Biomarker for early diagnosis of non-small cell lung cancer and application thereof

Abstract

The invention belongs to the technical field of biology, and relates to a biomarker for early diagnosis of non-small cell lung cancer and application of the biomarker. The biomarker comprises a combination of secretory phosphoprotein 1, epithelial cell adhesion molecules and matrix metallopeptidase 14, and / or a combination of coding nucleic acid of the secretory phosphoprotein 1, coding nucleic acid of the epithelial cell adhesion molecules and coding nucleic acid of the matrix metallopeptidase 14. The coding nucleic acid comprises mRNA or cDNA. In a test set, a non-small cell lung cancer circulating tumor cell scoring diagnosis model constructed by taking the biomarker as the characteristic has the diagnosis accuracy of 87.5% and the sensitivity and specificity of 92.5% and 82.5% respectively. Compared with existing clinical tumor indexes, cancer can be found more early, and early screening of the non-small cell lung cancer is facilitated.

Description

Technical Field

[0001] The invention belongs to the field of biotechnology and relates to a biomarker for early diagnosis of non-small cell lung cancer and application thereof. Background Art

[0002] Non-small cell lung cancer (NSCLC) is an important histological subtype of lung cancer. Despite many efforts and attempts to achieve early diagnosis over the years, most patients are still diagnosed in the middle and late stages of the disease. Traditional early diagnosis methods include imaging examinations, lung cancer cytology and histology, and serum tumor markers, but most of them have poor prediction sensitivity and specificity. Therefore, there is an urgent need to develop a highly sensitive, highly specific, and less invasive NSCLC diagnostic method, which is of great significance for early detection of precancerous lesions and timely intervention to improve patient survival.

[0003] Circulating tumor cells (CTCs) refer to tumor cells that break away from solid tumors and enter the peripheral blood circulation. They are transported to distant tissues, infiltrate, adapt to the new microenvironment, and eventually "seed", "proliferate", "colonize", and form metastatic lesions. They are the "seeds" of tumor metastasis. Therefore, CTC, as a "liquid biopsy" for non-invasive diagnosis, has broad prospects.

[0004] Currently, many technologies have been applied to the separation and enrichment of CTCs. Epithelial cell adhesion molecules are one of the most commonly used biomarkers for the separation of lung cancer-derived CTCs. However, primary lung cancer tumors have significant heterogeneity, which leads to the traditional CTCs isolation method that relies on a single marker of epithelial cell adhesion molecules to easily miss mesenchymal phenotype CTCs. In addition, a large number of studies have confirmed that the expression profile of CTCs and its contents are very similar to those of parental cells, and the bioinformatic molecules contained are closely related to the occurrence and development of cancer, which helps to assist diagnosis and gain a deeper understanding of its heterogeneity and drug resistance.

[0005] Therefore, there is an urgent need to develop a new type of early diagnostic marker and method for non-small cell lung cancer to further improve the accuracy of non-small cell lung cancer diagnosis. Summary of the invention

[0006] In view of the deficiencies in the prior art and actual needs, the present invention provides a biomarker for early diagnosis of non-small cell lung cancer and its application, and constructs a model for early diagnosis of non-small cell lung cancer based on the biomarker to achieve accurate, efficient and rapid diagnosis of early non-small cell lung cancer.

[0007] In order to achieve the purpose of the invention, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a biomarker for early diagnosis of non-small cell lung cancer, wherein the biomarker comprises a combination of secretory phosphoprotein 1, epithelial cell adhesion molecule and matrix metallopeptidase 14, and / or a combination of nucleic acids encoding secretory phosphoprotein 1, epithelial cell adhesion molecule and matrix metallopeptidase 14; the encoding nucleic acids comprise mRNA or cDNA.

[0008] SEQ ID NO.1 (mRNA sequence of secretory phosphoprotein 1 NM_000582.3):

[0009] SEQ ID NO.2 (mRNA sequence of epithelial cell adhesion molecule NM_002354.2):

[0010] SEQ ID NO.3 (mRNA sequence of matrix metallopeptidase 14 NM_004995.3):

[0011] The non-small cell lung cancer circulating tumor cell scoring diagnostic model constructed using the biomarkers of the present invention as features has a diagnostic accuracy of 87.5% in the training set, and a sensitivity and specificity of 92.5% and 82.5% respectively. Compared with existing clinical tumor indicators, it can detect cancer earlier and is conducive to the early screening of non-small cell lung cancer.

[0012] In a second aspect, the present invention provides use of the biomarker for early diagnosis of non-small cell lung cancer and / or its detection reagent according to the first aspect in the preparation of a product for early diagnosis of non-small cell lung cancer.

[0013] In a third aspect, the present invention provides a kit for early diagnosis of non-small cell lung cancer, the kit comprising a reagent for detecting the presence or expression level of the biomarker for early diagnosis of non-small cell lung cancer described in the first aspect.

[0014] Preferably, the reagent comprises primers and / or probes for detecting the biomarkers for early diagnosis of non-small cell lung cancer described in the first aspect.

[0015] Preferably, the kit further comprises immunomagnetic beads modified with capture antibodies.

[0016] Preferably, the capture antibody comprises any one of an antibody against epithelial adhesion molecule, an antibody against N-cadherin or an antibody against epidermal growth factor, or a combination of at least two of them.

[0017] The present invention uses multi-antibody modified magnetic beads (EpCAM / N-cadherin / EGFR antibodies) to target and capture CTCs specific to non-small cell lung cancer. The antibodies can be mixed with the circulating tumor cell sample first and then mixed with the magnetic beads, or can be mixed with the magnetic beads first and then mixed with the circulating tumor cell sample.

[0018] The present invention can capture circulating tumor cells in peripheral blood from complex blood samples, effectively obtain biological information of NSCLC cancer sites for diagnosis, and can non-destructively detect tumor status. The blood sample processing method is fast and simple, which greatly simplifies the blood sample processing process before sample capture.

[0019] In a fourth aspect, the present invention provides a method for using the kit according to the third aspect, the method comprising the following steps: (1) Separating circulating tumor cells of non-small cell lung cancer from a biological sample using the immunomagnetic beads modified with the capture antibody described in the third aspect; (2) Lysing circulating tumor cells of non-small cell lung cancer and extracting RNA, or reverse transcribing it into cDNA; (3) Quantitatively detecting mRNA or cDNA using PCR to calculate the mRNA expression level of the biomarker described in the first aspect; (4) Using the expression level of the mRNA described in step (3) as a feature, constructing an early diagnosis model for non-small cell lung cancer, obtaining the score of circulating tumor cells of non-small cell lung cancer of the subject, and determining whether the subject is positive for non-small cell lung cancer based on the score.

[0020] Preferably, the early diagnosis model for non-small cell lung cancer includes a multivariate logistic regression model, the output variable of the multivariate logistic regression model is the non-small cell lung cancer circulating tumor cell score of the subject, and the input variables of the multivariate logistic regression model are: the expression level of secretory phosphoprotein 1, the expression level of epithelial cell adhesion molecule, and the expression level of matrix metallopeptidase 14; or the expression level of secretory phosphoprotein 1 encoding nucleic acid, the expression level of epithelial cell adhesion molecule encoding nucleic acid, and the expression level of matrix metallopeptidase 14 encoding nucleic acid.

[0021] Preferably, the calculation formula for the circulating tumor cell score of non-small cell lung cancer is as shown in formula (1): NSCLC CTC Scores D = -9.311 + 0.480 × SPP1 + 0.459 × EPCAM + 0.44 × MMP14 (1); Among them, NSCLC CTC Scores D is the score of circulating tumor cells of non-small cell lung cancer, SPP1 is the expression level of secretory phosphoprotein 1 or its encoding nucleic acid, EPCAM is the expression level of epithelial cell adhesion molecule or its encoding nucleic acid, and MMP14 is the expression level of matrix metallopeptidase 14 or its encoding nucleic acid.

[0022] Preferably, the judgment criteria are: NSCLC CTC Scores D >-0.4554 is considered positive for non-small cell lung cancer.

[0023] In a fifth aspect, the present invention provides a device for early diagnosis of non-small cell lung cancer, the device comprising an information acquisition module, a calculation module and a diagnosis module; The information acquisition module is used to perform the following steps: Acquiring test information of the subject, wherein the test information includes the expression level information of the biomarker for early diagnosis of non-small cell lung cancer described in the first aspect; The computing module is used to perform the following steps: The expression level information of the acquired biomarkers is substituted into the early diagnosis model of non-small cell lung cancer to calculate the score of circulating tumor cells of non-small cell lung cancer. The calculation formula is shown in formula (1): NSCLC CTC Scores D = -9.311 + 0.480 × SPP1 + 0.459 × EPCAM + 0.44 × MMP14 (1); Among them, NSCLC CTC Scores D is the score of circulating tumor cells of non-small cell lung cancer, SPP1 is the expression level of secretory phosphoprotein 1 or its encoding nucleic acid, EPCAM is the expression level of epithelial cell adhesion molecule or its encoding nucleic acid, and MMP14 is the expression level of matrix metallopeptidase 14 or its encoding nucleic acid; The diagnostic module is used to perform the following steps: Whether the patient is positive for non-small cell lung cancer is determined based on the calculated circulating tumor cell score of non-small cell lung cancer. The judgment standard is: if the circulating tumor cell score of non-small cell lung cancer is greater than -0.4554, the patient is determined to be positive for non-small cell lung cancer.

[0024] Compared with the prior art, the present invention has the following beneficial effects: The present invention is the first to discover that secretory phosphoprotein 1, epithelial cell adhesion molecule and matrix metallopeptidase 14 are closely related to the occurrence and development of NSCLC, detect their mRNA levels, and establish an early diagnosis model for NSCLC using a multifactorial logistic regression model. The diagnostic performance of the diagnostic model is better than that of the commonly used serum tumor marker CEA in clinical practice. The accuracy rate in the training set can reach 87.5%, and the sensitivity and specificity can reach 92.5% and 82.5% respectively. The accuracy rate in the total sample can reach 89%, and the sensitivity and specificity can reach 94% and 94% respectively. The model has excellent diagnostic performance for early NSCLC and provides a method reference for the current early clinical diagnosis of NSCLC. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a flow chart for screening characteristic mRNA genes for NSCLC; Figure 2A The expression diagram of diagnostic model-related characteristic genes in normal tissues and tumor tissues; Figure 2B It is the heat map of characteristic mRNA gene expression in peripheral blood PBMCs of benign pulmonary nodules in the training set; Figure 2C This is the heat map of characteristic mRNA gene expression in peripheral blood PBMCs of early non-small cell lung cancer in the training set; Figure 2D To verify the characteristic mRNA gene expression calorimetry in peripheral blood PBMCs of concentrated benign pulmonary nodules; Figure 2E To validate the characteristic mRNA gene expression heat map in peripheral blood PBMCs of early non-small cell lung cancer; Figure 3 The ROC curve of a single target gene in distinguishing benign pulmonary nodules from patients with early non-small cell lung cancer; Figure 4A is the composite heat map of the training set; Figure 4B CTC Score for early non-small cell lung cancer and benign lung nodules in the training set D Box plot of results; Figure 4C This is the ROC graph of early non-small cell lung cancer and benign lung nodules in the training set; Figure 4D Diagnostic performance graphs of the model were further evaluated using confusion matrix algorithm; Figure 5A To validate CTC Scores for early non-small cell lung cancer, benign lung nodules, and other cancers D Box plot of results; Figure 5B This is the ROC diagram for early non-small cell lung cancer and other cancers in the validation set; Figure 5C CTC Scores for overall NSCLC and overall benign lung nodules D ROC plots and serum tumor biomarker ROC plots; Figure 5D CTC Scores for overall NSCLC and overall benign lung nodules D Confusion matrix plot. DETAILED DESCRIPTION

[0026] To further illustrate the technical means and effects of the present invention, the present invention is further described below in conjunction with the embodiments and drawings. It should be understood that the specific implementation methods described herein are only used to explain the present invention, rather than to limit the present invention.

[0027] If no specific techniques or conditions are specified in the examples, the techniques or conditions described in the literature in the field or the product instructions are used. If no manufacturer is specified for the reagents or instruments used, they are all conventional products that can be purchased through regular channels.

[0028] In a specific embodiment of the present invention, NSCLC-derived CTCs in peripheral blood are captured by targeted multi-antibody modified magnetic beads (EpCAM / N-cadherin / EGFR antibodies), and the expression levels of characteristic mRNAs in circulating tumor cells are detected by droplet digital PCR (ddPCR) technology to determine whether the subject suffers from NSCLC; and the CTC ScoreD diagnostic model established by multivariate logistic regression and the expression level of serum carcinoembryonic antigen CEA are used to determine whether the subject suffers from cancer, and its diagnostic performance is evaluated with the help of ROC diagrams and confusion matrix diagrams.

[0029] In a specific embodiment of the present invention, a kit for early diagnosis of non-small cell lung cancer is provided, the kit comprising reagents for detecting the presence or expression level of the biomarkers for early diagnosis of non-small cell lung cancer described in the present invention, such as SPP1 probe (Hs00959010_m1), CEACAM5 probe (Hs00944025_m1), EPCAM probe (Hs00901885_m1), KRT5 probe (Hs00361185_m1), KRT19 probe (Hs01051611_gH), MMP14 probe (Hs00237119_m1) and capture antibody-modified immunomagnetic beads, wherein the capture antibody comprises any one of an antibody to epithelial adhesion molecule, an antibody to N-cadherin or an antibody to epidermal growth factor, or a combination of at least two thereof.

[0030] In a specific embodiment of the present invention, a method for using a kit for early diagnosis of non-small cell lung cancer is provided, and the method comprises the following steps: (1) Isolation of circulating tumor cells of non-small cell lung cancer from biological samples using capture antibody-modified immunomagnetic beads; (2) Lysing non-small cell lung cancer circulating tumor cells, extracting RNA, and reversely transcribing it into cDNA; (3) Quantitatively detect cDNA using PCR to calculate the expression level of mRNA corresponding to the cDNA of the biomarkers secretory phosphoprotein 1, epithelial cell adhesion molecule and matrix metallopeptidase 14 described in the present invention; (4) Using the expression level of the mRNA described in step (3) as a feature, constructing an early diagnosis model for non-small cell lung cancer, obtaining the score of circulating tumor cells of non-small cell lung cancer of the subject, and determining whether the subject is positive for non-small cell lung cancer based on the score.

[0031] Among them, the early diagnosis model of non-small cell lung cancer includes a multivariate logistic regression model, the output variable of the multivariate logistic regression model is the non-small cell lung cancer circulating tumor cell score of the subject, and the input variables of the multivariate logistic regression model are: the expression level of secretory phosphoprotein 1, the expression level of epithelial cell adhesion molecule and the expression level of matrix metallopeptidase 14; or the expression level of secretory phosphoprotein 1 encoding nucleic acid, the expression level of epithelial cell adhesion molecule encoding nucleic acid and the expression level of matrix metallopeptidase 14 encoding nucleic acid.

[0032] The calculation formula for the circulating tumor cell score of non-small cell lung cancer is shown in formula (1): NSCLC CTC Scores D =﹣9.311+0.480×SPP1+0.459×EPCAM+0.44×MMP14 formula (1).

[0033] Among them, NSCLC CTC Scores D is the score of circulating tumor cells of non-small cell lung cancer, SPP1 is the expression level of secretory phosphoprotein 1 or its encoding nucleic acid, EPCAM is the expression level of epithelial cell adhesion molecule or its encoding nucleic acid, and MMP14 is the expression level of matrix metallopeptidase 14 or its encoding nucleic acid.

[0034] The criteria for judgment are: NSCLC CTC Scores D >-0.4554 is considered positive for non-small cell lung cancer.

[0035] In a specific embodiment of the present invention, a device for early diagnosis of non-small cell lung cancer is provided, and the device includes an information acquisition module, a calculation module and a diagnosis module.

[0036] The information acquisition module is used to perform the following steps: Acquire test information of the subject, wherein the test information includes the expression level information of the biomarker for early diagnosis of non-small cell lung cancer as claimed in claim 1.

[0037] The computing module is used to perform the following steps: The expression level information of the acquired biomarkers is substituted into the early diagnosis model of non-small cell lung cancer to calculate the score of circulating tumor cells of non-small cell lung cancer. The calculation formula is shown in formula (1): NSCLC CTC Scores D = -9.311 + 0.480 × SPP1 + 0.459 × EPCAM + 0.44 × MMP14 (1); Among them, NSCLC CTC Scores Dis the score of circulating tumor cells of non-small cell lung cancer, SPP1 is the expression level of secretory phosphoprotein 1 or its encoding nucleic acid, EPCAM is the expression level of epithelial cell adhesion molecule or its encoding nucleic acid, and MMP14 is the expression level of matrix metallopeptidase 14 or its encoding nucleic acid.

[0038] The diagnostic module is used to perform the following steps: Whether the patient is positive for non-small cell lung cancer is determined based on the calculated circulating tumor cell score of non-small cell lung cancer. The judgment standard is: if the circulating tumor cell score of non-small cell lung cancer is greater than -0.4554, the patient is determined to be positive for non-small cell lung cancer. Example

[0039] This example constructs and evaluates an early diagnosis model based on characteristic mRNA of NSCLC CTCs.

[0040] A total of 112 subjects were recruited, including patients with benign pulmonary nodules, early NSCLC and other cancer patients. All the subjects were included in the study from February 2024 to December 2024, including 50 patients with stage I-II non-small cell lung cancer, 50 patients with benign pulmonary nodules and 12 patients with other cancers. A total of 112 peripheral blood samples were collected.

[0041] The inclusion criteria for the study subjects are as follows: 1) Patients who have not received surgery, radiotherapy, chemotherapy or other anti-tumor treatments at the time of initial diagnosis; 2) Patients without blood system diseases; 3) Patients who understand and agree to participate in this study and have signed the patient informed consent form. The exclusion criteria are as follows: 1) Patients with a history of other malignant tumors; 2) Patients with severe infection or heart, lung, liver and kidney dysfunction; 3) Patients with insufficient blood volume, coagulation or hemolysis after blood specimen collection. According to the relevant medical ethics review methods, all steps and processes of this experiment were approved by the Ethics Review Committee of the Second Affiliated Hospital of Soochow University (approval number #JD-LK2024021-I01), and all subjects were informed and consented to this study.

[0042] (1) Screening of characteristic mRNA genes in NSCLC Screening process Figure 1As shown in the figure, first, the adenocarcinoma datasets GSE19188, GSE75037, GSE27262, and GSE63459, and squamous cell carcinoma datasets GSE19188, GSE2088, and GSE51852 in the Gene Expression Omnibus (GEO) were used to screen differentially expressed genes that were overexpressed in NSCLC tissues but lowly expressed or not expressed in normal lung tissues as candidate genes using the Limma package in the R language. The screening criteria were set as: logFC ≥ 1 and P < 0.05. Then, according to the immune cell dataset in the Human Protein Atlas (HPA), the candidate genes were screened again to exclude genes that were highly expressed in immune cells. Finally, six target gene mRNAs that were specifically highly expressed in NSCLC were screened, namely secretory phosphoprotein 1 (SPP1), carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5), epithelial cell adhesion molecule (EPCAM), keratin 5 (KRT5), keratin 19 (KRT19) and matrix metallopeptidase 14 (MMP14). At the same time, the expression of these six genes in lung tissue and NSCLC tissue was queried in the TCGA and GTEx databases ( Figure 2A ), the results showed that these six genes can distinguish tumors from normal tissues, among which SPP1, EPCAM, MMP14 and KRT19 are more highly expressed in cancer tissues.

[0043] (2) CTCs isolation and RNA extraction from subject blood samples 4 mL of peripheral venous blood was collected from the subjects in EDTA vacuum anticoagulation blood collection tubes. After the collection was completed, the sampling tubes were turned upside down 5 times, treated at 4°C, and used within 24 hours. To avoid epithelial cell contamination, all blood samples were peripheral blood samples other than the first tube. The blood collection tubes were placed in a room temperature horizontal centrifuge and centrifuged at 300 g for 15 min to obtain plasma and lower layer blood cell sediments; after absorbing the upper layer of plasma, 1× PBS solution was added to the blood cell sediment to dilute to 10 mL (i.e., twice the initial peripheral blood volume), and blown evenly; SepMate TMPeripheral blood mononuclear cell layer (PBMCs) was separated by centrifugation tube, and after washing, 400 μL (i.e., 0.1 times the initial peripheral blood volume) of 1× PBS solution was added to resuspend PBMCs; 200 μL of PBMCs cell suspension (corresponding to 2 mL initial peripheral blood volume) was incubated with 0.1 mg of biotinylated multi-antibody (EpCAM / N-caherin / EGFR, antibody purchase source information is detailed in Table 1) modified magnetic beads at 25°C for 30 min to capture non-small cell lung cancer CTCs, and the remaining PBMCs cell suspension was added with 700 μL QIAzol lysis buffer and frozen at -20°C for use; after washing CTC samples twice, 700 μL QIAzol lysis buffer was added, RNA was extracted using Direct-zolTM RNA Microprep Kit (ZYMO RESEARCH) and reverse transcribed into cDNA template using Reverse Transcription Kit (Takara), and frozen at -20°C for use.

[0044] Table 1

[0045] (3) Quantification of characteristic mRNA genes of CTCs using ddPCR According to the target gene mRNA coding gene sequence screened in step (1), target gene primers and probes (Thermo Fisher) were ordered; the target gene mRNA molecules in the sample were detected by the QX200Auto DG Droplet Digital PCR (ddPCR) system to obtain the mRNA expression level of the target gene in NSCLC CTCs captured in each sample (2 mL corresponding to peripheral blood sample). The ddPCR reaction system volume was 20 μL, consisting of ddPCR probe premix (without dUTP), enzyme-free sterile water, cDNA template, target gene primers and probes. After PCR amplification of the target gene cDNA template, the cDNA corresponding to the target gene mRNAs in the sample was quantitatively detected by a droplet reader (QX200 Droplet Reader) (transcripts / μL), and the mRNA expression of the target gene in the NSCLC CTCs captured in each 2 mL of peripheral blood sample was calculated. 40 patients with benign pulmonary nodules and 40 patients with early NSCLC were used as the training set, and 10 patients with benign pulmonary nodules, 10 patients with early NSCLC, and 12 patients with other cancers were used as the validation set. The results of the training set detection are shown in the figure. Figure 2B , Figure 2C As shown in the figure, the verification set test results are as follows Figure 2D , Figure 2E shown.

[0046] The nucleic acid detection probes are commercial products, as shown in Table 2 Table 2 (4) Construction of an early diagnosis model for non-small cell lung cancer and evaluation of its diagnostic efficacy The mRNA expression levels in the preoperative blood samples of NSCLC patients and the blood samples of benign pulmonary nodules patients obtained in step (3) are diagnosed based on the device for early diagnosis of non-small cell lung cancer designed by the present invention, and the results are subjected to ROC analysis to calculate the area under the curve (AUC) to evaluate the diagnostic efficacy of a single target gene ( Figure 3 ), genes were selected as modeling features based on the AUC value (>0.70) and p value (p<0.05) of single genes, namely SPP1, EPCAM, and MMP14.

[0047] SPSS.27.0 software was used to establish the NSCLC CTC RNA diagnostic model through multivariate logistic regression analysis. D = -9.311+0.480×SPP1+0.459×EPCAM+0.44×MMP14. Substituting the expression of the modeling feature genes in the sample into the model, the box plot and composite heat map corresponding to the NSCLC CTC Scores of each subject sample can be obtained ( Figure 4A , Figure 4B ).

[0048] The ROC curve was used to evaluate the diagnostic effect of the NSCLC diagnostic model. The results showed that the sensitivity and specificity of the model for diagnosing patients in the training set were 92.5% and 82.5% respectively under the optimal condition, the diagnostic accuracy rate reached 87.5%, and the AUC reached 0.91 ( Figure 4C-4D In the small sample validation set, the results showed significant differences between other cancers and benign lung nodules and early NSCLC ( Figure 5A ), the AUC value of other cancers and early NSCLC reached 0.98 ( Figure 5B In summary, in the overall sample (including 50 cases of NSCLC, 50 cases of benign lung nodules, and 12 cases of other cancers), the diagnostic sensitivity and specificity were 94% and 84%, respectively, and the diagnostic accuracy rate reached 89% ( Figure 5D ), in order to compare the diagnostic ability of the NSCLC diagnostic model with traditional non-small cell lung cancer tumor markers such as CEA, under the condition of clinically recognized cutoff values, the AUCs of the modeling diagnosis using CEA, CA199, and CA125 were 0.7, 0.73, and 0.73, respectively ( Figure 5C ). It can be seen that the NSCLC early diagnosis model established by the present invention has better diagnostic performance for non-small cell lung cancer than the commonly used serum tumor markers in clinical practice.

[0049] In summary, the non-small cell lung cancer circulating tumor cell scoring diagnostic model constructed with the biomarkers of the present invention has a diagnostic accuracy of 87.5%, and a sensitivity and specificity of 92.5% and 82.5%, respectively, in the test set. Compared with existing clinical tumor indicators, it can detect cancer earlier and is conducive to the early screening of non-small cell lung cancer.

[0050] The applicant declares that the present invention illustrates the detailed method of the present invention through the above-mentioned embodiments, but the present invention is not limited to the above-mentioned detailed method, that is, it does not mean that the present invention must rely on the above-mentioned detailed method to be implemented. Those skilled in the art should understand that any improvement of the present invention, equivalent replacement of various raw materials of the product of the present invention, addition of auxiliary components, selection of specific methods, etc., all fall within the protection scope and disclosure scope of the present invention.

Claims

1. A biomarker for early diagnosis of non-small cell lung cancer, characterized in that: The biomarkers include a combination of secretory phosphoprotein 1, epithelial cell adhesion molecule and matrix metallopeptidase 14, and / or a combination of nucleic acids encoding secretory phosphoprotein 1, epithelial cell adhesion molecule and matrix metallopeptidase 14; the encoding nucleic acids include mRNA or cDNA.

2. Use of the biomarker for early diagnosis of non-small cell lung cancer and / or its detection reagent according to claim 1 in the preparation of a product for early diagnosis of non-small cell lung cancer.

3. A kit for early diagnosis of non-small cell lung cancer, characterized in that: The kit comprises a reagent for detecting the presence or expression level of the biomarker for early diagnosis of non-small cell lung cancer according to claim 1.

4. The kit for early diagnosis of non-small cell lung cancer according to claim 3, characterized in that: The reagent comprises primers and / or probes for detecting the biomarker for early diagnosis of non-small cell lung cancer according to claim 1.

5. The kit for early diagnosis of non-small cell lung cancer according to claim 3, characterized in that: The kit also includes capture antibody-modified immunomagnetic beads; The capture antibody comprises any one of an antibody against epithelial adhesion molecule, an antibody against N-cadherin or an antibody against epidermal growth factor, or a combination of at least two of them.

6. A device for early diagnosis of non-small cell lung cancer, characterized in that: The device includes an information acquisition module, a calculation module and a diagnosis module; The information acquisition module is used to perform the following steps: Acquiring test information of the subject, wherein the test information includes the expression level information of the biomarker for early diagnosis of non-small cell lung cancer as claimed in claim 1; The computing module is used to perform the following steps: The expression level information of the acquired biomarkers is substituted into the early diagnosis model of non-small cell lung cancer to calculate the score of circulating tumor cells of non-small cell lung cancer. The calculation formula is shown in formula (1): NSCLC CTC Scores D = -9.311 + 0.480 × SPP1 + 0.459 × EPCAM + 0.44 × MMP14 Formula (1); Among them, NSCLC CTC Scores D is the score of circulating tumor cells of non-small cell lung cancer, SPP1 is the expression level of secretory phosphoprotein 1 or its encoding nucleic acid, EPCAM is the expression level of epithelial cell adhesion molecule or its encoding nucleic acid, and MMP14 is the expression level of matrix metallopeptidase 14 or its encoding nucleic acid; The diagnostic module is used to perform the following steps: Whether the patient is positive for non-small cell lung cancer is determined based on the calculated circulating tumor cell score of non-small cell lung cancer. The judgment standard is: if the circulating tumor cell score of non-small cell lung cancer is greater than -0.4554, the patient is determined to be positive for non-small cell lung cancer.

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