Research on hsa-miR-155-3p and hsa-miR-155-5p as biomarkers for systemic sclerosis and their role in regulating biological behavior

WANG Bao-yue, SUN Xiao-lin, WANG Yong-fu?

1.Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou 014010, China

2.Department of Rheumatology, the First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology,Baotou 014010, China

Keywords:

ABSTRACT Objective: This study was to investigate the role of hsa-miR-155-3p and hsa-miR-155-5p as biomarkers and regulators of biological behavior in Systemic Sclerosis.Methods: A total of 10 SSc patients and 10 healthy controls were selected for the study.The expression levels of hsa-miR-155-3p and hsa-miR-155-5p in peripheral blood mononuclear cells of SSc patients and healthy controls were measured using RT-qPCR.The diagnostic value of these miRNAs was explored using Receiver Operating Characteristic curve analysis.Pearson or Spearman correlation analysis was performed to assess the correlation between miRNAs and clinical indicators in SSc patients.Potential target genes of hsa-miR-155-3p and hsa-miR-155-5p were predicted using miRDB, Targetscan, and miRDIP databases.GO functional annotation, KEGG pathway enrichment analysis, protein-protein interaction network construction, and selection of central genes were conducted.Results: The expression levels of hsa-miR-155-3p and hsamiR-155-5p were significantly higher in PBMCs of SSc patients compared to healthy controls(P＜0.001).The ROC curve analysis showed that hsa-miR-155-3p and hsa-miR-155-5p had a high diagnostic value for SSc (AUC=1, P＜0.001).Correlation analysis revealed that hsamiR-155-3p, hsa-miR-155-5p, and clinical indicators such as high-resolution CT, neutrophil percentage, lymphocyte percentage, and albumin to globulin ratio were correlated (P＜0.05).The signaling pathways enriched with target genes of hsa-miR-155-3p and hsa-miR-155-5p were closely associated with the occurrence and development of SSc fibrosis, immunity,and inflammation.Conclusions: hsa-miR-155-3p and hsa-miR-155-5p may be involved in regulating the occurrence and development of SSc fibrosis, immunity, and inflammation.They have the potential to serve as biomarkers for clinical diagnosis and treatment of SSc.

1.Introduction

Systemic Sclerosis (SSc) is a rheumatic disease caused by various factors such as genetics and environment[1].The exact mechanism of SSc pathogenesis is not fully understood, but extensive research suggests that the interaction between immune dysregulation,endothelial dysfunction, and pro-fibrotic mechanisms is a common cause of SSc development[2].In SSc, activation of myofibroblasts leads to excessive deposition of extracellular matrix in the skin,internal organs, and the presence of lung fibrosis is a significant contributor to its high mortality rate[3].Therefore, the search for new predictive biomarkers to explore the occurrence and progression of SSc may become a novel direction for SSc treatment.

MicroRNAs (miRNAs) are non-coding RNA molecules that regulate gene expression by binding to complementary sites on target mRNA, promoting mRNA degradation or inhibiting its expression[4].Mature miRNAs are composed of two strands, derived from the 5’ and 3’ arms of the miRNA precursor (pre-miRNA),hence named “-5p” and “-3p”[5].Increasing evidence suggests that miR-155 can regulate processes such as immune dysregulation,fibrosis, and inflammation in diseases[6-8].In SSc dermal and lung fibroblasts, NOD-like receptor thermal protein domain-associated protein 3 (NLRP3) can induce collagen synthesis and promote SSc fibrosis by upregulating miR-155 expression[9].Additionally,interfering with miR-155 expression can inhibit the Wnt/β-catenin and Akt pathways, reducing the degree of skin fibrosis in an SSc mouse model[10].These findings highlight the significant role of miR-155 in SSc, but whether it can serve as a clinical diagnostic biomarker for SSc still requires further exploration.

Therefore, this study aims to investigate the expression levels of hsa-miR-155-3p and hsa-miR-155-5p in PBMCs of SSc patients and healthy controls, analyze their correlation with clinical data of SSc, and explore their potential as diagnostic biomarkers for SSc.In addition, this study will utilize bioinformatics methods to analyze the target genes of hsa-miR-155-3p and hsa-miR-155-5p, further elucidating the mechanisms of action of these miRNAs in SSc.

2.Information and methodology

2.1 Research target

A total of ten SSc patients and ten age- and gender-matched healthy controls were selected from the Rheumatology and Immunology Department and Physical Examination Department of the First Affiliated Hospital of Baotou Medical College, Inner Mongolia University of Science and Technology.Inclusion criteria were as follows: (1) age 18 years; (2) male or non-pregnant female; (3)diagnosed with systemic sclerosis; (4) able to communicate and participate voluntarily, with signed informed consent.Exclusion criteria were as follows: (1) age ＜ 18 years; (2) patients with severe infections; (3) patients with malignant tumors or with a history of malignant tumors; (4) any other condition deemed inappropriate for inclusion in this clinical trial by the researchers.The diagnosis of SSc in all cases was consistent with the 2013 American College of Rheumatology (ACR)/European League Against Rheumatism(EULAR) SSc classification criteria[11].The control group consisted of three males and seven females, with an age range of 31-67 years and an average age of (54.30±13.26) years; the body mass index ranged from 20 to 25 kg/m2, with an average of (21.26±0.77).The SSc group consisted of three males and seven females, with an age range of 33-70 years and an average age of (56.20±12.09) years;the body mass index ranged from 20 to 25 kg/m2, with an average of (21.76±0.98) kg/m2.There were no statistically significant differences in gender, age, or body mass index between the control group and the SSc group (P＞0.05), indicating comparability.This study was approved by the Medical Ethics Committee of our hospital, with the ethics approval number: Baoyi Ethics 2022 No.(106).Informed consent was obtained from all patients for the acquisition of peripheral blood samples.

2.2 Experimental materials

Human peripheral blood lymphocyte isolate( Haoyang Biotechnology Co., Ltd., Tianjin, China); Trizol (Thermo Fisher Scientific, Waltham, MA, USA); Chloroform (Sigma-Aldrich Trading Co.Ltd., Shanghai, China); Isopropyl Alcohol (Beijing Soleibao Technology Co., Ltd., Beijing, China); 70% Ethanol(Tianjin Oubokai, Tianjin, China); RNase Free (Beijing Soleibao Technology Co., Ltd., Beijing, China); miRNA cDNA first strand synthesis kit (stem-loop method) (Shanghai Bioengineering,Shanghai, China); RT-PCR kit, SYBR Green Realtime PCR Master Mix (Toyobo Bio-technology Co., Ltd., Osaka, Japan); fluorescence quantitative PCR instrument (Applied Biosystems, Foster City, CA,USA).

2.3 Methodologies

2.3.1 Laboratory data collection

The clinical indicators include high-resolution CT (HRCT),percentage of predicted value for forced vital capacity (VC%),percentage of predicted value for forced vital capacity during exhalation (FVC%), percentage of predicted value for forced expiratory volume in one second (FEV1%), erythrocyte sedimentation rate (ESR), percentage of lymphocytes (LYM%),percentage of neutrophils (NEUT%), albumin (ALB), globulin(GLB), and albumin to globulin ratio (ALB/GLB).

2.3.2 PBMCs and RNA extraction

Collect 2 mL of whole blood and transfer it into a rubber tube.Add 2 mL of physiological saline to the tube and mix slowly.Extract the mixed whole blood and place it into a rubber tube containing 2 mL of lymphocyte separation medium.Centrifuge at 2 000 r/min for 22 min.After extracting the intermediate layer of PBMCs, transfer them into a rubber tube containing 3 mL of physiological saline and mix well.Centrifuge at 1 500 r/min for 7 min.Discard the supernatant,add 3 mL of physiological saline and mix well.Centrifuge at 1 500 r/min for 4 min.Finally, discard the supernatant, add 1 mL of Trizol and mix well.Let it sit at room temperature for 5 min, then add 0.2 mL of chloroform and shake vigorously for 15 seconds.Let it stand for 5 min and centrifuge at 12 000 r/min for 5 min.Transfer the supernatant into a new centrifuge tube, add 0.5ml of isopropanol,shake vigorously, and centrifuge at 4 ℃, 12 000 r/min for 10 min.Discard the supernatant, add 1ml of 70% ethanol at 4 ℃, and centrifuge at 7 500 r/min for 5 min.Discard the supernatant and air dry at room temperature for 5-10 min.Add 30 μL of RNase-free water, take 2 μL for electrophoresis testing.

2.3.3 Real-time quantitative PCR (RT-qPCR) was performed to detect the expression levels of miRNA.

Total RNA was extracted from human PBMCs using Trizol reagent.The expression levels of hsa-miR-155-3p and hsa-miR-155-5p in human PBMCs were measured.ReverTra Ace qPCR RT Kit was used to reverse transcribe 1μg of total RNA into cDNA.The prepared cDNA was then amplified by PCR under the following reaction conditions: 95 ℃ for 1 min, 1 cycle; 95 ℃ for 15 seconds,40 cycles; 60 ℃ for 30 seconds.The data was analyzed using the 2-△△Ctmethod.The primer sequences used in this study are listed in Table 1

Tab 1 Primer sequences of hsa-miR-155-3p and hsa-miR-155-5p

2.3.4 Correlation analysis of miRNAs with clinical data miRNA

The correlation analysis between miRNA and clinical data was performed using IBM SPSS 26.0 and GraphPad Prism 8.0.2.The clinical data included HRCT, VC%, FVC%, FEVl%, ESR, LYM%,NEUT%, ALB, GLB, and ALB/GLB.Subsequently, the receiver operating characteristic curve (ROC) was plotted for the diagnosis of SSc.

2.3.5 Prediction of miRNA target genes

For the prediction of target genes of miR-155-3p and miR-155-5p,three online databases, namely miRDIP (http://ophid.utoronto.ca/mirDIP/), miRDB (http://www.mirdb.org/), and TargetScan (https://www.targetscan.org/), were utilized.The intersection of prediction results from these three databases was obtained using the online tool VENNY 2.1.0 (http://bioinfogp.cnb.csic.es/ tools/venny/index.html).

2.3.6 GO functional annotation and KEGG Pathway enrichment analysis of miRNA target genes

The gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the target genes were performed using the David (https://david.ncifcrf.gov/tools.jsp) and Kobas (http://kobas.cbi.pku.edu.cn/index.php) online websites.The GO and KEGG pathway maps were visualized using the bioinformatics website Microbiome (http://www.bioinformatics.com.cn/).The GO analysis included biological process (BP), cellular component (CC), and molecular function(MF), and statistical significance was defined as P＜0.05.

2.3.7 Construction of protein-protein inter-action (PPI)networks and screening of core (Hub) genes

The miRNA target gene protein-protein interaction (PPI) network was constructed using the String website (https://www.string-db.org/), and data with a confidence score 0.4 were selected.The PPI network was visualized using Cytoscape software version 3.9.1.The central genes were selected based on the maximal clique centrality(MCC), maximum neighborhood component (MNC), and Degree criteria using the cytoHubba plugin in Cytoscape.

2.4 Statistical processing

Data analysis was performed using IBM SPSS 26.0 and GraphPad Prism 8.0.2.Normally distributed data were presented as (±s), and paired sample t-test and one-way analysis of variance (ANOVA)were used for comparisons between two and multiple groups,respectively.Pearson correlation analysis was used for linear and normally distributed data, while Spearman correlation analysis was used for non-linear or non-normally distributed data.The diagnostic value of miRNA was evaluated using receiver operating characteristic (ROC) analysis, and statistical significance was defined as P＜0.05.

3.Result

3.1 Expression of hsa-miR-155-3p and hsa-miR-155-5p is upregulated in PBMCs from SSc patients

The expression levels of hsa-miR-155-3p and hsa-miR-155-5p in PBMCs of patients with SSc and healthy control individuals were detected using RT-qPCR.The results showed that the expression levels of hsa-miR-155-3p and hsa-miR-155-5p in SSc patient PBMCs were significantly higher than those in the healthy control group (P ＜ 0.05), as shown in Figure 1.

Fig 1 RT-qPCR validation of hsa-miR-155-3p and hsa-miR-155-5p expression levels in SSc PBMCs (n=10)

3.2 Diagnostic value of hsa-miR-155-3p and hsa-miR-155-5p for SSc

ROC curves demonstrated that hsa-miR-155-3p (AUC = 1, P =0.000 2) and hsa-miR-155-5p (AUC = 1, P = 0.000 2), indicating that hsa-miR-155-3p and hsa-miR-155-5p may play an important role in the clinical diagnosis of SSc, as shown in Figure 2.

Fig 2 ROC curve analysis of hsa-miR-155-3p and hsa-miR-155-5p independent diagnosis of SSc

3.3 Correlation analysis of hsa-miR-155-3p, hsa-miR-155-5p and clinical data

In order to further clarify whether hsa-miR-155-3p and hsa-miR-155-5p can serve as diagnostic markers for SSc, the correlation between miRNA and clinical data of SSc patients was analyzed using correlation analysis.The results showed that hsa-miR-155-3p was positively correlated with high-resolution CT (HRCT),neutrophil percentage (NEUT%), red blood cell distribution width standard deviation (RDW-SD), platelet distribution width (PDW),and globulin (GLB), and negatively correlated with lymphocyte percentage (LYM%), plateletcrit (PCT), albumin/globulin ratio(ALB/GLB) (P＜0.05).Hsa-miR-155-5p was positively correlated with HRCT, NEUT%, RDW-SD, red blood cell distribution width coefficient of variation (RDW-CV), PDW, and GLB, and negatively correlated with forced vital capacity as a percentage of predicted value (VC%), forced vital capacity as a percentage of predicted value(FVC%), forced expiratory volume in one second as a percentage of predicted value (FEVl%), lymphocyte absolute value (LYM#),LYM%, PCT, and ALB/GLB (P＜0.05) (Figure 3).

3.4 Target gene prediction results of hsa-miR-155-3p, hsamiR-155-5p

Fig 3 Correlation analysis of clinical data for hsa-miR-155-3p, hsa-miR-155-5p and SSc

The online databases miRDIP, miRDB, and TargetScan predicted 724, 422, and 2956 target genes for hsa-miR-155-3p, respectively.After taking the intersection, 309 predicted target genes were obtained.For hsa-miR-155-5p, the number of predicted target genes was 977, 234, and 556 in the three databases, respectively.After taking the intersection, 121 predicted target genes were obtained(Figure 4).

Fig 4 Target gene prediction results for hsa-miR-155-3p and hsa-miR-155-5p

3.5 Analysis of target genes for hsa-miR-155-3p and hsamiR-155-5p was conducted using GO and KEGG.

A Gene Ontology (GO) analysis was conducted on 309 genes predicted to be targeted by hsa-miR-155-3p and 121 genes predicted to be targeted by hsa-miR-155-5p.The analysis revealed that the target genes were mainly enriched in transcriptional regulation of RNA polymerase II promoters, transcriptional regulation triggered by DNA, and regulation of gene expression in terms of biological processes (BP).In terms of cellular components (CC), the target genes were mainly enriched in the nucleus, cytoplasm, and chromatin.As for molecular functions (MF), the target genes were mainly enriched in RNA polymerase II transcription regulatory region DNA sequence-specific binding, protein binding, and DNA binding.These findings are illustrated in Figure 5.Furthermore, the KEGG analysis showed that the significantly enriched pathways for hsa-miR-155-3p target genes were the Wnt signaling pathway, FoxO signaling pathway, TRP channels, and P53 signaling pathway.For hsa-miR-155-5p target genes, the significantly enriched pathways were the IL-17 signaling pathway, MAPK signaling pathway, TNF signaling pathway, T and B cell receptor signaling pathway, Tolllike receptor signaling pathway, PI3K-AKT signaling pathway, NFκB signaling pathway, NOD-like receptor signaling pathway, FoxO signaling pathway, as well as SSc fibrosis, immune response, and inflammation.These results are presented in Figure 6.

Fig 5 Bar graph of GO analysis of target genes of hsa-miR-155-3p and hsa-miR-155-5p

Fig 6 KEGG Pathway bubble map of target genes of hsa-miR-155-3p and hsa-miR-155-5p

3.6 Construction of PPI networks and Hub genes

PPI networks for hsa-miR-155-3p and hsa-miR-155-5p target genes were constructed using the String online website, as shown in Figures 7 and 8.The cytoHubba plugin in Cytoscape software was used to select the top 5 hub genes based on the MCC, MNC,and Degree algorithms.The intersection genes were identified by drawing a Venn diagram.The results revealed that the key target genes for hsa-miR-155-3p were SMAD4, HSP90AA1, and MAPK14, while the key target genes for hsa-miR-155-5p were FOS,SMARCA4, SMAD2, and KRAS.These target genes may play important roles in the pathogenesis of SSc, as depicted in Figure 9.

Fig 7 PPI network of hsa-miR-155-3p target genes

Fig 8 PPI network of hsa-miR-155-5p target genes

4.Discussion

Systemic sclerosis (SSc) is a rare immune-mediated disease characterized by multi-organ involvement and a poor prognosis.The treatment of this disease poses significant challenges, and finding effective therapeutic approaches is currently a pressing issue.Recently, there has been an increasing amount of research on potential biomarkers for SSc.The emergence of biomarkers has provided new avenues for the diagnosis and treatment of the disease.These biomarkers not only allow for the early detection of high-risk individuals but also guide treatment based on the severity of the disease, thereby improving patient outcomes.Consequently,the search for valuable biomarkers in SSc is currently a hot topic of research.

Fig 9 Screening of hsa-miR-155-3p and hsa-miR-155-5p key target genes

The role of miRNAs as biomarkers has been extensively studied.In individuals with positive autoantibodies but no symptoms, as well as in patients with rheumatoid arthritis (RA), the expression level of miR-103a-3p is significantly increased, suggesting its potential as a biomarker for the development of RA in high-risk individuals[12].In SSc patients with positive anti-topoisomerase I (Scl-70) antibodies,the expression level of miR-27a is significantly lower compared to antibody-negative patients.As this antibody is correlated with disease severity, miR-27a may serve as a potential biomarker for assessing disease progression[13].Niu et al.[14] found that miR-155 is significantly upregulated in patients with Child-Pugh C liver cirrhosis.Moreover, patients with high levels of miR-155 have a shorter post-transplant survival compared to those with low expression levels, indicating a close correlation between miR-155 and the progression and clinical prognosis of liver cirrhosis.Wajda et al.[15] confirmed that miR-155 is significantly upregulated in the serum of SSc patients compared to healthy controls, suggesting its association with early microvascular abnormalities in SSc.In this study, we found that the expression levels of hsa-miR-155-3p and hsa-miR-155-5p in peripheral blood mononuclear cells (PBMCs) of SSc patients were significantly higher than in healthy controls.ROC diagnostic experiments demonstrated that both hsa-miR-155-3p and hsa-miR-155-5p had an area under the curve (AUC) of 1, indicating their importance in the diagnosis and treatment of SSc.

Current research suggests that miR-155 is an important pro-fibrotic factor, with upregulated expression in pulmonary fibrosis, cardiac fibrosis, and non-alcoholic liver fibrosis[16-18].In SSc patients, the occurrence of pulmonary fibrosis, if left untreated, can lead to an increased mortality rate [3].HRCT, as a non-invasive diagnostic tool,can clearly display the location, extent, and nature of pulmonary lesions, and is of great value in the diagnosis of pulmonary fibrosis.Additionally, HRCT scores are positively correlated with the degree of pulmonary fibrosis[19].In this study, the expression levels of hsa-miR-155-3p and hsa-miR-155-5p were positively correlated with HRCT scores, indicating that they may reflect the severity of pulmonary fibrosis in SSc.

The pulmonary function test is an essential examination for diagnosing pulmonary fibrosis.It not only provides insights into lung ventilation and diffusion function, but also reflects the progression and prognosis of pulmonary fibrosis[20].The decreased compliance in pulmonary fibrosis leads to reduced lung capacity,manifested by decreased VC, FVC, FEV1, and total lung capacity(TLC)[21].Christmann et al.[22] found that the expression of miR-155 in PBMCs of SSc patients with interstitial lung disease was negatively correlated with FVC% and the percentage of predicted carbon monoxide diffusion capacity (DLCO%), suggesting that miR-155 may affect respiratory function and worsen the progression of pulmonary fibrosis.This study also found a negative correlation between the expression levels of hsa-miR-155-5p and lung function indicators VC%, FVC%, and FEV1%, as well as a positive correlation between the expression level of hsa-miR-155-5p and HRCT score, indicating that hsa-miR-155-5p may serve as a potential biomarker for monitoring SSc with interstitial lung disease and assessing disease severity.

miR-155 has been proven to be a major regulator of inflammatory responses.In smoke-induced acute lung injury, miR-155 can promote the activation and recruitment of neutrophils, leading to aggravated lung inflammation[23].In a mouse model of atherosclerosis,microvesicles released by activated neutrophils contain a large amount of miR-155, and microvesicles containing miR-155 can adhere to susceptible areas of the disease, promoting the expression of nuclear factor kappa-B (NF-κB), thereby exacerbating the formation of atherosclerosis[24].In this study, the expression levels of hsa-miR-155-3p and hsa-miR-155-5p were positively correlated with NEUT%, further indicating that hsa-miR-155-3p and hsa-miR-155-5p, like neutrophils, may serve as clinical indicators of SSc inflammation.

Abnormal lymphocyte subset is a common cause of immune disorders in SSc.Guo et al.[25] demonstrated that compared to healthy controls, SSc patients exhibited a significant decrease in the total number of T cells in peripheral blood, and the ratio of peripheral T cells, CD4+T cells, regulatory T cells (Tregs), and Th1/Th2 to CRP were all negatively correlated.Gernert et al.[26] also found that the number of B cells and T cells in peripheral blood of SSc patients without immunosuppression was lower than that of healthy controls.Furthermore, Ma et al.[27] indicated that excessive reduction in lymphocyte count can worsen the disease activity of SSc and increase the risk of organ involvement.This study found a negative correlation between the expression of hsa-miR-155-3p,hsa-miR-155-5p, and LYM%, suggesting that hsa-miR-155-3p and hsa-miR-155-5p can serve as clinical indicators for monitoring SSc lymphocytes and evaluating disease progression.

RDW is a routine indicator for diagnosing anemia, but multiple studies have confirmed that RDW can also be an independent risk factor affecting disease prognosis[28, 29].In patients with connective tissue disease-associated pulmonary arterial hypertension, a higher RDW value is associated with poorer prognosis[30].Additionally,RDW can serve as a clinical indicator for predicting the development of pulmonary arterial hypertension in SSc[31].Timely identification of risk factors and new biomarkers can facilitate early treatment of SSc, thereby improving prognosis.In this study, the expression of hsa-miR-155-3p, hsa-miR-155-5p was positively correlated with RDW-SD, indicating that the prognosis of SSc can also be reflected by the expression levels of hsa-miR-155-3p, hsa-miR-155-5p.

Research has shown that platelets play an important role in inflammation by stimulating pro-inflammatory substances.[32].PDW reflects the variation in platelet size and is associated with platelet activation[33].PCT refers to the proportion of platelet volume in whole blood.Yu et al.[34] found that PDW can be used as a biomarker for predicting lupus nephritis.Oral et al.[35] discovered that PCT can be a useful biomarker for early detection of nonalcoholic fatty liver disease.In this study, the expression of hsa-miR-155-3p and hsa-miR-155-5p was positively correlated with PDW and negatively correlated with PCT, further indicating their influence on inflammation in SSc.

ALB is the most abundant protein in plasma and is one of the indicators for evaluating malnutrition.Recent studies have found a negative correlation between ALB and inflammatory response,suggesting its potential as a biomarker for inflammation[36].GLB is also associated with inflammation, and the ALB/GLB ratio is a promising biomarker in inflammation.Higher levels of ALB/GLB are significantly associated with better prognosis in heart failure patients[37].In this study, it was also found that the expression of hsamiR-155-3p and hsa-miR-155-5p was positively correlated with GLB and negatively correlated with ALB/GLB, indicating that the upregulation of hsa-miR-155-3p and hsa-miR-155-5p could serve as potential biomarkers for monitoring inflammation in SSc.

miRNAs participate in the regulation of various biological processes associated with multiple diseases by interacting with their target genes.By predicting the target genes of hsa-miR-155-3p and hsa-miR-155-5p, and exploring the functions of these target genes,the specific mechanism of miRNA in SSc can be better understood,providing reliable reference for subsequent diagnosis and treatment.Based on the GO functional annotation results of the target genes of hsa-miR-155-3p and hsa-miR-155-5p in this study, it was found that these genes are closely related to the regulation of gene expression,protein synthesis, and other processes.KEGG analysis results showed that the signaling pathways enriched by the target genes of hsa-miR-155-3p and hsa-miR-155-5p are widely involved in biological processes such as immunity, inflammation, fibrosis, and tumorigenesis.Further analysis of the key target genes of hsa-miR-155-3p revealed SMAD4, HSP90AA1, and MAPK14 as central genes, with SMAD4 involved in Wnt and FoxO signaling pathways,and MAPK14 involved in the FoxO signaling pathway.The key target genes of hsa-miR-155-5p are FOS, SMARCA4, SMAD2, and KRAS, with FOS involved in IL-17, TNF, MAPK, Toll-like receptor,T and B cell signaling pathways, and KRAS involved in MAPK, T,and B cell signaling pathways.

SMAD4 and SMAD2 are signaling molecules in the transforming growth factor-β (TGF-β) pathway.The TGF-β/SMAD signaling pathway can lead to excessive deposition of extracellular matrix and contribute to fibrosis-related diseases[38].In a mouse model of bleomycin-induced lung fibrosis, Ginkgolic acid may inhibit TGFβ1-induced SMAD4 ubiquitination, decrease the production of reactive oxygen species, and suppress epithelial-mesenchymal transition (EMT), ultimately improving lung fibrosis[39].Jiang et al.[40] found that pectic polysaccharides can attenuate myofibroblast activation, reduce collagen expression, and ameliorate lung fibrosis in a mouse model of systemic sclerosis (SSc) by inhibiting TGF-β/Smad2/3 signaling.MAPK14, a subtype of the p38MAPK family,plays a role in various cellular processes including proliferation,apoptosis, senescence, and inflammation[41].It has been reported that the long non-coding RNA XIST can promote lipopolysaccharideinduced lung injury in mice by regulating the miR-12-132p/MAPK14 axis[42].FOS is associated with various pathological processes such as inflammation, vascular disease, and tumor development.Additionally, FOS also plays an important role in tissue fibrosis[43, 44].Xue et al.[45]demonstrated that miR-29b-3p inhibits TGF-β1-induced proliferation, migration, and differentiation of cardiac fibroblasts by targeting FOS, thereby alleviating cardiac fibrosis.KRAS, a cancer-related gene, has recently been found to be associated with fibrosis in patients with heart failure and may serve as a potential biomarker for diagnosing heart failure[46].Yi et al.[47]discovered that CircRNA_30032 promotes renal fibrosis in a mouse model of unilateral ureteral obstruction by targeting miR-96-5p and enhancing KRAS expression.These target genes are involved in the development of fibrosis-related diseases, suggesting that hsa-miR-155-3p and hsa-miR-155-5p may participate in the pathogenesis of SSc by regulating these target genes.

In conclusion, it is possible that hsa-miR-155-3p and hsa-miR-155-5p are involved in regulating the occurrence and development of SSc fibrosis, immune response, and inflammation.These miRNAs may have the potential to serve as potential biomarkers for the clinical diagnosis and treatment of SSc.However, it is important to note that this study has limitations due to the small sample size.Further research with a larger sample size and more clinical data is needed to support this viewpoint.

Authors’ Contribution

Wang Yongfu: Experimental design, article revision; Sun Xiaolin:Data and image organization, article revision; Wang Baoyue: Data collection, analysis, and article writing.

All authors of this paper declare no conflicts of interest.