IGF2BP3 promotes immune evasion and predicts poor prognosis in head and neck squamous cell carcinoma

Introduction

Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor originating from the mucosal tissues of the head and neck region, including the oral cavity, pharynx, larynx, and nasal cavity (1). HNSCC ranks as the sixth most common malignant tumor globally, with over 830,000 new cases and approximately 440,000 deaths worldwide in 2020. Its incidence is closely associated with smoking, heavy alcohol consumption, and high-risk human papillomavirus (HPV) infection (2,3). Although combined use of surgery, radiotherapy, and targeted therapies [such as programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors] has improved outcomes for some patients, approximately 60% of HNSCC patients present with locally advanced or metastatic disease at diagnosis. The 5-year survival rate remains below 65%, and significant challenges persist, including tumor heterogeneity and resistance to immunotherapy (4,5).

Insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) is a conserved RNA-binding protein that regulates target messenger RNA (mRNA) stability, translation, and subcellular localization by recognizing N⁶-methyladenosine (m⁶A) modifications (6,7). It functions as an oncoprotein in numerous solid tumors, where its overexpression promotes invasion, metastasis, and chemoresistance by activating key pathways like Wnt/β-catenin and PI3K/AKT (8,9). However, its specific expression pattern, prognostic value, and functional role in HNSCC pathogenesis are not fully elucidated.

The tumor microenvironment (TME) is a critical determinant of HNSCC progression. Immune cell infiltration plays a dual role: cytotoxic CD8⁺ T cells and natural killer (NK) cells can suppress tumor growth, whereas regulatory T cells (Tregs), M2 macrophages, and SPP1⁺ cancer-associated fibroblasts (CAFs) foster an immunosuppressive niche that promotes immune escape (5). Recent single-cell sequencing studies reveal that malignant cells form pro-tumorigenic interaction networks with specific stromal and immune cells, driving immunosuppression and metastasis (5). Notably, m⁶A modification can reshape the TME by regulating chemokines (e.g., CXCL5) and immune checkpoint molecules (e.g., PD-L1) (6). Deepening our understanding of its regulatory mechanisms is vital for elucidating tumor progression and identifying novel therapeutic targets (10). As an m⁶A reader, IGF2BP3 is poised to reshape the TME, but its impact on the immune landscape of HNSCC remains unclear.

Against this backdrop, this study aimed to integrate transcriptomic data from databases such as The Cancer Genome Atlas (TCGA) and The Human Protein Atlas (HPA) to systematically analyze the expression patterns of IGF2BP3 in HNSCC and its association with clinical staging and survival outcomes. We investigated its downstream signaling pathways through Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein interaction network mining. Utilizing the online gene/protein interaction search tool (STRING) platform, we constructed the protein interaction network of IGF2BP3. In vitro studies evaluated the correlation between the IGF2BPs gene family and immune cells using an immune infiltration algorithm. Cell experiments validated the function of IGF2BP3 in HNSCC cell lines, assessing its impact on cell proliferation and migration capabilities. Based on the above background, this study aimed to characterize the expression and function of IGF2BP3 in HNSCC and explore its potential as a prognostic biomarker. We present this article in accordance with the MDAR reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2742/rc).

Methods

Expression of IGF2BP3 in Pan-Cancer and HNSCC

We obtained the expression profile of IGF2BP3 along with its related clinical data from the TCGA database in HNSCC (11). The gene expression data in HTSeq-FPKM RNA sequencing format were converted to TPM and log2 transformed. We analyzed and visualized the expression data of IGF2BP3 in HNSCC and pan-cancer samples in R (v4.2.1). For unpaired samples, we used the Wilcoxon rank-sum test; for paired sample analysis, if the samples met the Shapiro-Wilk normality test (P>0.05), we employed a paired t-test; otherwise, we performed the Wilcoxon signed-rank test. Immunohistochemical staining images of IGF2BP3 in healthy control tissues and HNSCC were retrieved from the HPA database. Additionally, we used the pROC package in R to generate receiver operating characteristic (ROC) curves, which were visualized using the ggplot2 package. Logistic regression analysis was conducted to evaluate associations between IGF2BP3 expression and clinicopathological characteristics; the M stage was excluded from this model because only one patient had M1 disease (n=1). The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

HPA databases

The HPA database catalogs transcriptome and proteome data from diverse human samples, including tissue specimens, cell cultures, and pathological atlases. This online repository currently contains cell-specific localization data for 44 normal tissues and 20 common cancers, alongside immunohistochemical analysis data comparing tumor and normal human tissue samples.

Application of survival analysis methods

On the Xiantao platform’s clinical significance module (https://www.xiantao.love/), we analyzed prognostic parameters [such as overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI)] using data from TCGA patients. These analyses were conducted using Cox regression and Kaplan-Meier methods, where we determined the cutoff values for low and high IGF2BP3 expression groups based on the median. Combining the Wilcoxon signed-rank test with the logistic regression model, we explored the correlation between clinical pathological features and IGF2BP3 gene expression. A multivariate Cox regression model was used to analyze the impact of IGF2BP3 gene expression on survival probability and other clinical variables, with a significance threshold set at P<0.05. We combined the results of the Cox regression model with independent prognostic variables obtained from multivariate analysis, and calibration curves were used to convert the data into predicted survival probabilities for 1 year, 3 years, and 5 years. Finally, we compared the predicted values with actual incidence rates, where the 45-degree line represented the most accurate predictions.

Functional terms identification of the associated genes of the IGF2BP3

Comprehensive protein interaction analysis. We adapted our data processing workflow to the STRING network platform (https://string-db.org/), which integrates extensive protein interaction datasets (12). After importing IGF2BP3 expression data into the STRING platform, we extracted relevant information from the protein interaction network, setting the significance threshold at a confidence score greater than 0.6. We performed GO enrichment analysis of IGF2BP3 gene expression using the clusterProfiler package (version 3.6.3) in R, focusing on differentially expressed molecules, particularly those classified under cellular component (CC), molecular function (MF), and biological process (BP). Analysis parameters were set as follows: enrichment factor >1.5, minimum count >3, P value <0.01. For each study, gene set enrichment analysis (GSEA) was performed to rank the genome 1,000 times and identify pathways enriched in IGF2BP3 expression. In GSEA, statistical significance thresholds were set at a corrected P value <0.05 and a false discovery rate (FDR) <0.25. Enrichment results were defined by normalized enrichment scores (NESs) and corrected P values. The ClusterProfiler tool was used for both GSEA analysis and visualization.

Assessment of immune cell infiltration

Bindea et al. (13) published a research report to obtain marker genes for 24 different types of immune cells. To get a better grasp of the immune regulatory mechanisms in HNSCC, we considered previously identified immune-stimulating and immune-suppressing genes (14). The single-sample GSEA (ssGSEA) method utilized 24 different types of immune cells to study tumor infiltration. The Spearman correlation algorithm compared the levels of immune cell infiltration between IGF2BP3 high-expression and low-expression subgroups and assessed the correlation strength between IGF2BP3 expression and the infiltration concentrations of the 24 different types of immune cells. In the “Xiantao Tool” module, we analyzed the relationship between IGF2BP3 expression and immune infiltration, as well as the association between immune cell infiltration levels and the values obtained from different IGF2BP3 expression subgroups, based on the results of immune infiltration, Spearman correlation, and Wilcoxon signed-rank test.

Cell culture and transfection

The SCC-25 cell line is commonly used in HNSCC research. The human HNSCC cell line SCC-25 was purchased from Shenzhen Anyan Biotechnology Co., Ltd., and was confirmed to be free of mycoplasma contamination by quantitative polymerase chain reaction (PCR) testing (Shanghai Biowing Applied Biotechnology Co., Ltd., China; Report No. 20210330_21). Cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM) (Gibco, USA) supplemented with 10% fetal bovine serum (Gibco) and 1% penicillin-streptomycin (Gibco) in a cell incubator at 37 ℃ and 5% CO₂. To knock down the expression of the IGF2BP3 gene, we designed and synthesized small interfering RNA (siRNA) targeting IGF2BP3, provided by Jikai Gene Company (Wuhan, China). The siRNA sequences used for knockdown were as follows: si-NC: sense strand: TTCTCCGAACGTGTCACGT, antisense strand: ACGTGACACGTTCGGAGAA; si-IGF2BP3-1: sense strand: GTGAATGAACTTCAGAATT, antisense strand: AATTCTGAAGTTCATTCACCG; si-IGF2BP3-2: sense strand: AGTTGTAAATGTAACCTAT, antisense strand: ATAGGTTACATTTACAACTGC.

Reverse transcription-quantitative PCR (RT-qPCR) detection of mRNA levels in cells

We extracted and purified total RNA from SCC-25 cells in the si-NC group, si-IGF2BP3-1, and si-IGF2BP3-2 groups using Trizol reagent (Invitrogen, USA), and assessed its purity and integrity. cDNA was synthesized using a cDNA synthesis kit (Vazyme Bio, China), and real-time quantitative PCR analysis was performed using the SYBR Green qPCR SuperMix kit (Vazyme Bio). The reaction conditions were as follows: 95 ℃ for 5 minutes, 95 ℃ for 15 seconds, 60 ℃ for 34 seconds, for a total of 40 cycles. The primer sequences required for the experiment were as follows: IGF2BP3: F-ATCCGTATCCAAGCAGAAACC, R-GACTTACAAGCCGCAGAGG, with ACTB as the internal control: F-GCGTGACATTAAGGAGAAGC, R-CCACGTCACACTTCATGATGG, and relative expression levels were calculated using the 2^-ΔΔCT method.

Protein immunoblotting

We isolated total protein from SCC-25 cells in the si-NC group, si-IGF2BP3-1, and si-IGF2BP3-2 groups using a complete protein extraction kit provided by KeyGene Bio (China), and measured protein concentrations using a BCA kit (KeyGene Bio). Proteins were separated using 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and then transferred to a polyvinylidene difluoride (PVDF) membrane (Beyotime Bio, China). The PVDF membrane was incubated overnight at 4 ℃ with primary antibodies against IGF2BP3 (Abcam, 1:1,000) and β-actin (Abcam, 1:10,000). The next day, we washed the membrane with phosphate-buffered saline (PBS) and incubated it with secondary antibodies at room temperature for 1 hour. The detection process was carried out using ECL detection reagent (Beyotime Bio).

Cell Counting Kit-8 (CCK-8) assay

SCC-25 cells in the si-NC group, si-IGF2BP3-1, and si-IGF2BP3-2 groups were routinely cultured. We selected two groups of cells with good growth status and seeded them into 96-well plates at a density of 3×10³ cells per well. After culturing cells for 1–5 days, we added 10 µL of CCK-8 reagent (KeyGene Bio) to each well in the dark. After incubating at 37 ℃ for 1 hour, we measured the absorbance (OD) value at 450 nm using a microplate reader.

Cell scratch assay

Transfected SCC-25 cells in the si-NC group and si-IGF2BP3-2 group were cultured in 6-well plates at a density of 1×10⁶ with complete medium. The next day, when the cell density exceeded 90% under a microscope, we used a sterile 200 µL pipette tip to create scratches perpendicular to the plane of the 6-well plate, and washed three times with PBS to remove detached cells. The medium was then replaced with serum-free medium for continued culture, and images of the same scratch position were taken at 0 and 24 hours.

Transwell migration and invasion experiments

SCC-25 cells in the si-NC group and si-IGF2BP3-2 group were cultured until they grew well. We then seeded these cells into Transwell chambers (Corning, USA) at a density of 3×10⁴ cells per well for migration experiments. Serum-free medium was added to the upper chamber, and complete medium was added to the lower chamber. After 24 hours of culture, we removed the Transwell chambers. The cells were then fixed in 4% paraformaldehyde for 20 minutes and stained with 0.1% crystal violet. Subsequently, we took images and counted the cells under a microscope. In the invasion experiment, we pre-coated the Transwell chambers with Matrigel gel (Corning).

Statistical analysis

In the statistical analysis of this study, P<0.05 was considered statistically significant. The Wilcoxon signed-rank test was used for gene expression analysis, the t-test for comparing differences between two groups, analysis of variance (ANOVA) for comparing differences among multiple groups, and the log-rank test for survival analysis. Additionally, Pearson’s correlation coefficient or Spearman’s correlation coefficient was used for analyzing correlations between two variables. All algorithms were implemented in R software. For in vitro experiments, all experiments were performed with three biological replicates. Data were collected using ImageJ and statistically analyzed in GraphPad Prism 10.1.2 via t-tests, employing independent samples and one-way ANOVA. A P value <0.05 was considered statistically significant.

Results

The expression, immunohistochemistry, and clinical relevance of IGF2BP3 in HNSCC

We examined the expression patterns of all members of the IGF2BPs gene family across various cancers, and we observed a significant increase in IGF2BP3 levels in several types of malignant tumors (Figure 1A), including breast cancer (BRCA), cervical squamous carcinoma and endocervical adenocarcinoma (CESC), cholangiocarcinoma (CHOL), esophageal cancer (ESCA), hepatocellular carcinoma (LIHC), colon adenocarcinoma (COAD), lung squamous cell carcinoma (LUSC), head and neck squamous cell carcinoma (HNSC), glioblastoma multiforme (GBM), pancreatic adenocarcinoma (PAAD), gastric adenocarcinoma (STAD), rectal adenocarcinoma (READ), ovarian serous cystadenocarcinoma (OV), skin cutaneous melanoma (SKCM), endometrial carcinoma (UCEC), and uterine carcinosarcoma (UCS). Compared with healthy head and neck tissues, HNSCC samples had significantly higher mRNA levels of IGF2BP3 (P<0.001), a result confirmed by both unpaired and paired sample analyses (Figure 1B,1C). Subsequently, we assessed the diagnostic value of IGF2BP3 expression by constructing a ROC curve. This analysis compared the IGF2BP3 expression levels between normal tissue samples and HNSCC specimens. The results showed that the area under the curve (AUC) value for IGF2BP3 was 0.809 [95% confidence interval (CI): 0.753–0.866], indicating significant clinical diagnostic value (Figure 1D). The mRNA level of IGF2BP3 was dramatically higher in HNSCC tumor tissues than in normal tissues (Figure 1E). Similarly, using HPA data, IGF2BP3 protein was highly expressed in HNSCC tissue compared with normal tissue (Figure 1F). Logistic regression results revealed a significant correlation between IGF2BP3 expression and clinical staging (stage III & stage IV vs. stage I & stage II), with higher gene expression in stage III and IV patients (P=0.03) (Table 1). Higher IGF2BP3 expression correlated significantly with advanced clinical stage, and its correlation with characteristics such as N staging and histological grading in HNSCC patients requires further exploration.

Figure 1 The expression status of IGF2BP3 in malignant tumors. (A) The expression profile of IGF2BP3 in different human tumor tissues and homologous healthy tissues. (B) The difference in IGF2BP3 expression in unpaired HNSCC tissues and adjacent healthy tissues. (C) The difference in IGF2BP3 expression in paired HNSCC samples and their adjacent samples. (D) The ROC curve for IGF2BP3 expression discriminating HNSCC tumor tissues from normal tissues. (E) IGF2BP3 mRNA expression is upregulated in HNSCC tumor tissues relative to normal tissues. (F) In the HPA data, the expression of IGF2BP3 protein in HNSCC is higher than that in normal tissues (antibodies HPA076951, 10×, available from https://www.proteinatlas.org/ENSG00000136231-IGF2BP3/cancer/head+and+neck+cancer#HNSC_TCGA). ***, P<0.001. AUC, area under the curve; CI, confidence interval; FPR, false positive rate; HNSC/HNSCC, head and neck squamous cell carcinoma; HPA, The Human Protein Atlas; mRNA, messenger RNA; ROC, receiver operating characteristic; TCGA, The Cancer Genome Atlas; TPM, transcripts per million; TPR, true positive rate.

Prognostic value of IGF2BP3 for HNSCC patients

To determine the prognostic value of different expression levels of IGF2BP3, we conducted survival analysis and explored interactive correlations. Kaplan-Meier curves (Figure 2A-2C) indicated that higher levels of IGF2BP3 expression [hazard ratio (HR) =1.43, 95% CI: 1.07–1.93, P=0.02] in HNSCC patients were linked to lower OS, but there was no significant association with progression-free interval (PFI) and DSS. T stage (T3/T4 vs. T1/T2) was an independent adverse prognostic factor on multivariable analysis (HR =2.460, 95% CI: 1.079–5.607, P=0.03). N2/N3 stage vs. N0 stage was also an independent adverse prognostic factor (HR =2.712, 95% CI: 1.429–5.148, P=0.002); no significant difference was found for N1 stage vs. N0 stage (P=0.91). M1 (distant metastasis) vs. M0 (HR =19.168, 95% CI: 1.963–187.184, P=0.01) indicated that distant metastasis is a very strong independent adverse prognostic factor. Pathological staging, histological grading, gender, and age: P values were all >0.05, indicating no significant independent effect on prognosis (Figure 2D). We constructed a nomogram integrating IGF2BP3 expression with T, N, M, clinical stage, histological grade, and age to predict 1-, 3-, and 5-year OS (Figure 2E). Calibration curves indicated good agreement between predicted and observed survival probabilities (Figure 2F). The upregulation of IGF2BP3 is associated with poorer prognosis in HNSCC, suggesting that high IGF2BP3 expression plays an important role in the prognosis of HNSCC.

Figure 2 Prognostic analysis of IGF2BP3 expression. (A-C) Kaplan-Meier survival curves for OS (A), DSS (B), and PFI (C) stratified by IGF2BP3 expression in HNSCC patients (log-rank test, P<0.05). (D) Prognostic analysis of IGF2BP3 expression based on different clinical features (OS). (E) Nomogram of multivariate analysis based on the association between clinical features and IGF2BP3 expression. (F) The calibration curve shows the predictive accuracy of the model determined by multivariate Cox regression analysis. CI, confidence interval; DSS, disease-specific survival; HNSCC, head and neck squamous cell carcinoma; HR, hazard ratio; OS, overall survival; PFI, progression-free interval.

IGF2BP3 co-expressed gene interaction network, enrichment analysis and protein-protein interaction (PPI) network

We integrated differential gene screening, PPI network construction, expression pattern clustering, and functional enrichment analysis to systematically analyze the potential mechanism of IGF2BP3 in HNSCC. We screened for IGF2BP3-related differentially expressed genes (DEGs), and the volcano plot suggested that high IGF2BP3 expression is associated with upregulation of multiple oncogene-related transcripts (log₂FC >1, P<0.05) and is less likely associated with the inactivation of tumor suppressor pathways (log₂FC <−1, P<0.05) (Figure 3A).The heatmap showed that in the IGF2BP3 high expression group, metabolism-related genes (such as CYP26A1) were significantly upregulated, suggesting that metabolic reprogramming may be related to tumor progression (Figure 3B). Enrichment in cellular glucuronidation (P=0.01, count =5) suggests that IGF2BP3 mediates chemoresistance through drug metabolism pathways. Monocarboxylic acid binding (P=0.03, count =3) is associated with tumor energy metabolism reprogramming. Retinol metabolism (P=0.02, count =4) and pentose/glucuronidation interconversion (P=0.04, count =3) suggest effects on cell differentiation and oxidative stress balance. These findings suggest that IGF2BP3 may promote HNSCC progression by regulating metabolic pathways (drug metabolism, energy supply) and microenvironmental signaling (e.g., GABA receptors), and that glucuronidation-related pathways could contribute to chemoresistance (Figure 3C). The gene expression patterns were highly consistent with clinical grouping, supporting the potential of IGF2BP3 as a molecular typing biomarker. We downloaded the IGF2BP3-related co-expression gene dataset from the cBioPortal database and selected the top 10 genes with the strongest correlation based on Spearman values; we constructed the PPI network using the STRING database (Figure 3D) and selected the top 10 hub genes with the strongest correlation based on degree values and annotations: ELAVL1, HMGA2, HNRNPA2B1, IGF2, IGF2BP1, IGF2BP2, YTHDF2, YTHDC1, YTHDF3, YTHDF1 (Figure 3E).

Figure 3 Differential expression of IGF2BP3 gene, GO/KEGG enrichment analysis, and PPI. (A) A volcano plot based on the expression pattern of IGF2BP3 gene clearly shows the distribution of DEGs. (B) A heatmap generated from the expression level of IGF2BP3 gene visually displays 19 upregulated or downregulated genes. (C) GO enrichment analysis was performed on the differentially expressed genes selected based on IGF2BP3 gene expression. (D) Proteins interacting with IGF2BP3 in HNSCC. (E) Annotation of proteins that interact with IGF2BP3, along with their respective co-expression scores. BP, biological process; CC, cellular component; DEG, differentially expressed gene; GO, Gene Ontology; HNSCC, head and neck squamous cell carcinoma; KEGG, Kyoto Encyclopedia of Genes and Genomes; MF, molecular function; PPI, protein-protein interaction.

Relationship between IGF2BP3 gene expression and immune cell infiltration

High IGF2BP3 expression was positively correlated with Th2 and central memory T cells, but negatively correlated with cytotoxic cells and NK cells, indicating a shift towards an immunosuppressive TME (Figure 4A-4G). There were significant differences in the expression levels of the IGF2BP3 gene among different infiltrating immune cells, particularly in cytotoxic cells, Th17 cells, and immature dendritic cells (iDC) (Figure 4H-4J). The expression of IGF2BP3 was significantly positively correlated with the enrichment scores of various immune cells, indicating that IGF2BP3 may play an important role in the functional regulation of immune cells (Figure 4B-4G). These results provide important evidence for further studying the functions and mechanisms of IGF2BP3 in immune responses, especially in the activation and regulation of immune cells.

Figure 4 The relationship between IGF2BP3 gene expression and immune cell infiltration. (A) The relationship between IGF2BP3 gene expression and immune cell infiltration status. (B-G) The relationship between IGF2BP3 gene expression and tumor microenvironment characteristics. (H-J) The differences in the enrichment levels of certain immune cell subpopulations between the high expression group and low expression group of IGF2BP3 gene. TPM, transcripts per million; ns, P>0.05; *, P<0.05; **, P<0.01; ***, P<0.001.

Knockdown of IGF2BP3 inhibits proliferation, migration, and invasion of HNSCC cells

We subsequently conducted in vitro experiments on the IGF2BP3 gene to explore its potential role in the progression of HNSCC, selecting the SCC-25 cell line for functional experiments. To achieve knockdown of IGF2BP3 expression in the SCC-25 cell line, we verified the knockdown efficiency using RT-qPCR and Western blot experiments. Compared with the si-NC control group, the IGF2BP3 knockdown group (si-IGF2BP3-1, si-IGF2BP3-2) showed significantly reduced IGF2BP3 mRNA (Figure 5A) and protein expression levels (Figure 5B) (P<0.0001), confirming the efficient knockdown effect of the interference sequence on IGF2BP3. CCK-8 assays showed that IGF2BP3 knockdown significantly reduced SCC-25 cell proliferation compared with the si-NC group (P<0.0001) (Figure 5C). Combining WB, RT-qPCR, and CCK-8, we selected si-IGF2BP3-2 for subsequent experiments. Wound-healing and Transwell assays demonstrated that IGF2BP3 silencing decreased migratory and invasive cell counts by approximately 30% (P<0.01, Figure 5D,5E). In summary, knockdown of the IGF2BP3 gene effectively inhibits the proliferation, migration, and invasion abilities of HNSCC cells (SCC-25).

Figure 5 Knockdown of IGF2BP3 inhibits the proliferation, migration, and invasion ability of the SCC-25 cell line. (A,B) The expression of IGF2BP3 in the SCC-25 cell line was knocked down using siRNA, and the knockout efficiency was verified by RT-qPCR and Western blot. (C) CCK-8 assays revealed that the knockdown of IGF2BP3 expression considerably inhibited the proliferation behavior in SCC-25 cell line compared with si-NC. (D) Wound healing assay showed that compared with si-NC, knockdown of IGF2BP3 expression significantly inhibited the migration behavior of the SCC-25 cell line. (E) Transwell assay showed that compared with si-NC, knockdown of IGF2BP3 expression significantly inhibited the migration and invasion behavior of the SCC-25 cell line (crystal violet staining, scale bar =200 μm). **, P<0.01; ***, P<0.001; ****, P<0.0001. CCK-8, Cell Counting Kit-8; NC, negative control; RT-qPCR, reverse transcription-quantitative polymerase chain reaction; siRNA, small interfering RNA.

Discussion

In this study, we provide an integrative characterization of IGF2BP3 in HNSCC. We found that IGF2BP3 is significantly overexpressed in HNSCC tissues and is associated with adverse clinicopathological features and poorer OS (15). Loss-of-function experiments in SCC-25 cells showed that IGF2BP3 knockdown reduced proliferation, migration, and invasion, supporting a contributory role of IGF2BP3 in maintaining malignant phenotypes in this cellular context. In addition, immune deconvolution analyses revealed that high IGF2BP3 expression is associated with an immunosuppressive immune landscape (e.g., higher Th2 signatures and lower cytotoxic T/NK signatures). Together, these findings suggest that IGF2BP3 may serve as a potential biomarker and warrants further mechanistic and in vivo validation.

Tarsitano et al. found that IGF2BP3 was strongly associated with perineural invasion in patients with HNSCC during their analysis of preoperative biopsy specimens. This association aids in diagnosing HNSCC patients and enables accurate preoperative stratification, thereby facilitating precise treatment planning (16). Our data confirm the pan-cancer oncogenic role of IGF2BP3, with its pronounced overexpression in HNSCC being a key finding. The significant diagnostic power and the association with advanced clinical stage underscore its clinical relevance. This aligns with its established role in other malignancies, where it post-transcriptionally stabilizes mRNAs of oncogenes like MYC and MMP9, thereby enhancing tumor aggressiveness (17,18). The prognostic analysis further solidifies this, revealing that elevated IGF2BP3 expression is an independent predictor of poor OS, consistent with studies in gastric and colorectal cancers (19,20). Liu et al. found that IGF2BP3 expression is also associated with the clinical staging of urothelial carcinoma and ovarian clear cell carcinoma (21). Our nomogram, integrating IGF2BP3 with classic clinicopathological features, offers a refined tool for personalized prognosis prediction, addressing the need for better risk stratification in HNSCC.

Beyond its prognostic value, our enrichment analyses shed light on the potential mechanistic underpinnings of IGF2BP3 in HNSCC. IGF2BP3 exerts effects on glioblastoma via IGF-2, leading to activation of the MAPK signaling pathway and ultimately promoting glioblastoma progression (22). CircIGHG can target miR-142-5p to enhance IGF2BP3 activity and promote HNSCC progression through epithelial-mesenchymal transition (23). Zhou et al. elucidated through a systematic review the molecular mechanism by which HNRNPA2B1 regulates the stability of tumor-associated mRNAs by recognizing m⁶A-modified sites, thereby driving cancer stemness and immune evasion (24). This suggests a previously underappreciated role for IGF2BP3 in regulating drug metabolism and detoxification pathways, which could contribute to chemoresistance—a major clinical hurdle in HNSCC treatment. Furthermore, the identification of a tightly interconnected PPI network with hub genes like ELAVL1, HNRNPA2B1, and other m⁶A readers (YTHDF1-3) implies that IGF2BP3 operates within a complex RNA-regulatory network. This network likely cooperates to fine-tune the epitranscriptome, amplifying oncogenic signaling outputs, a concept gaining traction in cancer biology (25).

A pivotal and novel aspect of our study is the elucidation of the relationship between IGF2BP3 and the immune TME. Wan et al. demonstrated that suppressing IGF2BP3 expression in breast cancer leads to T cell activation, thereby improving immune regulation within tumors (26). Th2 cells exhibited a positive correlation with IGF2BP3 expression, whereas CD4⁺ effector memory T cells (Tem) showed a negative correlation with IGF2BP3 expression in lung adenocarcinoma (27). Hanniford et al. found that IGF2BP3 correlates with PD-L1 in melanoma (28). Consistent with these findings, we observed that high IGF2BP3 expression in HNSCC is associated with a distinctly suppressive immune landscape, characterized by a strong positive correlation with Th2 cells and a negative correlation with cytotoxic T cells and NK cells. While this association suggests a potential pathway for immune evasion, we acknowledge that this is based on bioinformatic inference. This pattern provides a plausible explanation for the poor survival outcomes associated with high IGF2BP3 expression, suggesting that its oncogenic function is at least partly mediated by the establishment of an immunologically “cold” TME. Taken together, our findings suggest a correlation between IGF2BP3 and a pro-tumorigenic immune contexture in HNSCC, highlighting a potential mechanism of immune evasion and a rationale for targeting IGF2BP3 in combination with immunotherapy.

The IGF2BPs gene family displayed a significant association with a variety of tumor-infiltrating immune cells and immune genes in HNSCC (29). Tang et al. demonstrated in vitro that IGF2BP2 silencing suppressed the migration, proliferation, and invasion of SCC-4 cells (30). Functional validation in SCC-25 cells demonstrates that knockdown of IGF2BP3 significantly impairs proliferation, migration, and invasion, confirming its critical role in maintaining the malignant phenotype of HNSCC. This is consistent with its function in stabilizing pro-proliferative and pro-invasive mRNA targets, as reported in other cancers. Our in vitro evidence, combined with the bioinformatic analyses, suggests that IGF2BP3 may be a potential therapeutic target; however, whether IGF2BP3 modulates antitumor immunity requires mechanistic studies and in vivo validation.

There are several limitations in this study. First, our transcriptomic analyses rely primarily on TCGA data. While we acknowledge that pan-cancer overexpression observed in silico could potentially be a “bystander effect” of malignancy, our in vitro knockdown experiments support the hypothesis that IGF2BP3 plays a functional role in HNSCC progression rather than being solely correlative. Nevertheless, external validation in independent, multi-center cohorts is needed to confirm the robustness of IGF2BP3 as a prognostic biomarker. Second, although we observed correlations between IGF2BP3 and immune cell infiltration, we did not experimentally dissect the underlying mechanisms, such as direct regulation of chemokines or immune checkpoint molecules. Techniques such as RIP-seq or CLIP-seq will be necessary to identify IGF2BP3-bound transcripts that shape the immune microenvironment in HNSCC. Third, the functional assays were performed in a single HNSCC cell line using loss-of-function approaches. We acknowledge that gain-of-function (overexpression) experiments would provide further evidence of oncogenic sufficiency. Furthermore, using co-culture systems or in vivo studies in xenograft or immunocompetent models is required to evaluate the therapeutic potential of targeting IGF2BP3 and to validate its role in immune cell trafficking within a physiological context.

Conclusions

Our integrative analysis suggests IGF2BP3 as a multi-faceted regulator of HNSCC pathogenesis, linking its oncogenic functions to a distinct immunosuppressive microenvironment. It serves as a robust diagnostic and prognostic biomarker. Future efforts should focus on developing targeted strategies against IGF2BP3 and exploring its potential as a novel immunotherapeutic avenue to improve outcomes for HNSCC patients.

Acknowledgments

We extend our sincere gratitude to all individuals who made invaluable contributions to this work.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2742/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2742/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2742/prf

Funding: This work was supported by the Natural Science Foundation of Shenzhen (Nos. JCYJ20220530142413031 and JCYJ20250604180831041), and the Shenzhen Key Laboratory for Cancer Metastasis and Personalized Therapy (No. ZDSYS20210623091811035).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1-2742/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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