APLN, a novel prognostic biomarker, contributes to esophageal carcinoma development

APLN, a novel prognostic biomarker, contributes to esophageal carcinoma development | 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 APLN, a novel prognostic biomarker, contributes to esophageal carcinoma development Weifeng Xu, Caiyun Nie, Zhen Liu, Guanghui Liang, Penghui Yu, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7592740/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Jan, 2026 Read the published version in Functional & Integrative Genomics → Version 1 posted 9 You are reading this latest preprint version Abstract Background: Esophageal carcinoma (ESCA) is a highly aggressive malignancy with poor prognosis. The apelin gene (APLN) encodes a secreted peptide involved in various physiological processes, but its role in ESCA progression and chemoresistance remains unclear. Methods: We integrated transcriptomic data from TCGA and GEO databases with CRISPR screening to identify key oncogenes in ESCA. ALPN was identified as a key gene. Functional assays in vitro and in vivo were performed to investigate the biological role of APLN. Mechanistic studies explored the involvement of APLN in autophagy regulation and chemoresistance. Furthermore, we developed an exosome-based siRNA delivery system targeting APLN and constructed a prognostic nomogram incorporating APLN expression. Results: APLN was significantly overexpressed in ESCA tissues and correlated with poor patient prognosis. DNA hypomethylation contributed to APLN upregulation. Functional experiments demonstrated that APLN knockdown suppressed tumor cell proliferation, induced apoptosis, and enhanced sensitivity to cisplatin. Mechanistically, APLN promoted autophagic flux, which mediated chemoresistance in ESCA cells. Exosome-mediated delivery of APLN siRNA effectively inhibited tumor growth in vivo without systemic toxicity. Additionally, a nomogram combining APLN expression with clinical stage accurately predicted patient survival, providing a practical tool for individualized prognosis. Conclusions: Our study identifies APLN as a novel driver of ESCA progression and chemoresistance through autophagy regulation. Targeting APLN via exosome-based siRNA delivery offers a promising therapeutic strategy. Moreover, the APLN-based prognostic nomogram holds potential for guiding personalized treatment decisions in ESCA patients. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Esophageal carcinoma is one of the most aggressive gastrointestinal malignancies, ranking as the sixth leading cause of cancer-related deaths worldwide( 1 ). Despite advances in surgical techniques, radiotherapy, and chemotherapy, the overall survival rate of ESCA remains dismal, with a 5-year survival rate of less than 20%( 2 , 3 ). Tumor recurrence and chemoresistance are the main reasons for treatment failure, underscoring the urgent need to identify novel biomarkers and therapeutic targets to improve prognosis and guide personalized therapy in ESCA patients. As the principal agonist for the G protein-coupled receptor APJ, it forms the apelin/APJ signaling axis, a critical regulator of diverse physiological processes spanning cardiovascular homeostasis, energy metabolism, angiogenesis, and neuroendocrine functions( 4 – 7 ). APLN signaling primarily activates Gαi/o proteins upon binding APJ, inhibiting adenylate cyclase and modulating key downstream pathways: the PI3K/Akt/mTOR cascade (promoting cell survival, glucose uptake, and angiogenesis), ERK1/2 MAPK (regulating proliferation and migration), and eNOS/NO synthesis (mediating vasodilation and cardioprotection) ( 8 – 10 ). Consequently, dysregulation of APLN/APJ signaling is implicated in cardiometabolic diseases (heart failure, pulmonary hypertension, diabetes), tumor angiogenesis (e.g., in hepatocellular carcinoma), and reproductive dysfunction (e.g., blood-testis barrier disruption in diabetes)( 7 , 11 – 13 ). However, the role of APLN in esophageal carcinoma remains poorly understood, and its potential as a prognostic biomarker and therapeutic target in ESCA has not been systematically investigated. In this study, we aimed to investigate the biological function and clinical significance of APLN in ESCA. By integrating multi-omics data from public databases and functional assays in vitro and in vivo, we explored the oncogenic role of APLN and its impact on autophagy-mediated chemoresistance. We further evaluated the therapeutic potential of exosome-mediated APLN siRNA delivery and established a prognostic nomogram model incorporating APLN expression for individualized survival prediction in ESCA patients. Methods Data Collection and Bioinformatic Analysis Gene expression and clinical data for ESCA were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GSE53624) databases. Differentially expressed genes (DEGs) between tumor and normal tissues were identified using the “limma” R package with |log2FC| >1 and adjusted p-value < 0.05. Prognostic genes were determined by univariate Cox regression analysis. Genome-wide CRISPR/Cas9 screening data related to ESCA cell invasion were retrieved from the study by Wu et al( 14 ). Genes at the intersection of DEGs, prognostic genes, and CRISPR hits were selected for further investigation. DNA methylation and copy number variation (CNV) data were analyzed using cBioPortal and UCSC Xena. Correlation analyses and gene set enrichment analysis (GSEA) were conducted using R software. Cell Lines and Transfection Human esophageal carcinoma cell lines KYSE-520 (catalog no. C6510) were purchased from Beyotime Biotechnology (Beijing, China). All cell lines were authenticated by short tandem repeat (STR) profiling to ensure their identity and confirmed to be free of mycoplasma contamination. Cells were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum at 37°C in a humidified incubator with 5% CO2. APLN knockdown was achieved using lentiviral short hairpin RNA (shRNA). The specific shRNA sequence targeting APLN was: shAPLN: 5'-TCTCCCATAAGGGACCCAT-3'. Lentiviral particles encoding shAPLN or a scrambled shControl sequence were produced and used to infect ESCA cells. Stable clones were selected using puromycin (2 µg/mL) for 7 days prior to downstream assays. Cell Proliferation and Apoptosis Assays Cell proliferation was evaluated using the Cell Counting Kit-8 (CCK-8, Beyotime Biotechnology, catalog no. C0037). Briefly, ESCA cells were seeded in 96-well plates at a density of 3×10^3 cells per well. At indicated time points (0, 24, 48, 72, and 96 hours), 10 µL of CCK-8 solution was added to each well and incubated at 37°C for 2 hours. Absorbance at 450 nm was measured using a microplate reader. For DNA synthesis analysis, EdU incorporation assays were performed using a commercial EdU assay kit (Beyotime Biotechnology, catalog no. C0078S) following the manufacturer’s protocol. Cells were incubated with EdU (10 µM) for 2 hours, fixed, and stained for EdU incorporation. The percentage of EdU-positive cells was quantified under a fluorescence microscope. Cell apoptosis was analyzed by flow cytometry using the Annexin V-FITC/PI Apoptosis Detection Kit (Beyotime Biotechnology, catalog no. C1062S). Cells were harvested, washed twice with cold PBS, and resuspended in 1× binding buffer. Annexin V-FITC and propidium iodide (PI) were added, and the cells were incubated in the dark at room temperature for 15 minutes. Apoptotic cells were then quantified by flow cytometry (BD FACSCalibur), and data were analyzed using FlowJo software. In Vivo Xenograft and Metastasis Models Male Rag1 −/− mice (4–6 weeks old) were purchased from SPF (Beijing) Biotechnology Co., Ltd, eeks old), and were kept in an environment that was free of pathogens. Rag1 −/− mice were subcutaneously injected with 1×10 6 KYSE-520 cells transduced with shControl or shAPLN. Tumor volumes were measured every 3 days. For lung metastasis assays, 1×10 6 cells were injected via tail vein. After 4 weeks, lung metastatic nodules were counted. Animal experiments were approved by the Institutional Animal Care and Use Committee of Henan Cancer Hospital. Exosome Isolation and siRNA Delivery Exosomes were isolated from HEK293T cell supernatants by ultracentrifugation and characterized by nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM). APLN siRNA was loaded into exosomes via electroporation. Exosome-siRNA complexes were administered via intratumoral injection (50 µg per tumor) every 3 days for a total of 4 doses. Autophagic Flux Assay Autophagic flux was assessed using mRFP-GFP-LC3 tandem fluorescent-tagged assays. Cells were infected with mRFP-GFP-LC3 lentivirus and observed under a confocal microscope. LC3-positive puncta were quantified per cell. Autophagosome formation was further evaluated by TEM. Immunohistochemistry (IHC) Tissue microarrays of 60 ESCA specimens were acquired from Superbiotek (catalog no. ESC1602, Shanghai, China). The clinicopathologic details of the patients were shown in supplement file 1. Paraffin-embedded sections (4 µm thick) were deparaffinized in xylene and rehydrated through a graded ethanol series. Antigen retrieval was performed by heating the slides in citrate buffer (pH 6.0) at 95°C for 20 minutes. After cooling to room temperature, endogenous peroxidase activity was blocked using 3% hydrogen peroxide for 10 minutes. Sections were then incubated with primary antibody against APLN (Abcam, catalog no. ab230536, dilution 1:300) overnight at 4°C in a humidified chamber. After washing with PBS, the slides were incubated with HRP-conjugated secondary antibodies for 30 minutes at room temperature. Signal detection was performed using a DAB substrate kit, followed by counterstaining with hematoxylin. H-scores were calculated based on staining intensity and percentage of positive cells. Nomogram Construction and Statistical Analysis A prognostic nomogram was constructed using multivariate Cox regression analysis incorporating APLN expression and pathological stage. Model performance was evaluated using time-dependent ROC curves and calibration plots. Statistical analyses were performed using R and GraphPad Prism. P-values < 0.05 were considered statistically significant. Results APLN is a Robust Diagnostic and Prognostic Biomarker Overexpressed in Esophageal Carcinoma To identify potential oncogenic drivers in ESCA, we performed a multi-step integrative analysis. Differential gene expression analysis between tumor and normal tissues in the TCGA dataset revealed a number of significantly altered genes (Fig. 1 A). Besides, survival analysis identified 210 adverse prognostic genes (supplementary file 2). In parallel, we derived genome-wide CRISPR/Cas9 screening data from Wu et al.( 14 ), which identified genes essential for ESCA cell invasion and survival (Fig. 1 B, supplementary file 3). By intersecting these results with adverse prognostic genes from the TCGA and GEO databases, we identified APLN, ABRACL, and SNRPB as key candidates, with APLN emerging as a strong focus for further investigation (Fig. 1 C). Expression analysis across independent cohorts confirmed that APLN is significantly upregulated in ESCA. In both the GSE53624 and TCGA datasets, APLN levels were notably higher in tumor tissues compared to adjacent normal tissues (Fig. 1 D–E), and paired-sample comparisons reinforced this difference. Furthermore, pan-cancer analysis revealed elevated APLN expression in several malignancies, with particularly high levels observed in ESCA (Fig. 1 F), indicating a possible role in broader tumorigenic processes. We next evaluated the diagnostic potential of APLN. ROC curve analysis showed high diagnostic accuracy in distinguishing tumor from normal tissues, with AUCs of 0.935 in GSE53624 and 0.851 in TCGA (Fig. 1 G). To validate these findings at the protein level, we conducted immunohistochemical staining of APLN in 60 paired ESCA and normal tissues. Tumor tissues showed consistently stronger APLN staining (Fig. 1 H), which was confirmed by significantly higher H-scores (Fig. 1 I). ROC analysis of this cohort yielded an AUC of 0.871, further confirming the diagnostic potential of APLN (Fig. 1 J). To explore the mechanisms underlying APLN upregulation in esophageal carcinoma, we first analyzed its genetic alterations in ESCA samples. APLN showed amplification in approximately 2.6% of cases, indicating that copy number gain may contribute to its overexpression in a subset of patients (Figure S1 A). Next, we investigated whether epigenetic regulation plays a role in APLN expression. DNA methylation profiling across the APLN gene locus revealed multiple CpG sites, with several showing a negative correlation between methylation levels and gene expression (Figure S1 B). Notably, one CpG site (cg08610278) demonstrated a significant inverse correlation (r = − 0.208, p = 0.006), suggesting that hypomethylation at this site may relieve transcriptional repression and contribute to APLN overexpression (Figure S1 C). Taken together, these results indicate that both genomic amplification and epigenetic hypomethylation may underlie the elevated expression of APLN in ESCA. Although amplification occurs in a minority of cases, altered methylation appears to be a broader mechanism that may support the dysregulation of APLN during tumor development. These findings identify APLN as a robust biomarker candidate in ESCA. High APLN expression predicts poor prognosis in esophageal carcinoma patients To assess the clinical significance of APLN in ESCA, we analyzed its association with patient survival across three independent cohorts. In the GSE53624 cohort, patients with high APLN expression had significantly worse overall survival compared to those with low expression (HR = 1.87, 95% CI: 1.17–2.98, p = 0.009; Fig. 2 A). Risk stratification based on APLN expression clearly separated patients into high- and low-risk groups, with higher APLN levels correlating with shorter survival times. Consistent results were observed in the TCGA cohort. Patients with high APLN expression showed significantly poorer overall survival than those with low expression (HR = 1.90, 95% CI: 1.15–3.14, p = 0.012; Fig. 2 B). The survival curve again demonstrated that elevated APLN expression was associated with increased mortality risk. We further validated these findings in our own cohort of ESCA patients. High APLN expression was significantly linked to reduced overall survival (Fig. 2 C). The survival distribution plot showed a clear trend, with most high-APLN patients exhibiting short PFS and poor outcomes. Overall, data from all three cohorts consistently indicate that high APLN expression is associated with unfavorable prognosis in ESCA. These results support the utility of APLN as a prognostic biomarker for predicting survival outcomes in patients with esophageal carcinoma. APLN knockdown suppresses esophageal carcinoma cell proliferation and tumor growth in vitro and in vivo To investigate the functional role of APLN in ESCA, we first examined its expression in various ESCA cell lines. APLN expression was found to be highest in the KYSE-520 cell line, which was selected for subsequent functional assays (Fig. 3 A). We established APLN-knockdown KYSE-520 cells using shRNA. Knockdown efficiency was confirmed at both mRNA and protein levels, with a significant reduction in APLN expression compared to control cells (Fig. 3 B). Cell viability assays and EdU assays revealed that APLN depletion markedly suppressed cell proliferation (Fig. 3 C and D). Furthermore, APLN knockdown led to increased cell death, as evidenced by elevated apoptosis rates detected by Annexin V/PI staining (Fig. 3 E). To evaluate the effects of APLN in vivo, we performed subcutaneous xenograft experiments in nude mice. Tumors derived from APLN-knockdown cells were significantly smaller in size and grew at a slower rate compared to the control group (Fig. 3 F). Both tumor volume and final tumor weight were markedly reduced in the APLN-depleted group (Fig. 3 G). We further assessed the metastatic potential of APLN in a lung metastasis model. Mice injected with sh-APLN cells developed fewer and smaller metastatic nodules compared to controls, as shown by macroscopic lung examination and histological analysis (Fig. 3 H). Quantitative analysis confirmed a significant reduction in the number of metastatic nodules in the APLN-knockdown group (Fig. 3 I). These results demonstrate that APLN plays a critical role in promoting ESCA cell proliferation, survival, tumor growth, and metastasis, highlighting its potential as a therapeutic target. APLN depletion sensitizes esophageal carcinoma cells to cisplatin-induced cell death To investigate whether APLN influences chemotherapy sensitivity in ESCA, we analyzed gene expression and cisplatin sensitivity data from the Cancer Cell Line Encyclopedia (CCLE) database. Specifically, we retrieved APLN expression profiles and corresponding cisplatin IC50 values for esophageal carcinoma cell lines. Correlation analysis revealed a positive association between APLN expression and cisplatin resistance (r = 0.38, p = 0.04), suggesting that elevated APLN expression may contribute to drug resistance (Fig. 4 A). Notably, the KYSE-520 cell line exhibited the highest APLN expression and the highest cisplatin IC50 value among the analyzed ESCA cell lines, highlighting its suitability as an in vitro model for functional studies. Next, we assessed the effect of APLN knockdown on cisplatin sensitivity in KYSE-520 cells. Dose–response analysis showed that APLN-depleted cells (sh-APLN) were significantly more sensitive to cisplatin than control cells, with a reduced IC50 value of 21.5 µM compared to 37.2 µM in the control group (Fig. 4 B), indicating that APLN depletion enhances cisplatin cytotoxicity. Flow cytometry analysis further demonstrated that APLN knockdown increased apoptosis in ESCA cells, and this effect was markedly enhanced when combined with cisplatin treatment (Fig. 4 C). Together, these results indicate that APLN mediates cisplatin resistance in ESCA, and that targeting APLN enhances chemotherapy sensitivity, providing a potential therapeutic strategy for improving treatment outcomes in esophageal carcinoma. APLN promotes autophagic flux and mediates chemoresistance in esophageal carcinoma cells To explore the potential mechanisms by which APLN contributes to cisplatin resistance in ESCA, we performed gene set enrichment analysis (GSEA) using the GSE53624 dataset. The results revealed that high APLN expression was significantly associated with enrichment of autophagy-related pathways, suggesting a link between APLN and autophagy regulation (Fig. 5 A). Previous studies have shown that autophagy plays a dual role in cancer, where sustained autophagic flux can promote tumor cell survival under stress conditions, including chemotherapy exposure. Based on these findings, we hypothesized that APLN may contribute to chemoresistance through the regulation of autophagy. To validate this, we analyzed correlations between APLN expression and key autophagy-related genes (ATG12, ATG101, ATG4A, and ATG5) in both GSE53624 and TCGA datasets. APLN expression was positively correlated with these autophagy genes (Fig. 5 B), indicating that APLN may promote autophagic activity. Besides, RFP-GFP-LC3 tandem fluorescent-tagged assays demonstrated that cisplatin treatment induced autophagic flux in control cells, as shown by abundant LC3-positive puncta. However, APLN knockdown markedly reduced the number of autophagolysosomes, suggesting impaired autophagic flux (Fig. 5 C–D). Transmission electron microscopy (TEM) further confirmed reduced autophagosome formation in APLN-depleted cells (Fig. 5 E). Collectively, these results indicate that APLN maintains autophagic flux to promote chemoresistance in ESCA cells, and its depletion sensitizes cells to cisplatin-induced apoptosis by impairing autophagy. Exosome-mediated delivery of APLN siRNA suppresses tumor growth without systemic toxicity Exosomes have gained attention as ideal nanocarriers for therapeutic delivery due to their natural biocompatibility, low immunogenicity, and intrinsic ability to target tumor cells. To evaluate the therapeutic potential of targeting APLN in vivo, we designed an exosome-based delivery system to administer APLN siRNA (siAPLN) into ESCA xenografts. The workflow included exosome isolation, siRNA loading, and quality control prior to in vivo administration (Fig. 6 A). Nanoparticle tracking analysis (NTA) confirmed that the size distribution of exosomes was not altered by siRNA loading (Fig. 6 B). Transmission electron microscopy (TEM) further showed that both control and siAPLN-loaded exosomes exhibited typical cup-shaped morphology (Fig. 6 C). We then assessed the anti-tumor efficacy of exosome-delivered siAPLN in Rag1 -/- mice bearing ESCA xenografts. Exosome preparations were administered via intratumoral injection. Tumors treated with siAPLN-loaded exosomes were visibly smaller compared to the control group (Fig. 6 D). Tumor growth curves demonstrated a significant reduction in tumor volume in the siAPLN-treated group (Fig. 6 E), and tumor weights were markedly lower at the endpoint (Fig. 6 F). These findings indicate that exosome-mediated delivery of siAPLN effectively suppresses ESCA tumor growth in vivo. Importantly, the administration of siAPLN-loaded exosomes did not result in significant systemic toxicity. There were no significant differences in body weight between treatment groups (Fig. 6 G). Histological examination of major organs (liver, lung, kidney) showed no evident tissue damage or pathological changes (Fig. 6 H). Moreover, serum levels of liver and kidney function markers, including AST, ALP, and creatinine, remained unchanged (Fig. 6 I), suggesting good biosafety of the exosome-siRNA delivery system. Collectively, these results demonstrate that exosome-mediated APLN silencing effectively inhibits ESCA tumor growth in vivo with minimal off-target toxicity, supporting its potential as a therapeutic strategy. APLN-based nomogram model predicts survival outcomes in esophageal carcinoma patients To evaluate the clinical utility of APLN as a prognostic biomarker, we developed a nomogram that integrated APLN expression with pathological stage to predict 1-year and 3-year overall survival probabilities in ESCA patients (Fig. 7 A). Each variable was assigned a specific score, and the total score corresponded to predicted survival probabilities, providing a quantitative tool for individualized risk assessment. The predictive performance of the nomogram was assessed using time-dependent ROC curve analysis. APLN expression alone achieved an AUC of 0.671 for 1-year survival prediction and 0.593 for 3-year survival (Fig. 7 B, top). When combined into the nomogram risk score, the model showed improved predictive accuracy, with AUC values of 0.678 for 1-year survival and 0.814 for 3-year survival (Fig. 7 B, bottom), indicating good prognostic discrimination. Kaplan-Meier survival analysis further demonstrated the prognostic significance of the nomogram. Patients stratified into high-risk and low-risk groups based on the nomogram score exhibited significantly different survival outcomes. The high-risk group had markedly poorer overall survival compared to the low-risk group (HR = 3.87, 95% CI: 2.14–6.99, p < 0.001; Fig. 7 C). Calibration plots were generated to assess the agreement between predicted and observed survival probabilities. The 1-year and 3-year calibration curves showed that the nomogram-predicted survival closely matched actual outcomes, indicating good calibration of the model (Fig. 7 D). Together, these results suggest that APLN expression, when combined with clinical stage in a nomogram model, can effectively predict survival outcomes in ESCA patients, providing a valuable tool for personalized prognostic assessment. Discussion In this study, we identified APLN as a novel prognostic biomarker that promotes esophageal carcinoma progression. By integrating data from TCGA, GEO, and CRISPR library screening, we found that APLN is significantly upregulated in ESCA and associated with poor patient prognosis. Functional experiments demonstrated that APLN knockdown inhibited tumor cell proliferation, induced apoptosis, and sensitized ESCA cells to cisplatin in vitro and in vivo. Mechanistically, we showed that APLN sustains autophagic flux, contributing to chemotherapy resistance. Moreover, exosome-mediated delivery of APLN siRNA effectively suppressed tumor growth in mouse models. Finally, we constructed a prognostic nomogram combining APLN expression and clinical stage, which accurately predicted patient survival outcomes. Our findings align with previous studies highlighting the dual role of autophagy in cancer. While autophagy can suppress tumor initiation, it often supports tumor cell survival under stress, including chemotherapy exposure( 15 – 17 ). We demonstrated that APLN positively regulates autophagy-related genes (ATG12, ATG101, ATG4A, ATG5) and maintains autophagic flux, which in turn promotes ESCA cell survival and chemoresistance. Consistent with reports in other cancers where APLN is involved in tumor progression and therapy resistance, our study expands these observations to ESCA, providing new evidence for APLN's oncogenic role. Exosomes have emerged as promising natural nanocarriers for therapeutic delivery due to their inherent biocompatibility, low immunogenicity, and efficient cellular uptake( 18 – 20 ). Unlike synthetic nanoparticles or viral vectors, exosomes can naturally fuse with recipient cell membranes, enhancing the targeted delivery of therapeutic molecules while minimizing off-target effects and systemic toxicity( 21 ). In the context of tumor therapy, exosome-mediated delivery offers the advantage of improved stability in circulation and the ability to penetrate the dense tumor microenvironment. In our study, we utilized exosomes to deliver APLN siRNA directly into tumor tissues via intratumoral injection. This approach effectively suppressed tumor growth without causing adverse effects on major organs or systemic biochemical markers. The successful knockdown of APLN through exosomal delivery underscores the feasibility of using exosomes as a safe and efficient platform for RNA interference-based cancer therapy. Our findings not only provide proof-of-concept evidence for APLN-targeted exosome therapy in ESCA but also highlight the broader potential of exosome-based strategies for overcoming the limitations of conventional drug delivery systems in solid tumors. The most significant academic contribution of this study is the comprehensive demonstration of APLN as both a prognostic biomarker and a therapeutic target in ESCA. We not only revealed the molecular mechanism by which APLN enhances tumor progression through autophagy regulation but also provided a feasible therapeutic strategy by delivering APLN siRNA via exosomes. Furthermore, the nomogram model we developed has potential clinical application for individualized survival prediction in ESCA patients, filling a gap in prognostic tools. However, this study has several limitations. First, the in vivo validation was conducted in immunodeficient mice, which does not fully represent the tumor-immune microenvironment. Second, while we identified APLN’s role in autophagy, the precise upstream signaling pathways remain to be elucidated. In future studies, we aim to explore the interaction of APLN with tumor immunity and its potential in combination therapies with immune checkpoint inhibitors or autophagy inhibitors. Additionally, clinical validation of the nomogram in larger, independent ESCA patient cohorts is warranted. In summary, our study not only highlights the oncogenic role of APLN in esophageal carcinoma but also provides compelling evidence that exosome-based siRNA delivery is a promising, safe, and effective therapeutic approach. This strategy holds significant potential to overcome the limitations of conventional treatments and paves the way for the clinical translation of RNA interference therapies in solid tumors. Declarations Acknowledgements We are grateful to the Natural Science Foundation of Henan Province and Technology Innovation Excellent Youth Talent Project for providing financial support for this research. Funding This study was funded by the Henan Provincial Middle-aged and Young People's Health Science, Technology Innovation Excellent Youth Talent Project (YXKC2021053), Medical Science and Technique Foundation of Henan Province (No. LHGJ20210186), Natural Science Foundation of Henan Province (No. 242300420091 for B.-B. C), and Medical Science and Technique Foundation of Henan Province (No. LHGJ20210201 for J.Z). Contributions Conceptualization, Shegan Gao, and Xiaobing Chen; formal analysis, Weifeng Xu, and Caiyun Nie; investigation, Weifeng Xu and Zhen Liu; methodology, Guanghui Liang, and Penghui Yu; writing—original draft, Weifeng Xu, Huifang Lv, and Beibei Chen; revise and editing, Jianzheng Wang, Saiqi Wang, Jing Zhao, and Yunduan He. All authors have confirmed and agreed to the published version of the manuscript. Competing interests The authors declare no competing interests. Ethics All animal experiments were approved by the Institutional Animal Care and Use Committee of Henan Cancer Hospital. Consent to participate Not applicable. Consent to publish declaration All the listed authors have participated in the study, and have approved the manuscript. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. 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(B) Correlation heatmap between APLN expression and DNA methylation levels at CpG sites. (C) Scatter plot showing a significant inverse correlation between APLN expression and cg08610278 methylation. Cite Share Download PDF Status: Published Journal Publication published 07 Jan, 2026 Read the published version in Functional & Integrative Genomics → Version 1 posted Editorial decision: Revision requested 25 Oct, 2025 Reviews received at journal 08 Oct, 2025 Reviewers agreed at journal 04 Oct, 2025 Reviewers agreed at journal 02 Oct, 2025 Reviewers agreed at journal 20 Sep, 2025 Reviewers invited by journal 16 Sep, 2025 Editor assigned by journal 15 Sep, 2025 Submission checks completed at journal 15 Sep, 2025 First submitted to journal 11 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-7592740","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":518368564,"identity":"02eb5ef2-882d-46d0-88ff-45704ff514e1","order_by":0,"name":"Weifeng Xu","email":"","orcid":"","institution":"Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Weifeng","middleName":"","lastName":"Xu","suffix":""},{"id":518368565,"identity":"75ebb7aa-5eee-4b27-8098-824e401332ee","order_by":1,"name":"Caiyun Nie","email":"","orcid":"","institution":"Affiliated Cancer Hospital 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1","display":"","copyAsset":false,"role":"figure","size":927090,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of APLN as a key oncogene in esophageal carcinoma (ESCA).\u003cbr\u003e\n \u003c/strong\u003e(A) Differentially expressed genes between ESCA tumor and normal tissues in the TCGA cohort.\u003cbr\u003e\n(B) Genome-wide CRISPR/Cas9 screening data from Wu et al. identifying genes essential for ESCA cell invasion.\u003cbr\u003e\n(C) Venn diagram showing the intersection of differentially expressed genes, prognostically adverse genes, and CRISPR screening hits, with APLN identified as a key gene.\u003cbr\u003e\n(D, E) APLN expression levels in ESCA tumor versus normal tissues in GEO (GSE53624) and TCGA datasets. P-values were determined using a Wilcoxon rank-sum test (D) or paired sample t-text (E) (**p \u0026lt; 0.01, ***p \u0026lt; 0.001).\u003cbr\u003e\n(F) Pan-cancer analysis of APLN expression across multiple tumor types in TCGA database. Red represented APLN over-expression.\u003cbr\u003e\n(G) ROC curves demonstrating the diagnostic performance of APLN in GSE53624 and TCGA cohorts.\u003cbr\u003e\n(H) Immunohistochemical staining of APLN in 60 paired ESCA tumor and adjacent normal tissues.\u003cbr\u003e\n(I) Quantification of APLN H-scores in tumor versus normal tissues. P-values were determined using a paired sample t-text (E) (***p \u0026lt; 0.001).\u003cbr\u003e\n(J) ROC curve analysis of APLN protein expression for ESCA diagnosis.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/1e039e82db35f19acea6bd7c.png"},{"id":92126391,"identity":"a856a5ce-7ca2-4041-92ac-6efd74adea33","added_by":"auto","created_at":"2025-09-25 01:33:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":847841,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHigh APLN expression predicts poor prognosis in ESCA patients.\u003c/strong\u003e\u003cbr\u003e\n(A) Kaplan-Meier survival curve of overall survival in GSE53624 cohort stratified by APLN expression.\u003cbr\u003e\n(B) Kaplan-Meier survival curve of overall survival in TCGA cohort stratified by APLN expression.\u003cbr\u003e\n(C) Kaplan-Meier survival curve of overall survival in our ESCA cohort based on APLN expression.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/e57eb363f7406839249b26fa.png"},{"id":92126398,"identity":"87ed81d5-f326-49b4-b9fb-360c4a786110","added_by":"auto","created_at":"2025-09-25 01:33:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1052929,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAPLN promotes ESCA cell proliferation and tumor growth.\u003cbr\u003e\n \u003c/strong\u003e(A) APLN mRNA expression in ESCA cell lines. Data from CCLE database.\u003cbr\u003e\n(B) Validation of APLN knockdown efficiency by qRT-PCR and western blot. P-value was determined using unpaired two-tailed Student’s t-test (***p \u0026lt; 0.001).\u003cbr\u003e\n(C) Cell viability curves of sh-control and sh-APLN cells. P-value was determined using unpaired two-tailed Student’s t-test (***p \u0026lt; 0.001).\u003cbr\u003e\n(D) EdU proliferation assay showing reduced DNA synthesis upon APLN knockdown. P-value was determined using unpaired two-tailed Student’s t-test (***p \u0026lt; 0.001).\u003cbr\u003e\n(E) Flow cytometric analysis of apoptosis in sh-control and sh-APLN cells. P-value was determined using unpaired two-tailed Student’s t-test (***p \u0026lt; 0.001).\u003cbr\u003e\n(F) Representative images of tumor xenografts formed by sh-control and sh-APLN cells.\u003cbr\u003e\n(G) Tumor volume growth curves in xenograft-bearing mice.\u003cbr\u003e\n(H) Tumor weight comparison between groups. P-value was determined using unpaired two-tailed Student’s t-test (**p \u0026lt; 0.01).\u003cbr\u003e\n(I) Quantification of lung metastatic nodules in mice injected with sh-control or sh-APLN cells. P-value was determined using unpaired two-tailed Student’s t-test (**p \u0026lt; 0.01).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/dc715586be1cd0981940e761.png"},{"id":92127208,"identity":"0304f664-11ff-4ed5-a53e-56a5118e5006","added_by":"auto","created_at":"2025-09-25 01:49:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":582989,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAPLN knockdown enhances cisplatin sensitivity in ESCA cells.\u003cbr\u003e\n \u003c/strong\u003e(A) Correlation between APLN expression and cisplatin IC50 values in ESCA cell lines from CCLE database, highlighting KYSE520 with highest APLN and IC50.\u003cbr\u003e\n(B) Dose-response curves showing reduced cisplatin IC50 upon APLN knockdown in KYSE-520 cells.\u003cbr\u003e\n(C) Flow cytometry analysis of apoptosis in cells treated with cisplatin, sh-APLN, or their combination. P-value was determined using unpaired two-tailed Student’s t-test (**p \u0026lt; 0.01, ***p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/fd20323f3e3a39c2ce09b8ef.png"},{"id":92126402,"identity":"3ecf1c3c-bbaa-49e8-a355-94867060d872","added_by":"auto","created_at":"2025-09-25 01:33:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":395391,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAPLN promotes autophagic flux to mediate chemoresistance in ESCA cells.\u003cbr\u003e\n \u003c/strong\u003e(A) GSEA plots showing enrichment of autophagy-related pathways in high-APLN expression group.\u003cbr\u003e\n(B) Correlation heatmap of APLN expression with autophagy-related genes (ATG12, ATG101, ATG4A, ATG5).\u003cbr\u003e\n(C) RFP-GFP-LC3 tandem fluorescent assays showing impaired autophagic flux upon APLN knockdown with cisplatin treatment (20μM).\u003cbr\u003e\n(D) Quantification of LC3-positive puncta per cell. P-value was determined using unpaired two-tailed Student’s t-test (**p \u0026lt; 0.01).\u003cbr\u003e\n(E) Transmission electron microscopy images illustrating decreased autophagosome formation in sh-APLN cells with cisplatin treatment (20μM).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/67576412f8e36de70b4ff627.png"},{"id":92127210,"identity":"9afe0a35-ea4e-4747-88f1-7e511485f8c9","added_by":"auto","created_at":"2025-09-25 01:49:16","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":517032,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIntratumoral exosome-mediated delivery of APLN siRNA suppresses ESCA tumor growth without systemic toxicity.\u003cbr\u003e\n \u003c/strong\u003e(A) Workflow of exosome isolation, siRNA loading, and in vivo administration.\u003cbr\u003e\n(B) Nanoparticle tracking analysis of exosome size distribution pre- and post-siRNA loading. \u003cbr\u003e\n(C) TEM images showing morphology of control and siAPLN-loaded exosomes.\u003cbr\u003e\n(D) Representative images of ESCA xenografts from control and siAPLN-treated groups. Exosome-siRNA complexes were administered via intratumoral injection (50 μg per tumor) every 3 days for a total of 4 doses.\u003c/p\u003e\n\u003cp\u003e(E) Tumor growth curves following intratumoral exosome treatment. P-value was determined using unpaired two-tailed Student’s t-test (***p \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e(F) Tumor weight comparison at endpoint. P-value was determined using unpaired two-tailed Student’s t-test (**p \u0026lt; 0.01).\u003cbr\u003e\n(G) Body weight monitoring of mice during treatment. P-value was determined using unpaired two-tailed Student’s t-test (ns, p \u0026gt; 0.05).\u003cbr\u003e\n(H) H\u0026amp;E staining of major organs showing no pathological abnormalities.\u003cbr\u003e\n(I) Serum biochemical analyses (AST, ALP, creatinine) indicating no systemic toxicity. P-value was determined using unpaired two-tailed Student’s t-test (ns, p \u0026gt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/bb2081b20a2e2cc7514ea212.png"},{"id":92126407,"identity":"2fcda994-17bd-49c5-88b8-a33d28730c7e","added_by":"auto","created_at":"2025-09-25 01:33:16","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":728076,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAPLN-based nomogram accurately predicts survival outcomes in ESCA patients.\u003c/strong\u003e\u003cbr\u003e\n (A) Nomogram integrating APLN expression and pathological stage to predict 1-year and 3-year survival probabilities.\u003cbr\u003e\n(B) Time-dependent ROC curves for survival prediction using APLN expression and nomogram risk score.\u003cbr\u003e\n(C) Kaplan-Meier survival curves stratified by nomogram-defined risk groups.\u003cbr\u003e\n(D) Calibration plots assessing agreement between predicted and actual survival outcomes.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/ee5d82527dab69dce55b6095.png"},{"id":100069384,"identity":"f2487683-22d4-42f5-bc7f-689c18c55157","added_by":"auto","created_at":"2026-01-12 16:13:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6165002,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/428abf71-5c49-42fa-8b80-dd293a3b665b.pdf"},{"id":92126394,"identity":"434d4866-bb3b-419b-a5c9-43fc02444673","added_by":"auto","created_at":"2025-09-25 01:33:15","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":419485,"visible":true,"origin":"","legend":"","description":"","filename":"supplementfile1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/917c9783d96806c7650af247.xlsx"},{"id":92127976,"identity":"4726e397-3d7e-440d-aa9c-46e87a22d8a8","added_by":"auto","created_at":"2025-09-25 01:57:15","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":24856,"visible":true,"origin":"","legend":"","description":"","filename":"supplementfile2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/ced0450b174088a3e80db2f8.xlsx"},{"id":92127134,"identity":"edf3099f-5d13-41a5-afec-c3a4a8ce0473","added_by":"auto","created_at":"2025-09-25 01:41:15","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":61614,"visible":true,"origin":"","legend":"","description":"","filename":"supplementfile3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/adcc789324c8ba52e3cfd25d.xlsx"},{"id":92126408,"identity":"7af5e54c-433d-4b63-8f50-465e9209ab3d","added_by":"auto","created_at":"2025-09-25 01:33:16","extension":"zip","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":110828,"visible":true,"origin":"","legend":"","description":"","filename":"uncroppedblotsimage.zip","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/fe50122156b84c9609e0f93f.zip"},{"id":92127149,"identity":"015343dd-d3dc-4864-b479-101120faca7e","added_by":"auto","created_at":"2025-09-25 01:41:16","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":182967,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S1. Genomic and epigenetic mechanisms contribute to APLN overexpression in ESCA.\u003cbr\u003e\n \u003c/strong\u003e(A) Copy number variation (CNV) profile of APLN in ESCA from TCGA data.\u003cbr\u003e\n(B) Correlation heatmap between APLN expression and DNA methylation levels at CpG sites.\u003cbr\u003e\n(C) Scatter plot showing a significant inverse correlation between APLN expression and cg08610278 methylation.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7592740/v1/f1e23c3b8793d5f1cabe1b5b.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"APLN, a novel prognostic biomarker, contributes to esophageal carcinoma development","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEsophageal carcinoma is one of the most aggressive gastrointestinal malignancies, ranking as the sixth leading cause of cancer-related deaths worldwide(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Despite advances in surgical techniques, radiotherapy, and chemotherapy, the overall survival rate of ESCA remains dismal, with a 5-year survival rate of less than 20%(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Tumor recurrence and chemoresistance are the main reasons for treatment failure, underscoring the urgent need to identify novel biomarkers and therapeutic targets to improve prognosis and guide personalized therapy in ESCA patients.\u003c/p\u003e\u003cp\u003eAs the principal agonist for the G protein-coupled receptor APJ, it forms the apelin/APJ signaling axis, a critical regulator of diverse physiological processes spanning cardiovascular homeostasis, energy metabolism, angiogenesis, and neuroendocrine functions(\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). APLN signaling primarily activates Gαi/o proteins upon binding APJ, inhibiting adenylate cyclase and modulating key downstream pathways: the PI3K/Akt/mTOR cascade (promoting cell survival, glucose uptake, and angiogenesis), ERK1/2 MAPK (regulating proliferation and migration), and eNOS/NO synthesis (mediating vasodilation and cardioprotection) (\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Consequently, dysregulation of APLN/APJ signaling is implicated in cardiometabolic diseases (heart failure, pulmonary hypertension, diabetes), tumor angiogenesis (e.g., in hepatocellular carcinoma), and reproductive dysfunction (e.g., blood-testis barrier disruption in diabetes)(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). However, the role of APLN in esophageal carcinoma remains poorly understood, and its potential as a prognostic biomarker and therapeutic target in ESCA has not been systematically investigated.\u003c/p\u003e\u003cp\u003eIn this study, we aimed to investigate the biological function and clinical significance of APLN in ESCA. By integrating multi-omics data from public databases and functional assays in vitro and in vivo, we explored the oncogenic role of APLN and its impact on autophagy-mediated chemoresistance. We further evaluated the therapeutic potential of exosome-mediated APLN siRNA delivery and established a prognostic nomogram model incorporating APLN expression for individualized survival prediction in ESCA patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData Collection and Bioinformatic Analysis\u003c/h2\u003e\u003cp\u003eGene expression and clinical data for ESCA were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GSE53624) databases. Differentially expressed genes (DEGs) between tumor and normal tissues were identified using the \u0026ldquo;limma\u0026rdquo; R package with |log2FC| \u0026gt;1 and adjusted p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Prognostic genes were determined by univariate Cox regression analysis. Genome-wide CRISPR/Cas9 screening data related to ESCA cell invasion were retrieved from the study by Wu et al(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Genes at the intersection of DEGs, prognostic genes, and CRISPR hits were selected for further investigation. DNA methylation and copy number variation (CNV) data were analyzed using cBioPortal and UCSC Xena. Correlation analyses and gene set enrichment analysis (GSEA) were conducted using R software.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCell Lines and Transfection\u003c/h3\u003e\n\u003cp\u003eHuman esophageal carcinoma cell lines KYSE-520 (catalog no. C6510) were purchased from Beyotime Biotechnology (Beijing, China). All cell lines were authenticated by short tandem repeat (STR) profiling to ensure their identity and confirmed to be free of mycoplasma contamination. Cells were cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum at 37\u0026deg;C in a humidified incubator with 5% CO2.\u003c/p\u003e\u003cp\u003eAPLN knockdown was achieved using lentiviral short hairpin RNA (shRNA). The specific shRNA sequence targeting APLN was: shAPLN: 5'-TCTCCCATAAGGGACCCAT-3'. Lentiviral particles encoding shAPLN or a scrambled shControl sequence were produced and used to infect ESCA cells. Stable clones were selected using puromycin (2 \u0026micro;g/mL) for 7 days prior to downstream assays.\u003c/p\u003e\n\u003ch3\u003eCell Proliferation and Apoptosis Assays\u003c/h3\u003e\n\u003cp\u003eCell proliferation was evaluated using the Cell Counting Kit-8 (CCK-8, Beyotime Biotechnology, catalog no. C0037). Briefly, ESCA cells were seeded in 96-well plates at a density of 3\u0026times;10^3 cells per well. At indicated time points (0, 24, 48, 72, and 96 hours), 10 \u0026micro;L of CCK-8 solution was added to each well and incubated at 37\u0026deg;C for 2 hours. Absorbance at 450 nm was measured using a microplate reader.\u003c/p\u003e\u003cp\u003eFor DNA synthesis analysis, EdU incorporation assays were performed using a commercial EdU assay kit (Beyotime Biotechnology, catalog no. C0078S) following the manufacturer\u0026rsquo;s protocol. Cells were incubated with EdU (10 \u0026micro;M) for 2 hours, fixed, and stained for EdU incorporation. The percentage of EdU-positive cells was quantified under a fluorescence microscope.\u003c/p\u003e\u003cp\u003eCell apoptosis was analyzed by flow cytometry using the Annexin V-FITC/PI Apoptosis Detection Kit (Beyotime Biotechnology, catalog no. C1062S). Cells were harvested, washed twice with cold PBS, and resuspended in 1\u0026times; binding buffer. Annexin V-FITC and propidium iodide (PI) were added, and the cells were incubated in the dark at room temperature for 15 minutes. Apoptotic cells were then quantified by flow cytometry (BD FACSCalibur), and data were analyzed using FlowJo software.\u003c/p\u003e\n\u003ch3\u003eIn Vivo Xenograft and Metastasis Models\u003c/h3\u003e\n\u003cp\u003eMale Rag1\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice (4\u0026ndash;6 weeks old) were purchased from SPF (Beijing) Biotechnology Co., Ltd, eeks old), and were kept in an environment that was free of pathogens. Rag1\u003csup\u003e\u0026minus;/\u0026minus;\u003c/sup\u003e mice were subcutaneously injected with 1\u0026times;10\u003csup\u003e6\u003c/sup\u003e KYSE-520 cells transduced with shControl or shAPLN. Tumor volumes were measured every 3 days. For lung metastasis assays, 1\u0026times;10\u003csup\u003e6\u003c/sup\u003e cells were injected via tail vein. After 4 weeks, lung metastatic nodules were counted. Animal experiments were approved by the Institutional Animal Care and Use Committee of Henan Cancer Hospital.\u003c/p\u003e\n\u003ch3\u003eExosome Isolation and siRNA Delivery\u003c/h3\u003e\n\u003cp\u003eExosomes were isolated from HEK293T cell supernatants by ultracentrifugation and characterized by nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM). APLN siRNA was loaded into exosomes via electroporation. Exosome-siRNA complexes were administered via intratumoral injection (50 \u0026micro;g per tumor) every 3 days for a total of 4 doses.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eAutophagic Flux Assay\u003c/h2\u003e\u003cp\u003eAutophagic flux was assessed using mRFP-GFP-LC3 tandem fluorescent-tagged assays. Cells were infected with mRFP-GFP-LC3 lentivirus and observed under a confocal microscope. LC3-positive puncta were quantified per cell. Autophagosome formation was further evaluated by TEM.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eImmunohistochemistry (IHC)\u003c/h3\u003e\n\u003cp\u003eTissue microarrays of 60 ESCA specimens were acquired from Superbiotek (catalog no. ESC1602, Shanghai, China). The clinicopathologic details of the patients were shown in supplement file 1. Paraffin-embedded sections (4 \u0026micro;m thick) were deparaffinized in xylene and rehydrated through a graded ethanol series. Antigen retrieval was performed by heating the slides in citrate buffer (pH 6.0) at 95\u0026deg;C for 20 minutes. After cooling to room temperature, endogenous peroxidase activity was blocked using 3% hydrogen peroxide for 10 minutes. Sections were then incubated with primary antibody against APLN (Abcam, catalog no. ab230536, dilution 1:300) overnight at 4\u0026deg;C in a humidified chamber. After washing with PBS, the slides were incubated with HRP-conjugated secondary antibodies for 30 minutes at room temperature. Signal detection was performed using a DAB substrate kit, followed by counterstaining with hematoxylin. H-scores were calculated based on staining intensity and percentage of positive cells.\u003c/p\u003e\n\u003ch3\u003eNomogram Construction and Statistical Analysis\u003c/h3\u003e\n\u003cp\u003eA prognostic nomogram was constructed using multivariate Cox regression analysis incorporating APLN expression and pathological stage. Model performance was evaluated using time-dependent ROC curves and calibration plots. Statistical analyses were performed using R and GraphPad Prism. P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eAPLN is a Robust Diagnostic and Prognostic Biomarker Overexpressed in Esophageal Carcinoma\u003c/h2\u003e\u003cp\u003eTo identify potential oncogenic drivers in ESCA, we performed a multi-step integrative analysis. Differential gene expression analysis between tumor and normal tissues in the TCGA dataset revealed a number of significantly altered genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Besides, survival analysis identified 210 adverse prognostic genes (supplementary file 2). In parallel, we derived genome-wide CRISPR/Cas9 screening data from Wu et al.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), which identified genes essential for ESCA cell invasion and survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, supplementary file 3). By intersecting these results with adverse prognostic genes from the TCGA and GEO databases, we identified APLN, ABRACL, and SNRPB as key candidates, with APLN emerging as a strong focus for further investigation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eExpression analysis across independent cohorts confirmed that APLN is significantly upregulated in ESCA. In both the GSE53624 and TCGA datasets, APLN levels were notably higher in tumor tissues compared to adjacent normal tissues (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD\u0026ndash;E), and paired-sample comparisons reinforced this difference. Furthermore, pan-cancer analysis revealed elevated APLN expression in several malignancies, with particularly high levels observed in ESCA (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF), indicating a possible role in broader tumorigenic processes.\u003c/p\u003e\u003cp\u003eWe next evaluated the diagnostic potential of APLN. ROC curve analysis showed high diagnostic accuracy in distinguishing tumor from normal tissues, with AUCs of 0.935 in GSE53624 and 0.851 in TCGA (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG). To validate these findings at the protein level, we conducted immunohistochemical staining of APLN in 60 paired ESCA and normal tissues. Tumor tissues showed consistently stronger APLN staining (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eH), which was confirmed by significantly higher H-scores (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eI). ROC analysis of this cohort yielded an AUC of 0.871, further confirming the diagnostic potential of APLN (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eJ).\u003c/p\u003e\u003cp\u003eTo explore the mechanisms underlying APLN upregulation in esophageal carcinoma, we first analyzed its genetic alterations in ESCA samples. APLN showed amplification in approximately 2.6% of cases, indicating that copy number gain may contribute to its overexpression in a subset of patients (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNext, we investigated whether epigenetic regulation plays a role in APLN expression. DNA methylation profiling across the APLN gene locus revealed multiple CpG sites, with several showing a negative correlation between methylation levels and gene expression (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB). Notably, one CpG site (cg08610278) demonstrated a significant inverse correlation (r = \u0026minus;\u0026thinsp;0.208, p\u0026thinsp;=\u0026thinsp;0.006), suggesting that hypomethylation at this site may relieve transcriptional repression and contribute to APLN overexpression (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003eTaken together, these results indicate that both genomic amplification and epigenetic hypomethylation may underlie the elevated expression of APLN in ESCA. Although amplification occurs in a minority of cases, altered methylation appears to be a broader mechanism that may support the dysregulation of APLN during tumor development. These findings identify APLN as a robust biomarker candidate in ESCA.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eHigh APLN expression predicts poor prognosis in esophageal carcinoma patients\u003c/h2\u003e\u003cp\u003eTo assess the clinical significance of APLN in ESCA, we analyzed its association with patient survival across three independent cohorts. In the GSE53624 cohort, patients with high APLN expression had significantly worse overall survival compared to those with low expression (HR\u0026thinsp;=\u0026thinsp;1.87, 95% CI: 1.17\u0026ndash;2.98, p\u0026thinsp;=\u0026thinsp;0.009; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Risk stratification based on APLN expression clearly separated patients into high- and low-risk groups, with higher APLN levels correlating with shorter survival times.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eConsistent results were observed in the TCGA cohort. Patients with high APLN expression showed significantly poorer overall survival than those with low expression (HR\u0026thinsp;=\u0026thinsp;1.90, 95% CI: 1.15\u0026ndash;3.14, p\u0026thinsp;=\u0026thinsp;0.012; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). The survival curve again demonstrated that elevated APLN expression was associated with increased mortality risk.\u003c/p\u003e\u003cp\u003eWe further validated these findings in our own cohort of ESCA patients. High APLN expression was significantly linked to reduced overall survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). The survival distribution plot showed a clear trend, with most high-APLN patients exhibiting short PFS and poor outcomes.\u003c/p\u003e\u003cp\u003eOverall, data from all three cohorts consistently indicate that high APLN expression is associated with unfavorable prognosis in ESCA. These results support the utility of APLN as a prognostic biomarker for predicting survival outcomes in patients with esophageal carcinoma.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eAPLN knockdown suppresses esophageal carcinoma cell proliferation and tumor growth in vitro and in vivo\u003c/h2\u003e\u003cp\u003eTo investigate the functional role of APLN in ESCA, we first examined its expression in various ESCA cell lines. APLN expression was found to be highest in the KYSE-520 cell line, which was selected for subsequent functional assays (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). We established APLN-knockdown KYSE-520 cells using shRNA. Knockdown efficiency was confirmed at both mRNA and protein levels, with a significant reduction in APLN expression compared to control cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Cell viability assays and EdU assays revealed that APLN depletion markedly suppressed cell proliferation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and D). Furthermore, APLN knockdown led to increased cell death, as evidenced by elevated apoptosis rates detected by Annexin V/PI staining (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo evaluate the effects of APLN in vivo, we performed subcutaneous xenograft experiments in nude mice. Tumors derived from APLN-knockdown cells were significantly smaller in size and grew at a slower rate compared to the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). Both tumor volume and final tumor weight were markedly reduced in the APLN-depleted group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eG). We further assessed the metastatic potential of APLN in a lung metastasis model. Mice injected with sh-APLN cells developed fewer and smaller metastatic nodules compared to controls, as shown by macroscopic lung examination and histological analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eH). Quantitative analysis confirmed a significant reduction in the number of metastatic nodules in the APLN-knockdown group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003eI).\u003c/p\u003e\u003cp\u003eThese results demonstrate that APLN plays a critical role in promoting ESCA cell proliferation, survival, tumor growth, and metastasis, highlighting its potential as a therapeutic target.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eAPLN depletion sensitizes esophageal carcinoma cells to cisplatin-induced cell death\u003c/h2\u003e\u003cp\u003eTo investigate whether APLN influences chemotherapy sensitivity in ESCA, we analyzed gene expression and cisplatin sensitivity data from the Cancer Cell Line Encyclopedia (CCLE) database. Specifically, we retrieved APLN expression profiles and corresponding cisplatin IC50 values for esophageal carcinoma cell lines. Correlation analysis revealed a positive association between APLN expression and cisplatin resistance (r\u0026thinsp;=\u0026thinsp;0.38, p\u0026thinsp;=\u0026thinsp;0.04), suggesting that elevated APLN expression may contribute to drug resistance (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Notably, the KYSE-520 cell line exhibited the highest APLN expression and the highest cisplatin IC50 value among the analyzed ESCA cell lines, highlighting its suitability as an in vitro model for functional studies.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNext, we assessed the effect of APLN knockdown on cisplatin sensitivity in KYSE-520 cells. Dose\u0026ndash;response analysis showed that APLN-depleted cells (sh-APLN) were significantly more sensitive to cisplatin than control cells, with a reduced IC50 value of 21.5 \u0026micro;M compared to 37.2 \u0026micro;M in the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), indicating that APLN depletion enhances cisplatin cytotoxicity. Flow cytometry analysis further demonstrated that APLN knockdown increased apoptosis in ESCA cells, and this effect was markedly enhanced when combined with cisplatin treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003eTogether, these results indicate that APLN mediates cisplatin resistance in ESCA, and that targeting APLN enhances chemotherapy sensitivity, providing a potential therapeutic strategy for improving treatment outcomes in esophageal carcinoma.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eAPLN promotes autophagic flux and mediates chemoresistance in esophageal carcinoma cells\u003c/h2\u003e\u003cp\u003eTo explore the potential mechanisms by which APLN contributes to cisplatin resistance in ESCA, we performed gene set enrichment analysis (GSEA) using the GSE53624 dataset. The results revealed that high APLN expression was significantly associated with enrichment of autophagy-related pathways, suggesting a link between APLN and autophagy regulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePrevious studies have shown that autophagy plays a dual role in cancer, where sustained autophagic flux can promote tumor cell survival under stress conditions, including chemotherapy exposure. Based on these findings, we hypothesized that APLN may contribute to chemoresistance through the regulation of autophagy. To validate this, we analyzed correlations between APLN expression and key autophagy-related genes (ATG12, ATG101, ATG4A, and ATG5) in both GSE53624 and TCGA datasets. APLN expression was positively correlated with these autophagy genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eB), indicating that APLN may promote autophagic activity. Besides, RFP-GFP-LC3 tandem fluorescent-tagged assays demonstrated that cisplatin treatment induced autophagic flux in control cells, as shown by abundant LC3-positive puncta. However, APLN knockdown markedly reduced the number of autophagolysosomes, suggesting impaired autophagic flux (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eC\u0026ndash;D). Transmission electron microscopy (TEM) further confirmed reduced autophagosome formation in APLN-depleted cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003eCollectively, these results indicate that APLN maintains autophagic flux to promote chemoresistance in ESCA cells, and its depletion sensitizes cells to cisplatin-induced apoptosis by impairing autophagy.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eExosome-mediated delivery of APLN siRNA suppresses tumor growth without systemic toxicity\u003c/h2\u003e\u003cp\u003eExosomes have gained attention as ideal nanocarriers for therapeutic delivery due to their natural biocompatibility, low immunogenicity, and intrinsic ability to target tumor cells. To evaluate the therapeutic potential of targeting APLN in vivo, we designed an exosome-based delivery system to administer APLN siRNA (siAPLN) into ESCA xenografts. The workflow included exosome isolation, siRNA loading, and quality control prior to in vivo administration (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Nanoparticle tracking analysis (NTA) confirmed that the size distribution of exosomes was not altered by siRNA loading (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Transmission electron microscopy (TEM) further showed that both control and siAPLN-loaded exosomes exhibited typical cup-shaped morphology (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWe then assessed the anti-tumor efficacy of exosome-delivered siAPLN in Rag1\u003csup\u003e-/-\u003c/sup\u003e mice bearing ESCA xenografts. Exosome preparations were administered via intratumoral injection. Tumors treated with siAPLN-loaded exosomes were visibly smaller compared to the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). Tumor growth curves demonstrated a significant reduction in tumor volume in the siAPLN-treated group (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eE), and tumor weights were markedly lower at the endpoint (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eF). These findings indicate that exosome-mediated delivery of siAPLN effectively suppresses ESCA tumor growth in vivo.\u003c/p\u003e\u003cp\u003eImportantly, the administration of siAPLN-loaded exosomes did not result in significant systemic toxicity. There were no significant differences in body weight between treatment groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eG). Histological examination of major organs (liver, lung, kidney) showed no evident tissue damage or pathological changes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eH). Moreover, serum levels of liver and kidney function markers, including AST, ALP, and creatinine, remained unchanged (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e6\u003c/span\u003eI), suggesting good biosafety of the exosome-siRNA delivery system.\u003c/p\u003e\u003cp\u003eCollectively, these results demonstrate that exosome-mediated APLN silencing effectively inhibits ESCA tumor growth in vivo with minimal off-target toxicity, supporting its potential as a therapeutic strategy.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eAPLN-based nomogram model predicts survival outcomes in esophageal carcinoma patients\u003c/h2\u003e\u003cp\u003eTo evaluate the clinical utility of APLN as a prognostic biomarker, we developed a nomogram that integrated APLN expression with pathological stage to predict 1-year and 3-year overall survival probabilities in ESCA patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Each variable was assigned a specific score, and the total score corresponded to predicted survival probabilities, providing a quantitative tool for individualized risk assessment.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe predictive performance of the nomogram was assessed using time-dependent ROC curve analysis. APLN expression alone achieved an AUC of 0.671 for 1-year survival prediction and 0.593 for 3-year survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eB, top). When combined into the nomogram risk score, the model showed improved predictive accuracy, with AUC values of 0.678 for 1-year survival and 0.814 for 3-year survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eB, bottom), indicating good prognostic discrimination. Kaplan-Meier survival analysis further demonstrated the prognostic significance of the nomogram. Patients stratified into high-risk and low-risk groups based on the nomogram score exhibited significantly different survival outcomes. The high-risk group had markedly poorer overall survival compared to the low-risk group (HR\u0026thinsp;=\u0026thinsp;3.87, 95% CI: 2.14\u0026ndash;6.99, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003eCalibration plots were generated to assess the agreement between predicted and observed survival probabilities. The 1-year and 3-year calibration curves showed that the nomogram-predicted survival closely matched actual outcomes, indicating good calibration of the model (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e7\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003eTogether, these results suggest that APLN expression, when combined with clinical stage in a nomogram model, can effectively predict survival outcomes in ESCA patients, providing a valuable tool for personalized prognostic assessment.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we identified APLN as a novel prognostic biomarker that promotes esophageal carcinoma progression. By integrating data from TCGA, GEO, and CRISPR library screening, we found that APLN is significantly upregulated in ESCA and associated with poor patient prognosis. Functional experiments demonstrated that APLN knockdown inhibited tumor cell proliferation, induced apoptosis, and sensitized ESCA cells to cisplatin in vitro and in vivo. Mechanistically, we showed that APLN sustains autophagic flux, contributing to chemotherapy resistance. Moreover, exosome-mediated delivery of APLN siRNA effectively suppressed tumor growth in mouse models. Finally, we constructed a prognostic nomogram combining APLN expression and clinical stage, which accurately predicted patient survival outcomes.\u003c/p\u003e\u003cp\u003eOur findings align with previous studies highlighting the dual role of autophagy in cancer. While autophagy can suppress tumor initiation, it often supports tumor cell survival under stress, including chemotherapy exposure(\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). We demonstrated that APLN positively regulates autophagy-related genes (ATG12, ATG101, ATG4A, ATG5) and maintains autophagic flux, which in turn promotes ESCA cell survival and chemoresistance. Consistent with reports in other cancers where APLN is involved in tumor progression and therapy resistance, our study expands these observations to ESCA, providing new evidence for APLN's oncogenic role.\u003c/p\u003e\u003cp\u003eExosomes have emerged as promising natural nanocarriers for therapeutic delivery due to their inherent biocompatibility, low immunogenicity, and efficient cellular uptake(\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Unlike synthetic nanoparticles or viral vectors, exosomes can naturally fuse with recipient cell membranes, enhancing the targeted delivery of therapeutic molecules while minimizing off-target effects and systemic toxicity(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In the context of tumor therapy, exosome-mediated delivery offers the advantage of improved stability in circulation and the ability to penetrate the dense tumor microenvironment. In our study, we utilized exosomes to deliver APLN siRNA directly into tumor tissues via intratumoral injection. This approach effectively suppressed tumor growth without causing adverse effects on major organs or systemic biochemical markers. The successful knockdown of APLN through exosomal delivery underscores the feasibility of using exosomes as a safe and efficient platform for RNA interference-based cancer therapy. Our findings not only provide proof-of-concept evidence for APLN-targeted exosome therapy in ESCA but also highlight the broader potential of exosome-based strategies for overcoming the limitations of conventional drug delivery systems in solid tumors.\u003c/p\u003e\u003cp\u003eThe most significant academic contribution of this study is the comprehensive demonstration of APLN as both a prognostic biomarker and a therapeutic target in ESCA. We not only revealed the molecular mechanism by which APLN enhances tumor progression through autophagy regulation but also provided a feasible therapeutic strategy by delivering APLN siRNA via exosomes. Furthermore, the nomogram model we developed has potential clinical application for individualized survival prediction in ESCA patients, filling a gap in prognostic tools.\u003c/p\u003e\u003cp\u003eHowever, this study has several limitations. First, the in vivo validation was conducted in immunodeficient mice, which does not fully represent the tumor-immune microenvironment. Second, while we identified APLN\u0026rsquo;s role in autophagy, the precise upstream signaling pathways remain to be elucidated. In future studies, we aim to explore the interaction of APLN with tumor immunity and its potential in combination therapies with immune checkpoint inhibitors or autophagy inhibitors. Additionally, clinical validation of the nomogram in larger, independent ESCA patient cohorts is warranted.\u003c/p\u003e\u003cp\u003eIn summary, our study not only highlights the oncogenic role of APLN in esophageal carcinoma but also provides compelling evidence that exosome-based siRNA delivery is a promising, safe, and effective therapeutic approach. This strategy holds significant potential to overcome the limitations of conventional treatments and paves the way for the clinical translation of RNA interference therapies in solid tumors.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to the Natural Science Foundation of Henan Province and Technology Innovation Excellent Youth Talent Project for providing financial support for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Henan Provincial Middle-aged and Young People\u0026apos;s Health Science, Technology Innovation Excellent Youth Talent Project (YXKC2021053), Medical Science and Technique Foundation of Henan Province (No. LHGJ20210186), Natural Science Foundation of Henan Province (No. 242300420091 for B.-B. C), and Medical Science and Technique Foundation of Henan Province (No. LHGJ20210201 for J.Z).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, Shegan Gao, and Xiaobing Chen; formal analysis, Weifeng Xu, and Caiyun Nie; investigation, Weifeng Xu and Zhen Liu; methodology, Guanghui Liang, and Penghui Yu; writing\u0026mdash;original draft, Weifeng Xu, Huifang Lv, and Beibei Chen; revise and editing, Jianzheng Wang, Saiqi Wang, Jing Zhao, and Yunduan He. All authors have confirmed and agreed to the published version of the manuscript.\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\u003eEthics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal experiments were approved by the Institutional Animal Care and Use Committee of Henan Cancer Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the listed authors have participated in the study, and have approved the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209-49.\u003c/li\u003e\n\u003cli\u003eYang H, Wang F, Hallemeier CL, Lerut T, Fu J. Oesophageal cancer. Lancet. 2024;404(10466):1991-2005.\u003c/li\u003e\n\u003cli\u003eMorgan E, Soerjomataram I, Rumgay H, Coleman HG, Thrift AP, Vignat J, et al. The Global Landscape of Esophageal Squamous Cell Carcinoma and Esophageal Adenocarcinoma Incidence and Mortality in 2020 and Projections to 2040: New Estimates From GLOBOCAN 2020. Gastroenterology. 2022;163(3).\u003c/li\u003e\n\u003cli\u003eLi C, Cheng H, Adhikari BK, Wang S, Yang N, Liu W, et al. The Role of Apelin-APJ System in Diabetes and Obesity. Front Endocrinol (Lausanne). 2022;13:820002.\u003c/li\u003e\n\u003cli\u003eMastrella G, Hou M, Li M, Stoecklein VM, Zdouc N, Volmar MNM, et al. Targeting APLN/APLNR Improves Antiangiogenic Efficiency and Blunts Proinvasive Side Effects of VEGFA/VEGFR2 Blockade in Glioblastoma. Cancer Res. 2019;79(9):2298-313.\u003c/li\u003e\n\u003cli\u003eWu D, He L, Chen L. Apelin/APJ system: a promising therapy target for hypertension. Mol Biol Rep. 2014;41(10):6691-703.\u003c/li\u003e\n\u003cli\u003eGuo R, Rogers O, Nair S. Targeting Apelinergic System in Cardiometabolic Disease. Curr Drug Targets. 2017;18(15):1785-91.\u003c/li\u003e\n\u003cli\u003eWang Q, Wang B, Zhang W, Zhang T, Liu Q, Jiao X, et al. APLN promotes the proliferation, migration, and glycolysis of cervical cancer through the PI3K/AKT/mTOR pathway. Arch Biochem Biophys. 2024;755:109983.\u003c/li\u003e\n\u003cli\u003eCeraudo E, Galanth C, Carpentier E, Banegas-Font I, Schonegge A-M, Alvear-Perez R, et al. Biased signaling favoring gi over \u0026beta;-arrestin promoted by an apelin fragment lacking the C-terminal phenylalanine. J Biol Chem. 2014;289(35):24599-610.\u003c/li\u003e\n\u003cli\u003eAlizadeh Pahlavani H. Possible roles of exercise and apelin against pregnancy complications. Front Endocrinol (Lausanne). 2022;13:965167.\u003c/li\u003e\n\u003cli\u003eChen H, Wong C-C, Liu D, Go MYY, Wu B, Peng S, et al. APLN promotes hepatocellular carcinoma through activating PI3K/Akt pathway and is a druggable target. Theranostics. 2019;9(18):5246-60.\u003c/li\u003e\n\u003cli\u003eZhou Q, Cao J, Chen L. Apelin/APJ system: A novel therapeutic target for oxidative stress-related inflammatory diseases (Review). Int J Mol Med. 2016;37(5):1159-69.\u003c/li\u003e\n\u003cli\u003eWysocka MB, Pietraszek-Gremplewicz K, Nowak D. The Role of Apelin in Cardiovascular Diseases, Obesity and Cancer. Front Physiol. 2018;9:557.\u003c/li\u003e\n\u003cli\u003eXu WW, Liao L, Dai W, Zheng C-C, Tan X-P, He Y, et al. Genome-wide CRISPR/Cas9 screening identifies a targetable MEST-PURA interaction in cancer metastasis. EBioMedicine. 2023;92:104587.\u003c/li\u003e\n\u003cli\u003eNiu X, You Q, Hou K, Tian Y, Wei P, Zhu Y, et al. Autophagy in cancer development, immune evasion, and drug resistance. Drug Resist Updat. 2025;78:101170.\u003c/li\u003e\n\u003cli\u003eMele L, Del Vecchio V, Liccardo D, Prisco C, Schwerdtfeger M, Robinson N, et al. The role of autophagy in resistance to targeted therapies. Cancer Treat Rev. 2020;88:102043.\u003c/li\u003e\n\u003cli\u003eSui X, Chen R, Wang Z, Huang Z, Kong N, Zhang M, et al. Autophagy and chemotherapy resistance: a promising therapeutic target for cancer treatment. Cell Death Dis. 2013;4(10):e838.\u003c/li\u003e\n\u003cli\u003eBatrakova EV, Kim MS. Using exosomes, naturally-equipped nanocarriers, for drug delivery. J Control Release. 2015;219:396-405.\u003c/li\u003e\n\u003cli\u003eIqbal Z, Rehman K, Mahmood A, Shabbir M, Liang Y, Duan L, et al. Exosome for mRNA delivery: strategies and therapeutic applications. J Nanobiotechnology. 2024;22(1):395.\u003c/li\u003e\n\u003cli\u003eKim HI, Park J, Zhu Y, Wang X, Han Y, Zhang D. Recent advances in extracellular vesicles for therapeutic cargo delivery. Exp Mol Med. 2024;56(4):836-49.\u003c/li\u003e\n\u003cli\u003eVader P, Mol EA, Pasterkamp G, Schiffelers RM. Extracellular vesicles for drug delivery. Adv Drug Deliv Rev. 2016;106(Pt A):148-56.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"functional-and-integrative-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"fige","sideBox":"Learn more about [Functional \u0026 Integrative Genomics](http://link.springer.com/journal/10142)","snPcode":"10142","submissionUrl":"https://submission.nature.com/new-submission/10142/3","title":"Functional \u0026 Integrative Genomics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7592740/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7592740/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e\u003cp\u003eEsophageal carcinoma (ESCA) is a highly aggressive malignancy with poor prognosis. The apelin gene (APLN) encodes a secreted peptide involved in various physiological processes, but its role in ESCA progression and chemoresistance remains unclear.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eWe integrated transcriptomic data from TCGA and GEO databases with CRISPR screening to identify key oncogenes in ESCA. ALPN was identified as a key gene. Functional assays in vitro and in vivo were performed to investigate the biological role of APLN. Mechanistic studies explored the involvement of APLN in autophagy regulation and chemoresistance. Furthermore, we developed an exosome-based siRNA delivery system targeting APLN and constructed a prognostic nomogram incorporating APLN expression.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eAPLN was significantly overexpressed in ESCA tissues and correlated with poor patient prognosis. DNA hypomethylation contributed to APLN upregulation. Functional experiments demonstrated that APLN knockdown suppressed tumor cell proliferation, induced apoptosis, and enhanced sensitivity to cisplatin. Mechanistically, APLN promoted autophagic flux, which mediated chemoresistance in ESCA cells. Exosome-mediated delivery of APLN siRNA effectively inhibited tumor growth in vivo without systemic toxicity. Additionally, a nomogram combining APLN expression with clinical stage accurately predicted patient survival, providing a practical tool for individualized prognosis.\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e\u003cp\u003eOur study identifies APLN as a novel driver of ESCA progression and chemoresistance through autophagy regulation. Targeting APLN via exosome-based siRNA delivery offers a promising therapeutic strategy. Moreover, the APLN-based prognostic nomogram holds potential for guiding personalized treatment decisions in ESCA patients.\u003c/p\u003e","manuscriptTitle":"APLN, a novel prognostic biomarker, contributes to esophageal carcinoma development","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-25 01:33:10","doi":"10.21203/rs.3.rs-7592740/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-25T22:53:39+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-08T16:17:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"26263778368760695305295982364405210854","date":"2025-10-04T23:11:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"298934820461265060479347804096366677822","date":"2025-10-02T11:47:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"128732960355847584526087412176488303738","date":"2025-09-20T05:27:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-16T09:56:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-15T12:10:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-15T12:10:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"Functional \u0026 Integrative Genomics","date":"2025-09-11T14:01:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"functional-and-integrative-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"fige","sideBox":"Learn more about [Functional \u0026 Integrative Genomics](http://link.springer.com/journal/10142)","snPcode":"10142","submissionUrl":"https://submission.nature.com/new-submission/10142/3","title":"Functional \u0026 Integrative Genomics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"106ebada-77c0-445e-90a2-5ee9cdd6a293","owner":[],"postedDate":"September 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:05:28+00:00","versionOfRecord":{"articleIdentity":"rs-7592740","link":"https://doi.org/10.1007/s10142-025-01790-z","journal":{"identity":"functional-and-integrative-genomics","isVorOnly":false,"title":"Functional \u0026 Integrative Genomics"},"publishedOn":"2026-01-07 15:58:56","publishedOnDateReadable":"January 7th, 2026"},"versionCreatedAt":"2025-09-25 01:33:10","video":"","vorDoi":"10.1007/s10142-025-01790-z","vorDoiUrl":"https://doi.org/10.1007/s10142-025-01790-z","workflowStages":[]},"version":"v1","identity":"rs-7592740","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7592740","identity":"rs-7592740","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}