A total of 12 fresh tissue samples from patients with CSCC, with or without lymph node metastases, were collected during gynecological treatments at the Third Hospital of Shanxi Medical University (Taiyuan, China) during the period from June 2024 to August 2024. All selected patients did not have any other systemic malignant tumors, had not undergone surgery for any reason, and had no other comorbidities. In addition, they had not received any preoperative radiation or chemotherapy for CSCC, and their clinical, imaging and pathological data, and follow-up information were complete. Each sample underwent independent assessment and diagnosis by three senior clinical pathologists. After surgical removal, the fresh tissue specimens were promptly frozen and preserved in the biological specimen repository at the hospital. Written informed consent was obtained from patients and their families for the use of their samples and data, and the study protocol was approved by the Ethics Committee of the Third Hospital of Shanxi Medical University (approval no. YXLL-2024-117).

The human CSCC cell lines SiHa (cat. no. TCHu113; http://www.cellbank.org.cn/search-detail.php?id=187) and CaSki (cat. no. TCHu137; http://www.cellbank.org.cn/search-detail.php?id=210), both of which are human papillomavirus 16 positive, were obtained from The Cell Bank of Type Culture Collection of The Chinese Academy of Sciences. The H8 human normal cervical epithelial cell line (cat. no. TCH-C616; http://www.cas9×.com/bdxb/106381.html) was obtained from the Haixing Biosciences. The THP-1 human monocytic leukemia cell line (cat. no. CL-0233) was sourced from Wuhan Pricella Biotechnology Co., Ltd. The SiHa and CaSki cell lines are immortalized cell lines derived from cervical cancer tissues. The SiHa and CaSki cell lines were utilized at the 5th passage after purchase. SiHa and H8 cells were cultured in DMEM (cat. no. PYG0073; Boster Biological Technology) supplemented with 10% FBS (cat. no. PYG0109-500; Boster Biological Technology) and 1% antibiotics (penicillin-streptomycin). CaSki and THP-1 cell lines were cultured in RPMI-1640 medium (cat. no. PYG0006; Boster Biological Technology) supplemented with 10% FBS and 1% antibiotics. All cell lines were maintained in a cell culture incubator at 37°C with 95% air and 5% CO₂. Cells were cultured in a 6-well plate, ensuring that the cell count reached ~1×10⁶ and the confluence reached 70–80% before using the cells for subsequent experiments. THP-1 cells were used as they are widely used in scientific research as a model for studying macrophage function and differentiation. THP-1 cells are a cell line derived from human acute monocytic leukemia, and they have the potential to differentiate into macrophage-like cells, making them an important tool for studying the biological characteristics, functions and drug effects on macrophages. Due to their easy cultivation, rapid proliferation and the ability to be induced to differentiate under specific stimulation conditions, THP-1 cells have become a commonly used cell model for studying macrophage-related diseases (15).

The culture flask was gently shaken to mix the cell culture supernatant uniformly. An appropriate amount of cell culture supernatant was carefully aspirated into a new centrifuge tube, and an appropriate amount of fresh medium added to the culture flask. The aspirated culture supernatant was centrifuged at 4°C and 1,000 × g for 10 min, and then the supernatant was re-aspirated into a new spare centrifuge tube, discarding the remaining cell debris and impurities in the tube. The re-collected cell culture supernatant was filtered through a virus filter (0.22 µm). The filtered cell culture supernatant samples were stored at −20°C or −80°C to avoid repeated freeze-thaw cycles. Before use, the samples were thawed and the required medium was prepared for the experiment according to the following ratio: Conditioned medium:fresh medium=1:1.

THP-1 cells with good growth status and a density of 80–90% were selected. After digestion and counting, the cells were added to RPMI-1640 complete medium to achieve a concentration of 5×10⁵ cells/Ml. next, 100 ng/ml PMA was added, and the mixture was thoroughly mixed by pipetting. The cells were plated into a six-well plate and incubated in a cell incubator with 5% CO₂ at 37°C for 24 h. After 24 h, the supernatant was discarded, and the cells were washed three times with PBS. RPMI-1640 complete medium was added to allow the cells to recover for another 24 h. Subsequently, the supernatant was removed again, and the cells were washed three times with PBS. The previously collected Cell Culture Supernatant was then used as the co-culture conditioned medium, added to the six-well plate and supplemented with RPMI-1640 complete medium to a total volume of 2 ml per well. The cells were co-cultured for 24 h and prepared for subsequent experiments.

Cells were cultured in a 6-well plate, until the cell count reached ~1×10⁶, with a cell density of 70–80%. At this point, the cells were ready for analysis. Total RNA was extracted from cells and tissue samples using Total RNA Extraction Kit (cat. no. R1200; Beijing Solarbio Science & Technology Co., Ltd.). For mRNA quantification, the RNA was reverse transcribed into cDNA using a Reverse Transcription kit (cat. no. R223-01; Vazyme Biotech Co., Ltd.) according to the manufacturer's protocol. Subsequently, qPCR was performed using a Real-Time PCR kit (cat. no. Q711-02; Vazyme Biotech Co., Ltd.) according to the manufacturer's protocol. The thermocycling conditions were: Initial denaturation at 95°C for 30 sec; 40 cycles of 95°C for 3 sec and 60°C for 10 sec; and a final melting curve stage at 95°C for 15 sec, 60°C for 30 sec and 95°C for 15 sec. The relative mRNA expression levels were normalized to those of GAPDH using the 2^−ΔΔCq method (16). The sequences of the primers used for amplification were: GAPDH forward, 5′-TGACTTCAACAGCGACACCCA-3′ and reverse, 5′-CACCCTGTTGCTGTAGCCAAA-3′; MIF forward, 5′-ACCAGCTCATGGCCTTCGG-3′ and reverse, 5′-TTGGCCGCGTTCATGTCG-3′; NLRP3 forward, 5′-TGAACAGCCACCTCACTT-3′ and reverse, 5′-CAACCACAATCTCCGAAT-3′; apoptosis-associated speck-like protein containing a CARD (ASC) forward, 5′-TGGACGCCTTGGACCTCA-3′ and reverse, 5′-TTGGCTGCCGACTGAGGA-3′; caspase-1 forward, 5′-ATTACAGACAAGGGTGCT-3′ and reverse, 5′-GAATAACGGAGTCAATCAAA-3′; prostate stem cell antigen (PSCA) forward, 5′-AGCCCAGGTGAGCAACGA-3′ and reverse, 5′-TCATCCACGCAGTTCAAGC-3′; laminin subunit β 1 (LAMB1) forward, 5′-TACACCTCCTCTGATAGCG-3′ and reverse, 5′-ATCTCCTGAACCTCCCAC −3′; solute carrier 39 member 10 (SLC39A10) forward, 5′-TGCCTCATTTGTTTGCTG-3′ and reverse, 5′-TTCCACGATGCTGTCTGT-3′; solute carrier 35 member F2 (SLC35F2) forward, 5′-TGGACTCTTTCTGTTTGGCTAT-3′ and reverse, 5′-GGAGGCACGCTGCTTTCA-3′; solute carrier family 1 member 4 (SLC1A4) forward, 5′-CCATTGGGCTGCCTACTC-3′ and reverse, 5′-CCTTTCTTTGTTGCCTTCTG-3′; ArfGAP with coiled-coil, ankyrin repeat and PH domain-containing protein 3 (ACAP3) forward, 5′-AGGGCGACACCGTCATCT-3′ and reverse, 5′-TTCCGCACATCCTCTTTGA-3′; oxysterol binding protein like 6 (OSBPL6) forward, 5′-TCACTGTCTCAGGCACTC-3′ and reverse, 5′-TCTCATTGGCTACTTGCT-3′; TSCC22 domain family protein 3 (TSC22D3) forward, 5′-CACCCTGTTGAAGACCCT-3′ and reverse, 5′-TTACACCGCAGAACCACC-3′; asparagine synthetase (ASNS) forward, 5′-AACAGTTCGTGCTTCAGT-3′ and reverse, 5′-ATGTAACCCTGCGTAAGT-3′; coagulation factor III (F3) forward, 5′-CCGACGAGATTGTGAAGG-3′ and reverse, 5′-TGGCTGTCCGAGGTTTGT-3′; tribbles pseudokinase 3 (TRIB3), forward 5′-GCGGTTGGAGTTGGATGA-3′ and reverse, 5′-GCCACAGCAGTTGCACGA-3′; inducible nitric oxide synthase (iNOS) forward, 5′-ACATGGCTCAACAGCCTGAA-3′ and reverse, 5′-CCAAACACCAAGGTCATGCG-3′; arginase 1 (Arg1) forward, 5′-AATCCTGGCACATCGGGAATC-3′ and reverse, 5′-TCCTGGTACATCTGGGAACTTTC-3′; CD86 forward, 5′-ATTTGGAACCAAGCAAGAGCA-3′ and reverse, 5′-TACTCAGTCCCATAGTGCTGTCAC-3′; CD206 forward, 5′-ACCTCACAAGTATCCACACCATC-3′ and reverse, 5′-CTTTCATCACCACACAATCCTC-3′. Each experimental condition was replicated in three separate assays.

The tissue was removed from liquid nitrogen, and a piece about the size of a soybean was quickly cut and placed in an Eppendorf tube. This was rinsed 2–3 times with pre-cooled sterile PBS. An appropriate volume of RIPA buffer (cat. no. AR0105; Boster Biological Technology), phosphatase inhibitor and protease inhibitor (cat. no. P1045-1; Beyotime Biotechnology) was added in a ratio of 100:1:1. The mixture was ground thoroughly on ice and then placed on a shaker to allow for complete lysis for 30 min for use (with ice added). Cells were cultured in a 6-well plate until the cell count reached ~1×10⁶, with a cell density of 70–80%. Total protein was then extracted from the cells using RIPA buffer and quantified using a BCA Protein Assay kit (cat. no. AR118; Boster Biological Technology). SDS gels were prepared using a PAGE Gel Fast Preparation Kit (cat. no. AR0138; Boster Biological Technology). Following SDS-PAGE (typically using a gel with a concentration of 10% and loading 25 µg of sample per lane), the resolved proteins were transferred to PVDF membranes (cat. no. AR0136-04; Boster Biological Technology) and blocked using a protein-free rapid blocking solution (cat. no. AR0041; Boster Biological Technology) for 10 min at 25°C. The membranes were subsequently incubated with a primary antibody overnight at 4°C. The following primary antibodies were used: Anti-MIF (1:1,000 dilution; cat. no. DF6404; Affinity Biosciences), anti-GAPDH (1:3,000; cat. no. AP0063; Bioworld Technology, Inc.), anti-NLRP3 (1:1,000; cat. no. ab263899; Abcam), anti-ASC (1:1,000; cat. no. ab283684; Abcam), anti-caspase-1 (1:1,000; cat. no. ab207802; Abcam) and anti-TSC22D3 (1:2,000; cat. no. DF10077; Affinity Biosciences). After washing, the membranes were incubated with horseradish peroxidase-labeled goat anti-rabbit secondary antibody (1:3,000; cat. no. S0001; Affinity Biosciences) for 1 h at 25°C. Antibody antigen complexes were detected using Ultra-sensitive ECL Substrate (cat. no. AR1191; Boster Biological Technology). For the densitometric quantification of the blots, ImageJ software (version 1.8; National Institutes of Health) was used. Each experimental condition was replicated in three separate assays.

A Cell-Counting Kit-8 (CCK-8) assay (cat. no. AR1160; Boster Biological Technology) was used to assess cell viability. Cells were seeded in a 96-well plate at a density of 5,000-10,000 cells/well in 100 µl media and incubated at 37°C for 24 h. After incubation, 10 µl CCK-8 solution was added to each well and the plate was incubated for 1 h. The absorbance at 450 nm was measured using a microplate reader after 24, 48, 72, 96 and 120 h. Three replicate wells were used for each time point, and the mean absorbance value was calculated to plot cell growth curves.

To evaluate colony formation, 500–1,000 cells were seeded into 6-well plates and cultured for 2 weeks. Subsequently, the cells were fixed using 4% paraformaldehyde at room temperature for 15–30 min and stained using 0.5% crystal violet at room temperature for 10–20 min. Colonies consisting of >50 cells were considered viable and counted using a light microscope. Each experimental condition was replicated in three separate assays.

Transwell invasion assays were performed using 24-well Transwell plates with 8-µm pores (Corning Inc.), pre-coated with Matrigel (cat. no. Falcon 354480; BD Biosciences), which were incubated in a 37°C incubator for 30 min to 1 h until the Matrigel was completely solidified to form a uniform gel layer. A suspension containing 1×10⁵ cells in 500 µl DMEM with 1% FBS was added to the upper chamber, while 750 µl DMEM supplemented with 10% FBS was added to the lower chamber. After 48 h of incubation, the Matrigel and cells remaining in the upper chamber were removed using cotton swabs. The cells on the lower surface of the membrane were fixed in 4% paraformaldehyde at room temperature for 20–30 min and then stained with 0.5% crystal violet at room temperature for 15–30 min. Subsequently, cells in five microscopic fields (×200 magnification) were counted and images captured. All experiments were conducted in triplicate. For the migration assay, Transwell plates that were not coated with Matrigel were utilized. The remaining steps were similar to those of the invasion assay, with the exception of omitting the Matrigel coating and solidification processes.

Cells were cultured in a 6-well plate, until the cell count reached ~1×10⁶, with a cell density of 70–80%. At this point, the culture medium was collected and centrifuged at 1,000 × g for 20 min at 2–8°C to remove impurities and cell debris, and the supernatant was separated for analysis. The levels of IL-1β and IL-18 in the supernatant were determined using Human IL-1β ELISA Kit (cat. no. SEKH-0002, Beijing Solarbio Science & Technology Co., Ltd.) and Human IL-18 ELISA Kit (cat. no. SEKH-0028), according to the manufacturer's protocol. A linear fit method was used to generate a standard curve. Each experimental condition was replicated in three separate assays.

Cells were cultured in a 6-well plate, until a cell count of ~1×10⁶ and a cell density of 70–80% were achieved. The cells were then collected, processed into a single-cell suspension, and centrifuged at 300 × g for 5 min at 25°C. Subsequently, the cells were washed twice with 4 ml flow buffer, centrifuged at 300 × g for 5 min at 4°C, and then resuspended in 0.5 ml flow buffer. After adding 5 µl Annexin V/FITC and mixing well, the mixture was incubated at room temperature in the dark for 5 min. Next, 5 µl propidium iodide (PI) solution and 400 µl PBS were added, and flow cytometry detection was performed. Cell apoptosis was determined using an Annexin V-FITC Apoptosis Detection Kit (cat. no. CA1020; Beijing Solarbio Science & Technology Co., Ltd.). A total of 100 µl cell suspension containing 1×10⁶ cells was taken and 20 µl Fc receptor blocker was added before incubation at room temperature for 5–10 min. Next, 0.625 µl CD86 antibody (cat. no. 12-0862-82; Thermo Fisher Scientific, Inc.) was added to stain the cells, which were incubated on ice in the dark for 30–60 min. Subsequently, 1 ml flow cytometry staining buffer was added to wash the cells, which were then centrifuged at 400–600 × g for 5 min at room temperature. This washing step was repeated before detection. Flow cytometry analysis was performed using a BD FACSCelesta™ flow cytometer (BD Biosciences), and the data were analyzed using FlowJo version 10.8.1 (FlowJo LLC). Each experimental condition was replicated in three separate assays.

SiHa cells in which the expression of MIF had been knocked down and the corresponding negative control cells (vide infra) were collected during the logarithmic growth. As previously mentioned, total RNA and protein was extracted from the cells. Cells with a transfection efficiency >80% were selected for transcriptomics and proteomics sequencing.

The transcriptome data were generated using the Illumina sequencing platform and the raw data were processed to obtain high-quality clean reads. Total RNA was extracted from cells using Total RNA Extraction Kit (cat. no. R1200; Beijing Solarbio Science & Technology Co., Ltd.). To verify the quality and integrity of the samples, the Agilent 2100 bioanalyzer was used to analyze the RNA Integrity Number for assessing the completeness and purity of the RNA. The sequencing kit used was the NEBNext^® Ultra™ RNA Library Prep Kit for Illumina^® (NEB #E7530S/L; New England Biolabs). After preparing the sequencing library, its concentration was measured to ensure that the optimal concentration of the library was loaded onto the sequencer. The final loading concentration of the library was 10 nM. The Illumina NovaSeq 6000 (Illumina, Inc.) sequencing instrument was used, employing paired-end sequencing with a nucleotide length of 150 bp. The DESeq2 software package (version 1.20.0; http://bioconductor.org/packages/release/bioc/html/DESeq2.html) was used for inter-sample differential gene analysis. The expression ratios between the two groups of samples were expressed as fold change (FC) values, with screening criteria of P<0.05 and |log₂FC|>1 for differentially expressed genes (DEGs). Statistical analysis was performed with corrections for multiple comparisons using the false discovery rate method.

A 0.2-mg protein sample was used for Tandem Mass Tag analysis, using TMT^® Mass Tagging Kits and Reagents according to the manufacturer's protocol (Thermo Fisher Scientific, Inc.). A high-resolution mass spectrometer (Q Exactive™ plus; Thermo Fisher Scientific, Inc.) was used to perform the quantitative proteomics analysis. The mass spectrometer employed a data-dependent acquisition mode, with a full scan range of 350–1,500 m/z. The resulting spectra from each run were searched separately against 1327172-1327172-Homo_sapiens using the Fasta (109,914 sequences) database with the Proteome Discoverer 2.4 search engine (Thermo Fisher Scientific, Inc.). Proteins with significant differences between the two groups of cells (P<0.05 and |log₂FC|>1), were considered differentially expressed proteins. Each experimental condition was replicated in three separate assays.

To generate retroviral vectors containing short hairpin RNAs (shRNAs) targeting MIF and a shRNA control (shCtrl) the following oligodeoxyribonucleotide sequences were annealed and subcloned between the AgeI and EcoRI restriction sites of a BR-V108 vector (Shanghai GeneChem Co., Ltd.): shCtrl: Pbr17579-a, CCGGGGGCCTCTTTCTGCTCTATAACTCGAGTTATAGAGCAGAAAGAGGCCCTTTTTG and Pbr17579-b, AATTCAAAAAGGGCCTCTTTCTGCTCTATAACTCGAGTTATAGAGCAGAAAGAGGCCC; shMIF-1: Pbr17580-a, CCGGGGGTCTACATCAACTATTACTCGAGTAATAGTTGATGTAGACCCTTTTTG and Pbr17580-b, AATTCAAAAAGGGTCTACATCAACTATTACTCGAGTAATAGTTGATGTAGACCC; shMIF-2: Pbr17581-a, CCGGTGCCAGTACGTGCAAGGTGTTCTCGAGAACACCTTGCACGTACTGGCATTTTTG and Pbr17581-b, AATTCAAAAATGCCAGTACGTGCAAGGTGTTCTCGAGAACACCTTGCACGTACTGGCA.

Retroviral particles were generated through the transfection of TOP10 E. coli Competent cells (cat. no. CB104-03, Tiangen Biotech, Co., Ltd.) with the BR-V108 constructs and the necessary packaging plasmids, using Lipofectamine^® 2000 (Thermo Fisher Scientific, Inc.). A second-generation lentiviral packaging system was employed, utilizing 20 µg GV vector plasmid, 15 µg pHelper 1.0 vector plasmid and 10 µg pHelper 2.0 vector plasmid for transfection. The transfection was incubated in a 37°C incubator for 72–96 h. Regarding the multiplicity of infection, a value of 10 was used to infect the target cells. SiHa and CaSki cells were cultured in 6-well plates until they reached 50–60% confluence. Subsequently, the cells were transduced with either shRNA or the empty BR-V108 vector (negative control) in a 37°C incubator for 72–96 h and selected in a medium containing 10 µg/ml Puromycin for 3–4 days to allow for the selection of stably transfected cells. The efficiency of MIF knockdown was assessed at various time points.

The pcDNA3 expression plasmids were acquired from Invitrogen (Thermo Fisher Scientific, Inc.). The empty plasmid was employed as a control, with a transfection concentration of 1.5 µg/ml. Plasmid transfection was carried out using Lipofectamine 2000 according to the manufacturer's guidelines. In brief, cells were plated in 6-well plates at a concentration of 2×10⁵ cells/well and permitted to adhere overnight. Subsequently, the plasmid was diluted in Opti-MEM medium (Life Technologies; Thermo Fisher Scientific, Inc.) and combined with Lipofectamine 2000. This combination was then introduced to the cells and incubated for 4–6 h at 37°C in an atmosphere containing 5% CO₂. The medium was then exchanged with fresh DMEM supplemented with 10% FBS, and the cells were further incubated for 24 h in an environment of 95% air and 5% CO₂ prior to use in subsequent experiments. The empty plasmid served as the control (Ctrl) for MIF-OE and TSC22D3-OE.

To prepare cells with shMIF/TSC22D3-OE co-transfections, the SiHa cells with MIF knockdown were combined with the TSC22D3-OE plasmid and Lipofectamine 2000, and subjected to the aforementioned transfection protocol. The efficiency of overexpression or knockdown was assessed at various time points.

Following the adjustment of THP-1 cell density to 5×10⁵ cells/ml, 2 ml cell suspension was added to each well of a 6-well plate, and supplemented with phorbol 12-myristate 13-acetate (100 ng/ml). The plate was then incubated in a constant temperature incubator at 37°C with 5% CO₂ for 48 h. When 85% of the suspended THP-1 monocytes had adhered to the plate, the supernatant was aspirated and discarded, and replenishment with fresh complete medium was performed. Differentiation was induced by adding LPS (100 ng/ml) and IFN-γ (20 ng/ml) for M1 polarization, and IL-4 (20 ng/ml) for M2 polarization. The cells were further incubated in under the same incubator conditions for an additional 48 h. Under high-power microscopy, the cells exhibited larger cell bodies and elongated protrusions, indicating differentiation into M1 and M2 macrophages, respectively. Each experimental condition was replicated in three separate assays.

Publicly available databases were used for expression, survival and prognostic analyses. For analysis using the Gene Expression Profiling Interactive Analysis (GEPIA) database (http://gepia.cancer-pku.cn/), the expression of MIF was compared between normal and CSCC tissues, and among different cancer stages. In addition, in the ‘Survival Analysis’ module, the gene symbol MIF was input, the specific tumor type was selected, and overall survival (OS) was analyzed. It was not possible to restrict the time range in GEPIA to remove the late-stage crossover of the survival curves. Similarly, the UALCAN database (http://ualcan.path.uab.edu/) was used to compare the expression of MIF between normal and primary CSCC tissues, and among different cancer stages. Kaplan-Meier Plotter (http://kmplot.com/analysis/) was used to generate the Kaplan-Meier survival curve.

Statistical analysis was performed using SPSS version 22.0 (IBM Corp.). Graphs were created and analyzed using GraphPad Prism version 9.5 (Dotmatics) and Adobe Illustrator Creative Cloud 2017 (Adobe Systems Europe, Ltd.). For quantitative data, normality and homogeneity of variance were assessed. Data with a normal distribution were expressed as the mean ± standard deviation, while non-normally distributed data were presented as the median (interquartile range). When comparing data between two groups, an independent samples t-test was used if the data were normally distributed and a Mann-Whitney U test was used for non-normally distributed data. Comparisons between multiple groups were performed using a one-way ANOVA followed by least significant difference or Tukey's post hoc tests. P<0.05 was considered to indicate a statistically significant difference.

Initial analysis of MIF expression in cervical cancer using the GEPIA database revealed that MIF levels in cervical cancer tissues were significantly elevated compared with those in normal cervical tissues (Fig. 1A). Further analysis using the UALCAN database confirmed that MIF expression in cervical cancer was higher than that in normal tissue (Fig. 1C). Additionally, MIF expression levels increased as the stage of cervical cancer increased, as evidenced by analyses from both databases (Fig. 1B and D). In fresh CSCC tissues, MIF expression levels were significantly higher in the tissues of patients with lymph node metastasis than in those without (Fig. 1E-G). Furthermore, MIF expression levels were significantly elevated in the SiHa and CaSki CSCC cell lines compared with those in the H8 normal cervical epithelial cell line (Fig. 1H), highlighting the potential role of MIF in cervical cancer progression. Analysis of OS data from 292 patients with cervical cancer using GEPIA indicated that high MIF expression was associated with significantly poorer OS compared with that of patients with low MIF expression (Fig. 1I). This was corroborated by data obtained using Kaplan-Meier Plotter, confirming the association between high MIF expression and reduced OS in patients with cervical cancer (Fig. 1J). These results underscore the potential significance of MIF in cervical cancer progression and prognosis.

To investigate the impact of MIF on the malignant behavior of CSCC, MIF-knockdown plasmids were designed and packaged into lentiviral particles for transfection into SiHa and CaSki CSCC cells. Fluorescence microscopy revealed markedly higher fluorescence intensity in the SiHa cells than in the CaSki cells (Fig. 2A), indicating superior infection efficiency in the SiHa cells. Therefore, SiHa cells were selected for use in subsequent experiments. The efficiency of MIF knockdown and overexpression in the SiHa cells was then evaluated (Fig. 2B-G).

To investigate the effects of MIF knockdown on CSCC progression, a CCK-8 assay was performed, which revealed a significant reduction in the proliferative ability of SiHa cells in the shMIF groups compared with that of cells in the control group (Fig. 3A). Additionally, flow cytometry indicated a notable increase in the total percentage of apoptotic SiHa cells in the shMIF groups compared with that in the control group, with significantly higher percentages of both early and late apoptotic cells (Fig. 3D). The colony formation assay demonstrated a substantial reduction in the colony formation capacity of SiHa cells in the shMIF groups, as evidenced by a significant reduction in the number of colonies compared with those in the control group, as well as a clear reduction in the area of the colonies (Fig. 3E). Furthermore, the Transwell assay revealed a significant reduction in the invasive capacity of SiHa cells in the shMIF groups compared with that of the control group (Fig. 3F).

Further investigation of changes in the inflammasome following MIF knockdown included assessment of the expression of the inflammasome-related proteins NLRP3, ASC and caspase-1 and their respective mRNAs. The results revealed significant reductions in the mRNA and protein expression levels of NLRP3, ASC and caspase-1 in the shMIF groups compared with those in the control group (Fig. 3G-J). Additionally, the ELISA analysis of inflammasome-related factors IL-1β and IL-18 in the supernatant of SiHa cells revealed that secretion of these factors was reduced following MIF knockdown compared with that in the control group (Fig. 3B and C).

By comparison, the proliferative ability of cells in the MIF-OE group was significantly higher than that of cells in the control group (Fig. 4A). In addition, flow cytometry revealed a significant reduction in the apoptotic rate of the MIF-OE group compared with that of the control (Fig. 4D). Additionally, the colony formation assay showed a significant increase in the colony formation capacity of the cells due to MIF overexpression (Fig. 4E). The results of the Transwell assays indicated a significant increase in the invasive ability of cells following MIF overexpression (Fig. 4F). The expression of inflammasome-related proteins and their respective mRNAs was assessed, and significant increases for all proteins and mRNAs were observed in the MIF-OE group compared with those in the control group (Fig. 4G and H). Furthermore, ELISA analysis revealed that MIF overexpression significantly increased the levels of IL-1β and IL-18 in the supernatant of SiHa cells (Fig. 4B and C). These results suggest that MIF may promote CSCC progression and is associated with inflammasome activation.

To investigate downstream molecules potentially regulated by MIF in the development of CSCC, SiHa cells with the knockdown of MIF expression were used for transcriptomic and proteomic sequencing to identify changes in the expression of the downstream genes, both upregulated and downregulated. Based on the observation that shMIF-2 exhibits higher knockdown efficiency than shMIF-1, shMIF-2 was selected for use in subsequent experiments. DEGs were screened based on criteria of P<0.05 and |log₂FC|>1. Heat maps and volcano plots were generated following the multi-omics screening of downstream genes (Figs. 5, 6A and B). Correlation analysis of the multi-omics sequencing results revealed 10 common DEGs in both the transcriptome and proteome sequencing data (P<0.005 and |log2FC|>0.5; Fig. 6C), consisting of three upregulated genes (PSCA and LAMB1) and eight downregulated genes (SLC35F2, SLC1A4, ACAP3, OSBPL6, TSC22D3, ASNS, F3 and TRIB3). Validation performed by the RT-qPCR analysis of MIF-knockdown SiHa cells confirmed the significant upregulation of PSCA and LAMB1 (P<0.01) and significant downregulation of SLC35F2, SLC14A, ACAP3, OSBPL6, TSC22D3, ASNS, F3 and TRIB3 (P<0.05; Fig. 6D). The experimental validation of MIF expression aligned with the results of sequencing, confirming the reliability of these results. The downregulated gene TSC22D3 was selected for further investigation given the limited reports on its role in cervical cancer. Notably, its known roles in inflammation and immune regulation suggest a significant role in the regulation of tumor growth (17–20); therefore, it is hypothesized that TSC22D3 may significantly influence CSCC progression.

Subsequently, the expression of TSC22D3 in CSCC tissues was investigated. The findings revealed that the mRNA and protein expression levels of TSC22D3 in the tissues of patients with lymph node metastasis were significantly higher compared with those in the tissues of patients without lymph node metastasis (Figs. 1F and G, and 6E). These results suggest that TSC22D3 may be a pivotal gene with similar pro-tumor inflammatory properties to MIF, and their combined interaction may promote CSCC progression.

Rescue experiments were performed to explore the functional interaction between MIF and TSC22D3. Separate MIF knockdown and TSC22D3 overexpression plasmids were constructed and packaged into lentiviruses, which were co-infected into SiHa cells. The transfection efficiency of the plasmids was subsequently confirmed (Fig. 7A-B, D-E).

Experiments were then performed to investigate the biological behaviors of the transfected SiHa cells. The results of the CCK-8 assays indicate a significant reduction in the proliferative capacity of SiHa cells in the shMIF group compared with the control group (Fig. 7C). Moreover, following TSC22D3 overexpression, the proliferative ability of SiHa cells in the shMIF + OE-TSC22D3 group was higher than that in the shMIF group, yet lower than that in the OE-TSC22D3 group, although this latter variation has not yet shown statistical differences. These findings suggest that TSC22D3 overexpression may partially reversed the reduction in proliferation of SiHa cells induced by MIF knockdown. Moreover, the analysis of apoptosis using flow cytometry indicated that TSC22D3 overexpression partially attenuated the increase in apoptosis of SiHa cells following MIF knockdown (Fig. 7F and I). In addition, colony formation assays demonstrated that TSC22D3 overexpression partially reversed the reduction in the colony formation capacity of SiHa cells following MIF knockdown (Fig. 7G and H). The results of the Transwell invasion assays are presented in Fig. 7J and K, and indicate that the number of invasive SiHa cells in the shMIF group was significantly reduced compared with that in the control group. This suggests that the knockdown of MIF had an inhibitory effect on the invasive capacity of SiHa cells. Furthermore, the overexpression of TSC22D3 in the shMIF + OE-TSC22D3 group resulted in a partial restoration of the invasive ability of SiHa cells, as evidenced by an increase in the number of invasive cells compared with that in the shMIF group. However, the invasive capacity of the shMIF + OE-TSC22D3 group remained lower than that of the OE-TSC22D3 group, indicating that the overexpression of TSC22D3 can partially reverse these effects.

To investigate the roles of MIF and TSC22D3 in inflammasome formation in CSCC, the expression of inflammasome-related proteins was assessed. The results of western blot analysis revealed that the expression levels of NLRP3, ASC and caspase-1 were significantly reduced in the shMIF group compared with those in the control group. However, upon TSC22D3 overexpression, the protein expression levels of these inflammasome-related molecules in the shMIF + OE-TSC22D3 group were increased compared with those in the shMIF group, yet were lower than those in the OE-TSC22D3 group (Fig. 7L and M), although this latter variation has not yet shown statistical differences. Furthermore, the results of ELISA analysis indicated that the levels of IL-18 and IL-1β in the supernatant of SiHa cells were significantly decreased in the shMIF group compared with those in the control group. Following TSC22D3 overexpression, the expression of IL-18 and IL-1β in the supernatant was significantly higher in the shMIF + OE-TSC22D3 group compared with that in the shMIF group, yet significantly lower than that in the OE-TSC22D3 group (Fig. 7N and O). These results indicate that TSC22D3 overexpression partially reversed the impaired ability of SiHa cells to form inflammasomes following MIF knockdown.

The tumor microenvironment significantly influences cancer initiation and progression, with immune cell infiltration being a crucial target in cancer immunotherapeutic strategies (21–23). Tumor cells release cytokines and other mediators that recruit macrophages and other inflammatory cells, which promote tumor growth and metastasis (24–26). Therefore, the role of MIF, an inflammatory factor, in macrophage recruitment in CSCC was investigated. Supernatants from cultured SiHa cells with established MIF-OE transfection and control cells were collected, and elevated mRNA and protein levels of MIF in the supernatants were confirmed by RT-qPCR and western blotting (Fig. 8A-C). These cell supernatants were then co-cultured with THP-1 cells. Results from the CCK-8 assay demonstrated a significant increase in THP-1 cell proliferation in the MIF-OE group compared with that in the control group (Fig. 8D). Furthermore, co-culture with the MIF-OE-transfected cell supernatant was revealed to induce a significant increase in the number of THP-1 cells migrating across the Transwell membrane compared with that of the control, which is indicative of increased migratory ability post-MIF overexpression (Fig. 8E). These findings suggest that the overexpression of MIF in CSCC cells may promote macrophage recruitment.

To explore whether MIF regulates macrophage recruitment through its interaction with TSC22D3, MIF expression was knocked down and TSC22D3 expression was overexpressed simultaneously in SiHa cells (Fig. 8F and G). Co-culture of THP-1 cells with the cell culture supernatant caused a significant reduction in the proliferative ability of the cells in the shMIF group compared with that in the control group. Upon TSC22D3 overexpression, the proliferative ability of THP-1 cells in the shMIF + OE-TSC22D3 group was increased compared with that in the shMIF group, but lower than that in the OE-TSC22D3 group (Fig. 8H), and both comparisons showed statistically significant differences.. This result indicates that TSC22D3 overexpression partially reversed the reduction in THP-1 cell proliferation caused by MIF knockdown. Similarly, Transwell experiments demonstrated that the overexpression of TSC22D3 significantly attenuated the reduction in the migratory ability of the THP-1 cells following MIF knockdown (Fig. 8I).

Macrophages play a pivotal role in the infiltration of inflammatory cells at tumor sites, exhibiting significant functional plasticity and the ability to rapidly polarize between M1 and M2 activation states (27–29). To investigate the role of MIF in the induction of macrophage polarization, MIF expression in CSCC SiHa cells was manipulated and the supernatant was cultured with THP-1 cells, which had been induced to undergo polarization towards M1 and M2 macrophage phenotypes. Prior to MIF manipulation, RT-qPCR analysis confirmed the successful establishment of the in vitro macrophage polarization model by demonstrating the significant upregulation of M1-related genes (iNOS and CD86) in the M1 control group and M2-related genes (ARG1 and CD206) in the M2 control group (Fig. 9A-D). The subsequent manipulation of MIF expression levels in SiHa cells revealed that its overexpression significantly increased the expression levels of the M2 surface markers ARG1 and CD206 and decreased the expression levels of the M1 surface markers iNOS and CD86 in the respective macrophage models compared with those in the control group when cultured with the SiHa cell supernatant, whereas MIF knockdown yielded the opposite effects (Fig. 9E-L). Flow cytometry corroborated these findings, indicating that MIF overexpression significantly increased the expression of the M2 surface marker CD206 and decreased that of the M1 surface marker CD86 compared with that in the control group, whereas MIF knockdown induced the opposite effects, with all differences being statistically significant (Fig. 9M-O). These results indicate that MIF overexpression promotes macrophage polarization toward the M2 phenotype while inhibiting polarization toward the M1 phenotype.