WO2016070819A1

WO2016070819A1 - Hepatocellular carcinoma diagnostic marker consisting of serum micro-rna, and diagnostic kit

Info

Publication number: WO2016070819A1
Application number: PCT/CN2015/093845
Authority: WO
Inventors: 庄诗美; 崇雨田; 林雪嘉; 郭智伟; 元云飞; 杨晓静; 曾春贤; 方坚鸿
Original assignee: 中山大学
Priority date: 2014-11-06
Filing date: 2015-11-05
Publication date: 2016-05-12
Also published as: CN104372087B; CN104372087A

Abstract

A hepatocellular carcinoma diagnostic marker consisting of serum mircoRNA is disclosed. The marker consists of hsa-miR-29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR-145, hsa-miR-192, and hsa-miR-505. A hepatocellular carcinoma diagnostic kit is also disclosed. The kit contains a test for detecting the level of the described seven microRNA molecules in serum.

Description

Liver cancer diagnostic marker and diagnostic kit consisting of serum microRNA

Technical field

The present invention relates to a diagnostic combination of liver cancer consisting of serum microRNAs including hsa-miR-29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR-145, hsa -miR-192 and hsa-miR-505, specifically related to the application of early hepatocellular carcinoma early warning and early diagnosis kits, belong to the field of biomedical diagnosis.

Background technique

Primary liver cancer is a common malignant tumor with high morbidity and high mortality in the world. Hepatocellular carcinoma (HCC) accounts for more than 90% of primary liver cancer. The World Health Organization's "Global Cancer Report 2014" pointed out that in 2012, the world's new cases of liver cancer ranked fifth in malignant tumors, and its mortality rate ranked second, including new cases of liver cancer in China and deaths. It accounts for half of the global cases. Due to the lack of effective screening methods, 60%-70% of liver cancer patients are in advanced stage of diagnosis, missing the opportunity of radical resection. It can be seen that early diagnosis and early treatment are the most effective ways to increase the survival rate of liver cancer patients and reduce the mortality of liver cancer.

The occurrence and development of liver cancer is a multi-factor, multi-stage, multi-step process. Cirrhosis caused by any cause is the most common risk factor for liver cancer. In Asia, hepatitis B and cirrhosis caused by chronic hepatitis B virus (HBV) are the most important risk factors for liver cancer. The vast majority of patients with liver cancer are accompanied by pathological changes of hepatitis and cirrhosis. After the stage of hepatitis and cirrhosis, they eventually develop into liver cancer, which is called "hepatocellular trilogy". It is estimated that the number of hepatitis B carriers in China is nearly 120 million, of which 20% will develop into chronic hepatitis B patients, and 15%-40% of patients with chronic hepatitis B will further develop into cirrhosis. Therefore, long-term monitoring of high-risk groups of liver cancer, early detection and early warning of early liver cancer, easy to identify targeted individualized prevention and treatment programs, delay or even prevent the occurrence of liver cancer, is conducive to improving the quality of life of patients.

The Early Detection Research Network (EDRN), established by the National Cancer Institute, clearly proposes five steps to screen and evaluate early markers of cancer: 1) screening for possible marker molecules; 2) large-scale retrospective Study and analysis; 3) retrospective analysis of candidate markers in the prospectively collected high-risk population samples; 4) prospective observation of candidate markers for disease detection; 5) prospective clinical randomized trials, screening the general population . At present, liver cancer is mainly screened by serum alpha-fetoprotein (AFP) detection or imaging examination. Although AFP has been used for liver cancer screening for many years, its diagnostic sensitivity is not high enough: A 35 levels of liver cancer patients are still below the warning value (20 ng / ml); AFP is detected in early liver cancer screening The rate is only 22%, even low in the year or months before diagnosis Up to 3% (200 ng/ml is the threshold). Although imaging methods such as ultrasound, CT, and MRI can be used as a supplement to AFP testing, long-term follow-up screening is expensive, and the detection rate of these methods depends on tumor size and operator experience, and may be misdiagnosed. Missed diagnosis. Therefore, it has been found that new high-sensitivity, high-specificity, low-cost and easy-to-detect liver cancer early diagnostic markers have important clinical significance.

MicroRNAs are a class of endogenous small molecule non-coding RNAs that are widely found in eukaryotes and are 18-24 nucleotides in length (nt). MicroRNA inhibits the expression of target genes through post-transcriptional levels, regulates cell differentiation, proliferation, apoptosis and other life activities, and plays an important role in various physiological and pathological processes such as embryonic development, body metabolism, and disease development. In recent years, researchers have detected microRNAs in various body fluids such as blood, saliva, and urine, and proposed the concept of circulating microRNAs. Body fluid specimens such as blood are easy to obtain, clinically operative and less invasive, and the circulating microRNA has good stability and convenient detection. Therefore, circulating microRNA has the potential to be a non-invasive biomarker for diseases such as tumors, and is suitable for screening high-risk populations. .

Recent studies have indicated that liver cancer patients have different circulating microRNA expression profiles than non-hepatoma controls. For example, the levels of miR-21, miR-122, and miR-223 in serum of patients with liver cancer and HBV hepatitis are higher than those of healthy people; and miR-21 elevated in plasma of liver cancer patients is down-regulated after resection of patients; Li By detecting 513 individual serum microRNA expression profiles, we determined the classification of HBV hepatitis patients and healthy people, as well as liver cancer patients and healthy people; Zhou et al. detected the levels of nearly one thousand plasma samples microRNA, found by miR-122 a classification module consisting of seven circulating microRNAs such as miR-192, miR-21, miR-223, miR-26a, miR-27a and miR-801, which can distinguish between liver cancer and all non-hepatoma populations (including healthy people, hepatitis, Patients with cirrhosis), and can diagnose AFP-negative liver cancer. These studies suggest the potential of circulating microRNAs as diagnostic markers for liver cancer.

However, the current research on circulating microRNA as a diagnostic marker for liver cancer still has the following shortcomings: 1) Most of the studies only select microRNAs that have been reported to be dysregulated in liver cancer tissues as candidate indicators, and may not fully and objectively reflect the situation of circulating microRNAs; 2) Part of the study sample is small, lack of multi-center verification; 3) The control setting is imperfect, it is difficult to indicate that the identified marker is a specific diagnostic marker for liver cancer; 4) All studies are currently performed in specimens that have been diagnosed as liver cancer. A retrospective analysis of the lack of prospective studies in high-risk populations failed to clarify the value of circulating microRNAs for early warning of liver cancer. Therefore, it is still necessary to find early diagnostic markers of liver cancer with clinical application value for the monitoring of high-risk populations of liver cancer, so as to early warning early small liver cancer, so that clinicians can take appropriate preventive measures in time.

Summary of the invention

The object of the present invention is to provide an effective liver cancer diagnostic marker for the above technical problems to be solved.

To achieve the above technical object, the present invention provides a liver cancer diagnostic marker which encodes the following microRNAs, respectively The nucleic acid molecule consists of hsa-miR-29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR-145, hsa-miR-192 and hsa-miR-505.

In a preferred embodiment, the level of the microRNA in the serum of a liver cancer patient is higher than in a healthy person, a hepatitis B carrier, a chronic hepatitis B patient, or a cirrhosis patient. Preferably, the liver cancer is primary hepatocellular carcinoma.

In another aspect, the present invention provides a microRNA molecule combination for diagnosis of liver cancer, which comprises hsa-miR-29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR- 145, hsa-miR-192 and hsa-miR-505.

Specifically, the present invention obtains the above-mentioned liver cancer diagnosis combination consisting of 7 serum microRNAs by the following steps:

1. Screening for candidate serum microRNAs in patients with liver cancer and chronic hepatitis B by high-throughput qPCR Array;

2. Real-time fluorescent quantitative PCR to verify candidate serum microRNAs;

3. Establish a serum microRNA combination that distinguishes between liver cancer and non-cancer controls (including healthy people, hepatitis and cirrhosis patients) in a training group consisting of healthy people, hepatitis, cirrhosis, and liver cancer patients;

4. The effect of serum microRNA combination established in step 2 of two independent validation groups to diagnose liver cancer;

5. Analyze the diagnostic effect of serum microRNA combination established in step 3 in small liver cancer, early TNM and AFP-negative liver cancer patients.

The experimental results and related statistics show that in the above step 1, the inventors identified 19 candidate microRNAs by high-throughput qPCR Array screening, and verified the average of 19 candidate microRNAs in the serum of liver cancer patients in step 2. Raise. The levels of candidate microRNAs in the training group (sample size 257) were further tested and an optimal serum microRNA combination was established to distinguish between liver cancer and non-cancerous controls. Furthermore, it was verified in the independent verification group 1 and the verification group 2 (sample size 352, 139 parts, respectively) that the serum microRNA combination can distinguish between liver cancer and non-cancer control. At the same time, the inventors found that compared with traditional liver cancer screening methods, such as AFP, serum microRNA combination has a better diagnostic effect in small liver cancer, early TNM and AFP negative liver cancer patients.

The inventors further conducted nested control case studies in prospectively collected high-risk populations (including patients with chronic hepatitis B and cirrhosis). Through long-term monitoring of the development of 1484 patients with chronic hepatitis B or cirrhosis, the inventors found 27 cases of new liver cancer in the validation group 3, and collected the clinical diagnosis of liver cancer in each case (set to zero, M0) and 12 before diagnosis. Sequence serum samples at 9, 6, and 3 months (M-12, -9, -6, -3), and serial serum samples from 135 sex-aged patients with chronic hepatitis/cirrhosis at the corresponding time points were collected as controls. .

Analysis of the experimental results and related statistics show that serum microRNA combination has a good predictive effect in the early diagnosis of subclinical liver cancer, which is shown in the following: the sensitivity of the combination predicting liver cancer is higher than AFP at each time point, and The passage of time gradually increased; in addition, the area under the curve (AUC) of the serum microRNA combination was greater than that of AFP.

In another aspect, the invention also discloses a kit for diagnosis of liver cancer, comprising reagents for detecting the level of the following microRNA molecules in serum: hsa-miR-29a, hsa-miR-29c, hsa-miR-133a hsa-miR-143, hsa-miR-145, hsa-miR-192 and hsa-miR-505.

In one embodiment, the reagent for detecting the level of a microRNA molecule in serum is a real-time fluorescent quantitative PCR-related reagent.

In still another preferred embodiment, the kit further comprises a serum RNA extraction system and a reverse transcription system. In a preferred embodiment, the kit further comprises an analytical method for assessing whether or not suffering from liver cancer. In a preferred embodiment, the kit comprises 7 pairs of LNA-modified primers that can be used to detect the following microRNA levels: hsa-miR-29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR-145, hsa-miR-192, hsa-miR-505. More preferably, the kit further comprises an LNA modified primer for detecting the exogenous reference NC67. The level of the above 7 target genes in the serum sample to be ^tested is 2 - ^ΔCt ( ^ΔCt = Ct _taget - Ct _reference ) by calibration with an exogenous reference NC67. According to the microRNAs threshold, the microRNAs of the test specimens are assigned a value of 1 or 0, respectively, to achieve discretization. Further analysis of serum microRNA combination according to logistic regression method to assess whether the test subject is suffering from liver cancer: Logit (p=HCC)=-0.356-0.264*hsa-miR-29a-0.081*hsa-miR-29c-0.518*hsa-miR-133a -0.250*hsa-miR-143-0.489*hsa-miR-145-0.466*hsa-miR-192-0.417*hsa-miR-505, wherein hsa-miR-29a, hsa-miR-29c, hsa-miR- 133a, hsa-miR-143, hsa-miR-145, hsa-miR-192, hsa-miR-505 are the discretization values of the corresponding serum microRNA detection levels, and Logit (p=HCC)=0.5 is used as the diagnostic threshold. Above 0.5, it is diagnosed as liver cancer, and below 0.5 is diagnosed as non-liver cancer. Thus, the diagnostic kit can be applied to liver cancer early warning.

The superiority of serum microRNA combination for liver cancer detection and early diagnosis lies in: (1) the specimen is easy to obtain, clinically operability and traumatic, and the serum microRNA has good stability and convenient detection. (2) The experimental method is very mature, the detection process is simple and easy to repeat, and can be completed by ordinary technicians. (3) The present invention uses high-throughput screening, multi-center validation, and prospectively collected high-risk population samples to conduct a comprehensive evaluation of the effects of serum microRNA combination and diagnostic kits. The application of the above methods and strategies ensures The invention has potential application value in the clinical diagnosis of liver cancer, and provides a method strategy for the development of other disease biomarkers. (4) The serum microRNA diagnosis liver cancer kit can timely reflect the disease state of liver cancer patients, avoid the complicated detection, save time and labor cost, and facilitate clinicians to adopt personalized prevention and treatment programs in time.

DRAWINGS

1 is a graph showing ROC curves of a training group and a verification group according to Embodiments 4 and 5 of the present invention. The ROC curves of the training group (A), the validation group 1 (B) and the validation group 2 (C) serum microRNA combination and AFP distinguish liver cancer from non-cancerous controls (top panel) and high-risk population (bottom panel).

2 is a ROC graph of a nested control case study in Example 5 of the present invention. ROC curves of liver cancer patients with pre-diagnosis 12 (A), 9 (B), 6 (C) or 3 (D) months and at the time of diagnosis (E) serum microRNA combination and AFP distinguish liver cancer from hepatitis/cirrhosis control.

Fig. 3 is a graph showing the ROC curve of a small liver cancer patient (tumor ≤ 3 cm) according to Example 6 of the present invention. Training group (A), validation group 1 (B), validation group 2 (C), and training group and all validation groups (D) serum microRNA combination and AFP distinguish small liver cancer patients from non-cancerous controls (left) and high-risk groups (Right image) ROC graph.

Figure 4 is a graph showing ROC of Example 7 of different TNM staged liver cancer patients in accordance with the present invention. The serum microRNA combination and AFP differentiated the ROC curves of TNM stage I (A), TNM stage II (B) or TNM stage III/IV (C) liver cancer patients with non-cancer controls (top panel) and high-risk groups (bottom panel).

Figure 5 is a graph showing ROC of Example 8 of an AFP-negative liver cancer patient (AFP ≤ 20 ng/ml). Training group (A), validation group 1 (B), validation group 2 (C), and training group and all validation groups (D) serum microRNA combination distinguishes AFP-negative liver cancer patients from non-cancerous controls (left) and high-risk groups ( ROC graph on the right).

detailed description

In order to make the present invention easier to understand, the present invention will be further described below in conjunction with the drawings and specific embodiments. It is to be understood that the invention is not intended to limit the scope of the invention;

Example 1: Collection and preparation of serum samples

The inventors collected healthy people (HC), hepatitis B carriers (IHC), chronic hepatitis B patients (CHB), cirrhotic patients (LC), and liver cancer patients (HCC) from August 2009 to August 2014. Blood samples, these people meet the inclusion criteria (Table 1), and according to the principle of gender and age matching, set the liver cancer and its control group specimens.

Training group: 257 serum samples collected from healthy people (51 cases), chronic hepatitis B patients (51 cases), liver cirrhosis patients (47 cases), and liver cancer patients (108 cases) collected from August 2009 to March 2012 .

Verification group 1: 352 sera from healthy people (60 cases), chronic hepatitis B patients (68 cases), cirrhosis patients (71 cases), and liver cancer patients (153 cases) collected from April 2012 to April 2013 specimen.

Verification group 2: 139 serum samples of healthy people (48 cases), hepatitis B virus carriers (42 cases), and liver cancer patients (49 cases) collected from May 2013 to August 2013.

Verification group 3: 668 serial serum samples from chronic hepatitis B or cirrhosis patients (135 patients in 135 cases) and liver cancer patients (27 in total) collected from August 2009 to August 2014 for nesting Control case study. The specific situation is: recruiting 1484 patients with chronic hepatitis B or cirrhosis for long-term follow-up, screening for liver cancer every 3 months, detecting biochemical indicators such as AFP, AST, ALT, and imaging examinations such as B-ultrasound, and collecting serum samples at the same time. Store at -80 °C. As of August 2014, 27 of the 1484 follow-up patients had new liver cancer, of which 15 were confirmed by histopathology and 12 were diagnosed by imaging.

The clinical characteristics of the above-mentioned participating populations are shown in Tables 2 and 3.

Table 1. Enrollment criteria for participating populations

The inclusion criteria were referred to the American Association for the Study of Liver Diseases (AASLD) 2009 Practice Guide.

Refer to the liver biopsy Metavir system.

^§ In addition to the imaging diagnosis of 12 new liver cancer patients in the validation group 3, the remaining liver cancer cases were confirmed by histopathology.

Refer to Table 3 for specific information on these 12 cases.

Table 2. Clinicopathological features of participants in the training and validation groups

Table 3. Clinical and pathological features of 27 new liver cancer patients in the validation group 3

4 ml of peripheral venous blood of preoperative, healthy person, hepatitis B carrier, chronic hepatitis B patients and cirrhosis patients were taken from liver cancer patients, and allowed to stand in a dry blood collection tube at 4 ° C for more than half an hour. Subsequently, 400 g, centrifuged at 4 ° C for 10 min, the supernatant was taken, further 1800 g, and the supernatant was centrifuged at 4 ° C for 10 min to obtain serum, which was stored at -80 ° C until use.

Example 2: qPCR Array and its data analysis

The inventors selected serum samples from 6 liver cancer patients before surgery and 8 chronic hepatitis B patients for at least one year from the last examination for qPCR Array screening. These patients were male, and there was no significant difference in mean age and distribution (Table 4).

Table 4. Clinicopathological features of specimens used for qPCR Array analysis

The invention adopts Applied Biosystems

The Array Human MicroRNA method screens microRNAs differentially between liver cancer and chronic hepatitis B, and detects the levels of 754 known human microRNAs. See the Applied Biosystems website for specific steps. After the obtained raw data was calibrated, the inventors used the Significant Analysis of Microarray (SAM) analysis method to select differential microRNAs, and finally screened 19 candidate microRNAs for subsequent validation (Table 5).

Table 5. Candidate microRNAs and exogenous reference information used in the present invention

Exiqon product number

Example 3: Real-time quantitative PCR detection of microRNAs in training group specimens

1.1 Serum RNA extraction

The invention adopts Trizol reagent to extract, and obtains serum RNA by phenol/chloroform extraction purification, isopropanol precipitation and glycogen subsidence, and the specific steps are as follows:

1. Take 200 μl of serum, preferably an equal volume of double-stranded RNA mixed with cel-miR-67 (NC67, based on the nematode miR-67 mature sequence with no homology to the human genome sequence, at a final concentration of 0.2 nM, the sequence is shown in Table 5) Trizol lysate, mixed well and shaken for 15 min.

2. Add 100 μl of pre-cooled chloroform, mix by shaking, centrifuge at 12000 g for 15 min at 4 °C.

3. Transfer the supernatant, add an equal volume of pre-cooled phenol/chloroform (1:1), mix by shaking, centrifuge at 14000 g for 10 min at 4 °C. And repeat this step once.

4. Transfer the supernatant, add an equal volume of pre-cooled chloroform, mix by shaking, centrifuge at 14000 g for 15 min at 4 °C.

5. Transfer the supernatant, preferably add an equal volume of isopropanol and glycogen (final concentration 200 μg/ml), mix by shaking, centrifuge at 16000 g for 30 min at 4 °C.

6. Carefully pour the supernatant, wash the pellet once with 1 ml of 70% ethanol, centrifuge at 16000 g for 10 min at 4 °C.

7. Discard the supernatant. After the ethanol is evaporated, add 10 μl of DEPC water to dissolve, and store at -80 °C for later use.

1.2 Real-time quantitative PCR (RT-qPCR)

The present invention preferably uses a Universal cDNA Synthesis reverse transcription kit to reverse transcribe an equal volume of serum RNA. Further preferably, the SYBR Green qPCR master mix kit is used, and the 20-fold diluted cDNA is used as a template, and the LNA-modified primer is subjected to RT-qPCR detection. The reverse transcription kit, qPCR detection kit, and LNA modified primers were purchased from Exiqon Corporation (Denmark).

The expression value of the target microRNA was 2 - ^ΔCt ( ^ΔCt = Ct _taget - Ct _reference ) by calibration with an exogenous reference NC67. The results showed that the levels of 19 candidate microRNAs in the serum of liver cancer patients were significantly increased.

Example 4: Determining optimal serum microRNA combinations in a training group

The training group specimens were arranged according to the respective detection levels of 19 microRNAs, and the values were sequentially taken (if only one was repeated), and the specimens were judged as positive or negative groups according to the values, and the established categories of the specimens were analyzed. The sensitivity and specificity of each value were obtained, and the Receiver Operating Characteristic Curve was further drawn. Find the point at which the (sensitivity + specificity)/2 value is maximized, and the corresponding expression value at this point is the threshold for microRNA discretization. Further, the specimens with high or lower thresholds are assigned 1 or 0 respectively to achieve discretization for further model construction. The microRNAs discretization thresholds used in the present invention (Table 5) will be used for the corresponding microRNAs in the training and validation groups. The discretization of the data transforms the continuous variable into a binary variable.

The modeling results show that the seven serum microRNAs constructed by the logistic regression model are the optimal combination, and the formula for evaluating whether or not the liver cancer is: Logit(p=HCC)=-0.356-0.264*hsa-miR-29a-0.081*hsa -miR-29c-0.518*hsa-miR-133a-0.250*hsa-miR-143-0.489*hsa-miR-145-0.466*hsa-miR-192-0.417*hsa-miR-505, of which hsa-miR- 29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR-145, hsa-miR-192, hsa-miR-505 are the discretization values of the corresponding serum microRNA detection levels. The combination can distinguish between liver cancer and non-cancer control or high-risk population in the training group, and has a good diagnostic effect on liver cancer. The AUC of the serum microRNA combination is greater than the AUC of AFP20 or AFP400 (20 or 400 ng/ml as the AFP threshold). (Figure 1A).

Example 5: Verifying the effect of serum microRNA combination in the validation group on diagnosis of liver cancer

A combination of serum microRNAs established in the training group was used to validate the group for diagnosis of liver cancer. Similarly, experiments were performed using Trizol extraction and real-time PCR assays. The combination can still distinguish between liver cancer and non-cancer control or high-risk population in the verification group 1, 2, and has a good diagnosis effect of liver cancer, and the AUC of the serum microRNA combination is greater than the AUC of AFP20 or AFP400 (Fig. 1B, C). .

The present invention further uses a nested control case study to analyze the predictive effect of serum microRNA combination in early liver cancer. The inventors have long-term monitoring of the development of 1484 patients with chronic hepatitis B or cirrhosis. In the validation group 3, 27 cases of new liver cancer were found, and the diagnosis of liver cancer in each case was collected (set to zero, M0) and its top 12 Sequence serum samples of 9, 6 and 3 months (M-12, -9, -6, -3) were collected, and serial serum samples of 135 gender-matched chronic hepatitis/cirrhosis patients at the corresponding time points were collected as controls. In order to avoid the presence of subclinical liver cancer in the control case, the inventors only selected patients who had not found liver cancer at the last examination, and set their zero point (M0) to a time point of at least one year from the last examination. The results showed that the serum microRNA combination has a good early diagnosis effect of subclinical liver cancer, and can be used for early warning and early diagnosis of liver cancer. The performance of the serum microRNA combination predicting liver cancer is higher than AFP at each time point. In the 12 months before the clinical diagnosis, the sensitivity of the combination was 44.4%. With the passage of time, the sensitivity gradually increased and reached 70.4% at the diagnostic zero point. The sensitivity of AFP at the time point before diagnosis was as low as 0. -25%, even the diagnostic zero is only 40.7% (AFP20) or 18.5% (AFP400) (Table 6). In addition, the AUC of the combination was greater than that of AFP20, especially in the 12th and 9th months before diagnosis, the difference was 0.626vs 0.536, 0.654vs 0.506; the AUC of the combination was much larger than AFP400 at any time point (Fig. 2 ).

Table 6. Predictive effects of serum microRNA combinations in nested control case studies

Example 6: Diagnostic effect of serum microRNA combination in small liver cancer patients (tumor ≤ 3 cm)

The present invention further demonstrates that serum microRNA combination has a good effect in diagnosing small liver cancer. In the training group, the verification group 1, and the verification group 2, the AUC of the combined diagnosis of small liver cancer was significantly larger than that of AFP; the combined analysis results of the training group and the three verification groups also showed that the AUC of the combined diagnosis of small liver cancer was much larger than AFP20 or AFP400. The AUC of small liver cancer and non-cancer control or high-risk population was 0.837 vs 0.729 or 0.616, 0.831 vs 0.711 or 0.615, respectively (Fig. 3).

Example 7: Diagnostic effect of serum microRNA combination in patients with different TNM staging liver cancer

Serum microRNA combination has a better diagnostic effect in patients with different TNM staging liver cancer. The AUC of this combination is significantly greater than the AUC of AFP: all non-cancerous controls/high-risk groups are used as controls, in TNM I, TNM II, TNM III/ In the diagnosis of stage IV liver cancer, the AUC of the combination was 0.822/0.816, 0.816/0.810 and 0.860/0.852, respectively, while AFP20 or AFP400 were 0.727/0.706 or 0.654/0.653, 0.741/0.717 or 0.641/0.639, 0.820/0.795, respectively. Or 0.720/0.719 (Figure 4).

Example 8: Diagnostic effect of serum microRNA combination in AFP negative (AFP ≤ 20 ng / ml) liver cancer patients

Serum microRNA combination also has a good diagnostic effect in AFP-negative liver cancer patients: all non-cancerous controls/high-risk groups are compared, the combination is in the training group, the validation group 1, the validation group 2, and the prediction AFP of all the central combinations. The AUC of negative liver cancer were 0.826/0.820, 0.820/0.824, 0.856/0.817, and 0.826/0.819, respectively (Fig. 5).

Example 9: Preparation of serum microRNA kit

The kit of the invention is used for early warning and diagnosis of liver cancer, especially early liver cancer, by serum RNA extraction system and reverse transcription system A real-time, real-time PCR system, a primer system, and a logistic regression analysis method for assessing whether or not liver cancer is present. In the serum RNA extraction system of the kit, the inventors extracted with Trizol reagent, and obtained serum RNA by phenol/chloroform extraction purification, isopropanol precipitation, and glycogen assisted sedimentation. The inventors used a series of primers modified by Exiqon LNA as the primer system of the kit for detecting the following molecules: hsa-miR-29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR-145, hsa-miR-192, hsa-miR-505 and NC67 (exogenous reference). In the real-time PCR system, the inventors used the Exiqon reverse transcription kit and the SYBR Green qPCR master mix kit for detection. The logistic regression formula used to assess whether or not suffering from liver cancer is: Logit(p=HCC)=-0.356-0.264*hsa-miR-29a-0.081*hsa-miR-29c-0.518*hsa-miR-133a-0.250* hsa-miR-143-0.489*hsa-miR-145-0.466*hsa-miR-192-0.417*hsa-miR-505. Among them, hsa-miR-29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR-145, hsa-miR-192, hsa-miR-505 are discrete levels of corresponding serum microRNA detection The value after the transformation. Logit (p=HCC)=0.5 is used as the diagnostic threshold, above 0.5 is the liver cancer patient, and below 0.5 is the non-liver cancer patient.

Claims

A diagnostic marker for liver cancer consisting of nucleic acid molecules encoding the following microRNAs: hsa-miR-29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR-145, hsa- miR-192 and hsa-miR-505.
The liver cancer diagnostic marker according to claim 1, wherein said microRNA is higher in serum of a liver cancer patient than a healthy person, a hepatitis virus carrier, a chronic hepatitis patient or a liver cirrhosis patient.
The liver cancer diagnostic marker according to claim 1 or 2, wherein the liver cancer is primary hepatocellular carcinoma.
A microRNA molecule combination for diagnosis of liver cancer, which consists of hsa-miR-29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR-145, hsa-miR-192 and hsa -miR-505 composition.
The microRNA molecule combination according to claim 4, wherein said microRNA is higher in serum of a liver cancer patient than a healthy person, a hepatitis virus carrier, a chronic hepatitis patient or a liver cirrhosis patient.
The microRNA molecule combination according to claim 4 or 5, wherein the liver cancer is primary hepatocellular carcinoma.
A diagnostic kit for the diagnosis of liver cancer, comprising reagents for detecting the levels of the following microRNA molecules in serum: hsa-miR-29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR-145, hsa-miR-192 and hsa-miR-505. Preferably, the reagent for detecting the level of a microRNA molecule in serum is a real-time fluorescent quantitative PCR related reagent.
The diagnostic kit according to claim 7, wherein the logistic regression formula is:

Logit(p=HCC)=-0.356-0.264*hsa-miR-29a-0.081*hsa-miR-29c-0.518*hsa-miR-133a-0.250*hsa-miR-143-0.489*hsa-miR-145- 0.466*hsa-miR-192-0.417*hsa-miR-505,

Among them, hsa-miR-29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR-145, hsa-miR-192, hsa-miR-505 discretization of the corresponding serum microRNA detection levels The latter value, with a diagnostic threshold of 0.5, is diagnosed as liver cancer above 0.5, and non-liver cancer is diagnosed below 0.5.
A diagnostic kit according to claim 7 or 8, wherein said diagnostic kit is applied to an early warning diagnosis of liver cancer. Preferably, the liver cancer early warning group is a healthy person and a high risk group of liver cancer such as a chronic hepatitis or a liver cirrhosis patient. Preferably, the liver cancer is primary hepatocellular carcinoma.
Use of the diagnostic kit according to any one of claims 7-9 for the diagnosis of liver cancer.