,[56]20], and DEGs with log2FC > 1 and p-adjust < 0.05
   were considered to be significantly differently expressed genes. The
   Database for Annotation, Visualization, and Integrated Discovery
   (DAVID) was used to systematically extract biological information from
   numerous genes [[57]21,[58]22] and to perform GO enrichment and Kyoto
   Encyclopedia of Genes and Genomes (KEGG) pathway analysis. p < 0.05 in
   the analysis was considered to indicate a statistically significant
   difference.

2.5. Reverse Transcription Polymerase Chain Reaction

   Following treatment with 0 and 0.5 mM lidocaine for 12 h, the RNA
   stabilization solution was removed on the next day, and total RNA was
   extracted using the RNAeasy Kit (QIAGEN, Hilden, Germany) according to
   the manufacturer’s instructions. One µg of total RNA was
   reverse-transcribed into 20 µL cDNAs with the iScript Reverse
   Transcription Kit according to the manufacturer’s instructions
   (Bio-Rad, Hercules, CA, USA). The reactions were carried out by adding
   the following reagents: 1 μM of each primer (stock was prepared at 10
   μM; [59]Table S1), 25 ng cDNA, and 10 μL of 2 × SYBR green master mixes
   (Bio-Rad) in a total of 25 μL. The Polymer Chain Reaction was performed
   on 96-well plates at the following temperature cycles: Step 1: 95 °C
   for 5 min; Step 2: 95 °C for 30 s, 60 °C for 30 s, and 72 °C for 35 s
   for 35 more cycles; and Step 3: 72 °C for 5 min. Relative fold changes
   of gene expression were normalized using β-actin, and the results were
   plotted and analyzed using Prism software 8.3 (GraphPad Software,
   Boston, MA, USA).

2.6. Statistical Analysis

   Three independent experiments with cell lines from different donors
   were performed for each test. Data are shown as mean ± standard error
   of the mean (SEM). A post hoc test was employed following ANOVA to
   assess differences among the groups using Prism (GraphPad Software, San
   Diego, CA, USA). A p-value of less than 0.05 was considered
   statistically significant.

3. Results

3.1. High Concentrations of Lidocaine Affect Macrophage Viability

   The MTT method was used to determine cell viability after treatment
   with lidocaine for 0–24 h ([60]Figure 1A). The viability of the
   macrophages was not statistically affected by lidocaine at lower
   concentrations, ranging from 0.1 to 0.5 mM at 6 h and 12 h ([61]Figure
   1A). However, macrophage viability appeared to be reduced slightly
   after a longer exposure to lidocaine at 12 h, and was significantly
   affected at 24 h exposure at concentrations higher than 1 mM
   ([62]Figure 1A). Moreover, we observed that lidocaine has a
   time-dependent effect on the viability of macrophages, meaning that
   longer exposures caused more damage to macrophages. Bright-field
   microscopic observations are consistent with MTT results.
   Representative images of various treatments are shown in [63]Figure 1B,
   which showed concentration- and time-dependent effects of lidocaine on
   cell morphology. Lidocaine at lower concentrations (0.1 and 0.5 mM) was
   found to not alter morphology ([64]Figure 1B). On the other hand,
   higher concentrations of lidocaine (i.e., 1, 2, 5 and 10 mM) were seen
   to significantly alter cellular morphology at 12 and 24 h. We concluded
   that elevated concentrations of lidocaine exhibited a time-dependent
   impact. This effect was observed to hinder cell proliferation and
   manifest the existence of clusters of deceased cells (indicated by
   arrows in [65]Figure 1B).

Figure 1.

   [66]Figure 1
   [67]Open in a new tab

   Cell proliferation measurement by MTT colorimetric assay and RT-qPCR.
   (A) Viability of THP-1 cells exposed to various lidocaine
   concentrations for 0, 6, 12, and 24 h; (B) cell morphology visualized
   using light microscope (20× magnification) at various lidocaine
   concentrations for 0, 6, 12, and 24 h, where arrows indicate
   significant morphological changes in THP-1 cells; and (C) qPCR analysis
   of KI67 and MYC markers in THP-1 treated with or without lidocaine for
   6, 12, and 24 h. The results from three independent experiments are
   presented as the mean ± SD. * p < 0.05.

   To further verify the cytotoxic effects of lidocaine, we next examined
   the gene expressions of cell proliferation markers Ki67 and Myc at the
   mRNA levels in THP-1 cells. As shown in [68]Figure 1C, there was a
   significant reduction in the mRNA expression of Ki67 and Myc in
   macrophages at concentrations higher than 0.5 mM (~0.01%) at 24 h. In
   contrast, lidocaine at concentrations lower than 0.5 mM did not affect
   cell proliferation with shorter exposure times to lidocaine at 6 and 12
   h ([69]Figure 1C).

3.2. Transcriptome Analysis of Lidocaine-Treated Macrophages Revealed
Significant Upregulation of Tissue Remodeling Cassettes in Macrophages

   To verify the underlying mechanisms behind the lidocaine on
   macrophages, RNA-seq was conducted to determine the possible genes and
   signaling pathways that could be involved in this process. Samples from
   two groups were used for comparison: untreated only (Un) and
   lidocaine-treated (Lido). After sequencing, differentially expressed
   gene (DEG) analysis was performed to identify gene expression changes
   among these two groups. After comparing the genes in the
   lidocaine-treated and non-treated macrophages, a scatter plot showed
   that there were 2282 DEGs in lidocaine-treated macrophages compared to
   untreated, including 1012 upregulated genes and 1270 downregulated ones
   ([70]Figure 2A). To describe the functions of the DEGs obtained from
   RNA-Seq more generally, we analyzed the obtained genes with Database
   for Annotation, Visualization, and Integrated Discovery (DAVID) to
   obtain the gene ontology (GO) terms of the DEGs. GO term assignment and
   enrichment analyses showed that multiple GO terms were significantly
   enriched in lidocaine-treated groups (e.g., signaling transduction,
   cell adhesion, cell differentiation of the plasma membrane, and
   integral components of extracellular membrane). GO terms with q < 0.05
   were identified as significantly enriched. According to the functional
   enrichment and gene ontology results, several terms were significantly
   enriched within each category (CC, BP, and MF) ([71]Table 1).

Figure 2.

   [72]Figure 2
   [73]Open in a new tab

   Identification of DEGs among untreated and 0.5 mM lidocaine-treated
   THP-1 samples for 12 h. (A) The scatter plot shows the DEGs in
   lidocaine-treated compared to untreated samples. (B) The heat map shows
   the DEGs related to pro-inflammatory genes in lidocaine-treated
   compared to untreated samples. (C) The heat map shows the DEGs related
   to anti-inflammatory genes in lidocaine-treated compared to untreated
   samples. (D) The heat map shows the DEGs related to ECM assembly genes
   in lidocaine-treated compared to untreated samples.

Table 1.

   The top 20 GO terms of BP, CC, and MF of upregulated and downregulated
   genes. Abbreviations: BP, biological process; CC, cellular component;
   MF, molecular function.
   (A) The top 20 enriched GO terms of upregulated genes
   Category Term Count p Value
   BP signal transduction 64 1.9 × 10^−5
   BP cell adhesion 50 4.3 × 10^−12
   BP cell differentiation 40 4.4 × 10^−5
   BP proteolysis 26 5.2 × 10^−4
   BP nervous system development 23 4.7 × 10^−3
   BP protein phosphorylation 23 5.9 × 10^−2
   BP spermatogenesis 22 2.1 × 10^−2
   CC plasma membrane 224 4.7 × 10^−11
   CC integral component of membrane 210 2.2 × 10^−7
   CC extracellular region 90 3.4 × 10^−4
   CC integral component of plasma membrane 89 6.9 × 10^−12
   CC extracellular exosome 78 4.0 × 10^−2
   CC extracellular space 71 3.2 × 10^−2
   CC cell surface 37 1.4 × 10^−4
   CC apical plasma membrane 34 3.7 × 10^−8
   CC synapse 34 3.3 × 10^−5
   CC neuron projection 29 2.7 × 10^−6
   CC external side of plasma membrane 29 2.7 × 10^−4
   CC dendrite 24 5.1 × 10^−3
   CC glutamatergic synapse 22 7.5 × 10^−3
   MF identical protein binding 61 7.5 × 10^−2
   MF calcium ion binding 47 1.9 × 10^−6
   MF protein homodimerization activity 38 1.0 × 10^−3
   MF sequence-specific double-stranded DNA binding 30 2.2 × 10^−3
   MF transcription factor activity, sequence-specific DNA binding 29 4.6
   × 10^−3
   MF protein serine/threonine/tyrosine kinase activity 24 5.5 × 10^−3
   MF receptor binding 22 9.0 × 10^−3
   (B) The top 20 enriched GO terms of downregulated genes
   Category Term Count p Value
   BP signal transduction 83 2.6 × 10^−4
   BP cell adhesion 57 6.1 × 10^−9
   BP nervous system development 50 2.5 × 10^−10
   BP cell differentiation 44 1.1 × 10^−2
   BP chemical synaptic transmission 36 1.6 × 10^−9
   BP positive regulation of gene expression 35 9.0 × 10^−3
   BP cell–cell signaling 34 1.4 × 10^−9
   BP positive regulation of cell proliferation 33 4.6 × 10^−2
   BP proteolysis 30 1.0 × 10^−2
   BP inflammatory response 30 1.2 × 10^−2
   BP intracellular signal transduction 29 4.2 × 10^−2
   BP brain development 27 7.2 × 10^−5
   BP axon guidance 26 7.5 × 10^−7
   BP positive regulation of cell migration 26 1.9 × 10^−4
   BP cell surface receptor signaling pathway 26 3.8 × 10^−3
   BP homophilic cell adhesion via plasma membrane adhesion molecules 24
   1.9 × 10^−6
   BP positive regulation of protein phosphorylation 22 3.9 × 10^−4
   BP extracellular matrix organization 20 4.7 × 10^−4
   BP visual perception 20 2.2 × 10^−3
   CC plasma membrane 346 3.9 × 10^−19
   CC integral component of membrane 309 2.5 × 10^−9
   CC extracellular region 157 5.5 × 10^−11
   CC extracellular space 138 6.0 × 10^−9
   CC integral component of plasma membrane 136 1.0 × 10^−18
   CC Golgi apparatus 63 3.2 × 10^−2
   CC synapse 58 2.6 × 10^−10
   CC cell surface 53 1.4 × 10^−5
   CC dendrite 52 2.0 × 10^−10
   CC glutamatergic synapse 49 2.9 × 10^−10
   CC neuronal cell body 46 2.2 × 10^−10
   CC neuron projection 43 7.5 × 10^−9
   CC axon 41 3.6 × 10^−8
   CC perinuclear region of cytoplasm 40 9.8 × 10^−2
   CC Golgi membrane 38 6.2 × 10^−2
   CC endoplasmic reticulum lumen 36 1.4 × 10^−7
   CC apical plasma membrane 33 4.1 × 10^−4
   CC extracellular matrix 30 2.1 × 10^−6
   CC external side of plasma membrane 26 3.7 × 10^−2
   CC perikaryon 26 2.3 × 10^−8
   MF calcium ion binding 72 2.1 × 10^−9
   MF receptor binding 36 1.9 × 10^−4
   MF sequence-specific double-stranded DNA binding 36 3.0 × 10^−2
   MF macromolecular complex binding 28 5.9 × 10^−3
   MF growth factor activity 22 1.9 × 10^−5
   MF cytokine activity 22 1.5 × 10^−4
   MF integrin binding 21 2.8 × 10^−5
   MF transmembrane signaling receptor activity 21 3.1 × 10^−4
   MF signaling receptor activity 21 2.9 × 10^−3
   [74]Open in a new tab

   Moreover, KEGG pathway enrichment was performed to explore the enriched
   pathways for DEGs. As compared to the untreated group, 16 KEGG pathways
   were identified as significantly enriched in the lidocaine-treated
   macrophages ([75]Table 2). It is worth noting that the most enriched
   pathways in both upregulated and downregulated groups were neuroactive
   ligand–receptor interactions and pathways in cancer ([76]Table 2).

Table 2.

   KEGG pathway enrichment analyses of DEGs in unregulated and
   downregulated groups.
   (A) The KEGG pathway enrichment analysis of upregulated genes
   Term Count p Value
   Pathways in cancer 30 9.4 × 10^−4
   Neuroactive ligand–receptor interaction 25 2.1 × 10^−4
   Calcium signaling pathway 22 1.7 × 10^−5
   PI3K-Akt signaling pathway 19 1.7 × 10^−2
   Cytokine–cytokine receptor interaction 16 3.0 × 10^−2
   MAPK signaling pathway 15 6.4 × 10^−2
   cGMP-PKG signaling pathway 14 1.3 × 10^−3
   Hematopoietic cell lineage 13 3.2 × 10^−5
   Platelet activation 13 2.9 × 10^−4
   Oxytocin signaling pathway 13 2.0 × 10^−3
   (B) The KEGG pathway enrichment analysis of downregulated genes
   Term Count p Value
   Neuroactive ligand–receptor interaction 37 2.3 × 10^−6
   Pathways in cancer 32 4.6 × 10^−2
   Cytokine–cytokine receptor interaction 24 4.2 × 10^−3
   Calcium signaling pathway 21 5.9 × 10^−3
   MAPK signaling pathway 21 3.4 × 10^−2
   [77]Open in a new tab

   Additionally, the specific pathways of PI3K-Akt, cGMP-PKG, Oxytocin,
   and MAPK signaling pathways were also identified in upregulated DEGs
   ([78]Table 2). In contrast, only the MAPK signaling pathway was
   identified in downregulated DEGs ([79]Table 2).

   Since there is no KEGG category regarding macrophage polarization,
   therefore, the analysis of DEGs related to macrophage polarization was
   conducted manually. Consistent with previous findings [[80]15,[81]23],
   specific DEGs selected in untreated and lidocaine-treated groups showed
   that lidocaine reduces inflammatory responses by decreasing the gene
   expression of Tumor Necrosis Factor Alpha (Tnfa), Interleukin 1 Beta
   (Il1b), Cluster of Differentiation 38 (Cd38), Cluster of
   Differentiation 80 (Cd80), G Protein-Coupled Receptor 18 (Gpr18),
   Toll-Like Receptor 4 (Tlr4), and Prostaglandin-Endoperoxide Synthase 2
   (Ptgs2) ([82]Figure 2B). In contrast, lidocaine treatment increases the
   anti-inflammatory gene expression of Interferon Regulatory Factor 6
   (Irf6), Kinase Insert Domain Receptor (Kdr), Programmed Cell Death 1
   Ligand 2 (Pcdc1lg2), Breast Cancer Anti-Estrogen Resistance 3 (bcar3),
   Matrix Metalloproteinase 12 (mmp12), Von Willebrand Factor (vwf),
   Suppressor of Cytokine Signaling 2 (socs2), Integrin Subunit Beta 3
   (Itgb3), Interleukin 10 (Il10), Purinergic Receptor P2Y1 (P2ry1), and
   Aquaporin 9 (Aqp9) ([83]Figure 2C). Intriguingly, among these DEGs, we
   found that genes associated with wound healing (i.e., growth factor
   secretion, ECM remodeling and angiogenesis) were upregulated in
   lidocaine-treated macrophages ([84]Figure 2D). Specifically, Growth
   Differentiation Factor 15 (Gdf15), Fibroblast Growth Factor 7 (Fgf7),
   Hepatocyte Growth Factor (Hgf), Collagen Type IV Alpha 3 Chain
   (Col4a3), Collagen Type VIII Alpha 2 Chain (Col8a2), Laminin Subunit
   Beta 2 (Lamb2), Laminin Subunit Gamma 2 (Lamc2), Platelet-Derived
   Growth Factor Receptor Alpha (Pdgfra), and Vascular Endothelial Growth
   Factor A (Vegfa) were upregulated in lidocaine-treated DEGs as compared
   to the untreated group ([85]Figure 2D). Upon further analysis,
   utilizing functional protein association networks (STRING), it was
   revealed that these genes are correlated with extracellular matrix
   organization and remodeling (see [86]Figure S2).

3.3. Lidocaine Increases the Resolution of Inflammation-Associated Gene
Expression in Macrophages

   Macrophages exhibit a remarkable degree of phenotypic plasticity,
   enabling them to adeptly react to a wide array of stimuli
   [[87]12,[88]24]. This plasticity empowers macrophages to orchestrate a
   spectrum of functions aimed at finely regulating inflammation, the
   resolution of inflammation, and tissue repair mechanisms. Therefore, we
   sought to understand whether lidocaine has an impact on modulating the
   plasticity of macrophages. Among these DEGs, a panel of macrophage
   polarization markers of M2 subtypes (M2a–d) were used to determine the
   effects under lidocaine treatment. Our results showed that 0.5 mM
   lidocaine polarizes resting THP-1 into a mixed M2 subtype by
   significantly increasing the gene expression levels of Mrc1, Fabp4,
   Plin2, Dsc1, Vegfa, and Il-10 ([89]Figure 3A) in these DEGs.

Figure 3.

   [90]Figure 3
   [91]Open in a new tab

   Identification of DEGs along with qPCR validation among untreated and
   lidocaine-treated THP-1 samples. (A) The heat map shows the DEGs
   related to M2a, M2b, M2c, M2d, Inflammatory, and resolution of
   inflammation genes in 0.5 mM lidocaine-treated compared to untreated
   samples. (B) qPCR analysis of FPR2, ALOX5, IL1RL1, CPEB4, SOCS1, and
   GATA3 markers in THP-1 treated with or without lidocaine (0, 0.1 and
   0.5 mM) for 6, 12, and 24 h (* p  <  0.05, as compared to the control).
   The results from three independent experiments are presented as the
   mean ± SD. * p < 0.05.

   To further assess the influence of lidocaine on the resolution of the
   inflammation pathway, an in-depth characterization of lidocaine-treated
   DEGs using multiple markers associated with the resolution of
   inflammation pathway was undertaken. Notably, existing research in the
   scientific literature suggests that the G-protein-coupled receptor FPR2
   plays a pivotal role in modulating anti-inflammatory responses and
   initiating the resolution of inflammation, which is integral to the
   maintenance of tissue homeostasis [[92]25,[93]26,[94]27]. Furthermore,
   essential enzymes and proteins, including alox5, alox15, and alox5ap,
   have been identified as critical components of the pro-resolving
   process [[95]28,[96]29]. The perturbation of these enzymatic entities
   has demonstrated a capacity to alter macrophage polarization towards an
   M1 phenotype that did not favor wound healing. Our results demonstrated
   that lidocaine significantly decreased the inflammatory markers of
   Fpr2, alox5, and Il1rl1 gene expression in THP-1. In contrast, the
   resolution of inflammation markers such as Cpeb4, Socs1, Socs2, Socs3,
   Dusp1, Tnfaip3, Gata3, and IRG1 was significantly increased under
   lidocaine treatment ([97]Figure 3A).

   Further validation of these RNA-Seq results was performed by
   quantitative real-time PCR (qPCR) using six genes, Fpr2, Alox5, Il1rl1,
   Cpeb4, Socs1, and Gata3 ([98]Table S1). We screened different
   concentrations of lidocaine at three time points on THP-1, and found
   similar results for RNA-Seq. Specifically, we found that
   pro-inflammatory markers FPR2, ALOX5, and IL1RL1 were downregulated
   with 0.5 mM lidocaine treatment at both 6 and 12 h ([99]Figure 3B). In
   contrast, the resolution of inflammation markers CPEB4, SOCS1, and
   GATA3 was upregulated with 0.5 mM lidocaine treatment at both 6 and 12
   h ([100]Figure 3B). At 24 h treatment, we did not observe significant
   changes in these tested genes. Together with our findings on the
   anti-inflammatory function of lidocaine (e.g., the upregulation of
   CPEB4, SOCS1, and GATA3), we concluded that lidocaine promotes the
   resolution of inflammatory responses in resting THP-1 cells.

4. Discussion

   Apart from its established role as an analgesic in dental clinical
   practice [[101]1,[102]30], lidocaine has recently been revealed to
   possess immunomodulatory capacities. These encompass the inhibition of
   neutrophil migration and accumulation, decreases in macrophage
   phagocytosis, and the activation of cytotoxic functions within killer
   cells. Particularly noteworthy is its involvement in regulating the
   anti-inflammatory abilities of macrophages, an area that has begun to
   be explored. Our experimental findings are in concurrence with earlier
   research, as we have found that small doses of lidocaine (<0.5 mM,
   ~0.01%) can lower the overall inflammatory response of macrophages. Our
   KEGG enrichment pathway analysis has also unveiled an elevation in
   neuropeptide oxytocin signaling among lidocaine-treated macrophages.
   Notably, lidocaine’s anti-inflammatory influence becomes apparent at
   concentrations lower than those necessary for sodium channel blockades
   [[103]31]. It is imperative to note that lidocaine’s effect on
   inflammation, particularly concerning inflammatory polymorphonuclear
   granulocytes (PMNs), macrophages, and monocytes, is independent of
   sodium channel blockade [[104]15]. Notably, our findings revealed that
   macrophages display reduced tolerance to lidocaine in comparison to
   other cell types like fibroblasts [[105]32]. Specifically, even at a 1
   mM concentration (0.02%) of lidocaine, macrophages demonstrate
   toxicity. This concentration is significantly lower than the 4.27 mM
   lidocaine (~0.1%) toxicity reported for fibroblasts in prior
   investigations [[106]33]. This fourfold contrast in tolerance
   underscores the imperative to thoroughly consider dosage-dependent
   immunotoxicity when utilizing lidocaine within clinical scenarios.

   By modulating excessive inflammatory responses in macrophages, numerous
   studies have established a connection between this modulation and
   accelerated tissue repair. A prior clinical study [[107]34] indicated
   that lidocaine effectively expedites wound healing after melanoma
   resection. The authors also observed a significant increase in CD31+
   cell count following lidocaine treatment. They speculated that
   lidocaine might influence the proliferation or aggregation of CD31+
   cells, subsequently impacting tissue repair, given the close
   association of CD31/PECAM-1 with angiogenesis and tissue repair.
   Interestingly, CD31 is not solely expressed in endothelial cells; it
   has also been identified in macrophages in substantial quantities
   [[108]34]. This suggests that under the influence of lidocaine, CD31+
   macrophages could potentially contribute to an accelerated tissue
   repair process, thus justifying the need for future investigations in
   this direction.

   Along with our findings, this has suggested that lidocaine might affect
   the behavior of macrophages towards a healing subtype ([109]Figure 2
   and [110]Figure 3). For instance, our results ([111]Figure 2C,D)
   revealed the upregulation of critical factors associated with the wound
   healing process (such as IL-10, AQP9, RUNX2, TGFβ, COL8A2, GDF15, and
   others) due to lidocaine exposure [[112]35,[113]36]. Furthermore, it
   has been demonstrated that the elevated expression of RUNX2 is pivotal
   for the differentiation of mesenchymal stem cells into osteoprogenitor
   cells, particularly immediately after tooth extraction
   [[114]6,[115]37].

   Nevertheless, the shortage of studies has not demonstrated that
   lidocaine orchestrates macrophage phenotype modulation via CD31 to
   facilitate tissue repair. Furthermore, the intricate molecular
   mechanism behind lidocaine’s effects lacks in vivo validation as yet.
   Despite the absence of a precise molecular understanding, gel-based
   products containing lidocaine, such as Astero^TM, are already
   accessible in the market for addressing pain-associated diabetic
   wounds, supported by clinical trial findings that attest to their
   significant efficacy in wound repair [[116]38]. Our experimental
   outcomes provide supplementary validation by confirming that lidocaine
   unequivocally exerts a direct influence on macrophage phenotypes. Based
   on the observations in [117]Figure 3, we observed a polarization shift
   of the macrophage phenotype toward the M2 subtype upon exposure to
   lidocaine. While it is regrettable that this study cannot definitively
   discern which of the M2a–d subtypes lidocaine shifts the macrophages
   towards, an overall examination of transcriptome expression indicates
   that lidocaine does transform THP-1 cells into a M2-like macrophage
   subtype. Moreover, it increases the expression of growth factors,
   elevates molecules related to TGFβ signaling, enhances macrophage ECM
   remodeling capability, and augments angiogenesis potential ([118]Figure
   2D). In general, an increase in M2 macrophages is associated with pain
   relief and closely linked to wound repair [[119]11,[120]39].
   Suppressing the inflammatory response of M1 macrophages accelerates the
   resolution of tissue inflammation, consequently expediting tissue
   repair [[121]40,[122]41].

5. Conclusions

   In conclusion, this study has explored the impact of lidocaine on
   macrophages, revealing that even at low doses, lidocaine can mitigate
   macrophage inflammatory responses while concurrently enhancing the
   expression of genes associated with tissue repair and inflammation
   resolution. While the focus was primarily on the transcriptomic changes
   in lidocaine-induced THP-1 cell behavior, this investigation sheds
   light on the potential of lidocaine in treating inflammatory diseases
   related to macrophages. Moreover, there is considerable potential for
   refining lidocaine’s formulation and developing targeted therapeutic
   strategies to address macrophage-related disorders.

6. Limitations

   Future research should prioritize protein and functional assays and
   relevant animal models to further elucidate inflammation resolution and
   extracellular matrix remodeling mechanisms under lidocaine treatment.

Supplementary Materials

   The following supporting information can be downloaded at:
   [123]https://www.mdpi.com/article/10.3390/biomedicines12030509/s1,
   Figure S1: Raw images of bright-field microscopy in untreated and
   lidocaine-treated THP-1 cells.; Figure S2: Protein-protein interactions
   of identified genes. The STRING protein database was utilized to
   analyze the protein-protein interactions of GDF15, FGF7, HGF, COL4A3,
   COL8A2, LAMB2, LAMC2, PDGFRA, and VEGFA. Table S1: qPCR primers used in
   this study.
   [124]biomedicines-12-00509-s001.zip^ (2.1MB, zip)

Author Contributions

   Conceptualization, C.-S.W. and S.-W.F.; methodology, C.-S.W., W.-C.L.
   and I.-T.L.; software, C.-S.W., W.-C.L., S.-D.L. and I.-T.L.;
   validation, C.-S.W. and S.-W.F.; formal analysis, C.-S.W. and S.-W.F.;
   investigation, C.-S.W. and S.-W.F.; resources, C.-S.W. and S.-W.F.;
   data curation, C.-S.W., S.-W.F. and S.-D.L.; writing—original draft
   preparation, S.-W.F.; writing—review and editing, C.-S.W.;
   visualization, C.-S.W.; supervision, C.-S.W. and S.-W.F.; project
   administration, C.-S.W. and S.-W.F.; funding acquisition, C.-S.W. and
   S.-W.F. All authors have read and agreed to the published version of
   the manuscript.

Institutional Review Board Statement

   Not applicable.

Informed Consent Statement

   Not applicable.

Data Availability Statement

   The data presented in this study are available on request from the
   corresponding author.

Conflicts of Interest

   The authors declare no conflicts of interest.

Funding Statement

   This work was financially supported by Taipei Medical University and
   Taipei Medical University Hospital (grant no: 110TMU-TMUH-13).

Footnotes

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References