CN113186285A - Method for auxiliary diagnosis of gastric cancer and miRNA combination used in method - Google Patents
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Abstract
The invention discloses a method for early screening of gastric cancer, which comprises the following steps: performing binary Logistic regression analysis according to the expression quantities of miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p and miR-424-5p in peripheral blood samples of gastric cancer patients and healthy people to obtain a LogitP value calculation formula and determine a threshold value; detecting the expression quantity of the miRNA in the peripheral blood sample of the person to be detected and substituting the expression quantity into a LogitP value calculation formula to obtain the LogitP value of the person to be detected; then, the following judgment is made: if the LogitP value of the person to be detected is larger than the threshold value, the person to be detected suffers from gastric cancer; if the LogitP value of the subject is below the threshold value, the subject does not have gastric cancer. Experiments prove that the method for early screening the gastric cancer provided by the invention has good specificity, high sensitivity and high accuracy. The invention has important application value.
Description
Technical Field
The invention belongs to the field of biomedicine, and particularly relates to a method for auxiliary diagnosis of gastric cancer and a miRNA combination used in the method.
Background
Gastric cancer is a malignant tumor with a high incidence rate. At present, although the diagnosis and treatment market for gastric cancer is huge, a novel gastric cancer auxiliary diagnosis technology is generally lacked in the market. In order to accurately screen early gastric cancer, prevent the gastric cancer from developing into irreversible chronic diseases which seriously harm the health of people, reduce the physical quality of people and increase the burden of a medical system, the method has important significance for the prevention and treatment of cancer, particularly for early diagnosis, besides developing an effective treatment method. At present, the diagnosis of early gastric cancer still depends on endoscopy and histopathological examination, the degree of the examination willing to be made by the patient is reduced due to higher cost, more pain, higher operation requirement and the like, and the diagnosis of most gastric cancer patients with symptoms is already in the advanced stage due to the lack of systematic general examination and the lack of serological diagnosis markers with high sensitivity and strong specificity. Therefore, a simple, reliable, noninvasive or minimally invasive detection method for early screening of large-flux gastric cancer is important.
Currently, non-invasive methods that can aid in the diagnosis of gastric cancer are Circulating Tumor Cell (CTC) detection, circulating tumor DNA (ctdna) detection, DNA methylation detection, and high-throughput sequencing. However, the early detection sensitivity of CTC and ctDNA is low, the direction of DNA methylated gastric cancer is not deeply researched, the high-throughput sequencing is long in time and high in cost, and different methods have certain defects, so that the clinical application is limited.
miRNAs are a class of non-coding single-stranded RNA molecules whose endogenous genes encode a length of about 19-24 nt. Since miRNA can well identify and pair before transcribing gene and further regulate protein expression, it is closely related to biological process in animal body. Research shows that miRNA has close relation with various tumorigenesis, and may play an important role in regulation and control in the process of tumorigenesis and development like oncogenes or cancer suppressor genes. When the miRNA is abnormal in behavior, the disease can be caused, for example, miRNA-122 is a tumor marker for liver cancer cell pathogenesis. Moreover, mirnas are present not only in tissues and cells, but also stably in peripheral blood and body fluids. Therefore, miRNA is an important biological indicator in screening, diagnosing and treating many cancers.
Disclosure of Invention
The invention aims to early screen gastric cancer or evaluate the gastric cancer risk of a person to be tested.
The invention firstly protects a method for early screening of gastric cancer, which comprises the following steps:
(1) performing binary Logistic regression analysis according to the expression quantities of miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p and miR-424-5p in peripheral blood samples of a plurality of gastric cancer patients and peripheral blood samples of a plurality of healthy people to obtain a LogitP value calculation formula and determine a threshold value;
(2) detecting the expression quantities of miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p and miR-424-5p in a peripheral blood sample of the person to be detected, and substituting the expression quantities into the LogitP value calculation formula obtained in the step (1) to obtain the LogitP value of the person to be detected; then, the following judgment is made:
if the LogitP value of the subject is greater than the threshold value, the subject suffers from gastric cancer or is suspected to suffer from gastric cancer;
if the LogitP value of the subject is below the threshold value, the subject does not have gastric cancer or is suspected not to have gastric cancer;
the nucleotide sequence of the miR-126-3p is shown as SEQ ID NO 2;
the nucleotide sequence of the miR-150-5p is shown as SEQ ID NO. 3;
the nucleotide sequence of the miR-199a-3p is shown as SEQ ID NO. 4;
the nucleotide sequence of the miR-221-3p is shown as SEQ ID NO. 5;
the nucleotide sequence of the miR-424-5p is shown as SEQ ID NO 6;
the method is useful for diagnosis and treatment of non-diseases.
The above method can be used for preventing diseases.
In the above method, the expression level may be a relative expression level.
In the above method, the relative expression level may be an expression level of the target miRNA relative to an internal reference. The target miRNA can be miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p or miR-424-5 p. The internal reference can be miR-16-5 p. The nucleotide sequence of the miR-16-5p can be shown as SEQ ID NO. 1.
The invention also protects the application of the miRNA combination A in preparing a product for early screening of gastric cancer;
miRNA combination a may be a1) or a 2):
A1) comprising said miR-126-3p, said miR-150-5p, said miR-199a-3p, said miR-221-3p and said miR-424-5 p;
A2) consists of the miR-126-3p, the miR-150-5p, the miR-199a-3p, the miR-221-3p and the miR-424-5 p;
the use is for the diagnosis and treatment of non-diseases.
The invention also protects the application of the miRNA combination B in preparing a product for early screening of gastric cancer;
miRNA combination B may be B1) or B2):
B1) comprises the miR-16-5p, the miR-126-3p, the miR-150-5p, the miR-199a-3p, the miR-221-3p and the miR-424-5 p;
B2) consists of the miR-16-5p, the miR-126-3p, the miR-150-5p, the miR-199a-3p, the miR-221-3p and the miR-424-5 p;
the use is for the diagnosis and treatment of non-diseases.
The invention also provides a method for evaluating the risk of gastric cancer, which comprises the following steps:
(1) performing binary Logistic regression analysis according to the expression quantities of miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p and miR-424-5p in peripheral blood samples of a plurality of gastric cancer patients and peripheral blood samples of a plurality of healthy people to obtain a LogitP value calculation formula and determine a threshold value;
(2) detecting the expression quantities of miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p and miR-424-5p in a peripheral blood sample of the person to be detected, and substituting the expression quantities into the LogitP value calculation formula obtained in the step (1) to obtain the LogitP value of the person to be detected; then, the following judgment is made:
if the LogitP value of the person to be tested is larger than the threshold value, the risk that the person to be tested suffers from gastric cancer is high;
if the LogitP value of the person to be tested is below the threshold value, the risk that the person to be tested suffers from gastric cancer is low;
the nucleotide sequence of the miR-126-3p is shown as SEQ ID NO 2;
the nucleotide sequence of the miR-150-5p is shown as SEQ ID NO. 3;
the nucleotide sequence of the miR-199a-3p is shown as SEQ ID NO. 4;
the nucleotide sequence of the miR-221-3p is shown as SEQ ID NO. 5;
the nucleotide sequence of the miR-424-5p is shown as SEQ ID NO 6;
the method is useful for diagnosis and treatment of non-diseases.
The above method can be used for preventing diseases.
In the above method, the expression level may be a relative expression level.
In the above method, the relative expression level may be an expression level of the target miRNA relative to an internal reference. The target miRNA can be miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p or miR-424-5 p. The internal reference can be miR-16-5 p. The nucleotide sequence of the miR-16-5p can be shown as SEQ ID NO. 1.
In any of the above methods, the method for detecting the relative expression amounts of miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p and miR-424-5p in the peripheral blood sample can be as follows:
(1) obtaining cDNA of a peripheral blood sample;
(2) taking cDNA of a peripheral blood sample as a template, and carrying out real-time fluorescence quantitative PCR by using a primer pair consisting of a universal amplification primer (nucleotide sequence: 5'-CAGTGCAGGGTCCGAGGT-3') and a corresponding specific amplification primer of the target miRNA to obtain the expression quantity of the target miRNA; taking cDNA of a peripheral blood sample as a template, and carrying out real-time fluorescence quantitative PCR by adopting a primer pair consisting of a universal amplification primer and 5'-TTCGGTAGCAGCACGTAAATA-3' to obtain the expression quantity of miR-16-5 p;
(3) the results of Real-Time fluorescent quantitative PCR were passed through ABI 7300plus Real-Time PCR SoA software v2.4 output, i.e., Ct value for each sample; then calculating the Delta CtTarget miRNA，ΔCtTarget miRNA＝CtTarget miRNA-CtmiR-16-5p. The delta Ct is the relative expression quantity of the target miRNA (taking miR-16-5p as an internal reference).
In the step (1), the cDNA of the peripheral blood sample is obtained by reverse transcription with reverse transcriptase by using RNA of the peripheral blood sample as a template. The RT primer for reverse transcription may be 5 '-CAGTGCAGGGTCCGAGGTCAGAGCCACCTGGGCAATTTTTTTTTTTVN-3'.
In the step (2), the nucleotide sequence of the specific amplification primer of the target miRNA is shown in Table 2.
The application of any miRNA combination A in preparing a product for evaluating the risk of gastric cancer also belongs to the protection scope of the invention;
the use is for the diagnosis and treatment of non-diseases.
The application of any miRNA combination B in preparing a product for evaluating the risk of gastric cancer also belongs to the protection scope of the invention;
the use is for the diagnosis and treatment of non-diseases.
In one embodiment of the invention, expression amounts of miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p and miR-424-5p in peripheral blood samples of 140 healthy people and peripheral blood samples of 60 gastric cancer patients are detected, binary Logistic regression analysis is carried out, and a LogitP value calculation formula is obtained as follows: LogitP ═ Δ CtmiR-126-3p×(3.076)+ΔCtmiR-150-5p×(-7.676)+ΔCtmiR-199a-3p×(-1.758)+ΔCtmiR-221-3p×5.262+ΔCtmiR-424-5pX (-1.603) + 2.095. From the LogitP values of these 200 samples, ROC curves were made using MedCalc 19. The results showed a sensitivity of 90.00% for gastric cancer diagnosis, a specificity of 90.71% and a threshold of-0.0852.
Experiments prove that the early screening gastric cancer or gastric cancer risk assessment method provided by the invention has the advantages of good specificity, high sensitivity and high accuracy. The invention has important application value.
Drawings
Fig. 1 is a ROC curve prepared using the LogitP values of MedCalc 19 versus 200 samples.
Detailed Description
The present invention is described in further detail below with reference to specific embodiments, which are given for the purpose of illustration only and are not intended to limit the scope of the invention. The examples provided below serve as a guide for further modifications by a person skilled in the art and do not constitute a limitation of the invention in any way.
The experimental procedures in the following examples, unless otherwise indicated, are conventional and are carried out according to the techniques or conditions described in the literature in the field or according to the instructions of the products. Materials, reagents and the like used in the following examples are commercially available unless otherwise specified.
In the examples below, statistical analysis was performed using SPSS 25.0 software, and P <0.05 was considered statistically significant.
In the examples described below, the names and nucleotide sequences of the 10 mirnas are shown in table 1 on lines 2 to 11.
TABLE 1
Examples of the following,
First, obtaining of Positive and negative samples
1. Gastric cancer group
The gastric cancer group consists of 79 positive samples which are sequentially named as P001-P079.
5-6mL of peripheral blood of 79 patients (all patients are informed) clinically diagnosed with gastric cancer is respectively extracted, placed in an EDTA-containing anticoagulated blood collection tube, turned upside down for 5-6 times (the aim is to uniformly mix the anticoagulated liquid and the peripheral blood), and then centrifuged at 3000rpm for 10min, and supernatant is collected to obtain 79 positive samples.
2. Healthy control group
The healthy control group consisted of 163 negative samples, designated N001-N163 in that order.
Separately, 5-6mL of peripheral blood of 163 healthy persons (informed consent) was collected, placed in an EDTA-containing anticoagulated blood collection tube, and inverted 5-6 times from top to bottom (in order to mix the anticoagulated solution and the peripheral blood uniformly), and then centrifuged at 3000rpm for 10min, and the supernatant was collected to obtain 163 negative samples.
II, obtaining cDNA
1. 242 samples (i.e., 79 positive samples and 163 negative samples) were taken, and corresponding plasma was obtained.
2. 242 parts of plasma RNA were extracted using TRIzol reagent, and 242 samples of RNA were obtained.
3. After completion of step 2, (a small) 242 samples of RNA were each taken and quantified using Qubit 4.0(Life Technologies) (i.e. the concentration of RNA in 242 samples was measured).
4. After completion of step 3, 242 samples of RNA were each used as a template (about 10ng of RNA) and reverse transcription was carried out using reverse transcriptase to obtain the corresponding cDNA. The RT primer for reverse transcription was 5 '-CAGTGCAGGGTCCGAGGTCAGAGCCACCTGGGCAATTTTTTTTTTTVN-3'.
Screening of target miRNA and auxiliary diagnosis of gastric cancer based on relative expression quantity of 5 target miRNA
The target miRNA is miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p, miR-424-5p, miR-21-5p, miR-182-5p, miR-195-5p or miR-214-3 p.
1. Real-time fluorescent quantitative PCR detection
And (3) respectively taking the cDNA obtained in the second step as a template, and carrying out real-time fluorescence quantitative PCR (three parallel samples are made for each template) by using a primer pair consisting of a universal amplification primer (nucleotide sequence: 5'-CAGTGCAGGGTCCGAGGT-3') and a corresponding specific amplification primer of the target miRNA to obtain the expression quantity of the target miRNA. The nucleotide sequence of the specific amplification primer of the target miRNA is shown in Table 2.
TABLE 2
| Target miRNA | Nucleotide sequence of specific amplification primer (5 '-3') |
| miR-126-3p | TCGGTCGTACCGTGAGTAAT |
| miR-150-5p | CGGTCTCCCAACCCTTGTA |
| miR-199a-3p | TCGGACAGTAGTCTGCACAT |
| miR-221-3p | TGGAGCTACATTGTCTGCTG |
| miR-424-5p | TCGGCAGCAGCAATTCATGT |
| miR-21-5p | TTCGGTAGCTTATCAGACTGA |
| miR-182-5p | TGGTTTGGCAATGGTAGAACT |
| miR-195-5p | GTCGGTAGCAGCACAGAAAT |
| miR-214-3p | TGGACAGCAGGCACAGACA |
And (3) respectively taking the cDNA obtained in the second step as a template, and carrying out real-time fluorescence quantitative PCR (making three parallel samples for each template) by using a primer pair consisting of a universal amplification primer and 5'-TTCGGTAGCAGCACGTAAATA-3' to obtain the expression quantity of the miR-16-5 p.
2. The Real-Time fluorescent quantitative PCR result obtained in step 1 is output by ABI 7300plus Real-Time PCR Software v2.4 (product of Thermo Fisher Scientific, USA), i.e., Ct value of each sample. The smaller the Ct value, the higher the expression level of the target miRNA (a Ct value greater than 35 was considered as non-expression by statistical analysis). Then calculating the Delta CtTarget miRNA，ΔCtTarget miRNA＝CtTarget miRNA-CtmiR-16-5p. The delta Ct is the relative expression quantity of the target miRNA (taking miR-16-5p as an internal reference).
The Ct of the target miRNA in 200 samples is shown in the table 3-1 and the table 3-2.
TABLE 3-1
TABLE 3-2
3. Screening of target MiRNAs
And (3) carrying out statistical analysis on the relative expression quantity (taking miR-16-5p as an internal reference) of the 9 miRNAs in the step 2 by adopting SPSS 25.0 software. The results show that miR-21-5p, miR-182-5p, miR-195-5p and miR-214-3p have no significant difference between the positive sample and the negative sample. Therefore, the final identified miRNAs for auxiliary diagnosis purpose are 5 miRNAs, namely miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p and miR-424-5 p.
4. Auxiliary diagnosis
(1) According to the Delta Ct in 200 samplesmiR-126-3p、ΔCtmiR-150-5p、ΔCtmiR-199a-3p、ΔCtmiR-221-3pAnd Δ CtmiR-424-5pBinary Logistic regression analysis (forward LR) was performed using SPSS 25.0, yielding the following formula:
LogitP＝ΔCtmiR-126-3p×(3.076)+ΔCtmiR-150-5p×(-7.676)+ΔCtmiR-199a-3p×(-1.758)+ΔCtmiR-221-3p×5.262+ΔCtmiR-424-5p×(-1.603)+2.095
(2) the LogitP value for each sample was calculated according to the above formula, and then an ROC curve was generated using MedCalc 19.
The ROC curve is shown in FIG. 1. The results showed a sensitivity of 90.00% for gastric cancer diagnosis, a specificity of 90.71%, and a threshold of-0.0852, i.e. if LogitP > -0.0852, the sample is positive, i.e. the provider of the sample has gastric cancer; otherwise the provider of the sample does not have gastric cancer.
5. Authentication
The assay was performed on the other 42 samples in step 2, specifically 19 positive samples (sample numbers P61-P79) and 23 negative samples (sample numbers N141-N163).
The Ct of 6 mirnas for 42 samples is shown in table 4.
TABLE 4
The delta Ct values in 42 samples were eachmiR-126-3p、ΔCtmiR-150-5p、ΔCtmiR-199a-3p、ΔCtmiR-221-3pAnd Δ CtmiR-424-5pSubstituting the formula in the step 4 to obtain a corresponding LogitP value, and judging as follows: LogitP>0.0852, the sample is positive, i.e. the provider of the sample has gastric cancer; otherwise the provider of the sample does not have gastric cancer.
The results are shown in Table 5.
TABLE 5
Kappa consistency checks were performed using SPSS 25.0 software. The Kappa value was 0.8078, which is more consistent.
The results show that the method provided by the invention has higher accuracy in detecting the gastric cancer.
The present invention has been described in detail above. It will be apparent to those skilled in the art that the invention can be practiced in a wide range of equivalent parameters, concentrations, and conditions without departing from the spirit and scope of the invention and without undue experimentation. While the invention has been described with reference to specific embodiments, it will be appreciated that the invention can be further modified. In general, this application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. The use of some of the essential features is possible within the scope of the claims attached below.
<110> Shenzhen exhibition Living Ltd
<120> method for auxiliary diagnosis of gastric cancer and miRNA combination used in same
<160>10
<170> PatentIn version 3.5
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Claims (10)
1. A method for early screening of gastric cancer comprises the following steps:
(1) performing binary Logistic regression analysis according to the expression quantities of miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p and miR-424-5p in peripheral blood samples of a plurality of gastric cancer patients and peripheral blood samples of a plurality of healthy people to obtain a LogitP value calculation formula and determine a threshold value;
(2) detecting the expression quantities of miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p and miR-424-5p in a peripheral blood sample of the person to be detected, and substituting the expression quantities into the LogitP value calculation formula obtained in the step (1) to obtain the LogitP value of the person to be detected; then, the following judgment is made:
if the LogitP value of the subject is greater than the threshold value, the subject suffers from gastric cancer or is suspected to suffer from gastric cancer;
if the LogitP value of the subject is below the threshold value, the subject does not have gastric cancer or is suspected not to have gastric cancer;
the nucleotide sequence of the miR-126-3p is shown as SEQ ID NO 2;
the nucleotide sequence of the miR-150-5p is shown as SEQ ID NO. 3;
the nucleotide sequence of the miR-199a-3p is shown as SEQ ID NO. 4;
the nucleotide sequence of the miR-221-3p is shown as SEQ ID NO. 5;
the nucleotide sequence of the miR-424-5p is shown as SEQ ID NO 6;
the method is useful for diagnosis and treatment of non-diseases.
2. The method of claim 1, wherein: the expression amount is a relative expression amount.
3. The method of claim 2, wherein: the relative expression quantity is the expression quantity of the target miRNA relative to the internal reference;
the target miRNA is miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p or miR-424-5 p;
the internal reference is miR-16-5 p;
the nucleotide sequence of the miR-16-5p is shown in SEQ ID NO 1.
4, application of the miRNA combination A in preparation of a product for early screening of gastric cancer;
miRNA combination a is a1) or a 2):
A1) comprises the miR-126-3p, the miR-150-5p, the miR-199a-3p, the miR-221-3p and the miR-424-5p in the claim 1;
A2) consists of the miR-126-3p, the miR-150-5p, the miR-199a-3p, the miR-221-3p and the miR-424-5p in claim 1;
the use is for the diagnosis and treatment of non-diseases.
5, application of the miRNA combination B in preparation of a product for early screening of gastric cancer;
miRNA combination B1) or B2):
B1) comprises the miR-16-5p in claim 3, the miR-126-3p in claim 1, the miR-150-5p, the miR-199a-3p, the miR-221-3p and the miR-424-5 p;
B2) consists of the miR-16-5p in claim 3, the miR-126-3p in claim 1, the miR-150-5p, the miR-199a-3p, the miR-221-3p and the miR-424-5 p;
the use is for the diagnosis and treatment of non-diseases.
6. A method of assessing the risk of gastric cancer comprising the steps of:
(1) performing binary Logistic regression analysis according to the expression quantities of miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p and miR-424-5p in peripheral blood samples of a plurality of gastric cancer patients and peripheral blood samples of a plurality of healthy people to obtain a LogitP value calculation formula and determine a threshold value;
(2) detecting the expression quantities of miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p and miR-424-5p in a peripheral blood sample of the person to be detected, and substituting the expression quantities into the LogitP value calculation formula obtained in the step (1) to obtain the LogitP value of the person to be detected; then, the following judgment is made:
if the LogitP value of the person to be tested is larger than the threshold value, the risk that the person to be tested suffers from gastric cancer is high;
if the LogitP value of the person to be tested is below the threshold value, the risk that the person to be tested suffers from gastric cancer is low;
the nucleotide sequence of the miR-126-3p is shown as SEQ ID NO 2;
the nucleotide sequence of the miR-150-5p is shown as SEQ ID NO. 3;
the nucleotide sequence of the miR-199a-3p is shown as SEQ ID NO. 4;
the nucleotide sequence of the miR-221-3p is shown as SEQ ID NO. 5;
the nucleotide sequence of the miR-424-5p is shown as SEQ ID NO 6;
the method is useful for diagnosis and treatment of non-diseases.
7. The method of claim 6, wherein: the expression amount is a relative expression amount.
8. The method of claim 7, wherein: the relative expression quantity is the expression quantity of the target miRNA relative to the internal reference;
the target miRNA is miR-126-3p, miR-150-5p, miR-199a-3p, miR-221-3p or miR-424-5 p;
the internal reference is miR-16-5 p;
the nucleotide sequence of the miR-16-5p is shown in SEQ ID NO 1.
9. Use of the miRNA combination A of claim 4 for the preparation of a product for assessing the risk of gastric cancer;
the use is for the diagnosis and treatment of non-diseases.
10. Use of a combination b of mirnas as claimed in claim 5 in the manufacture of a product for assessing the risk of gastric cancer;
the use is for the diagnosis and treatment of non-diseases.
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