The ZEB1/LAYN cascade promotes cancer cell malignant phenotypes and macrophage M2 polarization in gastric cancer

The ZEB1/LAYN cascade promotes cancer cell malignant phenotypes and macrophage M2 polarization in gastric cancer | 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 The ZEB1/LAYN cascade promotes cancer cell malignant phenotypes and macrophage M2 polarization in gastric cancer Dong Jiang, Si Niu, Yuanyuan Xie, Meng Xue, Mao zhang, Qianqian Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7027452/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background M2-polarized macrophages in the tumor microenvironment contribute to tumor development, angiogenesis, and immune suppression. Layilin (LAYN) is linked to macrophage infiltration and patient outcomes in gastric cancer (GC). Here, we characterized the role of LAYN in malignant progression and macrophage M2 polarization in GC. Methods Protein levels were assessed using immunoblotting and immunohistochemistry (IHC), and mRNA levels were detected through quantitative PCR (qPCR). The impact on GC cell functions was determined by assessing cell invasion, migration, apoptosis, proliferation, and colony formation ability. The effect on macrophage M2 polarization was evaluated by analyzing the expression of M2 markers and the percentage of CD163 + macrophages. Xenograft models were generated to determine the role in vivo . The ZEB1-LAYN relationship was confirmed by chromatin immunoprecipitation (ChIP) and luciferase assays. Results LAYN and ZEB1 were up-regulated in GC samples and cell lines. LAYN deficiency weakened cancer cell malignant phenotypes and induced their apoptosis in vitro , as well as diminished MKN-45 xenograft growth in vivo . Moreover, LAYN deficiency attenuated the migration and M2 polarization of GC-related macrophages. Mechanistically, ZEB1 transcriptionally enhanced LAYN expression. LAYN restoration enhanced malignant phenotypes in ZEB1-deficient GC cells and reduced the suppressive effects of ZEB1 depletion on the migration and M2 polarization of macrophages. Conclusion Our study demonstrates that the ZEB1/LAYN cascade contributes to the development of GC by enhancing cancer cell malignant phenotypes and macrophage M2 polarization. LAYN or ZEB1 could be a new target for GC intervention. Gastric cancer M2 polarization LAYN transcription factor ZEB1 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Gastric cancer (GC), originating from the epithelial cells of the gastric mucosa, is a formidable malignancy with a high incidence and mortality rate globally, particularly in East Asia, with China accounting for ~ 40% of all GC cases ( 1 , 2 ). Predominantly affecting individuals over 50 years of age, with a male-to-female incidence ratio of 2:1, GC often exhibits nonspecific symptoms such as upper abdominal discomfort and belching in its early stages, which are easily overlooked, leading to a low early diagnosis rate and a poor prognosis ( 3 ). Current conventional regimens include surgical resection, chemotherapy, radiation therapy, and targeted therapy, yet these treatments have shown limited efficacy, especially in advanced stages. The heterogeneity of GC poses a significant challenge, with varying responses to treatment and a propensity for recurrence and metastasis ( 4 ). The underlying mechanisms of gastric carcinogenesis are intricate, involving a complex interplay of genetic mutations, epigenetic alterations, and dysregulated signaling pathways ( 5 ). Unraveling these mechanisms could offer promising avenues for the development of innovative and more potent therapeutic strategies against GC. Macrophage M2 polarization is a critical immunological process where macrophages shift towards an anti-inflammatory and pro-healing phenotype ( 6 ). In cancer, M2-polarized macrophages, often referred to as tumor-associated macrophages, are influenced by the tumor microenvironment and exhibit a phenotype that contributes to tumor development, angiogenesis, and immune suppression ( 7 ). Specifically, in GC, M2 macrophages have been associated with poor prognosis and are involved in cancer metastasis and worse clinical outcomes ( 8 , 9 ). Despite the growing body of research, the precise mechanisms of M2 polarization in GC remain largely elusive and warrant further investigation. Layilin (LAYN), a pivotal protein in controlling T-cell function, has recently gained attention in the oncology field due to its potential role in tumorigenesis and cancer development. Aberrant expression of LAYN has been unveiled to closely associate with the prognosis and immune infiltration in pan-cancer ( 10 ). Elevated levels of LAYN have been observed in multiple types of cancer, including colorectal cancer, prostate cancer, breast cancer, head and neck squamous cell carcinoma, and bladder cancer, suggesting that LAYN may function as an oncoprotein ( 11 , 12 ). LAYN is also predicted to be related to the enhanced risk of breast cancer ( 13 ). Furthermore, in colorectal cancer, LAYN has the ability to enhance M2 macrophage polarization by targeting the NF-κB signaling ( 14 ). In GC, LAYN forebodes unfavorable patient outcomes and is positively linked to macrophage infiltration ( 11 , 15 ). Nonetheless, the specific functions of LAYN within the GC microenvironment and progression remain to be fully elucidated. Transfection factors (TFs) are crucial for regulating gene expression throughout the process of tumor development ( 16 ). Various TFs, such as HOXA10 and RUNX2, have been highlighted to contribute to gastric tumorigenesis by controlling the transcription and expression of genes involved in GC development ( 17 , 18 ). ZEB1, a key TF involved in the epithelial-mesenchymal transition and cancer metastasis, has been extensively studied in GC ( 19 , 20 ). The established promoting role of ZEB1 implies its potential as a therapeutic target in GC. Here, we used in vitro and in vivo experimental models to characterize the role of LAYN in the malignant progression and macrophage M2 polarization in GC. Furthermore, we deepened the understanding of the mechanisms underlying LAYN dysregulation in GC by identifying its regulatory TFs. Together, our findings demonstrate that the dysfunction of the ZEB1/LAYN cascade is responsible for M2 macrophage polarization and GC development. Materials and methods Bioinformatics We retrieved the transcriptomic data from plasma exosomes of GC patients using the GSE153413 dataset on the online web NCBI ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE153413 ) to observe potential regulators related to GC. To analyze the differentially expressed genes ( P =1), we utilized the limma differential analysis using the DECenter-V6 tool from the SangerBox website platform ( http://vip.sangerbox.com/ ). We utilized the Kaplan-Meier plotter web ( https://kmplot.com/analysis/ ) to clarify the relationship between LAYN or ZEB1 expression and patient outcomes in GC. The TIMER2.0 online method ( http://timer.cistrome.org/ ) was employed to observe the relationship between macrophages and GC prognosis, the association between LAYN expression and the infiltration of total macrophages and M2-like macrophages, and the correlation between LAYN expression and the levels of M2 polarization markers (CD163, CD206, CCL22, TGFB1, and IL10). The TCGA-stomach adenocarcinoma (STAD) dataset from the open-access LinkedOmics database ( https://www.linkedomics.org/login.php ) was applied to analyze the genes related to LAYN expression and the expression association between ZEB1 and LAYN. We retrieved the TFs from the JASPAR web ( https://jaspar.elixir.no/ ) and used the web to predict the binding sites for ZEB1 in the LAYN promoter region (-2000 bp-0 bp). Patient samples Patients (n = 53) were recruited in NanYang Central Hospital. They gave written informed consent to donate gastric specimens for research. We harvested their primary GC samples and corresponding non-cancerous gastric samples. Diagnosis of GC was made by two pathologists. The Ethics Committee of NanYang Central Hospital approved the study protocol for the evaluation of LAYN and ZEB1 expression in these human specimens. Cell lines and culture conditions We procured human immortalized gastric mucosal GSE-1 cells (#SNL-304, 1640) from SUNNCELL (Wuhan, China) and AGS cells (#CL-0022, gastric adenocarcinoma cell line), MKN-45 cells (#CL-0292, gastric carcinoma cell line), and human THP1 monocyte (#CL-0233) from Procell (Wuhan, China). In addition to Ham’s F-12 (Procell) for AGS culture, RPMI-1640 (Life Technologies, Bleiswijk, the Netherlands) was used for other cell lines. For cell cultivation (5% CO 2 , 37°C), 10% FBS (EuroClone, Milan, Italy) and 1% penicillin/streptomycin (Transgen, Beijing, China) was added into the medium, and 0.05 mM β-mercaptoethanol (Sigma-Aldrich, Milano, Italy) was used specially for THP1 culture. Constructs, transfection, and transduction Following the suggestions of the manufactory (Baidai, Changzhou, China), RFect Plasmid Transfection Reagent was applied for transfection with shRNA or shRNA + OE-LAYN into AGS and MKN-45 GC cells. We obtained recombinant constructs from Miaoling Biology (Wuhan, China): psh-EGFP-puro-LAYN(human) (sh-LAYN), psh-EGFP-puro-ZEB1(human) (sh-ZEB1), matched sh-NC control, and pEnCMV-EGFP-Linker-LAYN(human)-SV40-Neo (OE-LAYN). Lentivirus expressing sh-LAYN and sh-NC control virus were produced by VectorBuilder (Guangzhou, China). Following standard protocols ( 21 ), lentivirus particles were added to MKN-45 GC cells in the presence of 8 µg/mL polybrene. Post 20–24 h, the cells were subjected to puromycin selection at a concentration of 2 µg/mL for over 10 days. RNA preparation and quantitative PCR From human samples or cultured cell lines, we prepared mRNA with a BeyoMag™ RNA Kit as described by the supplier (Beyotime, Shanghai, China). The resulting mRNA (2 µg) was used for cDNA synthesis with a PrimeScript™ RT Master as per the vendor’s suggestions (TaKaRa, Dalian, China). Quantitative PCR (qPCR) was conducted on a Chromo4 System (Bio-Rad, Marnes-la-Coquette, France), employing SYBR Green reagents (TaKaRa). The relative quantification of gene expression was determined with the 2 −ΔΔCt method and normalized to β-actin. A list of the qPCR primers used can be found in Table 1 . Table 1 Primers sequences used for qPCR Name Primers for PCR (5’-3’) human LAYN Forward GCGTGGTCATGTACCATCAG Reverse AGGTGTTGTCAGCTCTGTTTC Human β-actin Forward CTTCGCGGGCGACGAT Reverse CCACATAGGAATCCTTCTGACC Mus musculus CD206(MRC1) Forward CTCTGTTCAGCTATTGGACGC Reverse CGGAATTTCTGGGATTCAGCTTC Mus musculus CCL22 Forward AGGTCCCTATGGTGCCAATGT Reverse CGGCAGGATTTTGAGGTCCA Mus musculus IL-10 Forward GCTCTTACTGACTGGCATGAG Reverse CGCAGCTCTAGGAGCATGTG Mus musculus TGFβ Forward CTCCCGTGGCTTCTAGTGC Reverse GCCTTAGTTTGGACAGGATCTG Mus musculus β-actin Forward TGAGCTGCGTTTTACACCCT Reverse TTTGGGGGATGTTTGCTCCA Antibodies and immunoblotting We employed a Total Protein Isolation Kit from Abcam (Cambridge, UK) to prepare protein extracts from human samples or cultured cell lines. Following quantification by BCA Protein Assay (Thermo Fisher Scientific, Milan, Italy), 30 µg of protein was subjected to SDS/PAGE, followed by electro-blotting to PVDF membranes (Millipore, Molsheim, France). After blocking with 5% BSA in TBST, probing was done (overnight; 4°C) using a desired antibody: anti-LAYN (#20535-1-AP, Proteintech, Wuhan, China, 1:6,000), anti-ZEB1 (#21544-1-AP, Proteintech, 1:1,500), or anti-β-actin (#20536-1-AP, Proteintech, 1:8,000). Following secondary antibody incubation, a chemiluminescent kit was applied for signal development as recommended by the producer (Nakarai Tesque, Tokyo, Japan). Cell colony formation and proliferation assays For colony growth analysis, we seeded AGS and MKN-45 cells at 48 h post-transfection in 6-well culture plates (Corning, Shanghai, China). Following this, colonies were grown for 10–14 days under standard conditions. After staining with crystal violet (0.5%), we quantified the number of generated colonies using ImageJ (NIH, Bethesda, MD, USA). For the EdU incorporation assay, we utilized a Click-iT EdU-594 Assay Kit as per the supplier’s instructions (Servicebio, Wuhan, China). Briefly, AGS and MKN-45 cells at 48 h post-transfection were treated with 10 µM EdU working reagent, fixed, and subjected to permeation. After staining with iF594 (red fluorescence) and DAPI (blue fluorescence), we quantified the ratio of EdU + cells with a TCS SP5 microscope (Leica, Wetzlar, Germany). The conditioned medium (CM) and co-culture system For co-culture systems, we collected the culture supernatant (called CM) from AGS and MKN-45 cells after 48 h transfection with sh-NC, sh-LAYN, sh-ZEB1, or sh-ZEB1 + OE-LAYN. Prior to co-culture, THP1 cells were stimulated with 100 ng/mL of PMA (Sigma-Aldrich) for 24 h to induce differentiation into macrophages (THP1-M0). THP1-M0 macrophages were characterized by microscopic detection and CD11b expression evaluation. Co-culture systems were set up by placing THP1-M0 macrophages, suspended in 10% FBS RPMI-1640, into 24-Tranwell inserts (Corning), and the bottom compartment was added with the collected CM. The co-culture was performed for 36–48 h, and co-cultured THP1-M0 cells were harvested and subjected to mRNA expression analysis, migration assay, and flow cytometry. Transwell cell migration and invasion assays Transwell assays were used to assess migratory and invasive capacities of AGS and MKN-45 cells at 24 h post-transfection as well as the migratory potential of co-cultured THP1-M0 cells with Matrigel-coated or uncoated 24-Tranwell inserts (Corning). In brief, we seeded cells, suspended in non-serum media, into inserts and allowed them to migrate or invade towards the lower compartment containing 15% FBS medium. After a 24-h incubation, the number of migratory or invasive cells was determined by staining with 0.1% crystal violet and subsequent counting under the BX53 microscope (Olympus, Tokyo, Japan). Flow cytometry The cytomics FC500 (Beckman Coulter, Krefeld, Germany) was used for flow cytometry assay. For apoptosis evaluation, we stained AGS and MKN-45 cells at 72 h post-transfection with FITC-Annexin V and propidium iodide under the application of a Commercial Staining Kit (Beyotime). For cell percentage assessment, THP1 and THP1-M0 cells were stained with an anti-CD11b antibody conjugated with FITC (#982614, Biolegend, San Diego, CA, USA), and co-cultured THP1-M0 cells were stained with an anti-CD163 antibody labeled with PE/Cyanine7 (#156707, Biolegend). The 7AAD Staining Solution (#420404, Biolegend) was also used for dead cell elimination. Xenograft models and immunohistochemistry (IHC) For the production of xenograft models, we utilized BALB/c nude mice from Vital River Laboratory (Beijing, China) and grouped them into two groups: sh-NC (n = 5) and sh-LAYN (n = 5). All experimental procedures were performed using 6-week-old female mice, conducted following the national guidelines, and were approved by the Animal Care and Use Committee of NanYang Central Hospital. Stable LAYN-depleted MKN-45 GC cells were established before subcutaneous inoculation in the right flank (2 × 10 6 cells/mouse in 150 µL of PBS). Tumor diameters were gauged weekly at right angles (d short and d long ), and tumor growth monitor was done by determining their volumes using the formula: (d short ) 2 × (d long ) × 0.5. Studies were terminated after 35 days of cell implantation, and xenografts were collected. In accordance with the established methods ( 22 ), IHC detection for LAYN and Ki-67 was performed on 4-µm-thick sections of formalin-fixed, paraffin-embedded xenografts. The sections were probed with anti-LAYN (#20535-1-AP, Proteintech, 1:600) or anti-Ki-67 (#27309-1-AP, Proteintech, 1:8,000) antibody. Chromatin immunoprecipitation (ChIP) assay Under the application of a ChIP Assay Kit and the accompanying suggestions (Beyotime), we performed ChIP experiments using an anti-ZEB1 antibody (#21544-1-AP, Proteintech) or anti-IgG Isotype control (#ab172730, Abcam). Chromatin DNA of AGS and MKN-45 GC cells were subjected to ultrasonication. A bead-antibody complex was formed by mixing the specific antibody with Protein A/G Agarose. The resultant DNA fragments were incubated with the bead-antibody complex overnight at 4°C. We extracted DNA from the precipitates and conducted qPCR to assess the enrichment amount of LAYN promoter segments using designed primers (Primer1 and Primer2). Luciferase assay We carried out these assays in human 293T cells (#CL-0005), which were obtained from Procell and cultivated using Procell-developed standard media. LAYN reporter constructs were made by subcloning the LAYN promoter fragments harboring both predicted BS1 and BS2 sites (WT), mutated BS1 and wild-type BS2 (BS1-MUT), wild-type BS1 and mutated BS2 (BS2-MUT), or mutated BS1 and mutated BS2 (BS1 + BS2-MUT) into the pGL3 basic vector (Life Technologies). Using RFect Plasmid Transfection Reagent, we transfected each reporter plasmid and sh-NC or sh-ZEB1 along with pRL-TK Renilla vector into 293T cells. Forty-eight hours post-transfection, cell lysates were analyzed for luciferase activity, with measurements of firefly and Renilla obtained using a TriStar S LB 942 plate reader from Berthold (Bad Wildbad, Germany). Statistical analysis For analyzing differences between two groups, we employed the Mann-Whitney U test or an unpaired t -test, while ANOVA was utilized for comparisons involving three or more groups, accompanied by Tukey’s or Sidak’s post-hoc tests as appropriate. Data were expressed as the mean ± standard deviation, and significance was set at a p -value less than 0.05. We utilized Pearson’s correlation coefficients to analyze the ZEB1/LAYN expression association in human GC samples. Results Bioinformatics and expression analyses identify the up-regulation of LAYN in human GC To identify potential regulators related to GC pathogenesis, we performed a bioinformatic analysis using the transcriptomic data from plasma exosomes of GC patients available from the NCBI-GSE153413 dataset. Using the limma differential analysis on the SangerBox-DECenter-V6 tool, we noted that there were a lot of up-regulated and down-regulated genes ( P =1) in GC plasma exosomes versus normal controls, as shown in volcano plot (Fig. 1 a). Heat map revealed the top five significantly up-regulated genes and down-regulated genes in GC plasma exosomes (Fig. 1 b). Among these, we focused on LAYN in this study as it was the most significantly up-regulated factor in GC plasma exosomes relative to normal counterparts (Fig. 1 b). We then clarified the relationship between LAYN expression and patient outcomes in GC. Utilizing the Kaplan-Meier plotter web, we confirmed that GC patients with LAYN expression above the median had remarkably worse overall survival (OS), first progression (FP), and post progression survival (PPS) compared with those with LAYN expression below the median (Fig. 1 c). To confirm the up-regulation of LAYN in GC, we determined the expression of LAYN in a cohort of 53 patients with GC. Consistently, primary GC samples displayed increased levels of LAYN mRNA than matched non-tumor gastric tissues (Fig. 1 d). Furthermore, elevated levels of LAYN protein were observed in primary GC samples and GC cell lines (AGS and MKN-45) compared to their counterparts (Fig. 1 e and 1 f). LAYN deficiency reduces cell malignant phenotypes and induces apoptosis in vitro Although LAYN has been shown to correlate with the prognosis of GC patients ( 11 , 15 ), no studies proved its precise function in GC development. Herein, we wanted to address the role of LAYN in gastric carcinogenesis. AGS and MKN-45 GC cells were introduced with a shRNA targeting LAYN (sh-LAYN), and their LAYN expression was evaluated by immunoblot assay. Transfection of cells with sh-LAYN resulted in decreased protein levels of LAYN compared with sh-NC cells (Fig. 2 a). Notably, the significant reduction in the number of colonies obtained with LAYN deficiency was validated by colony formation assay (Fig. 2 b). Depletion of LAYN also strongly decreased the ratio of EdU-positive cells in AGS and MKN-45 cells (Fig. 2 c). Conversely, LAYN knockdown remarkably enhanced cell apoptosis rate (Fig. 2 d). In addition, AGS and MKN-45 cells with LAYN deficiency exhibited suppressed migratory and invasive capacities compared with sh-NC-transfected cells (Fig. 2 e and 2 f). These data together establish LAYN as a crucial player in facilitating GC malignant progression. Deficiency of LAYN attenuates the migration and M2 polarization of GC-related macrophages The polarization towards the M2 phenotype and recruitment of macrophages are pivotal in exerting pronounced pro-tumorigenic effects within the realm of cancer biology ( 7 ). To verify this notion, we employed the TIMER2.0 online method to observe the relationship of macrophages with GC prognosis. Intriguingly, we found that patients with high macrophages and high M2-like macrophages had significantly worse survival rates (Fig. 3 a). The TIMER2.0 algorithm also predicted the positive association between LAYN expression and the infiltration of total macrophages and M2-like macrophages (Fig. 3 b). Moreover, LAYN expression was predicted by the TIMER2.0 algorithm to positively correlate with the levels of M2 polarization markers (CD163, CD206, CCL22, TGFB1, and IL10) (Fig. 3 c). These results suggest the association of LAYN expression with macrophage M2 polarization in GC. To confirm this possibility, we incubated THP1-differentiated macrophages induced by PMA (THP1-M0) with the conditioned medium (CM) from sh-LAYN- or sh-NC-transfected AGS (AGS sh−LAYN CM or AGS sh−NC CM) and MKN-45 cells (MKN-45 sh − LAYN CM or MKN-45 sh − NC CM), as illustrated in Fig. 4 a. The microscopic morphology of THP1 and THP1-M0 was shown in Fig. 4 b. In comparison to THP1 cells, THP1-M0 cells exhibited adherent growth characteristics, with an increase in cell size and irregularly shaped edges (Fig. 4 b). Flow cytometry results revealed that THP1-M0 had higher levels of macrophage marker CD11b (Fig. 4 c), demonstrating the successful differentiation of THP1 into macrophages. Using qPCR assay, we observed decreased transcript levels of M2 polarization markers CD206, CCL22, and IL-10 in THP1-M0 incubated with AGS sh−LAYN CM or MKN-45 sh − NC CM (Fig. 4 d and 4 e). The expression of TGF-β mRNA was significantly decreased in THP1-M0 incubated with MKN-45 sh − NC CM (Fig. 4 e). Furthermore, flow cytometry data showed that LAYN depletion significantly decreased the percentage of CD163 + macrophages (Fig. 4 f and 4 g), indicating that LAYN depletion weakens macrophage M2 polarization. We then investigated the impact of LAYN silencing on the migration of THP1-M0. Deficiency of LAYN in AGS and MKN-45 GC cells resulted in reduced migration ability of THP1-M0 (Fig. 4 h and 4 i). Collectively, our findings suggest that LAYN plays a role in enhancing the M2 polarization and recruitment of macrophages in GC. LAYN deficiency diminishes tumor growth in vivo We next evaluated the feasibility of LAYN depletion as a therapeutic approach for GC by establishing in vivo sh-LAYN or sh-NC xenograft models. Sh-LAYN-transduced MKN-45 cells exhibited significantly slower growth (Fig. 5 a) and produced smaller tumors (Fig. 5 b and 5 c) compared to the same cells transduced with sh-NC lentivirus. IHC assay confirmed decreased levels of LAYN in sh-LAYN subcutaneous xenografts compared with sh-NC controls (Fig. 5 d). Moreover, LAYN-depleted xenografts displayed reduced levels of Ki-67 staining by IHC (Fig. 5 d), confirming that LAYN depletion diminishes the growth of MKN-45 xenografts. Interestingly, the deficiency of LAYN led to a striking down-regulation in the expression of CD206, CCL22, IL-10, and TGF-β transcripts in formed xenografts (Fig. 5 e), implying the influence of LAYN knockdown in macrophage M2 polarization. ZEB1 is significantly overexpressed in GC and transcriptionally enhances LAYN expression To gain a deeper understanding of the mechanisms underlying the up-regulation of LAYN in GC, we focused on its regulatory transcription factors (TFs), as TFs play an essential role in gene expression during the tumorigenesis process ( 16 ). We first used the open-access LinkedOmics database to analyze the genes related to LAYN based on the TCGA-stomach adenocarcinoma (STAD) dataset. As shown in Fig. 6 a, volcano plot showed the LAYN-associated genes in STAD samples. The top 50 significantly positively associated genes of LAYN in the TCGA-STAD dataset were revealed by heat map in Fig. 6 b. When we combined the 1712 positively associated genes of LAYN (with the criteria of Pearson’s correlation coefficient > 0.5 and P < 0.05) in the TCGA-STAD dataset from the LinkedOmics database (Supplementary Table 1), the 888 TFs on the JASPAR web, and the 299 up-regulated genes in plasma exosomes of GC patients from the GSE153413 dataset (Supplementary Table 2), we found a total of three candidates (ZEB1, MEIS1, and FLI1) (Fig. 6 c). Among these, the TF ZEB1 caught our attention due to its established crucial role in driving GC progression ( 19 , 20 ). Utilizing the LinkedOmics database, we observed a significant and positive expression association between ZEB1 and LAYN in the TCGA-STAD dataset (Fig. 6 d). The Kaplan-Meier plotter online web also revealed that GC patients with ZEB1 expression above the median exhibited significantly worse OS, FP, and PPS compared with those with LAYN expression below the median (Fig. 6 e). Through qPCR assay, we also confirmed the elevated expression of LAYN transcript in primary GC specimens compared with normal gastric tissues (Fig. 6 f). Notably, we also confirmed the significantly positive expression association of LAYN with ZEB1 in primary GC specimens (Fig. 6 g). By contrast, the striking increase in ZEB1 protein expression was validated by immunoblot in primary GC specimens and AGS and MKN-45 GC cells (Fig. 6 h and 6 i). Having unveiled the positive association between LAYN and ZEB1 in GC, we sought to investigate the regulation of ZEB1 in LAYN transcription and expression. As expected, reduced expression of ZEB1 by sh-ZEB1 transfection, verified by immunoblot (Fig. 7 a), caused a significant down-regulation in LAYN expression at both protein and mRNA levels in AGS and MKN-45 cells (Fig. 7 b and 7 c), indicating that ZEB1 positively modulates LAYN expression. The JASPAR tool predicted multiple binding sites for ZEB1 in the LAYN promoter region (-2000 bp-0 bp), and the top 5 sites (BS1, BS2, BS3, BS4, and BS5) based on the score were shown in Fig. 7 d. In order to preliminarily determine the binding site of ZEB1 and the LAYN promoter, we performed ChIP-qPCR assay using a specific anti-ZEB1 antibody and designed primers (Primer1 and Primer2) targeting two regions of the LAYN promoter (Fig. 7 d). Intriguingly, we confirmed that the promoter segments of LAYN encompassing the BS1 and BS2 sites were strongly enriched in the ZEB1-associating precipitates using the Primer1 (Fig. 7 e), suggesting that ZEB1 may bind to the LAYN promoter through site BS1, site BS2, or both sites. However, in AGS and MKN-45 cells, no correlation was observed between ZEB1 and the LAYN promoter segments harboring the BS3, BS4, and BS5 sites (Fig. 7 f). Luciferase assays were then performed in 293T cells by generating LAYN reporter constructs, which included the LAYN promoter fragments harboring both BS1 and BS2 sites (WT), mutated BS1 and wild-type BS2 (BS1-MUT), wild-type BS1 and mutated BS2 (BS2-MUT), or mutated BS1 and mutated BS2 (BS1 + BS2-MUT). Transfection of WT reporter led to diminished luciferase activity in the presence of sh-ZEB1 in 293T cells (Fig. 7 g). Importantly, mutation of the BS1 site alone (BS1-MUT) and mutation in both BS1 and BS2 sites (BS1 + BS2-MUT), but not mutation in the BS2 site alone (BS2-MUT), completely abrogated the suppressive effect of ZEB1 depletion (Fig. 7 g). Taken together, these data demonstrate that ZEB1 transcriptionally increases LAYN expression by binding to the BS1 site within the LAYN promoter. LAYN restoration enhances malignant phenotypes in ZEB1-deficient GC cells and reduces the suppressive effects of ZEB1 depletion on migration and M2 polarization of macrophages Finally, we explored whether ZEB1 contributes to gastric tumorigenesis through LAYN. A LAYN ORF plasmid (OE-LAYN) was used to elevate LAYN protein expression in ZEB1-deficient AGS and MKN-45 GC cells (Fig. 8 a). Remarkably, ZEB1 silencing resulted in a repression in cell growth (Fig. 8 b and 8 c) and a promotion in cell apoptosis (Fig. 8 d), and these alterations were partially abolished by LAYN expression increase (Fig. 8 b- 8 d). Moreover, ZEB1 knockdown-triggered migration and invasion defects were rescued by restored expression of LAYN (Fig. 8 e and 8 f). When we incubated THP1-M0 with the CM from sh-ZEB1- or sh-NC-transfected AGS (AGS sh−ZEB1 CM or AGS sh−NC CM) and MKN-45 cells (MKN-45 sh − ZEB1 CM or MKN-45 sh − NC CM), we found that the mRNA levels of M2 polarization markers CD206, CCL22, IL-10, and TGF-β were decreased (Fig. 9 a and 9 b), and the percentage of CD163 + macrophages was declined (Fig. 9 c and 9 d), indicating that ZEB1 knockdown diminishes macrophage M2 polarization. We also incubated THP1-M0 with the CM from sh-ZEB1 + OE-LAYN-transfected cells (AGS sh−ZEB1+OE−LAYN CM or MKN-45 sh − ZEB1+OE−LAYN CM). Notably, ZEB1 knockdown-driven M2 polarization suppression was partially reversed by LAYN expression restoration (Fig. 9 a- 9 d). In addition, depletion of ZEB1 resulted in reduced migration ability of THP1-M0, which could be rescued by LAYN restoration (Fig. 9 e and 9 f). Thus, ZEB1 affects GC development by regulating cancer cell malignant phenotypes and macrophage M2 polarization by partially through LAYN. Discussion GC remains a formidable global health challenge, characterized by a complex interplay of multiple carcinogenic molecules ( 23 , 24 ). These regulators, including protein molecules, contribute to the intricate molecular landscape of the disease and GC progression ( 25 , 26 ). By understanding the action of these regulators, we can envision a future where targeted therapies are tailored to disrupt these carcinogenic pathways, potentially revolutionizing treatment strategies and improving patient outcomes. Our research has uncovered a significant role for LAYN in the immunological regulation and malignant progression of GC. Interestingly, we have shed light on a novel mechanism in driving the up-regulation of LAYN in GC. Thus, inhibiting LAYN could potentially serve as a therapeutic way in the fight against GC, opening up possibilities for the design and development of novel anti-cancer drugs tailored specifically for GC patients. LAYN has emerged as a significant player in the oncological landscape, with its role in tumor immune infiltration and cancer progression being increasingly recognized ( 10 ). For example, LAYN works as a strong driver in colorectal cancer by accelerating cancer metastasis and macrophage M2 polarization ( 14 ). LAYN negatively modulates the immune activity of CD8 + T cells in hepatocellular carcinoma, and LAYN + CD8 + T lymphocytes exhibit reduced cytotoxic activity ( 27 ). Additionally, down-regulation of LAYN in CD8 + T lymphocytes is responsible for the anti-cancer efficacy of anti-VEGFR2 therapy in lung adenocarcinoma ( 28 ). Emerging evidence also highlights the overexpression of LAYN in GC, which correlates with immune infiltration and patient outcomes ( 11 , 15 ). Our research has delved deeper into the role of LAYN in GC, revealing that LAYN deficiency weakens cancer cell malignant phenotypes and induces their apoptosis in vitro , as well as diminishes GC xenograft growth in vivo . The polarization towards the M2 phenotype of macrophages plays a key role in facilitating GC development ( 8 , 9 ). Importantly, our study also demonstrates that deficiency of LAYN reduces the migration and M2 polarization of GC-related macrophages. These discoveries not only clarify LAYN’s specific functions in GC but also unveil a previously uncharacterized molecular basis driving the disease’s progression, underscoring the potential of LAYN as a target for novel therapies against GC. ZEB1, a vital TF, is known for its role in promoting epithelial-mesenchymal transition and is frequently implicated in tumorigenesis and tumor progression ( 29 ). In various cancers, ZEB1 has been shown to modulate gene expression patterns that favor invasion and metastasis. For instance, ZEB1 has established a promoting role in hepatocellular carcinoma by enhancing the transcription of phosphofructokinase-1 ( 30 ). ZEB1 affects the progression of neuroendocrine prostate cancer by transcriptionally controlling the levels of crucial glycolytic factors ( 31 ). Furthermore, studies in ZEB1 have suggested its implication in cancer macrophage polarization and immune evasion ( 32 , 33 ). Depletion of ZEB1 is also reported to sensitize cancer cells to immune checkpoint inhibition therapy in colorectal cancer ( 34 ). In GC, the role of ZEB1 is particularly intriguing, with evidence implicating its contribution to increased tumor aggressiveness and poor patient outcomes ( 19 , 20 , 35 ). In line with earlier documents ( 19 , 36 ), our data confirm the up-regulation of ZEB1 in GC. Importantly, we demonstrate, for the first time, that ZEB1 transcriptionally elevates LAYN expression in GC cells by binding to the LAYN promoter. Our rescue experiments unveil that restoration of LAYN in ZEB1-deficient GC cells not only enhances their malignant phenotypes but also counteracts the inhibitory effects of ZEB1 depletion on the migration and M2 polarization of macrophages, suggesting a mechanistic link between ZEB1 and LAYN in the modulation of GC biology. Therefore, ZEB1 exerts its oncogenic function in GC, in part, by up-regulating LAYN, revealing a new epigenetic regulatory cascade that promotes GC development. Nevertheless, there is a dearth of in vivo studies examining this molecular cascade, necessitating additional investigative efforts. This study broadens the mechanisms underlying gastric carcinogenesis by providing novel cause data that the ZEB1/LAYN cascade contributes to the development of GC. Through this study, we envision that LAYN or ZEB1 serves as a new promising target for GC intervention.However, our study also has certain limitations. Whether exosomal ZEB1 affects GC cell migration and promotes macrophage M2 polarization through LAYN remains unclear and merits further exploration. Abbreviations GC：Gastric Cancer;EMT: Epithelial-Mesenchymal Transition;TME:Tumor Microenvironment; TAM:Tumor-Associated Macrophage;ZEB1: Zinc finger E-box binding homeobox 1;LAYN: Layilin;ZEB1-AS1:ZEB1 Antisense RNA 1;PAK2 P21-Activated Kinase 2;HTR2B；5-Hydroxytryptamine Receptor 2B；CREB1：CAMP Responsive Element Binding Protein 1；LOXL2 Lysyl Oxidase Like 2 Declarations Ethical Approval and Consent to Participate This study was approved by the NanYang Central Hospital(Approval No.2021625). All participants provided written informed consent, and the research was conducted in accordance with the Declaration of Helsinki. Consent for Publication All participants provided consent for publication. Written permissions were obtained for using identifiable images. Availability of data and materials Data are available from authors upon reasonable request due to restrictions. Competing Interests The authors declare no competing interests. Funding The present study was supported by the Nanyang Science and Technology Bureau (No.252102310269). Authors' Contributions DJ were responsible for designing the study.DJ ,SN and YX performing experiments. DJ and MX writing and revising the manuscript.DJ,MZ and Ql performing the statistical analysis. Acknowledgements This study obtained substantial support from the laboratory members. References López MJ, Carbajal J, Alfaro AL, et al. Characteristics of gastric cancer around the world. Crit Rev Oncol Hematol. 2023;181:103841. Wang Z, Han W, Xue F, et al. Nationwide gastric cancer prevention in China, 2021–2035: a decision analysis on effect, affordability and cost-effectiveness optimisation. Gut. 2022;71:2391–400. Yang WJ, Zhao HP, Yu Y, et al. Updates on global epidemiology, risk and prognostic factors of gastric cancer. World J Gastroenterol. 2023;29:2452–68. Guan WL, He Y, Xu RH. Gastric cancer treatment: recent progress and future perspectives. J Hematol Oncol. 2023;16:57. Machlowska J, Baj J, Sitarz M et al. Gastric Cancer: Epidemiology, Risk Factors, Classification, Genomic Characteristics and Treatment Strategies. Int J Mol Sci 2020; 21. Shapouri-Moghaddam A, Mohammadian S, Vazini H, et al. Macrophage plasticity, polarization, and function in health and disease. J Cell Physiol. 2018;233:6425–40. Boutilier AJ, Elsawa SF. Macrophage Polarization States in the Tumor Microenvironment. Int J Mol Sci 2021; 22. Zhang G, Gao Z, Guo X et al. CAP2 promotes gastric cancer metastasis by mediating the interaction between tumor cells and tumor-associated macrophages. J Clin Invest 2023; 133. Deng C, Huo M, Chu H, et al. Exosome circATP8A1 induces macrophage M2 polarization by regulating the miR-1-3p/STAT6 axis to promote gastric cancer progression. Mol Cancer. 2024;23:49. Jiawen W, Jinfu W, Jianyong L, et al. Comprehensive landscape of the miRNA-regulated prognostic marker LAYN with immune infiltration and stemness in pan-cancer. J Cancer Res Clin Oncol. 2023;149:10989–1011. Pan JH, Zhou H, Cooper L, et al. LAYN Is a Prognostic Biomarker and Correlated With Immune Infiltrates in Gastric and Colon Cancers. Front Immunol. 2019;10:6. Chen Q, Chen J, Lu Z, et al. The prognostic value of LAYN in HPV-related head and neck squamous cell carcinoma and its influence on immune cell infiltration. Discov Oncol. 2024;15:57. Mälarstig A, Grassmann F, Dahl L, et al. Evaluation of circulating plasma proteins in breast cancer using Mendelian randomisation. Nat Commun. 2023;14:7680. Yang Y, Chen Z, Chu X, et al. Targeting LAYN inhibits colorectal cancer metastasis and tumor-associated macrophage infiltration induced by hyaluronan oligosaccharides. Matrix Biol. 2023;117:15–30. Zhao Q, Zhao R, Song C, et al. Increased IGFBP7 Expression Correlates with Poor Prognosis and Immune Infiltration in Gastric Cancer. J Cancer. 2021;12:1343–55. Kant R, Manne RK, Anas M, et al. Deregulated transcription factors in cancer cell metabolisms and reprogramming. Semin Cancer Biol. 2022;86:1158–74. Song C, Zhou C. HOXA10 mediates epithelial-mesenchymal transition to promote gastric cancer metastasis partly via modulation of TGFB2/Smad/METTL3 signaling axis. J Exp Clin Cancer Res. 2021;40:62. Guo Z, Zhou K, Wang Q, et al. The transcription factor RUNX2 fuels YAP1 signaling and gastric cancer tumorigenesis. Cancer Sci. 2021;112:3533–44. Liu YJ, Zeng SH, Zhang W, et al. USP51/ZEB1/ACTA2 axis promotes mesenchymal phenotype in gastric cancer and is associated with low cohesion characteristics. Pharmacol Res. 2023;188:106644. Lu J, Li D, Jiang H, et al. The aryl sulfonamide indisulam inhibits gastric cancer cell migration by promoting the ubiquitination and degradation of the transcription factor ZEB1. J Biol Chem. 2023;299:103025. Liu C, Kelnar K, Liu B, et al. The microRNA miR-34a inhibits prostate cancer stem cells and metastasis by directly repressing CD44. Nat Med. 2011;17:211–5. Hu Z, Chen G, Zhao Y, et al. Exosome-derived circCCAR1 promotes CD8 + T-cell dysfunction and anti-PD1 resistance in hepatocellular carcinoma. Mol Cancer. 2023;22:55. Röcken C. Predictive biomarkers in gastric cancer. J Cancer Res Clin Oncol. 2023;149:467–81. Li J, Turner DC, Li F, et al. Pharmacokinetics of biologics in gastric cancer. Clin Transl Sci. 2023;16:564–74. Bolandi N, Derakhshani A, Hemmat N et al. The Positive and Negative Immunoregulatory Role of B7 Family: Promising Novel Targets in Gastric Cancer Treatment. Int J Mol Sci 2021; 22. Li W, Chen Y, Sun X, et al. Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival. Biol Res. 2019;52:42. Xiao S, Lu L, Lin Z, et al. LAYN Serves as a Prognostic Biomarker and Downregulates Tumor-Infiltrating CD8(+) T Cell Function in Hepatocellular Carcinoma. J Hepatocell Carcinoma. 2024;11:1031–48. Yang B, Deng B, Jiao XD, et al. Low-dose anti-VEGFR2 therapy promotes anti-tumor immunity in lung adenocarcinoma by down-regulating the expression of layilin on tumor-infiltrating CD8(+)T cells. Cell Oncol (Dordr). 2022;45:1297–309. Cheng L, Zhou MY, Gu YJ, et al. ZEB1: New advances in fibrosis and cancer. Mol Cell Biochem. 2021;476:1643–50. Zhou Y, Lin F, Wan T et al. ZEB1 enhances Warburg effect to facilitate tumorigenesis and metastasis of HCC by transcriptionally activating PFKM. Theranostics. 2021; 11: 5926–5938. Wang D, Du G, Chen X, et al. Zeb1-controlled metabolic plasticity enables remodeling of chromatin accessibility in the development of neuroendocrine prostate cancer. Cell Death Differ. 2024;31:779–91. Jiang H, Wei H, Wang H, et al. Zeb1-induced metabolic reprogramming of glycolysis is essential for macrophage polarization in breast cancer. Cell Death Dis. 2022;13:206. Chen XJ, Guo CH, Wang ZC, et al. Hypoxia-induced ZEB1 promotes cervical cancer immune evasion by strengthening the CD47-SIRPα axis. Cell Commun Signal. 2024;22:15. Menche C, Schuhwerk H, Armstark I, et al. ZEB1-mediated fibroblast polarization controls inflammation and sensitivity to immunotherapy in colorectal cancer. EMBO Rep. 2024;25:3406–31. Romero S, Musleh M, Bustamante M, et al. Polymorphisms in TWIST1 and ZEB1 Are Associated with Prognosis of Gastric Cancer Patients. Anticancer Res. 2018;38:3871–7. Gao ZY, Liu H, Zhang Z. miR-144-3p increases radiosensibility of gastric cancer cells by targeting inhibition of ZEB1. Clin Transl Oncol. 2021;23:491–500. Supplementary Material Supplementary Tables 1 and 2 are not available with this version. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7027452","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":497397938,"identity":"9ca9e45f-aa9e-454c-935b-c49d69b3f9a5","order_by":0,"name":"Dong Jiang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtUlEQVRIiWNgGAWjYBAC9vmNzY9/VNjIsbG3HyBOC+OMw8eMGc6kGfPxnEkgVktagjRj2+HEeRIOBsRqyTEwLjhzOL1NgiGB4UfFNuK0PJ5RkZ7bJt14gLHnzG3itBjwnLHObZM5kMDM2EakFgneNuZ0NokEA+K0CIK8z9vmnEC8FmmJw8cMZ5xJM2wDBvJBovzCJ9/Y/OBDhY28fHv7wQc/KojQggIOkKh+FIyCUTAKRgEuAAAdYD9+m5Wq/gAAAABJRU5ErkJggg==","orcid":"","institution":"NanYang Central Hospital","correspondingAuthor":true,"prefix":"","firstName":"Dong","middleName":"","lastName":"Jiang","suffix":""},{"id":497397939,"identity":"2a630cba-06da-4eb8-85d8-2f5da8f1259f","order_by":1,"name":"Si Niu","email":"","orcid":"","institution":"NanYang Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Si","middleName":"","lastName":"Niu","suffix":""},{"id":497397940,"identity":"2f1847e3-576a-4693-bff0-863a1d7602da","order_by":2,"name":"Yuanyuan Xie","email":"","orcid":"","institution":"NanYang Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuanyuan","middleName":"","lastName":"Xie","suffix":""},{"id":497397941,"identity":"30d22222-0a89-42f0-8936-683ea0812ac5","order_by":3,"name":"Meng Xue","email":"","orcid":"","institution":"NanYang Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Meng","middleName":"","lastName":"Xue","suffix":""},{"id":497397942,"identity":"eb896c11-9f53-4aa8-bb98-8f2933012c32","order_by":4,"name":"Mao zhang","email":"","orcid":"","institution":"NanYang Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mao","middleName":"","lastName":"zhang","suffix":""},{"id":497397943,"identity":"3dc1a06c-4f94-4d6f-a200-a5ba2df79769","order_by":5,"name":"Qianqian Li","email":"","orcid":"","institution":"NanYang Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qianqian","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-07-02 09:08:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7027452/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7027452/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88774313,"identity":"3f53130b-d8ff-4e46-ab9c-3a29fcf3abd1","added_by":"auto","created_at":"2025-08-11 10:00:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":354018,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLAYN is overexpressed in human GC.\u003c/strong\u003e (a and b) The transcriptomic data from plasma exosomes of GC patients were retrieved from the NCBI-GSE153413 dataset. The limma differential analysis and volcano plot showed a lot of up-regulated and down-regulated genes (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, Log2|FoldChange|\u0026gt;=1) in GC plasma exosomes versus normal controls (a), and heat map revealed the top five significantly up-regulated genes and down-regulated genes (b). (c) The Kaplan-Meier plotter web analyzed the relationship between LAYN expression and patient overall survival (OS), first progression (FP), and post progression survival (PPS). (d) qPCR assay of LAYN mRNA in primary GC samples (n=53) and matched non-tumor gastric tissues (n=53) from the same patients. (e) Immunoblot assay of LAYN protein in primary GC samples (n=3) and matched non-tumor gastric tissues (n=3). (f) Immunoblot assay of LAYN protein in AGS and MKN-45 GC cells and non-tumor GSE-1 cells. **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01, ***\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"OnlineFig1.png","url":"https://assets-eu.researchsquare.com/files/rs-7027452/v1/36800500ba151db3865bb75b.png"},{"id":88774314,"identity":"604650fa-f668-4a66-86f5-422c6cdae41d","added_by":"auto","created_at":"2025-08-11 10:00:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":963117,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLAYN deficiency leads to \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vitro\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e suppressed cell malignant phenotypes and enhanced apoptosis.\u003c/strong\u003e (a) Immunoblot assay of LAYN protein in AGS and MKN-45 GC cells transfected with sh-LAYN or sh-NC. (b) Colony formation assay with cells transfected with sh-LAYN or sh-NC. (c) EdU cell proliferation assay with sh-LAYN- or sh-NC-transfected cells. Scale bar: 50 µm. (d) Cell apoptosis assay by flow cytometry with sh-LAYN- or sh-NC-transfected cells. (e and f) Transwell migration and invasion assays with sh-LAYN- or sh-NC-transfected cells. Scale bars: 50 µm. **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01, ***\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"OnlineFig2.png","url":"https://assets-eu.researchsquare.com/files/rs-7027452/v1/2007bae698eb3b7808c06984.png"},{"id":88774316,"identity":"b3c1a2d9-bc44-4e01-abd1-411dac9577a2","added_by":"auto","created_at":"2025-08-11 10:00:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":321295,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePotential association of LAYN expression with macrophage M2 polarization.\u003c/strong\u003e (a) Relationship of macrophages and M2-like macrophages with GC prognosis predicted by the TIMER2.0 online method. (b) Association between LAYN expression and the infiltration of total macrophages and M2-like macrophages predicted by the TIMER2.0 online method. (c) Association between LAYN expression and M2 polarization markers (CD163, CD206, CCL22, TGFB1, and IL10) predicted by the TIMER2.0 online method.\u003c/p\u003e","description":"","filename":"OnlineFig3.png","url":"https://assets-eu.researchsquare.com/files/rs-7027452/v1/6ac467b221f1b7fd2d9b60aa.png"},{"id":88776783,"identity":"005f31b6-e266-4cb0-909d-a1350d95b279","added_by":"auto","created_at":"2025-08-11 10:08:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1089632,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLAYN deficiency attenuates the migration and M2 polarization of GC-related macrophages.\u003c/strong\u003e (a) Schematic of the incubation system of THP1-differentiated macrophages induced by PMA (THP1-M0) with the conditioned medium (CM) from sh-LAYN- or sh-NC-transfected AGS and MKN-45 cells. (b) The microscopic morphology of THP1 and THP1-M0. Scale bar: 100 µm. (c) Evaluation of CD11b-positive cells by flow cytometry in THP1 and THP1-M0. (d and e) qPCR of CD206, CCL22, IL-10, and TGF-β transcripts in CM-incubated THP1-M0. (f and g) Determination of the percentage of CD163\u003csup\u003e+\u003c/sup\u003e macrophages by flow cytometry in CM-incubated THP1-M0. (h and i) The number of migrated cells by transwell assay in CM-incubated THP1-M0. Scale bars: 50 µm. *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01, ***\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001, ns: non-significant.\u003c/p\u003e","description":"","filename":"OnlineFig4.png","url":"https://assets-eu.researchsquare.com/files/rs-7027452/v1/ab351a3357e172c9255ea106.png"},{"id":88774321,"identity":"9181c9c6-fada-4247-924c-59a4a899e018","added_by":"auto","created_at":"2025-08-11 10:00:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":399385,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLAYN knockdown diminishes the \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vivo\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e growth of MKN-45 xenografts.\u003c/strong\u003e (a-e) Subcutaneous xenografts were generated by injecting sh-LAYN- or sh-NC-transduced MKN-45 cells into the right flank of nude mice. After 35 days, xenografts were assayed. n=5 for each group. Tumor growth evaluation (a), images (b), average weight (c), LAYN and Ki-67 expression by IHC (d), the mRNA expression of CD206, CCL22, IL-10, and TGF-β by qPCR (e) of harvested xenografts. *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, ***\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"OnlineFig5.png","url":"https://assets-eu.researchsquare.com/files/rs-7027452/v1/a2bb36915a5eac58d00845b9.png"},{"id":88774328,"identity":"dd3ef319-f564-405b-b347-27fcbd00d0c8","added_by":"auto","created_at":"2025-08-11 10:00:56","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":429241,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eZEB1 is significantly overexpressed in GC tissues and cells.\u003c/strong\u003e (a) Volcano plot showing the LAYN-associated genes in GC samples based on the TCGA-stomach adenocarcinoma (STAD) dataset from the LinkedOmics database. (b) Heat map revealing the top 50 significantly positively associated genes of LAYN in the TCGA-STAD dataset. (c) Venn diagram showing the three candidates (ZEB1, MEIS1, and FLI1), the 1712 positively associated genes of LAYN (Pearson’s correlation coefficient \u0026gt; 0.5 and \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) in the TCGA-STAD dataset from the LinkedOmics database, the 888 TFs on the JASPAR web, and the 299 up-regulated genes in plasma exosomes of GC patients from the GSE153413 dataset. (d) The TCGA-STAD dataset from the LinkedOmics database showing the expression association between ZEB1 and LAYN. (e) Association between ZEB1 expression and patient outcome predicted by the Kaplan-Meier plotter web. (f) ZEB1 mRNA expression in primary GC samples (n=53) and matched non-tumor gastric tissues (n=53) from the same patients. (g) Association between ZEB1 expression and LAYN levels in GC samples using Pearson’s correlation coefficients. (h) ZEB1 protein expression in primary GC samples (n=3) and matched non-tumor gastric tissues (n=3). (i) ZEB1 protein levels in AGS and MKN-45 GC cells and non-tumor GSE-1 cells (n=3). **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01, ***\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"Onlinefig6.png","url":"https://assets-eu.researchsquare.com/files/rs-7027452/v1/aae479df7e6df35467bb898a.png"},{"id":88774327,"identity":"ec3e19d5-4966-484b-bf33-3dd76480ed90","added_by":"auto","created_at":"2025-08-11 10:00:56","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":256615,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eZEB1 transcriptionally enhances LAYN expression in GC cells.\u003c/strong\u003e (a and b) Immunoblot of ZEB1 (a) and LAYN (b) in AGS and MKN-45 GC cells transfected with sh-ZEB1 or sh-NC. (c) LAYN mRNA expression in cells transfected with sh-ZEB1 or sh-NC. (d) The motif of ZEB1, the top 5 sites (BS1, BS2, BS3, BS4, and BS5) based on the score for ZEB1 within the LAYN promoter, and designed primers (Primer1 and Primer2) targeting two regions of the LAYN promoter. (e and f) ChIP-qPCR assay with total cellular extractions using a specific anti-ZEB1 antibody and Primer1 (e) or Primer2 (f). (g) Luciferase assays in 293T cells transfected with LAYN reporter constructs, which included the LAYN promoter fragments harboring both BS1 and BS2 sites (WT), mutated BS1 and wild-type BS2 (BS1-MUT), wild-type BS1 and mutated BS2 (BS2-MUT), or mutated BS1 and mutated BS2 (BS1+BS2-MUT). *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05, **\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01, ***\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001, ns: non-significant.\u003c/p\u003e","description":"","filename":"OnlineFig7.png","url":"https://assets-eu.researchsquare.com/files/rs-7027452/v1/9dc742c1eb19c69f2a9a1439.png"},{"id":88776786,"identity":"ff40200a-7043-4aa2-a448-9c5021cb9e69","added_by":"auto","created_at":"2025-08-11 10:08:56","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1297196,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLAYN restoration enhances malignant phenotypes in ZEB1-deficient GC cells.\u003c/strong\u003e (a-f) AGS and MKN-45 cells were subjected to introduction with sh-NC, sh-ZEB1, or sh-ZEB1+OE-LAYN. The influence on LAYN expression (a), colony formation (b), cell proliferation (c), cell apoptosis (d), cell migration (e), and cell invasion (f). Scale bars: 50 µm. *\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":"OnlineFig8.png","url":"https://assets-eu.researchsquare.com/files/rs-7027452/v1/9cd3ea46dca050ad568aba86.png"},{"id":88776785,"identity":"faf92bb8-742b-4107-8961-5abd5e2b4dab","added_by":"auto","created_at":"2025-08-11 10:08:56","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":997540,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLAYN restoration reduces the suppressive effects of ZEB1 depletion on migration and M2 polarization of macrophages.\u003c/strong\u003e (a-f) THP1-differentiated macrophages induced by PMA (THP1-M0) were incubated with the conditioned medium (CM) from AGS and MKN-45 cells transfected with sh-NC, sh-ZEB1, or sh-ZEB1+OE-LAYN. The impact on CD206, CCL22, IL-10, and TGF-β mRNA levels (a and b), the percentage of CD163\u003csup\u003e+\u003c/sup\u003e macrophages (c and d), and cell migration (e and f).Scale bars: 50 µm. *\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":"OnlineFig9.png","url":"https://assets-eu.researchsquare.com/files/rs-7027452/v1/fb756519e383398691efe63c.png"},{"id":108601112,"identity":"2409f9b8-181a-43d3-bc3e-5dd2f9b9dd7f","added_by":"auto","created_at":"2026-05-06 11:28:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8623092,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7027452/v1/62fb776d-6d3c-483f-a01c-630e6e07da79.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The ZEB1/LAYN cascade promotes cancer cell malignant phenotypes and macrophage M2 polarization in gastric cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGastric cancer (GC), originating from the epithelial cells of the gastric mucosa, is a formidable malignancy with a high incidence and mortality rate globally, particularly in East Asia, with China accounting for ~\u0026thinsp;40% of all GC cases (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Predominantly affecting individuals over 50 years of age, with a male-to-female incidence ratio of 2:1, GC often exhibits nonspecific symptoms such as upper abdominal discomfort and belching in its early stages, which are easily overlooked, leading to a low early diagnosis rate and a poor prognosis (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Current conventional regimens include surgical resection, chemotherapy, radiation therapy, and targeted therapy, yet these treatments have shown limited efficacy, especially in advanced stages. The heterogeneity of GC poses a significant challenge, with varying responses to treatment and a propensity for recurrence and metastasis (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The underlying mechanisms of gastric carcinogenesis are intricate, involving a complex interplay of genetic mutations, epigenetic alterations, and dysregulated signaling pathways (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Unraveling these mechanisms could offer promising avenues for the development of innovative and more potent therapeutic strategies against GC.\u003c/p\u003e\u003cp\u003eMacrophage M2 polarization is a critical immunological process where macrophages shift towards an anti-inflammatory and pro-healing phenotype (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In cancer, M2-polarized macrophages, often referred to as tumor-associated macrophages, are influenced by the tumor microenvironment and exhibit a phenotype that contributes to tumor development, angiogenesis, and immune suppression (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Specifically, in GC, M2 macrophages have been associated with poor prognosis and are involved in cancer metastasis and worse clinical outcomes (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Despite the growing body of research, the precise mechanisms of M2 polarization in GC remain largely elusive and warrant further investigation.\u003c/p\u003e\u003cp\u003eLayilin (LAYN), a pivotal protein in controlling T-cell function, has recently gained attention in the oncology field due to its potential role in tumorigenesis and cancer development. Aberrant expression of LAYN has been unveiled to closely associate with the prognosis and immune infiltration in pan-cancer (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Elevated levels of LAYN have been observed in multiple types of cancer, including colorectal cancer, prostate cancer, breast cancer, head and neck squamous cell carcinoma, and bladder cancer, suggesting that LAYN may function as an oncoprotein (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). LAYN is also predicted to be related to the enhanced risk of breast cancer (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Furthermore, in colorectal cancer, LAYN has the ability to enhance M2 macrophage polarization by targeting the NF-κB signaling (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In GC, LAYN forebodes unfavorable patient outcomes and is positively linked to macrophage infiltration (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Nonetheless, the specific functions of LAYN within the GC microenvironment and progression remain to be fully elucidated.\u003c/p\u003e\u003cp\u003eTransfection factors (TFs) are crucial for regulating gene expression throughout the process of tumor development (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Various TFs, such as HOXA10 and RUNX2, have been highlighted to contribute to gastric tumorigenesis by controlling the transcription and expression of genes involved in GC development (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). ZEB1, a key TF involved in the epithelial-mesenchymal transition and cancer metastasis, has been extensively studied in GC (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The established promoting role of ZEB1 implies its potential as a therapeutic target in GC.\u003c/p\u003e\u003cp\u003eHere, we used \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e experimental models to characterize the role of LAYN in the malignant progression and macrophage M2 polarization in GC. Furthermore, we deepened the understanding of the mechanisms underlying LAYN dysregulation in GC by identifying its regulatory TFs. Together, our findings demonstrate that the dysfunction of the ZEB1/LAYN cascade is responsible for M2 macrophage polarization and GC development.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cb\u003eBioinformatics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe retrieved the transcriptomic data from plasma exosomes of GC patients using the GSE153413 dataset on the online web NCBI (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE153413\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE153413\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to observe potential regulators related to GC. To analyze the differentially expressed genes (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Log2|FoldChange|\u0026gt;=1), we utilized the limma differential analysis using the DECenter-V6 tool from the SangerBox website platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://vip.sangerbox.com/\u003c/span\u003e\u003cspan address=\"http://vip.sangerbox.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). We utilized the Kaplan-Meier plotter web (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://kmplot.com/analysis/\u003c/span\u003e\u003cspan address=\"https://kmplot.com/analysis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to clarify the relationship between LAYN or ZEB1 expression and patient outcomes in GC. The TIMER2.0 online method (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://timer.cistrome.org/\u003c/span\u003e\u003cspan address=\"http://timer.cistrome.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was employed to observe the relationship between macrophages and GC prognosis, the association between LAYN expression and the infiltration of total macrophages and M2-like macrophages, and the correlation between LAYN expression and the levels of M2 polarization markers (CD163, CD206, CCL22, TGFB1, and IL10). The TCGA-stomach adenocarcinoma (STAD) dataset from the open-access LinkedOmics database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.linkedomics.org/login.php\u003c/span\u003e\u003cspan address=\"https://www.linkedomics.org/login.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was applied to analyze the genes related to LAYN expression and the expression association between ZEB1 and LAYN. We retrieved the TFs from the JASPAR web (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://jaspar.elixir.no/\u003c/span\u003e\u003cspan address=\"https://jaspar.elixir.no/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and used the web to predict the binding sites for ZEB1 in the LAYN promoter region (-2000 bp-0 bp).\u003c/p\u003e\u003cp\u003e\u003cb\u003ePatient samples\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePatients (n\u0026thinsp;=\u0026thinsp;53) were recruited in NanYang Central Hospital. They gave written informed consent to donate gastric specimens for research. We harvested their primary GC samples and corresponding non-cancerous gastric samples. Diagnosis of GC was made by two pathologists. The Ethics Committee of NanYang Central Hospital approved the study protocol for the evaluation of LAYN and ZEB1 expression in these human specimens.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCell lines and culture conditions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe procured human immortalized gastric mucosal GSE-1 cells (#SNL-304, 1640) from SUNNCELL (Wuhan, China) and AGS cells (#CL-0022, gastric adenocarcinoma cell line), MKN-45 cells (#CL-0292, gastric carcinoma cell line), and human THP1 monocyte (#CL-0233) from Procell (Wuhan, China). In addition to Ham\u0026rsquo;s F-12 (Procell) for AGS culture, RPMI-1640 (Life Technologies, Bleiswijk, the Netherlands) was used for other cell lines. For cell cultivation (5% CO\u003csub\u003e2\u003c/sub\u003e, 37\u0026deg;C), 10% FBS (EuroClone, Milan, Italy) and 1% penicillin/streptomycin (Transgen, Beijing, China) was added into the medium, and 0.05 mM β-mercaptoethanol (Sigma-Aldrich, Milano, Italy) was used specially for THP1 culture.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConstructs, transfection, and transduction\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFollowing the suggestions of the manufactory (Baidai, Changzhou, China), RFect Plasmid Transfection Reagent was applied for transfection with shRNA or shRNA\u0026thinsp;+\u0026thinsp;OE-LAYN into AGS and MKN-45 GC cells. We obtained recombinant constructs from Miaoling Biology (Wuhan, China): psh-EGFP-puro-LAYN(human) (sh-LAYN), psh-EGFP-puro-ZEB1(human) (sh-ZEB1), matched sh-NC control, and pEnCMV-EGFP-Linker-LAYN(human)-SV40-Neo (OE-LAYN).\u003c/p\u003e\u003cp\u003eLentivirus expressing sh-LAYN and sh-NC control virus were produced by VectorBuilder (Guangzhou, China). Following standard protocols (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), lentivirus particles were added to MKN-45 GC cells in the presence of 8 \u0026micro;g/mL polybrene. Post 20\u0026ndash;24 h, the cells were subjected to puromycin selection at a concentration of 2 \u0026micro;g/mL for over 10 days.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRNA preparation and quantitative PCR\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFrom human samples or cultured cell lines, we prepared mRNA with a BeyoMag\u0026trade; RNA Kit as described by the supplier (Beyotime, Shanghai, China). The resulting mRNA (2 \u0026micro;g) was used for cDNA synthesis with a PrimeScript\u0026trade; RT Master as per the vendor\u0026rsquo;s suggestions (TaKaRa, Dalian, China). Quantitative PCR (qPCR) was conducted on a Chromo4 System (Bio-Rad, Marnes-la-Coquette, France), employing SYBR Green reagents (TaKaRa). The relative quantification of gene expression was determined with the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method and normalized to β-actin. A list of the qPCR primers used can be found in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePrimers sequences used for qPCR\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eName\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003ePrimers for PCR (5\u0026rsquo;-3\u0026rsquo;)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ehuman LAYN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGCGTGGTCATGTACCATCAG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReverse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAGGTGTTGTCAGCTCTGTTTC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eHuman β-actin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCTTCGCGGGCGACGAT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReverse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCCACATAGGAATCCTTCTGACC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMus musculus CD206(MRC1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCTCTGTTCAGCTATTGGACGC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReverse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCGGAATTTCTGGGATTCAGCTTC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMus musculus CCL22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAGGTCCCTATGGTGCCAATGT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReverse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCGGCAGGATTTTGAGGTCCA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMus musculus IL-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGCTCTTACTGACTGGCATGAG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReverse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCGCAGCTCTAGGAGCATGTG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMus musculus TGFβ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCTCCCGTGGCTTCTAGTGC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReverse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGCCTTAGTTTGGACAGGATCTG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eMus musculus β-actin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTGAGCTGCGTTTTACACCCT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReverse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTTTGGGGGATGTTTGCTCCA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eAntibodies and immunoblotting\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe employed a Total Protein Isolation Kit from Abcam (Cambridge, UK) to prepare protein extracts from human samples or cultured cell lines. Following quantification by BCA Protein Assay (Thermo Fisher Scientific, Milan, Italy), 30 \u0026micro;g of protein was subjected to SDS/PAGE, followed by electro-blotting to PVDF membranes (Millipore, Molsheim, France). After blocking with 5% BSA in TBST, probing was done (overnight; 4\u0026deg;C) using a desired antibody: anti-LAYN (#20535-1-AP, Proteintech, Wuhan, China, 1:6,000), anti-ZEB1 (#21544-1-AP, Proteintech, 1:1,500), or anti-β-actin (#20536-1-AP, Proteintech, 1:8,000). Following secondary antibody incubation, a chemiluminescent kit was applied for signal development as recommended by the producer (Nakarai Tesque, Tokyo, Japan).\u003c/p\u003e\u003cp\u003e\u003cb\u003eCell colony formation and proliferation assays\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor colony growth analysis, we seeded AGS and MKN-45 cells at 48 h post-transfection in 6-well culture plates (Corning, Shanghai, China). Following this, colonies were grown for 10\u0026ndash;14 days under standard conditions. After staining with crystal violet (0.5%), we quantified the number of generated colonies using ImageJ (NIH, Bethesda, MD, USA). For the EdU incorporation assay, we utilized a Click-iT EdU-594 Assay Kit as per the supplier\u0026rsquo;s instructions (Servicebio, Wuhan, China). Briefly, AGS and MKN-45 cells at 48 h post-transfection were treated with 10 \u0026micro;M EdU working reagent, fixed, and subjected to permeation. After staining with iF594 (red fluorescence) and DAPI (blue fluorescence), we quantified the ratio of EdU\u003csup\u003e+\u003c/sup\u003e cells with a TCS SP5 microscope (Leica, Wetzlar, Germany).\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe conditioned medium (CM) and co-culture system\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor co-culture systems, we collected the culture supernatant (called CM) from AGS and MKN-45 cells after 48 h transfection with sh-NC, sh-LAYN, sh-ZEB1, or sh-ZEB1\u0026thinsp;+\u0026thinsp;OE-LAYN. Prior to co-culture, THP1 cells were stimulated with 100 ng/mL of PMA (Sigma-Aldrich) for 24 h to induce differentiation into macrophages (THP1-M0). THP1-M0 macrophages were characterized by microscopic detection and CD11b expression evaluation. Co-culture systems were set up by placing THP1-M0 macrophages, suspended in 10% FBS RPMI-1640, into 24-Tranwell inserts (Corning), and the bottom compartment was added with the collected CM. The co-culture was performed for 36\u0026ndash;48 h, and co-cultured THP1-M0 cells were harvested and subjected to mRNA expression analysis, migration assay, and flow cytometry.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTranswell cell migration and invasion assays\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTranswell assays were used to assess migratory and invasive capacities of AGS and MKN-45 cells at 24 h post-transfection as well as the migratory potential of co-cultured THP1-M0 cells with Matrigel-coated or uncoated 24-Tranwell inserts (Corning). In brief, we seeded cells, suspended in non-serum media, into inserts and allowed them to migrate or invade towards the lower compartment containing 15% FBS medium. After a 24-h incubation, the number of migratory or invasive cells was determined by staining with 0.1% crystal violet and subsequent counting under the BX53 microscope (Olympus, Tokyo, Japan).\u003c/p\u003e\u003cp\u003e\u003cb\u003eFlow cytometry\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe cytomics FC500 (Beckman Coulter, Krefeld, Germany) was used for flow cytometry assay. For apoptosis evaluation, we stained AGS and MKN-45 cells at 72 h post-transfection with FITC-Annexin V and propidium iodide under the application of a Commercial Staining Kit (Beyotime). For cell percentage assessment, THP1 and THP1-M0 cells were stained with an anti-CD11b antibody conjugated with FITC (#982614, Biolegend, San Diego, CA, USA), and co-cultured THP1-M0 cells were stained with an anti-CD163 antibody labeled with PE/Cyanine7 (#156707, Biolegend). The 7AAD Staining Solution (#420404, Biolegend) was also used for dead cell elimination.\u003c/p\u003e\u003cp\u003e\u003cb\u003eXenograft models and immunohistochemistry (IHC)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor the production of xenograft models, we utilized BALB/c nude mice from Vital River Laboratory (Beijing, China) and grouped them into two groups: sh-NC (n\u0026thinsp;=\u0026thinsp;5) and sh-LAYN (n\u0026thinsp;=\u0026thinsp;5). All experimental procedures were performed using 6-week-old female mice, conducted following the national guidelines, and were approved by the Animal Care and Use Committee of NanYang Central Hospital. Stable LAYN-depleted MKN-45 GC cells were established before subcutaneous inoculation in the right flank (2 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e cells/mouse in 150 \u0026micro;L of PBS). Tumor diameters were gauged weekly at right angles (d\u003csub\u003eshort\u003c/sub\u003e and d\u003csub\u003elong\u003c/sub\u003e), and tumor growth monitor was done by determining their volumes using the formula: (d\u003csub\u003eshort\u003c/sub\u003e)\u003csup\u003e2\u003c/sup\u003e \u0026times; (d\u003csub\u003elong\u003c/sub\u003e) \u0026times; 0.5. Studies were terminated after 35 days of cell implantation, and xenografts were collected. In accordance with the established methods (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), IHC detection for LAYN and Ki-67 was performed on 4-\u0026micro;m-thick sections of formalin-fixed, paraffin-embedded xenografts. The sections were probed with anti-LAYN (#20535-1-AP, Proteintech, 1:600) or anti-Ki-67 (#27309-1-AP, Proteintech, 1:8,000) antibody.\u003c/p\u003e\u003cp\u003e\u003cb\u003eChromatin immunoprecipitation (ChIP) assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUnder the application of a ChIP Assay Kit and the accompanying suggestions (Beyotime), we performed ChIP experiments using an anti-ZEB1 antibody (#21544-1-AP, Proteintech) or anti-IgG Isotype control (#ab172730, Abcam). Chromatin DNA of AGS and MKN-45 GC cells were subjected to ultrasonication. A bead-antibody complex was formed by mixing the specific antibody with Protein A/G Agarose. The resultant DNA fragments were incubated with the bead-antibody complex overnight at 4\u0026deg;C. We extracted DNA from the precipitates and conducted qPCR to assess the enrichment amount of LAYN promoter segments using designed primers (Primer1 and Primer2).\u003c/p\u003e\u003cp\u003e\u003cb\u003eLuciferase assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe carried out these assays in human 293T cells (#CL-0005), which were obtained from Procell and cultivated using Procell-developed standard media. LAYN reporter constructs were made by subcloning the LAYN promoter fragments harboring both predicted BS1 and BS2 sites (WT), mutated BS1 and wild-type BS2 (BS1-MUT), wild-type BS1 and mutated BS2 (BS2-MUT), or mutated BS1 and mutated BS2 (BS1\u0026thinsp;+\u0026thinsp;BS2-MUT) into the pGL3 basic vector (Life Technologies). Using RFect Plasmid Transfection Reagent, we transfected each reporter plasmid and sh-NC or sh-ZEB1 along with pRL-TK Renilla vector into 293T cells. Forty-eight hours post-transfection, cell lysates were analyzed for luciferase activity, with measurements of firefly and Renilla obtained using a TriStar S LB 942 plate reader from Berthold (Bad Wildbad, Germany).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eFor analyzing differences between two groups, we employed the Mann-Whitney \u003cem\u003eU\u003c/em\u003e test or an unpaired \u003cem\u003et\u003c/em\u003e-test, while ANOVA was utilized for comparisons involving three or more groups, accompanied by Tukey\u0026rsquo;s or Sidak\u0026rsquo;s \u003cem\u003epost-hoc\u003c/em\u003e tests as appropriate. Data were expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, and significance was set at a \u003cem\u003ep\u003c/em\u003e-value less than 0.05. We utilized Pearson\u0026rsquo;s correlation coefficients to analyze the ZEB1/LAYN expression association in human GC samples.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eBioinformatics and expression analyses identify the up-regulation of LAYN in human GC\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo identify potential regulators related to GC pathogenesis, we performed a bioinformatic analysis using the transcriptomic data from plasma exosomes of GC patients available from the NCBI-GSE153413 dataset. Using the limma differential analysis on the SangerBox-DECenter-V6 tool, we noted that there were a lot of up-regulated and down-regulated genes (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Log2|FoldChange|\u0026gt;=1) in GC plasma exosomes versus normal controls, as shown in volcano plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Heat map revealed the top five significantly up-regulated genes and down-regulated genes in GC plasma exosomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Among these, we focused on LAYN in this study as it was the most significantly up-regulated factor in GC plasma exosomes relative to normal counterparts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). We then clarified the relationship between LAYN expression and patient outcomes in GC. Utilizing the Kaplan-Meier plotter web, we confirmed that GC patients with LAYN expression above the median had remarkably worse overall survival (OS), first progression (FP), and post progression survival (PPS) compared with those with LAYN expression below the median (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). To confirm the up-regulation of LAYN in GC, we determined the expression of LAYN in a cohort of 53 patients with GC. Consistently, primary GC samples displayed increased levels of LAYN mRNA than matched non-tumor gastric tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed). Furthermore, elevated levels of LAYN protein were observed in primary GC samples and GC cell lines (AGS and MKN-45) compared to their counterparts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eLAYN deficiency reduces cell malignant phenotypes and induces apoptosis\u003c/b\u003e \u003cb\u003ein vitro\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAlthough LAYN has been shown to correlate with the prognosis of GC patients (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), no studies proved its precise function in GC development. Herein, we wanted to address the role of LAYN in gastric carcinogenesis. AGS and MKN-45 GC cells were introduced with a shRNA targeting LAYN (sh-LAYN), and their LAYN expression was evaluated by immunoblot assay. Transfection of cells with sh-LAYN resulted in decreased protein levels of LAYN compared with sh-NC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Notably, the significant reduction in the number of colonies obtained with LAYN deficiency was validated by colony formation assay (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Depletion of LAYN also strongly decreased the ratio of EdU-positive cells in AGS and MKN-45 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Conversely, LAYN knockdown remarkably enhanced cell apoptosis rate (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). In addition, AGS and MKN-45 cells with LAYN deficiency exhibited suppressed migratory and invasive capacities compared with sh-NC-transfected cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef). These data together establish LAYN as a crucial player in facilitating GC malignant progression.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eDeficiency of LAYN attenuates the migration and M2 polarization of GC-related macrophages\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe polarization towards the M2 phenotype and recruitment of macrophages are pivotal in exerting pronounced pro-tumorigenic effects within the realm of cancer biology (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). To verify this notion, we employed the TIMER2.0 online method to observe the relationship of macrophages with GC prognosis. Intriguingly, we found that patients with high macrophages and high M2-like macrophages had significantly worse survival rates (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). The TIMER2.0 algorithm also predicted the positive association between LAYN expression and the infiltration of total macrophages and M2-like macrophages (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). Moreover, LAYN expression was predicted by the TIMER2.0 algorithm to positively correlate with the levels of M2 polarization markers (CD163, CD206, CCL22, TGFB1, and IL10) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec). These results suggest the association of LAYN expression with macrophage M2 polarization in GC.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo confirm this possibility, we incubated THP1-differentiated macrophages induced by PMA (THP1-M0) with the conditioned medium (CM) from sh-LAYN- or sh-NC-transfected AGS (AGS\u003csup\u003esh\u0026minus;LAYN\u003c/sup\u003eCM or AGS\u003csup\u003esh\u0026minus;NC\u003c/sup\u003eCM) and MKN-45 cells (MKN-45\u003csup\u003esh\u0026thinsp;\u0026minus;\u0026thinsp;LAYN\u003c/sup\u003eCM or MKN-45\u003csup\u003esh\u0026thinsp;\u0026minus;\u0026thinsp;NC\u003c/sup\u003eCM), as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea. The microscopic morphology of THP1 and THP1-M0 was shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb. In comparison to THP1 cells, THP1-M0 cells exhibited adherent growth characteristics, with an increase in cell size and irregularly shaped edges (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Flow cytometry results revealed that THP1-M0 had higher levels of macrophage marker CD11b (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec), demonstrating the successful differentiation of THP1 into macrophages. Using qPCR assay, we observed decreased transcript levels of M2 polarization markers CD206, CCL22, and IL-10 in THP1-M0 incubated with AGS\u003csup\u003esh\u0026minus;LAYN\u003c/sup\u003eCM or MKN-45\u003csup\u003esh\u0026thinsp;\u0026minus;\u0026thinsp;NC\u003c/sup\u003eCM (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee). The expression of TGF-β mRNA was significantly decreased in THP1-M0 incubated with MKN-45\u003csup\u003esh\u0026thinsp;\u0026minus;\u0026thinsp;NC\u003c/sup\u003eCM (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee). Furthermore, flow cytometry data showed that LAYN depletion significantly decreased the percentage of CD163\u003csup\u003e+\u003c/sup\u003e macrophages (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ef and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eg), indicating that LAYN depletion weakens macrophage M2 polarization. We then investigated the impact of LAYN silencing on the migration of THP1-M0. Deficiency of LAYN in AGS and MKN-45 GC cells resulted in reduced migration ability of THP1-M0 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eh and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ei). Collectively, our findings suggest that LAYN plays a role in enhancing the M2 polarization and recruitment of macrophages in GC.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eLAYN deficiency diminishes tumor growth\u003c/b\u003e \u003cb\u003ein vivo\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe next evaluated the feasibility of LAYN depletion as a therapeutic approach for GC by establishing \u003cem\u003ein vivo\u003c/em\u003e sh-LAYN or sh-NC xenograft models. Sh-LAYN-transduced MKN-45 cells exhibited significantly slower growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea) and produced smaller tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec) compared to the same cells transduced with sh-NC lentivirus. IHC assay confirmed decreased levels of LAYN in sh-LAYN subcutaneous xenografts compared with sh-NC controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed). Moreover, LAYN-depleted xenografts displayed reduced levels of Ki-67 staining by IHC (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed), confirming that LAYN depletion diminishes the growth of MKN-45 xenografts. Interestingly, the deficiency of LAYN led to a striking down-regulation in the expression of CD206, CCL22, IL-10, and TGF-β transcripts in formed xenografts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ee), implying the influence of LAYN knockdown in macrophage M2 polarization.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eZEB1 is significantly overexpressed in GC and transcriptionally enhances LAYN expression\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo gain a deeper understanding of the mechanisms underlying the up-regulation of LAYN in GC, we focused on its regulatory transcription factors (TFs), as TFs play an essential role in gene expression during the tumorigenesis process (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). We first used the open-access LinkedOmics database to analyze the genes related to LAYN based on the TCGA-stomach adenocarcinoma (STAD) dataset. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea, volcano plot showed the LAYN-associated genes in STAD samples. The top 50 significantly positively associated genes of LAYN in the TCGA-STAD dataset were revealed by heat map in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb. When we combined the 1712 positively associated genes of LAYN (with the criteria of Pearson\u0026rsquo;s correlation coefficient\u0026thinsp;\u0026gt;\u0026thinsp;0.5 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the TCGA-STAD dataset from the LinkedOmics database (Supplementary Table\u0026nbsp;1), the 888 TFs on the JASPAR web, and the 299 up-regulated genes in plasma exosomes of GC patients from the GSE153413 dataset (Supplementary Table\u0026nbsp;2), we found a total of three candidates (ZEB1, MEIS1, and FLI1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec). Among these, the TF ZEB1 caught our attention due to its established crucial role in driving GC progression (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Utilizing the LinkedOmics database, we observed a significant and positive expression association between ZEB1 and LAYN in the TCGA-STAD dataset (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed). The Kaplan-Meier plotter online web also revealed that GC patients with ZEB1 expression above the median exhibited significantly worse OS, FP, and PPS compared with those with LAYN expression below the median (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ee). Through qPCR assay, we also confirmed the elevated expression of LAYN transcript in primary GC specimens compared with normal gastric tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ef). Notably, we also confirmed the significantly positive expression association of LAYN with ZEB1 in primary GC specimens (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eg). By contrast, the striking increase in ZEB1 protein expression was validated by immunoblot in primary GC specimens and AGS and MKN-45 GC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eh and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ei).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eHaving unveiled the positive association between LAYN and ZEB1 in GC, we sought to investigate the regulation of ZEB1 in LAYN transcription and expression. As expected, reduced expression of ZEB1 by sh-ZEB1 transfection, verified by immunoblot (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea), caused a significant down-regulation in LAYN expression at both protein and mRNA levels in AGS and MKN-45 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec), indicating that ZEB1 positively modulates LAYN expression. The JASPAR tool predicted multiple binding sites for ZEB1 in the LAYN promoter region (-2000 bp-0 bp), and the top 5 sites (BS1, BS2, BS3, BS4, and BS5) based on the score were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed. In order to preliminarily determine the binding site of ZEB1 and the LAYN promoter, we performed ChIP-qPCR assay using a specific anti-ZEB1 antibody and designed primers (Primer1 and Primer2) targeting two regions of the LAYN promoter (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed). Intriguingly, we confirmed that the promoter segments of LAYN encompassing the BS1 and BS2 sites were strongly enriched in the ZEB1-associating precipitates using the Primer1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ee), suggesting that ZEB1 may bind to the LAYN promoter through site BS1, site BS2, or both sites. However, in AGS and MKN-45 cells, no correlation was observed between ZEB1 and the LAYN promoter segments harboring the BS3, BS4, and BS5 sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ef). Luciferase assays were then performed in 293T cells by generating LAYN reporter constructs, which included the LAYN promoter fragments harboring both BS1 and BS2 sites (WT), mutated BS1 and wild-type BS2 (BS1-MUT), wild-type BS1 and mutated BS2 (BS2-MUT), or mutated BS1 and mutated BS2 (BS1\u0026thinsp;+\u0026thinsp;BS2-MUT). Transfection of WT reporter led to diminished luciferase activity in the presence of sh-ZEB1 in 293T cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eg). Importantly, mutation of the BS1 site alone (BS1-MUT) and mutation in both BS1 and BS2 sites (BS1\u0026thinsp;+\u0026thinsp;BS2-MUT), but not mutation in the BS2 site alone (BS2-MUT), completely abrogated the suppressive effect of ZEB1 depletion (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eg). Taken together, these data demonstrate that ZEB1 transcriptionally increases LAYN expression by binding to the BS1 site within the LAYN promoter.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eLAYN restoration enhances malignant phenotypes in ZEB1-deficient GC cells and reduces the suppressive effects of ZEB1 depletion on migration and M2 polarization of macrophages\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFinally, we explored whether ZEB1 contributes to gastric tumorigenesis through LAYN. A LAYN ORF plasmid (OE-LAYN) was used to elevate LAYN protein expression in ZEB1-deficient AGS and MKN-45 GC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ea). Remarkably, ZEB1 silencing resulted in a repression in cell growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eb and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ec) and a promotion in cell apoptosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ed), and these alterations were partially abolished by LAYN expression increase (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eb-\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ed). Moreover, ZEB1 knockdown-triggered migration and invasion defects were rescued by restored expression of LAYN (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ee and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ef). When we incubated THP1-M0 with the CM from sh-ZEB1- or sh-NC-transfected AGS (AGS\u003csup\u003esh\u0026minus;ZEB1\u003c/sup\u003eCM or AGS\u003csup\u003esh\u0026minus;NC\u003c/sup\u003eCM) and MKN-45 cells (MKN-45\u003csup\u003esh\u0026thinsp;\u0026minus;\u0026thinsp;ZEB1\u003c/sup\u003eCM or MKN-45\u003csup\u003esh\u0026thinsp;\u0026minus;\u0026thinsp;NC\u003c/sup\u003eCM), we found that the mRNA levels of M2 polarization markers CD206, CCL22, IL-10, and TGF-β were decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea and \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eb), and the percentage of CD163\u003csup\u003e+\u003c/sup\u003e macrophages was declined (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ec and \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ed), indicating that ZEB1 knockdown diminishes macrophage M2 polarization. We also incubated THP1-M0 with the CM from sh-ZEB1\u0026thinsp;+\u0026thinsp;OE-LAYN-transfected cells (AGS\u003csup\u003esh\u0026minus;ZEB1+OE\u0026minus;LAYN\u003c/sup\u003eCM or MKN-45\u003csup\u003esh\u0026thinsp;\u0026minus;\u0026thinsp;ZEB1+OE\u0026minus;LAYN\u003c/sup\u003eCM). Notably, ZEB1 knockdown-driven M2 polarization suppression was partially reversed by LAYN expression restoration (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ea-\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ed). In addition, depletion of ZEB1 resulted in reduced migration ability of THP1-M0, which could be rescued by LAYN restoration (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ee and \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003ef). Thus, ZEB1 affects GC development by regulating cancer cell malignant phenotypes and macrophage M2 polarization by partially through LAYN.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eGC remains a formidable global health challenge, characterized by a complex interplay of multiple carcinogenic molecules (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). These regulators, including protein molecules, contribute to the intricate molecular landscape of the disease and GC progression (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). By understanding the action of these regulators, we can envision a future where targeted therapies are tailored to disrupt these carcinogenic pathways, potentially revolutionizing treatment strategies and improving patient outcomes. Our research has uncovered a significant role for LAYN in the immunological regulation and malignant progression of GC. Interestingly, we have shed light on a novel mechanism in driving the up-regulation of LAYN in GC. Thus, inhibiting LAYN could potentially serve as a therapeutic way in the fight against GC, opening up possibilities for the design and development of novel anti-cancer drugs tailored specifically for GC patients.\u003c/p\u003e\u003cp\u003eLAYN has emerged as a significant player in the oncological landscape, with its role in tumor immune infiltration and cancer progression being increasingly recognized (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). For example, LAYN works as a strong driver in colorectal cancer by accelerating cancer metastasis and macrophage M2 polarization (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). LAYN negatively modulates the immune activity of CD8\u0026thinsp;+\u0026thinsp;T cells in hepatocellular carcinoma, and LAYN\u0026thinsp;+\u0026thinsp;CD8\u0026thinsp;+\u0026thinsp;T lymphocytes exhibit reduced cytotoxic activity (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Additionally, down-regulation of LAYN in CD8\u0026thinsp;+\u0026thinsp;T lymphocytes is responsible for the anti-cancer efficacy of anti-VEGFR2 therapy in lung adenocarcinoma (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Emerging evidence also highlights the overexpression of LAYN in GC, which correlates with immune infiltration and patient outcomes (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Our research has delved deeper into the role of LAYN in GC, revealing that LAYN deficiency weakens cancer cell malignant phenotypes and induces their apoptosis \u003cem\u003ein vitro\u003c/em\u003e, as well as diminishes GC xenograft growth \u003cem\u003ein vivo\u003c/em\u003e. The polarization towards the M2 phenotype of macrophages plays a key role in facilitating GC development (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Importantly, our study also demonstrates that deficiency of LAYN reduces the migration and M2 polarization of GC-related macrophages. These discoveries not only clarify LAYN\u0026rsquo;s specific functions in GC but also unveil a previously uncharacterized molecular basis driving the disease\u0026rsquo;s progression, underscoring the potential of LAYN as a target for novel therapies against GC.\u003c/p\u003e\u003cp\u003eZEB1, a vital TF, is known for its role in promoting epithelial-mesenchymal transition and is frequently implicated in tumorigenesis and tumor progression (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In various cancers, ZEB1 has been shown to modulate gene expression patterns that favor invasion and metastasis. For instance, ZEB1 has established a promoting role in hepatocellular carcinoma by enhancing the transcription of phosphofructokinase-1 (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). ZEB1 affects the progression of neuroendocrine prostate cancer by transcriptionally controlling the levels of crucial glycolytic factors (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Furthermore, studies in ZEB1 have suggested its implication in cancer macrophage polarization and immune evasion (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Depletion of ZEB1 is also reported to sensitize cancer cells to immune checkpoint inhibition therapy in colorectal cancer (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In GC, the role of ZEB1 is particularly intriguing, with evidence implicating its contribution to increased tumor aggressiveness and poor patient outcomes (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). In line with earlier documents (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), our data confirm the up-regulation of ZEB1 in GC. Importantly, we demonstrate, for the first time, that ZEB1 transcriptionally elevates LAYN expression in GC cells by binding to the LAYN promoter. Our rescue experiments unveil that restoration of LAYN in ZEB1-deficient GC cells not only enhances their malignant phenotypes but also counteracts the inhibitory effects of ZEB1 depletion on the migration and M2 polarization of macrophages, suggesting a mechanistic link between ZEB1 and LAYN in the modulation of GC biology. Therefore, ZEB1 exerts its oncogenic function in GC, in part, by up-regulating LAYN, revealing a new epigenetic regulatory cascade that promotes GC development. Nevertheless, there is a dearth of \u003cem\u003ein vivo\u003c/em\u003e studies examining this molecular cascade, necessitating additional investigative efforts.\u003c/p\u003e\u003cp\u003eThis study broadens the mechanisms underlying gastric carcinogenesis by providing novel cause data that the ZEB1/LAYN cascade contributes to the development of GC. Through this study, we envision that LAYN or ZEB1 serves as a new promising target for GC intervention.However, our study also has certain limitations. Whether exosomal ZEB1 affects GC cell migration and promotes macrophage M2 polarization through LAYN remains unclear and merits further exploration.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eGC：Gastric Cancer;EMT: Epithelial-Mesenchymal Transition;TME:Tumor Microenvironment; TAM:Tumor-Associated Macrophage;ZEB1: Zinc finger E-box binding homeobox 1;LAYN: Layilin;ZEB1-AS1:ZEB1 Antisense RNA 1;PAK2 P21-Activated Kinase 2;HTR2B；5-Hydroxytryptamine Receptor 2B；CREB1：CAMP Responsive Element Binding Protein 1；LOXL2 Lysyl Oxidase Like 2\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the NanYang Central Hospital(Approval No.2021625). All participants provided written informed consent, and the research was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided consent for publication. Written permissions were obtained for using identifiable images.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are available from authors upon reasonable request due to restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was supported by the Nanyang Science and Technology Bureau (No.252102310269).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDJ were responsible for designing the study.DJ ,SN and YX performing experiments. \u0026nbsp;DJ and MX writing and revising the manuscript.DJ,MZ and Ql performing the statistical analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study obtained substantial support from the laboratory members.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eL\u0026oacute;pez MJ, Carbajal J, Alfaro AL, et al. 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ZEB1 enhances Warburg effect to facilitate tumorigenesis and metastasis of HCC by transcriptionally activating PFKM. Theranostics. 2021; 11: 5926\u0026ndash;5938.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWang D, Du G, Chen X, et al. Zeb1-controlled metabolic plasticity enables remodeling of chromatin accessibility in the development of neuroendocrine prostate cancer. Cell Death Differ. 2024;31:779\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJiang H, Wei H, Wang H, et al. Zeb1-induced metabolic reprogramming of glycolysis is essential for macrophage polarization in breast cancer. Cell Death Dis. 2022;13:206.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen XJ, Guo CH, Wang ZC, et al. Hypoxia-induced ZEB1 promotes cervical cancer immune evasion by strengthening the CD47-SIRPα axis. Cell Commun Signal. 2024;22:15.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMenche C, Schuhwerk H, Armstark I, et al. ZEB1-mediated fibroblast polarization controls inflammation and sensitivity to immunotherapy in colorectal cancer. EMBO Rep. 2024;25:3406\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRomero S, Musleh M, Bustamante M, et al. Polymorphisms in TWIST1 and ZEB1 Are Associated with Prognosis of Gastric Cancer Patients. Anticancer Res. 2018;38:3871\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGao ZY, Liu H, Zhang Z. miR-144-3p increases radiosensibility of gastric cancer cells by targeting inhibition of ZEB1. Clin Transl Oncol. 2021;23:491\u0026ndash;500.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Supplementary Material","content":"\u003cp\u003eSupplementary Tables 1 and 2 are not available with this version.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Gastric cancer, M2 polarization, LAYN, transcription factor, ZEB1","lastPublishedDoi":"10.21203/rs.3.rs-7027452/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7027452/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eM2-polarized macrophages in the tumor microenvironment contribute to tumor development, angiogenesis, and immune suppression. Layilin (LAYN) is linked to macrophage infiltration and patient outcomes in gastric cancer (GC). Here, we characterized the role of LAYN in malignant progression and macrophage M2 polarization in GC.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eProtein levels were assessed using immunoblotting and immunohistochemistry (IHC), and mRNA levels were detected through quantitative PCR (qPCR). The impact on GC cell functions was determined by assessing cell invasion, migration, apoptosis, proliferation, and colony formation ability. The effect on macrophage M2 polarization was evaluated by analyzing the expression of M2 markers and the percentage of CD163\u003csup\u003e+\u003c/sup\u003e macrophages. Xenograft models were generated to determine the role \u003cem\u003ein vivo\u003c/em\u003e. The ZEB1-LAYN relationship was confirmed by chromatin immunoprecipitation (ChIP) and luciferase assays.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eLAYN and ZEB1 were up-regulated in GC samples and cell lines. LAYN deficiency weakened cancer cell malignant phenotypes and induced their apoptosis \u003cem\u003ein vitro\u003c/em\u003e, as well as diminished MKN-45 xenograft growth \u003cem\u003ein vivo\u003c/em\u003e. Moreover, LAYN deficiency attenuated the migration and M2 polarization of GC-related macrophages. Mechanistically, ZEB1 transcriptionally enhanced LAYN expression. LAYN restoration enhanced malignant phenotypes in ZEB1-deficient GC cells and reduced the suppressive effects of ZEB1 depletion on the migration and M2 polarization of macrophages.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eOur study demonstrates that the ZEB1/LAYN cascade contributes to the development of GC by enhancing cancer cell malignant phenotypes and macrophage M2 polarization. LAYN or ZEB1 could be a new target for GC intervention.\u003c/p\u003e","manuscriptTitle":"The ZEB1/LAYN cascade promotes cancer cell malignant phenotypes and macrophage M2 polarization in gastric cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-11 10:00:51","doi":"10.21203/rs.3.rs-7027452/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"94110aa7-4881-40bf-989f-c67897133ca1","owner":[],"postedDate":"August 11th, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Withdrawn","date":"2026-05-06T11:09:04+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-06T11:27:43+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-11 10:00:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7027452","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7027452","identity":"rs-7027452","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}