Dysregulation of MicroRNA-181a-5p Targets TNFAIP3 to Promote MIF-CXCR4 Signaling and Immune Inflammatory Remodeling in Chronic Myeloid Leukemia

Aims of the study

The objective of this research was to compare the miR-181a expression levels and blood concentrations of MIF, TNFAIP3, and CXCR4 in CML patients with those in healthy controls. The study also aimed to use bioinformatics analysis to determine the downstream impacts on pathways mediated by NF-κB and the regulatory link between miR-181a and TNFAIP3.

Study design

This case-control experimental study was designed to compare the gene expression of miR-181a and the serum concentrations of selected biomarkers (MIF, TNFAIP3, CXCR4) between CML patients and healthy controls. Bioinformatics analysis was additionally performed to investigate molecular interactions between miR-181a and its target genes.

Ethical approval

The study protocol was approved by the Iraqi Ministry of Health/Medical City/Center of Hematology, Baghdad, Iraq (approval number 41008, dated 14-11-2024). Informed written consent was obtained from all participants. The study was carried out from November 2024 to November 2025.

Sample size and subjects

The study included 90 people: 33 healthy controls who were the same age and sex as the participants and 57 patients with chronic-phase CML. Hematology clinics and hospitals in Iraq’s capital city of Baghdad were the sites of participant recruitment.

Inclusion and exclusion criteria

Participants were to be adults aged >20 years who had recently been diagnosed with chronic-phase CML according to molecular, hematological, and clinical criteria. None of the health controls had a family history of autoimmune diseases, chronic inflammatory illnesses, or hematologic malignancies were included in this study. Patients with CML in its rapid or blast crisis phases, individuals using immunosuppressive medication, or those suffering from autoimmune or infectious disorders at the same time were excluded in this study.

Hematological parameters

Using the ADVIA 2120i Hematology Analyzer (Siemens Healthcare Diagnostics, Germany) at the Research Unit, College of Health and Medical Techniques/Baghdad, Middle Technical University, we immediately after blood collection measured complete blood counts (CBC), which include Hb, RBCs, WBCs, and PLTs.

Serum biomarker measurement

Enzyme-linked immunosorbent assay (ELISA) kits (Sunglong Biotech Co., China) were used to quantify the serum concentrations of TNFAIP3, MIF, and CXCR4.

RNA extraction

Following the manufacturer’s instructions, 500 μL of serum samples were treated with TRIzolTM Reagent (Thermo Scientific, USA) to extract total RNA, which includes short RNAs. The RNA pellet was rinsed with 70% ethanol and resuspended in nuclease-free water after being separated with chloroform and isopropanol for RNA precipitation. In order to determine the amount and quality of the RNA, a Quantus Fluorometer (Promega, USA) was used.

cDNA synthesis

Complementary DNA (cDNA) was produced from RNA extraction by means of the GoScriptTM Reverse Transcription System (Promega, USA). Reverse transcription with random primers and the GoScript enzyme was carried out at 42°C for 60 minutes after the RNA and primer were denaturated at 70°C for 5 minutes. The enzyme was then inactivated at 70°C for 15 minutes to complete the operation.

Primers used in this study

The sequences for miR-181a and RNU43 were obtained from the iRbase database (https://www.mirbase.org/) and primers were designed consequently. The following primers were manufactured by Macrogen (Korea) and used in the study: miR-181a Forward Primer (miR-181a-F2): 5′-TGTTTGACCATCGACCGTTG-3′. miR-181a Reverse Transcription Primer (miR-181a-RT): 5′-GTTGGCTCTGGTGCAGGGTCCGAGGTATTCGCACCAGAGCCAACGGTACA-3′. RNU43 Reverse Transcription Primer (RNU43-RT): 5′-GTTGGCTCTGGTGCAGGGTCCGAGGTA TTCGCACCAGAGCCAACAATCAG-3′. RNU43 Forward Primer (RNU43-F): 5′-GTGAACTTATTGACGGGCG-3′. Universal Reverse Primer: 5′-GTGCAGGGTCCGAGGT-3′. The optimal annealing temperature was 55°C for each set of primers. To make working solutions, the concentration of primers was 10 pmol/μL, and the stock concentration was 100 pmol/μL, both of which were adjusted in nuclease free water.

Gene expression quantification (Real-Time PCR)

The relative expression of miR-181a was measured via qRT-PCR on a Mic qPCR Cycler (Bio Molecular Systems, Australia) with the GoTaq qPCR Master Mix (Promega, USA). A cDNA template, specific primers, and SYBR Green master mix were all components of each 20 μL PCR reaction. Initial denaturation was done at 95°C for 5 minutes, followed by 40-cycles of 95°C for 20 seconds, 55°C for 20 seconds (fluorescence collection), and 72°C for 20 seconds as the thermal cycling conditions. The relative expression was determined using the 2^-ΔΔCt method, also known as the Livac method, after normalizing the expression levels against the house keeping gene RNU43.

Bioinformatics analysis

Bioinformatics was used to predict the miR-181a-TNFAIP3 interaction utilizing the miRTarBase and TargetScan databases. Utilizing the STRING database, protein-protein interaction networks incorporating TNFAIP3, MIF, and CXCR4 were generated. The DAVID and Enrichr platforms were used to perform functional enrichment analysis on biological processes and signaling pathways.

Statistical analysis

The SPSS software (version 27) was used for all statistical analyses. An independent samples t-test was used to examine the differences between the control group and the CML patients. The correlation analysis was used to investigate the association between miR-181a expression and serum biomarker values. To evaluate the diagnostic adequacy of miR-181a and the investigated biomarkers, ROC curve analysis was carried out. Statistical significance was established when the p-value was less than 0.05. The relative gene expression of the target genes was assessed using the Livak (2^−ΔΔCt) method.¹³

Demographic characteristics of the study population

There was no significant difference in the age and sex distributions between the control. Percentages were derived from group totals (CML n = 57: 28 males, 29 females; Control n = 33: 16 males, 17 females). The sex distribution therefore corresponds to 49.1% male/50.9% female in CML and 48.5% male/51.5% female in controls (pairs sum to 100%). A chi-square test for the sex and age variable showed no difference across groups in sex distribution. For age (4 categories), the omnibus test showed χ² = 0.280, df = 3, p = 0.964 (NS) and demonstrated no disparity in age distributions, as indicated in Table 1 (p > 0.05).

Profile of study participants

Table 2 showed that there were statistically significant changes in major hematological parameters between healthy controls and CML patients. The CML group had significantly lower hemoglobin levels (8.74 ± 0.20 g/dL) when compared to the control group (11.41 ± 0.48 g/dL; p = 0.0000). Patients had significantly reduced RBC counts (3.51 ± 0.04 ×10⁶/μL) compared to controls (4.69 ± 0.12 ×10⁶/Μl, p = 0.0000). Compared to the controls, the CML group had significantly higher WBCs counts (27.87 ± 0.77 ×10³/μL) with a p-value of 0.0000. In comparison to the controls, patients had significantly decreased platelet counts (174.69 ± 2.49 ×10³/μL) with a p-value of 0.0001. Chronic myeloid leukemia is characterized by severe hematologic dysregulation, as shown in Table 2.

Biomarker expression

Comparing CML patients with healthy controls using quantitative analysis of circulating biomarkers showed striking differences. Signifying increased macrophage activation, MIF levels were significantly higher in the CML group (172.73 ± 8.22 pg/mL) in comparison to the controls (102.25 ± 3.88 pg/mL; p = 0.0000). The TNFAIP3 levels were considerably lower in CML patients (231.91 ± 4.85 pg/mL) compared to controls (409.89 ± 11.54 pg/mL; p = 0.0000), which may indicate that the anti-inflammatory regulation through the NF-κB pathway was suppressed. Patients had significantly increased CXCR4 expression (125.06 ± 5.05 pg/mL) compared to controls (63.30 ± 3.49 pg/mL; p = 0.0000) suggesting that there was an increase in chemokine receptor signaling and potential leukemic cell movement. The inflammatory and immunological dysregulation linked to CML pathogenesis is highlighted by these biomarker profiles, as shown in Figure 1.

Figure 1. Serum levels of inflammatory and signaling biomarkers in CML patients and healthy controls.

(A) MIF, (B) TNFAIP3, and (C) CXCR4 in CML patients (red bars) versus control subjects (blue bars). (p < 0.01, **).

Relative expression of miR-181 in CML patients and control

Patients with chronic myeloid leukemia (CML) had significantly higher transcript levels of miR-181 (2.28) than healthy controls fold change (1) according to relative quantification analysis (p = 0.0001) reported in Table 3.

Correlation between miR-181 expression and biomarkers

In the study population, the Pearson correlation analysis showed a slight association between the miR-181-fold change and the levels of MIF (r = 0.617, p < 0.0001) and CXCR4 (r = 0.630, p < 0.0001). The expression of miR-181 was shown to be strongly correlated negatively with TNFAIP3 levels (r = -0.758, p < 0.0001). Based on these results it appears that CML-specific inflammatory and chemokine signaling patterns are linked to miR-181 expression. As reported in Table 4.

Diagnostic performance of biomarkers and miR-181

In CML patients, ROC analysis showed that the sensitivity, specificity, AUC, cutoff, and p-value for MIF were 80.6%, 100.0%, 0.873, 80.10 pg/mL and p<0.001, respectively; for CXCR4 were 81.9%, 100.0%, 0.929, 68.10 pg/mL, and p<0.001, respectively; for TNFAIP3 were 6.9%, 100.0%, 0.142, 523.32 pg/mL, and p<0.001, respectively; and for miR-181a-5p were 100%, 11.1%, 0.201, 1.00 and p<0.001, respectively. These results are presented in Table 5 and Figure 2.

Figure 2. ROC curves of MIF, TNFAIP3, CXCR4, and miR-181a-5p in CML patients.

miR-181 and biomarker interactions

Bioinformatics analysis of miR-181a target interactions and regulatory pathways

The TNFAIP3 gene was predicted to be a likely direct target of hsa-miR-181a-5p in silico ( Figure 3). Target prediction was carried out with miRWalk 3.0 (version 2018 release), TargetScanHuman 8.0, and miRDB (version 6.0). The prediction was made with a minimum free energy (MFE) threshold ≤ -15 kcal/mol, binding probability ≥ 0.70, and seed region complementarity of ≥ 7 consecutive nucleotides. In miRWalk, miR-181a-5p had a noteworthy binding site within the CDS of TNFAIP3 mRNA at positions 394–406 with an MFE of -18.5 kcal/mol and a binding probability of 0.923. The predicted duplex has 11 consecutive base pairs in a 12-base region indicating a stable and efficient interaction. However, TNFAIP3 was not predicted to be a target by TargetScan or miRDB which underscores the differences in the databases. Functionally TNFAIP3 is a known negative regulator of NF-κB signaling. Suppression of TNFAIP3 by miR-181a-5p would relieve this inhibition and thus, promote NF-κB activity. Functional enrichment and network analyses were performed by STRING (version 12.0) and NDExBio which showed MIF and CXCR4 to be downstream targets of NF-κB. There were no sites of direct binding predicted for miR-181a-5p with MIF or CXCR4 in the prediction databases, but the results outlined above indicate that miR-181a-5p is also increased MIF and CXCR4 levels by indirectly targeting and downregulating TNFAIP3 thus stimulating inflammatory signaling pathways involved in the pathogenesis of CML.

Figure 3. Bioinformatic model of miR-181a-mediated post-transcriptional regulation of TNFAIP3 and its downstream impact on NF-κB signaling, MIF, and CXCR4 expression in CML.