EREG promotes colorectal cancer progression and immune suppressive microenvironment formation through IL-17A/NF-κB pathway

EREG promotes colorectal cancer progression and immune suppressive microenvironment formation through IL-17A/NF-κB pathway | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article EREG promotes colorectal cancer progression and immune suppressive microenvironment formation through IL-17A/NF-κB pathway Xiangpeng Gao, Wenqing Xia, Xiaoyang Duan, Yuanyuan Zhang, Xin Li, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7869610/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Colorectal cancer (CRC), as a common malignancy, predominantly exhibits an immune evasion phenotype, making it largely unresponsive to immune checkpoint inhibitors (ICIs). Epiregulin (EREG), a member of the epidermal growth factor family, is frequently overexpressed in CRC, which has been implicated in tumor progression and therapy resistance in various cancers, but its specific role and underlying mechanisms in CRC cell and tumor microenvironment (TME) regulation remain to be elucidated. Methods EREG expression levels in CRC tissues were analyzed using The Cancer Genome Atlas (TCGA) database and immunohistochemistry (IHC). Lentivirus-mediated RNA interference was employed to establish EREG knockdown CRC cell lines. The effects of EREG silencing on cell proliferation, invasion, colony formation, migration, and apoptosis were evaluated by CCK-8 assay, transwell invasion assay, colony formation assay, wound healing assay, and flow cytometry, respectively. Furthermore, mRNA sequencing (mRNA-seq), enzyme-linked immunosorbent assay (ELISA), and Western blot (WB) analyses were conducted to explore intracellular signaling pathway changes and TME modulation following EREG knockdown. Results EREG was significantly overexpressed in CRC tissues compared to adjacent normal tissues and correlated closely with intratumoral CD8 + T cell infiltration. EREG knockdown significantly inhibited CRC cell proliferation, invasion, clone and migration, while promoting apoptosis. Differentially expressed genes were enriched in the IL-17A/NF-κB signaling pathway. EREG depletion suppressed IL-17A and NF-κB expression, reversible by exogenous IL-17A. Additionally, EREG knockdown increased secretion of chemokines (CCL5, CXCL1, CXCL2, CXCL3), enhancing CD8 + T cell infiltration and remodeling the TME towards an immune-activated state. Conclusion EREG promotes CRC progression by modulating the IL-17A/NF-κB pathway and maintaining an immunosuppressive TME. Targeting EREG may improve immunotherapy outcomes by transforming cold tumors into hot tumors, providing a promising strategy for CRC treatment. colorectal cancer (CRC) Epiregulin (EREG) tumor microenvironment (TME) Transcriptomics IL17A/NF-κB Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction CRC is the third most commonly diagnosed and the second most lethal malignancy worldwide, with approximately 1.9 million new cases and 900,000 deaths reported in 2020[ 1 ]. More than 20% of cases are diagnosed with distant metastases at initial presentation, and the incidence is increasingly observed in younger individuals[ 2 ]. CRC is a highly heterogeneous disease, traditionally classified into two subtypes based on tumor location: proximal colon and distal colon types[ 3 , 4 ]. With the advancement of precision medicine and molecular diagnostics, the CRC Subtyping Consortium established a novel classification system in 2015, known as the Consensus Molecular Subtypes (CMSs), comprising four distinct molecular subtypes. This system aims to standardize CRC classification and guide subtype-specific therapeutic strategies[ 5 ]. At present, therapeutic approaches for CRC include endoscopic and surgical resection, radiotherapy, chemotherapy, immunotherapy, targeted therapy, and local ablative treatments[ 6 , 7 ]. While these interventions have improved outcomes for certain patient subsets, the overall prognosis remains poor. In recent years, immunotherapy, represented by PD-1 inhibitors, has emerged as one of the established standard-of-care therapies for multiple malignancies. However, due to the complexity and heterogeneity of the TME, the overall response rate to immunotherapy remains relatively low, at only 20–30%[ 8 ]. In CRC, immunotherapy shows clinical benefit primarily in a small subset of patients with high microsatellite instability-high (MSI-H), while the majority of microsatellite stable (MSS) tumors exhibit poor responsiveness, highlighting the need for more effective strategies to expand the responsive population. TME, a complex and dynamic ecosystem comprising immune cells, stromal cells, fibroblasts, endothelial cells, extracellular matrix components, and diverse cytokines and chemokines, plays a pivotal role in the initiation, progression, and therapeutic response of CRC[ 9 ]. Increasing evidence suggests that the TME not only supports tumor growth and metastasis but also critically shapes the immune landscape of CRC. In particular, the immunosuppressive characteristics of the TME such as regulatory T cell (Treg) infiltration, myeloid-derived suppressor cell (MDSC) expansion, and upregulation of immune checkpoint molecules contribute to immune evasion and resistance to immunotherapy[ 10 ]. Furthermore, the heterogeneity of the TME across different CRC subtypes, especially between MSI-H and MSS tumors, significantly influences the clinical efficacy of immune checkpoint blockade. MSI-H tumors are typically characterized by high tumor mutational burden (TMB), increased neoantigen load, and dense CD8 + T cell infiltration, rendering them more responsive to PD-1/PD-L1 inhibitors[ 11 ]. In contrast, the majority of MSS tumors exhibit an immunologically cold phenotype, with poor T cell infiltration and a suppressive TME, resulting in limited benefit from current immunotherapies[ 12 ]. To overcome the limited efficacy of ICIs in MSS CRC, considerable efforts have been devoted to reprogramming the TME and converting immunologically cold tumors into hot ones. Various strategies have been investigated, including the combination of PD-1/PD-L1 inhibitors with chemotherapeutic agents, radiotherapy, anti-angiogenic therapies (e.g., bevacizumab), and targeted therapies against EGFR or MEK[ 13 ]. These combinatorial approaches aim to enhance tumor immunogenicity, promote T cell infiltration, and modulate immunosuppressive elements within the TME. These advances underscore the importance of understanding and manipulating the TME to overcome resistance and expand the clinical benefit of immunotherapy in CRC. Despite these advances, the underlying mechanisms by which key immunomn colodulatory molecules regulate the immune landscape of CRC remain incompletely understood. EREG is a member of the epidermal growth factor (EGF) family that acts as a ligand for the epidermal growth factor receptor (EGFR) and ErbB4[ 14 , 15 ]. Through activation of EGFR downstream signaling cascades, including the RAS/RAF/MEK/ERK and PI3K/AKT pathways, EREG plays a pivotal role in regulating cell proliferation, survival, migration, and epithelial-mesenchymal transition (EMT)[ 16 ]. EREG has been reported to be upregulated, and the EGFR signaling pathway has likewise been demonstrated to be hyperactivated in various malignancies, including non-small cell lung cancer, breast cancer and bladder cancer[ 17 – 19 ]. Recent studies have implicated EREG in modulating tumor progression and immune signaling, with its frequent overexpression in CRC being associated with poor prognosis, enhanced tumor cell proliferation, and therapy resistance[ 20 ]. However, its specific role in CRC cell viability and shaping the immunosuppressive TME and mediating immune evasion remains poorly defined. Emerging data also suggest that certain chemokines, such as CXCL3 and CCL5, may be upregulated in specific CRC subtypes and are closely associated with immune cell recruitment and inflammatory signaling[ 21 ]. Whether these chemokines act downstream of EREG and contribute to the formation of a cold tumor phenotype is a question of significant interest. Moreover, the IL-17A/NF-κB pathway has been widely recognized for its contribution to chronic inflammation and tumorigenesis[ 22 ]. However, the relationship between EREG deficiency and alterations in the IL-17A/NF-κB signaling axis, as well as its impact on tumor immunogenicity, has yet to be elucidated. This study aims to elucidate the role of EREG in CRC cell viability and modulating the CRC TME, with a particular focus on its influence on immune-related signaling pathways and chemokine expression. By dissecting the molecular link between EREG and the IL-17A/NF-κB axis, we seek to clarify how EREG contributes to immune evasion in CRC. Understanding these mechanisms may provide new insights into immunotherapeutic resistance and uncover potential targets to enhance antitumor immunity, especially in MSS CRC. 2. Materials and Methods Bioinformatics analysis Differentially expressed genes (DEGs) were identified from TCGA database using R software, with thresholds set at |log₂ fold change| >1 and P < 0.05. Functional annotation of DEGs was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to explore biological processes and pathways involved. Immune cell infiltration was assessed using the TIMER2.0 web server to evaluate the tumor immune microenvironment. IHC Paraffin-embedded tissue sections were deparaffinized and rehydrated through graded alcohols. Antigen retrieval was performed using citrate buffer, followed by treatment with 3% hydrogen peroxide (H₂O₂) at room temperature for 15 min to block endogenous peroxidase activity. Non-specific binding sites were blocked by incubation with low-concentration serum for 15 min. The sections were then incubated overnight at 4°C with diluted primary antibodies (1:600), followed by incubation with secondary antibodies at room temperature for 20 min. Subsequently, the sections were incubated with streptavidin–horseradish peroxidase (SA-HRP) solution for 20 min. Visualization was achieved using 3,3’-diaminobenzidine (DAB) substrate (ZSGB-BIO, China), and counterstaining was performed with hematoxylin. The sections were mounted with neutral balsam and images were captured using a light microscope (Olympus, Japan) at 200×magnification. Quantitative analysis was performed using Image-Pro Plus software. Cell Culture and Lentiviral Infection The mouse CRC cell line CT26 (RRID: CVCL_7254) and MC38 (RRID: CVCL_B288) were purchased from Cyagen Biosciences (Shanghai) Co., Ltd. (Shanghai, China). All cell lines were authenticated by short tandem repeat (STR) profiling and confirmed to be free of mycoplasma contamination before use. Cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM; Hyclone, USA) supplemented with 10% fetal bovine serum (FBS; Gibco, USA) at 37°C in a humidified atmosphere containing 5% CO 2 . The lentiviral vector encoding shRNA targeting EREG was synthesized and packaged by GeneChem Co., Ltd., Shanghai. When the cells reached approximately 70% confluence, 5×10⁵ cells/well were seeded into six-well plates and infected with lentiviral vectors carrying either EREG shRNA sequences or negative control (NC) shRNA sequences at a multiplicity of infection (MOI) of 20. After 24 h of infection, the medium was replaced, and transfection efficiency was evaluated using an inverted fluorescence microscope. Subsequently, the cells were selected with puromycin (2 µg/mL) for 3 d. Real-time quantitative PCR (RT-qPCR) CT26 and MC38 cells transfected with either EREG shRNA or negative control (NC) shRNA were collected, and total RNA was extracted using a Total RNA Kit (Omega, USA) according to the manufacturer instructions. Complementary DNA (cDNA) was synthesized using the PrimeScript™ RT reagent kit with gDNA Eraser (Takara, Japan). Quantitative real-time PCR was performed using SYBR Premix Ex Taq™ II (Takara, Japan). The primer sequences for EREG were 5’-AAGTGGGCTACACTGGTCT-3’(forward) and 5’-TGTCAACGCAACGTATTCT-3’(reverse)and for Actb were 5’-GCACCACACCTTCTACAATG-3’(forward) and 5’-GTGAGGGAGAGCATAGCC-3’(reverse). The qPCR program consisted of 40 cycles of 95°C for 15 s, 55°C for 30 s, and 72°C for 30 s. The relative mRNA expression levels between groups were calculated using the 2-ΔΔCt method. Western blot Cells were lysed using RIPA buffer supplemented with 1 mM phenylmethylsulfonyl fluoride (PMSF) (both from Beyotime, China). Total protein concentrations were determined using a bicinchoninic acid (BCA) protein assay kit (Beyotime, China), with bovine serum albumin as the standard. Protein samples were mixed with loading buffer and boiled in a 100°C water bath for 5 min. Equal amounts of protein were separated on 12% SDS-polyacrylamide gels (Beyotime, China) and transferred onto polyvinylidene difluoride (PVDF) membranes (Bio-Rad, USA). The membranes were blocked with 5% non-fat dry milk to prevent nonspecific binding, and α-tubulin was used as the loading control. Subsequently, the membranes were incubated with primary antibodies (Santa Cruz Biotechnology, USA), followed by horseradish peroxidase (HRP)-conjugated secondary antibodies (TransGen Biotech, China). Protein bands were visualized using an enhanced chemiluminescence (ECL) detection kit (PLYGEN, China) and detected on X-ray film. Band intensities were quantified using ImageJ software. CCK-8 assay and transwell invasion assay For the cell proliferation assay, 100 µL of cell suspension (5000 cells/well) was seeded into 96-well plates, with three replicate wells per group at each time point. After the cells adhered, the original medium was replaced with complete medium containing the indicated treatments. At 0 h, 24 h, 48 h, and 72 h, 10 µL of CCK-8 solution (Dojindo, Japan) was added to each well, followed by incubation at 37°C for 2 h. The absorbance at 450 nm was measured using a microplate reader. For the invasion assay, Matrigel (BD Biosciences, USA) was diluted 1:8 with serum-free DMEM and applied to the upper chamber before cell seeding. The chambers were incubated at 37°C in a humidified atmosphere containing 5% CO 2 for 24 h. After incubation, the medium was discarded, and non-migrated or non-invaded cells on the inner surface of the membrane were gently removed with a cotton swab. Cells on the underside of the membrane were fixed and stained with 0.1% crystal violet for 10 min, then rinsed twice with double-distilled water (ddH 2 O). Migrated or invaded cells were counted in five randomly selected fields under a light microscope (Olympus, Japan) at 200×magnification. The average cell count was used to evaluate migratory and invasive capacities. Colony formation assay and wound healing assay For the colony formation assay, cells in the logarithmic growth phase were trypsinized, centrifuged, and seeded at a density of 500 cells/well in six-well plates. The plates were gently rotated to ensure even cell distribution and cultured for 13 d. Subsequently, the cells were washed with PBS, fixed with 4% paraformaldehyde for 20 min, and stained with 0.1% crystal violet for 20 min. Excess stain was washed away with running water, and the plates were air-dried. Colonies were photographed and counted manually. Cells from each group were collected and resuspended in serum-free DMEM at a concentration of approximately 1.5×10⁵ cells/mL. For the migration assay, 200 µL of the cell suspension was added to the upper chamber of a Transwell insert (Corning Costar, USA), and 800 µL of DMEM supplemented with 10% fetal bovine serum (FBS) was added to the lower chamber as a chemoattractant. Flow Cytometry Analysis Cells were collected and washed twice with ice-cold PBS, followed by fixation in 70% ice-cold ethanol at 4°C overnight. After centrifugation, the cells were resuspended in 400 µL of ice-cold PBS containing 20 µL of RNase A solution (Vazyme Biotech, China) and incubated in a 37°C water bath for 30 min. Subsequently, 400 µL of propidium iodide (PI) staining solution (Vazyme Biotech, China) was added. After incubation at 4°C for 30 min in the dark, the samples were analyzed using a flow cytometer (Roche, Switzerland). Transcriptomics Total RNA was extracted from EREG-knockdown and control cells using TRIzol reagent according to the manufacturer’s protocol. RNA sequencing (RNA-seq) was performed using the Illumina NovaSeq 6000 platform to generate 150 bp paired-end reads. The reads were aligned to the reference genome using HISAT2, and gene expression levels were quantified as FPKM (Fragments Per Kilobase of transcript per Million mapped reads). Read counts for each gene were obtained using HTSeq-count. Differentially expressed genes (DEGs) were identified using DESeq2, with genes meeting the criteria of q-value 1.0​considered statistically significant. Hierarchical clustering analysis of DEGs was performed using R (v3.2.0) to visualize gene expression patterns across different groups and samples.Functional enrichment analysis was conducted using​KEGG Pathway​and WikiPathways​databases based on the hypergeometric distribution algorithm to identify significantly enriched biological pathways and functional categories. The datasets generated and/or analysed during the current study have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under the accession number PRJNA1356697. The data can be accessed at: https://www.ncbi.nlm.nih.gov/sra/PRJNA1356697 . ELISA Reagents and microplate must reach room temperature; standards and samples are assayed in duplicate. Dispense 50 µL of each standard into the designated wells, and combine 10 µL test sample with 40 µL Sample Diluent in sample wells; leave blanks empty. Add 100 µL HRP-conjugate to every well, seal with an adhesive strip, and incubate 60 min at 37°C. Aspirate contents, then wash five times with 400 µL Wash Solution, inverting and blotting on paper towels after the final rinse. Pipette 50 µL chromogen A followed by 50 µL chromogen B into each well, mix gently, protect from light, and incubate 15 min at 37°C. Stop the reaction with 50 µL Stop Solution; color should shift to uniform yellow. Measure absorbance at 450 nm within 15 min. (Jiangsu Meimian Industrial Co., Ltd.) Statistical Analysis Statistical analyses were performed using SPSS software version 16.0 (SPSS Inc., USA). Data are presented as the mean ± standard deviation (SD). Comparisons between groups were conducted using Student’s t -test. P < 0.05 was considered statistically significant. 3. Results EREG is highly expressed in CRC and correlates with immune cell infiltration Based on analysis of the TCGA database, EREG is highly expressed in 28 tumor types, including CRC (Figures 1A 1B and 1D), and its expression level is negatively correlated with CD8 + T lymphocyte infiltration (Figure 1C). IHC analysis of tumor and adjacent normal tissues from eight colorectal cancer patients further confirmed the elevated expression of EREG in CRC tissues (Figure 1E). These findings indicate that EREG is highly expressed in CRC and is closely associated with the TME. EREG shRNA significantly downregulated EREG expression in CT26 and MC38 cells. EREG expression was markedly suppressed in CT26 and MC38 cells following shRNA-mediated knockdown. Successful lentiviral transduction was confirmed by the presence of green fluorescence in both control (shNC) and experimental (shEREG) groups at 72 h post-infection, as observed under fluorescence microscopy (Figure 2A). Subsequent RT-qPCR and Western blot analyses demonstrated a significant reduction in EREG mRNA and protein levels across CT26-shEREG-1, CT26-shEREG-2, CT26-shEREG-3, MC38-shEREG-1, MC38-shEREG-2 and MC38-shEREG-3 cell lines relative to the shNC controls (Figures 2B and 2C), thereby validating the effective establishment of EREG knockdown CRC cell models. Knockdown of EREG suppresses proliferation, invasion, clone, and migration in CRC cells. Cell proliferation, invasion, clone, and migration abilities were evaluated using CCK-8 assay, Transwell assay, colony formation assay, and wound healing assay respectively.Proliferative capacity was significantly inhibited in CT26 and MC38 cells transfected with EREG shRNA compared to the control group (Figure 3A). Invasive ability of both cell lines was markedly suppressed following EREG knockdown (Figure 3B). Similarly, clonogenic capacity was significantly reduced in EREG-silenced cells (Figure 3C). Furthermore, migratory ability was also notably impaired in the EREG shRNA group (Figure 3D). These results indicate that the lentiviral vector carrying EREG shRNA effectively inhibits proliferation, invasion, clone, and migration abilities in CT26 and MC38 cells. EREG knockdown promotes apoptosis in CRC cells. Flow cytometry analysis revealed a significant increase in apoptotic cells in the EREG knockdown groups compared to controls, indicating that EREG silencing enhances apoptosis in CT26 and MC38 cell lines (Figure 4). Differentially expressed genes following EREG knockdown were primarily enriched in the IL-17A/NF-κB signaling pathway. Transcriptomic analysis revealed that 538 genes were upregulated and 534 genes were downregulated in the EREG-knockdown groupcompared to the control group (screening criteria:q-value 1.0). Among the upregulated genes, CD276, Lag3, and IL-17c were identified, all of which are associated with tumor immune phenotype formation. Conversely, downregulated genes such as Traf1 andMmp9 were linked to inflammatory responses (Figure 5A 5B). Functional enrichment analysis of these differentially expressed genes (DEGs) was performed. KEGG pathway analysisof the top 20 enriched pathways highlighted the IL-17 signaling pathway andchemokine signaling pathway, which are primarily involved in immune microenvironment regulation. Similarly, WikiPathways analysis of the top 20 pathways also identified IL-17 signaling and chemokine signalingas significantly enriched (Figure 5C 5D). To further validate the functional relevance of EREG knockdown, we integrated data from TCGA database. TCGA analysis demonstrated that the IL-17A/NF-κB signaling pathway was the most prominently shared enriched pathway between our RNA-seq data and TCGA datasets (Figure 5E). EREG knockdown inhibits the activity of the IL-17A/NF-κB signaling pathway, which is partially restored upon IL-17A supplementation. Western blot analysis demonstrated that in CT26 (Figure 6 A) and MC38 (Figure 6 B) cells, EREG knockdown led to decreased expression of IL-17A upper, IL-17A lower, IL-17RA, Act1, NF-κB1, phosphorylated NF-κB1 (p-NF-κB1), and MMP9. However, following treatment with IL-17A, the expression levels of Act1, NF-κB1, p-NF-κB1, MMP9, IL-17A upper, and IL-17A lower were partially restored. These results indicate that EREG knockdown suppresses the IL-17A/NF-κB signaling pathway activity, and that the biological functions of EREG are at least partially mediated through this pathway. The addition of IL-17A partially restored the proliferation, invasion, clone, and migration abilities of CT26 and MC38 cells. These functional changes were assessed using CCK-8 assays, transwell invasion assays, colony formation assays, and wound healing assays. IL-17A treatment significantly rescued cell proliferation (Figure 7A). Invasion, clone and migration capacities were also partially restored following IL-17A supplementation (Figures 7B 7C and 7D). These results suggest that the inhibitory effects of lentiviral vectors carrying EREG shRNA on CT26 and MC38 cell proliferation, invasion, clone, and migration are, at least in part, mediated via the IL-17A/NF-κB signaling pathway. Changes in the Levels of Secreted Proteins in the TME Following EREG Knockdown After EREG knockdown, changes in the levels of several secreted proteins in the TME were assessed by ELISA using cell culture supernatants. EREG knockdown in CT26 cells led to increased expression of CCL5, CXCL1, CXCL2, CXCL3, and IL-6, while TNF-α expression decreased (Figure 8 A-F). Similarly, in MC38 cells, EREG knockdown induced upregulation of CCL5, CXCL1, CXCL2, CXCL3, and IL-6, accompanied by reduced TNF-α expression (Figure 8 G-L). Following IL-17A supplementation, expression levels of all these proteins except IL-6 were partially reversed. Previous studies have demonstrated that CCL5 is associated with increased infiltration of CD8⁺T lymphocytes. These results indicate that EREG knockdown can remodel the TME through the IL-17A/NF-κB signaling pathway, thereby promoting CD8⁺T cell infiltration. 4. Discussion In this study, we demonstrated that EREG expression was markedly elevated in CRC tissues compared to adjacent normal tissues, as confirmed by immunohistochemical analysis. Functional experiments revealed that knockdown of EREG significantly suppressed the proliferative, invasive, and migratory properties of CRC cells and induced cell apoptosis. Mechanistically, EREG depletion was associated with downregulation of IL-17A and NF-κB, while supplementation with IL-17A partially rescued these effects, suggesting that EREG may exert its tumor-promoting function through the IL-17A/NF-κB signaling axis. Interestingly, loss of EREG expression also led to increased levels of CCL5, CXCL1, CXCL2, and CXCL3, chemokines that are implicated in shaping the immune landscape of the TME. These findings highlight the dual role of EREG in promoting tumor cell activity and establishing an immunosuppressive TME, underscoring its potential as a therapeutic target in CRC. Consistent with our findings, previous studies have reported that EREG is frequently overexpressed in multiple malignancies, where it contributes to tumor cell proliferation, survival, and therapy resistance by activating EGFR signaling[ 23 ]. EREG has been identified as a driver of tumorigenesis in head and neck squamous cell carcinoma, and tumors with high EREG expression were shown to be highly sensitive to erlotinib treatment[ 24 ]. In lung cancer, EREG expression is closely associated with poor prognosis and the development of chemoresistance[ 25 , 26 ]. Similarly, EREG has been implicated in the initiation, progression, prognosis, and drug sensitivity of various gastrointestinal malignancies and cervical cancer[ 27 – 29 ]. Notably, high EREG expression has even been reported as an independent predictor of improved response to neoadjuvant chemoradiotherapy in CRC patients[ 30 ]. Collectively, these findings underscore the pivotal role of EREG in tumor biology across diverse cancer types and highlight its potential as a promising target for further mechanistic studies and therapeutic intervention. The immune landscape of CRC, in particular, is highly heterogeneous and influences the efficacy of immunotherapies[ 31 ]. In recent years, immune checkpoint inhibitors (ICIs), particularly PD-1 blockade, have emerged as one of the cornerstone strategies in cancer therapy. However, the recurrent and heterogeneous nature of the TME limits their efficacy, with an overall response rate of approximately 20%[ 32 ]. In CRC, the therapeutic benefit of PD-1 inhibitors is largely restricted to a small subset of patients with the MSI-H subtype. In the context of the TME, EREG has also been implicated in promoting immune evasion by modulating cytokine and chemokine networks that suppress anti-tumor immunity. For example, in non-small cell lung cancer, EREG expression correlates with regulatory T cell (Treg) infiltration and the expression of immunosuppressive factors such as PD-L1[ 33 ]. In this context, our findings that EREG knockdown leads to the upregulation of chemokines such as CCL5 and CXCL3 facilitating enhanced infiltration of CD8 + T cells and other immune effector populations—are particularly noteworthy. These results suggest that targeting EREG could remodel the immune landscape of CRC, shifting it from a cold to a more immunologically active phenotype, thereby potentially improving the efficacy of PD-1 blockade. Recent studies have underscored the significance of the IL-17A related signaling in tumorigenesis, TME remodeling, and immune evasion across multiple cancer types[ 34 – 36 ]. In this context, EREG has emerged as a crucial modulator of oncogenic signaling and immune regulation, while mechanistically, EREG depletion attenuated the expression of IL‑17A and NF-κB, indicating that EREG may orchestrate CRC progression through activation of the IL-17A/NF-κB signaling axis. Notably, supplementation with recombinant IL-17A restored tumor cell activity, suggesting a key role of IL-17A in mediating the pro-tumorigenic effects of EREG. The IL-17A/NF-κB pathway has been widely recognized for its contribution to chronic inflammation and tumorigenesis[ 37 , 38 ]. Upon binding to its receptor IL-17RA/RC, IL-17A recruits the adaptor molecule Act1 (also known as TRAF3IP2), which further engages TRAF6 to activate downstream NF-κB signaling[ 39 ]. This results in transcription of multiple cytokines, chemokines (such as CXCL1-3, CCL20), and metalloproteinases that shape the TME and support tumor growth and immune suppression[ 40 ]. In CRC, previous work has revealed that activation of this axis contributes to epithelial transformation, tumor cell invasion, and resistance to apoptosis [ 34 , 37 , 38 ]. Our data support and extend these findings by showing that EREG acts upstream of IL-17A/NF-κB. This positions EREG as a key regulatory node that may drive the chronic inflammatory and immunosuppressive landscape of the CRC TME. Taken together, our results reveal a previously uncharacterized EREG/IL-17A/NF-κB axis in CRC, whereby EREG promotes tumor cell aggressiveness and shapes an immune-suppressive microenvironment. Therapeutically, targeting EREG could not only suppress tumor-intrinsic growth signals but also enhance immunogenicity, making tumors more responsive to immune checkpoint blockade. Despite the compelling evidence supporting EREG’s role in CRC, several limitations of this study must be addressed. First, the functional assays and mechanistic explorations were primarily conducted in vitro and in murine CRC models. Although these models provide valuable information, they do not fully replicate the complexity of human CRC and its TME. Future studies employing patient-derived xenografts (PDX) or organoid systems could offer more clinically relevant insights. Second, while our data suggest that EREG promotes CRC progression and contributes to immune suppression via the IL-17A/NF-κB axis, the specific downstream targets and interactions within immune and stromal compartments remain incompletely characterized. Single-cell RNA sequencing and spatial transcriptomics may help elucidate how EREG driven signaling dynamically shapes the immune landscape in CRC. Moreover, the potential crosstalk between EREG signaling and other critical pathways in the TME, such as PD-1/PD-L1 and TGF-β, warrants further investigation. Given the emerging role of EREG in modulating both tumor cell-intrinsic and immune-related processes, targeting EREG could represent a promising therapeutic strategy. Combining EREG inhibition with immune checkpoint blockade or EGFR-targeted therapies might overcome resistance mechanisms observed in MSS-CRC, which remains largely refractory to current immunotherapies. Prospective clinical studies are needed to validate the translational potential of EREG as both a prognostic biomarker and a therapeutic target. In conclusion, our findings support a model in which EREG activates IL-17A/NF-κB signaling to drive immune suppression and tumor progression, while its inhibition remodels the TME to favor antitumor immunity. Future studies should evaluate the therapeutic potential of combinatorial strategies targeting EREG and IL-17A signaling pathways to enhance ICI efficacy in CRC. Abbreviations CRC colorectal cancer ICIs immune checkpoint inhibitors EREG Epiregulin IHC immunohistochemistry TCGA The Cancer Genome Atlas RT-qPCR real-time quantitative PCR TME tumor microenvironment ELISA enzyme-linked immunosorbent assay IL-17A Interleukin-17A Act1 Nuclear factor kappa-B activator 1 NF-κB༚Nuclear factor kappa-light-chain-enhancer of activated B cells PD-L1 programmed cell death 1 ligand 1 CCL5 C-C Motif Chemokine Ligand 5 CXCL1 C-X-C Motif Chemokine Ligand 1 CXCL2༚C-X-C Motif Chemokine Ligand 2 CXCL3 C-X-C Motif Chemokine Ligand 3 IL-6 Interleukin-6 TNF-α Tumor Necrosis Factor Alpha.​​​ Declarations Ethics Approval Statement: This study was approved by the Medical Ethics Committee of the Fourth Hospital of Hebei Medical University in accordance with the guidelines and regulations set forth by Ethical Review Measures for Life Science and Medical Research Involving Humans (2023). The protocol number for this approval is 2025KT330. Accordance Statement: All research procedures were conducted in accordance with the ethical standards of the Medical Ethics Committee of the Fourth Hospital of Hebei Medical University and adhered to the principles outlined in Ethical Review Measures for Life Science and Medical Research Involving Humans (2023), ensuring compliance throughout the study. Acknowledgements :We are grateful to the experimental platform provided by the Experimental Animal Center of the Fourth Hospital of Hebei Medical University. Data availability statement: The datasets generated and/or analyzed during the current study have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) and are publicly accessible under the accession number PRJNA1356697. The data can be accessed at the following permanent link: https://www.ncbi.nlm.nih.gov/sra/PRJNA1356697. All accession numbers and associated files have been fully released and are available for verification. Authors contributions :Data curation, Xiangpeng Gao; Funding acquisition, Jian Shi; Methodology, Xiangpeng Gao , Xiaoyang Duan; Project administration, Wenqing Xia, Yuanyuan Zhang, Xin Li; Supervision, Jian Shi; Writing-original draft, Xiangpeng Gao, Wenqing Xia; Writing-review & editing, Xiangpeng Gao, Wenqing Xia. All authors read and approved the final manuscript. Competing Interests :The authors have declared that no competing interest exists. Consent to Publish declaration :All authors have reviewed the manuscript and approved its submission for publication. Clinical trial number :not applicable. Consent to Participate declaration :Informed consent was obtained from all patients included in this study. Funding Declaration :This work was supported by the Health commission Medical Science Research Project of Hebei Province (grant no. 20240132). 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Supplementary Files Supplementarymaterial.zip Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 18 Dec, 2025 Reviews received at journal 12 Dec, 2025 Reviews received at journal 11 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers agreed at journal 08 Dec, 2025 Reviewers invited by journal 08 Dec, 2025 Editor assigned by journal 06 Dec, 2025 Submission checks completed at journal 06 Dec, 2025 First submitted to journal 27 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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(A) Expression levels of EREG in \u0026nbsp;\u0026nbsp;tumor versus adjacent normal tissues across multiple cancer types. (B) EREG \u0026nbsp;\u0026nbsp;expression is significantly higher in CRC tissues compared with adjacent \u0026nbsp;\u0026nbsp;normal tissues. (C) Negative correlation between EREG expression and CD8⁺T \u0026nbsp;\u0026nbsp;cell infiltration in CRC. (D) Heatmap showing markedly elevated EREG \u0026nbsp;\u0026nbsp;expression in CRC tissues relative to adjacent normal tissues. (E) IHC \u0026nbsp;\u0026nbsp;analysis validating EREG expression in human CRC and adjacent normal tissues. \u0026nbsp;\u0026nbsp;*\u003cem\u003eP\u003c/em\u003e \u0026lt;0.05，**\u003cem\u003eP\u003c/em\u003e \u0026lt;0.01,***\u003cem\u003eP\u003c/em\u003e \u0026lt;0.001.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7869610/v1/b38edb73f083637e2b906090.png"},{"id":98426014,"identity":"b04bdcd4-f6f9-40f3-96cc-2721b152a914","added_by":"auto","created_at":"2025-12-17 16:35:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":3341858,"visible":true,"origin":"","legend":"\u003cp\u003eSuccessful establishment of CRC cell models with EREG knockdown. (A) Representative fluorescence images of CT26 and MC38 cells at 72 h post-infection with shNC or shEREG lentiviral vectors, indicating efficient transduction. (B)RT-qPCR analysis showing reduced EREG mRNA levels in CT26 and MC38 cells treated with EREG shRNA compared to the control group. (C) Western blot analysis demonstrating decreased EREG protein expression in CT26 and MC38 cells following EREG shRNA treatment relative to controls. *\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05，**\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01，***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7869610/v1/bb699cd387a693617d623c09.png"},{"id":98007351,"identity":"3a1c2386-9fd9-4593-a4e1-07d4fe510cff","added_by":"auto","created_at":"2025-12-11 17:20:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1810881,"visible":true,"origin":"","legend":"\u003cp\u003eEREG knockdown suppresses proliferation,invasion,clone,and migration of CRC cells. (A) Cell proliferation assessed by CCK-8 assay. (B) Cell invasion analyzed using Transwell assay. (C) Cell clone evaluated by colony formation assay. (D) Cell migration measured by wound healing assay. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05，**\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01，***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7869610/v1/8b883ad9b448bfbac8b6c00f.png"},{"id":98425379,"identity":"14703e96-58c4-4114-bf1f-637c19ecc9c5","added_by":"auto","created_at":"2025-12-17 16:34:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":233082,"visible":true,"origin":"","legend":"\u003cp\u003eKnockdown of EREG promotes apoptosis in CRC cells. Flow cytometric analysis of apoptosis in CT26 and MC38 cells. Data demonstrate increased apoptosis rates in EREG knockdown groups compared to controls. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05，**\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01，***\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7869610/v1/a686033ef964b7803a448d8b.png"},{"id":98424666,"identity":"dad94f69-2cff-4fdf-b684-e93320ad90c8","added_by":"auto","created_at":"2025-12-17 16:33:38","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":722692,"visible":true,"origin":"","legend":"\u003cp\u003eDifferentially expressed genes (DEGs) following EREG knockdown were predominantly enriched in the IL-17A/NF-κB signaling pathway. (A) Volcano plot of DEGs. (B) Heatmap of DEGs. (C) Top 20 enriched KEGG pathways of DEGs. (D) Top 20 enriched WikiPathways of DEGs. (E) Top 20 enriched pathways of DEGs after EREG knockdown from TCGA analysis.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7869610/v1/5eabefa9b4a2757282f900c7.png"},{"id":98425470,"identity":"55c1d1fd-deea-4e40-954d-9c5fa0153c98","added_by":"auto","created_at":"2025-12-17 16:34:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1456352,"visible":true,"origin":"","legend":"\u003cp\u003eEREG knockdown inhibits the activity of the IL-17A/NF-κB signaling pathway, which is partially restored upon IL-17A supplementation. Western blot analysis showing that EREG knockdown downregulated Act1, IL-17RA, MMP9, phosphorylated NF-κB1 (p-NF-κB1) and IL-17A protein levels, while supplementation with IL-17A reversed these inhibitory effects and restored expression of these proteins in CT26 (A) and MC38 (B) CRC cells. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05，**\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01，***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7869610/v1/60664913329006fa1c89cccd.png"},{"id":98007357,"identity":"c8a26b24-3b20-43b8-b516-008af1a2e836","added_by":"auto","created_at":"2025-12-11 17:20:47","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1473522,"visible":true,"origin":"","legend":"\u003cp\u003eIL-17A supplementation partially reverses the phenotypic alterations induced by EREG knockdown in CRC cells. (A) Cell proliferation assessed by CCK-8 assay. (B) Cell invasion evaluated using transwell assays. (C) Cell clone determined by colony formation assays. (D) Cell migration assessed by wound healing assays. *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05，**\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01，***\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7869610/v1/8c12333ea389bc4bfc3fc5a4.png"},{"id":98425655,"identity":"0a3fd227-53ad-43db-bd27-eecee9b00fc6","added_by":"auto","created_at":"2025-12-17 16:35:01","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":996302,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in the Levels of Secreted Proteins in the TME Following \u0026nbsp;\u0026nbsp;EREG Knockdown. ELISA quantification of secreted proteins CCL5, CXCL1, CXCL2, \u0026nbsp;\u0026nbsp;CXCL3, IL-6, and TNF-α in culture supernatants from three experimental groups \u0026nbsp;\u0026nbsp;of CT26 (A–F) and MC38 (G–L) cells following EREG knockdown. *\u003cem\u003eP \u003c/em\u003e\u0026lt; \u0026nbsp;\u0026nbsp;0.05，**\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01，***\u003cem\u003eP\u003c/em\u003e \u0026nbsp;\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7869610/v1/30ecec51e4dd311029b94f37.png"},{"id":98622188,"identity":"f427c095-f200-4f4a-885c-7a05a669c09f","added_by":"auto","created_at":"2025-12-19 16:48:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13799852,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7869610/v1/56f66f2b-e1eb-4f3b-8c02-b7f0865458f4.pdf"},{"id":98007365,"identity":"6055ea55-3f2b-4546-a018-51bae55bff04","added_by":"auto","created_at":"2025-12-11 17:20:47","extension":"zip","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2539652,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.zip","url":"https://assets-eu.researchsquare.com/files/rs-7869610/v1/6bd3177282cfa9ccefe26b6b.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"EREG promotes colorectal cancer progression and immune suppressive microenvironment formation through IL-17A/NF-κB pathway","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCRC is the third most commonly diagnosed and the second most lethal malignancy worldwide, with approximately 1.9\u0026nbsp;million new cases and 900,000 deaths reported in 2020[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. More than 20% of cases are diagnosed with distant metastases at initial presentation, and the incidence is increasingly observed in younger individuals[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. CRC is a highly heterogeneous disease, traditionally classified into two subtypes based on tumor location: proximal colon and distal colon types[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. With the advancement of precision medicine and molecular diagnostics, the CRC Subtyping Consortium established a novel classification system in 2015, known as the Consensus Molecular Subtypes (CMSs), comprising four distinct molecular subtypes. This system aims to standardize CRC classification and guide subtype-specific therapeutic strategies[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. At present, therapeutic approaches for CRC include endoscopic and surgical resection, radiotherapy, chemotherapy, immunotherapy, targeted therapy, and local ablative treatments[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. While these interventions have improved outcomes for certain patient subsets, the overall prognosis remains poor. In recent years, immunotherapy, represented by PD-1 inhibitors, has emerged as one of the established standard-of-care therapies for multiple malignancies. However, due to the complexity and heterogeneity of the TME, the overall response rate to immunotherapy remains relatively low, at only 20\u0026ndash;30%[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In CRC, immunotherapy shows clinical benefit primarily in a small subset of patients with high microsatellite instability-high (MSI-H), while the majority of microsatellite stable (MSS) tumors exhibit poor responsiveness, highlighting the need for more effective strategies to expand the responsive population.\u003c/p\u003e\u003cp\u003eTME, a complex and dynamic ecosystem comprising immune cells, stromal cells, fibroblasts, endothelial cells, extracellular matrix components, and diverse cytokines and chemokines, plays a pivotal role in the initiation, progression, and therapeutic response of CRC[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Increasing evidence suggests that the TME not only supports tumor growth and metastasis but also critically shapes the immune landscape of CRC. In particular, the immunosuppressive characteristics of the TME such as regulatory T cell (Treg) infiltration, myeloid-derived suppressor cell (MDSC) expansion, and upregulation of immune checkpoint molecules contribute to immune evasion and resistance to immunotherapy[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Furthermore, the heterogeneity of the TME across different CRC subtypes, especially between MSI-H and MSS tumors, significantly influences the clinical efficacy of immune checkpoint blockade. MSI-H tumors are typically characterized by high tumor mutational burden (TMB), increased neoantigen load, and dense CD8\u003csup\u003e+\u003c/sup\u003eT cell infiltration, rendering them more responsive to PD-1/PD-L1 inhibitors[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In contrast, the majority of MSS tumors exhibit an immunologically cold phenotype, with poor T cell infiltration and a suppressive TME, resulting in limited benefit from current immunotherapies[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo overcome the limited efficacy of ICIs in MSS CRC, considerable efforts have been devoted to reprogramming the TME and converting immunologically cold tumors into hot ones. Various strategies have been investigated, including the combination of PD-1/PD-L1 inhibitors with chemotherapeutic agents, radiotherapy, anti-angiogenic therapies (e.g., bevacizumab), and targeted therapies against EGFR or MEK[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. These combinatorial approaches aim to enhance tumor immunogenicity, promote T cell infiltration, and modulate immunosuppressive elements within the TME. These advances underscore the importance of understanding and manipulating the TME to overcome resistance and expand the clinical benefit of immunotherapy in CRC. Despite these advances, the underlying mechanisms by which key immunomn colodulatory molecules regulate the immune landscape of CRC remain incompletely understood.\u003c/p\u003e\u003cp\u003eEREG is a member of the epidermal growth factor (EGF) family that acts as a ligand for the epidermal growth factor receptor (EGFR) and ErbB4[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Through activation of EGFR downstream signaling cascades, including the RAS/RAF/MEK/ERK and PI3K/AKT pathways, EREG plays a pivotal role in regulating cell proliferation, survival, migration, and epithelial-mesenchymal transition (EMT)[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. EREG has been reported to be upregulated, and the EGFR signaling pathway has likewise been demonstrated to be hyperactivated in various malignancies, including non-small cell lung cancer, breast cancer and bladder cancer[\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Recent studies have implicated EREG in modulating tumor progression and immune signaling, with its frequent overexpression in CRC being associated with poor prognosis, enhanced tumor cell proliferation, and therapy resistance[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, its specific role in CRC cell viability and shaping the immunosuppressive TME and mediating immune evasion remains poorly defined.\u003c/p\u003e\u003cp\u003eEmerging data also suggest that certain chemokines, such as CXCL3 and CCL5, may be upregulated in specific CRC subtypes and are closely associated with immune cell recruitment and inflammatory signaling[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Whether these chemokines act downstream of EREG and contribute to the formation of a cold tumor phenotype is a question of significant interest. Moreover, the IL-17A/NF-κB pathway has been widely recognized for its contribution to chronic inflammation and tumorigenesis[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, the relationship between EREG deficiency and alterations in the IL-17A/NF-κB signaling axis, as well as its impact on tumor immunogenicity, has yet to be elucidated.\u003c/p\u003e\u003cp\u003eThis study aims to elucidate the role of EREG in CRC cell viability and modulating the CRC TME, with a particular focus on its influence on immune-related signaling pathways and chemokine expression. By dissecting the molecular link between EREG and the IL-17A/NF-κB axis, we seek to clarify how EREG contributes to immune evasion in CRC. Understanding these mechanisms may provide new insights into immunotherapeutic resistance and uncover potential targets to enhance antitumor immunity, especially in MSS CRC.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cb\u003eBioinformatics analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDifferentially expressed genes (DEGs) were identified from TCGA database using R software, with thresholds set at |log₂ fold change| \u0026gt;1 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Functional annotation of DEGs was performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to explore biological processes and pathways involved. Immune cell infiltration was assessed using the TIMER2.0 web server to evaluate the tumor immune microenvironment.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIHC\u003c/b\u003e\u003c/p\u003e\u003cp\u003eParaffin-embedded tissue sections were deparaffinized and rehydrated through graded alcohols. Antigen retrieval was performed using citrate buffer, followed by treatment with 3% hydrogen peroxide (H₂O₂) at room temperature for 15 min to block endogenous peroxidase activity. Non-specific binding sites were blocked by incubation with low-concentration serum for 15 min. The sections were then incubated overnight at 4\u0026deg;C with diluted primary antibodies (1:600), followed by incubation with secondary antibodies at room temperature for 20 min. Subsequently, the sections were incubated with streptavidin\u0026ndash;horseradish peroxidase (SA-HRP) solution for 20 min. Visualization was achieved using 3,3\u0026rsquo;-diaminobenzidine (DAB) substrate (ZSGB-BIO, China), and counterstaining was performed with hematoxylin. The sections were mounted with neutral balsam and images were captured using a light microscope (Olympus, Japan) at 200\u0026times;magnification. Quantitative analysis was performed using Image-Pro Plus software.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCell Culture and Lentiviral Infection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe mouse CRC cell line CT26 (RRID: CVCL_7254) and MC38 (RRID: CVCL_B288) were purchased from Cyagen Biosciences (Shanghai) Co., Ltd. (Shanghai, China). All cell lines were authenticated by short tandem repeat (STR) profiling and confirmed to be free of mycoplasma contamination before use. Cells were cultured in Dulbecco\u0026rsquo;s Modified Eagle Medium (DMEM; Hyclone, USA) supplemented with 10% fetal bovine serum (FBS; Gibco, USA) at 37\u0026deg;C in a humidified atmosphere containing 5% CO\u003csub\u003e2\u003c/sub\u003e. The lentiviral vector encoding shRNA targeting EREG was synthesized and packaged by GeneChem Co., Ltd., Shanghai. When the cells reached approximately 70% confluence, 5\u0026times;10⁵ cells/well were seeded into six-well plates and infected with lentiviral vectors carrying either EREG shRNA sequences or negative control (NC) shRNA sequences at a multiplicity of infection (MOI) of 20. After 24 h of infection, the medium was replaced, and transfection efficiency was evaluated using an inverted fluorescence microscope. Subsequently, the cells were selected with puromycin (2 \u0026micro;g/mL) for 3 d.\u003c/p\u003e\u003cp\u003e\u003cb\u003eReal-time quantitative PCR (RT-qPCR)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCT26 and MC38 cells transfected with either EREG shRNA or negative control (NC) shRNA were collected, and total RNA was extracted using a Total RNA Kit (Omega, USA) according to the manufacturer instructions. Complementary DNA (cDNA) was synthesized using the PrimeScript\u0026trade; RT reagent kit with gDNA Eraser (Takara, Japan). Quantitative real-time PCR was performed using SYBR Premix Ex Taq\u0026trade; II (Takara, Japan). The primer sequences for EREG were 5\u0026rsquo;-AAGTGGGCTACACTGGTCT-3\u0026rsquo;(forward) and 5\u0026rsquo;-TGTCAACGCAACGTATTCT-3\u0026rsquo;(reverse)and for Actb were 5\u0026rsquo;-GCACCACACCTTCTACAATG-3\u0026rsquo;(forward) and 5\u0026rsquo;-GTGAGGGAGAGCATAGCC-3\u0026rsquo;(reverse). The qPCR program consisted of 40 cycles of 95\u0026deg;C for 15 s, 55\u0026deg;C for 30 s, and 72\u0026deg;C for 30 s. The relative mRNA expression levels between groups were calculated using the 2-ΔΔCt method.\u003c/p\u003e\u003cp\u003e\u003cb\u003eWestern blot\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCells were lysed using RIPA buffer supplemented with 1 mM phenylmethylsulfonyl fluoride (PMSF) (both from Beyotime, China). Total protein concentrations were determined using a bicinchoninic acid (BCA) protein assay kit (Beyotime, China), with bovine serum albumin as the standard. Protein samples were mixed with loading buffer and boiled in a 100\u0026deg;C water bath for 5 min. Equal amounts of protein were separated on 12% SDS-polyacrylamide gels (Beyotime, China) and transferred onto polyvinylidene difluoride (PVDF) membranes (Bio-Rad, USA). The membranes were blocked with 5% non-fat dry milk to prevent nonspecific binding, and α-tubulin was used as the loading control. Subsequently, the membranes were incubated with primary antibodies (Santa Cruz Biotechnology, USA), followed by horseradish peroxidase (HRP)-conjugated secondary antibodies (TransGen Biotech, China). Protein bands were visualized using an enhanced chemiluminescence (ECL) detection kit (PLYGEN, China) and detected on X-ray film. Band intensities were quantified using ImageJ software.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCCK-8 assay and transwell invasion assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor the cell proliferation assay, 100 \u0026micro;L of cell suspension (5000 cells/well) was seeded into 96-well plates, with three replicate wells per group at each time point. After the cells adhered, the original medium was replaced with complete medium containing the indicated treatments. At 0 h, 24 h, 48 h, and 72 h, 10 \u0026micro;L of CCK-8 solution (Dojindo, Japan) was added to each well, followed by incubation at 37\u0026deg;C for 2 h. The absorbance at 450 nm was measured using a microplate reader.\u003c/p\u003e\u003cp\u003eFor the invasion assay, Matrigel (BD Biosciences, USA) was diluted 1:8 with serum-free DMEM and applied to the upper chamber before cell seeding. The chambers were incubated at 37\u0026deg;C in a humidified atmosphere containing 5% CO\u003csub\u003e2\u003c/sub\u003e for 24 h. After incubation, the medium was discarded, and non-migrated or non-invaded cells on the inner surface of the membrane were gently removed with a cotton swab. Cells on the underside of the membrane were fixed and stained with 0.1% crystal violet for 10 min, then rinsed twice with double-distilled water (ddH\u003csub\u003e2\u003c/sub\u003eO). Migrated or invaded cells were counted in five randomly selected fields under a light microscope (Olympus, Japan) at 200\u0026times;magnification. The average cell count was used to evaluate migratory and invasive capacities.\u003c/p\u003e\u003cp\u003e\u003cb\u003eColony formation assay and wound healing assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor the colony formation assay, cells in the logarithmic growth phase were trypsinized, centrifuged, and seeded at a density of 500 cells/well in six-well plates. The plates were gently rotated to ensure even cell distribution and cultured for 13 d. Subsequently, the cells were washed with PBS, fixed with 4% paraformaldehyde for 20 min, and stained with 0.1% crystal violet for 20 min. Excess stain was washed away with running water, and the plates were air-dried. Colonies were photographed and counted manually.\u003c/p\u003e\u003cp\u003eCells from each group were collected and resuspended in serum-free DMEM at a concentration of approximately 1.5\u0026times;10⁵ cells/mL. For the migration assay, 200 \u0026micro;L of the cell suspension was added to the upper chamber of a Transwell insert (Corning Costar, USA), and 800 \u0026micro;L of DMEM supplemented with 10% fetal bovine serum (FBS) was added to the lower chamber as a chemoattractant.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFlow Cytometry Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCells were collected and washed twice with ice-cold PBS, followed by fixation in 70% ice-cold ethanol at 4\u0026deg;C overnight. After centrifugation, the cells were resuspended in 400 \u0026micro;L of ice-cold PBS containing 20 \u0026micro;L of RNase A solution (Vazyme Biotech, China) and incubated in a 37\u0026deg;C water bath for 30 min. Subsequently, 400 \u0026micro;L of propidium iodide (PI) staining solution (Vazyme Biotech, China) was added. After incubation at 4\u0026deg;C for 30 min in the dark, the samples were analyzed using a flow cytometer (Roche, Switzerland).\u003c/p\u003e\u003cp\u003e\u003cb\u003eTranscriptomics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTotal RNA was extracted from EREG-knockdown and control cells using TRIzol reagent according to the manufacturer\u0026rsquo;s protocol. RNA sequencing (RNA-seq) was performed using the Illumina NovaSeq 6000 platform to generate 150 bp paired-end reads. The reads were aligned to the reference genome using HISAT2, and gene expression levels were quantified as FPKM (Fragments Per Kilobase of transcript per Million mapped reads). Read counts for each gene were obtained using HTSeq-count. Differentially expressed genes (DEGs) were identified using DESeq2, with genes meeting the criteria of q-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log2FC| \u0026gt;1.0​considered statistically significant. Hierarchical clustering analysis of DEGs was performed using R (v3.2.0) to visualize gene expression patterns across different groups and samples.Functional enrichment analysis was conducted using​KEGG Pathway​and WikiPathways​databases based on the hypergeometric distribution algorithm to identify significantly enriched biological pathways and functional categories. The datasets generated and/or analysed during the current study have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under the accession number PRJNA1356697. The data can be accessed at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/sra/PRJNA1356697\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/sra/PRJNA1356697\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eELISA\u003c/b\u003e\u003c/p\u003e\u003cp\u003eReagents and microplate must reach room temperature; standards and samples are assayed in duplicate. Dispense 50 \u0026micro;L of each standard into the designated wells, and combine 10 \u0026micro;L test sample with 40 \u0026micro;L Sample Diluent in sample wells; leave blanks empty. Add 100 \u0026micro;L HRP-conjugate to every well, seal with an adhesive strip, and incubate 60 min at 37\u0026deg;C. Aspirate contents, then wash five times with 400 \u0026micro;L Wash Solution, inverting and blotting on paper towels after the final rinse. Pipette 50 \u0026micro;L chromogen A followed by 50 \u0026micro;L chromogen B into each well, mix gently, protect from light, and incubate 15 min at 37\u0026deg;C. Stop the reaction with 50 \u0026micro;L Stop Solution; color should shift to uniform yellow. Measure absorbance at 450 nm within 15 min. (Jiangsu Meimian Industrial Co., Ltd.)\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistical Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eStatistical analyses were performed using SPSS software version 16.0 (SPSS Inc., USA). Data are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Comparisons between groups were conducted using Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003eEREG is highly expressed in CRC and correlates with immune cell infiltration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on analysis of the TCGA database, EREG is highly expressed in 28 tumor types, including CRC (Figures 1A 1B and 1D), and its expression level is negatively correlated with CD8\u003csup\u003e+\u003c/sup\u003eT lymphocyte infiltration (Figure 1C). IHC analysis of tumor and adjacent normal tissues from eight colorectal cancer patients further confirmed the elevated expression of EREG in CRC tissues (Figure 1E). These findings indicate that EREG is highly expressed in CRC and is closely associated with the TME.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEREG shRNA significantly downregulated EREG expression in CT26 and MC38 cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEREG expression was markedly suppressed in CT26 and MC38 cells following shRNA-mediated knockdown. Successful lentiviral transduction was confirmed by the presence of green fluorescence in both control (shNC) and experimental (shEREG) groups at 72 h post-infection, as observed under fluorescence microscopy (Figure 2A). Subsequent RT-qPCR and Western blot analyses demonstrated a significant reduction in EREG mRNA and protein levels across CT26-shEREG-1, CT26-shEREG-2, CT26-shEREG-3, \u0026nbsp;MC38-shEREG-1, MC38-shEREG-2 and MC38-shEREG-3 cell lines relative to the shNC controls (Figures 2B and 2C), thereby validating the effective establishment of EREG knockdown CRC cell models.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKnockdown of EREG suppresses proliferation, invasion, clone, and migration in CRC cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCell proliferation, invasion, clone, and migration abilities were evaluated using CCK-8 assay, Transwell assay, colony formation assay, and wound healing assay respectively.Proliferative capacity was significantly inhibited in CT26 and MC38 cells transfected with EREG shRNA compared to the control group (Figure 3A). Invasive ability of both cell lines was markedly suppressed following EREG knockdown (Figure 3B). Similarly, clonogenic capacity was significantly reduced in EREG-silenced cells (Figure 3C). Furthermore, migratory ability was also notably impaired in the EREG shRNA group (Figure 3D). These results indicate that the lentiviral vector carrying EREG shRNA effectively inhibits proliferation, invasion, clone, and migration abilities in CT26 and MC38 cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEREG knockdown promotes apoptosis in CRC cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFlow cytometry analysis revealed a significant increase in apoptotic cells in the EREG knockdown groups compared to controls, indicating that EREG silencing enhances apoptosis in CT26 and MC38 cell lines (Figure 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDifferentially expressed genes following EREG knockdown were primarily enriched in the IL-17A/NF-\u0026kappa;B signaling pathway.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTranscriptomic analysis revealed that 538 genes were upregulated and 534 genes were downregulated in the EREG-knockdown groupcompared to the control group (screening criteria:q-value \u0026lt; 0.05 \u0026amp; |log2FC| \u0026gt; 1.0). Among the upregulated genes, CD276, Lag3, and IL-17c were identified, all of which are associated with tumor immune phenotype formation. Conversely, downregulated genes such as Traf1 andMmp9 were linked to inflammatory responses (Figure 5A 5B). Functional enrichment analysis of these differentially expressed genes (DEGs) was performed. KEGG pathway analysisof the top 20 enriched pathways highlighted the IL-17 signaling pathway andchemokine signaling pathway, which are primarily involved in immune microenvironment regulation. Similarly, WikiPathways analysis of the top 20 pathways also identified IL-17 signaling and chemokine signalingas significantly enriched (Figure 5C 5D). To further validate the functional relevance of EREG knockdown, we integrated data from TCGA database. TCGA analysis demonstrated that the IL-17A/NF-\u0026kappa;B signaling pathway was the most prominently shared enriched pathway between our RNA-seq data and TCGA datasets (Figure 5E).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEREG knockdown inhibits the activity of the IL-17A/NF-\u0026kappa;B signaling pathway, which is partially restored upon IL-17A supplementation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWestern blot analysis demonstrated that in CT26 (Figure 6 A) and MC38 (Figure 6 B) cells, EREG knockdown led to decreased expression of IL-17A upper, IL-17A lower, IL-17RA, Act1, NF-\u0026kappa;B1, phosphorylated NF-\u0026kappa;B1 (p-NF-\u0026kappa;B1), and MMP9. However, following treatment with IL-17A, the expression levels of Act1, NF-\u0026kappa;B1, p-NF-\u0026kappa;B1, MMP9, IL-17A upper, and IL-17A lower were partially restored. These results indicate that EREG knockdown suppresses the IL-17A/NF-\u0026kappa;B signaling pathway activity, and that the biological functions of EREG are at least partially mediated through this pathway.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe addition of IL-17A partially restored the proliferation, invasion, clone, and migration abilities of CT26 and MC38 cells.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese functional changes were assessed using CCK-8 assays, transwell invasion assays, colony formation assays, and wound healing assays. IL-17A treatment significantly rescued cell proliferation (Figure 7A). Invasion, clone and migration capacities were also partially restored following IL-17A supplementation (Figures 7B 7C and 7D). These results suggest that the inhibitory effects of lentiviral vectors carrying EREG shRNA on CT26 and MC38 cell proliferation, invasion, clone, and migration are, at least in part, mediated via the IL-17A/NF-\u0026kappa;B signaling pathway.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChanges in the Levels of Secreted Proteins in the TME Following EREG Knockdown\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter EREG knockdown, changes in the levels of several secreted proteins in the TME were assessed by ELISA using cell culture supernatants. EREG knockdown in CT26 cells led to increased expression of CCL5, CXCL1, CXCL2, CXCL3, and IL-6, while TNF-\u0026alpha; expression decreased (Figure 8 A-F). Similarly, in MC38 cells, EREG knockdown induced upregulation of CCL5, CXCL1, CXCL2, CXCL3, and IL-6, accompanied by reduced TNF-\u0026alpha; expression (Figure 8 G-L). Following IL-17A supplementation, expression levels of all these proteins except IL-6 were partially reversed. Previous studies have demonstrated that CCL5 is associated with increased infiltration of CD8⁺T lymphocytes. These results indicate that EREG knockdown can remodel the TME through the IL-17A/NF-\u0026kappa;B signaling pathway, thereby promoting CD8⁺T cell infiltration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this study, we demonstrated that EREG expression was markedly elevated in CRC tissues compared to adjacent normal tissues, as confirmed by immunohistochemical analysis. Functional experiments revealed that knockdown of EREG significantly suppressed the proliferative, invasive, and migratory properties of CRC cells and induced cell apoptosis. Mechanistically, EREG depletion was associated with downregulation of IL-17A and NF-κB, while supplementation with IL-17A partially rescued these effects, suggesting that EREG may exert its tumor-promoting function through the IL-17A/NF-κB signaling axis. Interestingly, loss of EREG expression also led to increased levels of CCL5, CXCL1, CXCL2, and CXCL3, chemokines that are implicated in shaping the immune landscape of the TME. These findings highlight the dual role of EREG in promoting tumor cell activity and establishing an immunosuppressive TME, underscoring its potential as a therapeutic target in CRC.\u003c/p\u003e\u003cp\u003eConsistent with our findings, previous studies have reported that EREG is frequently overexpressed in multiple malignancies, where it contributes to tumor cell proliferation, survival, and therapy resistance by activating EGFR signaling[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. EREG has been identified as a driver of tumorigenesis in head and neck squamous cell carcinoma, and tumors with high EREG expression were shown to be highly sensitive to erlotinib treatment[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In lung cancer, EREG expression is closely associated with poor prognosis and the development of chemoresistance[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Similarly, EREG has been implicated in the initiation, progression, prognosis, and drug sensitivity of various gastrointestinal malignancies and cervical cancer[\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Notably, high EREG expression has even been reported as an independent predictor of improved response to neoadjuvant chemoradiotherapy in CRC patients[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Collectively, these findings underscore the pivotal role of EREG in tumor biology across diverse cancer types and highlight its potential as a promising target for further mechanistic studies and therapeutic intervention.\u003c/p\u003e\u003cp\u003eThe immune landscape of CRC, in particular, is highly heterogeneous and influences the efficacy of immunotherapies[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In recent years, immune checkpoint inhibitors (ICIs), particularly PD-1 blockade, have emerged as one of the cornerstone strategies in cancer therapy. However, the recurrent and heterogeneous nature of the TME limits their efficacy, with an overall response rate of approximately 20%[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In CRC, the therapeutic benefit of PD-1 inhibitors is largely restricted to a small subset of patients with the MSI-H subtype. In the context of the TME, EREG has also been implicated in promoting immune evasion by modulating cytokine and chemokine networks that suppress anti-tumor immunity. For example, in non-small cell lung cancer, EREG expression correlates with regulatory T cell (Treg) infiltration and the expression of immunosuppressive factors such as PD-L1[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In this context, our findings that EREG knockdown leads to the upregulation of chemokines such as CCL5 and CXCL3 facilitating enhanced infiltration of CD8\u003csup\u003e+\u003c/sup\u003eT cells and other immune effector populations\u0026mdash;are particularly noteworthy. These results suggest that targeting EREG could remodel the immune landscape of CRC, shifting it from a cold to a more immunologically active phenotype, thereby potentially improving the efficacy of PD-1 blockade.\u003c/p\u003e\u003cp\u003eRecent studies have underscored the significance of the IL-17A related signaling in tumorigenesis, TME remodeling, and immune evasion across multiple cancer types[\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In this context, EREG has emerged as a crucial modulator of oncogenic signaling and immune regulation, while mechanistically, EREG depletion attenuated the expression of IL‑17A and NF-κB, indicating that EREG may orchestrate CRC progression through activation of the IL-17A/NF-κB signaling axis. Notably, supplementation with recombinant IL-17A restored tumor cell activity, suggesting a key role of IL-17A in mediating the pro-tumorigenic effects of EREG. The IL-17A/NF-κB pathway has been widely recognized for its contribution to chronic inflammation and tumorigenesis[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Upon binding to its receptor IL-17RA/RC, IL-17A recruits the adaptor molecule Act1 (also known as TRAF3IP2), which further engages TRAF6 to activate downstream NF-κB signaling[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. This results in transcription of multiple cytokines, chemokines (such as CXCL1-3, CCL20), and metalloproteinases that shape the TME and support tumor growth and immune suppression[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In CRC, previous work has revealed that activation of this axis contributes to epithelial transformation, tumor cell invasion, and resistance to apoptosis [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Our data support and extend these findings by showing that EREG acts upstream of IL-17A/NF-κB. This positions EREG as a key regulatory node that may drive the chronic inflammatory and immunosuppressive landscape of the CRC TME.\u003c/p\u003e\u003cp\u003eTaken together, our results reveal a previously uncharacterized EREG/IL-17A/NF-κB axis in CRC, whereby EREG promotes tumor cell aggressiveness and shapes an immune-suppressive microenvironment. Therapeutically, targeting EREG could not only suppress tumor-intrinsic growth signals but also enhance immunogenicity, making tumors more responsive to immune checkpoint blockade. Despite the compelling evidence supporting EREG\u0026rsquo;s role in CRC, several limitations of this study must be addressed. First, the functional assays and mechanistic explorations were primarily conducted in vitro and in murine CRC models. Although these models provide valuable information, they do not fully replicate the complexity of human CRC and its TME. Future studies employing patient-derived xenografts (PDX) or organoid systems could offer more clinically relevant insights. Second, while our data suggest that EREG promotes CRC progression and contributes to immune suppression via the IL-17A/NF-κB axis, the specific downstream targets and interactions within immune and stromal compartments remain incompletely characterized. Single-cell RNA sequencing and spatial transcriptomics may help elucidate how EREG driven signaling dynamically shapes the immune landscape in CRC. Moreover, the potential crosstalk between EREG signaling and other critical pathways in the TME, such as PD-1/PD-L1 and TGF-β, warrants further investigation. Given the emerging role of EREG in modulating both tumor cell-intrinsic and immune-related processes, targeting EREG could represent a promising therapeutic strategy. Combining EREG inhibition with immune checkpoint blockade or EGFR-targeted therapies might overcome resistance mechanisms observed in MSS-CRC, which remains largely refractory to current immunotherapies. Prospective clinical studies are needed to validate the translational potential of EREG as both a prognostic biomarker and a therapeutic target.\u003c/p\u003e\u003cp\u003eIn conclusion, our findings support a model in which EREG activates IL-17A/NF-κB signaling to drive immune suppression and tumor progression, while its inhibition remodels the TME to favor antitumor immunity. Future studies should evaluate the therapeutic potential of combinatorial strategies targeting EREG and IL-17A signaling pathways to enhance ICI efficacy in CRC.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCRC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ecolorectal cancer\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICIs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eimmune checkpoint inhibitors\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEREG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEpiregulin\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIHC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eimmunohistochemistry\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTCGA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eThe Cancer Genome Atlas\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRT-qPCR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ereal-time quantitative PCR\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTME\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003etumor microenvironment\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eELISA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eenzyme-linked immunosorbent assay\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIL-17A\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInterleukin-17A\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAct1\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNuclear factor kappa-B activator 1\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNF-κB༚Nuclear factor kappa-light-chain-enhancer of activated B cells\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePD-L1\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eprogrammed cell death 1 ligand 1\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCCL5\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eC-C Motif Chemokine Ligand 5\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCXCL1\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eC-X-C Motif Chemokine Ligand 1\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCXCL2༚C-X-C Motif Chemokine Ligand 2\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCXCL3\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eC-X-C Motif Chemokine Ligand 3\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIL-6\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInterleukin-6\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTNF-α\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTumor Necrosis Factor Alpha.​​​\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval Statement:\u003c/strong\u003e This study was approved by the Medical Ethics Committee of the Fourth Hospital of Hebei Medical University in accordance with the guidelines and regulations set forth by Ethical Review Measures for Life Science and Medical Research Involving Humans (2023). The protocol number for this approval is 2025KT330.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAccordance Statement:\u0026nbsp;\u003c/strong\u003eAll research procedures were conducted in accordance with the ethical standards of the Medical Ethics Committee of the Fourth Hospital of Hebei Medical University and adhered to the principles outlined in Ethical Review Measures for Life Science and Medical Research Involving Humans (2023), ensuring compliance throughout the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e:We are grateful to the experimental platform provided by the Experimental Animal Center of the Fourth Hospital of Hebei Medical University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003eThe datasets generated and/or analyzed during the current study have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) and are publicly accessible under the accession number PRJNA1356697. The data can be accessed at the following permanent link: https://www.ncbi.nlm.nih.gov/sra/PRJNA1356697. All accession numbers and associated files have been fully released and are available for verification.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions\u003c/strong\u003e:Data curation, Xiangpeng Gao; Funding acquisition, Jian Shi; Methodology, Xiangpeng Gao , Xiaoyang Duan; Project administration, Wenqing Xia, Yuanyuan Zhang, Xin Li; Supervision, Jian Shi; Writing-original draft, Xiangpeng Gao, Wenqing Xia; Writing-review \u0026amp; editing, Xiangpeng Gao, Wenqing Xia. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e:The authors have declared that no competing interest exists.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Publish declaration\u003c/strong\u003e:All authors have reviewed the manuscript and approved its submission for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e:not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate declaration\u003c/strong\u003e:Informed consent was obtained from all patients included in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e:This work was supported by the Health commission Medical Science Research Project of Hebei Province (grant no. 20240132).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eXi Y, Xu P.Global colorectal cancer burden in 2020 and projections to 2040.Transl Oncol 2021Oct;14(10).DOI:10.1016/j.tranon.2021.101174\u003c/li\u003e\n\u003cli\u003eNational Cancer Institute. 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Online ahead of print.\u003c/li\u003e\n\u003cli\u003eXia W, Shen Y, Chen F, Liu X, Cao Y, Shi Z.Sennoside A represses the malignant phenotype and tumor immune microenvironment of non-small cell lung cancer cells by inhibiting the TRAF6/NF-kappaB pathway.Naunyn Schmiedebergs Arch Pharmacol. 2025 May;398(5):5405-5415. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"colorectal cancer (CRC), Epiregulin (EREG), tumor microenvironment (TME), Transcriptomics, IL17A/NF-κB","lastPublishedDoi":"10.21203/rs.3.rs-7869610/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7869610/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eColorectal cancer (CRC), as a common malignancy, predominantly exhibits an immune evasion phenotype, making it largely unresponsive to immune checkpoint inhibitors (ICIs). Epiregulin (EREG), a member of the epidermal growth factor family, is frequently overexpressed in CRC, which has been implicated in tumor progression and therapy resistance in various cancers, but its specific role and underlying mechanisms in CRC cell and tumor microenvironment (TME) regulation remain to be elucidated.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eEREG expression levels in CRC tissues were analyzed using The Cancer Genome Atlas (TCGA) database and immunohistochemistry (IHC). Lentivirus-mediated RNA interference was employed to establish EREG knockdown CRC cell lines. The effects of EREG silencing on cell proliferation, invasion, colony formation, migration, and apoptosis were evaluated by CCK-8 assay, transwell invasion assay, colony formation assay, wound healing assay, and flow cytometry, respectively. Furthermore, mRNA sequencing (mRNA-seq), enzyme-linked immunosorbent assay (ELISA), and Western blot (WB) analyses were conducted to explore intracellular signaling pathway changes and TME modulation following EREG knockdown.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eEREG was significantly overexpressed in CRC tissues compared to adjacent normal tissues and correlated closely with intratumoral CD8\u003csup\u003e+\u003c/sup\u003eT cell infiltration. EREG knockdown significantly inhibited CRC cell proliferation, invasion, clone and migration, while promoting apoptosis. Differentially expressed genes were enriched in the IL-17A/NF-κB signaling pathway. EREG depletion suppressed IL-17A and NF-κB expression, reversible by exogenous IL-17A. Additionally, EREG knockdown increased secretion of chemokines (CCL5, CXCL1, CXCL2, CXCL3), enhancing CD8\u003csup\u003e+\u003c/sup\u003eT cell infiltration and remodeling the TME towards an immune-activated state.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eEREG promotes CRC progression by modulating the IL-17A/NF-κB pathway and maintaining an immunosuppressive TME. Targeting EREG may improve immunotherapy outcomes by transforming cold tumors into hot tumors, providing a promising strategy for CRC treatment.\u003c/p\u003e","manuscriptTitle":"EREG promotes colorectal cancer progression and immune suppressive microenvironment formation through IL-17A/NF-κB pathway","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-11 17:20:42","doi":"10.21203/rs.3.rs-7869610/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-18T07:55:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-12T07:45:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-11T11:40:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"287712090326925465987466572144634144931","date":"2025-12-11T01:46:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"298100326805109094556074155275377840537","date":"2025-12-09T04:15:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-09T01:45:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-06T08:33:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-06T07:18:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Oncology","date":"2025-11-27T17:08:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-oncology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dion","sideBox":"Learn more about [Discover Oncology](https://www.springer.com/12672)","snPcode":"","submissionUrl":"","title":"Discover Oncology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4e4565fa-9876-4037-a5e7-caf1f094be9c","owner":[],"postedDate":"December 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-16T14:38:27+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-11 17:20:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7869610","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7869610","identity":"rs-7869610","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}