Biomarker for detecting advanced non-small cell lung cancer and application thereof

Abstract

The invention discloses a biomarker for detecting advanced non-small cell lung cancer and application of the biomarker. The biomarker comprises a combination of secretory phosphoprotein 1, epithelial cell adhesion molecules, keratin 19 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, coding nucleic acid of the keratin 19 and coding nucleic acid of the matrix metallopeptidase 14. The coding nucleic acid comprises mRNA or cDNA. The advanced non-small cell lung cancer accompanying diagnosis model constructed by using the biomarker is accurate and reliable, and can dynamically monitor the subsequent state of a patient and early warn the disease progress.

Description

Technical Field

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

[0002] At present, lung cancer is still the cancer with the highest incidence and mortality in my country. 85% of patients have NSCLC (non-small cell lung cancer), and most patients have metastases to varying degrees when diagnosed, which seriously threatens people's health. Although drugs for NSCLC have emerged in an endless stream in recent years, there are differences in treatment efficacy and prognosis among different patients. Therefore, it is urgent to develop a monitoring method that is less invasive, highly sensitive and timely, to intervene in treatment as early as possible and improve the five-year survival rate of patients.

[0003] In addition to surgical treatment, the main treatments for NSCLC patients also include conventional chemotherapy, radiotherapy, immunotherapy and molecular targeted drug therapy. However, when conventional chemotherapy regimens are used to treat patients, due to the poor specificity of the drugs, they not only kill cancer cells but also damage the body's normal tissues, which can easily cause patients to have more adverse reactions and affect the patient's treatment efficacy. In recent years, programmed cell death protein (PD-1) has entered the public eye. Its main mechanism is to activate T lymphocytes and promote the immune system's response, which also provides a longer survival period for advanced patients. However, only a small number of people can get a response and benefit widely. It is necessary to find suitable biopredictive markers to help monitor NSCLC patients who benefit from the various treatments described above.

[0004] Currently, the prognosis of NSCLC patients can be evaluated by monitoring the changes in peripheral blood circulating tumor cells (CTCs), and the response to treatment can be dynamically monitored. The current mainstream technology is the Cellsearch system, which enriches CTCs based on epithelial cell adhesion molecule (EpCAM). However, this method ignores CTCs with mesenchymal phenotypes, which may interfere with the results. This affects the constructed model, making the model for predicting prognosis and monitoring treatment less accurate.

[0005] Therefore, there is an urgent need to develop a new biomarker associated with advanced non-small cell lung cancer and a corresponding detection method to strengthen the diagnosis of advanced non-small cell lung cancer and the monitoring of disease progression during the treatment of patients. Summary of the invention

[0006] In view of the deficiencies of the prior art and actual needs, the present invention provides a biomarker for detecting advanced non-small cell lung cancer and its application, which can accurately monitor the patient's response to treatment. The present invention solves the problem of real-time monitoring of treatment effect evaluation and better realizes accurate treatment.

[0007] In order to achieve the purpose of the invention, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a biomarker for the detection and companion diagnosis of advanced non-small cell lung cancer, the biomarker comprising: a combination of secretory phosphoprotein 1, carcinoembryonic antigen-related cell adhesion molecule 5, epithelial cell adhesion molecule, keratin 5, keratin 19 and matrix metallopeptidase 14, and / or a combination of nucleic acids encoding secretory phosphoprotein 1, carcinoembryonic antigen-related cell adhesion molecule 5, epithelial cell adhesion molecule, keratin 5, keratin 19 and matrix metallopeptidase 14; the encoding nucleic acid comprises mRNA or cDNA.

[0009] The companion diagnostic model for advanced non-small cell lung cancer constructed with the biomarkers of the present invention is accurate and reliable, and can dynamically monitor the patient's subsequent status and warn of disease progression earlier.

[0010] In a second aspect, the present invention provides the use of the biomarker for detection and companion diagnosis of advanced non-small cell lung cancer and / or its detection reagent according to the first aspect in the preparation of a product for detecting advanced non-small cell lung cancer.

[0011] In a third aspect, the present invention provides a kit for companion diagnosis of advanced non-small cell lung cancer, the kit comprising a reagent for detecting the presence or expression level of the biomarker for detection and companion diagnosis of advanced non-small cell lung cancer as described in the first aspect.

[0012] Preferably, the reagent comprises primers and / or probes for detecting the biomarkers for detection and concomitant diagnosis of advanced non-small cell lung cancer as described in the first aspect.

[0013] Preferably, the kit further comprises immunomagnetic beads modified with capture antibodies.

[0014] 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.

[0015] 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:

[0016] (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;

[0017] (2) extracting RNA from circulating tumor cells of non-small cell lung cancer after lysis or reverse transcribing it into cDNA;

[0018] (3) Quantitatively detecting mRNA or cDNA using PCR to calculate the expression level of mRNA of the biomarker described in the first aspect;

[0019] (4) Using the expression level of the mRNA described in step (3) as a feature, constructing a companion diagnostic model for non-small cell lung cancer, obtaining the scores of circulating tumor cells of non-small cell lung cancer of the subject before and after treatment, and making a judgment based on the follow-up scores before and after treatment.

[0020] Preferably, the non-small cell lung cancer companion diagnostic model 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, the expression level of keratin 19, 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, the expression level of keratin 19 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):

[0022] NSCLC CTC Scores M =-20.327+1.077×SPP1+1.069×EPCAM+0.124×

[0023] KRT19+0.727×MMP14 (Formula 1);

[0024] Among them, NSCLC CTC Scores M 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, KRT19 is the expression level of keratin 19 or its encoding nucleic acid, and MMP14 is the expression level of matrix metallopeptidase 14 or its encoding nucleic acid.

[0025] In a fifth aspect, the present invention provides a device for companion diagnosis of advanced non-small cell lung cancer, the device comprising an information acquisition module, a calculation module and a diagnosis module;

[0026] The information acquisition module is used to perform the following steps:

[0027] Acquiring test information of the subject, the test information including the expression level information of the biomarker for advanced non-small cell lung cancer detection and companion diagnosis described in the first aspect;

[0028] The computing module is used to perform the following steps:

[0029] The expression level information of the acquired biomarkers was substituted into the non-small cell lung cancer diagnostic model to calculate the scores of circulating tumor cells of non-small cell lung cancer of the subjects before and after treatment. The calculation formula is shown in formula (1):

[0030] NSCLC CTC Scores M =-20.327+1.077×SPP1+1.069×EPCAM+0.124×

[0031] KRT19+0.727×MMP14 (1);

[0032] Among them, NSCLC CTC Scores M 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, KRT19 is the expression level of keratin 19 or its encoding nucleic acid, and MMP14 is the expression level of matrix metallopeptidase 14 or its encoding nucleic acid.

[0033] The diagnostic module is used to perform the following steps:

[0034] The judgment was made based on the calculated scores of circulating tumor cells of non-small cell lung cancer. The judgment criteria were (1) NSCLC CTC Scores during the patient follow-up. M Scores higher than or equal to those before treatment M The score indicates that the patient may have disease progression or drug resistance; (2) NSCLC CTC Scores during patient follow-up M NSCLC CTC Scores lower than before treatment M The score indicates that the patient may be in remission.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] The biomarkers of the present invention can be used to construct a companion diagnostic model for advanced non-small cell lung cancer. Compared with common serum tumor biomarkers, the companion diagnostic model for advanced non-small cell lung cancer can more accurately evaluate the efficacy of advanced non-small cell lung cancer and provide a reference for patients' medication. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Schematic diagram of the process for establishing a prognostic model;

[0038] Figure 2 The expression results of three surface biomarkers in NSCLC cell lines are shown in Figure 2;

[0039] Figure 3 Results of exploring the optimal dosage of anti-EpCAM, anti-N-cadherin, and anti-EGFR antibodies to capture cells;

[0040] Figure 4 The results of the capture efficiency of three antibody combinations on cells of different cell lines are shown in the figure;

[0041] Figure 5A It is the heat map of characteristic mRNA gene expression in peripheral blood PBMCs of benign pulmonary nodules in the training set;

[0042] Figure 5B It is the heat map of characteristic mRNA gene expression in peripheral blood PBMCs of non-small cell lung cancer in the training set;

[0043] Figure 6 The ROC curve of a single target gene in distinguishing benign pulmonary nodules from advanced NSCLC patients;

[0044] Figure 7 is the composite heat map of the training set;

[0045] Figure 8 The ROC diagram and confusion matrix algorithm diagram for advanced non-small cell lung cancer and benign lung nodules in the training set;

[0046] Fig. 9 Composite graph of circulating tumor cell scores for 9 longitudinally monitored patients;

[0047] Fig. 10A This is a score chart for the dynamic monitoring of the patient's LC67 condition during treatment;

[0048] Fig. 10B This is a score chart for the dynamic monitoring of the patient's condition during LC141 treatment;

[0049] Fig. 10C This is a score chart for the dynamic monitoring of the patient's LC66 condition during treatment;

[0050] Fig.11A It is a score chart for dynamic monitoring of the patient's condition during LC55 treatment;

[0051] Fig. 11B This is a score chart for dynamic monitoring of the patient's condition during LC84 treatment. DETAILED DESCRIPTION

[0052] 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.

[0053] 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.

[0054] In a specific embodiment of the present invention, Figure 1 As shown in the figure, this study used a multi-antibody modified magnetic bead (EpCAM / N-cadherin / EGFR antibody) system to efficiently capture CTCs in peripheral blood samples of NSCLC patients, and then used droplet digital PCR (ddPCR) to absolutely quantify the characteristic genes of the biomarkers of the present invention. The companion diagnostic model established by multi-factor logistic regression was used to distinguish the expression levels of serum tumor biomarkers, and its distinguishing performance was evaluated with the help of ROC diagrams and confusion matrix diagrams, and the progression of the disease during treatment was verified with the help of dynamic score diagrams.

[0055] 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.

[0056] In a specific embodiment of the present invention, a method for using a kit for diagnosing advanced non-small cell lung cancer is provided, the method comprising the following steps:

[0057] (1) Isolation of circulating tumor cells of non-small cell lung cancer from biological samples using capture antibody-modified immunomagnetic beads;

[0058] (2) Lysing circulating tumor cells of non-small cell lung cancer and extracting RNA, or reverse transcribing it into cDNA;

[0059] (3) Quantitative detection of mRNA or cDNA by PCR was performed to calculate the expression levels of mRNA corresponding to the cDNA of biomarkers secreted phosphoprotein 1, carcinoembryonic antigen-related cell adhesion molecule 5, epithelial cell adhesion molecule, keratin 5, keratin 19, and matrix metallopeptidase 14;

[0060] (4) constructing a non-small cell lung cancer diagnostic model based on the mRNA expression level of step (3), obtaining the score of circulating tumor cells of non-small cell lung cancer of the subject, and making a judgment based on the score.

[0061] Among them, the non-small cell lung cancer diagnostic model 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, the expression level of keratin 19 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, the expression level of keratin 19 encoding nucleic acid and the expression level of matrix metallopeptidase 14 encoding nucleic acid.

[0062] The calculation formula for the circulating tumor cell score of non-small cell lung cancer is as shown in formula (1):

[0063] NSCLC CTC Scores M =-20.327+1.077×SPP1+1.069×EPCAM+0.124×

[0064] KRT19+0.727×MMP14 (1);

[0065] Among them, NSCLC CTC Scores M 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, KRT19 is the expression level of keratin 19 or its encoding nucleic acid, and MMP14 is the expression level of matrix metallopeptidase 14 or its encoding nucleic acid.

[0066] In a specific embodiment of the present invention, a device for companion diagnosis of advanced non-small cell lung cancer is provided, the device comprising an information acquisition module, a calculation module and a diagnosis module;

[0067] The information acquisition module is used to perform the following steps:

[0068] Acquiring test information of the subject, wherein the test information includes expression level information of biomarkers used for advanced non-small cell lung cancer detection and companion diagnosis;

[0069] The computing module is used to perform the following steps:

[0070] The expression level information of the acquired biomarkers was substituted into the companion diagnostic model for non-small cell lung cancer, and the scores of circulating tumor cells of non-small cell lung cancer of the subjects before and after treatment were calculated. The calculation formula is shown in formula (1):

[0071] NSCLC CTC Scores M =-20.327+1.077×SPP1+1.069×EPCAM+0.124×

[0072] KRT19+0.727×MMP14 (1);

[0073] Among them, NSCLC CTC Scores M 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, KRT19 is the expression level of keratin 19 or its encoding nucleic acid, and MMP14 is the expression level of matrix metallopeptidase 14 or its encoding nucleic acid.

[0074] The diagnostic module is used to perform the following steps:

[0075] The judgment is made based on the calculated scores of circulating tumor cells of non-small cell lung cancer, and the judgment criteria are: (1) based on the NSCLC CTC Scores before treatment M The scores were baseline and NSCLC CTCScores during follow-up. M Scores higher than or equal to those before treatment M The score indicates that the patient may have disease progression or drug resistance; (2) NSCLC CTC Scores during patient follow-up M NSCLC CTC Scores lower than before treatment M The score indicates that the patient may be in remission.

[0076] Example 1

[0077] This example evaluates the expression of NSCLC CTCs surface proteins on the cell membrane surface.

[0078] A549, H1299, SKMES1, and H2170 were used for flow cytometry experimental verification. The specific steps are as follows:

[0079] For each type of cell, 4 μL of the corresponding antibody (EpCAM / N-cadherin / EGFR) was added, blown evenly, and incubated for 30 minutes in an automatic flip oscillator in oscillation mode. After incubation, the supernatant was removed after three washes, and 2 μL of the corresponding secondary antibody was added and incubated in the dark for 20 minutes. Subsequently, the samples were tested using a flow cytometer to obtain the expression of surface marker proteins of the four tumor cell lines ( Figure 2), which demonstrated that in different subtypes of NSCLC cell lines, EpCAM, N-cadherin, and EGFR showed high heterogeneity on the cell membrane surface, which could fully simulate NSCLC-derived CTCs, including epithelial phenotype CTCs and epithelial-mesenchymal mixed phenotype CTCs.

[0080] This example also explored the optimal dosage of anti-EpCAM, anti-N-cadherin, and anti-EGFR antibodies to capture cells: SKMES1 was used as a model cell, and the optimal modification dosage of a single antibody was first explored, with four gradient modification dosages of 0, 100, 200, and 300 ng. After obtaining the optimal modification dosage of a single antibody, the nanomagnetic beads were modified with a mixture of the three antibodies ( Figure 3 ), and the capture efficiency was as high as 80% in four cell lines ( Figure 4 ).

[0081] Example 2

[0082] In this example, after capturing NSCLC CTCs, the characteristic mRNA genes were absolutely quantified, and a non-small cell lung cancer prognosis model was constructed for dynamic monitoring.

[0083] A total of 73 subjects, including patients with benign pulmonary nodules and advanced NSCLC, were recruited from February to December 2024, including 40 patients with stage III / IV non-small cell lung cancer and 40 patients with benign pulmonary nodules.

[0084] The inclusion criteria for the study subjects are as follows: 1) Tumor classification: non-small cell lung cancer confirmed by histology or cytology; 2) There is sufficient clinical information and good follow-up conditions; 3) Understand and agree to participate in this study and have signed the patient informed consent. The exclusion criteria are as follows: 1) Patients with a history of other tumors; 2) Patients with severe infection or heart, lung, liver and kidney dysfunction; 3) After the blood specimen is collected, there is insufficient blood volume, coagulation or hemolysis; 4) Patients refuse to accept the examination. According to the relevant medical ethics review methods, this experiment has been approved by the Ethics Review Committee of the Second Affiliated Hospital of Soochow University (approval number #JD-LK2024021-I01), and all subjects have informed consent to this study.

[0085] (1) Absolute quantification of characteristic mRNA genes after capturing NSCLC CTCs

[0086] First, PBMCs corresponding to 2 mL of peripheral blood were separated, and the cell suspension was incubated with 0.1 mg of multi-antibody (EpCAM / N-caherin / EGFR) modified magnetic beads at 25°C for 30 min to capture non-small cell lung cancer CTCs. After magnetic separation, the supernatant was discarded, and 700 μL of QIAzol lysis buffer was added and frozen at -20°C for later use.

[0087] Secondly, thaw the CTC sample with lysate in a 37℃ water bath, vortex and let stand for 5 minutes; add anhydrous ethanol or 95% ethanol with the same volume as the lysate and blow evenly; take the centrifuge column and collection tube of the zymo kit, put the centrifuge column into the collection tube, add 700μL of the mixed solution to the centrifuge column, centrifuge at 12,000rcf for 30s, discard the waste liquid in the collection tube, repeat this step until the mixed solution is centrifuged, and discard the collection tube; add 400μL Direct-zol TM RNAPreWash (DRP), centrifuge at 12,000 rcf for 30 seconds, discard the waste liquid in the collection tube, repeat this step; add 700 μL RNA WashBuffer (RWB) to the centrifuge column, centrifuge at 12,000 rcf for 1 minute, discard the waste liquid and collection tube in the collection tube; empty for 5 minutes, dry the liquid, add 15 μL DNase / RNase-Free Water to the centrifuge column to elute RNA, centrifuge at 15,000 rcf for 30 seconds to obtain RNA. Then, reverse transcribe it into a cDNA template using a reverse transcription kit (Takara) and freeze it at -20°C for later use.

[0088] The target gene mRNA molecules in the sample were absolutely quantified by the QX200Auto DG droplet digital PCR (ddPCR) system. The 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 the droplet reader (QX200 Droplet Reader) (transcripts / μL), and the mRNA expression level of the target gene of NSCLC CTCs captured in each 2 mL of peripheral blood sample was calculated. 40 benign pulmonary nodules and 30 advanced NSCLC patients were used as the training set, and 9 advanced NSCLC patients with longitudinal monitoring of CTCs were used as the validation set. The training set detection results are shown in the following figure. Figure 5A , Figure 5B shown.

[0089] (2) Construction of companion diagnostic model for non-small cell lung cancer

[0090] Based on the mRNA expression levels in the obtained training set blood samples, ROC analysis was performed to calculate the area under the curve (AUC) to evaluate the diagnostic efficacy of a single target gene ( Figure 6 ), genes were selected as modeling features based on the AUC values ​​(>0.75) and p values ​​(p<0.05) of single genes, namely SPP1, EPCAM, KRT19, and MMP14.

[0091] Establishment of NSCLC CTC RNA companion diagnostic model by multivariate logistic regression analysis:

[0092] NSCLC CTC Scores M =-20.327+1.077×SPP1+1.069×EPCAM+0.124×

[0093] KRT19+0.727×MMP14.

[0094] Substituting the expression of the modeling feature genes in the sample into the model, we can obtain the composite heat map corresponding to the score of each subject sample in the training set ( Figure 7 ), the ROC curve was used to evaluate the diagnostic effect of the NSCLC diagnostic model. The results showed that the AUC value of the model reached 0.91, the sensitivity and specificity were 93.3% and 95% respectively, and the diagnostic accuracy rate reached 94.3% ( Figure 8 ).

[0095] (3) Dynamically monitor changes in patients’ scores before, during, and after treatment, and evaluate and predict disease status based on imaging results.

[0096] The peripheral blood of patients was tested for CTC before, during, and after treatment, and the model score status in step (2) was analyzed to compare the trend of changes before and after treatment ( Fig. 9 ).

[0097] The imaging results corresponding to the patient's treatment time point were collected and evaluated according to the RICIST (Response Evaluation Criteria in Solid Tumours) standard. The specific standards are as follows:

[0098] 1) Complete remission (CR) means that all tumor target lesions disappear without the appearance of new lesions, which lasts for 4 weeks;

[0099] 2) Partial response (PR) means that the sum of the maximum diameters of target tumor lesions is reduced by ≥30% and maintained for at least 4 weeks;

[0100] 3) Stable lesion (SD) means that the sum of the maximum diameters of the target tumor lesions has not decreased to PR, or has not increased to PD;

[0101] 4) Progressive disease (PD) refers to an increase of at least 20% in the sum of the maximum diameters of target tumor lesions or the appearance of new lesions.

[0102] After treatment, the circulating tumor cell scores (CTC Score) of the three patients were lower than before treatment, and the trend was decreasing or stabilizing. The imaging results showed that the trend of CTC Score changes was closely related to the disease status, while the dynamic changes of the serum oncology indicator CYFRA21-1 did not completely match the disease status ( Figure 10A-10C ).

[0103] like Figure 11A-11B As shown, the CTC scores of the two patients increased during subsequent treatment, and PET-CT finally confirmed the progression of the disease and the occurrence of bone metastasis.

[0104] In summary, the present invention, by mining non-small cell lung cancer biomarkers, further constructs a companion diagnostic model for NSCLC based on multivariate logistic regression, fully considering the contribution of biological information contained in CTCs in tumor biology, so that the companion diagnostic model has higher accuracy. In the dynamic monitoring of the validation set, it is further confirmed that the model can more directly and accurately reflect the real-time changes in the disease state of cancer patients than traditional serum tumor markers. It shows that the model constructed by the present invention has the potential to be an auxiliary tool for monitoring the treatment response of advanced NSCLC.

[0105] 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 the detection and companion diagnosis of advanced non-small cell lung cancer, characterized in that: The biomarkers include: a combination of secretory phosphoprotein 1, epithelial cell adhesion molecule, keratin 19 and matrix metallopeptidase 14, and / or a combination of nucleic acids encoding secretory phosphoprotein 1, epithelial cell adhesion molecule, keratin 19 and matrix metallopeptidase 14; the encoding nucleic acids include mRNA or cDNA.

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

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

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

5. The kit for companion diagnosis of advanced 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 method for using the kit according to any one of claims 3 to 5, characterized in that: The method of use comprises 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 claim 5; (2) extracting RNA from circulating tumor cells of non-small cell lung cancer after lysis or reverse transcribing it into cDNA; (3) Quantitatively detecting mRNA or cDNA using PCR to calculate the expression level of mRNA of the biomarker described in claim 1; (4) Using the expression level of the mRNA described in step (3) as a feature, constructing a companion diagnostic model for non-small cell lung cancer, obtaining the circulating tumor cell scores of non-small cell lung cancer of the subject before and after treatment, and making a judgment based on the follow-up scores before and after treatment.

7. The method of use according to claim 6, characterized in that: The non-small cell lung cancer companion diagnostic model 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, the expression level of keratin 19 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, the expression level of keratin 19 encoding nucleic acid and the expression level of matrix metallopeptidase 14 encoding nucleic acid.

8. The method of use according to claim 6, characterized in that: The calculation formula of the circulating tumor cell score of non-small cell lung cancer is shown in formula (1): NSCLC CTC Scores M =-20.327+1.077×SPP1+1.069×EPCAM+0.124× KRT19+0.727×MMP14 (1); Among them, NSCLC CTC Scores M is the circulating tumor cell score 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, KRT19 is the expression level of keratin 19 or its encoding nucleic acid, and MMP14 is the expression level of matrix metallopeptidase 14 or its encoding nucleic acid.

9. The method of use according to claim 6, characterized in that: The criteria for judgment are: (1) If NSCLC CTC Scores after treatment M Scores higher than or equal to those before treatment M The score indicates that the patient's disease is progressing or resistant; (2) If NSCLC CTC Scores M NSCLC CTC Scores lower than before treatment M The score indicates that the patient's condition has improved.

10. A device for companion diagnosis of advanced 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 detection and companion diagnosis of advanced 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 was substituted into the companion diagnostic model for non-small cell lung cancer, and the scores of circulating tumor cells of non-small cell lung cancer of the subjects before and after treatment were calculated. The calculation formula is shown in formula (1): NSCLC CTC Scores M =-20.327+1.077×SPP1+1.069×EPCAM+0.124×KRT19+0.727×MMP14 Formula (1); Among them, NSCLC CTC Scores M 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, KRT19 is the expression level of keratin 19 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: The judgment is made based on the calculated scores of circulating tumor cells of non-small cell lung cancer. The judgment criteria are (1) if NSCLC CTC Scores after treatment M Scores higher than or equal to those before treatment M The score indicates that the patient's disease is progressing or resistant; (2) If NSCLC CTC Scores M NSCLC CTC Scores lower than before treatment M The score indicates that the patient's condition has improved.

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