CN105671179B - application of serum microRNA in liver cancer diagnosis and diagnosis kit - Google Patents
application of serum microRNA in liver cancer diagnosis and diagnosis kit Download PDFInfo
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Abstract
the invention discloses a liver cell liver cancer diagnosis marker combination consisting of serum microRNA and a kit containing the marker combination. The liver cancer diagnosis marker combination comprises the following microRNAs: hsa-miR-193a-5p, hsa-miR-143, hsa-miR-145, hsa-miR-29a, hsa-miR-133a, hsa-miR-505, hsa-miR-29c and hsa-miR-192. The invention can be used for diagnosing liver cancer.
Description
Technical Field
the invention belongs to the field of biomedical diagnosis, and particularly relates to a liver cancer diagnosis combination consisting of serum microRNA, wherein the serum microRNA comprises hsa-miR-193a-5p, hsa-miR-143, hsa-miR-145, hsa-miR-29a, hsa-miR-133a, hsa-miR-505, hsa-miR-29c and hsa-miR-192, and a kit for liver cancer diagnosis and application thereof.
background
Primary liver cancer is a common malignant tumor with high morbidity and high mortality in the world, wherein Hepatocellular Carcinoma (liver cancer, HCC for short) accounts for more than 90% of primary liver cancer. The global cancer report 2014 published by the world health organization indicates that the fatality rate of the fifth malignant tumor listed in the new cases of the liver cancer in 2012 worldwide is the second, wherein the new and dead cases of the liver cancer in China account for about half of the global cases. Due to the lack of effective screening means, 60-70% of liver cancer patients are diagnosed at the late stage and the radical resection chance is missed. Therefore, early diagnosis and early treatment are the most effective ways to increase the survival rate of liver cancer patients and reduce the death rate of liver cancer.
The occurrence and development process of liver cancer is a multi-factor, multi-stage and multi-step process. Cirrhosis of the liver, of any cause, is the most common risk factor for liver cancer. In asia, chronic Hepatitis B Virus (HBV) induced hepatitis, cirrhosis, is the most major risk factor for inducing liver cancer. Most liver cancer patients are accompanied by pathological changes of hepatitis and liver cirrhosis, and the liver cancer is finally developed after the liver cancer and liver cirrhosis stages, which is called as liver cancer tribasic. It is estimated that the number of hepatitis B carriers is nearly 1.2 hundred million in China, and 20% of the carriers will develop into chronic hepatitis B patients, and 15% -40% of the chronic hepatitis B patients will further develop into cirrhosis. Therefore, the method can be used for monitoring the high risk group of liver cancer for a long time, finding and early warning early liver cancer as soon as possible, is convenient for determining a targeted individual prevention and treatment scheme, delays or even prevents the liver cancer, and is beneficial to improving the life quality of patients.
liver cancer is currently screened clinically mainly by serum alpha-fetoprotein (AFP) detection or imaging examination. Although AFP has been widely used in liver cancer screening, its sensitivity to detect liver cancer is not high enough: in patients clinically diagnosed with liver cancer, the AFP level in about 35-60% of liver cancer patients remains below the alert value (20 ng/ml); sensitivity in subclinical liver cancer is only 14-40%. Although imaging examination methods such as ultrasound, CT, MRI, etc. can be used as a supplement to AFP detection, these methods are expensive due to long-term follow-up screening, and the detection rate depends on the size of the tumor and the experience of the operator, so that misdiagnosis and missed diagnosis may occur. Therefore, the discovery of a new liver cancer early diagnosis marker which has high sensitivity, high specificity, low cost and easy detection has important clinical significance.
MicroRNA is a kind of endogenous small molecule non-coding RNA widely existing in eukaryote, and has the length of 18-24 nucleotides (nt). MicroRNA inhibits the expression of target genes horizontally after transcription, regulates and controls the vital activities of cell differentiation, proliferation, apoptosis and the like, and plays an important role in various physiological and pathological processes such as embryonic development, body metabolism, disease occurrence and development and the like. In recent years, researchers have proposed the concept of circulating microRNA by detecting microRNA in various body fluids such as blood, saliva, and urine. The body fluid samples such as blood and the like are easy to obtain, the clinical operability is strong, the wound is small, the stability of the circulating microRNA is good, and the detection is convenient, so that the circulating microRNA has the potential of being used as a noninvasive biomarker for diseases such as tumor and the like, and is suitable for screening of high risk groups.
Recent studies have indicated that liver cancer patients have different circulating microRNA expression profiles than non-liver cancer controls. For example, the level of miR-21, miR-122 and miR-223 in the serum of patients with liver cancer and patients with HBV hepatitis is higher than that of healthy people; miR-21 which is increased in the plasma of a liver cancer patient is down-regulated after the resection of the patient; li et al determined the classification combination of HBV hepatitis patients and healthy persons and liver cancer patients and healthy persons by detecting 513 individual serum microRNA expression profiles; zhou et al detected the microRNA level of nearly a thousand plasma specimens, and found that a classification module consisting of seven circulating microRNAs such as miR-122, miR-192, miR-21, miR-223, miR-26a, miR-27a and miR-801 can distinguish liver cancer from the total population of all non-liver cancer (including healthy people, hepatitis and liver cirrhosis patients) and diagnose AFP negative liver cancer. These studies suggest the potential of circulating micrornas as markers for liver cancer diagnosis.
however, the current research on circulating microRNA as a liver cancer diagnosis marker still has the following defects: (1) most researches only select previously reported microRNA with dysregulated expression in liver cancer tissues as a candidate index, and probably cannot comprehensively and objectively reflect the condition of circulating microRNA; (2) the sample size of part of research is small, and multi-center verification is lacked; (3) the control setting is imperfect, and the determined marker is difficult to be explained as a diagnosis marker specific to the liver cancer. Therefore, at present, it is still necessary to find a marker for early diagnosis of liver cancer with clinical application value, which is used for monitoring high risk group of liver cancer, so as to early warn early small liver cancer and facilitate clinicians to take appropriate prevention and treatment measures in time.
In the patent application 201410623463.3 of Zhongshan university, a liver cancer diagnosis marker composed of seven microRNAs including hsa-miR-29a, hsa-miR-29c, hsa-miR-133a, hsa-miR-143, hsa-miR-145, hsa-miR-192 and hsa-miR-505 is disclosed, and the liver cancer diagnosis marker has the characteristics of high early diagnosis sensitivity, good specificity and the like. Nevertheless, there remains a need in the art to provide other diagnostic marker combinations for liver cancer analysis.
Disclosure of Invention
The invention aims to solve the technical problems and provides a liver cancer diagnosis marker which is simple and convenient to operate and can effectively diagnose liver cancer.
In order to achieve the technical purpose, the invention provides a liver cancer diagnostic marker, which comprises nucleic acid molecules respectively encoding the following microRNA molecule combinations:
1) The combination is as follows: hsa-miR-193a-5p, hsa-miR-143 and hsa-miR-145;
2) Combining two: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a and hsa-miR-505;
3) combining three components: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-29c, hsa-miR-145 and hsa-miR-192;
4) And (4) combining: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a, hsa-miR-145, hsa-miR-192 and hsa-miR-505.
In a preferred embodiment, the microRNA is present at a higher level in the serum of a liver cancer patient 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 also provides a combination of microRNA molecules for liver cancer diagnosis, which includes the following microRNA combinations:
1) the combination is as follows: hsa-miR-193a-5p, hsa-miR-143 and hsa-miR-145;
2) Combining two: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a and hsa-miR-505;
3) Combining three components: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-29c, hsa-miR-145 and hsa-miR-192;
4) and (4) combining: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a, hsa-miR-145, hsa-miR-192 and hsa-miR-505.
in a preferred embodiment, the microRNA is present at a higher level in the serum of a liver cancer patient 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.
Specifically, the four liver cancer diagnostic combinations consisting of serum microRNAs are obtained by the following steps:
1. Screening candidate serum microRNA of a liver cancer patient different from a chronic hepatitis B patient by a high-throughput qPCR Array;
2. Verifying the microRNA of the candidate serum by real-time fluorescent quantitative PCR;
3. establishing serum microRNA combination capable of distinguishing liver cancer from non-cancer control (including healthy people, hepatitis and liver cirrhosis patients) in a training group consisting of healthy people, hepatitis, liver cirrhosis and liver cancer patients;
4. verifying the effect of the serum microRNA combination determined in the step 3 on diagnosing the liver cancer in two independent verification groups;
5. and (3) analyzing the diagnosis effect of the serum microRNA combination established in the step 3 in patients with small liver cancer, early BCLC and liver cancer negative AFP.
The experimental results are analyzed and relevant statistics show that: in the step 1, the inventor determines 19 candidate microRNAs through high-throughput qPCR Array screening, and verifies that the levels of the 19 candidate microRNAs in the serum of the liver cancer patient are all increased in the step 2. The level of candidate microRNAs in the training set (sample size of 257) was further examined, and the optimal serum microRNA combination for differentiating liver cancer from non-cancer controls was established. Furthermore, it was verified that the serum microRNA combinations could distinguish liver cancer from non-cancer controls in independent verification group 1 and verification group 2 (sample size: 352 and 139, respectively). Meanwhile, compared with the traditional liver cancer screening means, such as AFP, serum microRNA combination has better diagnosis effect in patients with small liver cancer, BCLC early stage and liver cancer negative by AFP.
In another aspect, the invention also discloses a diagnostic kit for liver cancer diagnosis, which comprises reagents for detecting the levels of the following microRNA molecules in serum respectively:
1) The combination is as follows: hsa-miR-193a-5p, hsa-miR-143 and hsa-miR-145;
2) combining two: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a and hsa-miR-505;
3) Combining three components: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-29c, hsa-miR-145 and hsa-miR-192;
4) and (4) combining: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a, hsa-miR-145, hsa-miR-192 and hsa-miR-505.
in one embodiment, the reagent for detecting the level of the microRNA molecule in serum is a real-time fluorescent quantitative PCR related reagent.
In still another preferred embodiment, the diagnostic kit further comprises a serum RNA extraction system and a reverse transcription system. In a preferred embodiment, the kit further comprises an assay for assessing whether or not there is liver cancer.
in a preferred embodiment, the diagnostic kit comprises LNA modified primers useful for detecting the following microRNA levels:
1) the combination is as follows: hsa-miR-193a-5p, hsa-miR-143 and hsa-miR-145;
2) Combining two: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a and hsa-miR-505;
3) Combining three components: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-29c, hsa-miR-145 and hsa-miR-192;
4) And (4) combining: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a, hsa-miR-145, hsa-miR-192 and hsa-miR-505.
preferably, the reagent for detecting the level of the combination of microRNA molecules in serum is a real-time fluorescent quantitative PCR related reagent.
More preferably, the diagnostic kit further comprises an LNA modified primer for detecting the exogenous reference NC 67. The level 2 of the target gene in a serum sample to be detected is obtained by external reference NC67 calibration-ΔCt(ΔCt＝Cttaget-Ctreference). And (3) respectively assigning the microRNA level of the detection sample to be 1 or 0 according to the microRNA threshold value, so as to realize discretization.
further, serum microRNA combinations are analyzed according to a logistic regression method respectively to evaluate whether the testee suffers from liver cancer:
1) the combination is as follows: logit (p ═ HCC) ═ -0.333-0.578 hsa-miR-193a-5p-0.531 hsa-miR-143-0.692 hsa-miR-145;
2) combining two: logit (p ═ HCC) — 0.343-0.407 ═ hsa-miR-193a-5p-0.595 ═ hsa-miR-29a-0.706 ═ hsa-miR-133a-0.480 ═ hsa-miR-505;
3) combining three components: logit (p ═ HCC) — 0.326-0.419 ═ hsa-miR-193a-5p-0.347 ═ hsa-miR-29a-0.354 × -hsa-miR-29 c-0.654 × -hsa-miR-145-0.423 × hsa-miR-192;
4) And (4) combining: logit (p ═ HCC) ═ 0.355-0.171 ═ hsa-miR-193a-5p-0.338 ═ hsa-miR-29a-0.531 × -hsa-miR-133 a-0.511 × -hsa-miR-145-0.462 × -hsa-miR-192-0.393 × -hsa-miR-505.
Wherein hsa-miR-193a-5p, hsa-miR-143, hsa-miR-145, hsa-miR-29a, hsa-miR-133a, hsa-miR-505, hsa-miR-29c and hsa-miR-192 are values obtained after discretization of corresponding serum microRNA detection levels, a Logit (p ═ HCC) value is taken as a diagnosis threshold value, liver cancer is diagnosed when the value is higher than 0.5, and non-liver cancer is diagnosed when the value is lower than 0.5. The diagnostic kit can be applied to liver cancer diagnosis.
The serum microRNA combination has the advantages of being used for liver cancer detection and early diagnosis: (1) the sample is easier to obtain, the clinical operability is stronger, the wound is smaller, the serum microRNA stability is better, and the detection is more convenient; (2) the experimental method is mature, the detection process is simpler and more convenient and is easy to repeat, and the method can be completed by common technicians; (3) the invention adopts high-throughput screening, multi-center verification and research in high risk group samples, comprehensively evaluates the effect of serum microRNA combination and a diagnostic kit, ensures the potential application value of the invention in liver cancer clinical diagnosis by the application of the method and the strategy, and provides a referable method strategy for the development of other disease biomarkers; (4) the serum microRNA liver cancer diagnosis kit can reflect the disease state of a liver cancer patient more timely, avoid complicated detection, save time and labor cost and facilitate clinicians to adopt personalized prevention and treatment schemes in time.
drawings
FIG. 1 is a ROC graph of training set and validation set of examples 4 and 5 of the present invention. Specifically, ROC plots for serum microRNA combinations and AFPs in training group (a), validation group 1(B), and validation group 2(C) to distinguish liver cancer from non-cancer controls (top panel) and high risk group (bottom panel).
FIG. 2 is a ROC plot in patients with small liver cancer (tumor ≦ 3cm) according to example 6 of the present invention. Specifically, ROC plots for the training group (a), validation group 1(B), validation group 2(C), and combinations of serum microRNA and AFP in the training group and all validation groups (D) to distinguish patients with small liver cancer from non-cancerous controls (left panel) and high risk groups (right panel).
FIG. 3 is a ROC plot of different BCLC staged liver cancer patients according to example 7 of the present invention. Specifically, ROC profiles of serum microRNA combinations and AFPs to differentiate between BCLC stage 0+ a (a), BCLC stage B (B), or BCLC stage C (C) liver cancer patients versus non-cancerous controls (top panel) and high risk population (bottom panel).
FIG. 4 is a ROC plot in AFP-negative liver cancer patients (AFP ≦ 20ng/ml) of example 8 of the present invention. Specifically, ROC plots for the training group (a), validation group 1(B), validation group 2(C), and combinations of serum micrornas in the training group and all validation groups (D) to distinguish AFP-negative liver cancer patients from non-cancerous controls (left panel) and high risk groups (right panel).
Detailed Description
In order that the invention may be more readily understood, reference is now made to the following description taken in conjunction with the accompanying drawings. It should be understood that these examples are for illustrative purposes only, and are not intended to limit the scope of the present invention; the drawings described are only schematic and are considered non-limiting.
example 1: collection and preparation of serum specimen
the inventor collects blood samples of healthy people (HC), hepatitis B carriers (IHC), chronic hepatitis B patients (CHB), cirrhosis patients (LC) and liver cancer patients (HCC) from 8 months to 2014 8 months in 2009, the groups meet the grouping standard (table 1), and liver cancer and a control group sample thereof are set according to the principle of gender and age matching.
training group: 257 serum specimens from healthy persons (51 cases), chronic hepatitis b patients (51 cases), cirrhosis patients (47 cases), and liver cancer patients (108 cases) collected from 8 to 3 months in 2009.
verification group 1: 352 serum specimens of healthy people (60 cases), chronic hepatitis b patients (68 cases), cirrhosis patients (71 cases) and liver cancer patients (153 cases) collected from 4 months to 2013 months in 2012.
verification group 2: 139 serum samples of healthy persons (48 cases), hepatitis b carriers (42 cases) and liver cancer patients (49 cases) collected from 5 to 8 months in 2013.
the clinical characteristics of the above-mentioned participating populations are shown in Table 2.
TABLE 1 grouping criteria for participating populations
The inclusion condition was referred to the american liver disease research association (AASLD)2009 guidelines for practice.
reference liver biopsy Metavir system.
Extracting peripheral venous blood of preoperative, healthy people, hepatitis B carriers, chronic hepatitis B patients and cirrhosis patients respectively by 4ml, and standing in a dry blood collection tube at 4 ℃ for more than half an hour. Centrifuging at 4 deg.C for 10min to obtain supernatant 400g, centrifuging at 4 deg.C for 10min to obtain supernatant 1800g, and packaging at-80 deg.C.
TABLE 2 clinical pathological characteristics of the participants in the training and validation groups
example 2: qPCR Array and data analysis thereof
Selecting serum samples of 6 liver cancer patients before operation and 8 chronic hepatitis B patients at least one year away from the last examination for qPCR Array screening. These patients were all male, and had no significant difference in age means, distribution (table 3).
TABLE 3 specimen clinical pathological characteristics for qPCR Array analysis
The invention is based on the use of Applied BiosystemsMethod for screening difference between liver cancer and chronic hepatitis B by Array Human MicroRNAIn total detecting 754 known human micrornas. See the Applied Biosystems website for specific steps. After the obtained original data are calibrated, differential microRNAs are selected by adopting a Significant Analysis of Microarray (SAM) analysis method, and finally 19 candidate microRNAs for subsequent verification are obtained by screening (Table 4).
TABLE 4. candidate microRNAs and exogenous reference information used in the present invention
Product number of Exiqon corporation
Example 3: real-time fluorescence quantitative PCR detection training set specimen microRNA level
1.1 serum RNA extraction
the invention adopts Trizol reagent extraction, and obtains serum RNA through methods of phenol/chloroform extraction and purification, isopropanol precipitation and glycogen assisted precipitation, and the specific steps are as follows:
1. 200 μ l of serum is taken, and an equal volume of Trizol lysate mixed with cel-miR-67(NC67, double-stranded RNA designed based on nematode miR-67 mature body sequence having no homology with human genome sequence, final concentration is 0.2nM, sequence shown in Table 4) is preferably added, and the mixture is fully shaken and mixed uniformly and ice-cooled for 15 min.
2. Adding 100 μ l of precooled chloroform, shaking and mixing evenly, and centrifuging at 12000g for 15min at 4 ℃.
3. Transferring supernatant, adding equal volume of precooled phenol/chloroform (1:1), shaking and mixing, and centrifuging at 14000g for 10min at 4 ℃. And this step is repeated once.
4. Transferring supernatant, adding equal volume of precooled chloroform, shaking and mixing uniformly, and centrifuging at 14000g for 15min at 4 ℃.
5. the supernatant is transferred, preferably by adding equal volume of isopropanol and glycogen (final concentration 200. mu.g/ml), shaken and mixed, and centrifuged at 16000g for 30min at 4 ℃.
6. The supernatant was carefully decanted, the pellet washed once with 1ml 70% ethanol, and centrifuged at 16000g for 10min at 4 ℃.
7. the supernatant was discarded, after ethanol was evaporated, 10. mu.l of DEPC was added to dissolve it, and the solution was stored at-80 ℃ for further use.
1.2 real-time fluorescent quantitative PCR (RT-qPCR)
The invention preferably uses Universal cDNA Synthesis reverse transcription kit to carry out reverse transcription on serum RNA with equal volume. Further preferably, SYBR Green qPCR master mix kit is adopted, cDNA diluted by 20 times is used as a template, and LNA modified primers are used for RT-qPCR detection. The reverse transcription kit, the qPCR detection kit and the LNA modified primers were purchased from Exiqon corporation (denmark).
The expression value 2 of the target microRNA is obtained through the calibration of an exogenous reference NC67-ΔCt(ΔCt＝Cttaget-Ctreference). The result shows that the level of 19 candidate microRNAs in the serum of the liver cancer patient is obviously increased.
Example 4: determination of optimal serum microRNA combination in training set
The samples of the training group are arranged from large to small according to respective detection levels of 19 microRNAs, and are sequentially subjected to value taking (only once if repeated values exist), the samples are judged to be positive or negative groups according to the value taking, the sensitivity and specificity of each value taking are obtained by combining the established class analysis of the samples, and an ROC Curve (Receiver operating characteristic Curve) is further drawn. And searching a point which enables the value of (sensitivity + specificity)/2 to be maximum, wherein the corresponding expression value is the discretization threshold value of the microRNA. And further assigning the samples with the values higher or lower than the threshold value as 1 or 0 respectively, so as to realize discretization for further model construction. The microRNA discretization threshold (table 4) adopted by the invention is used for discretization of corresponding microRNA data in a training group and a verification group, so that continuous variables are converted into binary variables.
The modeling results show that the following combinations have good effects on diagnosing liver cancer:
1) The combination is as follows: hsa-miR-193a-5p, hsa-miR-143 and hsa-miR-145;
2) combining two: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a and hsa-miR-505;
3) Combining three components: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-29c, hsa-miR-145 and hsa-miR-192;
4) And (4) combining: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a, hsa-miR-145, hsa-miR-192 and hsa-miR-505.
The formulas for evaluating whether liver cancer is suffered from are respectively:
(1) the combination is as follows: logit (p ═ HCC) ═ -0.333-0.578 hsa-miR-193a-5p-0.531 hsa-miR-143-0.692 hsa-miR-145;
(2) combining two: logit (p ═ HCC) — 0.343-0.407 ═ hsa-miR-193a-5p-0.595 ═ hsa-miR-29a-0.706 ═ hsa-miR-133a-0.480 ═ hsa-miR-505;
(3) Combining three components: logit (p ═ HCC) — 0.326-0.419 ═ hsa-miR-193a-5p-0.347 ═ hsa-miR-29a-0.354 × -hsa-miR-29 c-0.654 × -hsa-miR-145-0.423 × hsa-miR-192;
(4) And (4) combining: logit (p ═ HCC) ═ 0.355-0.171 ═ hsa-miR-193a-5p-0.338 ═ hsa-miR-29a-0.531 × -hsa-miR-133 a-0.511 × -hsa-miR-145-0.462 × -hsa-miR-192-0.393 × -hsa-miR-505.
wherein, hsa-miR-193a-5p, hsa-miR-143, hsa-miR-145, hsa-miR-29a, hsa-miR-133a, hsa-miR-505, hsa-miR-29c and hsa-miR-192 are values after corresponding serum microRNA detection level discretization.
the combination can distinguish liver cancer from non-cancer control or high risk population in a training group, and has good liver cancer diagnosis effect, which is shown in that AUC of serum microRNA combination is larger than AUC of AFP20 or AFP400 (20 or 400ng/ml is used as AFP threshold) (figure 1A).
Example 5: the effect of serum microRNA combination diagnosis of liver cancer in the verification group
Serum microRNA combinations established in the training set were used in the validation set to diagnose liver cancer. Similarly, experiments were performed using Trizol extraction and real-time fluorescent quantitative PCR detection. The combination can still distinguish liver cancer from non-cancer control or high risk group in verification groups 1 and 2, and has good liver cancer diagnosis effect, which is shown in that AUC of serum microRNA combination is greater than AUC of AFP20 or AFP400 (B, C in figure 1).
Example 6: diagnostic effect of serum microRNA combination in small liver cancer patients (tumor is less than or equal to 3cm)
The invention further proves that the serum microRNA composition has a good effect of diagnosing the small liver cancer. In the training group, the verification group 1 and the verification group 2, AUC of the small liver cancer diagnosis by the combinations is obviously greater than AFP; the results of the analysis of the training group combined with the three cases of the validation group also show that the AUC of these combinations for distinguishing small liver cancer from non-cancerous controls or high risk groups is much greater than AFP20 or AFP400 (fig. 2), which are:
The combination is as follows: 0.815vs 0.729 or 0.616, 0.813vs 0.711 or 0.615;
Combining two: 0.833vs 0.729 or 0.616, 0.824vs 0.711 or 0.615;
combining three components: 0.839vs 0.729 or 0.616, 0.819vs 0.711 or 0.615;
And (4) combining: 0.839vs 0.729 or 0.616, 0.835vs 0.711 or 0.615.
Example 7: diagnostic effect of serum microRNA combination in different BCLC staged liver cancer patients
the serum microRNA combination has better diagnosis effect in different BCLC staged liver cancer patients, the AUC of the combination is obviously greater than that of AFP, and especially in BCLC 0+ A stage, namely BCLC early stage, the advantages of the combination are more obvious: all non-cancer controls/high risk groups are taken as controls, and in the diagnosis of liver cancer at BCLC 0+ A stage, the AUC of the combination is respectively as follows: the combination is as follows: 0.805/0.802; combining two: 0.821/0.811; combining three components: 0.805/0.785; and (4) combining: 0.823/0.819; whereas AFP20 or AFP400 were 0.735/0.709 or 0.649/0647, respectively (FIG. 3).
Example 8: diagnostic effect of serum microRNA combination in AFP negative (AFP less than or equal to 20ng/ml) liver cancer patient
The serum microRNA composition has good diagnosis effect in AFP negative liver cancer patients. All non-cancer control/high risk groups were used as controls, and the AUC (fig. 4) of the combinations in the training group, the validation group 1, the validation group 2, and all central combinations for predicting AFP negative liver cancer were:
the combination is as follows: 0.819/0.824, 0.803/0.816, 0.883/0.831, and 0.819/0.818;
combining two: 0.762/0.763, 0.782/0.784, 0.789/0.731, and 0.780/0.769;
Combining three components: 0.830/0.818, 0.799/0.787, 0.858/0.782 and 0.819/0.795;
And (4) combining: 0.844/0.847, 0.797/0.801, 0.892/0.865 and 0.827/0.824.
Example 9: preparation of serum microRNA kit
The kit is used for diagnosing liver cancer, particularly early liver cancer, and consists of a serum RNA extraction system, a reverse transcription system, a real-time fluorescent quantitative PCR system, a primer system and a logistic regression analysis method for evaluating whether liver cancer is suffered or not.
in the serum RNA extraction system of the kit, the inventor adopts Trizol reagent for extraction, and obtains serum RNA by phenol/chloroform extraction and purification, isopropanol precipitation and glycogen precipitation. The inventors used a series of primers modified by LNA from Exiqon as the primer system of the kit for detecting the following molecules: hsa-miR-193a-5p, hsa-miR-143, hsa-miR-145, hsa-miR-29a, hsa-miR-133a, hsa-miR-505, hsa-miR-29c, hsa-miR-192 and NC67 (exogenous reference).
In the real-time fluorescent quantitative PCR system, the inventor adopts a reverse transcription kit of Exiqon company and a SYBR Green qPCR master mix kit for detection. Further analyzing serum microRNA combination according to a logistic regression method to evaluate whether the testee suffers from liver cancer:
The combination is as follows: logit (p ═ HCC) ═ -0.333-0.578 hsa-miR-193a-5p-0.531 hsa-miR-143-0.692 hsa-miR-145;
Combining two: logit (p ═ HCC) — 0.343-0.407 ═ hsa-miR-193a-5p-0.595 ═ hsa-miR-29a-0.706 ═ hsa-miR-133a-0.480 ═ hsa-miR-505;
combining three components: logit (p ═ HCC) — 0.326-0.419 ═ hsa-miR-193a-5p-0.347 ═ hsa-miR-29a-0.354 × -hsa-miR-29 c-0.654 × -hsa-miR-145-0.423 × hsa-miR-192;
And (4) combining: logit (p ═ HCC) ═ 0.355-0.171 ═ hsa-miR-193a-5p-0.338 ═ hsa-miR-29a-0.531 × -hsa-miR-133 a-0.511 × -hsa-miR-145-0.462 × -hsa-miR-192-0.393 × -hsa-miR-505.
Wherein, hsa-miR-193a-5p, hsa-miR-143, hsa-miR-145, hsa-miR-29a, hsa-miR-133a, hsa-miR-505, hsa-miR-29c and hsa-miR-192 are values after corresponding serum microRNA detection level discretization. Logit (p ═ HCC) ═ 0.5 is used as a diagnosis threshold, patients with liver cancer are treated above 0.5, and patients with non-liver cancer are treated below 0.5.
Claims (6)
1. Use of a nucleic acid molecule combination for the preparation of a liver cancer diagnostic kit, said nucleic acid molecule combination consisting of nucleic acid molecules encoding the following microRNA molecule combinations, respectively:
1) the combination is as follows: hsa-miR-193a-5p, hsa-miR-143 and hsa-miR-145;
2) Combining two: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a and hsa-miR-505;
3) Combining three components: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-29c, hsa-miR-145 and hsa-miR-192; or
4) And (4) combining: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a, hsa-miR-145, hsa-miR-192 and hsa-miR-505;
The liver cancer is primary hepatocellular carcinoma.
2. The use of claim 1, wherein the microRNA is present in serum of a liver cancer patient at a level higher than that of a healthy human, a hepatitis virus carrier, a chronic hepatitis patient or a liver cirrhosis patient.
Use of a microRNA molecular combination in the preparation of a liver cancer diagnostic agent, said microRNA molecular combination consisting of the following microRNA combinations:
1) The combination is as follows: hsa-miR-193a-5p, hsa-miR-143 and hsa-miR-145;
2) Combining two: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a and hsa-miR-505;
3) Combining three components: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-29c, hsa-miR-145 and hsa-miR-192; or
4) And (4) combining: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a, hsa-miR-145, hsa-miR-192 and hsa-miR-505;
the liver cancer is primary hepatocellular carcinoma.
4. the use according to claim 3, wherein the microRNA in the microRNA combination is present in serum of a liver cancer patient at a level higher than that of a healthy person, a hepatitis virus carrier, a chronic hepatitis patient or a liver cirrhosis patient.
5. Use of a reagent for detecting the level of a combination of microRNA molecules in serum for the preparation of a diagnostic kit for the diagnosis of liver cancer, said combination of microRNA molecules consisting of the following combinations of microRNA:
1) the combination is as follows: hsa-miR-193a-5p, hsa-miR-143 and hsa-miR-145;
2) Combining two: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a and hsa-miR-505;
3) Combining three components: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-29c, hsa-miR-145 and hsa-miR-192; or
4) And (4) combining: hsa-miR-193a-5p, hsa-miR-29a, hsa-miR-133a, hsa-miR-145, hsa-miR-192 and hsa-miR-505;
the liver cancer is primary hepatocellular carcinoma.
6. The use according to claim 5, wherein the logistic regression formula is:
1) The combination is as follows: logit (p ═ HCC) ═ -0.333-0.578 hsa-miR-193a-5p-0.531 hsa-miR-143-0.692 hsa-miR-145;
2) Combining two: logit (p ═ HCC) — 0.343-0.407 ═ hsa-miR-193a-5p-0.595 ═ hsa-miR-29a-0.706 ═ hsa-miR-133a-0.480 ═ hsa-miR-505;
3) combining three components: logit (p ═ HCC) — 0.326-0.419 ═ hsa-miR-193a-5p-0.347 ═ hsa-miR-29a-0.354 × -hsa-miR-29 c-0.654 × -hsa-miR-145-0.423 × hsa-miR-192;
4) And (4) combining: logit (p ═ HCC) ═ 0.355-0.171 × hsa-miR-193a-5p-0.338 × hsa-miR-29a-0.531 × hsa-miR-133a-0.511 × hsa-miR-145-0.462 × hsa-miR-192-0.393 hsa-miR-505;
Wherein hsa-miR-193a-5p, hsa-miR-143, hsa-miR-145, hsa-miR-29a, hsa-miR-133a, hsa-miR-505, hsa-miR-29c and hsa-miR-192 are values obtained after discretization of corresponding serum microRNA detection levels, a Logit (p ═ HCC) value is taken as a diagnosis threshold value, liver cancer is diagnosed when the value is higher than 0.5, and non-liver cancer is diagnosed when the value is lower than 0.5.
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