MicroRNA miR-126-3p and its application

Abstract

The present invention relates to a micro RNA miR-126-3p and its application. The present invention proposes a new standard for accurately predicting the therapeutic effect of UDCA treatment in PBC patients from the perspective of miRNA, so that before the first UDCA treatment of PBC patients, by detecting the micro RNA miR-126-3p, it is possible to accurately know whether the UDCA treatment is sensitive or ineffective for the patient, so that the clinician can take measures in advance, try other treatment methods while UDCA treatment, and improve the treatment effect of the patient; for some patients with very poor efficacy, liver sources can be contacted in advance to improve the survival rate of the patient.

Description

Technical Field

[0001] The present invention relates to the field of medical technology, and in particular to a micro RNA miR-126-3p and an application thereof. Background Art

[0002] Primary biliary cirrhosis (PBC) is an autoimmune-mediated chronic inflammatory, cholestatic liver disease. In my country, PBC was previously considered a rare disease, but with the improvement of clinical physicians' understanding of PBC, the development of anti-mitochondrial antibody (AMA) testing, and changes in environmental factors, the number of confirmed cases of PBC has increased year by year, becoming another liver disease that threatens the health of the Chinese people. Ursodeoxycholic acid (UDCA) is the only drug approved by the US FDA for the treatment of PBC. About 60% of PBC patients respond well to UDCA treatment, and their quality of life and survival are similar to those of the general healthy population; however, 40% of PBC patients still respond poorly to UDCA, and the disease rapidly progresses to the extent of cirrhosis and liver failure, and eventually develops to the extent of requiring liver transplantation, and even death occurs. How to quickly and accurately predict the efficacy of UDCA in patients so as to adjust the drug in time for patients with poor efficacy is a problem that all clinicians are concerned about and urgently need to solve.

[0003] The efficacy evaluation currently used is mainly judged by biochemical indicators. Different regions and countries have their own different standards (such as the Barcelona standard in Spain, the Paris I standard in France, etc.). However, these standards are time-consuming, have many detection indicators, and are not convenient to use. MiRNA in the blood can be free from cells and stably exist in the circulating blood. Its abnormal expression in tissues and serum is closely related to a variety of human diseases, and has shown unique value in the diagnosis and prognosis of a variety of diseases. MiRNA in plasma or serum has been successfully used for early diagnosis, prognosis, and efficacy evaluation of a variety of diseases (such as tumors, sepsis, heart failure, etc.). There have been preliminary reports on the correlation and some mechanisms between miRNA and PBC patients, but there has been no report on whether there is a difference in the expression of miRNA in circulating blood between different efficacy groups of PBC patients. More importantly, whether this difference can be used as a marker to predict efficacy and a target for future treatment is also unknown. Summary of the invention

[0004] The object of the present invention is to provide a marker that can be used to predict the sensitivity of primary biliary cholangitis patients to ursodeoxycholic acid treatment.

[0005] The present invention provides a micro RNA miR-126-3p, characterized in that the nucleotide sequence of the micro RNA miR-126-3p is shown in SEQ ID NO.1.

[0006] The present invention also provides the use of the microRNA miR-126-3p as a marker in the preparation of a product for predicting the sensitivity of primary biliary cholangitis patients to ursodeoxycholic acid treatment.

[0007] In some embodiments, when the product detects that the expression level of the microRNA miR-126-3p is higher than 0.786, it is predicted that the corresponding primary biliary cholangitis patient is sensitive to ursodeoxycholic acid treatment.

[0008] In some embodiments, the product is a reagent, a kit, or a device.

[0009] The present invention also provides the use of a detection reagent for the micro RNA miR-126-3p in the preparation of a product for predicting the sensitivity of primary biliary cholangitis patients to ursodeoxycholic acid treatment.

[0010] The present invention also provides a kit for predicting the sensitivity of primary biliary cholangitis patients to ursodeoxycholic acid treatment, comprising a reagent for detecting the microRNA miR-126-3p suitable for at least one of the following methods:

[0011] Fluorescent dye method, digital PCR, resonance light scattering method, real-time fluorescence quantitative PCR, sequencing or biological mass spectrometry.

[0012] In some embodiments, an upstream primer and a downstream primer are included for detecting the microRNA miR-126-3p by RT-PCR.

[0013] In some embodiments, the nucleotide sequences of the upstream primer and the downstream primer are shown as SEQ ID NO.2 and SEQ ID NO.3, respectively.

[0014] In some embodiments, an RNA extraction reagent and a reverse transcription primer are also included. Optionally, the sequence of the reverse transcription primer is shown in SEQ ID NO.6.

[0015] In some embodiments, a primer pair for detecting an internal reference gene is also included, and the nucleotide sequences thereof are shown as SEQ ID NO.4 and SEQ ID NO.5, respectively.

[0016] In this study, 5 patients were selected from each group. Serum samples of PBC patients in the sensitive group and the drug-resistant group before the first treatment and serum samples of patients in the sensitive group after treatment were used as research objects. MiRNAs sequencing was performed to obtain the differential expression profiles of miRNAs in the two groups before treatment and the differential expression profiles of miRNAs in the sensitive group before and after treatment. On the basis of the presence of differential miRNAs in the two groups before treatment, the differentially expressed miRNAs in the sensitive group before and after treatment were excluded, and the miRNAs with stable differences before and after treatment in the two groups were determined. On the basis of the presence of differential miRNAs in the two groups before treatment, the differentially expressed miRNAs in the sensitive group before and after treatment were merged to find miRNAs that had significant changes in the sensitive group after UDCA treatment and that were different between the two groups before treatment. A total of 10 serum samples of PBC patients in the sensitive group and the drug-resistant group before and after treatment were used as research objects. Based on the previous miRNAs sequencing and screening results, the selected miRNAs were verified by qRT-PCR. The trend of changes was studied, and among the screened miRNAs, the stable differential miRNAs before and after treatment were determined. At the same time, we searched for miRNAs whose levels were close to those before treatment in the sensitive / resistant group after UDCA treatment, but more significantly different in the resistant / sensitive group, that is, miRNAs with significant differences before and after treatment. We further verified the results by using qRT-PCR of serum samples of the remaining 30 patients in the two groups before and after treatment. We studied the baseline differences in miRNA expression levels and the relationship between changes in miRNA levels before and after UDCA treatment and related biochemical indicators (AST, ALP, TBIL, etc.). According to the changes in serum miRNAs, the receiver operating characteristic curve (ROC) was used to evaluate the efficacy prediction performance of candidate miRNAs, and finally the efficacy prediction miRNAs were determined.

[0017] The scheme of the present invention can accurately know whether UDCA treatment is sensitive or ineffective for PBC patients before the first UDCA treatment. Then clinicians can take measures in advance and try other treatment methods (such as mesenchymal stem cell treatment, immunosuppressant treatment, etc.) while UDCA treatment to improve the treatment effect of patients; for some patients with poor efficacy, liver sources can be contacted in advance to improve the survival rate of patients. The results of this study can enable patients to predict the efficacy through testing before receiving UDCA treatment, plan and adjust the treatment plan in advance, improve the treatment effect and survival rate of patients, and save treatment time and treatment costs. The results of this study can also be used as markers for predicting efficacy and targets for future treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1A schematic diagram of serum collection time and treatment process according to an embodiment of the present invention;

[0019] Figure 2 This is a hotspot map of differential miRNAs expression between the drug-resistant group and the sensitive group before treatment in one embodiment of the present invention;

[0020] Figure 3 This is a hotspot map of differential miRNAs expression in the sensitive group before and after treatment according to an embodiment of the present invention;

[0021] Figure 4 qRT-PCR validation of the research subjects in the sequencing phase of one embodiment of the present invention;

[0022] Figure 5 qRT-PCR verification of the research object in the verification phase of one embodiment of the present invention;

[0023] Figure 6 The ROC curve analysis of miR-126-3p predicting therapeutic efficacy according to one embodiment of the present invention is shown;

[0024] Figure 7 This is a comparison of the expression levels of miR-126-3p before and after treatment in one embodiment of the present invention;

[0025] Figure 8 This is the correlation between miR-126-3p and clinical indicators according to one embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to more concisely and clearly show the technical solutions, purposes and advantages of the present invention, the present invention is further described in detail below in conjunction with specific embodiments and accompanying drawings thereof. It is understood that those skilled in the art can refer to the contents of this article and appropriately improve the process parameters to achieve. It is particularly important to point out that all similar replacements and modifications are obvious to those skilled in the art, and they are all deemed to be included in the present invention. The methods and applications of the present invention have been described through preferred embodiments, and relevant personnel can obviously modify or appropriately change and combine the methods and applications described herein without departing from the content, spirit and scope of the present invention to implement and apply the technology of the present invention.

[0027] 1. Experimental steps

[0028] 1. Sample clinical data

[0029] 1.1 Basic Information

[0030] This study selected 40 PBC patients with complete follow-up data for more than 1 year who visited the Fifth Medical Center of PLA General Hospital from January 2017 to June 2020. Patient history, baseline characteristics, laboratory indicators, and serum samples before and after treatment were collected. All serum specimens were stored in a -80°C refrigerator in the biospecimen bank of the Fifth Center of PLA General Hospital. According to the Paris I standard, that is, TBIL≤1mg / dl (17umol / L), ALP≤3ULN, and AST≤2ULN after 1 year of UDCA treatment, all PBC patients who received UDCA standard dosing treatment for 1 year were evaluated for efficacy. Patients who met the Paris I standard were included in the UDCA effective treatment group (sensitive group), and the remaining PBC patients who did not meet the Paris I standard were included in the UDCA ineffective treatment group (resistant group). The basic information of the two groups of patients was statistically analyzed. There were 22 cases in the UDCA effective group (sensitive group), including 20 females and 2 males, with an average age of (47.95±9.17) years old; there were 18 cases in the UDCA ineffective group (resistant group), all of whom were females, with an average age of (53.28±9.37) years old. This study was approved by the Medical Ethics Committee of the Fifth Medical Center of the PLA General Hospital (2016-211-D), and informed written consent was obtained from each patient and their family members.

[0031] 1.2 Inclusion criteria of patients included in the analysis

[0032] 1) Patients aged between 18 and 75 years old; diagnosed with PBC in accordance with the diagnostic criteria for PBC published by AASLD; 2) not receiving regular UDCA standard dosing treatment when first diagnosed with PBC; 3) receiving regular UDCA treatment during follow-up; 4) completing follow-up for more than 48 weeks, and conducting follow-up at 48 weeks, with serological specimens that meet the requirements for the "Paris I Criteria" evaluation retained; 5) obtaining informed consent from the patient and signing the informed consent form.

[0033] 1.3 Exclusion criteria for patients included in the analysis

[0034] 1) Patients with other viral infections, such as hepatitis A, hepatitis B, hepatitis E, cytomegalovirus infection, HIV infection, etc.; 2) Patients with other liver diseases, including alcoholic liver disease, drug-induced hepatitis, autoimmune hepatitis, Wilson's disease, etc.; 3) Failure of important organs (heart, kidney or respiratory system, etc.); 4) Pregnancy; 5) Presence of any potential tumor; 6) Receiving immunosuppressive drugs or any experimental drug treatment during the trial or within 6 months before the trial; 7) Failure to obtain informed consent from the patient or the patient fails to sign the informed consent form.

[0035] 2. Test process

[0036] 2.1 Sequencing and screening of miRNAs

[0037] In this study, 5 cases were selected from each group of patients. Serum samples of PBC patients in the sensitive group and the resistant group before the first treatment and serum samples of patients in the sensitive group after treatment were used as research objects. MiRNAs sequencing and further analysis were performed to obtain the differential expression profiles of miRNAs in the two groups before treatment and the differential expression profiles of miRNAs in the sensitive group before and after treatment. On the basis of the presence of differential miRNAs in the two groups before treatment, the differentially expressed miRNAs in the sensitive group before and after treatment were excluded, and the miRNAs with stable differences before and after treatment in the two groups of patients were determined. On the basis of the presence of differential miRNAs in the two groups before treatment, the differentially expressed miRNAs in the sensitive group before and after treatment were merged, and miRNAs that had significant changes in the sensitive group patients after UDCA treatment and were different in the two groups of patients before treatment were found.

[0038] 2.2 PCR validation of miRNAs

[0039] The serum samples of 10 patients with PBC in the sensitive group and the drug-resistant group sequenced in the previous stage before and after treatment were used as the research objects. Based on the results of the previous miRNAs sequencing and screening, the selected miRNAs were verified by qRT-PCR. The trend of change was studied, and the stable difference miRNAs before and after treatment were determined among the screened miRNAs. At the same time, miRNAs were found that were close to the pre-treatment levels in the sensitive group / resistant group patients after UDCA treatment, but the difference was more obvious in the drug-resistant group / sensitive group patients, that is, miRNAs with significant differences before and after treatment. The serum samples of the remaining 30 patients in the two groups before and after treatment were further verified by qRT-PCR.

[0040] 2.3 Target miRNAs and clinical relevance

[0041] The baseline differences in miRNAs expression levels and the relationship between changes in miRNAs levels before and after UDCA treatment and related biochemical indicators (AST, ALP, TBIL, etc.) were studied.

[0042] 2.4 Prediction of therapeutic efficacy of target miRNAs

[0043] According to the changes of serum miRNAs, the receiver operating characteristic curve (ROC) was used to evaluate the efficacy prediction performance of candidate miRNAs, and the efficacy prediction miRNAs were determined, such as Figure 1 shown.

[0044] 3. Specific methods

[0045] 3.1 Extraction and screening of miRNAs

[0046] A total of 40 samples of serum RNA from the sensitive group and the drug-resistant group were stored on ice and transported to Beijing Baiti Biotechnology Co., Ltd. on the same day under dry ice conditions. Five samples from each of the sensitive group and the drug-resistant group were taken out, and after the serum RNA quality was qualified, each serum RNA was sequenced to establish two groups of serum miRNA expression profiles.

[0047] 3.1.1 The main experimental reagents and consumables for miRNA sequencing are as follows (Table 1-1):

[0048] Table 1-1 Main experimental reagents and consumables involved in the experiment

[0049]

[0050] 3.1.2 The main experimental instruments and equipment for miRNAs sequencing are as follows (Table 1-2):

[0051] Table 1-2 Main instruments, equipment and software involved in the experiment

[0052]

[0053] 3.1.3 Extraction of serum RNA

[0054] In this study, serum RNA was extracted using the Norgen 51000 kit according to the instructions.

[0055] 1). Add 0.2 ml Slurry C2 and 1.8 ml Lysis Buffer A to a 50 ml test tube. Vortex mix for 15 seconds;

[0056] 2) The mixture in step 1 was allowed to stand at 60°C for 10 minutes;

[0057] 3). Add 3 ml of 96-100% ethanol. Vortex and mix for 15 seconds;

[0058] 4). Centrifuge at 1000RPM for 30 seconds, then carefully pour out the supernatant;

[0059] 5). Add 0.3 ml of Lysis Buffer A to the precipitate and vortex for 15 seconds to mix thoroughly;

[0060] 6) The mixture in step 5 was allowed to stand at 60°C for 10 minutes;

[0061] 7). Add 3 ml of 96-100% ethanol. Vortex to mix for 15 seconds;

[0062] 8). Transfer 650 μl of the mixture in step 7 to the Mini Filter Spin Column and centrifuge at 14,000 RPM for 1 minute; discard the waste liquid and reassemble the spin column with a collection tube;

[0063] 9). Repeat step 8 until all the mixture in step 7 is transferred to the Mini Filter Spin Column;

[0064] 10). Add 400 μl Wash Solution A to the column and centrifuge at 14,000 RPM for 1 minute; discard the waste liquid and reassemble the column with a collection tube;

[0065] 11). Repeat step 10 twice, washing 3 times in total;

[0066] 12). Spin the empty column at 14000 RPM for 3 minutes; discard the collection tube;

[0067] 13). Transfer the spin column to a new 1.7 ml elution tube; add 100 μl Elution Solution A to the spin column and centrifuge at 2000 RPM for 2 minutes, then centrifuge at 14000 RPM for 3 minutes.

[0068] 3.1.4 Extraction RNA quality control process

[0069] The integrity of RNA was tested by bioanalyzer (Agilent, CA, USA) and RNA quality inspection kit: RNA 6000Nano LabChip Kit (Agilent, CA, USA). The concentration was >50 ng / μl. The RNA integrity was based on the RIN value requirements: >6.3; OD260 / 280>1.8; total RNA>1μg.

[0070] 3.1.5 High-throughput sequencing to detect miRNA expression profiles

[0071] The experimental process was performed according to the Illumina standard steps, including library preparation and sequencing experiments. The small RNA sequencing library was prepared using the TruSeq Small RNA Sample Prep Kits (Illumina, San Diego, USA) and followed the standard steps provided. The 3'UTR and 5'UTR were connected at both ends, and the first-strand cDNA was synthesized by reverse transcription through PCR amplification, followed by PCR library amplification, and then the library was purified to construct the small RNA sequencing library. After the library preparation was completed, the constructed library was sequenced using Illumina Hiseq2000 / 2500, and the sequencing read length was single-end 1x50bp.

[0072] 3.1.6 Information Analysis Process

[0073] The miRNA data analysis software provided is ACGT101-miR. The analysis process of the software is as follows: (1) Remove 3' linkers and junk sequences: obtain clean data; (2) Length screening: retain sequences with base lengths of 18-25nt for plants and 18-26nt for animals; (3) Comparison and analysis of various RNA databases: compare the remaining sequences (excluding miRNA) with the mRNA, RFam and Repbase databases and filter them; (4) miRNA identification: obtain valid data and compare precursors and genomes for miRNA identification; (5) miRNA differential analysis; (6) Differential miRNA target gene prediction analysis. The specific experimental process was completed with the assistance of Beijing Baiti Biotechnology Co., Ltd.

[0074] 3.1.7 miRNA expression and differential analysis

[0075] According to different experimental designs, suitable difference test methods were used to screen genes with significant differences, such as Fisher's exact test, chi-square (2*2), chi-square (N*N), T test, and ANOVA algorithms. For sample analysis with biological replication, the screening of differentially expressed genes was based on P≤0.05 as the threshold; for sample analysis without biological replication, the screening of differentially expressed genes was based on |log2(Fold change)|>1 (i.e., two-fold difference) and P≤0.05 as the threshold.

[0076] 3.2 qRT-PCR validation of miRNAs

[0077] 3.2.1 The main experimental reagents and consumables of qRT-PCR are as follows (Table 1-3):

[0078] Table 1-3 Main experimental reagents and consumables involved in the experiment

[0079]

[0080] 3.2.2 The main experimental instruments and equipment for qRT-PCR are as follows (Table 1-4):

[0081] Table 1-4 Main instruments and equipment involved in the experiment

[0082]

[0083] 3.2.3 Extraction of serum RNA

[0084] 1). Take out the serum and thaw it at 4℃.

[0085] 2) Add 1 ml of QIAzol Lysis Reagent to every 200 μl of serum. Vortex up and down for 15 seconds to mix the sample.

[0086] 3). Let stand at room temperature (15–25°C) for 5 minutes.

[0087] 4).Add 3.5μl MiRNeasy Serum / Plasma Spike-In Control(1.6x10 8 copies / μl).

[0088] 5). Add 200 μl of chloroform to every 200 μl of starting serum. Shake vigorously for 15 seconds.

[0089] 6). Let stand at room temperature for 2-3 minutes.

[0090] 7). Centrifuge at 12,000 x g for 15 minutes at 4°C.

[0091] 8) Transfer the upper aqueous phase to a new collection tube using a pipette. Avoid transferring the interphase during the process. Add 900 μl of ethanol to every 600 μl of sample.

[0092] 9). Transfer 700 μl of sample (including any precipitate) into a 2 ml collection tube and add to the RNeasy MinElute spin column. Centrifuge at 8000 x g for 15 seconds at room temperature. Discard the waste liquid.

[0093] 10) Repeat step 9 above with the remaining samples.

[0094] 11). Add 700 μl Buffer RWT to the RNeasy MinElute spin column. Centrifuge at 8000 x g for 15 seconds. Discard the waste liquid.

[0095] 12). Add 500 μl Buffer RPE to the RNeasy MinElute spin column. Centrifuge at 8000 x g for 15 seconds. Discard the waste solution.

[0096] 13). Add 500 μl of 80% ethanol to the RNeasy MinElute spin column. Centrifuge at 8000 x g for 2 minutes. Discard the waste liquid.

[0097] 14). Transfer the RNeasy MinElute spin column to a new 2 ml collection tube. Open the spin column cap and centrifuge at 12000 x g for 5 minutes. Discard the waste liquid.

[0098] 15). Transfer the RNeasy MinElute spin column to a new 1.5 ml collection tube. Add 14 μl of RNase-free water directly to the center of the spin column membrane. Close the cap and centrifuge at 12,000 x g for 1 minute to elute the RNA.

[0099] 3.2.4 qPCR detection process of miRNAs

[0100] The primers required for qRT-PCR were selected and synthesized based on the high-throughput sequencing results, and U6 was used as an internal reference.

[0101] 3.2.4.1 cDNA first strand synthesis (20 μl system):

[0102] (1) Before using the RNA sample, each component was gently mixed and then centrifuged at 2000 rpm for 20 seconds;

[0103] (2) Take a sterilized, nuclease-free 0.2 mL PCR tube and add the following components (Table 1-5) in order:

[0104] Table 1-5 Reverse transcription reaction system

[0105] Reagent Volume(μl) RNA (2 μg) 2 5× PrimeScriptRTMasterMix 2 Nuclease-free double-distilled water 6

[0106] (3) After gentle mixing, centrifuge at 2000 rpm for 20 seconds;

[0107] (4) Incubate at 37°C for 15 min, then at 85°C for 5 s, and then place on ice for 5 min;

[0108] (5) The above products can be used for the next PCR reaction immediately or stored at -20℃.

[0109] 3.2.4.2 RT-PCR Preliminary Experiment

[0110] (1) To reduce interference, each cDNA sample was diluted 10 times (5 μl cDNA + 45 μl H2O);

[0111] (2) Primer MIX (primers F and R are in the same tube), concentration of each is 10 μM;

[0112] (3) Add the following components (Table 1-6) to a 0.1 ml PCR tube:

[0113] Table 1-6 Reaction system

[0114] Reagent Volume(μl) 2×RealltimePCRMasterMix(SYBRGreen) 10 Template (cDNA diluted 10 times) 1 Primer MIX (10 μM each for F / R) 2 0.1% DEPC water 7

[0115] (4) PCR procedure. Use 2 -ΔΔCtMethods The relative expression of miRNA was calculated, Δ Ct = Ct (miRNA) - Ct (U6). The PCR reaction program was set as follows: 95°C pre-denaturation for 10 minutes; 95°C denaturation for 15 seconds, 60°C annealing for 20 seconds, 72°C extension for 40 seconds, 40 cycles; dissociation process 95°C for 15 seconds, 60°C for 1 minute, 95°C for 15 seconds.

[0116] 3.2.4.3 RT-PCR formal experiment

[0117] (1) Three replicate wells are made for one sample gene in a certain order;

[0118] (2) Add the following components (Table 1-7) to a 0.1 ml PCR tube:

[0119] Table 1-7 Reaction system

[0120]

[0121]

[0122] (3) PCR procedure. Use 2 -ΔΔCt Methods The relative expression of miRNA was calculated, Δ Ct = Ct (miRNA) - Ct (U6). The PCR reaction program was set as follows: 95°C pre-denaturation for 10 minutes; 95°C denaturation for 15 seconds, 60°C annealing for 20 seconds, 72°C extension for 40 seconds, 40 cycles; dissociation process 95°C for 15 seconds, 60°C for 1 minute, 95°C for 15 seconds.

[0123] 3.3 Statistical analysis methods

[0124] SPSS version 26.0 software (SPSS Inc, Chicago, IL, USA) was used to analyze the demographic and clinical characteristics of patients in the PBC sensitive group and the PBC resistant group. GraphPad Prism version 9.0.2 software was used to plot the statistical results. For the analysis of samples with biological replication, the screening of differentially expressed genes was based on the threshold of P ≤ 0.05; for the analysis of samples without biological replication, the screening of differentially expressed genes was based on the threshold of |log2(Fold change)|>1 (i.e., two-fold difference) and P ≤ 0.05. Normally distributed continuous variables such as patient age were expressed as mean ± standard deviation, and the student t test was used for inter-group comparison. Non-normally distributed laboratory data such as relative expression of miRNAs and biochemical indicators were expressed as median (interquartile range), and the Mann-Whitney U test was used for comparison between the two groups, and the Wilcoxon rank sum test was used for inter-group comparison. Enumeration data such as gender and autoantibodies were expressed as frequency, and the chi-square test was used for inter-group comparison. 2Test (Fisher's exact probability method). The receiver operating characteristic curve (ROC curve) was drawn to evaluate the efficacy prediction probability of candidate miRNAs, and the binary logistic regression analysis was used to analyze the significance of prediction. The area under the ROC curve (AUC) was used to evaluate the accuracy of the prediction performance of the selected miRNAs, and the Spearman's rank correlation coefficient was used to analyze the correlation between miRNAs and clinical indicators. P < 0.05 was considered statistically significant.

[0125] 2. Experimental Results

[0126] 1. Clinical characteristics of patients

[0127] 1.1 Clinical characteristics of subjects in the sequencing phase

[0128] A total of 10 subjects participated in the sequencing phase, and their clinical characteristics were statistically analyzed. All 10 patients were female, with an average age of (49.00±5.39) years in the resistant group and (43.80±10.45) years in the sensitive group. There were no significant differences in age, gender, ALT, AST, ALP, GGT, TBIL, LDH, IgG, IgA, IgM, anti-mitochondrial antibodies, autoantibodies Gp210 and Sp100 between the two groups before treatment (P>0.05). After receiving standard dose UDCA treatment for one year, the indicators of the two groups of patients improved; compared with the resistant group, the AST, ALP, TBIL, and LDH of the sensitive group were lower, and the difference was statistically significant (P<0.05). After treatment, ALT and GGT of the two groups of patients tended to be stable, and there was no significant difference (P>0.05). Compared with before treatment, IgG, IgA, and IgM in the sensitive group showed a decreasing trend after treatment, while they showed an increasing trend in the resistant group. However, there was no significant difference in IgG, IgA, and IgM between the two groups before and after treatment (P>0.05). The clinical characteristics of the sequenced patients are shown in Table 2-1.

[0129] Table 2-1 Baseline characteristics of sequencing patients and characteristics of laboratory indicators in follow-up after 1 year

[0130]

[0131]

[0132] Note: ALT is alanine aminotransferase; AST is aspartate aminotransferase; ALP is alkaline phosphatase; GGT is glutamyl transpeptidase; TBIL is total bilirubin; LDH is lactate dehydrogenase; IgG is immunoglobulin G; IgA is immunoglobulin A; IgM is immunoglobulin M; AMA is anti-mitochondrial antibody

[0133] 1.2 Clinical characteristics of subjects in the validation phase

[0134] A total of 30 subjects participated in the validation phase, and their clinical characteristics were statistically analyzed. There were 13 cases in the resistant group, all of whom were female, with an average age of (54.92±10.21) years; there were 17 cases in the sensitive group, including 15 females and 2 males, with an average age of (49.18±8.72) years. There was no significant difference in age, gender, ALT, AST, ALP, GGT, LDH, IgA, IgM, anti-mitochondrial antibodies, autoantibodies Gp210 and Sp100 between the two groups (P>0.05). Compared with the resistant group, the sensitive group had lower TBIL and IgG before treatment, and the difference was statistically significant (P=0.002; P=0.022). After receiving standard dose UDCA treatment for one year, some indicators of the two groups of patients improved; compared with the resistant group, the sensitive group had lower AST, TBIL, and LDH, and the difference was statistically significant (P<0.05). The clinical characteristics of the validation patients are shown in Table 2-2.

[0135] Table 2-2 Verification of baseline characteristics of patients and characteristics of laboratory indicators in follow-up after 1 year

[0136]

[0137]

[0138] Note: ALT is alanine aminotransferase; AST is aspartate aminotransferase; ALP is alkaline phosphatase; GGT is glutamyl transpeptidase; TBIL is total bilirubin; LDH is lactate dehydrogenase; IgG is immunoglobulin G; IgA is immunoglobulin A; IgM is immunoglobulin M; AMA is anti-mitochondrial antibody

[0139] 2. Differential expression and analysis of miRNAs

[0140] 2.1 Quality and integrity testing of miRNAs

[0141] All RNA samples passed the quality test. The quality and integrity of RNA were tested by Bioanalyzer 2100 (Agilent, CA, USA) and RNA quality test kit: RNA 6000Nano LabChip Kit (Agilent, CA, USA). Agilent 2100 fragment detection showed a flat baseline, and ROD260 / 280

[0142] The value of RNA was between 1.2 and 2.0, and most of the fragment length peaks were concentrated around 18-25 nt. The quality of serum RNA extracted from the samples was qualified.

[0143] 2.2 Sequence analysis of differentially expressed miRNAs

[0144] Based on the differential expression of miRNAs, a miRNA expression hotspot map was created to perform hierarchical cluster analysis on miRNAs. The clustering tree of different miRNAs is shown on the left, and the clustering tree of different samples is shown on the top. The redder the color, the higher the expression level of miRNAs, and the bluer the color, the lower the expression level of miRNAs. Statistical analysis of the differential expression of serum miRNAs before treatment in the drug-resistant group and the sensitive group showed that a total of 69 miRNAs were significantly differentially expressed (P<0.05). The results are shown in Figure 2 Note: DRpre: Drug resistance previous, representing samples of the drug-resistant group before treatment; DRpost: Drug resistance post, representing samples of the drug-resistant group after treatment; DSpre: Drug sensitive previous, representing samples of the sensitive group before treatment; DSpost: Drug sensitive post, representing samples of the sensitive group after treatment.

[0145] In the sensitive group, there were 40 serum miRNAs with significant differences in expression before and after treatment (P<0.05). Figure 3 Note: DRpre: Drug resistance previous, representing samples of the drug-resistant group before treatment; DRpost: Drug resistance post, representing samples of the drug-resistant group after treatment; DSpre: Drug sensitive previous, representing samples of the sensitive group before treatment; DSpost: Drug sensitive post, representing samples of the sensitive group after treatment.

[0146] After excluding non-human miRNAs, there were 49 miRNAs with different expressions between the two groups before treatment (P<0.05). Compared with the drug-resistant group, 34 miRNAs were upregulated and 15 miRNAs were downregulated in the sensitive group. See Table 3-1 and Table 3-2 for details. After excluding non-human miRNAs, there were 21 miRNAs with different expressions before and after treatment in the sensitive group (P<0.05). Compared with before treatment, 9 miRNAs were upregulated and 12 miRNAs were downregulated in the sensitive group after treatment. See Table 3-3 and Table 3-4 for details.

[0147] Table 3-1 Differentially expressed upregulated miRNAs in the resistant group and sensitive group before treatment (with the resistant group as the baseline)

[0148]

[0149]

[0150] Table 3-2 Differentially expressed downregulated miRNAs between the drug-resistant group and the sensitive group before treatment (with the drug-resistant group as the baseline)

[0151]

[0152] Table 3-3 Differentially expressed upregulated miRNAs in the sensitive group before and after treatment (with pre-treatment as the baseline)

[0153]

[0154] Table 3-4 Differentially expressed downregulated miRNAs in the sensitive group before and after treatment (with pre-treatment as the baseline)

[0155]

[0156]

[0157] 2.3 Preliminary screening and analysis of miRNAs

[0158] After excluding the miRNAs with significant changes before and after treatment in the sensitive group, a total of 7 human miRNAs were screened out after significant difference sorting, namely: miR-22-5p, miR-10a-5p, miR-126-3p, miR-7706, miR-223-3p, miR-556-5p and miR-130a-3p. The differential expression of these miRNAs was stable after receiving UDCA treatment. After combining the miRNAs with significant changes before and after treatment in the sensitive group, a total of 4 human miRNAs were screened out after significant difference sorting, namely: miR-3909, miR-6513-3p, miR-219a-5p and miR-146-3p. For subsequent screening and verification. The results of screening miRNAs are detailed in Table 3-5.

[0159] Table 3-5 Preliminary screening of miRNAs

[0160]

[0161]

[0162] 3. qRT-PCR Validation of miRNAs

[0163] 3.1 Primer information

[0164] According to the previous sequencing and screening results, qRT-PCR primers for 11 miRNAs, including miR-22-5p, miR-10a-5p, miR-126-3p, miR-7706, miR-223-3p, miR-556-5p, miR-130a-3p, miR-3909, miR-6513-3p, miR-219a-5p and miR-146-3p, were selected for synthesis, and U6 was used as an internal reference. The primer information is shown in Table 4-1.

[0165] Table 4-1 qRT-PCR primer information of miRNAs

[0166]

[0167]

[0168] 3.2 qRT-PCR validation of subjects in the sequencing phase

[0169] Based on the previous miRNAs sequencing and screening results, the selected miRNAs were verified by qRT-PCR. The results showed that they were basically consistent with the sequencing results: before receiving UDCA treatment, the expression of miR-22-5p, miR-126-3p, miR-223-3p, miR-556-5p, miR-130a-3p, and miR-219a-5p in the sensitive group was higher than that in the resistant group, and the difference was statistically significant (P=0.008); the expression of miR10a-5p, miR-7706, miR-3909, miR-6513-3p, and miR-146-3p in the sensitive group was lower than that in the resistant group, and the difference was statistically significant (P=0.008). At the same time, the PCR results of miR3909, miR-6513-3p, and miR-146-3p, which showed expression changes in the sensitive group before and after treatment, showed that after treatment, the expression of the above three miRNAs in the sensitive group increased, with a statistically significant difference (P=0.043), which was basically consistent with the sequencing results. Compared with the sensitive group before treatment, the expression of miR-219a-5p in the sensitive group decreased after treatment, which was consistent with the trend of the sequencing results, but the difference was not statistically significant (P=0.138). In addition, the expression of miR-223-3p decreased in the sensitive group after UDCA treatment, with a statistically significant difference (P=0.043), but in the sequencing results, the sensitive group did not show significant differences before and after treatment. After UDCA treatment, the expression of miR-126-3p, miR-556-5p, and miR-219a-5p in the drug-resistant group was upregulated, while the expression of miR-10a-5p was downregulated, and the differences were statistically significant (P=0.043). The results are shown in Table 5-1. Figure 4 Note: DRpre: Drug resistance previous, represents samples before treatment of drug resistance group; DRpost: Drug resistance post, represents samples after treatment of drug resistance group; DSpre: Drug sensitive previous, represents samples before treatment of sensitive group; DSpost: Drug sensitive post, represents samples after treatment of sensitive group. *: P<0.05, **: P<0.01, ***: P<0.001.

[0170] Table 5-1 qRT-PCR verification results of research subjects in the sequencing stage

[0171]

[0172] 3.3 qRT-PCR validation of subjects in the validation phase

[0173] According to the PCR results, expression change trend, sequencing multiple difference and significance ranking of the subjects in the sequencing stage, three miRNAs, miR-22-5p, miR-126-3p and miR-7706, were selected. The serum samples of the remaining 30 patients before and after treatment were further verified by qRT-PCR. The results showed that before receiving UDCA treatment, compared with the resistant group, the expression of miR-22-5p and miR-126-3p in the sensitive group was higher, and the difference was statistically significant (P<0.001); the expression of miR-7706 was lower, and the difference was statistically significant (P=0.017). The expression differences and change trends of each miRNA among the groups were analyzed. The expression of miR-22-5p was downregulated in the resistant group after treatment, but the difference was not statistically significant (P=0.055), but it was significantly downregulated in the sensitive group after treatment, and the difference was statistically significant (P<0.001). At the same time, the relative expression level in the sensitive group after treatment was significantly lower than that in the resistant group before and after treatment. miR-7706 was significantly upregulated in the drug-resistant group after treatment, with a statistically significant difference (P=0.003); while it was significantly downregulated in the sensitive group after treatment, with a statistically significant difference (P<0.001). miR-126-3p was downregulated in the drug-resistant group after treatment, with a statistically significant difference (P=0.003), while it was significantly upregulated in the sensitive group after treatment, with a statistically significant difference (P<0.001). The relative expression levels of the two groups of patients before and after treatment were quite different. The results are shown in Table 5-2. Figure 5 As shown, Note: DR_pre: Drug resistance previous, represents the samples before treatment of the drug-resistant group; DR_post: Drug resistance post, represents the samples after treatment of the drug-resistant group; DS_pre: Drug sensitive previous, represents the samples before treatment of the sensitive group; DS_post: Drug sensitive post, represents the samples after treatment of the sensitive group. *: P<0.05, **: P<0.01, ***: P<0.001.

[0174] Table 5-2 qRT-PCR verification results of research subjects in the verification phase

[0175]

[0176] 4. Clinical relevance of miRNAs

[0177] The correlation between the three screened miRNAs and patients' ALT, AST, ALP, GGT, TBIL, and IgG was analyzed. The results showed that the expression level of miR-22-5p had no significant correlation with patients' ALT, AST, ALP, GGT, TBIL, and IgG (P>0.05). The expression level of miR-126-3p was significantly negatively correlated with patients' TBIL (r=-0.356, P=0.005) and patients' IgG (r=-0.311, P=0.015), and the correlation was statistically significant; there was no significant correlation with patients' ALT, AST, ALP, and GGT (P>0.05). The expression level of miR-7706 was significantly positively correlated with TBIL (r=0.513, P<0.001) and AST (r=0.409, P=0.001), and the correlation was statistically significant; it was not significantly correlated with ALT, ALP, GGT, and IgG (P>0.05). The results are shown in Table 5-1.

[0178] Table 5-1 Spearman correlation analysis between miRNAs and clinical indicators of patients

[0179]

[0180] 5. Prediction of PBC efficacy using miRNAs

[0181] ROC curve analysis of the selected three miRNAs was performed to predict the efficacy and evaluate the efficacy prediction performance. First, a binary logistic regression analysis was performed to determine whether the three miRNAs had predictive significance for efficacy. The results showed that the expression of miR-22-5p and miR-7706 had nothing to do with sensitivity or resistance (P=0.990; P=0.157), and had no predictive significance for efficacy; the expression of miR-126-3p was significantly positively correlated with sensitivity or resistance (P=0.016), and had certain predictive significance. The higher the expression level of miR-126-3p, the more likely the patient is to be sensitive to UDCA. Further ROC curve analysis of miR-126-3p was performed, and the results are as follows Figure 6 shown.

[0182] The area under the curve (AUC) of miR-126-3p was 0.891 (P=0.0003, 95%CI: 0.772-1.000), the sensitivity was 82.4%, and the specificity was 84.6%. The results show that miR-126-3p has significant value in predicting the efficacy of patients. In order to find the critical point of patient sensitivity or resistance represented by the expression level of miRNAs, the Youden index was calculated, and the maximum screening index was 0.67, corresponding to the miR-126-3p expression of 0.786, that is, when the miR-126-3p expression level is higher than 0.786, the patient is judged to be sensitive to UDCA.

[0183] 6. Correlation between miR-126-3p changes and clinical indicators

[0184] The expression of miR-126-3p before and after treatment was compared and the correlation analysis was performed. Figure 7 As shown. It can be seen that there is a correlation between the expression of miR-126-3p before and after medication in the sensitive and resistant groups (r=0.953, P<0.001; r=0.984, P<0.001). The expression of the sensitive group increased after medication, and the expression of the resistant group decreased after medication, and the difference was statistically significant (Z=4.625, P<0.001). The correlation between the expression level of miR-126-3p and clinical indicators (TBIL, ALP, GGT, ALT, AST, IgG) was analyzed. The results are shown in Figure 8 The results showed that the expression level of miR-126-3p was significantly negatively correlated with TBIL (r=-0.356, P=0.005) and IgG (r=-0.311, P=0.015), and the correlation was statistically significant; there was no significant correlation with ALT, AST, ALP, and GGT (P>0.05).

[0185] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims. Sequence Listing <110> The Fifth Medical Center of PLA General Hospital <120> MicroRNA miR-126-3p and its application <160> 6 <170> SIPOSequenceListing 1.0 <210> 1 <211> twenty one <212> RNA <213> Artificial Sequence <400> 1 ucguaccgug aguaauaaug c 21 <210> 2 <211> 20 <212> DNA <213> Artificial Sequence <400> 2 cgcgtcgtac cgtgagtaat 20 <210> 3 <211> 20 <212> DNA <213> Artificial Sequence <400> 3 agtgcagggt ccgaggtatt 20 <210> 4 <211> 17 <212> DNA <213> Artificial Sequence <400> 4 ctcgcttcgg cagcaca 17 <210> 5 <211> 20 <212> DNA <213> Artificial Sequence <400> 5 aacgcttcac gaatttgcgt 20 <210> 6 <211> 50 <212> DNA <213> Artificial Sequence <400> 6 gtcgtatcca gtgcagggtc cgaggtattc gcactggata cgaccgcatt 50

Claims

1. Use of a reagent for detecting microRNA miR-126-3p in the preparation of a product for predicting the sensitivity of patients with primary biliary cholangitis to ursodeoxycholic acid treatment, characterized in that: The nucleotide sequence of the microRNA miR-126-3p is shown in SEQ ID NO.

1.

2. The use according to claim 1, characterized in that: When the product detects that the expression level of the microRNA miR-126-3p is higher than 0.786, it is predicted that the corresponding primary biliary cholangitis patient is sensitive to ursodeoxycholic acid treatment.

3. The use according to claim 1, characterized in that: The product is a reagent, a kit or a device.

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