IL6 and CD40 Identified by OLINK Proteomics as Potential Biomarkers for Evaluating Neoadjuvant Immune-Chemotherapy Efficacy in Esophageal Adenocarcinoma.

IL6 and CD40 Identified by OLINK Proteomics as Potential Biomarkers for Evaluating Neoadjuvant Immune-Chemotherapy Efficacy in Esophageal Adenocarcinoma. | 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 IL6 and CD40 Identified by OLINK Proteomics as Potential Biomarkers for Evaluating Neoadjuvant Immune-Chemotherapy Efficacy in Esophageal Adenocarcinoma. yuchuan Zhou, Zhonghui Jiang, Shu Peng, Yue Xiang, Guoyi Li, Caihong Luo, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8331704/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Esophageal cancer ranks among the top six malignancies in terms of mortality rates in China. The integration of neoadjuvant immunotherapy with chemotherapy has improved treatment outcomes for resectable esophageal adenocarcinoma (EAC); however, more than 50% of patients demonstrate suboptimal responses to neoadjuvant therapy. Currently, aside from imaging modalities and postoperative pathological evaluations, there is a notable lack of effective molecular biomarkers for monitoring the efficacy of neoadjuvant treatments. Methods : EAC patients who have received neoadjuvant immunochemotherapy should be stratified into two cohorts according to the efficacy of the treatment. Subsequently, OLINK immunoproteomics can be employed to identify molecules that are differentially expressed between these two groups. Results : Utilizing OLINK proteomics, this study identifies IL6 and CD40 as differentially expressed and correlated with patient survival； Conclusion: This study proposes CD40 and IL6 as potential biomarkers for assessing the clinical efficacy of neoadjuvant therapy in cases of esophageal adenocarcinoma (EAC). These findings are expected to enhance the evaluation of neoadjuvant therapy effectiveness in resectable EAC. Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Esophageal cancer significantly impacts public health, with GLOBOCAN 2022 reporting around 510,000 new cases and 440,000 deaths globally each year, making up 4.6% of cancer deaths 1 . In China, esophageal squamous cell carcinoma constitutes about 85% of cases, while EAC makes up 10% 2 . The 5-year survival rate for esophageal squamous cell carcinoma is 20–30%, but it improves to 60–80% with early-stage surgical treatment and 30–50% with neoadjuvant therapy and surgery for locally advanced stages. EAC is prevalent in Western countries and predominantly occurs in the distal esophagus. Characterized by its insidious onset and aggressive nature, EAC has a 5-year survival rate that is marginally lower than that of squamous cell carcinoma, generally ranging from 15% to 25%. 3 . It often goes undetected until advanced stages, making surgery unfeasible for many. Even with surgery, early lymph node metastasis leads to poor outcomes. Standard treatments like chemotherapy, radiotherapy, and surgery have limited success in improving survival rates 4 . Neoadjuvant chemotherapy has been a standard for resectable esophageal cancer 5 , boosting resection rates from 60% to 70–80% compared to surgery alone. However, it only modestly improves 5-year survival rates by 5–10% and has a low pathological complete response (pCR) rate of 5–10% 6 . It also causes significant side effects like myelosuppression and neuropathy, affecting quality of life and treatment adherence 7 . Recently, immune checkpoint inhibitors, particularly anti-PD-1/PD-L1 antibodies, have transformed cancer treatment, including for esophageal cancer 8910 . Recent single-arm studies over the past five years have shown that neoadjuvant immunotherapy in esophageal cancer achieves pCR rates of 10–20% 11 . However, single-agent neoadjuvant immunotherapy has limitations, including low objective response rates and many patients not responding due to resistance mechanisms like an immunosuppressive tumor microenvironment 12 . To address these issues, combining chemotherapy with immunotherapy is a promising approach, as chemotherapy can kill tumor cells and enhance the tumor microenvironment's immunogenicity. Chemotherapy releases tumor-associated antigens and cytokines, enhancing immune cell activation and boosting immunotherapy effects 1314 . Recent clinical trials highlight the benefits of combining neoadjuvant chemotherapy with immunotherapy. In 2024, an article published in Nature Medicine reported that among 491 patients with thoracic esophageal squamous cell carcinoma (ESCC), the pCR rate was 28.0% in the chemo-immunotherapy group, compared to 4.7% in the traditional chemotherapy group 15 . Additionally, a study in China found a two-year overall survival rate of 81.3% for the combined treatment, compared to 71.3% for traditional therapy 16 . The safety of neoadjuvant chemo-immunotherapy is acceptable, with grade ≥ 3 treatment-related adverse events occurring at a similar rate (13–15%) as in traditional chemotherapy (10–12%)Most immune-related adverse events, like thyroid function impairment, are mild, manageable, and often reversible. 17181920 . Despite significant advancements in the integration of neoadjuvant immunotherapy with chemotherapy, substantial variability persists in patient treatment responses. Some patients achieve a pCR and enjoy markedly prolonged survival, while others exhibit limited therapeutic efficacy. A thorough investigation into the factors contributing to these disparities is essential for optimizing treatment protocols and advancing precision medicine. Current research suggests that variations in therapeutic outcomes may be attributed to a range of factors, including individual genetic profiles, the tumor microenvironment, and immune status 2122 . In summary, the combination of chemotherapy and immunotherapy in the neoadjuvant setting holds promise for enhancing pCR rates and survival outcomes in patients with esophageal cancer, while maintaining an acceptable safety profile. Nonetheless, further research is required to identify predictive biomarkers, refine therapeutic regimens, and expand the applicability of this approach. This study conducts an analysis of samples from patients with EAC who have undergone neoadjuvant treatment, categorizing them based on their response to the therapy. The research utilizes Olink immunoproteomics to identify differential molecules, with the goal of discovering potential biomarkers. The primary aim is to investigate the mechanisms underlying the varying efficacy of neoadjuvant chemoimmunotherapy by examining immune-related proteins. This approach seeks to provide a novel theoretical framework and identify biomarkers for the precision treatment of esophageal cancer. The study focuses on pinpointing key immune factors that affect the success of neoadjuvant chemoimmunotherapy by analyzing the expression of immune-related proteins in patients exhibiting either "good" or "poor" treatment responses, employing Olink technology. By exploring differential proteins and their associated signaling pathways, this research aspires to furnish more precise guidance for clinical practice. Materials and Methods Study population and data collection In this study, 14 patients diagnosed with EAC were recruited to receive neoadjuvant immunochemotherapy. The treatment regimen consisted of 2 cycles of neoadjuvant therapy, incorporating a platinum-based chemotherapy agent and a PD-1 inhibitor as the immunotherapeutic component. Upon completion of the neoadjuvant therapy, a comprehensive evaluation was conducted to determine tumor progression. Patients demonstrating no evidence of disease progression and absence of distant metastasis were deemed eligible for radical surgical intervention. Subsequently, the thoracic surgery department performed a radical esophagectomy. The pathology department then utilized Mandard’s Tumor Regression Grade (TRG) 23 to evaluate the efficacy of the neoadjuvant therapy in treating esophageal cancer. Patients with TRG grades 1–2 were classified as responders to the neoadjuvant therapy, while those with TRG grades 3–5 were categorized as non-responders. RNA-Seq and Bioinformatics EAC samples, obtained from radical resections following neoadjuvant therapy, were classified into responder and non-responder groups utilizing the OLINK classification methodology. Subsequent RNA sequencing (RNA-seq) and bioinformatics analyses were performed, with three biological replicates designated for each experimental condition. Total RNA was extracted using the TRIzol® reagent, and complementary DNA (cDNA) libraries were constructed prior to sequencing on the Illumina NovaSeq 6000 platform. Differential expression analysis between the two groups was conducted using DESeq2 (version 1.20.0). This analysis was followed by enrichment analyses of the differentially expressed genes, employing the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Olink Proteomics was utilized in this study. OLINK Immunoproteomics Postoperative specimens were obtained from 14 patients diagnosed with neoadjuvant EAC, and the expression levels of inflammatory factors were subsequently analyzed using OLINK Immunoproteomics technology. This technology employs the Proximity Extension Assay (PEA) technique, which is based on dual antibody recognition. In this method, each target protein is bound by a pair of antibodies, with each antibody conjugated to a unique DNA oligonucleotide. When these antibody-oligonucleotide complexes bind in close proximity on the same protein molecule, they facilitate the hybridization of the oligonucleotides. This process results in the generation of a specific DNA amplification product through polymerase-mediated extension. Quantification is conducted via microfluidic real-time quantitative PCR (qPCR), wherein each oligonucleotide tag is associated with a specific protein. This methodology permits the simultaneous analysis of up to 96 inflammatory proteins per reaction. The signal intensity correlates directly with protein concentration, thereby enabling highly sensitive and specific absolute quantification. The results are expressed as normalized protein expression (NPX) values on a log2 scale, with elevated values indicating increased protein expression. The validation data, encompassing detection limits and precision metrics, are accessible on the manufacturer's website ( www.olink.com ). Following quality control and log2 normalization, the data are expressed as normalized protein expression (NPX), with the median value serving as an indicator of protein expression levels. Normalization is achieved through Olink's proprietary algorithm, which incorporates background subtraction and inter-plate calibration using internal controls. A t-test is employed to identify differentially expressed proteins (DEPs) between the two groups when the p-value is less than 0.05. Clustering analysis of DEPs, based on serum protein expression profiles, is conducted using heatmaps. Survival Analysis and Bioinformatics using OLINK Immunoproteomics Data. The DEPs is illustrated using volcano plots, followed by functional analyses based on Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). These bioinformatics analyses were performed by LC-Bio Technology Co., Ltd. (Hangzhou, China). Additionally, we employed KMplot ( https://kmplot.com/analysis/ ), a tool commonly used for survival analysis, to conduct statistical evaluations. Statistical analysis Data from two unpaired groups were analyzed using an unpaired t-test for parametric data or a Mann-Whitney test for non-parametric data. For more than three groups, a one-way ANOVA was used for parametric data, and a Kruskal-Wallis test for non-parametric data, with post-hoc analyses for significant differences. All analyses were conducted using GraphPad Prism 10.1.0. Quantitative variables are shown as median ± IQR, and categorical variables as proportions. The Wilcoxon test was applied for non-normally distributed variables, and Fisher’s exact test for two categorical variables. Survival analysis utilized a Kaplan-Meier plot with a log-rank test p value. Significance was set at p < 0.05 (*) and p < 0.01 (**). Result Clinical characteristics of the participants and tumor tissue samples Between January 2024 and January 2025, a total of 14 patients were diagnosed with esophageal adenocarcinoma at our hospital. These patients were enrolled in a study where they received a two-cycle neoadjuvant immunochemotherapy regimen, which included anti-PD-1 immune checkpoint inhibitors (ICIs) in combination with a platinum-based doublet chemotherapy regimen. Following this treatment, all patients underwent a radical esophagogastrectomy, and subsequent postoperative pathological examinations were conducted (Fig. 1 A). According to Mandard's Tumor Regression Grade (TRG) system, patients with scores of 1–2 were classified as responders (R), while those with scores of 3–5 were classified as non-responders (NR). Our observations indicated that patients with TRG grades 1–2, following neoadjuvant immunochemotherapy, exhibited pathological sections with minimal residual tumor cells, which were predominantly replaced by fibrous tissue (Fig. 1 B). In contrast, patients with TRG grades 3–5 showed pathological sections with a substantial presence of residual tumor cells (Fig. 1 C). Ultimately, 7 patients were identified as responders, and the remaining 7 were classified as non-responders. There were no significant differences in clinical characteristics between responders and non-responders at baseline. Consequently, we collected tumor tissues from these 14 patients to conduct paired tissue proteomic assays and RNA sequencing after surgery. Transcriptome Sequencing Results and Bioinformatics Analysis To examine the molecular alterations in esophageal cancer following neoadjuvant immunochemotherapy, we performed transcriptome sequencing on tumor tissues. Our analysis identified 229 differentially expressed genes between the treated and control groups, with 37 genes upregulated and 192 genes downregulated in the treated group (Fig. 2 A). Subsequent Gene Ontology (GO) enrichment analysis of Biological Processes revealed significant enrichment in pathways related to anatomical structure development, organ induction, anterior/posterior pattern specification, embryonic skeletal system morphogenesis, positive regulation of ubiquitin-protein transferase activity, regulation of transcription by RNA polymerase II, and signal transduction mediated by the p53 class. In terms of Molecular Function, significant enrichment was observed in histone deacetylase binding, sequence-specific double-stranded DNA binding, DNA-binding transcription factor activity, and RNA polymerase II specificity (Fig. 2 B). Disease Ontology (DO) enrichment analysis indicated a relatively weak specificity of disease association for the differentially expressed genes, with predominant associations observed with melanoma and squamous cell carcinoma (Fig. 2 C). KEGG enrichment analysis was conducted, revealing significant enrichment in retinol metabolism, metabolism of xenobiotics by cytochrome P450, transcriptional misregulation in cancer and other signaling pathways (Fig. 2 D). Olink Inflammation-Related Biomarker Analysis To examine the response of Inflammation-Related Biomarker at EAC treated with neoadjuvent immunochemotherapy, we performed an Olink proteomic analysis. This technique was utilized to evaluate and compare the expression levels of 92 inflammation-related proteins between the treated and control groups. A total of 7 differentially expressed inflammation-related proteins were identified between R and NR groups, of which 7 were downregulated in the responsed group (Fig. 4A). Among them, IL6, CXCL1, MUC16, VEGFA, TNFASF12A, CD40 and MCP4 was significantly expressed. Subsequent GO enrichment analysis of Biological Processes revealed significant enrichment in pathways related to inflammatory response, cellular response to lipopolysaccharide, positive regulation of MAPK cascade et al. In terms of top 20 of interpro enrichment observed in mucin-16, SEA domain, IL-6, IL-6/GCSF/MGF, TNFR12, VEGF (Fig. 2 B). Disease Ontology (DO) enrichment analysis indicated disease association for the differentially expressed proteins, with predominant associations observed with ovarian carcinoma, atherosclerosis, sarcoma and temporal arteritis (Fig. 2 C). KEGG enrichment analysis was conducted, revealing significant enrichment in cytokine–cytokine receptor interactions, viral protein interaction with cytokine–cytokine receptor interactions, NF-kappaB signaling pathways and other signaling pathways (Fig. 2 D). The predictive and prognostic significance of the inflammation factor in EAC neoadjuvant immunochemotherapy. Following the screening of seven molecules using OLINK sequencing, we proceeded to validate their impact on the survival outcomes of esophageal cancer patients. This validation was conducted using the public database analysis platform KMplot ( https://kmplot.com/analysis/ ), which is widely utilized for survival analysis. KMplot aggregates data from the GEO, EGA, and TCGA databases, thereby facilitating the assessment of the correlation between gene expression and patient survival across more than 30,000 samples from 21 tumor types. This enables the identification and validation of survival-related biomarkers. In our study, a cohort of 80 patients was analyzed to evaluate the impact of differential protein expression on the survival curves of esophageal cancer patients. The findings indicated that for the 36-month overall survival (OS), proteins such as CD40 and IL6 exhibited statistically significant p-values (p < 0.05). Other indicators demonstrated a trend but did not reach statistical significance. Notably, the analysis results for MCP4 remain incomplete. It is important to note that the sample size for esophageal cancer data is limited, necessitating further data collection and support in future research endeavors. Figure 4༎Analysis of Differentially Expressed Inflammation-Related Biomarkers and Their Association with Survival Using Olink Technology. B. In the Kaplan-Meier plot analysis platform, the survival curve analysis reveals a statistically significant difference between IL6 and CD40(p < 0.05). Discussion Esophageal cancer exhibits a high incidence rate in China, characterized by distinct regional distribution patterns. Patients who attain a major pathological response or a complete pathological response following neoadjuvant therapy generally have a favorable prognosis 24 . This is particularly evident in cases where neoadjuvant chemoradiotherapy is combined with immunotherapy, demonstrating significant efficacy 25 . Nevertheless, approximately 50% of patients exhibit a poor response to neoadjuvant therapy 26 . The underlying mechanisms of this variability in response remain unclear, and further research is needed to develop methods for evaluating the efficacy of neoadjuvant therapy prior to surgical intervention. The efficacy of neoadjuvant immunotherapy for esophageal cancer can be demonstrated in several aspects: 1. Significant improvement in eating obstruction, reduction in patient nutritional risk scores, and weight gain; 2. Imaging assessment, using RECIST 1.1 criteria to evaluate tumor regression 27 ; 3. Postoperative pathology; 4. Tumor markers, etc., although these indicators all have certain limitations 28 . Developing earlier and more sensitive detection methods can help adjust neoadjuvant treatment plans and courses, improving efficacy for esophageal cancer patients 2930 . In the era of immunotherapy, due to the advantages of tumor immunity in anti-cancer treatment, it has been gradually recognized that immune response is also one of the methods to assess tumor efficacy 3132 . This study compiles clinical standards for patients with esophageal cancer following neoadjuvant therapy and suggests categorizing them into a 'response group' and a 'non-response group' based on pathological remission. Utilizing Olink technology 32 , the expression levels of immune-inflammatory factors were analyzed between the two groups. Through the integration of bioinformatics and survival curve data from relevant databases, two candidate factors, IL-6 and CD40, were identified as potential indicators of the efficacy of clinical neoadjuvant therapy. Specifically, monitoring the changes in these two factors during the treatment process may facilitate the assessment of the tumor's response to neoadjuvant therapy. Interleukin-6 (IL-6), a pleiotropic cytokine, activates the signal transducer and activator of transcription 3 (STAT3) via both classical and trans-signaling pathways, thereby regulating critical processes such as tumor proliferation, angiogenesis, and immune evasion 33 . In malignancies such as colorectal cancer and non-small cell lung cancer, elevated IL-6 expression is correlated with poor prognosis. IL-6 upregulates programmed death-ligand 1 (PD-L1) expression, suppresses CD8⁺ T cell infiltration, and recruits myeloid-derived suppressor cells and M2 macrophages 343536 , thus fostering an immunosuppressive microenvironment and diminishing therapeutic efficacy 37 . In the context of neoadjuvant therapy for esophageal cancer, dynamic alterations in IL-6 levels are closely associated with therapeutic efficacy. Empirical evidence indicates that a reduction in IL-6 concentrations during treatment is significantly correlated with extended progression-free survival, suggesting that IL-6 may serve as an indicator of the therapy's remodeling effect on the tumor microenvironment 38 . The present study further corroborates that in patients exhibiting poor therapeutic response, IL-6 levels remain elevated post-treatment, aligning with its role in safeguarding tumor cells against treatment-induced DNA damage and apoptosis. Compared to liquid biopsy markers such as circulating tumor DNA (ctDNA), IL-6 testing offers a more convenient and rapid means of assessing treatment efficacy, making it particularly advantageous in clinical settings with constrained resources 39 . As a constituent of the tumor necrosis factor receptor family, CD40 is aberrantly expressed in a range of malignancies, and its pathway activation can mediate anti-tumor effects through diverse mechanisms. Firstly, the activation of CD40 can directly suppress tumor cell proliferation and enhance their susceptibility to radiotherapy and chemotherapy. Secondly, by activating dendritic cells, CD40 facilitates antigen presentation and the initiation of anti-tumor immune responses, a process that is positively associated with the degree of CD8⁺ T cell infiltration 4041 . In the context of esophageal cancer treatment, the expression status of CD40 has not been extensively investigated; however, existing mechanistic studies have yielded significant insights. Given the pivotal role of the CD40 pathway in modulating the tumor immune microenvironment, its expression level may serve as an indicator of immune function recovery post-treatment 42 . In this study, the cohort exhibiting more favorable treatment outcomes demonstrated low CD40 expression, which appears to contradict the hypothesis that CD40-mediated immune activation enhances treatment efficacy 43 . This finding also diverges from previous research suggesting that the CD40 pathway can augment the synergistic effects of radiotherapy and chemotherapy. A plausible explanation is that, following increased sensitivity to neoadjuvant therapy, the tumor burden diminishes, resulting in decreased expression of tumor immune molecules. This observation broadens the potential application of CD40 in monitoring therapeutic efficacy in solid tumors and offers a novel avenue for predicting the success of combined immunotherapy. In various other cancer types, IL-6 and CD40 are typically considered biomarkers from the dual perspectives of immunosuppression and immune activation, respectively. However, their roles differ in the context of assessing the tumor microenvironment status following neoadjuvant therapy for esophageal cancer. Elevated IL-6 expression indicates persistent immunosuppression, while increased CD40 expression is associated with a suboptimal anti-tumor immune response. The concurrent assessment of these biomarkers may enhance the precision of treatment efficacy evaluations 4445 . A significant limitation of this study is the small sample size, which can be attributed to the relatively low incidence of esophageal adenocarcinoma in the Chinese population. Future research should consider testing serum using CD40 and IL-6 markers. Consequently, prospective large-scale studies are warranted to substantiate these findings. Future investigations could delve into the relationship between the expression ratio of these molecules and both the pathological complete response rate and overall survival, with the aim of refining diagnostic thresholds. Additionally, incorporating markers such as circulating tumor DNA to develop a multidimensional evaluation framework could facilitate the transition of esophageal cancer treatment from an empirical to a molecularly-driven approach. Furthermore, the combined application of IL-6 pathway inhibitors and CD40 atagonists may emerge as a novel strategy to enhance the prognosis of patients exhibiting poor responses to treatment. Conclusion Our research suggests that the effectiveness of neoadjuvant therapy in esophageal cancer can be assessed using CD40 and IL-6 as biomarkers. This approach offers a novel auxiliary method for monitoring neoadjuvant therapy in esophageal cancer. However, further validation through peripheral blood analysis in subsequent prospective studies is necessary. Declarations Ethics approval and consent to participate This study was performed in line with the Declaration of Helsinki and approved by the Ethics Committee of Affiliated Hospital of North Sichuan Medical College, thus alleviating patients of the requirement to sign a written informed consent form (ethics number, 2024ER796-01). All research experiments were conducted in accordance with the principles of the Declaration. Consent The authors have nothing to report. Availability of data and materials The data that support the findings of this study are available on request from the corresponding author(NCBI accession number acc=GSE315001). The data are not publicly available due to privacy or ethical restrictions. Competing interests The authors declare no conflicts of interest. Funding The authors thank all the professors who provided support for this study and thank the editors as well as reviewers for reading the manuscript. This study was supported by special Project of the Science and Technology Plan, Nanchong Science and Technology Bureau (Grant No. 23JCYJPT0061), and the High-Level Talent Research Start-up Project of the Affiliated Hospital of North Sichuan Medical College (No. 2023-2GC017). Author Contributions Yuchuan Zhou: conceptualization; validation; writing – original draft; writing – review and editing; software. Zhonghui Jiang: data curation; investigation; project administration. 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Eichhorn, M.E., Niedermaier, B., Charoentong, P., Klotz, L.V., Baum, P., Griffo, R., Allgäuer, M., Stenzinger, A., Bischoff, H., Schneider, M.A., et al. (2025). Neoadjuvant anti-programmed death-1 immunotherapy by pembrolizumab in resectable non-small cell lung cancer: results of the NEOMUN trial. J Immunother Cancer 13 , e011874. https://doi.org/10.1136/jitc-2025-011874. Qin, H., Liu, F., Zhang, Y., Liang, Y., Mi, Y., Yu, F., Xu, H., Li, K., Lin, C., Li, L., et al. (2023). Comparison of neoadjuvant immunotherapy versus routine neoadjuvant therapy for patients with locally advanced esophageal cancer: A systematic review and meta-analysis. Front Immunol 14 , 1108213. https://doi.org/10.3389/fimmu.2023.1108213. Yang, H., Liu, H., Chen, Y., Zhu, C., Fang, W., Yu, Z., Mao, W., Xiang, J., Han, Y., Chen, Z., et al. (2018). 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The efficacy and safety of anlotinib plus PD-1 inhibitor in locally advanced/metastatic esophageal squamous cell carcinoma (ESCC) patients who progressed on prior immune checkpoint inhibitors (ICIs): a retrospective real-world study (NCT 04984096). Ann Med 57 , 2443811. https://doi.org/10.1080/07853890.2024.2443811. Liu, Z., Zhang, Y., Ma, N., Yang, Y., Ma, Y., Wang, F., Wang, Y., Wei, J., Chen, H., Tartarone, A., et al. (2023). Progenitor-like exhausted SPRY1+CD8+ T cells potentiate responsiveness to neoadjuvant PD-1 blockade in esophageal squamous cell carcinoma. Cancer Cell 41 , 1852-1870.e9. https://doi.org/10.1016/j.ccell.2023.09.011. Yue, P., Bie, F., Zhu, J., Gao, L.-R., Zhou, Z., Bai, G., Wang, X., Zhao, Z., Xiao, Z.-F., Li, Y., et al. (2024). Minimal residual disease profiling predicts pathological complete response in esophageal squamous cell carcinoma. Mol Cancer 23 , 96. https://doi.org/10.1186/s12943-024-02006-x. Ng, H.Y., Ko, J.M.Y., Lam, K.O., Kwong, D.L.W., Lo, A.W.I., Wong, I.Y.H., Wong, C.L.Y., Chan, S.Y., Chan, K.K., Law, T.T., et al. (2023). Circulating Tumor DNA Dynamics as Prognostic Markers in Locally Advanced and Metastatic Esophageal Squamous Cell Carcinoma. JAMA Surg 158 , 1141–1150. https://doi.org/10.1001/jamasurg.2023.4395. Feng, T., Li, Q., Zhu, R., Yu, C., Xu, L., Ying, L., Wang, C., Xu, W., Wang, J., Zhu, J., et al. (2024). Tumor microenvironment biomarkers predicting pathological response to neoadjuvant chemoimmunotherapy in locally advanced esophageal squamous cell carcinoma: post-hoc analysis of a single center, phase 2 study. J Immunother Cancer 12 , e008942. https://doi.org/10.1136/jitc-2024-008942. Han, D., Han, Y., Guo, W., Wei, W., Yang, S., Xiang, J., Che, J., Zhu, L., Hang, J., van den Ende, T., et al. (2023). High-dimensional single-cell proteomics analysis of esophageal squamous cell carcinoma reveals dynamic alterations of the tumor immune microenvironment after neoadjuvant therapy. J Immunother Cancer 11 , e007847. https://doi.org/10.1136/jitc-2023-007847. Qiao, Y., Zhang, C., Li, A., Wang, D., Luo, Z., Ping, Y., Zhou, B., Liu, S., Li, H., Yue, D., et al. (2018). IL6 derived from cancer-associated fibroblasts promotes chemoresistance via CXCR7 in esophageal squamous cell carcinoma. Oncogene 37 , 873–883. https://doi.org/10.1038/onc.2017.387. Xie, M., Yuan, K., Zhang, Y., Zhang, Y., Zhang, R., Gao, J., Wei, W., Jiang, L., Li, T., Ding, Y., et al. (2025). Tumor-resident probiotic Clostridium butyricum improves aPD-1 efficacy in colorectal cancer models by inhibiting IL-6-mediated immunosuppression. Cancer Cell 43 , 1885-1901.e10. https://doi.org/10.1016/j.ccell.2025.07.012. Wang, R., Li, W., Lv, Y., Ba, W., Jiang, Y., Li, X., and Fang, J. (2025). Colorectal Cancer Cells-Derived Exosomal PIK3CA Mutation DNA Promotes Tumor Metastasis by Activating Fibroblast and Affecting Tumor Metastatic Microenvironment. Adv Sci (Weinh) 12 , e2501792. https://doi.org/10.1002/advs.202501792. Jeong, H., Koh, J., Kim, S., Yim, J., Song, S.G., Kim, H., Li, Y., Lee, S.H., Chung, Y.K., Kim, H., et al. (2025). Cell-intrinsic PD-L1 signaling drives immunosuppression by myeloid-derived suppressor cells through IL-6/Jak/Stat3 in PD-L1-high lung cancer. J Immunother Cancer 13 , e010612. https://doi.org/10.1136/jitc-2024-010612. Berraondo, P., Cuesta, R., Aranda, F., Martinez-Riaño, A., Eguren-Santamaria, I., Luri-Rey, C., Risson, A., Melero, A., Gomis, G., and Melero, I. (2025). Immunocytokines and cytokine neutralization for cancer immunotherapy. Trends Cancer 11 , 790–805. https://doi.org/10.1016/j.trecan.2025.04.014. Ma, H., Zhang, S., Jiao, P., Ding, H., Wang, F., Zhao, Y., Wu, J., and Guo, Z. (2025). Serum IL-6 predicts immunotherapy-related adverse and outcome in advanced gastric and esophageal cancer patients with Anti-PD-1 treatment. Front Immunol 16 , 1553882. https://doi.org/10.3389/fimmu.2025.1553882. Huang, P., Zhao, M., Xia, J., Li, H., Sun, J., Li, X., Yang, C., Gao, G., Zhou, W., Zhong, M., et al. (2025). IL-6 is a prognostic biomarker in patients with advanced esophageal squamous cell carcinoma received with PD-1 inhibitors. Front Immunol 16 , 1569042. https://doi.org/10.3389/fimmu.2025.1569042. Yan, C., and Richmond, A. (2021). Hiding in the dark: pan-cancer characterization of expression and clinical relevance of CD40 to immune checkpoint blockade therapy. Mol Cancer 20 , 146. https://doi.org/10.1186/s12943-021-01442-3. Labiano, S., Marco-Sanz, J., Ausejo-Mauleon, I., Laspidea, V., Hernández-Osuna, R., Garcia-Moure, M., Nava, D. de la, Nuin, S., Gonzalez-Huarriz, M., Phoenix, T.N., et al. (2025). Targeting the CD40 costimulatory receptor to improve virotherapy efficacy in diffuse midline gliomas. Cell Rep Med 6 , 102204. https://doi.org/10.1016/j.xcrm.2025.102204. Li, H., Zhang, H., Dai, R., Zheng, D., Zhao, J., Jing, H., Ma, X., Zhang, L., Sun, W., and Suo, Z. (2025). CD68 as a multi-omic prognostic biomarker in digestive system cancers: correlations with tumor-infiltrating immune cells and immune checkpoints. Front Immunol 16 , 1599677. https://doi.org/10.3389/fimmu.2025.1599677. Yan, J., Zhang, Y., Du, S., Hou, X., Li, W., Zeng, C., Zhang, C., Cheng, J., Deng, B., McComb, D.W., et al. (2022). Nanomaterials-Mediated Co-Stimulation of Toll-Like Receptors and CD40 for Antitumor Immunity. Adv Mater 34 , e2207486. https://doi.org/10.1002/adma.202207486. Yang, F., He, Z., Duan, H., Zhang, D., Li, J., Yang, H., Dorsey, J.F., Zou, W., Nabavizadeh, S.A., Bagley, S.J., et al. (2021). Synergistic immunotherapy of glioblastoma by dual targeting of IL-6 and CD40. Nat Commun 12 , 3424. https://doi.org/10.1038/s41467-021-23832-3. Eliopoulos, A.G., Stack, M., Dawson, C.W., Kaye, K.M., Hodgkin, L., Sihota, S., Rowe, M., and Young, L.S. (1997). Epstein-Barr virus-encoded LMP1 and CD40 mediate IL-6 production in epithelial cells via an NF-kappaB pathway involving TNF receptor-associated factors. Oncogene 14 , 2899–2916. https://doi.org/10.1038/sj.onc.1201258. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-8331704","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":583618668,"identity":"32f67891-3339-4ece-a3dd-c21eccb957b1","order_by":0,"name":"yuchuan Zhou","email":"","orcid":"","institution":"Affiliated Hospital of North Sichuan Medica College","correspondingAuthor":false,"prefix":"","firstName":"yuchuan","middleName":"","lastName":"Zhou","suffix":""},{"id":583618669,"identity":"e8a5fd66-083f-4597-aba5-e2dd40074244","order_by":1,"name":"Zhonghui Jiang","email":"","orcid":"","institution":"Affiliated Hospital of North Sichuan Medica College","correspondingAuthor":false,"prefix":"","firstName":"Zhonghui","middleName":"","lastName":"Jiang","suffix":""},{"id":583618670,"identity":"79fdf7af-3730-4ebb-8ec8-9a43cb3ab8aa","order_by":2,"name":"Shu Peng","email":"","orcid":"","institution":"Nanchong Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shu","middleName":"","lastName":"Peng","suffix":""},{"id":583618671,"identity":"1d9d24d7-2587-4f69-999a-ff0f7a2da5d5","order_by":3,"name":"Yue Xiang","email":"","orcid":"","institution":"Affiliated Hospital of North Sichuan Medica College","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Xiang","suffix":""},{"id":583618672,"identity":"0c6ae9da-8889-47fd-bdc9-9e9dc42e1009","order_by":4,"name":"Guoyi Li","email":"","orcid":"","institution":"Affiliated Hospital of North Sichuan Medica College","correspondingAuthor":false,"prefix":"","firstName":"Guoyi","middleName":"","lastName":"Li","suffix":""},{"id":583618673,"identity":"38532fe6-dc56-43db-883f-0c338c66359b","order_by":5,"name":"Caihong Luo","email":"","orcid":"","institution":"Affiliated Hospital of North Sichuan Medica College","correspondingAuthor":false,"prefix":"","firstName":"Caihong","middleName":"","lastName":"Luo","suffix":""},{"id":583618674,"identity":"d059ad15-3ab1-4073-a5df-670f5267215f","order_by":6,"name":"Zhike Li","email":"","orcid":"","institution":"Affiliated Hospital of North Sichuan Medica College","correspondingAuthor":false,"prefix":"","firstName":"Zhike","middleName":"","lastName":"Li","suffix":""},{"id":583618675,"identity":"2230247c-7278-4c12-9c78-46f00c77ac79","order_by":7,"name":"Yan Gui","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIie3PoQ6CQBzH8T/DneWUekyEV4Dsixi5sWFyMxIMbLojOLqPYSSajnJ2bPAAbto0OAV1Ro7o5n3DBfb/7DcAVKqfTIub1wJAWulHy+4E10R3S8G7bzUEmdVal58604CRWwbYzXkY0RiBkWz8VuIVlJmpqIkIeUEzC4g47NrJljIyYDUp+qygAoFL5nJi3j9kQZkuJw6hbPReQRw6ERdXq8m4JqYIA+ILjqX/4iSz6nhiYA9z7l2u0dI2klSysoceAXh8P+DW89dKDPpZeqVSqVT/3RNlUEZDQgSrCgAAAABJRU5ErkJggg==","orcid":"","institution":"Affiliated Hospital of North Sichuan Medica College","correspondingAuthor":true,"prefix":"","firstName":"Yan","middleName":"","lastName":"Gui","suffix":""}],"badges":[],"createdAt":"2025-12-11 02:23:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8331704/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8331704/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101648537,"identity":"5c9a40d9-ec84-4862-b74e-ba2865aa25b0","added_by":"auto","created_at":"2026-02-02 08:58:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":855416,"visible":true,"origin":"","legend":"\u003cp\u003eStudy workflow and pathology outcomes post-neoadjuvant therapy for EAC. A. Group the pathological results of EAC post-neoadjuvant therapy by TRG grading, and analyze differential molecules and mechanisms between the groups using RNA-seq and OLINK; B. Pathological results for an esophageal adenocarcinoma patient with a TRG grade of 1 post-neoadjuvant therapy revealed no tumor cells, but extensive immune cell infiltration and fibrosis; C. Pathological results for a patient with esophageal adenocarcinoma, graded TRG 4 after neoadjuvant therapy, revealed numerous tumor cells, minimal immune cells, and limited fibrous tissue; EAC：Esophageal adenocarcinoma；TRG：Tumor regression grade;\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8331704/v1/b30c3f883c93842c35a2caeb.png"},{"id":101648622,"identity":"587209f8-69c5-47ba-8cee-2d33cc0e16c8","added_by":"auto","created_at":"2026-02-02 08:59:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":328501,"visible":true,"origin":"","legend":"\u003cp\u003eTranscriptome Sequencing Results and Bioinformatics Analysis. A. Volcano plot of DEP: RNA-seq analysis reveals 229 differentially expressed genes in the R group compared to the NR group, with 37 upregulated and 192 downregulated; B-D. GO, DO, and top 20 of KEGG enrichment; DEP: differential\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8331704/v1/2438ea1861e154e2cb6c987d.png"},{"id":101648546,"identity":"0cb0d288-09e2-412c-b0d1-11bd6ff21ef3","added_by":"auto","created_at":"2026-02-02 08:59:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":408831,"visible":true,"origin":"","legend":"\u003cp\u003eBioinformatic analysis of Olink inflammation-related biomarkers. A. Barplot of GO enrichment for Olink inflammation biomarkers in R vs NR; B. Barplot of the top 20 InterPro enrichments; C. DO enrichment scatterplot; D. KEGG enrichment barplot; GO: Gene Ontology; DO: Disease Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes;**** p\u0026lt; 0.0001\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8331704/v1/58a99055717aa4aaa26cc23d.png"},{"id":101648562,"identity":"13f8dd7b-d211-4352-8323-00dd8730524f","added_by":"auto","created_at":"2026-02-02 08:59:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":180271,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of Differentially Expressed Inflammation-Related Biomarkers and Their Association with Survival Using Olink Technology. B. In the Kaplan-Meier plot analysis platform, the survival curve analysis reveals a statistically significant difference between IL6 and CD40（p\u0026lt; 0.05）.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8331704/v1/dc73ed50cef281d70dc585d7.png"},{"id":104200270,"identity":"cc7bcb94-db58-451b-918c-c5340d00ad08","added_by":"auto","created_at":"2026-03-09 05:10:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2281982,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8331704/v1/d8ac1c28-db1f-4437-8a5b-151ff07dda88.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"IL6 and CD40 Identified by OLINK Proteomics as Potential Biomarkers for Evaluating Neoadjuvant Immune-Chemotherapy Efficacy in Esophageal Adenocarcinoma.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEsophageal cancer significantly impacts public health, with GLOBOCAN 2022 reporting around 510,000 new cases and 440,000 deaths globally each year, making up 4.6% of cancer deaths\u003csup\u003e1\u003c/sup\u003e. In China, esophageal squamous cell carcinoma constitutes about 85% of cases, while EAC makes up 10%\u003csup\u003e2\u003c/sup\u003e. The 5-year survival rate for esophageal squamous cell carcinoma is 20\u0026ndash;30%, but it improves to 60\u0026ndash;80% with early-stage surgical treatment and 30\u0026ndash;50% with neoadjuvant therapy and surgery for locally advanced stages. EAC is prevalent in Western countries and predominantly occurs in the distal esophagus. Characterized by its insidious onset and aggressive nature, EAC has a 5-year survival rate that is marginally lower than that of squamous cell carcinoma, generally ranging from 15% to 25%.\u003csup\u003e3\u003c/sup\u003e. It often goes undetected until advanced stages, making surgery unfeasible for many. Even with surgery, early lymph node metastasis leads to poor outcomes. Standard treatments like chemotherapy, radiotherapy, and surgery have limited success in improving survival rates\u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eNeoadjuvant chemotherapy has been a standard for resectable esophageal cancer\u003csup\u003e5\u003c/sup\u003e, boosting resection rates from 60% to 70\u0026ndash;80% compared to surgery alone. However, it only modestly improves 5-year survival rates by 5\u0026ndash;10% and has a low pathological complete response (pCR) rate of 5\u0026ndash;10%\u003csup\u003e6\u003c/sup\u003e. It also causes significant side effects like myelosuppression and neuropathy, affecting quality of life and treatment adherence\u003csup\u003e7\u003c/sup\u003e. Recently, immune checkpoint inhibitors, particularly anti-PD-1/PD-L1 antibodies, have transformed cancer treatment, including for esophageal cancer\u003csup\u003e8910\u003c/sup\u003e. Recent single-arm studies over the past five years have shown that neoadjuvant immunotherapy in esophageal cancer achieves pCR rates of 10\u0026ndash;20%\u003csup\u003e11\u003c/sup\u003e. However, single-agent neoadjuvant immunotherapy has limitations, including low objective response rates and many patients not responding due to resistance mechanisms like an immunosuppressive tumor microenvironment\u003csup\u003e12\u003c/sup\u003e. To address these issues, combining chemotherapy with immunotherapy is a promising approach, as chemotherapy can kill tumor cells and enhance the tumor microenvironment's immunogenicity. Chemotherapy releases tumor-associated antigens and cytokines, enhancing immune cell activation and boosting immunotherapy effects\u003csup\u003e1314\u003c/sup\u003e. Recent clinical trials highlight the benefits of combining neoadjuvant chemotherapy with immunotherapy. In 2024, an article published in Nature Medicine reported that among 491 patients with thoracic esophageal squamous cell carcinoma (ESCC), the pCR rate was 28.0% in the chemo-immunotherapy group, compared to 4.7% in the traditional chemotherapy group\u003csup\u003e15\u003c/sup\u003e. Additionally, a study in China found a two-year overall survival rate of 81.3% for the combined treatment, compared to 71.3% for traditional therapy\u003csup\u003e16\u003c/sup\u003e. The safety of neoadjuvant chemo-immunotherapy is acceptable, with grade\u0026thinsp;\u0026ge;\u0026thinsp;3 treatment-related adverse events occurring at a similar rate (13\u0026ndash;15%) as in traditional chemotherapy (10\u0026ndash;12%)Most immune-related adverse events, like thyroid function impairment, are mild, manageable, and often reversible. \u003csup\u003e17181920\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDespite significant advancements in the integration of neoadjuvant immunotherapy with chemotherapy, substantial variability persists in patient treatment responses. Some patients achieve a pCR and enjoy markedly prolonged survival, while others exhibit limited therapeutic efficacy. A thorough investigation into the factors contributing to these disparities is essential for optimizing treatment protocols and advancing precision medicine. Current research suggests that variations in therapeutic outcomes may be attributed to a range of factors, including individual genetic profiles, the tumor microenvironment, and immune status\u003csup\u003e2122\u003c/sup\u003e. In summary, the combination of chemotherapy and immunotherapy in the neoadjuvant setting holds promise for enhancing pCR rates and survival outcomes in patients with esophageal cancer, while maintaining an acceptable safety profile. Nonetheless, further research is required to identify predictive biomarkers, refine therapeutic regimens, and expand the applicability of this approach.\u003c/p\u003e \u003cp\u003eThis study conducts an analysis of samples from patients with EAC who have undergone neoadjuvant treatment, categorizing them based on their response to the therapy. The research utilizes Olink immunoproteomics to identify differential molecules, with the goal of discovering potential biomarkers. The primary aim is to investigate the mechanisms underlying the varying efficacy of neoadjuvant chemoimmunotherapy by examining immune-related proteins. This approach seeks to provide a novel theoretical framework and identify biomarkers for the precision treatment of esophageal cancer. The study focuses on pinpointing key immune factors that affect the success of neoadjuvant chemoimmunotherapy by analyzing the expression of immune-related proteins in patients exhibiting either \"good\" or \"poor\" treatment responses, employing Olink technology. By exploring differential proteins and their associated signaling pathways, this research aspires to furnish more precise guidance for clinical practice.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population and data collection\u003c/h2\u003e \u003cp\u003eIn this study, 14 patients diagnosed with EAC were recruited to receive neoadjuvant immunochemotherapy. The treatment regimen consisted of 2 cycles of neoadjuvant therapy, incorporating a platinum-based chemotherapy agent and a PD-1 inhibitor as the immunotherapeutic component. Upon completion of the neoadjuvant therapy, a comprehensive evaluation was conducted to determine tumor progression. Patients demonstrating no evidence of disease progression and absence of distant metastasis were deemed eligible for radical surgical intervention. Subsequently, the thoracic surgery department performed a radical esophagectomy. The pathology department then utilized Mandard\u0026rsquo;s Tumor Regression Grade (TRG) \u003csup\u003e23\u003c/sup\u003eto evaluate the efficacy of the neoadjuvant therapy in treating esophageal cancer. Patients with TRG grades 1\u0026ndash;2 were classified as responders to the neoadjuvant therapy, while those with TRG grades 3\u0026ndash;5 were categorized as non-responders.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRNA-Seq and Bioinformatics\u003c/h3\u003e\n\u003cp\u003eEAC samples, obtained from radical resections following neoadjuvant therapy, were classified into responder and non-responder groups utilizing the OLINK classification methodology. Subsequent RNA sequencing (RNA-seq) and bioinformatics analyses were performed, with three biological replicates designated for each experimental condition. Total RNA was extracted using the TRIzol\u0026reg; reagent, and complementary DNA (cDNA) libraries were constructed prior to sequencing on the Illumina NovaSeq 6000 platform. Differential expression analysis between the two groups was conducted using DESeq2 (version 1.20.0). This analysis was followed by enrichment analyses of the differentially expressed genes, employing the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Olink Proteomics was utilized in this study.\u003c/p\u003e\n\u003ch3\u003eOLINK Immunoproteomics\u003c/h3\u003e\n\u003cp\u003ePostoperative specimens were obtained from 14 patients diagnosed with neoadjuvant EAC, and the expression levels of inflammatory factors were subsequently analyzed using OLINK Immunoproteomics technology. This technology employs the Proximity Extension Assay (PEA) technique, which is based on dual antibody recognition. In this method, each target protein is bound by a pair of antibodies, with each antibody conjugated to a unique DNA oligonucleotide. When these antibody-oligonucleotide complexes bind in close proximity on the same protein molecule, they facilitate the hybridization of the oligonucleotides. This process results in the generation of a specific DNA amplification product through polymerase-mediated extension. Quantification is conducted via microfluidic real-time quantitative PCR (qPCR), wherein each oligonucleotide tag is associated with a specific protein. This methodology permits the simultaneous analysis of up to 96 inflammatory proteins per reaction. The signal intensity correlates directly with protein concentration, thereby enabling highly sensitive and specific absolute quantification. The results are expressed as normalized protein expression (NPX) values on a log2 scale, with elevated values indicating increased protein expression. The validation data, encompassing detection limits and precision metrics, are accessible on the manufacturer's website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ewww.olink.com\u003c/span\u003e\u003cspan address=\"http://www.olink.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Following quality control and log2 normalization, the data are expressed as normalized protein expression (NPX), with the median value serving as an indicator of protein expression levels. Normalization is achieved through Olink's proprietary algorithm, which incorporates background subtraction and inter-plate calibration using internal controls. A t-test is employed to identify differentially expressed proteins (DEPs) between the two groups when the p-value is less than 0.05. Clustering analysis of DEPs, based on serum protein expression profiles, is conducted using heatmaps.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSurvival Analysis and Bioinformatics using OLINK Immunoproteomics Data.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe DEPs is illustrated using volcano plots, followed by functional analyses based on Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). These bioinformatics analyses were performed by LC-Bio Technology Co., Ltd. (Hangzhou, China). Additionally, we employed KMplot (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://kmplot.com/analysis/\u003c/span\u003e\u003cspan address=\"https://kmplot.com/analysis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), a tool commonly used for survival analysis, to conduct statistical evaluations.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData from two unpaired groups were analyzed using an unpaired t-test for parametric data or a Mann-Whitney test for non-parametric data. For more than three groups, a one-way ANOVA was used for parametric data, and a Kruskal-Wallis test for non-parametric data, with post-hoc analyses for significant differences. All analyses were conducted using GraphPad Prism 10.1.0. Quantitative variables are shown as median\u0026thinsp;\u0026plusmn;\u0026thinsp;IQR, and categorical variables as proportions. The Wilcoxon test was applied for non-normally distributed variables, and Fisher\u0026rsquo;s exact test for two categorical variables. Survival analysis utilized a Kaplan-Meier plot with a log-rank test p value. Significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (*) and p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 (**).\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eClinical characteristics of the participants and tumor tissue samples\u003c/h2\u003e \u003cp\u003eBetween January 2024 and January 2025, a total of 14 patients were diagnosed with esophageal adenocarcinoma at our hospital. These patients were enrolled in a study where they received a two-cycle neoadjuvant immunochemotherapy regimen, which included anti-PD-1 immune checkpoint inhibitors (ICIs) in combination with a platinum-based doublet chemotherapy regimen. Following this treatment, all patients underwent a radical esophagogastrectomy, and subsequent postoperative pathological examinations were conducted (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). According to Mandard's Tumor Regression Grade (TRG) system, patients with scores of 1\u0026ndash;2 were classified as responders (R), while those with scores of 3\u0026ndash;5 were classified as non-responders (NR). Our observations indicated that patients with TRG grades 1\u0026ndash;2, following neoadjuvant immunochemotherapy, exhibited pathological sections with minimal residual tumor cells, which were predominantly replaced by fibrous tissue (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). In contrast, patients with TRG grades 3\u0026ndash;5 showed pathological sections with a substantial presence of residual tumor cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Ultimately, 7 patients were identified as responders, and the remaining 7 were classified as non-responders. There were no significant differences in clinical characteristics between responders and non-responders at baseline. Consequently, we collected tumor tissues from these 14 patients to conduct paired tissue proteomic assays and RNA sequencing after surgery.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTranscriptome Sequencing Results and Bioinformatics Analysis\u003c/h3\u003e\n\u003cp\u003eTo examine the molecular alterations in esophageal cancer following neoadjuvant immunochemotherapy, we performed transcriptome sequencing on tumor tissues. Our analysis identified 229 differentially expressed genes between the treated and control groups, with 37 genes upregulated and 192 genes downregulated in the treated group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Subsequent Gene Ontology (GO) enrichment analysis of Biological Processes revealed significant enrichment in pathways related to anatomical structure development, organ induction, anterior/posterior pattern specification, embryonic skeletal system morphogenesis, positive regulation of ubiquitin-protein transferase activity, regulation of transcription by RNA polymerase II, and signal transduction mediated by the p53 class. In terms of Molecular Function, significant enrichment was observed in histone deacetylase binding, sequence-specific double-stranded DNA binding, DNA-binding transcription factor activity, and RNA polymerase II specificity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Disease Ontology (DO) enrichment analysis indicated a relatively weak specificity of disease association for the differentially expressed genes, with predominant associations observed with melanoma and squamous cell carcinoma (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). KEGG enrichment analysis was conducted, revealing significant enrichment in retinol metabolism, metabolism of xenobiotics by cytochrome P450, transcriptional misregulation in cancer and other signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eOlink Inflammation-Related Biomarker Analysis\u003c/h3\u003e\n\u003cp\u003eTo examine the response of Inflammation-Related Biomarker at EAC treated with neoadjuvent immunochemotherapy, we performed an Olink proteomic analysis. This technique was utilized to evaluate and compare the expression levels of 92 inflammation-related proteins between the treated and control groups. A total of 7 differentially expressed inflammation-related proteins were identified between R and NR groups, of which 7 were downregulated in the responsed group (Fig.\u0026nbsp;4A). Among them, IL6, CXCL1, MUC16, VEGFA, TNFASF12A, CD40 and MCP4 was significantly expressed. Subsequent GO enrichment analysis of Biological Processes revealed significant enrichment in pathways related to inflammatory response, cellular response to lipopolysaccharide, positive regulation of MAPK cascade et al. In terms of top 20 of interpro enrichment observed in mucin-16, SEA domain, IL-6, IL-6/GCSF/MGF, TNFR12, VEGF (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Disease Ontology (DO) enrichment analysis indicated disease association for the differentially expressed proteins, with predominant associations observed with ovarian carcinoma, atherosclerosis, sarcoma and temporal arteritis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). KEGG enrichment analysis was conducted, revealing significant enrichment in cytokine\u0026ndash;cytokine receptor interactions, viral protein interaction with cytokine\u0026ndash;cytokine receptor interactions, NF-kappaB signaling pathways and other signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe predictive and prognostic significance of the inflammation factor in EAC neoadjuvant immunochemotherapy.\u003c/p\u003e \u003cp\u003eFollowing the screening of seven molecules using OLINK sequencing, we proceeded to validate their impact on the survival outcomes of esophageal cancer patients. This validation was conducted using the public database analysis platform KMplot (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://kmplot.com/analysis/\u003c/span\u003e\u003cspan address=\"https://kmplot.com/analysis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), which is widely utilized for survival analysis. KMplot aggregates data from the GEO, EGA, and TCGA databases, thereby facilitating the assessment of the correlation between gene expression and patient survival across more than 30,000 samples from 21 tumor types. This enables the identification and validation of survival-related biomarkers. In our study, a cohort of 80 patients was analyzed to evaluate the impact of differential protein expression on the survival curves of esophageal cancer patients. The findings indicated that for the 36-month overall survival (OS), proteins such as CD40 and IL6 exhibited statistically significant p-values (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Other indicators demonstrated a trend but did not reach statistical significance. Notably, the analysis results for MCP4 remain incomplete. It is important to note that the sample size for esophageal cancer data is limited, necessitating further data collection and support in future research endeavors.\u003c/p\u003e \u003cp\u003eFigure 4༎Analysis of Differentially Expressed Inflammation-Related Biomarkers and Their Association with Survival Using Olink Technology. B. In the Kaplan-Meier plot analysis platform, the survival curve analysis reveals a statistically significant difference between IL6 and CD40(p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eEsophageal cancer exhibits a high incidence rate in China, characterized by distinct regional distribution patterns. Patients who attain a major pathological response or a complete pathological response following neoadjuvant therapy generally have a favorable prognosis\u003csup\u003e24\u003c/sup\u003e. This is particularly evident in cases where neoadjuvant chemoradiotherapy is combined with immunotherapy, demonstrating significant efficacy\u003csup\u003e25\u003c/sup\u003e. Nevertheless, approximately 50% of patients exhibit a poor response to neoadjuvant therapy\u003csup\u003e26\u003c/sup\u003e. The underlying mechanisms of this variability in response remain unclear, and further research is needed to develop methods for evaluating the efficacy of neoadjuvant therapy prior to surgical intervention. The efficacy of neoadjuvant immunotherapy for esophageal cancer can be demonstrated in several aspects: 1. Significant improvement in eating obstruction, reduction in patient nutritional risk scores, and weight gain; 2. Imaging assessment, using RECIST 1.1 criteria to evaluate tumor regression\u003csup\u003e27\u003c/sup\u003e; 3. Postoperative pathology; 4. Tumor markers, etc., although these indicators all have certain limitations\u003csup\u003e28\u003c/sup\u003e. Developing earlier and more sensitive detection methods can help adjust neoadjuvant treatment plans and courses, improving efficacy for esophageal cancer patients\u003csup\u003e2930\u003c/sup\u003e. In the era of immunotherapy, due to the advantages of tumor immunity in anti-cancer treatment, it has been gradually recognized that immune response is also one of the methods to assess tumor efficacy\u003csup\u003e3132\u003c/sup\u003e. This study compiles clinical standards for patients with esophageal cancer following neoadjuvant therapy and suggests categorizing them into a 'response group' and a 'non-response group' based on pathological remission. Utilizing Olink technology\u003csup\u003e32\u003c/sup\u003e, the expression levels of immune-inflammatory factors were analyzed between the two groups. Through the integration of bioinformatics and survival curve data from relevant databases, two candidate factors, IL-6 and CD40, were identified as potential indicators of the efficacy of clinical neoadjuvant therapy. Specifically, monitoring the changes in these two factors during the treatment process may facilitate the assessment of the tumor's response to neoadjuvant therapy.\u003c/p\u003e \u003cp\u003eInterleukin-6 (IL-6), a pleiotropic cytokine, activates the signal transducer and activator of transcription 3 (STAT3) via both classical and trans-signaling pathways, thereby regulating critical processes such as tumor proliferation, angiogenesis, and immune evasion\u003csup\u003e33\u003c/sup\u003e. In malignancies such as colorectal cancer and non-small cell lung cancer, elevated IL-6 expression is correlated with poor prognosis. IL-6 upregulates programmed death-ligand 1 (PD-L1) expression, suppresses CD8⁺ T cell infiltration, and recruits myeloid-derived suppressor cells and M2 macrophages\u003csup\u003e343536\u003c/sup\u003e, thus fostering an immunosuppressive microenvironment and diminishing therapeutic efficacy\u003csup\u003e37\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the context of neoadjuvant therapy for esophageal cancer, dynamic alterations in IL-6 levels are closely associated with therapeutic efficacy. Empirical evidence indicates that a reduction in IL-6 concentrations during treatment is significantly correlated with extended progression-free survival, suggesting that IL-6 may serve as an indicator of the therapy's remodeling effect on the tumor microenvironment\u003csup\u003e38\u003c/sup\u003e. The present study further corroborates that in patients exhibiting poor therapeutic response, IL-6 levels remain elevated post-treatment, aligning with its role in safeguarding tumor cells against treatment-induced DNA damage and apoptosis. Compared to liquid biopsy markers such as circulating tumor DNA (ctDNA), IL-6 testing offers a more convenient and rapid means of assessing treatment efficacy, making it particularly advantageous in clinical settings with constrained resources\u003csup\u003e39\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs a constituent of the tumor necrosis factor receptor family, CD40 is aberrantly expressed in a range of malignancies, and its pathway activation can mediate anti-tumor effects through diverse mechanisms. Firstly, the activation of CD40 can directly suppress tumor cell proliferation and enhance their susceptibility to radiotherapy and chemotherapy. Secondly, by activating dendritic cells, CD40 facilitates antigen presentation and the initiation of anti-tumor immune responses, a process that is positively associated with the degree of CD8⁺ T cell infiltration\u003csup\u003e4041\u003c/sup\u003e. In the context of esophageal cancer treatment, the expression status of CD40 has not been extensively investigated; however, existing mechanistic studies have yielded significant insights. Given the pivotal role of the CD40 pathway in modulating the tumor immune microenvironment, its expression level may serve as an indicator of immune function recovery post-treatment\u003csup\u003e42\u003c/sup\u003e. In this study, the cohort exhibiting more favorable treatment outcomes demonstrated low CD40 expression, which appears to contradict the hypothesis that CD40-mediated immune activation enhances treatment efficacy\u003csup\u003e43\u003c/sup\u003e. This finding also diverges from previous research suggesting that the CD40 pathway can augment the synergistic effects of radiotherapy and chemotherapy. A plausible explanation is that, following increased sensitivity to neoadjuvant therapy, the tumor burden diminishes, resulting in decreased expression of tumor immune molecules. This observation broadens the potential application of CD40 in monitoring therapeutic efficacy in solid tumors and offers a novel avenue for predicting the success of combined immunotherapy.\u003c/p\u003e \u003cp\u003eIn various other cancer types, IL-6 and CD40 are typically considered biomarkers from the dual perspectives of immunosuppression and immune activation, respectively. However, their roles differ in the context of assessing the tumor microenvironment status following neoadjuvant therapy for esophageal cancer. Elevated IL-6 expression indicates persistent immunosuppression, while increased CD40 expression is associated with a suboptimal anti-tumor immune response. The concurrent assessment of these biomarkers may enhance the precision of treatment efficacy evaluations\u003csup\u003e4445\u003c/sup\u003e. A significant limitation of this study is the small sample size, which can be attributed to the relatively low incidence of esophageal adenocarcinoma in the Chinese population. Future research should consider testing serum using CD40 and IL-6 markers. Consequently, prospective large-scale studies are warranted to substantiate these findings. Future investigations could delve into the relationship between the expression ratio of these molecules and both the pathological complete response rate and overall survival, with the aim of refining diagnostic thresholds. Additionally, incorporating markers such as circulating tumor DNA to develop a multidimensional evaluation framework could facilitate the transition of esophageal cancer treatment from an empirical to a molecularly-driven approach. Furthermore, the combined application of IL-6 pathway inhibitors and CD40 atagonists may emerge as a novel strategy to enhance the prognosis of patients exhibiting poor responses to treatment.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur research suggests that the effectiveness of neoadjuvant therapy in esophageal cancer can be assessed using CD40 and IL-6 as biomarkers. This approach offers a novel auxiliary method for monitoring neoadjuvant therapy in esophageal cancer. However, further validation through peripheral blood analysis in subsequent prospective studies is necessary.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in line with the Declaration of Helsinki and approved by the Ethics Committee of Affiliated Hospital of North Sichuan Medical College, thus alleviating patients of the requirement to sign a written informed consent form (ethics number,\u0026nbsp;2024ER796-01). All research experiments were conducted in accordance with the principles of the Declaration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have nothing to report.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available on request from the corresponding author(NCBI accession number acc=GSE315001). The data are not publicly available due to privacy or ethical restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all the professors who provided support for this study and thank the editors as well as reviewers for reading the manuscript.\u0026nbsp;This study was supported by special Project of the Science and Technology Plan, Nanchong Science and Technology Bureau (Grant No. 23JCYJPT0061), and the High-Level Talent Research Start-up Project of the Affiliated Hospital of North Sichuan Medical College (No. 2023-2GC017).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYuchuan Zhou: conceptualization; validation; writing \u0026ndash; original draft; writing \u0026ndash; review and editing; software. Zhonghui Jiang: data curation; investigation; project administration. Shu Peng: methodology; formal analysis. Yue Xiang: project administration; investigation. Guoyi Li: methodology; software. Caihong Luo: methodology; formal analysis; supervision. Zhike Li: writing \u0026ndash; review and editing; data curation; formal analysis. Yan Gui: funding acquisition; visualization; project administration; supervision; resources; data curation; methodology. Yuchuan Zhou and Zhonghui Jiang contributed equally to this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBray, F., Laversanne, M., Sung, H., Ferlay, J., Siegel, R.L., Soerjomataram, I., and Jemal, A. (2024). Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. 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Oncogene \u003cem\u003e14\u003c/em\u003e, 2899\u0026ndash;2916. https://doi.org/10.1038/sj.onc.1201258.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8331704/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8331704/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Esophageal cancer ranks among the top six malignancies in terms of mortality rates in China. The integration of neoadjuvant immunotherapy with chemotherapy has improved treatment outcomes for resectable esophageal adenocarcinoma (EAC); however, more than 50% of patients demonstrate suboptimal responses to neoadjuvant therapy. Currently, aside from imaging modalities and postoperative pathological evaluations, there is a notable lack of effective molecular biomarkers for monitoring the efficacy of neoadjuvant treatments.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e:\u0026nbsp;EAC\u0026nbsp;patients who have received neoadjuvant immunochemotherapy should be stratified into two cohorts according to the efficacy of the treatment. Subsequently, OLINK immunoproteomics can be employed to identify molecules that are differentially expressed between these two groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Utilizing OLINK proteomics, this study identifies IL6 and CD40 as differentially expressed and correlated with patient survival；\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThis study proposes CD40 and IL6 as potential biomarkers for assessing the clinical efficacy of neoadjuvant therapy in cases of esophageal adenocarcinoma (EAC). These findings are expected to enhance the evaluation of neoadjuvant therapy effectiveness in resectable EAC.\u003c/p\u003e","manuscriptTitle":"IL6 and CD40 Identified by OLINK Proteomics as Potential Biomarkers for Evaluating Neoadjuvant Immune-Chemotherapy Efficacy in Esophageal Adenocarcinoma.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-02 08:56:09","doi":"10.21203/rs.3.rs-8331704/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a0bd0f01-c3fa-42c7-b72b-398b89045234","owner":[],"postedDate":"February 2nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-12T15:09:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-02 08:56:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8331704","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8331704","identity":"rs-8331704","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}