Application of plasma small extracellular vesicle miRNA markers in the preparation of a product for predicting the efficacy of combined immunotherapy and chemotherapy for lung cancer

Abstract

The present invention provides the use of plasma small extracellular vesicle miRNA markers in the preparation of a product for predicting the efficacy of combined immunotherapy and chemotherapy for lung cancer. The plasma small extracellular vesicle miRNA markers include: any one of miR-96-5p, miR-99b-3p, miR-100-5p, miR-193a-5p, miR-320d or miR-6815-5p, or a combination of at least two. The present invention models multiple sEVs miRNA combinations and identifies effective models containing two or three sEV miRNAs to determine the true responding population, showing high performance with an AUC greater than 0.9, achieving the potential benefit population for combined immunotherapy and chemotherapy of lung adenocarcinoma screened from the level of peripheral blood small extracellular vesicles.

Description

Technical Field

[0001] The present invention belongs to the field of molecular biological detection, and specifically relates to the application of plasma small extracellular vesicle miRNA markers in the preparation of a product for predicting the efficacy of combined immunotherapy and chemotherapy for lung cancer. Background Art

[0002] Lung cancer has become a major threat to human health. In recent years, immunotherapy combined with chemotherapy has become an important interventional therapy for lung cancer. Tumor immunotherapy using immune checkpoint inhibitors represents a major breakthrough in lung cancer treatment. Pembrolizumab (K drug), a PD-1 inhibitor, has been used in both first-line and second-line immunotherapy for lung cancer. Pembrolizumab combined with chemotherapy drugs has a synergistic effect, extending the survival of lung cancer patients. Immunotherapy combined with chemotherapy has become an important option for the clinical treatment of lung cancer patients.

[0003] Several common biomarkers used in immunotherapy research to predict efficacy include PD-L1 expression, tumor mutational burden (TMB), and microsatellite instability (MSI). High MSI (MSI-high, MSI-H) is an FDA-approved screening marker for immune checkpoint inhibitors (ICIs) in various tumor types, primarily colorectal cancer. However, its incidence in multiple studies of non-small cell lung cancer (NSCLC) is extremely low (<1%), making it difficult to predict immune-related efficacy in NSCLC. PD-L1 expression on tumor cells may influence the efficacy of immune checkpoint inhibitors in lung cancer patients. Pembrolizumab-based immunotherapy strategies for NSCLC have an objective response rate of 19.4% among all patients. Even among those with the highest PD-L1 expression (≥50%), the response rate is only 45.2%. TMB levels also have numerous drawbacks, including high cost, long detection time, low success rate, and unclear cutoff values. Furthermore, the relative merits of tissue tumor mutational burden (tTMB) and blood tumor mutational burden (bTMB) remain controversial. Due to unclear mechanisms of action and practical challenges, neither PD-L1 levels nor TMB have become widely used predictive markers in immunotherapy. Although an increasing number of patients are benefiting from immunotherapy combined with chemotherapy, effective biomarkers for evaluating clinical efficacy remain lacking. Exploring predictive biomarkers to accurately screen for responders to combined immunotherapy and chemotherapy is crucial, reducing unnecessary waste of medical resources, avoiding potential side effects in non-responders, and improving the efficacy of combined immunotherapy and chemotherapy.

[0004] At present, the imaging examinations (such as chest enhanced CT, chest X-ray, MRI and ultrasound and other auxiliary imaging examinations) and tumor marker tests (such as CEA, NSE, CYFRA21-1, proGRP and SCC-Ag, etc.) widely used in clinical practice have low sensitivity and specificity for lung cancer efficacy detection and are prone to false positives.

[0005] Small extracellular vesicles (sEVs) are biologically active vesicles secreted by multicellular bodies, also known as exosomes, with a diameter of generally 30-150 nm and a lipid bilayer membrane structure. The contents of sEVs, such as lipids, proteins and nucleic acids, play a vital role in intercellular communication. The stability and easy availability of sEVs make them potential biomarkers for precision medicine, especially early tumor screening, diagnosis and treatment. In addition, sEVs play an important role in tumor occurrence, metastasis, malignancy and immune escape. Studies have shown that tumor-delivered sEVs interact with stromal cells in the tumor microenvironment, and the information transmission between tumor cells, sEVs and the tumor microenvironment determines the development and malignancy of the tumor. Small RNAs in sEVs, including microRNAs (miRNAs), have been considered as potential biomarkers for various cancers. However, it is still unclear whether sEVs miRNAs can be used as biomarkers to predict the efficacy of combined immunotherapy and chemotherapy.

[0006] At present, there are no reports on the use of highly specific blood small extracellular vesicle miRNA biomarkers for predicting the efficacy of combined immunotherapy and chemotherapy in patients with lung adenocarcinoma; there are only a few studies on predicting the efficacy of combined immunotherapy and chemotherapy in patients with lung adenocarcinoma.

[0007] In CN116574807A, researchers conducted high-throughput sequencing and bioinformatics analysis of plasma extracellular vesicle long RNA (exLRs) in patients with advanced lung adenocarcinoma before and after immunotherapy combined with chemotherapy, and combined treatment response and survival analysis to identify and evaluate efficacy markers. They found that EV-derived CD160 can predict the efficacy of anti-PD-1 immunotherapy combined with chemotherapy in lung adenocarcinoma, and verified it at the RT-qPCR level. A prediction model based on peripheral blood EV-CD160 levels, NLR levels, and bone metastasis was established for predicting the efficacy of immunotherapy combined with chemotherapy in patients with lung adenocarcinoma. However, the markers they discovered had poor predictive performance, with the AUC obtained from ROC curve analysis being only 0.648, and the markers were low in abundance in blood exLRs.

[0008] In CN114220486B, researchers detected the expression of five immune cells and input the expression of the five immune cells into an efficacy prediction model pre-trained by a support vector machine to predict the efficacy of combined immunotherapy and chemotherapy in lung cancer patients. The AUC of the training group and validation group of the vector model were 0.886 and 0.874, respectively, with high predictive performance. However, their research mainly focused on the expression of immune cells and did not involve blood small extracellular vesicle miRNA biomarkers.

[0009] Combining immunotherapy with chemotherapy has become an important option for the clinical treatment of lung cancer, with an increasing number of patients benefiting from this treatment regimen. However, biomarkers that effectively identify true responders remain lacking. Therefore, identifying and screening novel sEVs (small interstitial cell) miRNA biomarkers has important application value in predicting the therapeutic efficacy of combined immunotherapy with chemotherapy for lung adenocarcinoma. Summary of the Invention

[0010] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide the application of plasma small extracellular vesicle miRNA markers in the preparation of a product for predicting the efficacy of combined immunotherapy and chemotherapy for lung cancer. The present invention analyzed the differentially expressed miRNAs (DEMs) in plasma small extracellular vesicles (sEVs) of patients with advanced or metastatic lung adenocarcinoma who received combined immunotherapy and chemotherapy by small RNA sequencing. A variety of sEVs miRNA combinations were modeled, and an effective model containing 2 or 3 sEVmiRNAs combinations was identified to determine the true response population, and showed a high predictive performance (AUC>0.9), realizing the screening of potential beneficiaries of lung adenocarcinoma combined immunotherapy and chemotherapy from the level of peripheral blood small extracellular vesicles.

[0011] In order to achieve the purpose of the invention, the present invention adopts the following technical solutions:

[0012] In the first aspect, the present invention provides the use of plasma small extracellular vesicle miRNA markers in the preparation of a product for predicting the efficacy of combined immunotherapy and chemotherapy for lung cancer, wherein the plasma small extracellular vesicle miRNA markers include: any one of miR-96-5p, miR-99b-3p, miR-100-5p, miR-193a-5p, miR-320d or miR-6815-5p, or a combination of at least two of them.

[0013] In the present invention, blood from patients with advanced or metastatic lung adenocarcinoma receiving immunotherapy combined with chemotherapy was used as research samples. The small extracellular vesicle (exosome) extraction reagent L3525 independently developed by Shanghai Silidi Biomedical Technology Co., Ltd. was used to extract blood exosomes. Next-generation sequencing technology (small RNA sequencing) was further used to detect the expression of small extracellular vesicle miRNAs in the blood of responders and non-responders to the combined treatment. In this way, highly specific small extracellular vesicle miRNA biomarkers that can be used to predict the efficacy of immunotherapy combined with chemotherapy were discovered and verified. The miRNA biomarkers can be used to establish a prediction model for the efficacy of immunotherapy combined with chemotherapy.

[0014] Preferably, the plasma small extracellular vesicle miRNA markers include: a combination of at least two of miR-96-5p, miR-99b-3p, miR-100-5p, miR-193a-5p, miR-320d or miR-6815-5p.

[0015] In the present invention, multiple sEVs miRNA combinations were modeled, and an effective model containing a combination of 2 or 3 sEVmiRNAs was identified to determine the true responding population, and showed high performance (AUC>0.9), realizing the screening of potential beneficiaries of lung adenocarcinoma immunotherapy combined with chemotherapy from the level of small extracellular vesicles in peripheral blood.

[0016] Preferably, the lung cancer immunotherapy combined with chemotherapy efficacy prediction product predicts that the subject is a responder to lung cancer immunotherapy combined with chemotherapy, or predicts that the subject is a non-responder to lung cancer immunotherapy combined with chemotherapy based on the expression level of the plasma small extracellular vesicle miRNA marker.

[0017] Preferably, compared with the non-responder group, the subject whose expression level of miR-96-5p or miR-6815-5p is increased; or the subject whose expression level of any one or a combination of at least two of miR-99b-3p, miR-100-5p, miR-193a-5p or miR-320d is decreased is a responder to combined immunotherapy and chemotherapy for lung cancer.

[0018] Preferably, the immunotherapy in the lung cancer combined with chemotherapy includes PD-1 inhibitor therapy, and the chemotherapy includes pemetrexed and / or platinum chemotherapy.

[0019] Preferably, the PD-1 inhibitor is selected from pembrolizumab.

[0020] Preferably, the platinum is selected from carboplatin.

[0021] Immunotherapy combined with chemotherapy has become an important choice for the clinical treatment of lung cancer patients. More and more patients have benefited from the immunotherapy combined with chemotherapy treatment regimen. However, biomarkers that effectively identify true responders are still lacking. In the present invention, based on the expression level of miRNA in small extracellular vesicles in the plasma of lung cancer patients, the samples are grouped according to the imaging evaluation results after immunotherapy combined with chemotherapy treatment, and statistical methods are used to explore plasma small extracellular vesicle miRNAs that can be used for the evaluation of the efficacy of immunotherapy combined with chemotherapy for lung cancer and the screening of benefited populations as biomarkers. The plasma small extracellular vesicle miRNA marker combination is obtained by screening after receiving the "pembrolizumab (K drug, PD-1 inhibitor) + pemetrexed + carboplatin" treatment regimen, which is a biomarker that effectively identifies true responders.

[0022] Preferably, the plasma small extracellular vesicle miRNA marker is a combination of miR-320d and miR-96-5p;

[0023] Or, the plasma small extracellular vesicle miRNA marker is a combination of miR-193a-5p and miR-99b-3p;

[0024] Or, the plasma small extracellular vesicle miRNA marker is a combination of miR-100-5p, miR-6815-5p and miR-96-5p;

[0025] Or, the plasma small extracellular vesicle miRNA marker is a combination of miR-100-5p, miR-6815-5p and miR-193a-5p;

[0026] Or, the plasma small extracellular vesicle miRNA marker is a combination of miR-96-5p, miR-193a-5p and miR-320d;

[0027] Alternatively, the plasma small extracellular vesicle miRNA marker is a combination of miR-99b-3p, miR-100-5p and miR-193a-5p.

[0028] In the present invention, the risk scoring models established using the six combinations described above all demonstrated good predictive performance and can be used to screen for potential beneficiaries of combined immunotherapy and chemotherapy for lung cancer. Among them, the risk scoring models established using miR-99b-3p + miR-100-5p + miR-193a-5p or miR-193a-5p + miR-99b-3p showed the best predictive performance and can be used to accurately screen for potential beneficiaries of combined immunotherapy and chemotherapy for lung cancer.

[0029] In a second aspect, the present invention provides a method for screening plasma small extracellular vesicle miRNA markers, the screening method comprising:

[0030] Sample grouping: Based on the imaging evaluation results after lung cancer immunotherapy combined with chemotherapy, the subjects who underwent lung cancer immunotherapy combined with chemotherapy were divided into response group and non-response group;

[0031] Screening of miRNA markers: Statistical methods were used to analyze miRNAs with significant expression differences between the response group and the non-response group before lung cancer immunotherapy combined with chemotherapy; miRNAs with an expression CPM greater than 32, a change of more than 1.5 times between the two groups, and a test result of P ≤ 0.05 were selected as candidate molecular markers.

[0032] Preferably, the immunotherapy in the lung cancer combined with chemotherapy includes PD-1 inhibitor therapy, and the chemotherapy includes pemetrexed and / or platinum chemotherapy.

[0033] Preferably, the PD-1 inhibitor is selected from pembrolizumab.

[0034] Preferably, the platinum is selected from carboplatin.

[0035] In the present invention, a plasma small extracellular vesicle small RNA sequencing strategy was used to discover for the first time six lung cancer plasma small extracellular vesicle miRNAs, including miR-96-5p, miR-99b-3p, miR-100-5p, miR-193a-5p, miR-320d, and miR-6815-5p. These miRNAs can be used as biomarkers to identify patients who may benefit from immunotherapy combined with chemotherapy for lung cancer. Among these biomarkers, patients with elevated expression levels of miR-96-5p and miR-6815-5p or decreased expression levels of miR-99b-3p, miR-100-5p, miR-193a-5p, and miR-320d may benefit from immunotherapy combined with chemotherapy.

[0036] In a third aspect, the present invention provides the use of a detection reagent for the expression level of plasma small extracellular vesicle miRNA markers in the preparation of a product for predicting the efficacy of combined immunotherapy and chemotherapy for lung cancer, wherein the detection reagent includes: a qRT-PCR reagent for detecting any one or a combination of at least two of miR-96-5p, miR-99b-3p, miR-100-5p, miR-193a-5p, miR-320d or miR-6815-5p.

[0037] Preferably, the reagents for qRT-PCR include primers and probes, and the primers include stem-loop reverse transcription primers, forward primers and reverse primers.

[0038] Preferably, the stem-loop reverse transcription primer comprises any one of SEQ ID NO: 1, 5, 8, 11, 14, 17 or 20, or a combination of at least two thereof.

[0039] Preferably, the forward primer comprises any one of SEQ ID NO: 2, 6, 9, 12, 15, 18 or 21, or a combination of at least two thereof.

[0040] Preferably, the reverse primer comprises SEQ ID NO: 4 and / or 23.

[0041] Preferably, the detection reagent further comprises: a reagent for extracting plasma small extracellular vesicles and / or plasma small extracellular vesicle miRNA.

[0042] In this study, plasma SVs were extracted using the L3525 small extracellular vesicle (exosome) isolation reagent, independently developed by Shanghai Silidi Biomedical Technology Co., Ltd. Other methods for extracting SVs from plasma include centrifugation (differential centrifugation, density gradient centrifugation), precipitation (PEG precipitation, organic solvent precipitation), particle size separation (ultrafiltration, size exclusion chromatography), immunoaffinity, microfluidics, and other commercial exosome isolation kits.

[0043] Preferably, the immunotherapy in the lung cancer combined with chemotherapy includes PD-1 inhibitor therapy, and the chemotherapy includes pemetrexed and / or platinum chemotherapy.

[0044] Preferably, the PD-1 inhibitor is selected from pembrolizumab.

[0045] Preferably, the platinum is selected from carboplatin.

[0046] In a fourth aspect, the present invention provides a lung cancer immunotherapy combined with chemotherapy efficacy prediction model, wherein the calculation formula of the prediction model includes:

[0047] Risk score = 1.3667 + 0.1051 × (miR-320d) – 0.1641 × (miR-96-5p);

[0048] or, risk score = -0.1994 + 0.1122 × (miR-193a-5p) + 0.0590 × (miR-99b-3p);

[0049] or, risk score = 2.2004 + 0.0573 × (miR-100-5p)–0.1826 × (miR-6815-5p)–0.1230 × (miR-96-5p);

[0050] or, risk score = 0.8594 + 0.0397 × (miR-100-5p) + 0.0966 × (miR-6815-5p) – 0.1917 × (miR-193a-5p);

[0051] or, risk score = 0.9107 + 0.0510 × (miR-193a-5p) + 0.0943 × (miR-320d) – 0.1584 × (miR-96-5p);

[0052] or, risk score = -0.6055 + 0.1197 × (miR-193a-5p) + 0.0311 × (miR-100-5p) + 0.0564 × (miR-99b-3p);

[0053] In the above calculation formula, miR-96-5p, miR-99b-3p, miR-100-5p, miR-193a-5p, miR-320d or miR-6815-5p refers to the expression level of the corresponding plasma small extracellular vesicle miRNA marker.

[0054] Preferably, the efficacy of combined immunotherapy and chemotherapy for lung cancer is judged according to the risk score value of the prediction model.

[0055] Preferably, the judgment standard is: the higher the risk score, the worse the therapeutic effect of the subject receiving lung cancer immunotherapy combined with chemotherapy.

[0056] In a fifth aspect, the present invention provides a method for constructing a model for predicting the efficacy of combined immunotherapy and chemotherapy for lung cancer, the method comprising:

[0057] Data acquisition: Obtain the expression levels of plasma small extracellular vesicle miRNA markers in the subjects before lung cancer immunotherapy combined with chemotherapy; the plasma small extracellular vesicle miRNA markers include: any one or a combination of at least two of miR-96-5p, miR-99b-3p, miR-100-5p, miR-193a-5p, miR-320d, or miR-6815-5p;

[0058] Model construction: Based on the expression levels of plasma small extracellular vesicle miRNA markers, an efficacy prediction model was established using any of the following analytical methods: least absolute shrinkage and selection operator, support vector machine, neural network, or random forest.

[0059] Preferably, in the model construction, the LASSO prediction models and risk scores of different miRNAs combinations are analyzed using the least absolute shrinkage and selection operator using the glmnet v4.0.2 software package, and the prediction models with AUC>0.9 are retained.

[0060] Preferably, the calculation formula of the prediction model includes:

[0061] Risk score = 1.3667 + 0.1051 × (miR-320d) – 0.1641 × (miR-96-5p);

[0062] or, risk score = -0.1994 + 0.1122 × (miR-193a-5p) + 0.0590 × (miR-99b-3p);

[0063] or, risk score = 2.2004 + 0.0573 × (miR-100-5p)–0.1826 × (miR-6815-5p)–0.1230 × (miR-96-5p);

[0064] or, risk score = 0.8594 + 0.0397 × (miR-100-5p) + 0.0966 × (miR-6815-5p) – 0.1917 × (miR-193a-5p);

[0065] or, risk score = 0.9107 + 0.0510 × (miR-193a-5p) + 0.0943 × (miR-320d) – 0.1584 × (miR-96-5p);

[0066] or, risk score = -0.6055 + 0.1197 × (miR-193a-5p) + 0.0311 × (miR-100-5p) + 0.0564 × (miR-99b-3p);

[0067] In the above calculation formula, miR-96-5p, miR-99b-3p, miR-100-5p, miR-193a-5p, miR-320d or miR-6815-5p refers to the expression level of the corresponding plasma small extracellular vesicle miRNA marker.

[0068] In the present invention, the risk scoring models based on the six miRNA combinations all demonstrated good predictive performance and can be used to screen for patients who may benefit from combined immunotherapy and chemotherapy for lung cancer. Among them, the risk scoring models constructed using the combination of miR-99b-3p, miR-100-5p, and miR-193a-5p, and the combination of miR-193a-5p and miR-99b-3p, demonstrated the best predictive performance and can be used to accurately screen for patients who may benefit from combined immunotherapy and chemotherapy for lung cancer.

[0069] Preferably, in constructing the model, the efficacy of combined immunotherapy and chemotherapy for lung cancer is judged based on the risk score value of the model.

[0070] Preferably, the judgment standard is: the higher the risk score, the worse the therapeutic effect of the subject receiving lung cancer immunotherapy combined with chemotherapy.

[0071] The present invention uses one of the contents of small extracellular vesicles in the blood, miRNA, to establish a biomarker model to identify people who benefit from the immunotherapy combined with chemotherapy treatment plan for lung cancer. In addition, there are many other contents of small extracellular vesicles, such as proteins, lipids, small molecule metabolites, lncRNA, circRNA, mRNA and piRNA, etc. These small extracellular vesicle contents in the blood may also be used to construct a biomarker model to achieve similar effects as miRNA. In addition, various components in the patient's blood, such as CTCs (Circulating tumor cells), ctDNA (Circulating tumor DNA), extracellular free nucleic acids (cfRNA and cfDNA) and protein biomarkers can be used as biomarkers to predict the efficacy of immunotherapy combined with chemotherapy for lung cancer.

[0072] Compared with the prior art, the present invention has the following beneficial effects:

[0073] Currently, widely used clinical imaging tests (such as chest contrast-enhanced CT, chest X-ray, MRI, and ultrasound, among other auxiliary imaging tests) and tumor marker tests (such as CEA, NSE, CYFRA21-1, proGRP, and SCC-Ag) have low sensitivity and specificity for lung cancer efficacy testing and cannot be directly used to predict the efficacy of immunotherapy combined with chemotherapy. There are no reports on highly specific blood-based small extracellular vesicle miRNA biomarkers for predicting the efficacy of immunotherapy combined with chemotherapy in patients with lung adenocarcinoma. Studies on predicting the efficacy of immunotherapy combined with chemotherapy in patients with lung adenocarcinoma have the following characteristics: a. The number of studies focusing on predicting the efficacy of immunotherapy combined with chemotherapy in patients with lung adenocarcinoma is relatively small; b. The number of studies based on second-generation sequencing platforms is relatively small; c. There are relatively few studies on small extracellular vesicle contents as biomarkers for predicting the efficacy of immunotherapy combined with chemotherapy in patients with lung adenocarcinoma; d. There are no reports on studies proposing small extracellular vesicle miRNAs as highly specific biomarkers to screen patients who benefit from immunotherapy combined with chemotherapy.

[0074] The present invention analyzed differentially expressed miRNAs (DEMs) in sEVs of patients with advanced or metastatic lung adenocarcinoma receiving immunotherapy combined with chemotherapy through small RNA sequencing. Multiple sEVs-miRNA combinations were modeled, and for the first time, an effective model of sEVs-miRNA combinations was proposed and identified to identify the true responder population. This enabled the screening of potential beneficiaries of lung adenocarcinoma immunotherapy combined with chemotherapy at the level of small extracellular vesicles in peripheral blood, avoiding potential side effects in non-responders, reducing additional patient suffering, and wasting clinical medical resources. The advantages of the present invention specifically include the following six points:

[0075] (1) The present invention adopts the plasma small extracellular vesicle small RNA sequencing strategy and discovers for the first time 6 lung cancer plasma small extracellular vesicle miRNAs: miR-96-5p, miR-99b-3p, miR-100-5p, miR-193a-5p, miR-320d and miR-6815-5p, which can be used as biomarkers to identify people who benefit from the combined immunotherapy and chemotherapy treatment regimen for lung cancer.

[0076] (2) The present invention found that compared with the non-responder group, patients with increased expression levels of miR-96-5p or miR-6815-5p in (1) or decreased expression levels of any one or a combination of at least two of miR-99b-3p, miR-100-5p, miR-193a-5p or miR-320d can benefit from the immunotherapy combined with chemotherapy regimen.

[0077] (3) Based on the six lung cancer plasma small extracellular vesicle miRNAs discovered in (1), the present invention constructed six risk scoring models containing combinations of two or three miRNAs: miR-193a-5p+miR-99b-3p, miR-320d+miR-96-5p, miR-100-5p+miR-6815-5p+miR-193a-5p, miR-96-5p+miR-193a-5p+miR-320d, miR-100-5p+miR-6815-5p+miR-96-5p, miR-99b-3p+miR-100-5p+miR-193a-5p. The above six risk scoring models all showed good predictive performance and can be used to screen potential beneficiaries of combined immunotherapy and chemotherapy for lung cancer.

[0078] (4) The present invention further detected the expression levels of the six miRNAs discovered in (1) in the plasma small extracellular vesicles of lung cancer patients using the qRT-PCR method, further confirming the reliability of the risk scoring model, providing a solid foundation for the application and development of the model, and having great market potential.

[0079] (5) Based on the qRT-PCR method, the present invention further verified that two risk scoring models in (3), miR-99b-3p+miR-100-5p+miR-193a-5p and miR-193a-5p+miR-99b-3p, had the best prediction performance and could be used to accurately screen potential beneficiaries of combined immunotherapy and chemotherapy for lung cancer.

[0080] (6) The present invention uses liquid biopsy identification technology, which can be combined with imaging examinations to improve the specificity of identifying people who respond to immunotherapy combined with chemotherapy treatment, reduce false positives, avoid potential side effects of non-responders, and reduce additional pain for patients and waste of clinical medical resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 This is the HE and IHC pathological diagnosis results of a patient with lung adenocarcinoma before combined immunotherapy and chemotherapy.

[0082] Figure 2 This is the imaging test result of a representative lung cancer patient who achieved partial remission after immunotherapy combined with chemotherapy. Baseline represents the CT image before treatment, and C2 represents the CT image after treatment.

[0083] Figure 3 This is the TEM detection result of plasma small extracellular vesicles.

[0084] Figure 4 This is the result of NTA detection of small extracellular vesicles in plasma.

[0085] Figure 5 Figure 2 is the ROC curve of two combined models containing two plasma small extracellular vesicle miRNAs.

[0086] Figure 6 Figure 2 is the ROC curve of four combined models containing three plasma small extracellular vesicle miRNAs.

[0087] Figure 7 Figure 3 is the ROC curve of the plasma small extracellular vesicle miRNAs combination model based on qRT-PCR. DETAILED DESCRIPTION

[0088] The technical solution of the present invention is further described below by way of specific embodiments. It should be understood by those skilled in the art that the embodiments are merely to help understand the present invention and should not be regarded as specific limitations of the present invention.

[0089] If no specific techniques or conditions are specified in the examples, the experiments were carried out according to the techniques or conditions described in the literature in the field or according to the product instructions. If no manufacturer is specified for the reagents or instruments used, they are all conventional products that can be purchased through regular channels.

[0090] Example 1

[0091] 1. Study cohort and clinical information

[0092] This study included 29 patients diagnosed with lung cancer using existing clinical testing methods. Blood samples were collected from each patient before drug treatment for plasma small extracellular vesicle extraction and subsequent analysis. HE and IHC pathological diagnosis results were obtained for all 29 patients before immunotherapy combined with chemotherapy. The HE and IHC test results of representative patients are shown in Figure 1 .

[0093] After one month of treatment with the "pembrolizumab (K drug) + pemetrexed + carboplatin" regimen, 14 patients had partial remission (PR), 10 patients had stable disease (SD), and 5 patients had progressive disease (PD). The imaging test results of representative lung cancer patients with partial remission after immunotherapy combined with chemotherapy are shown in Figure 2 , where Baseline represents the CT image before treatment, and C2 represents the CT image after treatment.

[0094] 2. Extraction and Characterization of Plasma Small Extracellular Vesicles

[0095] 2.1 Plasma Collection and Small Extracellular Vesicle Extraction

[0096] Blood samples were collected from patients before immunotherapy and chemotherapy and stored in 10 mL vacutainer tubes (REF367525, BD, USA). The tubes were gently inverted several times and then placed upright. Samples were centrifuged at 1600 g for 10 min at 4°C. After centrifugation, the hemolysis grade of the samples was determined according to a standard, and samples with a grade of less than 4 were used for subsequent studies. The supernatant was transferred to a 1.5 mL EP tube and centrifuged at 16,000 g for 15 min at 4°C to remove residual cell debris. The supernatant was then aliquoted into 1.5 mL EP tubes and stored at −80°C until use.

[0097] Frozen plasma samples were thawed in a 37°C water bath and centrifuged at 12,000 g for 10 min at 4°C. The supernatant was filtered sequentially through a 0.45 μm filter column (CLS8163-100EA, Corning, USA) and then a 0.22 μm filter column (CLS8161-100EA, Corning, USA). The supernatant was centrifuged at 12,000 g for 5 min at 4°C and the filtrate was collected into a 2 mL EP tube. The volume of the filtrate was measured, and 1 / 4 volume of L-type exosome precipitation reagent (L3525, 3Dmed, Shanghai) was added. After thorough mixing, the tube was incubated at 4°C for 30 min and centrifuged at 4,700 g for 30 min at 4°C. The supernatant was discarded, and the small extracellular vesicles were resuspended in 200 μL of PBS.

[0098] 2.2 Characterization of plasma small extracellular vesicles

[0099] TEM detection: resuspend the small extracellular vesicles with PBS and fix them with 4% paraformaldehyde. Take the fixed small extracellular vesicles and drop them on the carbon-coated copper grid. After incubation at room temperature for 5 minutes, rinse with PBS twice, rinse once with PBS containing glycine (50mM), incubate with PBS containing 0.5% BSA for 10 minutes, and finally negatively stain the copper grid with 2% uranyl acetate for 10 minutes. Observe and photograph using a transmission electron microscope (H-7650, Hitachi, Japan). The results show that the small extracellular vesicles have a typical "horseshoe-shaped" morphology (see Figure 3 ).

[0100] NTA assay: First, plasma small extracellular vesicles were diluted with PBS to 1×10 7 -1×10 9 / mL, pipette and mix. Subsequently, turn on the NTA instrument (NanoSight NS300, Malvern, UK) and inject the sample into the sample chamber. Use the 488nm excitation module, set the camera lens parameters, select the shutter value of 890, the gain value of 146, and the detection threshold of 7. At least 200 complete tracks were analyzed and obtained for each video. Finally, the nanoparticle tracking data of plasma small extracellular vesicles were analyzed using NTA version 2.3 analysis software. The results of the particle size distribution of small extracellular vesicles detected by NTA showed that the main peak of the small extracellular vesicle particle size was 106nm, which is consistent with the particle size distribution of small extracellular vesicles (see Figure 4 ).

[0101] 3. Molecular marker discovery

[0102] 3.1 Extraction of plasma small extracellular vesicle miRNA

[0103] Total RNA was extracted from small extracellular vesicles using the miRNeasy Serum / Plasma Kit (217184, QIAGEN, Shanghai) according to the product instructions. RNA was eluted with 15 μL of nuclease-free water. The concentration and fragment distribution of miRNAs were determined using an Agilent 2100 Bioanalyzer and the accompanying small RNA analysis kit (5067-1548, Agilent).

[0104] 3.2 Construction of plasma small extracellular vesicle miRNA library

[0105] miRNA libraries were prepared using the NEBNext Multiplex Small RNA Library Prep Set for Illumina (E7300L, NEB, USA) according to the product instructions. Six μL of each RNA sample was loaded, followed by ligation of a 3' end adapter, hybridization of a reverse transcription primer, ligation of a 5' end adapter, reverse transcription, and 18 cycles of PCR amplification. PCR-enriched products were purified using the NucleoSpin Geland PCR Clean-up Kit (740609.250, MN, Germany), and the library DNA was eluted with 30 μL of nuclease-free water. DNA concentration was quantified using an Invitrogen Qubit 4 fluorometer and the accompanying reagent Qubit dsDNA HS Assay Kit (Q32854, Thermofisher, USA). The distribution of library DNA fragments was detected using an Agilent 2100 Bioanalyzer using the accompanying chip and reagents Agilent High Sensitivity DNA Kit & Reagents (5067-4626, Agilent, USA). Sequencing was performed using the Illumina NovaSeq platform, with a sequencing strategy of PE150 and a sequencing data volume of 6G for each library.

[0106] 3.3 Sequencing data analysis process

[0107] Using small RNA sequencing technology, we determined the expression levels of miRNAs in small extracellular vesicles (SECs) in the plasma of lung cancer patients. The analysis process for sequencing data is as follows:

[0108] 1) Sequencing data alignment: After removing the sequencing adapters of the small RNA sequencing data, the sequencing data were aligned to the human reference genome hg19 (genome download link: http: / / hgdownload.soe.ucsc.edu / goldenPath / hg19 / bigZips / ) using BWA software (version: 0.7.12-r1039), and the number of reads aligned to the miRNA was counted.

[0109] 2) miRNA annotation: miRNAs were annotated using the Gencode v25 and miRBase v21 databases, and those annotated as known mature miRNAs were retained for subsequent analysis.

[0110] 3) miRNA filtering: Mature miRNAs with a length of 30 nt or less and covered by at least 2 reads per sample were retained for subsequent analysis.

[0111] 4) Normalization of miRNA expression: The trimmed mean of M-values ​​(TMM) method of the edgeR v3.26.8 analysis package in R language and the voom method of the limma v3.40.6 analysis package were used to normalize the miRNA expression of the samples.

[0112] 3.4 Screening of plasma small extracellular vesicle miRNAs

[0113] Based on the expression of miRNA in plasma small extracellular vesicles of lung cancer patients, samples were grouped according to the imaging evaluation results after immunotherapy combined with chemotherapy, and statistical methods were used to discover plasma small extracellular vesicle miRNA biomarkers that can be used to evaluate the efficacy of immunotherapy combined with chemotherapy for lung cancer and screen the beneficiary population. The process is as follows:

[0114] 1) Sample grouping: Based on the imaging evaluation results after immunotherapy combined with chemotherapy, patients were divided into two groups: response group (PR+SD) and non-response group (PD).

[0115] 2) Candidate molecular markers: The limma-voom method in the R language limma analysis package was used to analyze miRNAs with significantly different expression levels between the PR and PD groups. MiRNAs with an expression level CPM (Counts Per Million) greater than 32, a difference of more than 1.5-fold between the two groups, and a test result P ≤ 0.05 were selected as candidate molecular markers.

[0116] Statistical methods were used to identify six miRNA biomarkers for evaluating the efficacy of combined immunotherapy and chemotherapy for lung cancer and screening for patients who could benefit. These miRNAs included miR-96-5p, miR-99b-3p, miR-100-5p, miR-193a-5p, miR-320d, and miR-6815-5p. Compared to the non-responder group, patients with elevated miR-96-5p and miR-6815-5p expression or decreased miR-99b-3p, miR-100-5p, miR-193a-5p, and miR-320d expression were shown to benefit from combined immunotherapy and chemotherapy.

[0117] miR-96-5p (SEQ ID NO:24): UUUGGCACUAGCACAUUUUUGCU.

[0118] miR-99b-3p (SEQ ID NO:25): CAAGCUCGUGUCUGUGGGCG.

[0119] miR-100-5p (SEQ ID NO:26): AACCCGUAGAUCCGAACUUGUG.

[0120] miR-193a-5p (SEQ ID NO:27): UGGGUCUUUGCGGGCGAGAUGA.

[0121] miR-320d (SEQ ID NO:28): AAAAGCUGGGUUGAGAGGA.

[0122] miR-6815-5p (SEQ ID NO:29): UAGGGUGGCGCCGGAGGAGUCAUU.

[0123] 4. Risk scoring model construction

[0124] Candidate miRNAs significantly upregulated or downregulated in the PR sample group were analyzed using the least absolute shrinkage and selection operator (LASSO) with the glmnet v4.0.2 software package to analyze the LASSO prediction models and risk scores for different miRNA combinations. Models with an AUC greater than 0.9 were retained. Based on the six lung cancer plasma small extracellular vesicle miRNAs discovered above, six risk score models were constructed, each containing two or three miRNA combinations, to identify responders to immunotherapy combined with chemotherapy.

[0125] Among the six risk scoring models, two included combinations of two plasma small extracellular vesicle miRNAs (ROC curves are shown in Figure 2). Figure 5 ): miR-193a-5p+miR-99b-3p and miR-320d+miR-96-5p; there were 4 combinations containing 3 plasma small extracellular vesicle miRNAs (ROC curve see Figure 6 ) : miR-100-5p + miR-6815-5p + miR-193a-5p, miR-96-5p + miR-193a-5p + miR-320d, miR-100-5p + miR-6815-5p + miR-96-5p, and miR-99b-3p + miR-100-5p + miR-193a-5p. The calculation formulas for the six risk score models are shown in Table 1. The model's risk score cutoff value is the median risk score. A higher risk score indicates a worse response to combined immunotherapy and chemotherapy in lung cancer patients. All six risk score models demonstrated good predictive performance (AUC > 0.9). The specificity, sensitivity, and AUC values ​​of the six models are shown in Table 2.

[0126] Table 1

[0127]

[0128] Table 2

[0129] miRNA Specificity Sensitivity AUC miR-320d+miR-96-5p 79.20％ 100.00％ 92.50％ miR-193a-5p+miR-99b-3p 87.50％ 100.00％ 92.50％ miR-100-5p+miR-6815-5p+miR-96-5p 87.50％ 100.00％ 97.50％ miR-100-5p+miR-6815-5p+miR-193a-5p 91.70％ 100.00％ 97.50％ miR-96-5p+miR-193a-5p+miR-320d 83.30％ 100.00％ 95.00％ miR-99b-3p+miR-100-5p+miR-193a-5p 91.70％ 100.00％ 94.20％

[0130] 5. Consistency evaluation of qRT-PCR detection and high-throughput sequencing data

[0131] To further evaluate whether the constructed risk score model can be validated by other detection technologies, this example used qRT-PCR technology (TaqMan probe method) to detect the expression levels of 6 plasma small extracellular vesicle miRNAs in the response group (13 patients) and the non-response group (5 patients). First, HiScript III Reverse Transcriptase (Vazyme, R302, Nanjing) was used to synthesize the first-strand cDNA. The 20 μL reaction system consisted of: 4 μL RNA, 8.5 μL nuclease-free water, 4 μL 5× HiScript III buffer, 1 μL 10 mM dNTP, 0.5 μL HiScript III reverse transcriptase, 1 μL ribonuclease inhibitor, and 1 μL miRNA-specific stem-loop reverse transcription primer. The cDNA synthesis reaction program was 12°C for 5 minutes; 42°C for 15 minutes; 85°C for 5 minutes; and 4°C hold.

[0132] Subsequently, qPCR was performed using Taq HSDNA polymerase (Vazyme, P132, Nanjing). The 25 μL reaction system consisted of: 2 μL cDNA, 8.75 μL nuclease-free water, 9 μL PCR buffer (company-prepared), 1.5 μL Taq HSDNA polymerase, 0.75 μL 10 μM probe, 1.25 μL 30 μM forward primer, and 1.75 μL 10 μM reverse primer. The qPCR reaction program was 95 ° C, 5 min; 95 ° C, 10 s, 60 ° C, 35 s, 45 cycles. The experiment used miR-451 as an internal reference. Each experimental reaction was repeated 3 wells. Fluorescence quantification was performed using an ABI7500 PCR instrument, and finally 2 (-ΔΔCT) Methods The relative expression levels of miRNAs were analyzed. The primer sequences used for qRT-PCR detection are shown in Table 3.

[0133] Table 3

[0134]

[0135] It was found that the ROC curve of the miRNA scoring model obtained by PCR detection was highly consistent with the ROC curve obtained by second-generation sequencing data. Two of the six risk scoring models: miR-99b-3p+miR-100-5p+miR-193a-5p and miR-193a-5p+miR-99b-3p, had the best prediction performance. The risk scoring model miR-99b-3p+miR-100-5p+miR-193a-5p had a specificity of 100%, a sensitivity of 80%, and an AUC value of 0.94. The risk scoring model miR-193a-5p+miR-99b-3p had a specificity of 100%, a sensitivity of 80%, and an AUC value of 0.95. Figure 7 is the ROC curve of the above two risk scoring models.

[0136] In summary, this study used small RNA sequencing to analyze differentially expressed miRNAs (DEMs) in plasma small extracellular vesicles (sEVs) from patients with advanced or metastatic lung adenocarcinoma receiving combined immunotherapy and chemotherapy. Multiple sEV-miRNA combinations were modeled, and effective models containing combinations of two or three sEV miRNAs were identified to identify true responders, demonstrating high performance (AUC>0.9). This enabled the identification of potential beneficiaries of combined immunotherapy and chemotherapy for lung adenocarcinoma at the level of peripheral blood small extracellular vesicles.

[0137] The applicant declares that the above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention fall within the scope of protection and disclosure of the present invention.

Claims

1. The use of a detection reagent for the expression level of plasma small extracellular vesicle miRNA markers in the preparation of a product for predicting the efficacy of combined immunotherapy and chemotherapy for lung adenocarcinoma, characterized in that: The plasma small extracellular vesicle miRNA marker is a combination of miR-99b-3p and miR-193a-5p, or a combination of miR-99b-3p, miR-100-5p and miR-193a-5p. The immunotherapy in the lung adenocarcinoma combined immunotherapy and chemotherapy is PD-1 inhibitor treatment, and the chemotherapy treatment is pemetrexed and platinum chemotherapy; the PD-1 inhibitor is pembrolizumab; and the platinum is carboplatin.

2. The use according to claim 1, characterized in that The lung adenocarcinoma immunotherapy combined with chemotherapy efficacy prediction product predicts that the subject is a responder to lung adenocarcinoma immunotherapy combined with chemotherapy, or predicts that the subject is a non-responder to lung adenocarcinoma immunotherapy combined with chemotherapy based on the expression level of the plasma small extracellular vesicle miRNA marker; Compared with the non-response group, the subjects whose combined expression levels of miR-99b-3p, miR-100-5p and miR-193a-5p are reduced are responders to the combined immunotherapy and chemotherapy of lung adenocarcinoma; or, the subjects whose combined expression levels of miR-99b-3p and miR-193a-5p are reduced are responders to the combined immunotherapy and chemotherapy of lung adenocarcinoma.

3. The use of a detection reagent for the expression level of plasma small extracellular vesicle miRNA markers in the preparation of a product for predicting the efficacy of combined immunotherapy and chemotherapy for lung adenocarcinoma, characterized in that: The detection reagents include: reagents for qRT-PCR to detect miR-99b-3p and miR-193a-5p, or reagents for qRT-PCR to detect miR-99b-3p, miR-100-5p and miR-193a-5p; the immunotherapy in the lung adenocarcinoma combined immunotherapy and chemotherapy is PD-1 inhibitor treatment, and the chemotherapy is pemetrexed and platinum chemotherapy; the PD-1 inhibitor is pembrolizumab; and the platinum is carboplatin.

4. The use according to claim 3, characterized in that The detection reagent also includes: a reagent for extracting plasma small extracellular vesicles and / or plasma small extracellular vesicle miRNA.

5. A method for constructing a model for predicting the efficacy of combined immunotherapy and chemotherapy for lung adenocarcinoma for purposes other than disease diagnosis or treatment, characterized in that: The method comprises: Data acquisition: The expression levels of plasma small extracellular vesicle miRNA markers of the subjects before immunotherapy combined with chemotherapy for lung adenocarcinoma are obtained; the plasma small extracellular vesicle miRNA markers are a combination of miR-99b-3p and miR-193a-5p, or a combination of miR-99b-3p, miR-100-5p and miR-193a-5p; the immunotherapy in the immunotherapy combined with chemotherapy for lung adenocarcinoma is PD-1 inhibitor therapy, and the chemotherapy is pemetrexed and platinum chemotherapy; the PD-1 inhibitor is pembrolizumab; and the platinum is carboplatin; Model construction: Based on the expression levels of plasma small extracellular vesicle miRNA markers, an efficacy prediction model was established using any of the following analytical methods: least absolute shrinkage and selection operator, support vector machine, neural network, or random forest.

6. The method for constructing a lung adenocarcinoma immunotherapy combined with chemotherapy efficacy prediction model according to claim 5, characterized in that: In the model construction, the LASSO prediction models and their risk scores of different miRNAs combinations were analyzed using the least absolute shrinkage and selection operators using the glmnet v4.0.2 software package, and the prediction models with AUC>0.9 were retained; The calculation formula of the prediction model includes: Risk score = -0.1994 + 0.1122 × (miR-193a-5p) + 0.0590 × (miR-99b-3p); or, risk score = −0.6055 + 0.1197 × (miR-193a-5p) + 0.0311 × (miR-100-5p) +0.0564 × (miR-99b-3p); In the above calculation formula, miR-99b-3p, miR-100-5p, and miR-193a-5p refer to the expression levels of the corresponding plasma small extracellular vesicle miRNA markers; Judging the efficacy of combined immunotherapy and chemotherapy for lung adenocarcinoma according to the risk score value of the model; The judgment standard is: the higher the risk score, the worse the efficacy of the subject's combined immunotherapy and chemotherapy for lung adenocarcinoma.

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