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

Abstract

The application discloses a biomarker for detecting advanced non-small cell lung cancer and application thereof. The biomarker comprises a combination of secreted phosphoprotein 1, epithelial cell adhesion molecule, keratin 19 and matrix metallopeptidase 14, and / or a combination of a coding nucleic acid of secreted phosphoprotein 1, a coding nucleic acid of epithelial cell adhesion molecule, a coding nucleic acid of keratin 19 and a coding nucleic acid of 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 of the application is accurate and reliable, can dynamically monitor the subsequent state of a patient, and can early warn disease progression.

Description

Technical Field

[0001] This invention belongs to the field of molecular biology technology and relates to a biomarker for detecting advanced non-small cell lung cancer and its application. Background Technology

[0002] Currently, lung cancer remains the leading cause of cancer incidence and mortality in my country. 85% of patients have non-small cell lung cancer (NSCLC), and most have already experienced varying degrees of metastasis at the time of diagnosis, seriously threatening public health. Although numerous drugs for NSCLC have emerged in recent years, treatment efficacy and prognosis vary among patients. Therefore, there is an urgent need to develop a minimally invasive, highly sensitive, and timely monitoring method to intervene and treat as early as possible, thereby improving the five-year survival rate of patients.

[0003] Besides surgery, the main treatments for NSCLC patients include conventional chemotherapy, radiotherapy, immunotherapy, and molecularly targeted therapy. However, conventional chemotherapy regimens, due to the poor specificity of the drugs, not only kill cancer cells but also damage normal tissues, easily leading to numerous adverse reactions and affecting the treatment efficacy. In recent years, programmed cell death protein (PD-1) has come into the public eye. Its main mechanism is to activate T lymphocytes, prompting an immune system response, and it has also provided longer survival for advanced patients. However, only a minority of patients achieve a response and widespread benefit. There is a need to find suitable biomarkers to help monitor NSCLC patients who benefit from the aforementioned treatments.

[0004] Currently, monitoring changes in circulating tumor cells (CTCs) in peripheral blood can assess the prognosis of NSCLC patients and dynamically monitor their response to treatment. The mainstream technology is the Cellsearch system, which enriches CTCs based on epithelial cell adhesion molecules (EpCAM). However, this method ignores CTCs with a mesenchymal phenotype, which may interfere with the results. This can affect the constructed model, resulting in lower accuracy in predicting prognosis and monitoring treatment.

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

[0006] To address the shortcomings of existing technologies and practical needs, this invention provides a biomarker for detecting advanced non-small cell lung cancer and its application, enabling precise monitoring of patient response to treatment. This invention solves the challenge of real-time monitoring and evaluation of treatment effectiveness, thus better realizing precision medicine.

[0007] To achieve this objective, the present invention adopts the following technical solution:

[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 secreted phosphoprotein 1, carcinoembryonic antigen-associated cell adhesion molecule 5, epithelial cell adhesion molecule, keratin 5, keratin 19 and matrix metallopeptidase 14, and / or a combination of nucleic acids encoding secreted phosphoprotein 1, carcinoembryonic antigen-associated cell adhesion molecule 5, epithelial cell adhesion molecule, keratin 5, keratin 19 and matrix metallopeptidase 14; wherein the encoded nucleic acid comprises mRNA or cDNA.

[0009] The biomarker-based companion diagnostic model for advanced non-small cell lung cancer developed in this invention is accurate and reliable, and can dynamically monitor the patient's subsequent condition and provide earlier warning of disease progression.

[0010] In a second aspect, the present invention provides the use of biomarkers and / or detection reagents thereof for the detection and companion diagnosis of advanced non-small cell lung cancer according to the first aspect in the preparation of products for the detection of advanced non-small cell lung cancer.

[0011] Thirdly, the present invention provides a kit for companion diagnostics of advanced non-small cell lung cancer, the kit comprising reagents for detecting the presence or expression level of the biomarkers described in the first aspect for the detection and companion diagnostics of advanced non-small cell lung cancer.

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

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

[0014] Preferably, the capturing antibody includes any one or a combination of at least two of the following: antibodies against epithelial adhesion molecules, antibodies against N-cadherin, or antibodies against epidermal growth factor.

[0015] Fourthly, the present invention provides a method for using the reagent kit described in the third aspect, the method comprising the following steps:

[0016] (1) Using the capture antibody-modified immunomagnetic beads described in the third aspect to isolate circulating tumor cells of non-small cell lung cancer from biological samples;

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

[0018] (3) Use PCR to quantitatively detect mRNA or cDNA and calculate the expression level of the mRNA of the biomarkers mentioned in the first aspect;

[0019] (4) Based on the expression level of mRNA described in step (3), a companion diagnostic model for non-small cell lung cancer is constructed. The scores of circulating tumor cells of non-small cell lung cancer in the subjects before and after treatment are obtained, and the results are judged based on the follow-up scores before and after treatment.

[0020] Preferably, the companion diagnostic model for non-small cell lung cancer includes a multivariate logistic regression model, wherein 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 nucleic acid encoded by secretory phosphoprotein 1, the expression level of nucleic acid encoded by epithelial cell adhesion molecule, the expression level of nucleic acid encoded by keratin 19, and the expression level of nucleic acid encoded by matrix metallopeptidase 14.

[0021] Preferably, the formula for calculating the circulating tumor cell score of non-small cell lung cancer is shown in equation (1):

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

[0023] KRT19+0.727×MMP14(Equation 1);

[0024] Among them, NSCLC CTC Scores M The score represents the circulating tumor cells in non-small cell lung cancer. SPP1 represents the expression level of secreted phosphoprotein 1 or its encoded nucleic acid, EPCAM represents the expression level of epithelial cell adhesion molecule or its encoded nucleic acid, KRT19 represents the expression level of keratin 19 or its encoded nucleic acid, and MMP14 represents the expression level of matrix metallopeptidase 14 or its encoded nucleic acid.

[0025] Fifthly, 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 diagnostic module;

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

[0027] Obtain the subject's detection information, which includes the expression level information of the biomarkers used for the detection and companion diagnosis of advanced non-small cell lung cancer as described in the first aspect;

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

[0029] The expression level information of the obtained biomarkers was substituted into the non-small cell lung cancer diagnostic model to calculate the non-small cell lung cancer circulating tumor cell score of the subjects before and after treatment. The calculation formula is shown in Equation (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 The score represents the circulating tumor cells in non-small cell lung cancer. SPP1 represents the expression level of secreted phosphoprotein 1 or its encoded nucleic acid, EPCAM represents the expression level of epithelial cell adhesion molecule or its encoded nucleic acid, KRT19 represents the expression level of keratin 19 or its encoded nucleic acid, and MMP14 represents the expression level of matrix metallopeptidase 14 or its encoded nucleic acid.

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

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

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

[0036] The biomarkers of this invention can be used to construct companion diagnostic models for advanced non-small cell lung cancer. Compared with common serum tumor biomarkers, these companion diagnostic models can more accurately assess the efficacy of treatment for advanced non-small cell lung cancer and provide a reference for patient medication. Attached Figure Description

[0037] Figure 1 A schematic diagram illustrating the process of establishing a prognostic model;

[0038] Figure 2 The graph shows the expression levels of three surface biomarkers in NSCLC cell lines.

[0039] Figure 3 Figure showing the results of the investigation into the optimal dosage of anti-EpCAM, anti-N-cadherin, and anti-EGFR antibodies for cell capture;

[0040] Figure 4 The graph shows the capture efficiency of the three antibody combinations against different cell lines.

[0041] Figure 5A To train a heatmap of characteristic mRNA gene expression levels in peripheral blood PBMCs from benign pulmonary nodules;

[0042] Figure 5B To train a heatmap of characteristic mRNA gene expression levels in peripheral blood PBMCs of non-small cell lung cancer;

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

[0044] Figure 7 A composite heatmap of the training set;

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

[0046] Figure 9 A composite plot of circulating tumor cell scores from nine longitudinal monitoring outcomes of patients;

[0047] Figure 10A A dynamic monitoring score chart of the patient's condition during LC67 treatment;

[0048] Figure 10B A dynamic monitoring score chart of the patient's condition during LC141 treatment;

[0049] Figure 10C A dynamic monitoring score chart of the patient's condition during LC66 treatment;

[0050] Figure 11A A dynamic monitoring score chart of the patient's condition during LC55 treatment;

[0051] Figure 11B A dynamic monitoring score chart of the patient's condition during LC84 treatment. Detailed Implementation

[0052] To further illustrate the technical means and effects of this invention, the following description, in conjunction with embodiments and accompanying drawings, provides a further explanation of the invention. It is understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it.

[0053] Where specific techniques or conditions are not specified in the examples, they shall be performed in accordance with the techniques or conditions described in the literature in this field, or in accordance with the product instructions. Reagents or instruments whose manufacturers are not specified are all conventional products that can be purchased through legitimate channels.

[0054] In specific embodiments of the present invention, such as Figure 1 As shown, this study efficiently captured central cytokines (CTCs) in peripheral blood samples from NSCLC patients using a multi-antibody modified magnetic bead (EpCAM / N-cadherin / EGFR antibody) system. Then, absolute quantification of the biomarker characteristic genes of this invention was performed using droplet digital PCR (ddPCR). A companion diagnostic model established using multivariate logistic regression was used to distinguish between the expression levels of serum tumor biomarkers and the results. The discriminative performance was evaluated using ROC plots and confusion matrices, and the dynamic scoring plot was used to verify disease progression during treatment.

[0055] In one specific embodiment of the present invention, a kit for early diagnosis of non-small cell lung cancer is provided. The kit includes reagents for detecting the presence or expression level of biomarkers for early diagnosis of non-small cell lung cancer as 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 immunomagnetic beads modified with capture antibodies. The capture antibodies include any one or a combination of at least two of the following: antibodies against epithelial adhesion molecules, antibodies against N-cadherin, or antibodies against epidermal growth factor.

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

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

[0058] (2) Extract RNA from circulating tumor cells of non-small cell lung cancer after lysis, or reverse transcribe it into cDNA;

[0059] (3) Quantitative detection of mRNA or cDNA was performed using PCR, and the expression levels of the cDNA corresponding to the biomarkers secretory phosphoprotein 1, carcinoembryonic antigen-associated cell adhesion molecule 5, epithelial cell adhesion molecule, keratin 5, keratin 19 and matrix metallopeptidase 14 were calculated.

[0060] (4) Using the expression level of mRNA described in step (3) as a feature, construct a diagnostic model for non-small cell lung cancer, obtain the score of circulating tumor cells of non-small cell lung cancer in the subject, and make a judgment based on the score.

[0061] 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. 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 nucleic acid encoded by secretory phosphoprotein 1, the expression level of nucleic acid encoded by epithelial cell adhesion molecule, the expression level of nucleic acid encoded by keratin 19, and the expression level of nucleic acid encoded by matrix metallopeptidase 14.

[0062] The formula for calculating the circulating tumor cell score in non-small cell lung cancer is shown in equation (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 The score represents the circulating tumor cells in non-small cell lung cancer. SPP1 represents the expression level of secreted phosphoprotein 1 or its encoded nucleic acid, EPCAM represents the expression level of epithelial cell adhesion molecule or its encoded nucleic acid, KRT19 represents the expression level of keratin 19 or its encoded nucleic acid, and MMP14 represents the expression level of matrix metallopeptidase 14 or its encoded nucleic acid.

[0066] In one 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 diagnostic module;

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

[0068] Acquire the subject's detection information, which includes the expression level information of biomarkers used for the detection and companion diagnosis of advanced non-small cell lung cancer;

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

[0070] The expression level information of the obtained biomarkers was substituted into the non-small cell lung cancer companion diagnostic model to calculate the non-small cell lung cancer circulating tumor cell score of the subject before and after treatment. The calculation formula is shown in Equation (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 The score represents the circulating tumor cells in non-small cell lung cancer. SPP1 represents the expression level of secreted phosphoprotein 1 or its encoded nucleic acid, EPCAM represents the expression level of epithelial cell adhesion molecule or its encoded nucleic acid, KRT19 represents the expression level of keratin 19 or its encoded nucleic acid, and MMP14 represents the expression level of matrix metallopeptidase 14 or its encoded nucleic acid.

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

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

[0076] Example 1

[0077] This embodiment assesses the expression levels of surface proteins of NSCLC CTCs on the cell membrane surface.

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

[0079] For each cell type, 4 μL of the corresponding antibody (EpCAM / N-cadherin / EGFR) was added, mixed well, and incubated for 30 min in shaking mode on an automated rotary shaker. After incubation, the cells were washed three times, the supernatant was removed, and 2 μL of the corresponding secondary antibody was added and incubated for 20 min in the dark. Subsequently, flow cytometry was used to analyze the samples and obtain the expression of surface marker proteins of the four tumor cell lines. Figure 2This study demonstrates that EpCAM, N-cadherin, and EGFR exhibit high heterogeneity on the cell membrane surface in different NSCLC cell lines, effectively mimicking NSCLC-derived CTCs, including epithelial phenotype CTCs and epithelial-mesenchymal mixed phenotype CTCs.

[0080] This embodiment also investigated the optimal dosage of anti-EpCAM, anti-N-cadherin, and anti-EGFR antibodies for cell capture: using SKMES1 cells as a model, the optimal modification dosage of a single antibody was first investigated at four gradients: 0, 100, 200, and 300 ng. After obtaining the optimal modification dosage of a single antibody, a mixture of the three antibodies was used to modify the magnetic nanobeads. Figure 3 In capture experiments conducted on four cell lines, the capture efficiency reached as high as 80%. Figure 4 ).

[0081] Example 2

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

[0083] A total of 73 participants were recruited, including patients with benign pulmonary nodules and patients with advanced NSCLC. All participants were enrolled in the study between February 2024 and 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 participants were as follows: 1) Tumor classification: histologically or cytologically confirmed non-small cell lung cancer; 2) Sufficient clinical information and good follow-up conditions; 3) Understanding and consent to participate in this study, and having signed the patient informed consent form. The exclusion criteria were as follows: 1) Patients with a history of other tumors; 2) Patients with severe infections or heart, lung, liver, or kidney dysfunction; 3) Patients experiencing insufficient blood volume, coagulation, or hemolysis after blood sample collection; 4) Patients who refused examination. In accordance with relevant medical ethics review methods, this experiment has been approved by the Ethics Review Committee of the Second Affiliated Hospital of Soochow University (Approval No. #JD-LK2024021-I01), and all participants provided informed consent for this study.

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

[0086] First, 2 mL of peripheral blood corresponding to PBMCs were isolated. 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 the cells were frozen at -20 °C for later use.

[0087] Next, thaw the CTC sample with lysis buffer in a 37°C water bath, vortex and let stand for 5 min; add an equal volume of anhydrous ethanol or 95% ethanol to the lysis buffer and mix well; using the centrifuge column and collection tube from the ZYMO kit, place the centrifuge column into the collection tube, add 700 μL of the mixture to the centrifuge column, centrifuge at 12,000 rcf for 30 s, discard the waste liquid in the collection tube, repeat this step until the mixture is completely centrifuged, then discard the collection tube; add 400 μL of Direct-zol to the centrifuge column. TM RNAPreWash (DRP) was performed at 12,000 rcf for 30 seconds, and the waste liquid in the collection tube was discarded. This step was repeated once. 700 μL of RNA Wash Buffer (RWB) was added to the centrifuge column, and centrifuged at 12,000 rcf for 1 minute. The waste liquid in the collection tube and the collection tube were discarded. After 5 minutes of air-free centrifugation, the liquid was shaken off, and 15 μL of DNase / RNase-Free Water was added to the centrifuge column to elute the RNA. The column was centrifuged at 15,000 rcf for 30 seconds to obtain RNA. Then, the RNA was reverse transcribed into a cDNA template using a reverse transcription kit (Takara) and stored at -20°C for later use.

[0088] Absolute quantification of target gene mRNA molecules in samples was performed using the QX200Auto DG Droplet Digital PCR (ddPCR) system. The reaction volume was 20 μL, consisting of ddPCR probe premix (dUTP-free), 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 (transcripts / μL) was quantitatively detected using a droplet reader (QX200 Droplet Reader). The mRNA expression level of the target gene in NSCLC CTCs captured in each 2 mL peripheral blood sample was calculated. Forty patients with benign pulmonary nodules and 30 patients with advanced NSCLC were used as the training set, and longitudinal monitoring of CTCs in 9 patients with advanced NSCLC was used as the validation set. The training set results are shown below. Figure 5A , Figure 5B As shown.

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

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

[0091] A companion diagnostic model for NSCLC CTC RNA was established using 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] By substituting the expression levels of modeling feature genes in the samples into the model, a composite heatmap corresponding to the Score of each subject sample in the training set can be obtained. Figure 7 The diagnostic effectiveness of the NSCLC diagnostic model was evaluated using ROC curves. The results showed that the model achieved an AUC value of 0.91, with a sensitivity of 93.3% and a specificity of 95%, and a diagnostic accuracy of 94.3%. Figure 8 ).

[0095] (3) Dynamically monitor the changes in the patient's scores before, during and after treatment, and assess and predict the disease status based on imaging results.

[0096] CTCs were detected in peripheral blood of patients before, during, and after treatment, and the results were analyzed using the model score status from step (2) to compare the trends before and after treatment. Figure 9 ).

[0097] Imaging results corresponding to the patient's treatment time points were collected and evaluated according to the RICIST (Response Evaluation Criteria in Solid Tumours) criteria, as follows:

[0098] 1) Complete remission (CR) means that all tumor target lesions have disappeared, no new lesions have appeared, and the remission is maintained for 4 weeks;

[0099] 2) Partial response (PR) is defined as a reduction of ≥30% in the sum of the largest diameters of the target tumor lesions, maintained for at least 4 weeks;

[0100] 3) Stable disease (SD) refers to a condition where the sum of the maximum diameters of the target tumor lesions does not shrink to the point of partial response (PR) or increase to the point of partial response (PD).

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

[0102] After treatment, the circulating tumor cell score (CTC Score) of the three patients decreased compared to before treatment, showing a downward trend or stabilizing. 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 marker CYFRA21-1 did not completely correlate with the disease status. Figures 10A-10C ).

[0103] like Figures 11A-11B As shown, the CTC scores of both patients increased during subsequent treatment, and PET-CT eventually confirmed that the disease had progressed and bone metastasized.

[0104] In summary, this invention, by mining biomarkers for non-small cell lung cancer (NSCLC), further constructs a companion diagnostic model for NSCLC based on multivariate logistic regression. This fully considers the contribution of intracellular biological information carried by tumor cells (CTCs) to tumor biology, resulting in higher accuracy for the companion diagnostic model. Dynamic monitoring on the validation set further confirms that this model can more directly and accurately reflect real-time changes in the disease status of cancer patients than traditional serum tumor markers. This demonstrates that the model constructed in this invention has the potential to serve as an adjunct tool for monitoring treatment response in advanced NSCLC.

[0105] The applicant declares that the detailed method of the present invention is illustrated by the above embodiments, but the present invention is not limited to the above detailed method, that is, it does not mean that the present invention must rely on the above detailed method to be implemented. Those skilled in the art should understand that any improvements to the present invention, equivalent substitutions of the 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. The application of a combination of secretory phosphoprotein 1, epithelial cell adhesion molecule, keratin 19, and matrix metallopeptidase 14 derived from peripheral blood circulating tumor cells, and / or a combination of nucleic acids encoding secretory phosphoprotein 1, epithelial cell adhesion molecule, keratin 19, and matrix metallopeptidase 14 derived from peripheral blood circulating tumor cells as biomarkers in the preparation of products for the detection of advanced non-small cell lung cancer; wherein the encoding nucleic acids include mRNA or cDNA.

2. The application according to claim 1, characterized in that, The product includes a kit comprising reagents for detecting the presence or expression of a combination of secreted phosphoprotein 1, epithelial cell adhesion molecule, keratin 19, and matrix metallopeptidase 14 derived from peripheral blood circulating tumor cells, and / or primers and / or probes for the combination of nucleic acids encoding secreted phosphoprotein 1, epithelial cell adhesion molecule, keratin 19, and matrix metallopeptidase 14 derived from peripheral blood circulating tumor cells.

3. The application according to claim 2, characterized in that, The kit also includes immunomagnetic beads modified with capture antibodies; The capture antibody includes any one or a combination of at least two of the following: antibodies against epithelial adhesion molecules, antibodies against N-cadherin, or antibodies against epidermal growth factor.

4. A device for companion diagnostics of advanced non-small cell lung cancer, characterized in that, The device includes an information acquisition module, a calculation module, and a diagnostic module; The information acquisition module is used to perform the following: The detection information of the subject is obtained, including the expression level information of the combination of secretory phosphoprotein 1, epithelial cell adhesion molecule, keratin 19 and matrix metallopeptidase 14 derived from peripheral blood circulating tumor cells as described in claim 1, and / or the expression level information of the combination of the nucleic acid encoding secretory phosphoprotein 1, the nucleic acid encoding epithelial cell adhesion molecule, the nucleic acid encoding keratin 19 and the nucleic acid encoding matrix metallopeptidase 14 derived from peripheral blood circulating tumor cells; The calculation module is used to perform the following: The obtained expression level information was substituted into the non-small cell lung cancer companion diagnostic model to calculate the non-small cell lung cancer circulating tumor cell score of the subject before and after treatment. The calculation formula is shown in Equation (1): NSCLC CTC Scores M =-20.327+1.077×SPP1+1.069×EPCAM+0.124×KRT19+0.727×MMP14 Equation (1); Among them, NSCLC CTC Scores M The score represents the circulating tumor cells in non-small cell lung cancer. SPP1 represents the expression level of secreted phosphoprotein 1 or its encoded nucleic acid, EPCAM represents the expression level of epithelial cell adhesion molecule or its encoded nucleic acid, KRT19 represents the expression level of keratin 19 or its encoded nucleic acid, and MMP14 represents the expression level of matrix metallopeptidase 14 or its encoded nucleic acid. The diagnostic module is used to perform the following: The judgment is made based on the calculated circulating tumor cell score of non-small cell lung cancer. The judgment criteria are (1) if the NSCLC CTC Scores after treatment M A score higher than or equal to the pre-treatment NSCLC CTC Scores M The score indicates the progression of the patient's disease or drug resistance; (2) if NSCLC CTC Scores after treatment M The score of NSCLC CTC Scores was lower than that before treatment. M The score indicates that the patient's condition has improved.

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