miRNA MARKER COMBINATION FOR DIAGNOSING GASTRIC CANCER, AND KIT

Abstract

To provide a combination of miRNA markers and a kit capable of diagnosing gastric cancer easily, effectively, and non-invasively.SOLUTION: A miRNA marker combination for diagnosing gastric cancer comprises at least four markers selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p. The marker combination for diagnosing gastric cancer can be used to distinguish blood serum of a patient with gastric cancer from that of a healthy human.SELECTED DRAWING: None

Description

[Technical Field]

[0001] This application claims priority to a Chinese patent application with application number 201910392316.2, filed with the China Patent Office on April 30, 2019, entitled "miRNA Marker Combination and Kit for Diagnosing Gastric Cancer," the entire contents of which are incorporated herein by reference.

[0002] Technical Field The present invention is in the field of molecular biology, and in particular relates to a combination of miRNA markers and a kit for diagnosing gastric cancer. [Background technology]

[0003] background Gastric cancer is one of the most common malignant tumors worldwide and has the highest mortality rate. The majority of gastric cancer patients miss the optimal time for diagnosis and treatment when they are diagnosed, resulting in disease progression, tumor metastasis, and even progression to advanced stages. From the perspective of the TMN classification of gastric cancer, the 5-year survival rate for gastric cancer is 97.6% for early stage I, 94.9% for late stage I, 70.49% for stage II, 56.7% for early stage III, 31.9% for late stage III, and 6.5% for stage IV. This highlights the importance of early gastric cancer diagnosis.

[0004] Endoscopy (gastroscope) is currently the most useful tool for diagnosing gastric cancer. Endoscopic signs of early gastric cancer include abnormal mucosal color, loss of blood vessels on the mucosal surface, depression or thickening of the mucosal layer, irregular nodules, and abnormal mucosal folds around ulcers. If necessary, a portion of tissue can be removed for biopsy. Detection of protein markers in the blood can be used as a criterion for diagnosing gastric cancer. Commonly used tumor protein markers for gastric cancer include carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 72-4 (CA72-4), carbohydrate antigen 50 (CA50), and gastric proteases.

[0005] Biopsy after endoscopy is the gold standard for detecting gastric cancer. However, this method is invasive and can cause discomfort and fear for patients. In addition, asymptomatic patients usually do not undergo endoscopy. Although traditional tumor protein markers are often used to detect gastrointestinal cancers, they are not recommended for diagnosing gastric cancer due to lack of sensitivity and / or specificity.

[0006] Currently, detection of miRNA tumor markers in tissues, serum, or plasma is used as the standard for diagnosing gastric cancer. miRNAs are a type of small, non-coding, single-stranded RNA molecule approximately 19–24 nt in length. Most miRNAs can inhibit the protein translation of target genes through complementary binding to their 3'UTR regions, thereby affecting the growth and development of organisms at the cellular, tissue, or individual levels and contributing to the progression of various diseases. miRNA expression profiles exhibit clear tissue specificity, with distinct expression patterns in various tumors. These characteristics enable miRNAs to serve as novel biological markers and therapeutic targets for tumor diagnosis. qPCR is the most commonly used method for detecting the expression of known miRNAs. It is rapid, simple, and reproducible, and allows for highly sensitive and accurate quantitative analysis of miRNA expression, making it the most important method for clinical applications. This provides solid technical support for circulating miRNAs as noninvasive diagnostic markers for tumors.

[0007] Although existing studies have identified many promising serum miRNAs for the early diagnosis of gastric cancer, these results are inconsistent and cannot be cross-validated. This is due to inconsistencies in sample selection, collection, and storage processes across various studies. The content of biomarkers in peripheral blood samples isolated and stored using different methods varies. Individuals' body fluid environments, genetic characteristics, and other non-cancerous factors affect miRNA expression, and eliminating this influence requires a large number of population samples. Additionally, miRNA detection presents certain challenges. Therefore, the precise serum miRNA biomarkers and biomarker combinations that can ultimately be used for gastric cancer screening have yet to be determined. Summary of the Invention

[0008] Abstract In view of this, the object of the present invention is to provide a marker combination and kit for diagnosing early gastric cancer, which can easily, effectively and non-invasively detect gastric cancer by distinguishing the serum of gastric cancer patients from the serum of healthy individuals and further distinguishing the serum of gastric cancer patients from the serum of gastritis patients. In order to achieve the objectives of the present invention, the present invention adopts the following technical solutions:

[0009] The applicant has used RT-qPCR technology to identify 12 miRNAs, specifically hsa-miR-29c-3, as biomarkers and combinations for detecting gastric cancer. The miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p were screened and obtained. The miRNA marker combinations of the present invention were used to test 4,566 subjects. The results were compared with the Helicobacter pylori test and the pepsinogen test and showed good agreement with the clinical gold standard of endoscopy (AUC 0.84) and significantly superior to two existing biomarkers, the pepsinogen I / II ratio and the Helicobacter pylori test (AUC 0.62 and 0.64, respectively).

[0010] The combination of miRNA markers for diagnosing gastric cancer includes at least four miRNA markers selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0011] In some embodiments, the combination of miRNA markers comprises at least five miRNA markers selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0012] In some embodiments, the combination of miRNA markers comprises hsa-m The gene expression vector contains at least six miRNA markers selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0013] In some embodiments, the combination of miRNA markers comprises at least seven miRNA markers selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0014] In some embodiments, the combination of miRNA markers comprises at least eight miRNA markers selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0015] In some embodiments, the combination of miRNA markers comprises at least nine miRNA markers selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0016] In some embodiments, the combination of miRNA markers comprises at least 10 miRNA markers selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0017] In some embodiments, the combination of miRNA markers comprises at least 11 miRNA markers selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0018] In some embodiments, the combination of miRNA markers in a peripheral blood sample for diagnosing gastric cancer comprises hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-103b-3p, hsa-miR-103c-3p, hsa-miR-103d-3p, hsa-miR-103e-3p, hsa-miR-103f ... -181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0019] In some embodiments, the combination of miRNA markers consists of 12 miRNA markers: hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0020] In some embodiments, the combination of miRNA markers consists of 11 miRNA markers: hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0021] In some embodiments, the combination of miRNA markers consists of 10 miRNA markers: hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0022] In some embodiments, the combination of miRNA markers consists of nine miRNA markers: hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0023] In some embodiments, the combination of miRNA markers consists of eight miRNA markers: hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-126-3p, and hsa-miR-340-5p.

[0024] In some embodiments, the combination of miRNA markers consists of seven miRNA markers: hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, and hsa-miR-340-5p.

[0025] In some embodiments, the combination of miRNA markers consists of six miRNA markers: hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, and hsa-miR-340-5p.

[0026] In some embodiments, the combination of miRNA markers comprises five miRNA markers: hsa-miR-103a-3p, hsa-miR-181a-5p, It consists of hsa-miR-21-5p, hsa-miR-140-5p, and hsa-miR-340-5p.

[0027] In some embodiments, the combination of miRNA markers consists of four miRNA markers: hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, and hsa-miR-340-5p.

[0028] The present invention provides a method for identifying a subject at risk of having gastric cancer, comprising: a. detecting the expression levels of at least four miRNA markers selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p in a peripheral blood sample from the subject; b. Calculating and adjusting the subject's risk score relative to a non-cancer control sample; and c. Determining the likelihood that the subject will develop gastric cancer based on the risk score. Also provided is a method comprising:

[0029] In some embodiments, methods for determining miRNA expression levels include the use of quantitative RT-PCR (e.g., using SYBR-Green or Tagman-based chemistry), chip, or sequencing. In other embodiments, the biomarkers can be detected by Northern blot, droplet digital PCR, mass spectrometry, electrochemiluminescence, or other methods known in the art.

[0030] In some embodiments of the method, a linear regression model is used to calculate the risk score. In some embodiments of the method, the linear regression model used is logistic regression. In some embodiments of the method, the linear regression model is:

[0031]

number

[0032] (wherein miRNA1, miRNA2, miRNA3... are selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p; CT is the relative expression level of each miRNA detected by qPCR; and K is the coefficient of each miRNA marker) As follows.

[0033] The present invention also provides a kit for diagnosing gastric cancer, which comprises a reagent for specifically detecting the combination of miRNA markers.

[0034] In some embodiments, the reagents in the kits of the present invention are used as a test for qPCR. The detection reagents are detection reagents for the chip method, or detection reagents for the sequencing method.

[0035] In some embodiments, the reagents in the kit for specifically detecting a combination of miRNA markers comprise at least one oligonucleotide, at least some of which specifically bind to an miRNA marker in the combination of peripheral blood miRNA markers described above for diagnosing gastric cancer.

[0036] In some embodiments, the reagents for specifically detecting a combination of miRNA markers in a kit according to the present invention are detection reagents for qPCR methods.

[0037] Furthermore, in some embodiments, the detection reagents for the qPCR method in the kit according to the present invention comprise reverse transcription primers and / or qPCR amplification primers for a combination of miRNA markers.

[0038] Furthermore, in some embodiments, the kit comprises stem-loop reverse transcription primers and / or semi-nested qPCR primers for amplifying miRNA markers in the above-mentioned combination of peripheral blood miRNA markers for the diagnosis of gastric cancer.

[0039] In some embodiments, the detection reagents for qPCR in the kits according to the present invention comprise reverse transcription primers and / or qPCR amplification primers for each miRNA in a combination of 12 miRNA markers: hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0040] In some embodiments, the detection reagents for qPCR in the kits according to the present invention comprise reverse transcription primers and / or qPCR amplification primers for each miRNA in a combination of 11 miRNA markers: hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0041] In some embodiments, the detection reagents for the qPCR method in the kit according to the present invention comprise reverse transcription primers and / or qPCR amplification primers for each miRNA in a combination of 10 miRNA markers: hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

[0042] In some embodiments, the detection reagents for the qPCR method in the kit according to the present invention comprise the miRs consisting of nine miRNA markers: hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p. Include reverse transcription primers and / or qPCR amplification primers for each miRNA in the combination of miRNA markers.

[0043] In some embodiments, the detection reagents for the qPCR method in the kit according to the present invention comprise reverse transcription primers and / or qPCR amplification primers for each miRNA in a combination of eight miRNA markers: hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-126-3p, and hsa-miR-340-5p.

[0044] In some embodiments, the detection reagents for the qPCR method in the kit according to the present invention comprise reverse transcription primers and / or qPCR amplification primers for each miRNA in a combination of seven miRNA markers: hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, and hsa-miR-340-5p.

[0045] In some embodiments, the detection reagents for the qPCR method in the kit according to the present invention comprise reverse transcription primers and / or qPCR amplification primers for each miRNA in a combination of six miRNA markers: hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, and hsa-miR-340-5p.

[0046] In some embodiments, the detection reagents for the qPCR method in the kit according to the present invention comprise reverse transcription primers and / or qPCR amplification primers for each miRNA in a combination of five miRNA markers: hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, and hsa-miR-340-5p.

[0047] In some embodiments, the detection reagents for the qPCR method in the kit according to the present invention comprise reverse transcription primers and / or qPCR amplification primers for each miRNA in a combination of four miRNA markers: hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, and hsa-miR-340-5p.

[0048] Furthermore, in some embodiments, the detection reagents for qPCR in the kit according to the present invention further comprise at least one of a positive quality control, a negative quality control, a reverse transcriptase, dNTPs, a reverse transcription buffer, nuclease-free water, a qPCR buffer, magnesium chloride, a DNA polymerase, and a SYBR Green fluorescent dye.

[0049] The present invention also provides use of a combination of miRNA markers in the preparation of a gastric cancer diagnostic reagent for predicting the likelihood that a subject will develop or be affected by gastric cancer, said method comprising: detecting the presence of miRNA in a peripheral blood sample obtained from a subject; measuring the expression level of at least one miRNA in the combination of miRNA markers in said peripheral blood sample; and Predicting the likelihood that a subject will develop or have gastric cancer using a score based on previously measured miRNA expression levels Includes:

[0050] The peripheral blood is serum or plasma. The expression level of the miRNA is scored by using a linear regression algorithm to construct a simple linear regression model.The linear regression model is used to calculate risk score.Logistic regression is an example of the linear regression method that can be used for this purpose.However, those skilled in the art will understand that other types of linear regression calculations can be used to calculate and obtain score.The critical value of risk score is determined based on clinical needs, and two critical values are used to classify the group as high-risk group, low-risk group and undetermined group.

[0051] Subjects include, but are not limited to, Chinese, Malaysian, and Indian. From the above technical solution, it can be seen that the present invention provides a marker combination and kit for diagnosing gastric cancer. The miRNA marker combination for diagnosing gastric cancer according to the present invention comprises at least four miRNA markers selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p. Detection of serum in a subject using the marker combination for diagnosing gastric cancer can distinguish between serum from gastric cancer patients and healthy individuals, and between serum from gastritis patients. The above-mentioned combination of miRNA markers according to the present invention is used to test subjects. The results are compared with Helicobacter pylori test and pepsinogen test, and are in good agreement with the clinical gold standard of endoscopy, and are significantly superior to the two existing biomarkers, pepsinogen I / II ratio and Helicobacter pylori test. The kit for diagnosing gastric cancer according to the present invention has a simple composition and can easily, effectively, and non-invasively detect gastric cancer. [Brief explanation of the drawings]

[0052] BRIEF DESCRIPTION OF THE DRAWINGS In order to describe the technical solutions in the embodiments of the present invention or the prior art more clearly, the following briefly introduces the drawings that need to be used in the description of the embodiments or the prior art. [Figure 1] Figure 1 shows the roadmap for clinical evaluation of serum miRNAs in gastric cancer; [Figure 2] Figure 2 is a diagram showing the ROC characteristics of various blood markers; [Figure 3] Figure 3 is a diagram showing the ROC characteristics for men and women; [Figure 4] Figure 4 is a chart showing the ROC characteristics of the kit for subjects of different races; [Figure 5] Figure 5 is a chart showing the ROC characteristics of this kit for subjects with early stage gastric cancer and subjects with late stage gastric cancer; [Figure 6] Figure 6 is a chart showing the ROC characteristics of different miRNA number combinations under the linear regression algorithm; DETAILED DESCRIPTION OF THE INVENTION

[0053] Detailed Description The present invention discloses a combination of miRNA markers and a kit for diagnosing gastric cancer. Those skilled in the art can learn from the contents of this document and appropriately determine the process parameters to achieve the present invention. The present invention can be improved in various ways. In particular, it should be pointed out that all similar substitutions and modifications are apparent to those skilled in the art, and all of them are considered to be included in the present invention. The method and product of the present invention have been described in terms of preferred embodiments. It is apparent that those skilled in the art may make changes or appropriate modifications or combinations to the methods described herein in order to realize and apply the technology of the present invention, without departing from the content, spirit and scope of the present invention.

[0054] In order to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only a part of the examples of the present invention, rather than all of them. All other examples obtained by those skilled in the art based on the embodiments of the present invention without any creative efforts belong to the protection scope of the present invention.

[0055] Unless otherwise specified, all reagents used in the examples of the present invention are commercially available products and can be purchased through commercially available channels. The design method for reverse transcription primers and RT-qPCR primers for miRNAs according to the present invention is carried out according to the methods described in U.S. Patent Publication No. US9850527B2 and Wan G, Lim Q', Too H P. High-performance quantification of mature microRNAs by real-time RT-PCR using deoxyuridine-incorporated oligonucleotides and hemi-nested primers [J] Rna-a Publication of the RNA Society, 2010, 16(7):1436-45. All miRNA sequences disclosed in the present invention are stored in the miRBase database (http: / / www.mirbase.org / ). [Example]

[0056] Example 1 In the development phase, RT-qPCR technology was used to detect serum miRNAs in 236 gastric cancer patients and 236 non-cancer control subjects. 191 miRNAs were identified.

[0057] TIFF2025114665000002.tif12116

[0058] were detectable in more than 90% of subjects. 75 of 191 miRNAs were differentially expressed between control and cancer patients (FDR P value < 0.01). Of the 75 differentially expressed miRNAs, 51 were up-regulated and 24 were down-regulated in gastric cancer patients.

[0059] In the validation phase, RT-qPCR technology was used to detect serum miRNAs in 94 gastric cancer patients and 116 non-cancer control subjects. There was a good correlation between the fold changes in miRNA expression between the development and validation phases. Finally, 12 miRNAs, specifically hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p, were further selected as biomarkers and combinations for detecting gastric cancer. The miRNA sequences and their miRBase database accession numbers are shown in Table 1.

[0060] [Table 1]

[0061] To test the performance of combinations of 2 to 12 miRNA biomarkers, 200-fold cross-validation was performed on the combinations of the 12 miRNA biomarkers obtained from the screening and nonparametric factors. AUC was calculated using a simple linear regression model. The logistic regression model was used as an optimization index to construct a risk score. A linear regression model was used to calculate the risk score. In this example, a logistic regression model was used. The critical value of the risk score was determined based on clinical need, and two critical values were used to define the population as a high-risk population, a low-risk population, and an undetermined population. The logistic score of the gastric cancer population was significantly higher than that of the healthy population. The formula for the linear regression model is:

[0062]

number

[0063] where K is the coefficient of each miRNA marker, and the coefficient of each marker varies depending on the marker combination, the possible implementations of which are shown in the table.

[0064] CT is the relative expression level of each miRNA marker, i.e., the Ct value obtained by qPCR.

[0065] [Table 2]

[0066] Example 2 1) Preparation of test samples: blood collection and serum separation; A total of 20 ml of fasting blood samples were collected into two standard serum tubes. The serum tubes were centrifuged at 3000 rpm for 10 minutes at 20°C. Centrifugation and serum collection occurred within 4 hours of blood collection. Serum samples were immediately stored at -80°C.

[0067] 2) RNA extraction; Total RNA was isolated from 200 μl of serum using the miRNeasy serum / plasma miRNA extraction kit (Qiagen GmbH, Germany). The miRNA control (mixture of high, medium, and low concentrations) was used to evaluate the technical feasibility of this process. It was added to the sample lysis buffer to check for variations and to normalize.

[0068] 3) Reverse transcription real-time quantitative PCR (RT-qPCR) A reverse transcription buffer, reverse transcriptase, and reverse transcription primers were used for reverse transcription of miRNA under specific reaction conditions and temperatures. The reverse-transcribed cDNA was amplified by qPCR using a qPCR plate containing qPCR buffer, DNA polymerase, and miRNA-specific primers under specific reaction conditions and temperature. The Ct values of each miRNA were obtained by setting a threshold.

[0069] Prior to RT-qPCR, a set of artificially synthesized miRNA (3) controls was added to each sample to check and normalize technical variability in this step. During RT-qPCR, six log-diluted artificially synthesized templates, negative controls, and mixed human serum RNA standards were added to each miRNA, and each isolated serum RNA sample was reverse transcribed and quantified by qPCR. These quality control measures were implemented during pipetting and measurement during RT, cDNA amplification, and qPCR. It helps to check and standardize the technical variations in the efficiency of the assay.

[0070] 4) Protocol for the detection of 12 miRNAs in the validation phase (Example 3) Serum samples were lysed with phenol / guanidine, and total RNA from the serum samples was isolated using a silica purification column. In the reverse transcription step, 12 miRNAs in each sample were reverse transcribed into cDNA using corresponding stem-loop primers for miRNA reverse transcription. Subsequently, qPCR was performed using a sequence-specific forward PCR primer and a semi-nested sequence-specific reverse PCR primer, and SYBR Green I dye was used for detection.

[0071] 5) To perform statistical analysis and obtain a risk value for developing gastric cancer, the Ct values were imported into the linear regression model described in Example 1.

[0072] Example 3 5,282 subjects from the National University Hospital of Singapore and Tan Tock Seng Hospital of Singapore were selected for the clinical trial. The specific validation route is shown in Figure 1. A total of 5,282 subjects participated in the clinical validation. Following the method described in Example 2, the 12 miRNA biomarkers described in Example 1 were selected for miRNA testing, Helicobacter pylori testing, and pepsinogen testing, as well as gastroscopy and pathology testing, for all subjects. The 12-miRNA qPCR assay was developed and manufactured in accordance with the ISO 13485 Medical Device Quality Management System. In the absence of endoscopy and histopathology results, miRNA testing was performed in a CAP / ISO-accredited laboratory. Helicobacter pylori antibodies were measured in serum samples using a Western blot assay. Pepsinogen I and II levels were measured using a latex agglutination immunoturbidimetric assay kit. Both measurements were performed when clinical results were unknown. After the screening, 4,566 subjects were finally used for data analysis, of which 125 subjects were diagnosed with gastric cancer and 4,441 subjects were confirmed as healthy individuals without cancer. Table 3 shows the analysis results of the clinical findings data of the 4,566 subjects.

[0073] [Table 3]

[0074] The miRNA marker combination test, Helicobacter pylori test, and pepsinogen test according to the present invention were compared, and the results are shown in FIG. 2 and Table 4.

[0075] [Table 4]

[0076] From the results of 4566 subjects, it can be seen that the miRNA marker combination test method according to the present invention is in good agreement with the clinical gold standard of endoscopy (AUC of 0.84) and significantly superior to each of the two existing biomarkers, pepsinogen I / II ratio and Helicobacter pylori test (AUC of 0.62 and 0.64). The AUC (0.84) of 4566 subjects is close to the AUC (0.89) of the algorithm development cohort, demonstrating the consistency of the experimental results between the development cohort for the miRNA marker combination according to the present invention and the blinded clinical validation cohort.

[0077] Further analysis was performed on gender differences in clinical validation data. The miRNA marker combination test according to the present invention showed consistent AUCs in male and female subjects (Figure 3 and Table 5).

[0078] [Table 5]

[0079] The clinical validation data was further analyzed to determine whether the performance of the miRNA marker combination test according to the present invention differed in different ethnic groups. Generally consistent with the demographic data of Singapore, most of the subjects participating in this clinical trial were of Chinese descent (76.43%), with Malay, Indian, and other ethnic groups each accounting for approximately 8% (Table 3). The results showed that the AUC for Chinese subjects was higher than that for subjects of other ethnicities (Figure 4, Table 6).

[0080] [Table 6]

[0081] The performance of the miRNA marker combination test according to the present invention is evaluated by cancer staging. In the miRNA marker combination test according to the present invention, the AUC for early cancer (stages 0, I, and II) and advanced cancer (stages III and IV) were shown to be 0.83 and 0.85, respectively (Figure 5, Table 7).

[0082] [Table 7]

[0083] Furthermore, we demonstrated the clinical specificity of miRNA detection for seven other common cancers, including lung, breast, colorectal, liver, esophageal, prostate, and bladder cancers. The assay had little cross-reactivity with other common cancers, including gastrointestinal cancers (Table 8).

[0084] [Table 8]

[0085] Example 4 Following the method described in Example 2, combinations of 12, 11, 10, 9, 8, 7, 6, 5, and 4 miRNAs described in Example 1 were sequentially selected according to the order of importance of the miRNAs and tested using samples from cancer and control subjects described in Example 3 to obtain plots showing ROC characteristics (Figure 6, Table 9).

[0086] [Table 9]

[0087] It should be noted that when different scores are used as the borderline between cancer and non-cancer, the logistic algorithms show different diagnostic performance and are suitable for different diagnostic methods (Table 8). For example, when a 40-point borderline is used, i.e., patients with a score of 40 or more are defined as cancer patients, its sensitivity is significantly higher than that of the 50-point borderline, but its specificity and accuracy are significantly lower than that of the 50-point borderline. Therefore, a low logistic borderline is suitable for gastric cancer screening in populations, and a high logistic borderline is suitable for auxiliary diagnosis.

[0088] Consideration Although there is a large body of literature showing that miRNAs can be used as markers to diagnose cancer and other diseases, there is no consensus regarding the specific miRNA expression profiles for specific diseases. The use of miRNAs as diagnostic and prognostic markers may face some challenges (Tiberio et al., 2015). However, the miRNA markers screened in different studies can vary greatly (Leidner et al., 2013). Inconsistencies in the diagnostic steps and detection methods may lead to suboptimal selection of miRNA biomarkers for diagnosis and prognosis, and most of the findings in the literature have not been validated in large study cohorts.

[0089] The subject's health and treatment status, as well as environmental and genetic factors, may all influence the miRNA expression profile. If miRNA analysis is based only on samples from a single study cohort or the same location, the results may be biased. Therefore, to screen miRNA markers that can be applied to large populations, samples must be collected from a sufficiently large population and a well-designed and controllable data analysis workflow must be designed. The present invention fully validates the currently selected 12 miRNA biomarkers, which are validated in different patient cohorts from different study locations. Starting from the early development stage, the miRNA biomarkers are screened and validated in various cohorts. The selected 12 miRNAs will then be further validated in a larger prospective clinical trial involving 5,282 subjects. The 12 screened and validated miRNAs in a large number of subjects from multiple independent study cohorts ensure their robustness as biomarkers and can be applied to a wide range of populations to identify subjects at risk for gastric cancer.

[0090] The miRNA profile can also be affected by technical aspects, such as sample collection, processing steps, and methods for detecting miRNA expression levels in samples. The sensitivity and specificity for detecting changes in miRNA expression can vary significantly due to different detection methods. In most published studies, the sample collection and processing methods may be completely different. In addition, there are differences in the reagents and methods used in those studies. In this invention, semi-nested primers are designed based on the principles of Wan et al., 2010, and have been used to develop a highly sensitive and specific RT-qPCR method and optimal A streamlined miRNA expression profile and data analysis workflow is employed, and internal standards are used to check and adjust for differences in efficiency in miRNA extraction, reverse transcription, qPCR, and other steps. Additionally, a clinical validation study of 5,282 subjects employs more stringent methods than clinical validation of medical diagnostic tests (Wilson et al., 2008; Mattocks et al., 2010). The test kit is manufactured and operated under strict quality control requirements not common in clinical studies. The technical method of the present invention further ensures the validity and robustness of the 12 miRNA markers used to identify gastric cancer risk.

[0091] A prospective study to validate 12 miRNA biomarkers enrolled 5,282 subjects who were also tested for other risk factors associated with gastric cancer, such as Helicobacter pylori, pepsinogen I / II test, and gastroscopy. Results showed that the detection of the 12-miRNA combination significantly outperformed several conventional clinical tests for high-risk factors for gastric cancer, such as Helicobacter pylori and pepsinogen I / II, in identifying patients with gastric cancer. The 4-miRNA group had a more similar AUC compared to the pepsinogen I / II test (AUC = 0.62) and Helicobacter pylori (AUC = 0.64). MiRNA combinations with five or more miRNAs had superior AUCs for diagnosing gastric cancer (AUC = 0.8029 for the 5-miRNA group and 0.8423 for the 12-miRNA group). The AUC for miRNA detection consisting of five or more miRNAs is very similar to the AUC for gastroscopy, the current gold standard for gastric cancer diagnosis (AUC of 0.84).

[0092] Subjects determined to be at risk for gastric cancer may require further testing, such as gastroscopy, biopsy, or imaging studies such as magnetic resonance imaging (MRI) or computed tomography (CT). Patients diagnosed with gastric cancer receive appropriate treatment. Treatment of gastric cancer generally involves one or more of the following interventions: surgery, radiation therapy, chemotherapy or immunotherapy, or the use of targeted therapies such as trastuzumab or ramucirumab. Drug candidates for gastric cancer treatment include small molecules, antibodies, vaccines, or peptides. Chemotherapeutic agents for gastric cancer treatment include 5-fluorouracil, capecitabine, carboplatin, cisplatin, docetaxel, epirubicin, irinotecan, oxaliplatin, paclitaxel, trifluridine, and tipiracil. Immunotherapeutic agents for gastric cancer treatment include immune checkpoint inhibitors such as pembrolizumab. The treatment of choice for early-stage gastric cancer is usually surgery. For cancers detected early, endoscopic resection is also possible. It is generally believed that the therapeutic effect in patients with early-stage gastric cancer is significantly better than that in patients with advanced gastric cancer (Lello et al., 2007). Therefore, a reliable and easy-to-use detection method is essential for the early diagnosis of gastric cancer patients. This is very important for decision-making.

[0093] Therefore, the present invention provides detailed validation data from a large-scale clinical study on a combination of 12 miRNA biomarkers. Compared with traditional detection methods for assessing the risk of gastric cancer, the combination of miRNA markers can provide an AUC equivalent to that of gastroscopy for the diagnosis of gastric cancer, but without the invasiveness of gastroscopy and the associated risk of complications. An important principle of mass cancer screening is to adhere to regular screening to promote early detection of cancer. In this regard, blood-based tests, which require only one blood draw and provide reliable conclusions, are more promising than more invasive tests. This could be a promising direction for development.

Claims

1. A combination of peripheral blood miRNA markers for diagnosing gastric cancer, comprising at least five miRNA markers selected from hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

2. The combination of miRNA markers according to claim 1, characterized in that it consists of hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-142-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

3. The combination of miRNA markers according to claim 1, characterized in that it consists of hsa-miR-29c-3p, hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

4. The combination of miRNA markers according to claim 1, characterized in that it consists of hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-93-5p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

5. The combination of miRNA markers according to claim 1, characterized in that it consists of hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-126-3p, hsa-miR-183-5p, and hsa-miR-340-5p.

6. The combination of miRNA markers according to claim 1, characterized in that it consists of hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, hsa-miR-126-3p, and hsa-miR-340-5p.

7. The combination of miRNA markers according to claim 1, characterized in that it consists of hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, hsa-miR-30e-5p, and hsa-miR-340-5p.

8. The miRNA according to claim 1, characterized in that it consists of hsa-miR-424-5p, hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, and hsa-miR-340-5p. Marker combination.

9. The combination of miRNA markers according to claim 1, characterized in that it consists of hsa-miR-103a-3p, hsa-miR-181a-5p, hsa-miR-21-5p, hsa-miR-140-5p, and hsa-miR-340-5p.

10. a. detecting the expression level of the combination of miRNA markers of claim 1 in a peripheral blood sample of a subject; b. calculating and adjusting the subject's risk score relative to a non-cancer control sample; and c. Determining the likelihood that the subject will suffer from gastric cancer based on the risk score; A method for identifying a subject at risk for having gastric cancer.

11. 11. The method of claim 10, wherein a linear regression model is used to calculate the risk score.

12. The linear regression model is: [Equation 1] (In the formula, miRNA1, miRNA2, miRNA 3. ... is selected from the miRNA markers of claim 1; Ct is the relative expression level of each miRNA detected by qPCR; and K is the coefficient of each miRNA marker.

12. The method of claim 11, wherein the calculated value is:

13. The method of claim 10 , wherein the method comprises a qPCR method, a chip method, or a sequencing method for detecting miRNA markers.

14. A kit for diagnosing gastric cancer, comprising a reagent for specifically detecting the combination of miRNA markers according to claim 1.

15. The kit of claim 14, wherein the reagent comprises at least one oligonucleotide, at least a portion of which specifically binds to the miRNA marker of claim 1.

16. The kit of claim 15, wherein the kit comprises stem-loop reverse transcription primers and / or semi-nested qPCR primers for amplifying the miRNA markers of claim 1.

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