CN114839373B - Esophageal squamous carcinoma lymph node metastasis prediction model, construction method and application thereof - Google Patents
Esophageal squamous carcinoma lymph node metastasis prediction model, construction method and application thereof Download PDFInfo
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Abstract
本发明提供了一种食管鳞癌淋巴结转移预测模型及其构建方法和应用，涉及生物检测试剂盒。本发明提供检测外泌体中蛋白质的表达量的试剂在构建食管鳞癌淋巴结转移预测工具中的应用，并以血浆外泌体CORO1C、LIMS1、SULT1A3蛋白表达量为基础，构建血浆外泌体CORO1C、LIMS1、SULT1A3蛋白联合诊断食管鳞癌淋巴结转移预测模型的AUC＝0.854，说明血浆外泌体CORO1C、LIMS1、SULT1A3蛋白联合诊断食管鳞癌淋巴结转移效果较好，且在训练集及验证集中结果稳定。该预测模型的构建将为食管鳞癌淋巴结转移的评估提供更多的理论依据，并为精确制定食管鳞癌患者的治疗方案和预后判断提供了新的思路。
The present invention provides a prediction model for lymph node metastasis of esophageal squamous cell carcinoma and a construction method and application thereof, and relates to a biological detection kit. The present invention provides an application of a reagent for detecting the expression amount of proteins in exosomes in constructing a prediction tool for lymph node metastasis of esophageal squamous cell carcinoma, and based on the expression amount of plasma exosome CORO1C, LIMS1, and SULT1A3 proteins, a plasma exosome CORO1C, LIMS1, and SULT1A3 protein combined diagnosis prediction model for lymph node metastasis of esophageal squamous cell carcinoma is constructed with an AUC of 0.854, indicating that the plasma exosome CORO1C, LIMS1, and SULT1A3 protein combined diagnosis of lymph node metastasis of esophageal squamous cell carcinoma has a good effect, and the results are stable in the training set and the validation set. The construction of this prediction model will provide more theoretical basis for the evaluation of lymph node metastasis of esophageal squamous cell carcinoma, and provide new ideas for accurately formulating treatment plans and prognosis judgments for patients with esophageal squamous cell carcinoma.
Description
Technical Field
The invention belongs to the technical field of biological detection, and particularly relates to an esophageal squamous carcinoma lymph node metastasis prediction model, and a construction method and application thereof.
Background
Lymph node metastasis is a major cause of death of esophageal squamous carcinoma (EC), and the number of lymph node metastasis is related to poor prognosis of esophageal squamous carcinoma, so that early recognition of esophageal squamous carcinoma lymph node metastasis has important significance for guiding clinical treatment and prognosis judgment. At present, clinical stage of EC judgment mainly depends on CT, MRI, PET-CT and esophagoscope ultrasound. Although image examination equipment is continuously updated and developed, and an examination strategy is more refined, the current diagnosis of lymph node metastasis still has a certain limitation. CT is still currently the most common method for pre-operative staging and resectability assessment of EC, which is relatively low cost and widely available, but which has limitations in determining lymph node metastasis. Currently, the shortest diameter of the lymph nodes is more than 10mm as a standard for judging lymph node metastasis, and the standard enables the accuracy of CT diagnosis of lymph node metastasis to be not more than 60%, and the sensitivity to be low, namely only 30% -60%. In addition, normal size lymph nodes can also undergo micrometastasis, but CT does not recognize lymph node micrometastasis, and false negatives occur. The sensitivity of MRI diagnosis of esophageal cancer lymph node metastasis is 75.5% -88.73%, but the imaging is greatly influenced by the movements of breathing, swallowing and the like of a patient. The research shows that the accuracy of judging lymph node metastasis by PET-CT varies from 27% to 90%, and when the lymph node is very close to the primary tumor, more false positive diagnosis exists. Esophageal endoscopy is an important means of clinical staging of EC, but it is greatly disturbed by gas-containing tissues (e.g., trachea, lung, etc.) when detecting regional lymph nodes, and it is an invasive examination, so it is limited in popularity and application. Inaccurate lymph node metastasis determination can lead to misestimation of clinical stage, and thus may lead to errors in treatment planning. The pathological stage is used as a gold standard for diagnosing lymph node metastasis and stage, is relatively traumatic to a patient, is only suitable for the patient with operation, and is difficult to monitor the patient after esophageal squamous carcinoma operation for a long time.
Therefore, finding a convenient and quick identification method for esophageal squamous carcinoma lymph node metastasis with small damage, high sensitivity and high specificity is a clinical difficult problem to be solved urgently.
Disclosure of Invention
In view of the above, the invention aims to provide an esophageal squamous carcinoma lymph node metastasis prediction model, a construction method and application thereof, which have good operability and popularity for detecting esophageal squamous carcinoma lymph node metastasis, and have high sensitivity and good specificity, and can diagnose esophageal squamous carcinoma lymph node metastasis effect well.
In order to achieve the above object, the present invention provides the following technical solutions:
The invention provides application of a reagent for detecting the expression quantity of proteins in exosomes in constructing esophageal squamous carcinoma lymph node metastasis prediction tools, wherein the proteins comprise one or more than two of CORO1C, LIMS1 and SULT1A 3.
Preferably, the reagent comprises a Western Blot detection reagent, an Elisa detection reagent or an immunohistochemical detection reagent.
The invention also provides a construction method of the esophageal squamous carcinoma lymph node metastasis prediction model, which comprises the following steps: detecting the expression quantity of protein in exosomes of patients with esophageal squamous carcinoma before or after operation, and constructing an esophageal squamous carcinoma lymph node metastasis prediction model after carrying out data statistics on the expression quantity data;
The protein comprises one or more than two of CORO1C, LIMS1 and SULT1A 3.
Preferably, the data statistics method includes: a logistic regression analysis method, a random forest method or an artificial neural network.
Preferably, the source of protein in the exosomes comprises a blood sample, a urine sample or a saliva sample.
The invention also provides an esophageal squamous carcinoma lymph node metastasis prediction model constructed by the construction method.
The invention also provides a kit for predicting esophageal squamous carcinoma lymph node metastasis, which comprises a CORO1C antibody, a LIMS1 antibody and a SULT1A3 antibody.
Preferably, other reagents for performing Western Blot detection are also included.
The beneficial effects are that: the invention provides application of a reagent for detecting the expression quantity of proteins in exosomes in constructing a tool for predicting esophageal squamous carcinoma lymph node metastasis, and the invention discovers that the proteins of plasma exosomes CORO1C, LIMS1 and SULT1A3 are related to early metastasis of esophageal squamous carcinoma lymph node by utilizing a proteomics technology. Collecting blood of esophageal squamous carcinoma patients (including patients with lymph node metastasis and patients without lymph node metastasis), extracting exosomes, and measuring the expression level of plasma exosomes CORO1C, LIMS1 and SULT1A3 proteins in esophageal squamous carcinoma patients by using a Western Blot method. Based on the expression level of the CORO1C, LIMS protein and the SULT1A3 protein of the plasma exosome, an AUC=0.854 (sensitivity is 0.724 and specificity is 0.839) of a prediction model for jointly diagnosing esophageal squamous cell carcinoma lymph node metastasis of the plasma exosome CORO1C, LIMS protein and the SULT1A3 protein is constructed, which proves that the effect of jointly diagnosing esophageal squamous cell carcinoma lymph node metastasis of the plasma exosome CORO1C, LIMS1 protein and the SULT1A3 protein is better and the result is stable in a training set and a verification set. The construction of the prediction model provides more theoretical basis for the evaluation of esophageal squamous carcinoma lymph node metastasis, and provides a new thought for accurately making a treatment scheme and prognosis judgment of esophageal squamous carcinoma patients.
Drawings
FIG. 1 is a flow chart of a method for predicting esophageal squamous carcinoma lymph node metastasis according to the invention;
FIG. 2 is a ROC curve of plasma exosomes CORO1C, LIMS and SULT1A3 proteins with esophageal squamous carcinoma lymph node metastasis;
FIG. 3 is a ROC curve of plasma exosome CORO1C, LIMS and SULT1A3 proteins combined analysis to predict esophageal squamous carcinoma lymph node metastasis.
Detailed Description
The invention provides application of a reagent for detecting the expression quantity of proteins in exosomes in constructing esophageal squamous carcinoma lymph node metastasis prediction tools, wherein the proteins comprise one or more than two of CORO1C, LIMS1 and SULT1A 3.
The type of the reagent is not particularly limited, and preferably includes a Western Blot detection reagent, an Elisa detection reagent or an immunohistochemical detection reagent, and may be other reagents capable of detecting a change in the expression level of a protein. In the embodiments of the present invention, the Western Blot detection reagent is described as an example, but it is not to be construed as the full scope of the present invention. In the detection of the present invention, it is preferred that CORO1C, LIMS1 and SULT1A3 be the common targets. The sources of proteins of the present invention preferably include blood samples, urine samples or saliva samples, and the examples are described by taking proteins in exosomes from which blood samples are derived as examples, but they should not be construed as limiting the scope of the present invention.
The invention also provides a construction method of the esophageal squamous carcinoma lymph node metastasis prediction model, which comprises the following steps: detecting the expression quantity of protein in exosomes of patients with esophageal squamous carcinoma before or after operation, and constructing an esophageal squamous carcinoma lymph node metastasis prediction model after carrying out data statistics on the expression quantity data;
The protein in the exosome comprises one or more than two of CORO1C, LIMS1 and SULT1A 3.
The method for detecting the expression level of the protein in the exosome according to the present invention is preferably the same as that described above, and will not be described in detail here. The present invention preferably performs data statistics on the expression level obtained by the above method, and the data statistics method preferably includes: a logistic regression analysis method, a random forest method or an artificial neural network. In the embodiment of the invention, the data statistics is preferably performed by using a logistic regression analysis method, specifically comprising randomly dividing a study object into a training set and a verification set, calculating the probability of predicting esophageal squamous cell carcinoma lymph node metastasis by using logistic regression analysis to plasma exosome CORO1C, LIMS and SULT1A3 proteins, judging the efficacy of diagnosing lymph node metastasis by using the working characteristics (Receiver Operating Characteristic, ROC) Curve and Area Under the Curve (AUC) of a subject, and calculating the sensitivity and the specificity of a construction model, thereby constructing and obtaining the esophageal squamous cell carcinoma lymph node metastasis prediction model.
The invention also provides an esophageal squamous carcinoma lymph node metastasis prediction model constructed by the construction method.
In the invention, a logistic regression analysis is used for calculating the probability of predicting esophageal squamous carcinoma lymph node metastasis of plasma exosomes CORO1C, LIMS1 and SULT1A3 proteins, and a ROC curve of esophageal squamous carcinoma lymph node metastasis is drawn by taking whether lymph nodes metastasize as a final variable. The results showed that the area under ROC curve for the integration of plasma exosomes CORO1C, LIMS and SULT1A3 proteins using logistic regression analysis to predict esophageal squamous carcinoma lymph node metastasis were AUC in the full model, training set and validation set, respectively: 0.854 (0.787,0.921), 0.837 (0.749,0.925), 0.900 (0.803,0.997). The predictive model for predicting esophageal squamous carcinoma lymph node metastasis in combination with three proteins in plasma exosomes was superior in predictive efficacy to the use of a single protein in plasma exosomes (Delong methods, all P < 0.05).
The invention also provides a kit for predicting esophageal squamous carcinoma lymph node metastasis, which comprises a CORO1C antibody, a LIMS1 antibody and a SULT1A3 antibody.
The sources of the CORO1C antibody, LIMS1 antibody and SULT1A3 antibody are not particularly limited, and are preferably purchased from Abcam, and the product numbers are respectively: ab283693, ab76112, and ab92476. The kit of the invention preferably further comprises other reagents for performing WesternBlot detection.
The invention also provides a method for predicting the metastasis of the esophageal squamous carcinoma lymph nodes, which has a flow shown in a figure 1, and comprises the steps of detecting the expression changes of the preoperative or postoperative CORO1C, LIMS1 and the SULT1A3 by using a Western Blot method, and drawing an ROC curve of the metastasis of the esophageal squamous carcinoma lymph nodes by using whether the lymph nodes are metastasized as a final variable after logistic regression analysis. By utilizing the method, the esophageal lymph node metastasis is judged according to the expression levels of the plasma exosomes CORO1C, LIMS and SULT1A3, and only venous blood is extracted without operation, so that the method has good operability and popularity; the related steps are already provided with mature kits, the extraction process is convenient, the operability is strong, and the cost is low; the expression quantity of exosomes CORO1C, LIMS and SULT1A3 in the blood plasma can be dynamically detected before and after the operation to judge whether the lymph nodes are metastasized before the operation, and the prognosis and recurrence and metastasis conditions of the patients after the operation; the change of the expression amounts of plasma exosomes CORO1C, LIMS1 and SULT1A3 is detected by a Western Blot experiment, and the method has the characteristics of high sensitivity and high specificity and has good effect of diagnosing esophageal squamous carcinoma lymph node metastasis.
The method of extracting the exosomes and the proteins in the exosomes is not particularly limited, and the method is preferably performed by using a kit which is conventional in the art, and according to the instructions of the kit. In the present invention, it is preferable to extract plasma exosomes using ExoQuick TM kit (cat No. EXOQ A-1, SBI), extract proteins in exosomes using Total Exosome RNA and Protein Isolation Kit kit (cat No. 4478445, SBI), and measure protein concentration in exosomes using BCA kit (cat No. ZD301-1, beijing bang nationality biological gene technologies Co., ltd.).
The method of the present invention is not particularly limited, and preferably includes:
1) According to the calculated concentration of the protein to be detected, adding proper ultrapure water and 5 XSDS buffer solution to adjust the concentration so that the volume of the 5 XSDS buffer solution accounts for 20% of the total volume;
2) Placing the protein sample on a dry thermostat, boiling for 5 minutes, and cooling to directly use for experiments or storing in a refrigerator at-20 ℃;
3) Preparation of SDS polyacrylamide gel
TABLE 1 gel solution formulation
The lower layer of SDS polyacrylamide gel used in the invention is 12.5% separating gel, and the upper layer is 5% concentrating gel. When preparing the gel, 10% AP and catalyst TEMED are added at last, and after shaking, the gel is immediately poured between glass plates, and then 1ml n-butanol is poured for pressing. After the gel polymerization was completed, a refractive ray was observed between the liquid surfaces. Then, the n-butanol is washed cleanly, the residual liquid is carefully sucked by filter paper, 5% of concentrated glue is added, bubbles are avoided as much as possible, the comb is slowly inserted into the concentrated glue, the comb stands for about 30 minutes at room temperature, and the comb is pulled out after the concentrated glue is polymerized.
4) And (3) installing the prepared gel into an electrophoresis tank, adding a small amount of electrophoresis liquid to observe whether leakage exists, reinstalling the leakage, and adding enough electrophoresis liquid (about 1L) if the leakage does not exist.
5) Protein samples (50-100 mu L) are added into the sample holes, and the loading amount is determined according to the protein concentration. mu.L of protein Marker was added in place.
6) The power was turned on and a constant voltage of 60V was initially used. When the protein Marker began to appear separated, the voltage was changed to 90V. The electrophoresis time can be adjusted according to the target protein.
7) Taking down the gel, soaking in the transfer membrane liquid, and simultaneously taking two pieces of thick filter paper for soaking. Note that each gel needs to be marked for ease of distinction.
8) A PVDF film with the same size as the gel is cut off, soaked in methanol for 5 minutes and then soaked in the film transferring liquid for 20 minutes.
9) The thick filter paper, PVDF membrane, gel and thick filter paper are put down in sequence on the panel of the film transfer instrument. The superimposition process takes care of preventing the generation of bubbles.
10 When one film is turned, a constant current of 110mA is required, and when two films are turned at the same time, a constant current of 220mA is required. The film transfer time is generally 60 to 90 minutes.
11 Placing into skimmed milk sealing liquid, placing on a shaking table, and slowly shaking for more than 1 hr.
12 According to the molecular weight of the strip, the PVDF film is cut into strips, and the strips are respectively placed in diluted primary antibody incubation liquid, wherein the dilution ratio of the primary antibody incubation liquid is 1:1000, and the strips are incubated on a low-speed shaking table at 4 ℃ overnight.
13 Rinsing PVDF membrane strip 3 times with TBST for 5min each time, respectively placing into diluted secondary antibody incubation liquid with dilution ratio of 1:2000, and incubating on a low-speed shaking table at room temperature for 1 hr.
14 The PVDF membrane strip was rinsed 10 times for 10 minutes each with TBST.
15 Preparing developing solution A and developing solution B according to the ratio of L, adding 200 mu L of each PVDF film strip, uniformly coating by using a gun head, removing bubbles, exposing by using a chemiluminescent imager, adjusting parameters until the images are clear, and selecting clear pictures for storage.
The following describes the esophageal squamous carcinoma lymph node metastasis prediction model, the construction method and the application thereof in detail by referring to examples, but they are not to be construed as limiting the scope of the invention.
Example 1
Esophageal squamous carcinoma patients, who had been treated by the first hospital affiliated with the university of Fujian medical science, were collected 2014 by the tumor hospital of Fujian province, 6 of 2016, according to the explicit inclusion and exclusion criteria.
Inclusion criteria: (1) Primary esophageal squamous carcinoma diagnosed by surgical histopathology; (2) having a blood sample; (3) living locally in Fujian for more than 10 years; (4) voluntarily signing the informed consent form.
Exclusion criteria: (1) The pathological diagnosis proves that the patient is a patient with non-primary esophageal squamous carcinoma and recurrent esophageal squamous carcinoma; (2) associated with liver and kidney dysfunction or acute and chronic infections; (3) with other serious medical conditions; (4) patients with critical illness can not clearly answer questions. The study included 120 study controls, 58 of which were lymph node non-metastatic and 62 of which were lymph node non-metastatic.
The expression of plasma exosomes CORO1C, LIMS, SULT1A3 proteins in the transferred and untransferred groups was examined using WesternBlot. CORO1C (cat# ab 283693), LIMS1 (ab 76112), SULT1A3 (ab 92476) antibodies were purchased from Abcam; reference beta-Tublin (a 12289) antibodies were purchased from ABclonal.
120 Subjects were randomly divided into training (n=76) and validation (n=41) sets at 2:1. The probability of esophageal squamous cell carcinoma lymph node metastasis was predicted using logistic regression analysis to calculate plasma exosomes CORO1C, LIMS, SULT1A3 proteins, the efficacy of diagnosing lymph node metastasis was judged using the subject working characteristics (Receiver Operating Characteristic, ROC) Curve and Area Under the Curve (AUC), and the sensitivity and specificity of the constructed model were calculated.
Test results:
(1) Plasma exosome CORO1C, LIMS1, SULT1A3 protein and esophageal squamous carcinoma lymph node metastasis ROC curve
By taking lymph node metastasis as a final variable, ROC curves of plasma exosome CORO1C, LIMS1 and SULT1A3 proteins and esophageal squamous carcinoma lymph node metastasis are respectively drawn, and the results show that in a full model, the AUCs of the plasma exosome CORO1C, LIMS1 and SULT1A3 proteins for predicting esophageal squamous carcinoma lymph node metastasis are respectively: 0.696 (0.581,0.810), 0.711 (0.618,0.805), 0.797 (0.711,0.883); the sensitivity and specificity of the ROC curve in the training set and the validation set are shown in table 2 and fig. 2.
TABLE 2 sensitivity, specificity and AUC of protein in plasma exosomes for esophageal squamous carcinoma lymph node metastasis prediction model
(2) Construction of esophageal squamous cell carcinoma lymph node metastasis prediction model by integrating plasma exosome CORO1C, LIMS1 and SULT1A3 proteins using logistic regression analysis
Calculating the probability of metastasis of the plasma exosomes CORO1C, LIMS and SULT1A3 proteins by using logistic regression analysis, and drawing an ROC curve of metastasis of the esophageal squamous cell carcinoma lymph nodes by taking whether the lymph nodes metastasize as a final variable. The results are shown in table 3 and fig. 3, and the AUC of ROC curve under which plasma exosomes CORO1C, LIMS1, SULT1A3 proteins were integrated to predict esophageal squamous carcinoma lymph node metastasis using logistic regression analysis were: 0.854 (0.787,0.921), 0.837 (0.749,0.925), 0.900 (0.803,0.997). The prediction efficacy of the prediction model for predicting esophageal squamous carcinoma lymph node metastasis by combining three proteins in plasma exosomes is superior to that of the prediction model using a single protein in plasma exosomes (Delong methods, P < 0.05).
TABLE 3 plasma exosome CORO1C, LIMS1, SULT1A3 protein Joint analysis to construct a predictive model for esophageal squamous carcinoma lymph node metastasis
In summary, the combined use of plasma exosomes CORO1C, LIMS1, SULT1A3 to construct a model of esophageal squamous carcinoma lymph node metastasis is superior to models constructed using proteomics in only a single plasma exosome. The study objects are randomly divided into a training set and a verification set according to the ratio of 2:1, the results of the models in the training set and the verification set are consistent, and the results are stable.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (5)
1. The use of a reagent for detecting the expression level of a protein in an exosome in the construction of a tool for predicting esophageal squamous carcinoma lymph node metastasis, wherein the protein comprises one or more of CORO1C, LIMS1 and SULT1 A3.
2. The use according to claim 1, wherein the reagent comprises a Western Blot detection reagent, an Elisa detection reagent or an immunohistochemical detection reagent.
3. The construction method of the esophageal squamous carcinoma lymph node metastasis prediction model is characterized by comprising the following steps of: detecting the expression quantity of protein in exosomes of patients with esophageal squamous carcinoma before or after operation, and constructing an esophageal squamous carcinoma lymph node metastasis prediction model after carrying out data statistics on the expression quantity data;
The protein comprises one or more than two of CORO1C, LIMS1 and SULT1A 3.
4. A method of construction according to claim 3, wherein the data statistics method comprises: a logistic regression analysis method, a random forest method or an artificial neural network.
5. A method of construction according to claim 3, wherein the source of protein in the exosomes comprises a blood sample.
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