A panel of urine protein markers and their application in the preparation of a product for predicting the prognosis of non-small cell lung cancer

Abstract

The present invention belongs to the field of biotechnology, and specifically relates to a group of urine protein markers and their use in preparing a product for predicting the prognosis of non-small cell lung cancer. The present invention screens out for the first time from the urine of patients with non-small cell lung cancer a group of urine proteins closely related to the postoperative progression of non-small cell lung cancer: AVIL protein, CXCR5 protein, ENPEP protein, DPEP1 protein, SNC66 protein and XPNPEP2 protein, and constructs a prognosis prediction model based on these six urine proteins. The constructed prognosis prediction model has been verified to have high sensitivity and specificity for predicting the prognosis of patients after surgery of non-small cell lung cancer, reaching 84.5% and 81.2% respectively. It has a good prognosis prediction effect for non-small cell lung cancer, provides reliable guidance for clinical targeted treatment, and is of great significance for improving the prognosis and survival of patients with non-small cell lung cancer.

Description

Technical Field

[0001] The present invention belongs to the field of biotechnology and relates to a group of urine protein markers and their application in preparing lung cancer prognosis prediction products, and more specifically to the application of the group of urine protein markers in preparing non-small cell lung cancer prognosis products. Background Art

[0002] Non-small cell lung cancer is one of the common malignant tumors. The early symptoms of non-small cell lung cancer, such as cough, chest pain, persistent low-grade fever, hoarseness, chest tightness and shortness of breath, are often mistakenly attributed to recent fatigue by most people, making it difficult to associate these symptoms with non-small cell lung cancer. Although the diagnosis and treatment of non-small cell lung cancer have been greatly improved, most patients with non-small cell lung cancer are already in the late stage of the disease when they seek medical treatment, which greatly affects the prognosis of patients with non-small cell lung cancer. Currently, the 5-year survival rate of patients with early-stage non-small cell lung cancer after radical surgery can reach over 80%, while the 5-year survival rate of patients with mid-to-late stage non-small cell lung cancer, especially those in the late stage, is less than 5%. The prognosis of patients with mid-to-late stage non-small cell lung cancer is poor, and patients generally have high postoperative drug resistance or recurrence and metastasis, which further leads to a poor prognosis for patients with late-stage non-small cell lung cancer.

[0003] The prognostic grading of non-small cell lung cancer is mainly based on the pathological grading of CT-guided lung puncture biopsy as the "gold standard", which carries the risk of postoperative bleeding or concurrent pneumothorax and is less acceptable to patients. Currently discovered prognostic-related molecular markers still have relatively low sensitivity or specificity, and are not accurate enough in predicting patient prognosis. They have not yet been accepted for clinical application, and the prognosis prediction of patients with non-small cell lung cancer is still in the preliminary exploratory stage. Therefore, exploring and establishing a prognostic prediction index with high sensitivity, strong specificity, and high patient acceptance to accurately predict the prognosis of patients with non-small cell lung cancer, as a basis for guiding treatment and judging prognosis, guiding clinical individualized treatment, and avoiding overtreatment or undertreatment, is of great significance for clinical treatment, follow-up, and thus improving the prognosis and survival of patients with non-small cell lung cancer. Summary of the Invention

[0004] In response to the problems existing in the prior art, the present invention provides a group of urine protein markers and their application in the preparation of non-small cell lung cancer prognosis prediction products. The present invention screens out urine proteins that are closely related to the postoperative progression of non-small cell lung cancer from patients' urine for the first time, and constructs a prognosis prediction model based on this. The constructed prognosis prediction model has been verified to have high sensitivity and specificity for prognosis prediction of postoperative patients, providing powerful guidance for targeted treatment and prognosis efficacy evaluation of non-small cell lung cancer at different stages of progression.

[0005] Based on the above purpose, the technical solution adopted by the present invention is as follows:

[0006] In a first aspect, the present invention provides a group of urine protein markers for use in preparing a reagent for predicting the prognosis of non-small cell lung cancer, wherein the urine protein marker is a combination of AVIL protein, CXCR5 protein, ENPEP protein, DPEP1 protein, SNC66 protein and XPNPEP2 protein.

[0007] Preferably, the non-small cell lung cancer prognosis prediction reagent is a molecular combination for detecting whether AVIL protein, CXCR5 protein, ENPEP protein, DPEP1 protein, SNC66 protein and XPNPEP2 protein are expressed.

[0008] Preferably, the molecular combination consists of an antibody that specifically binds to AVIL protein, an antibody that specifically binds to CXCR5 protein, an antibody that specifically binds to ENPEP protein, an antibody that specifically binds to DPEP1 protein, an antibody that specifically binds to SNC66 protein, and an antibody that specifically binds to XPNPEP2 protein.

[0009] In a second aspect, the present invention provides an evaluation model for predicting the prognosis of non-small cell lung cancer, wherein the evaluation model includes the above-mentioned urine protein marker; the evaluation model uses the following regression equation to calculate the risk score:

[0010] Risk score Y = 0.215 × X1 + 0.379 × X2 + 0.294 × X3 + 0.238 × X4 + 0.257 × X5 + 0.273 × X6, where X1 is the expression level of AVIL protein; X2 is the expression level of CXCR5 protein; X3 is the expression level of ENPEP protein; X4 is the expression level of DPEP1 protein; X5 is the expression level of SNC66 protein; and X6 is the expression level of XPNPEP2 protein.

[0011] When Y≥19.35, it is high risk, and when Y<19.35, it is low risk.

[0012] In a third aspect, the present invention provides a device or system for predicting the prognosis of non-small cell lung cancer, comprising:

[0013] (1) a data acquisition module for acquiring the expression level of the above-mentioned urine protein marker in the urine sample of the test subject;

[0014] (2) a prediction module, configured to provide the expression levels of urine protein markers obtained by the data acquisition module as input data to the trained prediction model;

[0015] (3) A prediction result acquisition module, which is used to obtain the output results of the prediction model in the above prediction module and obtain the prognosis prediction results of the subject.

[0016] Preferably, the prediction model in the above-mentioned device or system for predicting the prognosis of non-small cell lung cancer is the aforementioned evaluation model.

[0017] In a fourth aspect, the present invention provides a kit for predicting the prognosis of non-small cell lung cancer, comprising the above-mentioned non-small cell lung cancer prognosis prediction reagent; the evaluation model used in the kit to predict the prognosis of non-small cell lung cancer patients based on the expression level of the detected urine protein marker is as shown above.

[0018] Preferably, the detection object of the kit for predicting the prognosis of non-small cell lung cancer is the urine of the subject.

[0019] Preferably, the subject's urine needs to be pre-treated by nitrocellulose membrane adsorption and eluted and precipitated before being tested by the kit.

[0020] Compared with the prior art, the present invention has the following beneficial effects:

[0021] The present invention uses urine as a sample for prognosis prediction of non-small cell lung cancer, which is non-invasive and has a high degree of acceptance among patients.

[0022] The present invention proposes for the first time a group of potentially feasible non-invasive biomarkers for predicting the prognosis of non-small cell lung cancer: AVIL protein, CXCR5 protein, ENPEP protein, DPEP1 protein, SNC66 protein and XPNPEP2 protein; experiments have found that compared with healthy people, the levels of these six urinary proteins in the urine of patients with non-small cell lung cancer are significantly increased. At the same time, analysis combined with the progression of non-small cell lung cancer found that the levels of these six urinary proteins are also closely related to the progression stage of non-small cell lung cancer, and show an increasing trend with the aggravation of non-small cell lung cancer.

[0023] The present invention further conducted telephone follow-up and survival analysis on patients with non-small cell lung cancer and found that although the above six urine proteins are closely related to the progression of non-small cell lung cancer, they cannot be used as independent prognostic predictors. The non-small cell lung cancer prognosis prediction evaluation model based on the above six urine proteins and COX regression processing has a better prediction effect on non-small cell lung cancer, and there is a significant difference in the overall survival rate between the high-risk group and the low-risk group.

[0024] The present invention further analyzed the predictive effect of the constructed non-small cell lung cancer prognosis prediction model using a validation sample set of 110 cases. The results still showed a good predictive effect. There was a significant difference in the overall survival rate between the high-risk group and the low-risk group. The prediction sensitivity and specificity reached 84.5% and 81.2%, respectively. This further shows that the non-small cell lung cancer prognosis prediction and evaluation model constructed by the present invention has a good predictive effect for non-small cell lung cancer, can provide effective guidance for clinical targeted treatment, and is of great significance for improving the prognosis and survival of patients with non-small cell lung cancer. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 The graph shows the protein levels of AVIL, CXCR5, ENPEP, DPEP1, SNC66, and XPNPEP2 in urine of patients with non-small cell lung cancer (NSCLC) and healthy controls (HL).

[0026] Figure 2 The levels of AVIL protein, CXCR5 protein, ENPEP protein, DPEP1 protein, SNC66 protein, and XPNPEP2 protein corresponding to the stages of non-small cell lung cancer patients;

[0027] Figure 3 The Kaplan-Meier survival curves of six urine protein markers for patients with postoperative non-small cell lung cancer;

[0028] Figure 4 To use the non-small cell lung cancer prognosis prediction and evaluation model to determine the Kaplan-Meier survival curve of patients with non-small cell lung cancer (120 cases) after surgery;

[0029] Figure 5 The figure shows the Kaplan-Meier survival curves of 110 patients with non-small cell lung cancer who underwent surgery using the prognosis prediction and evaluation model of the embodiment. DETAILED DESCRIPTION

[0030] To better illustrate the objectives, technical solutions, and advantages of the present invention, the present invention will be further described below with reference to specific examples. Those skilled in the art will appreciate that the specific examples described herein are intended only to illustrate the present invention and are not intended to limit the present invention. The experimental methods used in the examples are conventional methods unless otherwise specified; the materials and reagents used are commercially available unless otherwise specified.

[0031] Example 1

[0032] In this study, urine samples from 230 patients with non-small cell lung cancer (NSCLC) were collected from the China-Japan Friendship Hospital and stored frozen at -80°C. All patients with pathologically confirmed NSCLC underwent radical surgical resection. Among the 230 patients, 125 were male and 105 were female, with an average age of 49.3±4.6 years, ranging from 35 to 65 years. Among the 230 patients, 43 were confirmed to be stage I by pathological sections, 88 were stage II, 71 were stage III, and 28 were stage IV.

[0033] At the same time, urine samples from 200 healthy people from the Physical Examination Center of the China-Japan Friendship Hospital were collected and stored frozen at -80°C. The healthy people had no evidence of any tumor. Among the 200 cases, there were 98 males and 102 females with an average age of 45.1±3.3 years, and an age range of 30 to 60 years.

[0034] The urine of 120 patients with non-small cell lung cancer (the remaining 110 cases were used for subsequent model validation analysis) and 200 healthy people were selected. Among the 120 cases of non-small cell lung cancer, 20 were in stage I, 45 were in stage II, 42 were in stage III, and 13 were in stage IV.

[0035] The collected urine is subjected to nitrocellulose membrane adsorption pretreatment and urine protein elution treatment, wherein the steps of the nitrocellulose membrane adsorption pretreatment of urine are as follows:

[0036] (1) Urine was centrifuged at 5000 g for 40 min at 4°C to remove intact cells and cell debris.

[0037] (2) Take 15 mL of urine supernatant from the centrifuged urine sample, add 7.5 mL of phosphate buffer and mix well;

[0038] (3) Select a nitrocellulose membrane with a pore size of 0.22 μm, wet the membrane with water, place it on a vacuum filtration bottle, and collect the filtrate by vacuum filtration;

[0039] (4) Remove the nitrocellulose membrane and place it in a 56°C drying oven to dry. Place the dried nitrocellulose membrane that has adsorbed urine protein into a ziplock bag marked with the patient number and medical record number and store it in a -80°C refrigerator.

[0040] The urine protein elution process includes the following steps:

[0041] (1) Cut the nitrocellulose membrane that has adsorbed urine protein into small pieces and place it in a 5 mL centrifuge tube. Add 3.4 mL of acetone and 500 μL of 0.5% ammonium bicarbonate aqueous solution in sequence. Vortex the mixture vigorously for 20 seconds at room temperature and heat it in a 55°C drying oven for 60 minutes. Every 20 minutes, stop heating and vigorously vibrate for 30 seconds to ensure that the nitrocellulose membrane and the liquid are fully mixed.

[0042] (2) Gently shake at 4°C and 12 rpm for 2 h to precipitate the protein; then centrifuge at 12,000 rpm for 15 min, discard the supernatant, and collect the precipitate;

[0043] (3) Add 300 μL of urine extraction buffer to the precipitate until the precipitate is completely dissolved and dispersed. Then transfer the solution to a 2 mL centrifuge tube and ultrasonically resolubilize the protein at 4°C and 75W for 3 min.

[0044] (4) The sonicated solution was placed in a new 2 mL centrifuge tube and centrifuged at 4°C, 12,000 rpm, for 15 min. The supernatant was collected and stored at -80°C.

[0045] The supernatant after urinary protein elution was analyzed by data-independent protein spectrum analysis for urine protein in patients with non-small cell lung cancer and healthy controls. A total of more than 30 proteins with significant differential expression in the urine of patients with non-small cell lung cancer and healthy controls were screened out. Among them, the levels of AVIL protein, CXCR5 protein, ENPEP protein, DPEP1 protein, SNC66 protein and XPNPEP2 protein in the urine of patients with postoperative non-small cell lung cancer were significantly higher than those in healthy controls (such as Figure 1 shown).

[0046] The levels of AVIL protein, CXCR5 protein, ENPEP protein, DPEP1 protein, SNC66 protein and XPNPEP2 protein in urine also vary in different pathological stages. The levels of these proteins in urine of patients with stage I non-small cell lung cancer are relatively lower than those of patients with stage II, stage III and stage IV. Moreover, the levels of these proteins show an increasing trend with the aggravation of non-small cell lung cancer (e.g. Figure 2 As shown in the figure, it can be seen that AVIL protein, CXCR5 protein, ENPEP protein, DPEP1 protein, SNC66 protein and XPNPEP2 protein in urine are closely related to the pathological process of non-small cell lung cancer, and can be used to indicate whether there is recurrence or progression after surgery.

[0047] Further telephone follow-up was performed on patients with non-small cell lung cancer for survival analysis. The average follow-up time for all patients was 40 months. The median AVIL protein content in the urine of 120 patients with non-small cell lung cancer was used as the cutoff value. The patients with AVIL protein content higher than the cutoff value were classified as the high-risk group, and the patients with AVIL protein content lower than the cutoff value were classified as the low-risk group for postoperative survival analysis. The remaining proteins were analyzed by referring to the AVIL protein method, and the median protein content was used as the cutoff value for postoperative survival analysis. The Kaplan-Meier survival curve of the postoperative patients is shown below. Figure 3 As shown in the results of survival analysis, there was no significant difference between the high-risk group and the low-risk group divided according to the above-mentioned urine protein content, indicating that the above-mentioned urine protein cannot be used as an independent prognostic factor for non-small cell lung cancer.

[0048] Based on the above data of abnormally high expression of urine protein in 120 cases of non-small cell lung cancer, a prognostic prediction and evaluation model for non-small cell lung cancer was obtained through COX regression processing:

[0049] Y=0.215×X1+0.379×X2+0.294×X3+0.238×X4+0.257×X5+0.273×X6, where

[0050] X1 is the expression level of AVIL protein; X2 is the expression level of CXCR5 protein; X3 is the expression level of ENPEP protein; X4 is the expression level of DPEP1 protein; X5 is the expression level of SNC66 protein; X6 is the expression level of XPNPEP2 protein; and the Y values ​​of each of the 120 specimens are arranged in ascending order, with the median Y value being the cut-off value, that is, the cut-off value is 19.35; cases with a value less than the cut-off value are in the low-risk group, and patients with non-small cell lung cancer in the low-risk group have a higher three-year survival rate after surgery; cases with a value greater than the cut-off value are in the high-risk group, and patients with non-small cell lung cancer in the high-risk group have a lower three-year survival rate after surgery.

[0051] Based on this model, Kaplan-Meier survival curve analysis was performed on the above 120 patients with non-small cell lung cancer after surgery. Figure 4 As shown in the figure, it can be seen that when the six proteins were jointly detected based on the evaluation model, the overall survival rates of the low-risk group and the high-risk group gradually decreased, and the decrease in the high-risk group was more obvious, and there was a significant difference with the low-risk group, indicating that the above evaluation model has a high prognostic prediction value for non-small cell lung cancer.

[0052] Example 2

[0053] In this example, the remaining 110 urine samples from 230 non-small cell lung cancer patients were used to verify the prognostic effect of the non-small cell lung cancer prognosis prediction model constructed in Example 1. Among the 110 non-small cell lung cancer patients, 23 were in stage I, 43 were in stage II, 29 were in stage III, and 15 were in stage IV.

[0054] The urine of 110 cases of non-small cell lung cancer was pretreated with nitrocellulose membrane adsorption and eluted with urine protein according to the method described in Example 1. The levels of AVIL protein, CXCR5 protein, ENPEP protein, DPEP1 protein, SNC66 protein and XPNPEP2 protein in urine were then determined using commercially available ELISA kits.

[0055] The detected urine protein content data were used to calculate the risk score of each patient sample according to the prognostic prediction evaluation model in Example 1, and the patient samples were divided into high-risk group and low-risk group according to the cut-off value of 19.35, and then survival analysis was performed, as shown in FIG. Figure 5 As shown, compared with the low-risk group, the high-risk group of non-small cell lung cancer patients had a shorter overall survival, and the difference between the two groups was more significant, indicating that the non-small cell lung cancer prognosis prediction and evaluation model constructed by the present invention can accurately distinguish between the high-risk group and the low-risk group of non-small cell lung cancer patients.

[0056] In addition, the sensitivity and specificity of the non-small cell lung cancer prognosis prediction and evaluation model constructed based on the content levels of the above six proteins for predicting the three-year survival of the 110 patients were 84.5% and 81.2%, respectively. It can be seen that the prognosis prediction and evaluation model of the present invention has better prediction sensitivity and specificity for the three-year survival of patients with non-small cell lung cancer.

[0057] In summary, the prognostic prediction model jointly constructed by six protein markers including AVIL protein, CXCR5 protein, ENPEP protein, DPEP1 protein, SNC66 protein and XPNPEP2 protein in urine has a higher predictive value for the prognosis of patients with non-small cell lung cancer.

Claims

1. Use of a group of urine protein markers in the preparation of a reagent for predicting the prognosis of non-small cell lung cancer, characterized in that: The urine protein marker is a combination of AVIL protein, CXCR5 protein, ENPEP protein, DPEP1 protein, SNC66 protein and XPNPEP2 protein.

2. The use according to claim 1, characterized in that The non-small cell lung cancer prognosis prediction reagent is a molecular combination for detecting whether AVIL protein, CXCR5 protein, ENPEP protein, DPEP1 protein, SNC66 protein and XPNPEP2 protein are expressed.

3. The use according to claim 2, characterized in that The molecular combination consists of an antibody that specifically binds to AVIL protein, an antibody that specifically binds to CXCR5 protein, an antibody that specifically binds to ENPEP protein, an antibody that specifically binds to DPEP1 protein, an antibody that specifically binds to SNC66 protein, and an antibody that specifically binds to XPNPEP2 protein.

4. A device or system for predicting the prognosis of non-small cell lung cancer, characterized in that: The device or system comprises: (1) a data acquisition module for acquiring the expression level of the urine protein marker according to claim 1 in a urine sample of a test subject; (2) a prediction module, configured to provide the expression levels of urine protein markers obtained by the data acquisition module as input data to a trained prediction model; (3) A prediction result acquisition module, which is used to obtain the output result of the prediction model in the prediction module to obtain the prognosis prediction result of the subject.

5. The device or system for predicting the prognosis of non-small cell lung cancer according to claim 4, characterized in that: The prediction model uses the following regression equation to calculate the risk score: Risk score Y = 0.215 × X1 + 0.379 × X2 + 0.294 × X3 + 0.238 × X4 + 0.257 × X5 + 0.273 × X6, where X1 is the expression level of AVIL protein; X2 is the expression level of CXCR5 protein; X3 is the expression level of ENPEP protein; X4 is the expression level of DPEP1 protein; X5 is the expression level of SNC66 protein; and X6 is the expression level of XPNPEP2 protein. When Y≥19.35, it is high risk, and when Y<19.35, it is low risk.

6. A kit for predicting the prognosis of non-small cell lung cancer, characterized in that: The kit comprises the non-small cell lung cancer prognosis prediction reagent according to claim 2; the prediction model used by the kit to predict the prognosis of non-small cell lung cancer patients based on the expression level of the detected urine protein marker is as shown in claim 5.

7. The kit for predicting the prognosis of non-small cell lung cancer according to claim 6, characterized in that: The detection object of the kit is the urine of the subject.

8. The kit for predicting the prognosis of non-small cell lung cancer according to claim 7, characterized in that: The subject's urine needs to be pre-treated by nitrocellulose membrane adsorption and protein elution precipitation before being tested by the kit.

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