Application of sIL-2R and CA19-9 as biomarkers in the preparation of prognostic assessment products for pancreatic ductal adenocarcinoma

Abstract

This invention provides the application of sIL-2R and CA19-9 as biomarkers in the preparation of prognostic assessment products for pancreatic ductal adenocarcinoma. This invention uses sIL-2R and CA19-9 as detection biomarkers, which can be obtained through routine preoperative blood tests, eliminating the need for invasive or high-cost examinations such as tissue biopsies or gene testing, making it suitable for widespread application in medical institutions at all levels. Compared to using only CA19-9 as a single biomarker, this invention, combined with sIL-2R, can identify high-risk patients with normal CA19-9 but elevated sIL-2R, overcoming the limitation of CA19-9's inapplicability in Lewis antigen-negative individuals. Furthermore, it provides prognostic information from the perspective of the immune microenvironment that CA19-9 cannot reflect, significantly improving the comprehensiveness and accuracy of prognostic assessment.

Description

Technical Field

[0001] This invention belongs to the field of biomedical technology, specifically involving the application of sIL-2R and CA19-9 as biomarkers in the preparation of prognostic assessment products for pancreatic ductal adenocarcinoma. Background Technology

[0002] Pancreatic ductal adenocarcinoma (PDAC) has an extremely poor prognosis; even with radical surgical resection, the recurrence rate remains very high. Accurate postoperative prognostic assessment is crucial for developing individualized adjuvant therapy plans and follow-up strategies.

[0003] Currently, the most commonly used serum biomarker for pancreatic cancer in clinical practice is CA19-9 (carbohydrate antigen 19-9), which is the only serum biomarker approved by the FDA for pancreatic cancer surveillance. CA19-9 is mainly used to assist in diagnosis, monitor treatment response, and assess prognosis. However, CA19-9 has significant limitations in pancreatic cancer prognostic assessment: approximately 5-10% of Lewis antigen-negative individuals do not secrete CA19-9; CA19-9 is affected by benign diseases such as biliary obstruction, leading to a high false-positive rate; as a single biomarker, its sensitivity and specificity for prognostic assessment are limited, and it cannot comprehensively reflect tumor biological behavior and host immune status.

[0004] Pancreatic ductal adenocarcinoma lacks serum prognostic markers that reflect the state of the tumor immune microenvironment. Currently used clinical serum markers for pancreatic cancer (CA19-9, CEA, etc.) are all tumor-derived markers and cannot reflect the interaction between the tumor and the host immune system. However, the immune microenvironment is a key factor influencing the prognosis of pancreatic cancer. Therefore, there is an urgent need for a combined prognostic assessment system integrating tumor markers and immune markers. Soluble interleukin-2 receptor (sIL-2R) is a soluble form of the IL-2 receptor α chain (CD25), which can be released into the bloodstream via cell membrane cleavage. The prognostic value of sIL-2R in pancreatic cancer and its combined application with CA19-9 for prognostic assessment of pancreatic cancer have not been systematically studied or reported before. Summary of the Invention

[0005] This invention provides the application of sIL-2R and CA19-9 as biomarkers in the preparation of prognostic assessment products for pancreatic ductal adenocarcinoma; the application of substances that detect sIL-2R and CA19-9 in the preparation of prognostic assessment products for pancreatic ductal adenocarcinoma; a kit for prognostic assessment of pancreatic cancer; a method for constructing a personalized prognostic prediction model for pancreatic cancer; and the integration of tumor markers and immune markers in this invention can significantly improve the comprehensiveness and accuracy of prognostic assessment.

[0006] This invention provides the application of sIL-2R and CA19-9 as biomarkers in the preparation of prognostic assessment products for pancreatic ductal adenocarcinoma.

[0007] This invention provides the application of substances that detect sIL-2R and CA19-9 in the preparation of prognostic assessment products for pancreatic ductal adenocarcinoma.

[0008] Furthermore, the above prognostic assessment includes risk prediction of patients' postoperative overall survival and recurrence-free survival.

[0009] This invention provides a kit for prognostic assessment of pancreatic cancer, the kit comprising:

[0010] (1) sIL-2R detection reagent: contains microparticles coated with anti-human IL-2Rα monoclonal antibody, enzyme-labeled anti-human IL-2Rα monoclonal antibody, chemiluminescent substrate and sIL-2R standard;

[0011] (2) CA19-9 detection reagent: contains microparticles coated with anti-CA19-9 monoclonal antibody, enzyme-labeled anti-CA19-9 monoclonal antibody, chemiluminescent substrate and CA19-9 standard.

[0012] The kit in this invention also includes prognostic criteria: including the optimal cutoff value for each biomarker, prognostic risk grouping scheme, and reference interpretation instructions.

[0013] Furthermore, the above-mentioned kits are grouped by risk according to the following criteria:

[0014] Low-risk group: sIL-2R level < cutoff value and CA19-9 level < cutoff value;

[0015] Intermediate-risk group: sIL-2R level ≥ cutoff value or CA19-9 level ≥ cutoff value;

[0016] High-risk group: sIL-2R level ≥ cutoff value and CA19-9 level ≥ cutoff value.

[0017] The cutoff values ​​for the aforementioned markers are determined based on survival data using the surv_cutpoint function in the survminer package of the R language.

[0018] Furthermore, the cutoff value for sIL-2R is 295 U / ml, and the cutoff value for CA19-9 is 117.1 U / ml.

[0019] The cutoff values ​​for each laboratory may vary due to differences in experimental environment or conditions. Therefore, this section only provides the calculation method for the stage value, classifying patients into the following prognostic risk levels: Low-risk group: sIL-2R level < cutoff value and CA19-9 level < cutoff value; Medium-risk group: sIL-2R level ≥ cutoff value or CA19-9 level ≥ cutoff value; High-risk group: sIL-2R level ≥ cutoff value and CA19-9 level ≥ cutoff value.

[0020] Furthermore, sIL-2R is an independent prognostic factor for overall survival and recurrence-free survival after pancreatic cancer surgery.

[0021] Furthermore, there is a genetic causal relationship between sIL-2R and pancreatic cancer, specifically that pancreatic cancer causally leads to elevated serum sIL-2R levels.

[0022] This invention discloses a method for constructing a personalized prognostic prediction model for pancreatic cancer, the method comprising the following steps:

[0023] Obtain the preoperative serum sIL-2R and CA19-9 levels of the patient;

[0024] In conjunction with clinicopathological factors, the clinicopathological factors include at least one of T stage, N stage, degree of differentiation, tumor location, chemotherapy status, microvascular invasion, diabetes, and hypertension;

[0025] Construct a comprehensive prognostic scoring system or nomogram using the Cox regression model.

[0026] Furthermore, the sIL-2R level reflects the host's immunosuppressive state, and the CA19-9 level reflects the tumor burden. The two are used together to assess the tumor from two dimensions: tumor biology and host immunity.

[0027] In this invention, CA19-9 reflects tumor burden and sIL-2R reflects tumor-mediated immunosuppression. The combination of the two can provide a more comprehensive and accurate prognostic assessment of patients from both the dimensions of tumor biology and host immunity, which is superior to any single biomarker.

[0028] The bidirectional Mendelian randomization analysis of this invention confirms the causal direction of pancreatic cancer → elevated sIL-2R from a genetic perspective, providing causal inference evidence for sIL-2R as a prognostic marker for pancreatic cancer that surpasses traditional association analysis, thus enhancing the reliability of its clinical application.

[0029] This invention uses sIL-2R and CA19-9 as detection markers, which can be obtained through routine preoperative blood tests without the need for invasive or high-cost examinations such as tissue biopsy or gene testing, making it suitable for widespread application in medical institutions at all levels.

[0030] Compared with using only the single biomarker CA19-9, this invention, in combination with sIL-2R, can identify high-risk patients with normal CA19-9 but elevated sIL-2R, making up for the limitation of CA19-9 in Lewis antigen-negative populations, and providing prognostic information that CA19-9 cannot reflect from the perspective of the immune microenvironment, significantly improving the comprehensiveness and accuracy of prognostic assessment.

[0031] This invention is based on data from 453 consecutively enrolled PDAC surgery patients, with a sufficient sample size, a long follow-up period (January 2019 to May 2024), reliable data, and robust conclusions.

[0032] Even after incorporating known prognostic factors such as T stage, N stage, differentiation degree, and CA19-9, this invention still shows that sIL-2R remains an independent prognostic factor for OS and RFS, providing additional prognostic information independent of traditional clinicopathological indicators.

[0033] This invention has significant prognostic differentiation ability: the median overall survival (OS) difference between the high sIL-2R expression group and the low expression group was 36.3 months (26.0 months vs. 62.3 months), and the median remission rate (RFS) difference was 27.9 months (14.5 months vs. 42.4 months), with HRs of 2.138 and 1.813, respectively, demonstrating significant prognostic differentiation. Attached Figure Description

[0034] Figure 1 (AB) Scatter plot (A) and forest plot (B) show the causal effect of soluble interleukin-2 receptor levels on pancreatic ductal adenocarcinoma in the Finnish population; (CD) Scatter plot (A) and forest plot (B) show the causal effect of soluble interleukin-2 receptor levels on pancreatic ductal adenocarcinoma in the Greek population.

[0035] Figure 2 (AB) Scatter plot (A) and forest plot (B) show the causal effect of pancreatic ductal adenocarcinoma on soluble interleukin-2 receptor levels in the Finnish population; (CD) Scatter plot (A) and forest plot (B) show the causal effect of pancreatic ductal adenocarcinoma on soluble interleukin-2 receptor levels in the Greek population.

[0036] Figure 3 (A) OS (Outcome Scale) Kaplan-Meier survival curves for the high- and low-level sIL-2R groups. (B) RFS (Regression Scale) Kaplan-Meier survival curves for the high- and low-level sIL-2R groups. (C) Multivariate Cox regression forest plot (OS). (D) Multivariate Cox regression forest plot (RFS).

[0037] Figure 4(A) OS survival curves in patients with high sIL-2R levels and high / low CA19-9 levels; (B) RFS survival curves in patients with high sIL-2R levels and high / low CA19-9 levels; (C) OS survival curves in patients with low sIL-2R levels and high / low CA19-9 levels; (D) RFS survival curves in patients with low sIL-2R levels and high / low CA19-9 levels.

[0038] Figure 5 (A) Nonographs based on differentiation degree, N stage, CA19-9, sIL-2R, chemotherapy status, and neurological involvement were used to predict 1-year, 3-year, and 5-year overall survival (OS). (B) ROC curves and AUC of the nonograph model and the AJCC 8th edition TNM staging system for 1-year, 3-year, and 5-year OS were compared. (C) Calibration curves of the nonograph model for 1-year, 3-year, and 5-year OS were presented. (D) Decision curve analysis (DCA) of the nonograph model and the AJCC 8th edition TNM staging system was presented. Detailed Implementation

[0039] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to examples. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained in the art without creative effort should fall within the scope of protection of the present invention.

[0040] Unless otherwise specified, the experimental methods used in the following examples are conventional methods, performed according to the techniques or conditions described in the literature in this field or according to the product instructions. Unless otherwise specified, the materials and reagents used in the following examples are commercially available.

[0041] In this embodiment, the cases are from 453 consecutive cases of PDAC that were surgically removed and pathologically confirmed by a tertiary hospital in Fujian.

[0042] Example 1: Validation of sIL-2R as an independent prognostic factor for overall survival and recurrence-free survival after pancreatic cancer surgery.

[0043] 1. Experimental procedure:

[0044] Peripheral venous blood was collected from 453 patients with PDAC within 7 days prior to surgery. Serum was separated, and serum sIL-2R levels were detected using chemiluminescent immunoassay. The optimal cutoff value for sIL-2R was determined to be 295 U / ml using the `surv_cutpoint` function of the `survminer` package in R, based on overall survival (OS) data, using the maximum selection rank statistic. Patients were then divided into a high-sIL-2R group (≥295 U / ml) and a low-sIL-2R group (<295 U / ml) according to this cutoff value. OS and RFS survival curves were plotted using the Kaplan-Meier method, and differences between groups were compared using the Log-rank test. Prognostic factors with p<0.05 in univariate analysis were included in a multivariate Cox regression model to assess whether sIL-2R was an independent prognostic factor. Subgroup analyses were performed on the entire cohort to compare the risk factors (HRs) of high and low sIL-2R in each clinical subgroup. Interaction tests were used to assess the heterogeneity of the prognostic value of sIL-2R among different subgroups.

[0045] To determine the causal relationship between sIL-2R and pancreatic cancer, a two-way two-sample Mendelian randomization analysis was employed. This method uses genetic variants (SNPs) as instrumental variables, leveraging their random allocation at fertilization and independence from confounding factors to provide causal inferences similar to randomized controlled trials. Data were collected from two independent GWAS datasets from Finland (FinnGen) and Greece, and analyzed at a genome-wide significance level (p<5×10⁻⁻⁴). 8 SNPs were screened and instrumental variables were determined after linkage disequilibrium pruning (r² < 0.001, window 10,000 kb). Forward analysis (sIL-2R → pancreatic cancer) yielded 24 and 48 SNPs in the Finnish and Greek datasets, respectively; backward analysis (pancreatic cancer → sIL-2R) yielded 20 and 24 SNPs, respectively (Supplementary Tables 3-4 and 6-7). All instrumental variables had F-statistics > 10, excluding weak instrumental bias. The primary analysis used the fixed-effects inverse variance weighted method (IVW), and sensitivity analyses used MR-Egger, weighted median, weighted mode, and MR-PRESSO methods. Pleiotropy was assessed using the MR-Egger intercept test and the MR-PRESSO global test, and heterogeneity was assessed using Cochran's Q test. All analyses were performed in R software using the TwoSampleMR and MR-PRESSO packages.

[0046] 2. Experimental Results:

[0047] 2.1 Two-way Mendelian randomization analysis

[0048] In the positive MR analysis, no significant pleiotropy or heterogeneity was detected in either dataset. IVW analysis showed no causal association between genetically predicted sIL-2R levels and pancreatic cancer risk (Finland: p=0.95, OR=1.00; Greece: p=0.24, OR=0.94), and other sensitivity analyses yielded consistent results (see appendix). Figure 1 (Table 1).

[0049] Table 1. Causal relationship between serum sIL-2R and pancreatic cancer analyzed by two-way Mendelian randomization.

[0050] In the reverse MR analysis, the Finnish dataset showed that IVW causally elevated serum sIL-2R levels in pancreatic cancer (p=0.02, OR [95% CI]: 1.04 [1.01–1.07]), independently supported by the weighted mode (p=0.05, OR=1.05) and MR-PRESSO (p=0.02, OR=1.04). Consistent results were obtained from the Greek dataset (IVW: p=0.03, OR=1.04; weighted mode: p=0.05, OR=1.10) (see appendix). Figure 2 Key results are shown in Table 1.

[0051] 2.2 Survival Analysis and Independent Prognostic Value

[0052] With a cutoff of 295 U / ml, the median overall survival (OS) was 26.0 months in the high-level sIL-2R group and 62.3 months in the low-level group (p<0.001, HR [95% CI]: 2.138 [1.673–2.731]); the median remission rate of failure (RFS) was 14.5 months vs. 42.4 months (p<0.001, HR [95% CI]: 1.813 [1.416–2.320]). (See appendix) Figure 3 AB). Multivariate Cox regression analysis confirmed that sIL-2R was an independent prognostic factor for OS and RFS (p<0.05), independent of traditional parameters such as CA19-9, T stage, N stage, differentiation degree, and microvascular invasion (see appendix). Figure 3 CD).

[0053] Example 2: Comparison of sIL-2R and CA19-9 as detection markers versus single substance as detection markers

[0054] 1. Experimental Methods: Based on the cohort of 453 PDAC patients in Example 1, preoperative serum sIL-2R and CA19-9 levels were simultaneously obtained. The optimal cutoff values ​​for sIL-2R and CA19-9 were determined using the surv_cutpoint function: 295 U / ml for sIL-2R and 117.1 U / ml for CA19-9. The prognostic ability of CA19-9 (with a cutoff value of 117.1 U / ml) for overall survival (OS) and recurrent spontaneous fracturing (RFS) was evaluated in the high-level (≥295 U / ml) and low-level (<295 U / ml) sIL-2R subgroups. Kaplan-Meier survival curves were plotted, and the Log-rank test was used to compare differences between groups to verify the complementarity of the two biomarkers and the necessity of their combined application.

[0055] 2. Experimental Results:

[0056] 2.1 CA19-9 showed significant prognostic differentiating ability in the high-level sIL-2R subgroup.

[0057] In patients with high sIL-2R levels (≥295 U / ml), CA19-9 significantly differentiated prognosis: the median overall survival (OS) was 32.2 months in the low CA19-9 level group (<117.1 U / ml) and 20.3 months in the high CA19-9 level group (≥117.1 U / ml) (p=0.001, HR [95% CI]: 1.537 [1.191–1.984]). (Appendix) Figure 4 A); the median RFS was 20.5 months in the low CA19-9 group and 11.1 months in the high CA19-9 group (p<0.001, HR [95% CI]: 1.669 [1.282–2.172]) (Appendix) Figure 4 B).

[0058] 2.2 CA19-9 showed no significant prognostic differentiating ability in the low-sIL-2R subgroup.

[0059] In patients with low sIL-2R levels (<295 U / ml), CA19-9 failed to effectively differentiate prognosis: median OS was 66.0 months in the low CA19-9 group and 50.9 months in the high CA19-9 group (p=0.365, HR [95% CI]: 1.280 [0.738–2.220]). (See appendix) Figure 4 C); The median RFS was 50.4 months in the low CA19-9 group and 31.8 months in the high CA19-9 group (p=0.170, HR [95% CI]: 1.415 [0.844–2.370]) (Appendix) Figure 4 D).

[0060] The above results reveal an important interaction between sIL-2R and CA19-9: the prognostic discriminative ability of CA19-9 depends on sIL-2R levels. Only in patients with sIL-2R ≥ 295 U / ml (i.e., active ADAM10-sIL-2R immunosuppressive pathway) could CA19-9 effectively further stratify prognosis (both OS and RFS P < 0.01); while in patients with sIL-2R < 295 U / ml (inactive pathway, relatively favorable immune microenvironment), the prognostic discriminative ability of CA19-9 was lost (both OS and RFS P > 0.05). This finding has the following clinical implications:

[0061] First, using CA19-9 alone for prognostic assessment is insufficient, because its prognostic value is regulated by the state of the immune microenvironment.

[0062] Second, sIL-2R provides necessary immune background information for the prognostic assessment of CA19-9, and the combination of the two can achieve a comprehensive assessment from two dimensions: tumor burden (CA19-9) and host immune status (sIL-2R).

[0063] Third, patients with sIL-2R ≥ 295 U / ml and CA19-9 ≥ 117.1 U / ml represent the highest-risk subgroup with a heavy tumor burden and a highly suppressed immune microenvironment, and should receive the most aggressive adjuvant therapy and the closest follow-up monitoring.

[0064] Based on the above results, the following joint risk grouping criteria are formulated:

[0065] Low-risk group: sIL-2R < 295 U / ml and CA19-9 < 117.1 U / ml;

[0066] Intermediate-risk group: sIL-2R ≥ 295 U / ml or CA19-9 ≥ 117.1 U / ml (either one is elevated);

[0067] High-risk group: sIL-2R ≥ 295 U / ml and CA19-9 ≥ 117.1 U / ml.

[0068] Example 3: Prognostic assessment of pancreatic ductal adenocarcinoma using the predictive model of the present invention.

[0069] 1. Experimental Method:

[0070] 453 PDAC patients were randomly divided into a training cohort and a validation cohort according to a certain proportion. In the training cohort, factors with p<0.05 in univariate Cox regression analysis were included in multivariate Cox regression analysis. Based on the independent prognostic factors screened by multivariate analysis, a nomogram prediction model was constructed using the rms package in R language to predict 1-year, 3-year, and 5-year OS. The following methods were used to comprehensively evaluate the model: (1) Discrimination: The area under the receiver operating characteristic curve (AUC) of the model in 1-year, 3-year, and 5-year OS was calculated and compared with the traditional AJCC 8th edition TNM staging system; (2) Calibration: Calibration curves were plotted to evaluate the consistency between the model's predicted probability and the actual observed probability; (3) Clinical Utility: Decision Curve Analysis (DCA) was plotted to evaluate the net benefit of the model at different threshold probabilities and compared with the AJCC 8th edition TNM staging system.

[0071] 2. Experimental Results:

[0072] 2.1 Construction of Nodal Chart Model

[0073] Multivariate Cox regression analysis of the training cohort identified the following factors for inclusion in the nomogram model: differentiation degree, N stage, CA19-9 (cutoff value 117.1 U / ml), sIL-2R (cutoff value 295 U / ml), chemotherapy status, and neurological involvement. The nomogram constructed based on these factors can provide individualized 1-year, 3-year, and 5-year overall survival (OS) predictions for each patient (see attached). Figure 5 A).

[0074] 2.2 Model Performance Evaluation

[0075] The nomogram model achieved AUC values ​​of 0.740, 0.708, and 0.683 for 1-year, 3-year, and 5-year operating costs, respectively, significantly outperforming the traditional AJCC version 8 TNM staging system's 0.582, 0.527, and 0.521 (see appendix). Figure 5 B). The calibration curves show good agreement between the predicted probabilities of the nomogram model and the actual observed probabilities, with the prediction curve closely following the diagonal reference line (see attached). Figure 5 C). DCA shows that the nodal plot model outperforms the AJCC 8th Edition TNM staging system in net returns over a wider range of threshold probabilities (see appendix). Figure 5 (D) indicates that the model has higher practical value in clinical decision-making.

[0076] 2.3 Application Examples of Prognostic Risk Grouping

[0077] Based on the nomogram model, and combining the cutoff values ​​of sIL-2R (cutoff value 295 U / ml) and CA19-9 (cutoff value 117.1 U / ml), patients were grouped into prognostic risk groups as follows:

[0078] Step 1: Collect peripheral venous blood from the patient before surgery and measure serum sIL-2R and CA19-9 levels respectively;

[0079] Step 2: Compare the test results with their respective cutoff values ​​to determine the risk groups: low-risk group (sIL-2R < 295 U / ml and CA19-9 < 117.1 U / ml), medium-risk group (sIL-2R ≥ 295 U / ml or CA19-9 ≥ 117.1 U / ml), and high-risk group (sIL-2R ≥ 295 U / ml and CA19-9 ≥ 117.1 U / ml).

[0080] Step 3: Combine clinicopathological factors (differentiation degree, N stage, chemotherapy status, nerve invasion, etc.), read the scores corresponding to each variable on the nomogram, and sum them to obtain individualized 1-year, 3-year and 5-year OS prediction probabilities;

[0081] Step 4: Based on the risk grouping and nomogram prediction results, develop individualized adjuvant therapy plans and follow-up strategies—patients in the high-risk group are advised to receive more aggressive adjuvant therapy and closer follow-up monitoring; patients in the low-risk group may have their follow-up frequency appropriately reduced.

Claims

1. Application of sIL-2R and CA19-9 as biomarkers in the preparation of prognostic assessment products for pancreatic ductal adenocarcinoma.

2. Application of substances that detect sIL-2R and CA19-9 in the preparation of prognostic assessment products for pancreatic ductal adenocarcinoma.

3. The application according to claim 1 or 2, characterized in that: The prognostic assessment includes risk prediction of patients' overall postoperative survival and recurrence-free survival.

4. A kit for prognostic assessment of pancreatic cancer, characterized in that: include: (1) sIL-2R detection reagent: contains microparticles coated with anti-human IL-2Rα monoclonal antibody, enzyme-labeled anti-human IL-2Rα monoclonal antibody, chemiluminescent substrate and sIL-2R standard; (2) CA19-9 detection reagent: contains microparticles coated with anti-CA19-9 monoclonal antibody, enzyme-labeled anti-CA19-9 monoclonal antibody, chemiluminescent substrate and CA19-9 standard.

5. The reagent kit according to claim 4, characterized in that: The kit is grouped by risk according to the following criteria: Low-risk group: sIL-2R level < cutoff value and CA19-9 level < cutoff value; Intermediate-risk group: sIL-2R level ≥ cutoff value or CA19-9 level ≥ cutoff value; High-risk group: sIL-2R level ≥ cutoff value and CA19-9 level ≥ cutoff value.

6. The reagent kit according to claim 4, characterized in that: The cutoff value is determined based on the survival data using the surv_cutpoint function of the survminer package in R language. Preferably, the cutoff value for sIL-2R is 295 U / ml, and the cutoff value for CA19-9 is 117.1 U / ml.

7. The application or kit according to claim 3 or 4-5, characterized in that: The sIL-2R is an independent prognostic factor for overall survival and recurrence-free survival after pancreatic cancer surgery.

8. The application or kit according to claim 3 or 4-5, characterized in that: There is a genetic causal relationship between sIL-2R and pancreatic cancer, specifically that pancreatic cancer causally leads to an increase in serum sIL-2R levels.

9. A method for constructing a personalized prognostic prediction model for pancreatic cancer, characterized in that: Includes the following steps: Obtain the preoperative serum sIL-2R and CA19-9 levels of the patient; In conjunction with clinicopathological factors, these factors include differentiation degree, N stage, chemotherapy status, and neurological involvement. Construct a comprehensive prognostic scoring system or nomogram using the Cox regression model.

10. The method according to claim 9, characterized in that: The sIL-2R level reflects the host's immunosuppressive state, and the CA19-9 level reflects the tumor burden. The two are combined to assess the tumor from both the tumor biology and host immunity dimensions.

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