Detection kit and method for lung cancer diagnosis through exosomal miRNA biomarkers

Abstract

Provided herein is a detection kit for diagnosing lung cancer status in a subject, comprising a detection reagent for detecting the level of a miRNA biomarker in a biological sample from the subject, wherein the miRNA biomarker is selected from miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p and let-7g-5p and any combination thereof. Also provided herein is a method for diagnosing lung cancer status in a subject. The detection kit and method provided herein can be effectively used for diagnosing lung cancer status, have good clinical application value, and provide new ideas and methods for the screening and diagnosis of lung cancer.

Description

Technical Field

[0001] This article relates to exosomal miRNA biomarkers and detection kits for diagnosing human lung cancer. This article also relates to methods for identifying lung cancer status. Background Art

[0002] Lung cancer is the most common malignant tumor in the world, and also the malignant tumor with the highest morbidity and mortality rate, posing a serious threat to human life and health.

[0003] The main reason for the high mortality rate of lung cancer is that most patients are diagnosed in the late stages of the disease. Early detection and appropriate treatment can significantly reduce the mortality rate of lung cancer. For all stages of lung cancer, the five-year survival rate is only 15-19%. However, when lung cancer is diagnosed early, the five-year survival rate can increase to 50-60%, especially for stage I patients, where the survival rate can reach 81% to 85%. Therefore, improving the efficiency of early diagnosis of lung cancer in asymptomatic patients can effectively reduce the mortality rate of lung cancer and significantly improve the prognosis of lung cancer patients.

[0004] Currently, the diagnostic methods for lung cancer mainly include sputum cytology, imaging, and bronchoscopic biopsy. Studies have shown that the use of chest X-rays and sputum cytology as screening techniques does not reduce the mortality rate of lung cancer. In high-risk smokers, low-dose spiral computed tomography (CT) screening has been shown to be more sensitive than chest X-rays and can be used for early diagnosis of lung cancer and reduce lung cancer mortality. However, due to the poor specificity of CT screening, the downstream diagnostic costs are high and its diagnostic accuracy is limited. Therefore, there is an urgent need for other non-invasive methods to further improve lung cancer screening and reduce mortality.

[0005] MiRNAs are endogenous, small, noncoding RNAs (approximately 22 to 25 nucleotides in length) that regulate the expression and function of oncogenes or tumor suppressor genes at the transcriptional level by downregulating or inhibiting target mRNAs. Numerous studies have demonstrated that miRNAs are specifically expressed in different tumors and can distinguish between normal and tumor tissues. Furthermore, studies have confirmed that circulating miRNAs can serve as diagnostic markers for various diseases, including cancer. However, as diagnostic markers, circulating miRNAs are easily affected by miRNAs released by damaged cells, presenting certain limitations.

[0006] Exosomes are microvesicles with a diameter of 30-120 nm, secreted by various cells. They are widely present in human body fluids, including saliva, blood, urine, and breast milk. They contain a variety of active molecules, including DNA, RNA, and proteins, that regulate the homeostasis of proteins and lipids within cells, playing a crucial role in numerous physiological processes, including cellular communication, immune responses, and material exchange. Numerous studies have shown that exosomes can protect circulating miRNAs from degradation by endogenous RNases, thereby enhancing their stability in the circulation. Furthermore, exosomes are believed to serve as a means by which tumor cells deliver miRNAs into the circulation, indirectly reflecting changes in miRNA expression in tumor cells. Recent studies have confirmed that miRNAs in exosomes are closely associated with the development and metastasis of cancer. Exosomal miRNAs are often tumor-specific and have the potential to serve as effective biomarkers for cancer screening, diagnosis, and monitoring.

[0007] Currently, commonly used methods for quantitative miRNA detection include quantitative real-time PCR, deep sequencing, and microarrays. Fluorescence quantitative PCR methods primarily include the SYBR Green dye method and the TaqMan probe method. The former requires adjustment of primer concentration to improve primer amplification efficiency and minimize primer dimers and nonspecific amplification. The probe method requires the design of a fluorescent probe, which can be positioned in three ways: completely identical to the miRNA sequence, at the intersection of the miRNA and the RT primer, or completely on the RT primer. The specific placement of the probe can be determined based on individual experimental conditions. Microarrays are a relatively rapid method for detecting miRNA expression. Microarray analysis also relies on the principle of hybridization, employing a high density of fluorescently labeled probes that hybridize to RNA samples. Fluorescence scanning generates expression profiles, which are then analyzed using corresponding software. By measuring miRNA expression levels during specific processes, the regulatory mechanisms of miRNA expression and the expression of genes regulated by miRNAs can be analyzed. Despite this, effective methods for detecting cancer-related miRNAs and processing the detection results are still lacking. Summary of the Invention

[0008] In one aspect, provided herein is a detection kit for diagnosing lung cancer status in a subject, comprising a detection reagent for detecting the level of a miRNA biomarker in a biological sample from the subject, wherein the miRNA biomarker is selected from miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p and let-7g-5p and any combination thereof.

[0009] In some embodiments, the biomarker is selected from two or more of miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p, and let-7g-5p.

[0010] In some embodiments, the biomarker is selected from 5 or more of miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p, and let-7g-5p.

[0011] In some embodiments, the miRNA biomarkers include miR-126-3p, miR-140-5p, miR-17-5p, miR-19b-3p, and miR-22-3p.

[0012] In some embodiments, the miRNA biomarker is miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p, and let-7g-5p.

[0013] In some embodiments, the lung cancer status includes lung cancer susceptibility and / or the presence, progression, subtype, and / or stage of lung cancer.

[0014] In some embodiments, the lung cancer status is stage I or stage II lung cancer, and the miRNA biomarker is miR-140-5p, miR-19b-3p, and / or miR-22-3p.

[0015] In some embodiments, the lung cancer state is adenocarcinoma and the miRNA biomarker is miR-126-3p, miR-140-5p, miR-19b-3p, miR-22-3p, and / or miR-486-5p.

[0016] In some embodiments, the lung cancer state is squamous cell carcinoma and the miRNA biomarker is miR-126-3p, miR-140-5p, miR-19b-3p, miR-22-3p and / or miR-221-5p.

[0017] In some embodiments, the lung cancer state is large cell lung cancer and the miRNA biomarker is miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p and / or miR-486-5p.

[0018] In some embodiments, the lung cancer state is small cell lung cancer and the miRNA biomarker is miR-126-3p, miR-140-5p, miR-17-5p, miR-22-3p, miR-221-5p and / or miR-486-5p.

[0019] In some embodiments, the detection reagents for detecting the level of miRNA biomarkers include reverse transcription primers, PCR amplification primer pairs and / or Taqman probes.

[0020] In some embodiments, the detection reagents for detecting the level of miR-126-3p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 12; a PCR amplification primer pair including the sequence shown in SEQ ID NO: 23 and 34; and / or a Taqman probe including the sequence shown in SEQ ID NO: 35; the detection reagents for detecting the level of miR-140-5p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 13; a PCR amplification primer pair including the sequence shown in SEQ ID NO: 24 and 34; and / or a Taqman probe including the sequence shown in SEQ ID NO: 36; the detection reagents for detecting the level of miR-17-5p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 14; a PCR amplification primer pair including the sequence shown in SEQ ID NO: 25 and 34; and / or a Taqman probe including the sequence shown in SEQ ID NO: 37; the detection reagents for detecting the level of miR-181a-5p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 15; a PCR amplification primer pair including the sequence shown in SEQ ID NO: 3 NO: 26 and 34; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 38; a detection reagent for detecting the level of miR-19b-3p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 16; a PCR amplification primer pair comprising the sequence shown in SEQ ID NO: 27 and 34; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 39; a detection reagent for detecting the level of miR-22-3p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 17; a PCR amplification primer pair comprising the sequence shown in SEQ ID NO: 28 and 34; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 40; a detection reagent for detecting the level of miR-221-5p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 18; a PCR amplification primer pair comprising the sequence shown in SEQ ID NO: 29 and 34; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: NO: 41; a detection reagent for detecting the level of miR-30d-3p comprising: a reverse transcription primer comprising the sequence of SEQ ID NO: 19; a PCR amplification primer pair comprising the sequences of SEQ ID NOs: 30 and 34; and / or a Taqman probe comprising the sequence of SEQ ID NO: 42; a detection reagent for detecting the level of miR-486-5p comprising: a reverse transcription primer comprising the sequence of SEQ ID NO: 20; a PCR amplification primer pair comprising the sequences of SEQ ID NOs: 31 and 34;and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 43; and a detection reagent for detecting the level of let-7g-5p comprising: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 21; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 32 and 34; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 44.

[0021] In some embodiments, the detection kit further includes a detection reagent for detecting the level of miR-16-5p as an internal reference gene; the detection reagent includes: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 22; a PCR amplification primer pair comprising the sequences shown in SEQ ID NO: 33 and 34; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 45.

[0022] In some embodiments, the TaqMan probe is labeled with a reporter fluorescent group at its 5' end, such as HEX, FAM, etc., preferably FAM, and a quencher fluorescent group at its 3' end, such as ECLIPSE, TAMRA, MGB, etc., preferably MGB.

[0023] In some embodiments, the detection kit further comprises a reagent for isolating exosomes from the biological sample; optionally, further comprises a reagent for extracting miRNA from the exosomes.

[0024] In some embodiments, the detection kit further comprises instructions for determining the lung cancer status of the subject based on logistic regression according to the level of the miRNA biomarker.

[0025] In some embodiments, the biological sample is selected from the group consisting of blood, serum, plasma, sputum, lymph, cerebrospinal fluid, pleural effusion, bronchoalveolar lavage fluid, and urine. Preferably, the biological sample is plasma.

[0026] In some embodiments, the detection kit also includes the following reagents for the reverse transcription reaction system (capable of detecting 50 times): 250 μL reverse transcription buffer (5×), 120 μL deoxynucleotide (10 mM), 25 μL RNase inhibitor (40 U / μL), and 60 μL reverse transcriptase (200 U / μL).

[0027] In some embodiments, the detection kit also includes the following reagents for real-time fluorescence quantitative PCR reaction system (capable of detecting 50 times): 600 μL PCR premix (2×), 30 μL F-end primer solution (30 μM), 30 μL R-end primer solution (30 μM), 30 μL Taqman probe primer (10 μM) and 2 mL nuclease-free water.

[0028] In another aspect, provided herein is a method for identifying lung cancer status in a subject, comprising: 1) isolating exosomes from a biological sample from the subject; 2) detecting the level of a miRNA biomarker in the exosomes, wherein the miRNA biomarker is selected from miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p and let-7g-5p, and any combination thereof; and 3) comparing the level of the miRNA biomarker detected in step 2) with the level of the corresponding miRNA in a population to determine the lung cancer status in the subject.

[0029] In some embodiments, the miRNA biomarkers include miR-126-3p, miR-140-5p, miR-17-5p, miR-19b-3p, and miR-22-3p.

[0030] In some embodiments, the miRNA biomarker is miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p, and let-7g-5p.

[0031] In some embodiments, the biomarker is selected from two or more of miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p, and let-7g-5p.

[0032] In some embodiments, the biomarker is selected from 5 or more of miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p, and let-7g-5p.

[0033] In some embodiments, the lung cancer status includes lung cancer susceptibility and / or the presence, progression, subtype, and / or stage of lung cancer.

[0034] In some embodiments, the lung cancer status is stage I or stage II lung cancer, and the miRNA biomarker is miR-140-5p, miR-19b-3p, and / or miR-22-3p.

[0035] In some embodiments, the lung cancer state is adenocarcinoma and the miRNA biomarker is miR-126-3p, miR-140-5p, miR-19b-3p, miR-22-3p, and / or miR-486-5p.

[0036] In some embodiments, the lung cancer state is squamous cell carcinoma and the miRNA biomarker is miR-126-3p, miR-140-5p, miR-19b-3p, miR-22-3p and / or miR-221-5p.

[0037] In some embodiments, the lung cancer state is large cell lung cancer and the miRNA biomarker is miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p and / or miR-486-5p.

[0038] In some embodiments, the lung cancer state is small cell lung cancer and the miRNA biomarker is miR-126-3p, miR-140-5p, miR-17-5p, miR-22-3p, miR-221-5p and / or miR-486-5p.

[0039] In some embodiments, the detection of the miRNA biomarker level in step 2) comprises using a miRNA biomarker-specific detection reagent, wherein the detection reagent comprises a reverse transcription primer (eg, RT stem-loop primer), a PCR amplification primer pair, and / or a Taqman probe.

[0040] In some embodiments, the detection reagents for detecting the level of miR-126-3p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 12; a PCR amplification primer pair including the sequence shown in SEQ ID NO: 23 and 34; and / or a Taqman probe including the sequence shown in SEQ ID NO: 35; the detection reagents for detecting the level of miR-140-5p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 13; a PCR amplification primer pair including the sequence shown in SEQ ID NO: 24 and 34; and / or a Taqman probe including the sequence shown in SEQ ID NO: 36; the detection reagents for detecting the level of miR-17-5p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 14; a PCR amplification primer pair including the sequence shown in SEQ ID NO: 25 and 34; and / or a Taqman probe including the sequence shown in SEQ ID NO: 37; the detection reagents for detecting the level of miR-181a-5p include: a reverse transcription primer including the sequence shown in SEQ ID NO: 15; a PCR amplification primer pair including the sequence shown in SEQ ID NO: 3 NO: 26 and 34; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 38; a detection reagent for detecting the level of miR-19b-3p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 16; a PCR amplification primer pair comprising the sequence shown in SEQ ID NO: 27 and 34; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 39; a detection reagent for detecting the level of miR-22-3p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 17; a PCR amplification primer pair comprising the sequence shown in SEQ ID NO: 28 and 34; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 40; a detection reagent for detecting the level of miR-221-5p comprises: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 18; a PCR amplification primer pair comprising the sequence shown in SEQ ID NO: 29 and 34; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: NO: 41; a detection reagent for detecting the level of miR-30d-3p comprising: a reverse transcription primer comprising the sequence of SEQ ID NO: 19; a PCR amplification primer pair comprising the sequences of SEQ ID NOs: 30 and 34; and / or a Taqman probe comprising the sequence of SEQ ID NO: 42; a detection reagent for detecting the level of miR-486-5p comprising: a reverse transcription primer comprising the sequence of SEQ ID NO: 20; a PCR amplification primer pair comprising the sequences of SEQ ID NOs: 31 and 34;and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 43; and a detection reagent for detecting the level of let-7g-5p comprising: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 21; a PCR amplification primer pair comprising the sequences shown in SEQ ID NOs: 32 and 34; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 44.

[0041] In some embodiments, step 2) further includes detecting the level of miR-16-5p as an internal reference gene; the detection reagents for detecting the level of miR-16-5p include: a reverse transcription primer comprising the sequence shown in SEQ ID NO: 22; a PCR amplification primer pair comprising the sequences shown in SEQ ID NO: 33 and 34; and / or a Taqman probe comprising the sequence shown in SEQ ID NO: 45.

[0042] In some embodiments, the TaqMan probe is labeled with a reporter fluorescent group at its 5' end, such as HEX, FAM, etc., preferably FAM, and a quencher fluorescent group at its 3' end, such as ECLIPSE, TAMRA, MGB, etc., preferably MGB.

[0043] In some embodiments, step 3) comprises determining the lung cancer status in the subject based on logistic regression according to the miRNA biomarker level.

[0044] In some embodiments, the biological sample is selected from the group consisting of blood, serum, plasma, sputum, lymph, cerebrospinal fluid, pleural effusion, bronchoalveolar lavage fluid, and urine. Preferably, the biological sample is plasma.

[0045] In some embodiments, the method further comprises performing steps 1) and 2) again after the subject receives medical treatment, and comparing the miRNA expression level detection results obtained twice to determine the change in the lung cancer status in the subject.

[0046] This paper provides a method for diagnosing lung cancer using exosomal miRNA biomarkers. Ten exosomal miRNAs, which are closely associated with lung cancer development, can be used as diagnostic markers for lung cancer with high sensitivity and specificity. A diagnostic kit for detecting the levels of these 10 exosomal miRNAs has also been developed, comprising specific amplification primers and universal PCR amplification reagents. The method and detection kit provided herein have promising clinical applications for the early diagnosis of lung cancer, providing new insights and approaches for improving early diagnosis of lung cancer. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1Receiver operating characteristic (ROC) curves of 10 exosomal miRNA biomarkers are shown.

[0048] Figure 2 The level distribution of 10 exosomal miRNA biomarkers in different lung cancer stages is shown, including Figure 2 A shows the distribution of miRNA levels of miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, and miR-22-3p. Figure 2 B shows the distribution of miRNA levels of miR-221-5p, miR-30d-3p, miR-486-5p, and let-7g-5p.

[0049] Figure 3 The level distribution of 10 exosomal miRNA biomarkers in different lung cancer subtypes is shown, including Figure 3 A shows the distribution of miRNA levels of miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, and miR-22-3p. Figure 3 B shows the distribution of miRNA levels of miR-221-5p, miR-30d-3p, miR-486-5p, and let-7g-5p.

[0050] Figure 4 The receiver operating characteristic (ROC) curve of the logistic regression model constructed using 10 miRNA markers is shown;

[0051] Figure 5 Shown are the receiver operating characteristic (ROC) curves of the logistic regression model constructed using the five most characterized miRNA markers. DETAILED DESCRIPTION

[0052] Unless otherwise specified, the technical terms used in this application have the meanings commonly understood by those skilled in the art to which the present invention belongs.

[0053] In one aspect, the present invention relates to a method for diagnosing lung cancer status in a subject, comprising the steps of: 1) collecting a biological sample from the subject and isolating exosomes therefrom; 2) detecting the level of exosomal miRNA biomarkers in the biological sample, wherein the biomarkers are selected from one or more of the following: miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p, and let-7g-5p. And 3) comparing the miRNA expression levels detected in step 2) with the levels of corresponding miRNAs in a population to determine the lung cancer status in the subject. The sequences of the miRNA biomarkers and the internal reference (miR-16-5p) are as follows.

[0054]

[0055] The term "subject" as used herein refers to an individual (preferably a human) who has or is suspected of having a disease, or, in the case of predicting susceptibility, "subject" may also include healthy individuals. The term is often used interchangeably with "patient," "test subject," "treatment subject," and the like.

[0056] The term "population" as used herein generally refers to a healthy population. When referring to a specific disease (e.g., lung cancer), a "population" may include people who do not suffer from the specific disease but may suffer from other diseases. In addition, only a portion of individuals may be selected as a "population" based on characteristics such as age, gender, health status, and whether or not they smoke. "MiRNA levels in a population" can be obtained by testing a sufficient number of individuals or can be found in existing clinical literature.

[0057] The term "lung cancer status" as used herein includes a subject's susceptibility to lung cancer as well as the presence, progression, subtype and / or stage of lung cancer. In some embodiments, the subject's susceptibility to lung cancer can be predicted based on the miRNA biomarker level in the subject. In other embodiments, the presence of lung cancer in the subject can be identified based on the biomarker miRNA level in the subject; and if lung cancer is present, its subtype and / or stage are identified. Lung cancer subtypes may include adenocarcinoma, squamous cell carcinoma, large cell lung cancer, and small cell lung cancer. Lung cancer stages may include stage I, stage II, stage III, and stage IV. In some embodiments, the lung cancer is stage I lung cancer. In some embodiments, the lung cancer is stage II lung cancer. In some embodiments, the lung cancer is stage III lung cancer. In other embodiments, the lung cancer is stage IV lung cancer.

[0058] The methods provided herein further comprise measuring the biomarker level in the subject again after the subject has been treated, and correlating the measurement result with the lung cancer status to identify whether the treatment has resulted in a change in the lung cancer status in the subject.

[0059] The detection of the biomarker miRNA level in the method provided herein includes detecting the amount of miRNA present in the biomarker, and performing quantitative and qualitative detection of the miRNA.

[0060] The biological sample is selected from the body fluids of the subject, including blood, serum, plasma, sputum, lymph, cerebrospinal fluid, pleural effusion, bronchoalveolar lavage fluid and urine.

[0061] In the methods provided herein, the subject's age and smoking index SI can also be considered to predict the lung cancer status in the subject.

[0062] In some embodiments, the methods provided herein further comprise the step of providing a written or electronic report of the prediction of lung cancer, and optionally, the report comprises a prediction of the presence or likelihood of lung cancer in the subject or a tiered risk of lung cancer in the subject.

[0063] In some embodiments, the methods provided herein further comprise creating a report of the relative levels of the biomarkers for a physician and transmitting such a report by mail, fax, email, etc. In one embodiment, the data stream comprising the report of the biomarker levels is transmitted via the Internet.

[0064] In some embodiments, a diagnostic model based on biomarker levels is constructed using a statistical method selected from the following methods: multiple linear regression, lookup table, decision tree, support vector machine, probit regression, logistic regression, cluster analysis, neighborhood analysis, genetic algorithm, Bayesian, principal component analysis and non-Bayesian methods, etc.

[0065] In other embodiments, a predictive or diagnostic model based on biomarker levels is provided. The model can be in the form of software code, a computer-readable format, or written instructions for evaluating the relative levels of biomarkers.

[0066] Utilizing the method provided herein, new and important additional information can be obtained, which assists physicians in grading the risk of lung cancer in patients and planning the next diagnostic steps to be taken. The method provided herein can similarly also be used to assess the risk of lung cancer in asymptomatic high-risk patients, as well as for the general population as a screening tool. It is contemplated that the method provided herein can be used by clinicians as part of a comprehensive assessment of other predictive and diagnostic indicators.

[0067] The methods provided herein can be used to evaluate the therapeutic efficacy of existing and candidate chemotherapeutic agents, as well as other types of cancer treatments. For example, biological samples can be obtained from a subject before or during treatment, and the levels of biomarkers can be measured as described above. The test results can be used to diagnose changes in the lung cancer status of the subject, thereby determining the efficacy of the treatment.

[0068] The methods provided herein can also be used to identify whether a subject is potentially developing cancer. The relative levels of biomarker miRNAs are detected in biological samples taken from the subject over time, thereby interpreting changes in biomarker levels that point to cancer characteristics as progression toward cancer.

[0069] The combination of biomarkers provides a sensitive, specific, and accurate means for predicting the presence of lung cancer or detecting lung cancer at different stages of lung cancer progression. The evaluation of the biomarker levels in the biological sample can also be correlated with the presence of pre-malignant or preclinical conditions in the patient. Therefore, the disclosed method can be used to predict or detect the benign or malignant nature of lung nodules in a sample, the presence of lung cancer, the stage of lung cancer, the subtype of lung cancer, the likelihood of metastasis of lung cancer, the histological type of neoplasms associated with lung cancer, the painlessness or aggressiveness of the cancer, and other lung cancer characteristics relevant to the prevention, diagnosis, characterization, and treatment of lung cancer in a patient.

[0070] The methods provided herein can also be used to evaluate the efficacy of candidate drugs in inhibiting lung cancer, evaluate the efficacy of lung cancer therapies, monitor the progression of lung cancer, select agents or therapies that inhibit lung cancer, monitor the treatment of lung cancer patients, monitor the inhibition of lung cancer in patients, and evaluate the carcinogenic potential of test compounds by detecting the expression level of miRNA biomarkers in test animals after exposure to the test compounds.

[0071] Also provided herein is a kit for detecting exosomal miRNAs in lung cancer. The kit may include: 1) primers and reagents for reverse transcription; 2) primers, TaqMan probes, and reagents for real-time fluorescence quantitative PCR. Preferably, the TaqMan probes used have a 5'-terminal reporter fluorophore of FAM, JOE, TET, HEX, Cy3, Texas Red, Rox, or Cy5; and a 3'-terminal quencher of BHQ1, BHQ2, BHQ3, TAMRA, DABCYL, or MGB.

[0072] In certain embodiments, the kit may further include instructions for using the reagents within the kit to detect the level of a biomarker in a subject. In some embodiments, the kit includes instructions for using the kit to determine the status of lung cancer in a subject.

[0073] The miRNA biomarker detection method may include but is not limited to the following methods: array-based methods, real-time fluorescence PCR, digital PCR, sequencing, next-generation sequencing, gene chip technology, fluorescence in situ hybridization technology and mass spectrometry analysis technology.

[0074] The present invention is further described below by way of examples.

[0075] Example 1: Isolation of plasma exosomes and extraction of miRNA

[0076] Peripheral blood collected in a blood collection tube containing EDTA anticoagulant was centrifuged at 3000×g for 10 minutes at 4°C within 4 hours of blood collection. The light yellow supernatant was carefully aspirated and then centrifuged at 3000×g for 10 minutes at 4°C. The upper plasma was collected into a 1.5 mL enzyme-free EP tube and stored at -80°C until use.

[0077] Exosomes were isolated from plasma using SBI's exosome extraction reagent (EXOQ5TM-1). The following procedure was used: 500 μL of plasma was added to 120 μL of ExoQuick solution and mixed using a shaker. The mixture was incubated at 4°C for 30 minutes. The mixture was then centrifuged at 1500 × g for 30 minutes at room temperature. The exosome-precipitation complex was allowed to settle to the bottom of the EP tube. The supernatant was carefully aspirated and discarded using a pipette. The tube walls and exosome pellet were carefully washed with 500 μL of sterile PBS, and the waste liquid was aspirated and discarded. The EP tube was centrifuged at 1500 × g for 5 minutes, and the remaining residual liquid was aspirated and discarded.

[0078] Exosome miRNAs were extracted using the Qiagen miRNeasy Micro Kit. Specific procedures were performed according to the kit instructions. The concentration of miRNA was measured using a Qubit 2.0 fluorometer.

[0079] Example 2: Reverse transcription of miRNA into cDNA

[0080] cDNA reverse transcription reaction system

[0081] Reagents used to prepare the reverse transcription reaction system were purchased from Sangon Biotech (Shanghai) Co., Ltd., including M-MuLV reverse transcriptase (Cat: B600005), RNase inhibitor (Cat: B600008), and dNTP Mix 10 mM (Cat: B500056). The reverse transcription reaction system is as follows:

[0082] Table 1 Reverse transcription reaction system

[0083] Components volume 5×Reaction Buffer 2ul RNase inhibitor 0.2ul dNTP Mix, 10 mM 1ul M-MuLV reverse transcriptase 0.5ul Reverse transcription primer (1uM) 0.3ul RNA template 6ul

[0084] Reverse transcription procedure: 16°C for 30 min, 42°C for 30 min, and 85°C for 5 min. The resulting cDNA was stored at 4°C.

[0085] Example 3: Real-time fluorescence quantitative PCR detection of miRNA expression levels based on TaqMan probes

[0086] Using cDNA as a template, the expression levels of the target miRNAs in the test samples were detected by real-time fluorescence quantitative PCR technology based on TaqMan probes under the use of specific primers and TaqMan probes for miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p, let-7g-5p and miR-16 (internal reference). -ΔCt(Cttarget miRNAs-CtmiRNA-16) : The Ct value represents the number of PCR cycles required for a target miRNA to reach the experimental design threshold (15-40). When the Ct value is >40, the sample is considered to contain the target miRNA. If the amplification efficiency of the target miRNA and the internal reference miRNA is the same, the quantification of the target miRNA relative to the internal reference miRNA can be directly obtained (ΔCt = Ct target miRNA - Ct internal reference miRNA).

[0087] The designed corresponding primer and probe sequences are as follows:

[0088] miR-126-3p primer set

[0089] Reverse transcription primer: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCGCATTAT (SEQ ID NO: 12)

[0090] F-terminal primer (forward primer): GCGCGTCGTACCGTGAGTAATA (SEQ ID NO: 23)

[0091] R-terminal primer (reverse universal primer): GTGCAGGGTCCGAGGT (SEQ ID NO: 34)

[0092] TaqMan probe: CTGGATACGACCGCATT (SEQ ID NO: 35)

[0093] miR-140-5p primer set

[0094] Reverse transcription primer: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCTACCATA (SEQ ID NO: 13)

[0095] F-terminal primer (forward primer): CGACCAGTGGTTTTACCCTAT (SEQ ID NO: 24)

[0096] R-terminal primer (reverse universal primer): GTGCAGGGTCCGAGGT (SEQ ID NO: 34)

[0097] TaqMan probe: CTGGATACGACCTACCA (SEQ ID NO: 36)

[0098] miR-17-5p primer set

[0099] Reverse transcription primer: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCTACCTGC (SEQ ID NO: 14)

[0100] F-terminal primer (forward primer): CCGCCAAAGTGCTTACAGTG (SEQ ID NO: 25)

[0101] R-terminal primer (reverse universal primer): GTGCAGGGTCCGAGGT (SEQ ID NO: 34)

[0102] TaqMan probe: CTGGATACGACCTACCTGC (SEQ ID NO: 37)

[0103] miR-181a-5p primer set

[0104] Reverse transcription primer: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACACTCACCG (SEQ ID NO: 15)

[0105] F-terminal primer (forward primer): CATAACATTCAACGCTGTCG (SEQ ID NO: 26)

[0106] R-terminal primer (reverse universal primer): GTGCAGGGTCCGAGGT (SEQ ID NO: 34)

[0107] TaqMan probe: CACTGGATACGACACTCAC (SEQ ID NO: 38)

[0108] miR-19b-3p primer set

[0109] Reverse transcription primer: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACTCAGTTTTG (SEQ ID NO: 16)

[0110] F-terminal primer (forward primer): CCGCGTGTGCAAATCCATGCA (SEQ ID NO: 27)

[0111] R-terminal primer (reverse universal primer): GTGCAGGGTCCGAGGT (SEQ ID NO: 34)

[0112] TaqMan probe: CACTGGATACGACTCAGTTTTG (SEQ ID NO: 39)

[0113] miR-22-3p primer set

[0114] Reverse transcription primer: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACACAGTTC (SEQ ID NO: 17)

[0115] F-terminal primer (forward primer): CGGGAAGCTGCCAGTTGAAG (SEQ ID NO: 28)

[0116] R-terminal primer (reverse universal primer): GTGCAGGGTCCGAGGT (SEQ ID NO: 34)

[0117] TaqMan probe: CTGGATACGACACAGTTC (SEQ ID NO: 40)

[0118] miR-221-5p primer set

[0119] Reverse transcription primer: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACAAATCTAC (SEQ ID NO: 18)

[0120] F-terminal primer (forward primer): AGCCGACCTGGCATACAAT (SEQ ID NO: 29)

[0121] R-terminal primer (reverse universal primer): GTGCAGGGTCCGAGGT (SEQ ID NO: 34)

[0122] TaqMan probe: CTGGATACGACAAATCTACA (SEQ ID NO: 41)

[0123] miR-30d-3p primer set

[0124] Reverse transcription primer: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACGCAGCAAA (SEQ ID NO: 19)

[0125] F-terminal primer (forward primer): CCGCGCTTTCAGTCAGATG (SEQ ID NO: 30)

[0126] R-terminal primer (reverse universal primer): GTGCAGGGTCCGAGGT (SEQ ID NO: 34)

[0127] TaqMan probe: CTGGATACGACGCAGCAAA (SEQ ID NO: 42)

[0128] miR-486-5p primer set

[0129] Reverse transcription primer: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCTCGGGGC (SEQ ID NO: 20)

[0130] F-terminal primer (forward primer): CCGCGTCCTGTACTGAGCTGC (SEQ ID NO: 31)

[0131] R-terminal primer (reverse universal primer): GTGCAGGGTCCGAGGT (SEQ ID NO: 34)

[0132] TaqMan probe: CTGGATACGACCTCGGG (SEQ ID NO: 43)

[0133] let-7g-5p primer set

[0134] Reverse transcription primer: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACAACTGT (SEQ ID NO: 21)

[0135] F-terminal primer (forward primer): GCCCGCTGAGGTAGTAGTTTGTAC (SEQ ID NO: 32)

[0136] R-terminal primer (reverse universal primer): GTGCAGGGTCCGAGGT (SEQ ID NO: 34)

[0137] TaqMan probe: CTGGATACGACAACTGT (SEQ ID NO: 44)

[0138] miRNA detection reference gene miR-16-5p primer set

[0139] Reverse transcription primer: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACCGCCAATA (SEQ ID NO: 22)

[0140] F-terminal primer (forward primer): CGCGCGTAGCAGCACGTAAA (SEQ ID NO: 33)

[0141] R-terminal primer (reverse universal primer): GTGCAGGGTCCGAGGT (SEQ ID NO: 34)

[0142] TaqMan probe: CTGGATACGACCGCCAATA (SEQ ID NO: 45)

[0143] To detect miRNA expression levels, PCR reactions were performed three times per sample. Each reaction volume was 20 μL, consisting of 10 μL of PCR solution, 5 μL of primer mix, and 5 μL of PCR template. Real-time fluorescence quantitative PCR reaction conditions were as follows (Table 2):

[0144] Table 2 Reaction procedures for detecting miRNA expression levels

[0145]

[0146] Example 4: Accuracy of the kit in detecting lung cancer status

[0147] This study included 1,056 clinical samples, including 432 confirmed lung cancer samples and 624 non-lung cancer samples. Samples were collected preoperatively, and each enrolled patient received an accurate diagnosis based on postoperative imaging and pathological examinations. Lung cancer samples covered various stages and common subtypes of lung cancer, while non-lung cancer samples included benign nodules, inflammatory tumors, and cysts. Sample staging was based on the international TNM staging system, and sample subtypes were determined by tissue biopsy and immunohistochemistry. Table 3 shows the clinical information of the samples.

[0148] Table 3. Clinical characteristics of the subjects from whom samples were collected

[0149]

[0150]

[0151] The real-time fluorescence PCR method described in the above example was used to detect the expression levels of 10 miRNAs in 432 lung cancer samples and 624 non-lung cancer samples. Exosomes were isolated from biological samples (plasma) and exosomal miRNAs were extracted using the method of Example 1. Reverse transcription and PCR detection of cDNA were performed according to the methods of Examples 2 and 3. Finally, the Ct values ​​of each miRNA in the test sample were obtained, and then the expression of miRNAs in the sample was detected by 2 -ΔCt(Cttarget miRNAs-CtmiRNA-16)) To reflect the expression level of miRNA.

[0152] For each biomarker miRNA level detection data, MedCalc11.4.2.0 software was used to select 95% confidence intervals to generate ROC curves and their area under the curve (AUC) values. Compared with benign samples, the AUCs of the 10 biomarker miRNA levels in lung cancer samples were all greater than 0.8 (P value>0.05) and ranged from 0.81 to 0.90 (see Figure 1 and Table 4 ).

[0153] Table 4 Area under the curve (AUC) of receiver operating characteristic (ROC) curve analysis of 10 markers

[0154]

[0155] To determine whether certain biomarkers have greater discrimination between different stages of lung cancer (especially early stages), the detection levels of 10 miRNA markers were compared in benign samples and lung cancer samples of different stages ( Figure 2 For early-stage (stage I or II) lung cancer samples, miR-140-5p, miR-19b-3p, and miR-22-3p showed high discrimination (P value < 0.001). For miR-221-5p and miR-486-5p, there was no significant difference between early-stage lung cancer and benign conditions (P value > 0.05).

[0156] In addition, we compared the levels of the above 10 miRNAs between samples of benign conditions and various subtypes of lung cancer to see if there were statistically significant differences ( Figure 3For adenocarcinoma, miR-126-3p, miR-140-5p, miR-19b-3p, miR-22-3p, and miR-486-5p all had high discriminatory powers (P < 0.001), while miR-221-5p and miR-30d-3p had low discriminatory powers. For squamous cell carcinoma, miR-126-3p, miR-140-5p, miR-19b-3p, miR-22-3p, and miR-221-5p had high discriminatory powers (P < 0.001), while miR-17-5p and miR-486-5p had low discriminatory powers. For large cell lung cancer, miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, and miR-486-5p had high discrimination (P value < 0.001), while miR-221-5p had low discrimination for large cell lung cancer. For small cell lung cancer, miR-126-3p, miR-140-5p, miR-17-5p, miR-22-3p, miR-221-5p, and miR-486-5p had high discrimination (P value < 0.001), while miR-30d-3p and let-7g had low discrimination for small cell lung cancer.

[0157] In terms of simplicity and cost reduction, measuring single miRNA levels is superior to measuring multiple miRNA markers. However, single miRNA levels may not provide the inherent diversity of complex diseases, so the construction of multiple marker diagnostic models is often necessary. Multiple marker diagnostic models require the use of statistical analysis methods. The following uses a logistic regression model as an example to construct a multiple miRNA marker diagnostic model.

[0158] The logistic regression model is constructed by dividing the samples into case and control groups and then optimizing the regression coefficients using IBM SPSS Statistics 24 software. A regression coefficient is assigned for each marker, along with a bias parameter, to maximize the likelihood that the logistic regression model applies to the training data. After training, the set of regression coefficients defines the logistic regression model. By substituting the expression levels of the miRNA markers into the logistic regression equation, those skilled in the art can easily use this diagnostic model to predict the likelihood that any new sample is a case or a control.

[0159] The AUCs obtained for the above 10 miRNA markers were all greater than 0.80. We combined the 10 miRNA markers using logistic regression and generated an AUC of 0.985 (standard error: 0.00285; 95% CI: 0.976-0.992; P value: <0.0001) ( Figure 4To simplify the monitoring and analysis method, the five markers with the largest AUC values ​​(miR-126-3p, miR-140-5p, miR-17-5p, miR-19b-3p, and miR-22-3p) were combined and a logistic regression model was established. The resulting AUC value was 0.968 (standard error: 0.00557; 95% CI: 0.955-0.977; P value: <0.0001) ( Figure 5 ), generally speaking, the sensitivity and specificity of the logistic regression model with 10 markers are slightly better than that with 5 markers, but based on the operational analysis procedures and cost considerations, the combination of 5 markers is also a better choice.

[0160] The technical solution provided in this article improves the sensitivity and specificity of lung cancer detection by jointly detecting the expression levels of one or more miRNA biomarkers, including miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p, and let-7g-5p, in exosomes, thereby ensuring the accuracy and reliability of the detection results. In addition, diagnostic kits and detection methods have been developed for the detection of 10 miRNAs, including miR-126-3p, miR-140-5p, miR-17-5p, miR-181a-5p, miR-19b-3p, miR-22-3p, miR-221-5p, miR-30d-3p, miR-486-5p and let-7g-5p. These kits can easily detect the levels of these 10 miRNAs and use logistic regression equation analysis to quickly and conveniently determine whether the sample is positive and the risk value, providing a rapid detection kit for improving the early diagnosis of lung cancer.

[0161] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may be modified, or some or all of the technical features therein may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the present invention specification. SEQUENCE LISTING <110> Beijing Aikelun Medical Technology Co., Ltd. <120> Detection kit and method for lung cancer diagnosis through exosomal miRNA biomarkers <130> 21799CI <160> 45 <170> PatentIn version 3.3 <210> 1 <211> 22 <212> RNA <213> Homo sapiens <400> 1 ucguaccgug aguaauaaug cg 22 <210> 2 <211> 22 <212> RNA <213> Homo sapiens <400> 2 cagugguuuu acccuauggu ag 22 <210> 3 <211> 23 <212> RNA <213> Homo sapiens <400> 3 caaagugcuu acagugcagg uag 23 <210> 4 <211> 23 <212> RNA <213> Homo sapiens <400> 4 aacauucaac gcugucggug agu 23 <210> 5 <211> 23 <212> RNA <213> Homo sapiens <400> 5 ugugcaaauc caugcaaaac uga 23 <210> 6 <211> 22 <212> RNA <213> Homo sapiens <400> 6 aagcugccag uugaagaacu gu 22 <210> 7 <211> 22 <212> RNA <213> Homo sapiens <400> 7 accuggcaua caauguagau uu 22 <210> 8 <211> 22 <212> RNA <213> Homo sapiens <400> 8 cuuucaguca gauguuugcu gc 22 <210> 9 <211> 22 <212> RNA <213> Homo sapiens <400> 9 uccuguacug agcugccccg ag 22 <210> 10 <211> 22 <212> RNA <213> Homo sapiens <400> 10 ugagguagua guuuguacag uu 22 <210> 11 <211> 22 [[ID=৪৯]]<212> RNA <213> Homo sapiens <400> 11 uagcagcacg uaaauauugg cg 22 <210> 12 <211> 52 <212> DNA <213> Artificial <220> <223> Reverse transcription primer <400> 12 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgaccgcatt at 52 <210> 13 <211> 52 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 13 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacctacca ta 52 <210> 14 <211> 52 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 14 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacctacct gc 52 <210> 15 <211> 52 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 15 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacactcac cg 52 <210> 16 <211> 53 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 16 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgactcagtt ttg 53 <210> 17 <211> 51 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 17 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacacagtt c 51 <210> 18 <211> 52 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 18 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacaaatct ac 52 <210> 19 <211> 52 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 19 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacgcagca aa 52 <210> 20 <211> 52 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> 20 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacctcggg gc 52 <210> twenty one <211> 50 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> twenty one gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgacaactgt 50 <210> twenty two <211> 52 <212> DNA <213> Artificial <220> <223> Reverse transcription primers <400> twenty two gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgaccgccaa ta 52 <210> twenty three <211> twenty two <212> DNA <213> Artificial <220> <223> Forward primer <400> twenty three gcgcgtcgta ccgtgagtaa ta 22 <210> twenty four <211> twenty one <212> DNA <213> Artificial <220> <223> Forward primer <400> twenty four cgaccagtgg ttttacccta t 21 <210> 25 <211> 20 <212> DNA <213> Artificial <220> <223> Forward primer <400> 25 ccgccaaagt gcttacagtg 20 <210> 26 <211> 20 <212> DNA <213> Artificial <220> <223> Forward primer <400> 26 cataacattc aacgctgtcg 20 <210> 27 <211> twenty one <212> DNA <213> Artificial <220> <223> Forward primer <400> 27 ccgcgtgtgc aaatccatgc a 21 <210> 28 <211> 20 <212> DNA <213> Artificial <220> <223> Forward primer <400> 28 cgggaagctg ccagttgaag 20 <210> 29 <211> 19 <212> DNA <213> Artificial <220> <223> Forward primer <400> 29 agccgacctg gcatacaat 19 <210> 30 <211> 19 <212> DNA <213> Artificial <220> <223> Forward primer <400> 30 ccgcgctttc agtcagatg 19 <210> 31 <211> twenty one <212> DNA <213> Artificial <220> <223> Forward primer <400> 31 ccgcgtcctg tactgagctg c 21 <210> 32 <211> twenty four <212> DNA <213> Artificial <220> <223> Forward primer <400> 32 gcccgctgag gtagtagttt gtac 24 <210> 33 <211> 20 <212> DNA <213> Artificial <220> <223> Forward primer <400> 33 cgcgcgtagc agcacgtaaa 20 <210> 34 <211> 16 <212> DNA <213> Artificial <220> <223> Reverse primer <400> 34 gtgcagggtc cgaggt 16 <210> 35 <211> 17 <212> DNA <213> Artificial <220> <223> probe <400> 35 ctggatacga ccgcatt 17 <210> 36 <211> 17 <212> DNA <213> Artificial <220> <223> probe <400> 36 ctggatacga cctacca 17 <210> 37 <211> 19 <212> DNA <213> Artificial <220> <223> probe <400> 37 ctggatacga cctacctgc 19 <210> 38 <211> 19 <212> DNA <213> Artificial <220> <223> probe <400> 38 cactggatac gacactcac 19 <210> 39 <211> twenty two <212> DNA <213> Artificial <220> <223> probe <400> 39 cactggatac gactcagttt tg 22 <210> 40 <211> 18 <212> DNA <213> Artificial <220> <223> probe <400> 40 ctggatacga cacagttc 18 <210> 41 <211> 20 <212> DNA <213> Artificial <220> <223> probe <400> 41 ctggatacga caaatctaca 20 <210> 42 <211> 19 <212> DNA <213> Artificial <220> <223> probe <400> 42 ctggatacga cgcagcaaa 19 <210> 43 <211> 17 <212> DNA <213> Artificial <220> <223> probe <400> 43 ctggatacga cctcggg 17 <210> 44 <211> 17 <212> DNA <213> Artificial <220> <223> probe <400> 44 ctggatacga caactgt 17 <210> 45 <211> 19 <212> DNA <213> Artificial <220> <223> probe <400> 45 ctggatacga ccgccaata 19

Claims

1. Use of a detection kit in the preparation of a diagnostic kit for diagnosing lung cancer in a subject, wherein the detection kit comprises a detection reagent for detecting the level of exosomal miRNA biomarkers in a biological sample from the subject, wherein the miRNA biomarkers are miR-126-3p, miR-140-5p, miR-17-5p, miR-19b-3p, and miR-22-3p, and the biological sample is selected from blood, serum, and plasma.

2. The method of claim 1, wherein the miRNA biomarker further comprises one or more of the following biomarkers: miR-181a-5p, miR-221-5p, miR-30d-3p, miR-486-5p, and let-7g-5p.

3. The method according to claim 1 or 2, wherein the detection reagent for detecting the level of miRNA biomarkers comprises a reverse transcription primer, a PCR amplification primer pair and / or a Taqman probe.

4. The use according to claim 1, wherein: The detection reagents for detecting the level of miR-126-3p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 12; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 23 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO: 35; The detection reagents for detecting the level of miR-140-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 13; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 24 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO: 36; The detection reagents for detecting the level of miR-17-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 14; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 25 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO: 37; The detection reagents for detecting the level of miR-19b-3p include: a reverse transcription primer of the sequence shown in SEQ ID NO: 16; a PCR amplification primer pair of the sequences shown in SEQ ID NO: 27 and 34; and / or a Taqman probe of the sequence shown in SEQ ID NO: 39; and The detection reagents for detecting the level of miR-22-3p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 17; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 28 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO:

40.

5. The use according to claim 2, wherein: The detection reagents for detecting the level of miR-126-3p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 12; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 23 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO: 35; The detection reagents for detecting the level of miR-140-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 13; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 24 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO: 36; The detection reagents for detecting the level of miR-17-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 14; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 25 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO: 37; The detection reagents for detecting the level of miR-181a-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 15; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 26 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO: 38; The detection reagents for detecting the level of miR-19b-3p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 16; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 27 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO: 39; The detection reagents for detecting the level of miR-22-3p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 17; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 28 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO: 40; The detection reagents for detecting the level of miR-221-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 18; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 29 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO: 41; The detection reagents for detecting the level of miR-30d-3p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 19; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 30 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO: 42; The detection reagents for detecting the level of miR-486-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 20; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 31 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO: 43; and The detection reagents for detecting the level of let-7g-5p include: a reverse transcription primer with the sequence shown in SEQ ID NO: 21; a PCR amplification primer pair with the sequences shown in SEQ ID NO: 32 and 34; and / or a Taqman probe with the sequence shown in SEQ ID NO:

44.

6. The method according to claim 1 or 2, wherein the detection kit further comprises a detection reagent for detecting the level of miR-16-5p as an internal reference gene; the detection reagent comprises: a reverse transcription primer having the sequence shown in SEQ ID NO: 22; and a PCR amplification primer pair having the sequences shown in SEQ ID NOs: 33 and 34; and / or a Taqman probe having the sequence shown in SEQ ID NO:

45.

7. The use according to claim 1 or 2, wherein the detection kit further comprises a reagent for isolating exosomes from the biological sample; optionally, further comprises a reagent for extracting miRNA from the exosomes.

8. The use according to claim 1 or 2, wherein the diagnostic kit comprises instructions for determining the lung cancer status in the subject based on logistic regression according to the level of the miRNA biomarker.

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