This study included 43 diagnosed DLBCL patients and 43 healthy physical examination patients. All patients received R-CHOP based immunotherapy. The review committee of the First Hospital of Qiqihar approved this study after obtaining informed consent (2023-KY-001) following the Helsinki Declaration.

Collect peripheral blood from DLBCL patients into EDTA anticoagulant blood collection tubes, and mix the blood evenly in a sterile 50 mL tube. Add lymphocyte separation solution, blood, and PBS in a ratio of 1:1:1, and slowly add the above blood diluent along the tube wall to the 45 mL mark. Centrifuge 500g at room temperature for 30 minutes. Depending on the density of each component in the blood, the tube will be filled with a pale yellow plasma layer, a mononuclear cell white membrane layer, a transparent separation solution layer, and the bottom red blood cell layer from top to bottom after centrifugation.

Separate monocytes: Gently aspirate the upper plasma layer using a pipette, transfer the white membrane layer to a new 50 mL tube, add PBS to 50 mL, centrifuge and discard the supernatant, then scatter the cell pellet, add PBS to 50 mL, centrifuge again and discard the supernatant. Finally, the cell pellet was dispersed and purified using a monocyte positive separation kit.

To carry out our investigation, we accessed two gene expression datasets via the Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) to conduct differential expression analysis and survival analysis. The number of diffuse large B-cell lymphoma and human healthy tonsils was 55 and 33, respectively in GSE56315 dataset [39], which were used for differential expression analysis to explore variations in CEBPB gene expression levels between normal and DLBCL tissues. The GSE87371 dataset [40] contains clinical details and gene expression data of 223 DLBCL patients, which were analyzed to study the association between elevated CEBPB expression and unfavorable prognosis in DLBCL patients.

DLBCL cell lines, KARPAS422 (ATCC, CRL-2632) and WSUDLCL2 (ACC 575), were acquired from the American Type Culture Collection (ATCC) and the Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures (DSMZ, Braunschweig, Germany), respectively. Human lymphoblastoid B cells (GM12878, ATCC CRL-2230) were also acquired from ATCC. The DLBCL cell lines were the experimental group, with GM12878 as the control group. The DLBCL cell lines and the control group were cultured in the same manner, with both sets of cells being cultured in RPMI-1640 medium containing 10% fetal bovine serum (FBS) at 37 °C in a 5% CO₂ environment. Authenticity of all cell lines was confirmed through short tandem repeat (STR) profiling within the last three years (during the experimental period), ensuring the reliability of the experimental outcomes.

In the experiment, human THP-1 monocytes (TIB-202, ATCC) was cultured in α-MEM medium supplemented with 10% fetal calf serum and 1% penicillin–streptomycin. All THP-1 monocytes were differentiated into macrophages after 72 hours of treatment with 100 ng/mL phorbol 12-myristate 13-acetate (PMA).

To ensure the reliability of our experimental results, all cell lines utilized in this study underwent periodic testing for mycoplasma contamination. Prior to commencing any experimental procedures, cell line authentication and mycoplasma testing were performed to confirm the absence of mycoplasma contamination. This validation process was carried out routinely within the experimental period.

All animal experiments have been approved by the Biomedical Ethics Committee of the First Hospital of Qiqihar (Approval No.: 2023-KY-001). Six to eight week old male SCID mice with an average weight of 20 grams were purchased from the Chinese Academy of Sciences (Shanghai, China), Shanghai Institute of Materia Medica. In the study, mice were anesthetized by intraperitoneal injection of 0.3–0.4 mL of 0.3% pentobarbital sodium to ensure a painless state. Under aseptic conditions, 1 × 10⁷ low-passage human DLBCL OCI-Ly1 cells (ATCC) were placed into the left inguinal region of the mice. Introduce every IL-1B silenced/overexpressed macrophage (sh-IL1B or OE-IL1B macrophage) into the bloodstream in the left inguinal region of mice (inject 200 μL of 20 grams of mouse body weight). Monitor the weight and tumor growth of mice weekly, and record changes in tumor diameter and volume. Use a digital caliper every other day to assess tumor size. Tumor volume= (length × width 2) × 0.5. This study complies with the guidelines of our Institutional Animal Care and Use Committee and the Ethical Vertebrate and Regulated Invertebrate Research Committee, ensuring ethical behavior throughout the entire process.

In this study, we employed human-derived THP-1 macrophages (obtained from ATCC, catalog number TIB-202) and KARPAS422, WSUDLCL2 to investigate the functional silencing of IL1B and CEBPB genes. To achieve gene silencing, THP-1 macrophages were first differentiated using phorbol 12-myristate 13-acetate (PMA) at a concentration of 100 ng/mL for 72 hours. After differentiation, we utilized shRNA plasmids specifically designed to target IL1B and CEBPB (Merck, New York, NY, USA). The sequences of the shRNA used for gene silencing are detailed in Table 1. Transfection was carried out using Lipofectamine 3000 (Invitrogen, Thermo Fisher Scientific, New York, NY, USA), following the manufacturer ’s protocol. The THP-1 macrophages and KARPAS422, WSUDLCL2 were seeded into 6-well plates at a density of 2 × 105 cells per well and were transfected with 50 ng of shRNA plasmid DNA per well. Post- transfection, cells were incubated for 48 hours to allow for efficient silencing.

Simultaneously add 25 ng plasmids with and without IL-1B overexpression and CEBPB silencing, including: recombinant IL1B+sh-CEBPB; Recombinant IL1B+sh-negative control (NC); OE-NC+sh-CEPBB ; OE-NC+sh-NC co-transfected plasmids. After completion, co-culture the plasmids and transfection reagents with the tumor cells for 4 hours. After completion, remove the serum-free culture medium and transfection reagents, and add the necessary culture medium for cell proliferation for further cultivation.

The cell transfection groups for IL1B silencing were as follows: sh-negative control(NC) group (Forward oligo: 5^′-CCGGAAGGGTGAACTCACGTCAGAACTCGAGTTCTGACGTGAGTTCACCCTTTTTTTG-3^′, Reverse oligo: 5^′-AATTCAAAAAAAGGGTGAACTCACGTCAGAACTCGAGTTCTGACGTGAGTTCACCCTT-3^′. sh-IL1B group (Forward oligo: 5^′-CCGGGCGATTTGTCTTCAACAAGATCTCGAGATCTTGTTGAAGACAAATCGCTTTTTG-3^′, Reverse oligo: 5^′-AATTCAAAAAGCGATTTGTCTTCAACAAGATCTCGAGATCTTGTTGAAGACAAATCGC-3^′. RT-qPCR measured the silencing efficiency of the two sh-IL1B sequences. All expression plasmids were bought from Shanghai GenePharma Co., Ltd. (Shanghai, China), with a 50 ng/mL plasmid concentration.

The cell transfection groups for CEBPB silencing were as follows: sh-NC group, sh-CEBPB-#1 group (transfected with the sequence 5^′-CCGGCCCGTGGTGTTATTTAAAGAACTCGAGTTCTTTAAATAACACCACGGGTTTTTG-3^′ in macrophages), and sh-CEBPB-#2 group (transfected with the sequence 5^′-CCGGGCACAGCGACGAGTACAAGATCTCGAGATCTTGTACTCGTCGCTGTGCTTTTTG-3^′ in macrophages). RT-qPCR measured the silencing efficiency of the two sh-CEBPB sequences.

The overexpression groups included macrophages overexpressing IL1B/CEBPB, a vector control group, and a blank group. Western blot was employed to assess the efficacy of gene overexpression. All expression plasmids were acquired from Shanghai GenePharma Co., Ltd. (Shanghai, China) and used at a 50 ng/mL concentration.

The preparation of macrophages overexpressing IL1B/CEBPB involved the following steps: PCR amplification of IL1B/CEBPB mRNA, synthesis of the corresponding cDNA sequences, and insertion of the IL1B/CEBPB genes into an overexpression vector using DNA ligase to form a complete plasmid, including promoters, enhancers, and selection markers, to ensure high levels of gene expression. The overexpression vector plasmids (pCMV6-Entry, PS100001) and enzymes required for the experiment were purchased from Invitrogen (Thermo Fisher Scientific). The constructed IL1B/CEBPB overexpression plasmids were mixed with transfection reagents and then added to the macrophage culture. Transfected macrophages were established to overexpress IL1B and CEBPB, following the manufacturer’s instructions for the transfection reagent (Lipofectamine, Thermo Fisher Scientific).

Multicellular co-cultures were composed of IL1B-overexpressed/silenced THP-1 cells, and OCI-Ly1 cells at a 1:50 ratio, respectively. We chose these ratios based on immunohistochemical (IHC) quantification of diffuse large B-cell lymphoma patient tumors which reflected the tumor/TME composition. Cells were trypsinized and plated with THP-1 cells into 6-well plates at 1.5 $\times$ 10⁵ total cells/well.

Total RNA was extracted for the analysis of CEBPB gene expression using Trizol (16096020, Invitrogen, Waltham, MA, USA). Subsequently, 1 µg of the total RNA was reverse-transcribed into cDNA with a reverse transcription kit (RR047A, Takara, Japan). To quantify the mRNA expression levels of CEBPB and IL1B, cDNA samples were subjected to qRT-PCR amplification following the TaqMan gene expression assay protocol (Applied Biosystems, Foster City, CA, USA). Three independent experiments were conducted for each sample to statistically compare differences between groups. The PCR program was set as follows: 95 °C for 10 minutes, followed by 35 cycles of 95 °C for 15 seconds, 60 °C for 30 seconds, and 72 °C for 45 seconds. Each qRT-PCR reaction was performed in triplicate. The 2^{-Δ⁢Δ⁢Ct} method was used to calculate the fold change in gene expression between the experimental and control groups, where $\mathrm{\Delta }$$\mathrm{\Delta }$CT = $\mathrm{\Delta }$Ct (experimental group) – $\mathrm{\Delta }$Ct (control group), and $\mathrm{\Delta }$Ct = Ct (target gene) – Ct (reference gene). The cycle threshold (CT) signifies the point during the reaction when fluorescence intensity reaches a specific level, indicating exponential amplification. This experiment was conducted three times to ensure accuracy. The primer sequences are as follows: IL1B, Forward primer: 5^′-AGCTACGAATCTCCGACCAC-3^′, Reverse primer: 5^′-CGTTATCCCATGTGTCGAAGAA-3^′; CEBPB, Forward primer: 5^′-CTTCAGCCCGTACCTGGAG-3^′, Reverse primer: 5^′-GGAGAGGAAGTCGTGGTGC-3^′; GAPDH, Forward primer: 5^′-ACAACTTTGGTATCGTGGAAGG-3^′, Reverse primer: 5^′-GCCATCACGCCACAGTTTC-3^′.

Cells and tumor tissue were divided into experimental and control groups according to the experimental requirements and then harvested. Proteins were lysed with RIPA buffer from Thermo Fisher Scientific, and protease inhibitors from Roche were added. Protein concentrations were determined using the Pierce protein assay kit also from Thermo Fisher Scientific. Proteins were separated using SDS-PAGE and transferred to PVDF membranes (Millipore, Bedford, PA, USA). Membranes were then incubated with primary antibodies against IL1B (1:1000, Rabbit, Abcam, Cambridge, UK, ab216995), CEBPB (1:1000, Abcam, ab32358), GAPDH (1:3000, Rabbit, Abcam, ab181602), and $\beta$-actin (1:5000, Rabbit, Abcam, ab8227), which acts as a loading control, followed by incubation with Goat anti-Rabbit IgG (H+L) secondary antibody, HRP (1:10,000, Abcam, ab205718). The protein expression levels of CEBPB and IL1B were examined via chemiluminescence utilizing Bio-Rad technology with Image J ($\times$64, NIH, Bethesda, MD, USA). Statistical analysis was conducted to assess disparities in protein expression across different groups.

The dataset GSE87371, containing protein-coding gene expression data from DLBCL patients, was selected for WGCNA construction. The top 50% of genes with the largest absolute median difference were screened to establish a co-expression network and generate a gene expression matrix. Sample hierarchical clustering was performed to detect and exclude outlier samples to construct a standard scale-free network. Modules were detected through dynamic tree cutting, with a minimum size requirement of 50 for each module. Modules with very similar eigengene clustering were combined based on a threshold of dissimilarity less than 0.25, and the relationship between module eigengenes and CEBPB expression in DLBCL was calculated.

Cell proliferation was evaluated by employing the cell counting kit-8 (CCK-8) (Dojindo Molecular Technologies, Inc., Kawasaki, Japan). Cells in the logarithmic growth phase were diluted to a concentration of 5 $\times$ 10⁴ cells/mL in DMEM supplemented with 10% FBS. Subsequently, the cells were seeded into 96-well plates at a volume of 100 µL per well. After a 72-hour incubation period, the plates were processed by removing the supernatant and adding 10 µL of CCK-8 reagent to each well. The optical density (OD) at 450 nm was then determined using a microplate reader (Molecular Devices, Sunnyvale, CA, USA) with three replicates per group. This experimental procedure was repeated three times to ensure reliability. Subsequently, cell cycle analysis was conducted under various treatments to evaluate their impact on cell proliferation.

For cell cycle analysis, treated cells were fixed in 75% ethanol at 4 °C overnight, washed with PBS, and stained with 400 μL of propidium iodide (PI) staining solution (50 μg/mL, P4170, Sigma-Aldrich, USA) combined with 100 μL of RNase A (100 μg/mL, RNASEA-RO, Sigma-Aldrich, USA). This mixture was incubated at room temperature for 30 minutes in the dark. The samples were analyzed using a FACSCalibur flow cytometer (BD Biosciences, San Jose, CA, USA), and cell cycle phases were quantified using ModFit LT software (v5.0, Verity Software House, Topsham, ME, USA).

Various statistical methods were employed to process and interpret data in this study. Differential expression analysis was first conducted on data from the GEO database to compare the expression differences of the CEBPB gene between normal and DLBCL tissues. Survival analysis was conducted to investigate the correlation between high CEBPB expression and prognosis in patients with DLBCL. This analysis typically included the use of Kaplan–Meier survival curves and log-rank tests to assess survival disparities among different groups. The protein expression levels of CEBPB and IL1B were examined via chemiluminescence utilizing Bio-Rad technology with Image J. GraphPad Prism (7.0, GraphPad Software, San Diego, CA, USA) was used for statistical analyses. Results are presented as mean $\pm$ standard deviation (SD), with Student’s t-test or analysis of variance (ANOVA) used to compare groups. To evaluate the diagnostic accuracy of genes for DLBCL, receiver operating characteristic (ROC) curve analysis was performed with IBM SPSS Statistics software(SPSS Inc. Chicago, IL, USA). This analysis also involved calculating the area under the curve (AUC) to measure the effectiveness of the diagnostic test.

The high expression of CEBPB in DLBCL represents a notable observation. Differential expression analysis on the GSE56315 dataset revealed a significant upregulation of the CEBPB gene in DLBCL tissues (T = 16.64, p = 2.48 $\times$ 10^-23, Fig. 1A). This finding holds significant pathological implications in DLBCL, as it identifies a potential diagnostic marker. The assessment of the AUC value demonstrated the high accuracy of CEBPB expression levels in diagnosing DLBCL (AUC = 0.998, 95% (confidence interval) CI = [0.956, 1.000], p 0.0001, Fig. 1B), suggesting that CEBPB could serve as a novel clinical diagnostic marker to facilitate the early detection and diagnosis of DLBCL, thus improving the timeliness of treatment. Further comparisons between DLBCL cell lines and normal B cells have confirmed CEBPB’s high expression in DLBCL (Fig. 1C,D), providing direct evidence of its crucial function in the pathophysiology of the disease.

Fig. 1.

High expression of CCAAT/enhancer-binding protein beta (CEBPB) in diffuse large B-cell lymphoma (DLBCL) and its significance as a diagnostic key gene. (A) Expression levels of CEBPB in DLBCL cases versus normal tissues. $\bullet$ p 0.05. (B) The area under the curve (AUC) value represents the area under the receiver operating characteristic (ROC) curve, with the curve approaching the top left corner and the AUC nearing 1, indicating high discriminative power. (C) Quantitative realtime polymerase chain reaction (qRT-PCR) results show CEBPB expression levels in normal B lymphocytes (GM12878) compared to DLBCL cell lines (KARPAS422, WSUDLCL2) (n = 3). (D) Western blot results indicate higher mRNA and protein levels of CEBPB in DLBCL (KARPAS422, WSUDLCL2) compared to normal B lymphocytes (GM12878) (n = 3). Asterisks denote statistical significance: **p 0.01, ***p 0.001, ****p 0.0001.

The survival analysis presented strong evidence of a significant association between elevated CEBPB expression and unfavorable prognosis in patients with DLBCL. Within the GSE87371 dataset, it was observed that patients demonstrating elevated levels of CEBPB expression experienced notably reduced overall survival (OS) and progression-free survival (PFS) (OS: hazard ratio (HR) = 1.51, 95% confidence interval (CI) = 1.11–2.05, p 0.05; PFS: hazard ratio (HR) = 1.46, 95% confidence interval (CI) = 1.06–2.03, p 0.05, Fig. 2A,B). These findings underscore the importance of CEBPB as a potential prognostic marker in the clinical setting. Univariate and multivariate Cox analyses confirmed that CEBPB expression level is an independent factor influencing the survival of DLBCL patients (Fig. 2C,D), highlighting its potential value as a prognostic marker and providing crucial insights into disease progression and survival in DLBCL patients.

Fig. 2.

Survival analysis of CEBPB in DLBCL. (A,B) Kaplan–Meier survival curves with the x-axis representing time and the y-axis representing survival probability. The red and blue curves show the survival probability over time for high and low CEBPB expression groups, respectively. The hazard ratio (HR) value greater than 1 indicates a higher risk of events in one group than the other, while the HR value less than 1 indicates a lower risk. (C,D) Univariate and multivariate Cox analyses with variables including age, gender, etc., with CEBPB showing higher HR values, indicating an increased risk of DLBCL.

Our cell experiment results further confirmed the functional role of CEBPB in DLBCL. Through shRNA-mediated knockdown of CEBPB, we observed a significant inhibition of DLBCL cell proliferation via qRT-PCR and Western blot analyses (Fig. 3A,B), indicating CEBPB’s key role in promoting cell proliferation. The results of the CCK-8 assay demonstrated a significant inhibition in DLBCL cell proliferation following CEBPB knockdown (Fig. 3C,D). Flow cytometry analysis demonstrated that downregulation of CEBPB resulted in the accumulation of cells at the G0/G1 phase while decreasing the population of cells in the S/G2 phase (Fig. 3E). These results suggest that CEBPB supports the pathophysiological process of DLBCL by influencing the cell cycle, thereby promoting cell proliferation.

Fig. 3.

CEBPB promotes in vitro proliferation in DLBCL cells. (A) qRT-PCR analysis of CEBPB gene silencing efficiency in the blank, control, CEBPB sh1, and CEBPB sh2 groups. (B) Western blot analysis of CEBPB protein expression levels in the same groups. (C,D) Cell counting kit-8 (CCK-8) assay results show the absorbance values of the CEBPB knockdown group compared to the control group, reflecting the rate of tumor cell proliferation (n = 3). (E) Flow cytometry analysis of cell cycle status in each group (n = 3). Asterisks denote statistical significance: **p 0.01, ***p 0.001, ****p 0.0001, ns, statistically insignificant; NC, negative control.

WGCNA is a biological approach utilized for examining gene expression profiles, enabling the grouping or organization of genes exhibiting comparable expression patterns [41]. This method allows for the exploration of the correlation between gene modules and traits, such as clinical characteristics, particularly when genes with similar biological functions are clustered within the same module [42, 43]. Utilizing WGCNA, we systematically explored gene expression patterns, focusing on modules associated with CEBPB. Initially, two outlier samples were removed from the GSE87371 dataset, ensuring that 221 samples were included in the WGCNA analysis, successfully identifying gene modules related to CEBPB (Fig. 4A). A soft-thresholding power $\beta$ = 6 was chosen to construct a scale-free network (Fig. 4B), leading to the identification of modules. Upon modularization, a total of 11 gene co-expression modules were discovered (Fig. 4C), with particular attention given to the blue module due to its strong correlation with CEBPB expression and high R² value (R² = 0.88, p = 3 $\times$ 10^-72, Fig. 4D). Investigating the link between IL1B and CEBPB, inspired by previous research indicating that IL1B treatment can increase CEBPB expression [44], we observed a significant positive correlation between the gene significance (GS) of CEBPB in the blue module and module membership (MM), with a correlation coefficient of 0.93 and a highly significant p-value (p = 1 $\times$ 10^-200), further validating the close association between IL1B and CEBPB (Fig. 4E). This suggests that IL1B may act as one of the regulatory factors in the blue module’s gene expression, potentially cooperating with CEBPB to influence the development and progression of DLBCL.

Fig. 4.

Identification of CEBPB target genes. (A) Heatmap of GSE87371 samples and traits. (B) Scale-free fit index analysis results, with a scale-free R² = 0.850 at $\beta$ = 6. (C) Gene clustering dendrogram. (D) The blue module was identified as the critical module significantly related to CEBPB expression and R² value (R² = 0.88, p = 3 $\times$ 10^-72). (E) Scatter plot of gene significance (GS) vs. module membership (MM) for CEBPB in the blue module related to DLBCL patients.

Initial analysis of IL1B expression in DLBCL patients revealed a significant upregulation in the GSE56315 dataset (T = 9.49, p = 2.50 $\times$ 10^-15, Fig. 5A), suggesting a crucial role for IL1B in DLBCL. Subsequent survival analyses (GSE87371) underscored this by indicating that patients with high IL1B expression have a poor prognosis in terms of OS and PFS, with HR of 1.43 (95% CI = 1.06–1.95) and 1.41 (95% CI = 1.02–1.94), respectively, p 0.05 (Fig. 5B,C). These findings imply that elevated levels of IL1B expression may be closely associated with DLBCL progression and adverse outcomes. Given previous studies identifying macrophages as primary sources of IL1B [45], we obtained macrophages from the blood of both patients with DLBCL and healthy individuals. qPCR experiments confirmed the heightened expression of IL1B in DLBCL patients (Fig. 5D), further highlighting its significance in DLBCL. To explore the interrelation between IL1B and CEBPB, IL1B was overexpressed/silenced in macrophages (Fig. 5E), followed by co-culturing with tumor cells. The results indicated that IL1B overexpression significantly enhanced CEBPB expression in tumor cells while silencing IL1B reduced CEBPB levels (Fig. 5F). This outcome elucidates IL1B’s regulatory impact on CEBPB, suggesting IL1B acts as an upstream regulator of CEBPB in DLBCL, influencing its expression. In the final analysis, CCK-8 assays revealed that recombinant protein addition of IL1B notably enhanced the viability of DLBCL cells, while silencing IL1B resulted in a decrease in cell viability (Fig. 5G). This indicates that IL1B, through its regulatory effect on CEBPB, impacts the growth and proliferation of DLBCL cells, emphasizing IL1B’s potential as a therapeutic target, promising to have a significant impact on DLBCL treatment.

Fig. 5.

IL1B is a target gene of CEBPB. (A) Expression levels of IL1B in DLBCL cases versus normal tissues. $\bullet$$\bullet$ p 0.01. (B,C) Kaplan–Meier survival curves with the x-axis representing time and the y-axis representing survival probability show survival over time for high versus low IL1B expression groups. The Hazard Ratio (HR) value greater than 1 indicates a higher risk of events in one group over the other, while the HR value less than 1 indicates a lower risk. (D) qRT-PCR analysis of IL1B expression (n = 3). (E) mRNA and protein expression levels of IL1B in the IL1B overexpression, control, and IL1B silencing groups (n = 3). (F) mRNA and protein expression levels of CEBPB and tumor cell proliferation in the IL1B overexpression, control, and IL1B silencing groups (n = 3). (G) Results of CCK-8 assay in DLBCL (n = 3). Asterisks denote statistical significance: **p 0.01, ***p 0.001, ****p 0.0001

Assessments were conducted using the CCK-8 assay to evaluate DLBCL cell survival, focusing on KARPAS422 tumor cells. We found that knocking down CEBPB in tumor cells reversed cell proliferation induced by recombinant interleukin 1 beta (Fig. 6A). To explore the therapeutic potential of targeting IL1B in a DLBCL model, we introduced macrophages with silenced IL1B (sh-IL1B macrophages) into the bloodstream of DLBCL-bearing mice and monitored tumor growth. Notably, tumors in mice treated with sh-IL1B macrophages were significantly smaller compared to those in the control group, underscoring the potential of IL1B silencing in macrophages to inhibit tumor growth in DLBCL (Fig. 6B). This strategy showcases the distinct roles wherein the manipulation of CEBPB and IL1B occurs within tumor cells and macrophages, respectively, to exert therapeutic effects against DLBCL.

Fig. 6.

CEBPB promotes DLBCL cell proliferation in an IL1B-dependent manner. (A) CCK-8 assay of tumor cells with and without IL-1B overexpression and CEBPB silencing (A: recombinant IL1B+sh-CEBPB; B: recombinant IL1B+sh-NC; C: OE-NC+sh-CEBPB; D: OE-NC+sh-NC). (B) Comparison of tumor volumes between sh-NC and sh-IL1B groups (n = 5). (C) Flow cytometry analysis of cell cycle distribution in sh-NC versus sh-IL1B groups. *p 0.05, **p 0.01, ***p 0.001, ****p 0.0001, ns, no significant difference.

Moreover, flow cytometry analysis revealed an elevation in cells at the G0/G1 phase and a reduction in the S/G2 phase cells within the sh-IL1B group, suggesting a deceleration in the cell cycle progression (Fig. 6C). These results support the potential targeting of IL1B in DLBCL treatment, mainly through regulating CEBPB.

Western blot analysis of lymphatic B cells from IL1B-overexpressing mice, control mice, and blank group mice on day 40 revealed that CEBPB protein levels were higher in IL1B-overexpressing mice compared to normal B lymphocytes (Fig. 7A). To further verify IL1B’s potential role in DLBCL treatment, OE-IL1B macrophages were infused into the bloodstream of DLBCL mice, monitoring tumor growth. The tumors in the control macrophage group were smaller compared to those in the OE-IL1B group, suggesting that the overexpression of IL1B enhances the growth of DLBCL tumors (Fig. 7B). This further supports IL1B as a potential therapeutic strategy in DLBCL, mainly through regulating CEBPB.

Fig. 7.

IL1B overexpression elevates CEBPB protein levels and promotes DLBCL tumor growth. (A) Western blot bands and statistical analysis showing CEBPB protein expression in IL1B-overexpressing mice, interference control mice, and blank mice (n = 5). (B) Comparison of tumor diameters between IL1B overexpression and vector control groups (n = 5). *p 0.05, ***p 0.001.