CN111748623A

CN111748623A - Predictive marker and kit for recurrence of liver cancer patient

Info

Publication number: CN111748623A
Application number: CN202010513220.XA
Authority: CN
Inventors: 时程程; 王智慧; 张华鹏; 阎冰
Original assignee: First Affiliated Hospital of Zhengzhou University
Current assignee: Phoenix Intelligent Pharmaceutical Biotechnology Suzhou Co ltd
Priority date: 2020-06-08
Filing date: 2020-06-08
Publication date: 2020-10-09
Anticipated expiration: 2040-06-08
Also published as: CN111748623B

Abstract

The invention relates to the field of medical molecular diagnosis, in particular to a prognosis method of protein molecules in liver cancer diagnosis and application thereof; application of at least one protein of MRPL49 protein, CUTA protein, TIAL1 protein and CFL1 protein as a marker for determining whether liver cancer relapses in preparation of a liver cancer relapse determination reagent. According to the invention, an LC-MS/MS mass spectrometry is adopted, mass spectrometry is carried out on a large number of clinical samples, and 4 protein molecules can be determined to have good detection benefit through the difference multiple (more than 2 or less than 0.5) of the corresponding molecular contents of the cancer tissues of the patients with non-recurrent liver cancer and the cancer tissues of the patients with recurrent liver cancer; the protein is used as a biomarker to diagnose the prognosis condition of the liver cancer of a subject, the diagnosis is simple and easy, the diagnosis process is safe and effective, the diagnosis standard is uniformly accepted by the patient, and the influence of subjective factors is small.

Description

Predictive marker and kit for recurrence of liver cancer patient

Technical Field

The invention relates to the field of medical molecular diagnosis, in particular to a predictive marker and a kit for determining whether a liver cancer patient relapses.

Background

Cancer is a disease with great harm to human beings, and according to related epidemiological data, about 1100 million new cancers occur every year. Among many cancers, liver cancer is particularly dangerous, and has high morbidity and mortality, which respectively reside in the fifth and second places of the world.

Liver cancer is a malignant tumor occurring in the liver, and can be classified into primary liver cancer and metastatic liver cancer according to the cause, wherein primary liver cancer is the most common. According to the progress of hepatitis-cirrhosis-liver cancer, and China is a big country with hepatitis B, about 11 ten thousand people die of the disease every year, and new cases account for 54 percent of liver cancer patients all over the world, and the morbidity and mortality are rapidly increased.

In recent years, the diagnosis and treatment of liver cancer have been considerably advanced, but the prognosis is still poor in a large number of patients due to the lack of time for diagnosis. Relevant studies have shown that: in Asian population, early diagnosis can be achieved (the focus of liver cancer is less than 2 cm), the 5-year survival rate after operation can be improved to nearly 70%, and if the liver cancer reaches the middle and late stage, the prognosis is slightly better than that of pancreatic cancer at the current diagnosis and treatment level, and the 5-year survival rate can only reach 16%.

Hepatocellular carcinoma (liver cancer for short) is one of high-degree tumors in China, has high morbidity and mortality and seriously threatens the life health of human beings. Radical surgical resection treatment is the most main treatment mode at present, but the recurrence and metastasis rate after operation still reaches 40% -80%, which is the main reason of poor prognosis of liver cancer. The occurrence and development of liver cancer are associated with the expression of a great number of genes, which involve a large number of proteins that play an important role in the formation of liver recurrent tissue microvasculature and matrix destruction. The use of these proteins makes it possible to understand how some liver cancers recur and metastasize. Therefore, we should search the corresponding gene expression profile related to liver cancer recurrence to determine the prognosis of liver cancer, so as to perform the timely postoperative intervention on liver cancer. If the analysis is carried out in the specimen after surgical resection and the risk of recurrence of the patient can be accurately predicted, the high-risk recurrence population can be paid attention to, and the survival period of the liver cancer is prolonged.

Therefore, the development of the method for diagnosing whether the liver cancer patient relapses has very important practical significance for reducing the incidence and mortality of the liver cancer.

Disclosure of Invention

Technical problem to be solved

Aiming at the defects of the prior art, the invention provides a predictive marker and a kit for determining whether a liver cancer patient relapses, wherein the content of the marker is detected by adopting a mass spectrometry method to judge the risk of postoperative relapse of the liver cancer patient; the method is simple and practical, and the sensitivity and specificity of the detection method can be better improved through the detection of various small molecules.

(II) technical scheme

In order to achieve the purpose, the invention is realized by the following technical scheme:

application of at least one protein of MRPL49 protein, CUTA protein, TIAL1 protein and CFL1 protein as a marker for determining whether liver cancer relapses in preparation of a liver cancer relapse determination reagent.

The application of at least one specific nucleic acid probe of MRPL49 specific nucleic acid probe, CUTA specific nucleic acid probe, TIAL1 specific nucleic acid probe and CFL1 specific nucleic acid probe in preparing liver cancer recurrence diagnosis kit.

A kit for diagnosing liver cancer relapse comprises at least one reagent of a reagent for specifically detecting MRPL49 protein, a reagent for specifically detecting CUTA protein, a reagent for specifically detecting TIAL1 protein and a reagent for specifically detecting CFL1 protein.

Preferably, the agent for specifically detecting the MRPL49 protein is a primer or probe that specifically recognizes the nucleic acid of MRPL49 protein; the reagent for specifically detecting the CUTA protein is a primer or a probe for specifically recognizing the nucleic acid of the CUTA protein; the reagent for specifically detecting the TIAL1 protein is a primer or a probe which specifically recognizes the nucleic acid of the TIAL1 protein; the reagent for specifically detecting the CFL1 protein is a primer or a probe which specifically recognizes the CFL1 protein nucleic acid.

A prognostic method for a marker of whether a patient with liver cancer has relapsed, comprising the steps of: and detecting the protein expression quantity intensity value of MRPL49 protein, CUTA protein, TIAL1 protein or CFL1 protein in the sample to be detected by adopting an LC-MS/MS mass spectrometry.

Preferably, when the protein expression intensity value of MRPL49 protein in the sample is less than 37923871, the patient is judged to be a relapse patient, otherwise, the patient is judged to be a non-relapse patient after operation, and the false positive rate is 8.6%.

Preferably, when the protein expression intensity value of the CUTA protein in the sample is less than 382233711.7, the patient is judged to be a relapse patient, otherwise, the patient is judged to be a non-relapse patient after operation, and the false positive rate is 22.9%.

Preferably, when the protein expression intensity value of the TIAL1 protein in the sample is less than 131017834, the patient is judged to be a relapse patient, otherwise, the patient is judged to be a non-relapse patient after operation, and the false positive rate is 22.9%.

Preferably, the CFL1 protein expression intensity value in the sample is less than 6181959261, the sample is judged to be a relapse patient, otherwise, the sample is judged to be a non-relapse patient after operation, and the false positive rate is 22.9%.

(III) advantageous effects

Compared with the prior art, the invention has the following beneficial effects:

(1) the invention adopts LC-MS/MS mass spectrometry to detect the sample to be detected, after mass spectrometry is carried out on a large number of clinical samples, 4 protein molecules are determined to have good detection benefit by the difference multiple (more than 2 or less than 0.5) of the corresponding molecular contents of the cancer tissues of the patients without liver cancer recurrence and the cancer tissues of the patients with liver cancer recurrence. The 4 protein molecules (MRPL 49 protein, CUTA protein, TIAL1 protein and CFL1 protein) can be used as markers for diagnosing whether the liver cancer is recurrent.

(2) The invention takes MRPL49 protein, CUTA protein, TIAL1 protein and CFL1 protein as biomarkers to diagnose the postoperative recurrence risk of the liver cancer of a subject, is simple and easy to implement, has safe and effective diagnosis process, is easy to be accepted by patients, and has less influence of individual subjective factors on the unified diagnosis standard.

(3) The method can provide a new treatment target and thought for the research and development of anti-liver cancer relapse drugs in the future through the biomarkers detected by mass spectrometry.

Drawings

FIG. 1 is a ROC plot of protein expression intensity values of MRPL49 protein;

FIG. 2 is a graph showing the intensity values of protein expression levels of MRPL49 protein in a liver cancer recurrent tissue and a postoperative non-recurrent tissue;

FIG. 3 is a ROC graph showing the protein expression level intensity values of the CUTA protein;

FIG. 4 is a graph showing the intensity of the protein expression level of the CUTA protein in the recurrent tissue of liver cancer and the non-recurrent tissue after surgery;

FIG. 5 is a ROC plot of protein expression intensity values for TIAL1 protein;

FIG. 6 is a graph showing the intensity of protein expression levels of TIAL1 protein in a recurrent tissue of liver cancer and a non-recurrent tissue after surgery;

FIG. 7 is a ROC graph showing the intensity values of protein expression levels of CFL1 protein;

FIG. 8 is a graph showing the intensity of protein expression levels of CFL1 protein in a liver cancer recurrent tissue and a postoperative non-recurrent tissue.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Screening of biomarkers associated with liver cancer diagnosis

1. Experimental procedure

(1) Protein sample information

Sample preparation: samples from the liver cancer recurrent tissue were taken in 5 cases and 35 cases from the postoperative non-recurrent tissue, respectively.

(2) Sample pretreatment

Extracting protein from a sample by adopting an SDT (4% (w/v) sodium dodecyl sulfate, 100mM Tris/HCl pH7.6, 0.1M dithiothreitol) cracking method, and then carrying out protein quantification by adopting a BCA method; taking a proper amount of protein from each sample, carrying out trypsin enzymolysis by using a filtered protein preparation (FAS) method, desalting peptide fragments by using C18 Cartridge, adding 40 mu L of 0.1% formic acid solution for redissolving after freeze-drying the peptide fragments, and quantifying the peptide fragments (OD 280).

The BCA method is used for protein quantification, and is characterized in that the protein concentration can be calculated according to the light absorption value, and the protein binds Cu under the alkaline condition²⁺Reduction to Cu⁺，Cu⁺Form a purple colored complex with BCA reagent, two molecules of BCA chelate a Cu⁺. And comparing the absorption value of the water-soluble compound at 562nm with a standard curve to calculate the concentration of the protein to be detected.

(3) LC-MS/MS data acquisition

Each sample was separated using a nanoliter flow rate HPLC liquid phase system Easy nLC.

Wherein: the buffer solution A was 0.1% formic acid aqueous solution, and the solution B was 0.1% formic acid acetonitrile aqueous solution (acetonitrile: 84%).

The column was equilibrated with 95% solution A, and the sample was applied to a loading column (Thermo scientific Acclaim PepMap100, 100. mu.m. by 2cm, NanoViper C18) by an autosampler and separated by an analytical column (Thermo scientific easy column, 10cm, ID 75. mu.m, 3. mu.m, C18-A2) at a flow rate of 300 nL/min.

After chromatographic separation, the sample is subjected to mass spectrometry by using a Q-exact mass spectrometer. The detection method is positive ion, the scanning range of the parent ion is 300-1800 m/z, the first-order mass spectrum resolution is 70,000 at 200m/z, the AGC (automatic gain control) target is 1e6, the Maximum IT is 50ms, and the Dynamic exclusion time (Dynamic exclusion) is 60.0 s. The mass-to-charge ratio of the polypeptide and the polypeptide fragments was collected as follows: 20 fragment patterns (MS 2 scan) were collected after each full scan (full scan), MS2 Activation Type was HCD, Isolation window was 2m/z, secondary mass resolution 17, 500 at 200m/z, Normalized fusion Energy was 30eV, and Underfill was 0.1%.

(4) Protein identification and quantitative analysis

The RAW data of mass spectrometry is RAW file, and the software MaxQuant software (version number 1.5.3.17) is used for library checking and quantitative analysis.

iBAQ Intensity is the amount of protein expressed in sample X based on the iBAQ algorithm, and is approximately equal to the absolute concentration of protein in that sample. LFQ Intensity is the relative protein expression of sample X based on the LFQ algorithm, and is often used for group comparisons. One of them is generally selected by Labelfree as a quantitative result.

IBAQ (Intensity-based absorbance quantification) and LFQ belong to two different protein quantification algorithms provided by Maxquant software.

iBAQ is generally used for absolute quantification of proteins in samples, the main algorithm being based on the ratio of the sum of the intensities of the peptides identified for the protein to the theoretical number of peptides.

LFQ is generally used for pairwise quantitative comparisons between groups, the main algorithm being pair-wise correction through peptide and protein multilayers. This patent uses LFQ for protein quantification.

(5) Statistical analysis

Carrying out ratio calculation and statistical analysis on data which conform to at least two non-null values in the same group of the three-time repeated data, wherein the data comprise LFQ or iBAQ strength value ratios and P-values of all comparison groups; and (5) preliminarily screening out the difference foreign matters among the groups.

Whether the differential protein substance has significance is further verified according to P-value. Selecting a protein which has multidimensional statistical analysis of Fold change >2 or <0.5 and is considered that the content of the protein has obvious Fold difference between the cancer tissue and the tissue beside the cancer, and screening out the protein with univariate statistical analysis P value <0.05 as the protein with significant difference; thereby obtaining the differential protein molecules. Then, SPSS software is used for making a ROC curve of the differential protein, and the area under the curve (AUC) is calculated, so that the diagnostic value of the differential protein is judged. The specific judgment method is that the area under the AUC line is more than 0.7, P is less than 0.05, and the threshold standard (cut off value) when the John's index is maximum is used as the threshold standard for judging whether the tumor is present or not (if the multiple is more than 2, the tumor detection is positive if the multiple is more than the threshold, and if the multiple is less than 0.5, the liver cancer detection is positive if the multiple is less than the threshold), thereby obtaining higher sensitivity and specificity.

(6) Bioinformatics analysis

(GO) functional Annotation

The GO Annotation of a target protein set by using Blast2GO can be roughly summarized into four steps of sequence alignment (Blast), GO entry extraction (Mapping), GO Annotation (Annotation) and InterProScan supplementary Annotation (Annotation).

② KEGG pathway notes

The target protein set was annotated with the KEGG pathway using kaas (KEGG automated Annotation server) software.

Enrichment analysis of GO annotations and KEGG annotations

And comparing the distribution of each GO classification or KEGG channel in the target protein set and the total protein set by adopting Fisher's Exact Test, and performing GO annotation or KEGG channel annotation enrichment analysis on the target protein set.

Protein clustering analysis

First, quantitative information of a target protein set is normalized (normalized to a (-1, 1) interval). Then, two dimensions of the expression amounts of the sample and the protein were simultaneously classified using a Complexheatmap R package (R Version 3.4) (distance algorithm: Euclidean, ligation: Average linkage), and a hierarchical clustering heat map was generated.

Analysis of protein interaction network

The interaction relationship between the target proteins was found based on the information in the STRING database, and the interaction network was generated and analyzed using the Cytoscape software (version number: 3.2.1).

(7) Differentially expressed protein screening

Differentially expressed proteins were screened for numbers of differentially expressed proteins for each comparative group using criteria with fold change greater than 2.0 fold (up-regulation greater than 2 fold or down-regulation less than 0.5) and P value less than 0.05.

(8) Basic principle of experiment

Unlabeled quantitative proteomics (Label-free) technology has become an important method of mass spectrometry in recent years. There are two main quantitative principles of the Label-free technology: firstly, the development of non-labeled quantitative methods of spectra counts is earlier, and a plurality of quantitative algorithms are formed, but the core principle is that the identification result of MS2 is used as the basis of quantification, and the difference of the various methods lies in the correction of high-throughput data by a later algorithm; the principle of the second unlabeled quantification method is based on MS1, and the integral of each peptide fragment signal on LCMS chromatography is calculated. The Maxquant algorithm adopted by the invention is based on the second principle.

2. Results of the experiment

By mass spectrum data analysis and comparison of protein micromolecules of the liver cancer recurrent tissue and the non-recurrent tissue (non-recurrent after operation), 4 protein molecules are obtained and can be used as biomarkers related to liver cancer recurrence.

In order to evaluate the diagnosis efficiency of the protein expression intensity value of the protein molecule on liver cancer, the invention adopts ROC curve analysis, and AUC is the area under the ROC curve, is the most commonly used parameter for evaluating the characteristics of the ROC curve, and is also an important test accuracy index. If the AUC is below 0.7, the diagnosis accuracy is low; the AUC is more than 0.7, so that the requirement of clinical diagnosis can be met.

Specific results and analyses were as follows:

(1) by adopting LC-MS/MS mass spectrometry, the difference of MRPL49 protein in the liver cancer recurrent tissue and the postoperative non-recurrent tissue is detected.

The research finds that the MRPL49 protein is significantly down-regulated by 0.24 times in a liver cancer recurrence sample, and the p value is less than 0.05.

As shown in FIG. 1, the AUC of MRPL49 protein is 0.943> 0.7, which indicates that MRPL49 protein has a good judgment effect, i.e., can be used as a marker for recurrence after liver cancer surgery.

When the cut off value of MRPL49 protein is 37923871, the sensitivity is 100% and the specificity is 91.4%. When individual detection is carried out, the protein expression intensity value of MRPL49 protein is less than 37923871, the patient is judged to be a patient with recurrent liver cancer, otherwise, the patient is judged to be a patient without recurrent liver cancer after operation (the false positive rate is 8.6%).

As can be seen from FIG. 2, the liver cancer recurrent tissue samples are mainly distributed below the detection threshold (solid line in FIG. 2), and the postoperative non-recurrent tissue samples are mainly distributed above the detection threshold, indicating that the difference between the protein expression level intensity values of the liver cancer recurrent tissue and the postoperative non-recurrent tissue is large, and the detection threshold has a good detection effect.

In conclusion, the MRPL49 protein can be used as a predictive marker for recurrence after liver cancer surgery.

(2) The difference of the CUTA protein in the liver cancer recurrent tissue and the postoperative non-recurrent tissue is detected by adopting an LC-MS/MS mass spectrometry.

Research shows that the CUTA protein is down-regulated by 0.34 times in the significance of the liver cancer recurrence sample, and the p value is less than 0.05.

As can be seen from FIG. 3, the AUC of the CUTA protein is 0.863 >0.7, which indicates that the CUTA protein has a better judgment effect, i.e., the CUTA protein can be used as a marker for the recurrence of the liver cancer after the operation.

When the protein expression level intensity value of the CUTA protein was 382233711.7, the sensitivity was 100% and the specificity was 77.1%. When the individual detection is carried out, the protein expression intensity value of the CUTA protein is less than 382233711.7, the patient is judged to be a relapse patient, otherwise, the patient is judged to be a non-relapse patient after the operation (the false positive rate is 22.9%).

As can be seen from fig. 4, the liver cancer recurrent tissue samples are mainly distributed below the detection threshold (solid line in fig. 4), and the postoperative non-recurrent tissue samples are mainly distributed above the detection threshold, which indicates that the difference between the protein expression level intensity values of the liver cancer recurrent tissue and the postoperative non-recurrent tissue is large, and the detection threshold has a good detection effect.

In summary, the CUTA protein can be used as a predictive marker for recurrence after liver cancer operation.

(3) By adopting LC-MS/MS mass spectrometry, the TIAL1 protein is detected to have difference between the liver cancer recurrent tissue and the postoperative non-recurrent tissue.

The research finds that the TIAL1 protein is significantly down-regulated by 0.49 times in the liver cancer recurrence sample, and the p value is less than 0.05.

As shown in FIG. 5, the AUC of the TIAL1 protein is 0.869>0.7, which indicates that the protein has a better judgment effect, i.e., the TIAL1 protein can be used as a marker for the recurrence of the liver cancer after the operation.

When the protein expression level intensity value of the TIAL1 protein was 131017834, the sensitivity was 100% and the specificity was 77.1%. When the individual test was carried out, the protein expression level intensity value of the TIAL1 protein was less than 131017834, and the patient was judged to be a relapsed patient, otherwise, the patient was judged to be a non-relapsed patient after the operation (false positive rate was 22.9%).

As can be seen from fig. 6, the liver cancer recurrent tissue samples are mainly distributed below the detection threshold (solid line in fig. 6), and the postoperative non-recurrent tissue samples are mainly distributed above the detection threshold, indicating that the difference between the protein expression level intensity values of the liver cancer recurrent tissue and the postoperative non-recurrent tissue is large, and the detection threshold has a good detection effect.

In conclusion, the TIAL1 protein can be used as a predictive marker for recurrence after liver cancer operation.

(4) By adopting LC-MS/MS mass spectrometry, the difference of the CFL1 protein in the liver cancer recurrent tissue and the postoperative non-recurrent tissue is detected.

The research finds that the CFL1 protein is down-regulated by 0.49 times in the significance of the liver cancer recurrence sample, and the p value is less than 0.05.

As can be seen from FIG. 7, the AUC of CFL1 protein is 0.886 >0.7, which indicates that CFL1 protein has a good judgment effect, i.e., can be used as a marker for the recurrence of liver cancer after surgery.

When the protein expression intensity value of the CFL1 protein was 6181959261, the sensitivity was 80% and the specificity was 77.1%. When the individual detection is carried out, the protein expression intensity value of the CFL1 protein is less than 6181959261, the patient is judged to be a relapse patient, otherwise, the patient is judged to be a non-relapse patient after the operation (the false positive rate is 22.9%).

As can be seen from FIG. 8, the liver cancer recurrent tissue samples were mainly distributed below the detection threshold (solid line in FIG. 8), and the non-recurrent tissue samples were mainly distributed above the detection threshold, indicating that the difference in the protein expression level between the liver cancer recurrent tissue and the postoperative non-recurrent tissue was large, and the detection threshold had a good detection effect.

In conclusion, the protein of CFL1 can be used as a predictive marker for recurrence after liver cancer surgery.

Example 1

Application of MRPL49 protein as a marker of whether liver cancer recurs in preparation of a liver cancer recurrence judgment reagent.

Application of the MRPL49 specific nucleic acid probe in preparing a liver cancer recurrence diagnosis kit.

A kit for diagnosing liver cancer relapse comprises a reagent for specifically detecting MRPL49 protein; the reagent for specifically detecting the MRPL49 protein is a probe which specifically recognizes MRPL49 protein nucleic acid.

A prognostic method for a marker of whether a patient with liver cancer has relapsed, comprising the steps of: detecting the protein expression quantity intensity value of MRPL49 protein in the sample to be detected by adopting an LC-MS/MS mass spectrometry; when the protein expression intensity value of MRPL49 protein in the sample is less than 37923871, the patient is judged to be a relapse patient, otherwise, the patient is judged to be a non-relapse patient after operation, and the false positive rate is 8.6%.

Example 2

The CUTA protein is used as a marker for determining whether liver cancer recurs and is applied to the preparation of a liver cancer recurs determination reagent.

The CUTA specific nucleic acid probe is applied to the preparation of a liver cancer recurrence diagnosis kit.

A kit for diagnosing liver cancer recurrence comprises a reagent for specifically detecting a CUTA protein; the reagent for specifically detecting the CUTA protein is a probe for specifically recognizing the nucleic acid of the CUTA protein.

A prognostic method for a marker of whether a patient with liver cancer has relapsed, comprising the steps of: detecting the protein expression quantity intensity value of the CUTA protein in the sample to be detected by adopting an LC-MS/MS mass spectrometry; when the protein expression intensity value of the CUTA protein in the sample is less than 382233711.7, the patient is judged to be a relapse patient, otherwise, the patient is judged to be a non-relapse patient after operation, and the false positive rate is 22.9%.

Example 3

The use of TIAL1 protein as a marker for determining whether liver cancer is recurrent in the preparation of a reagent for determining recurrence of liver cancer.

The application of the TIAL1 specific nucleic acid probe in preparing a kit for diagnosing liver cancer recurrence.

A kit for diagnosing liver cancer recurrence comprises a reagent for specifically detecting TIAL1 protein; the reagent for specifically detecting the TIAL1 protein is a probe that specifically recognizes the nucleic acid of the TIAL1 protein.

A prognostic method for a marker of whether a patient with liver cancer has relapsed, comprising the steps of: detecting a protein expression quantity intensity value of the TIAL1 protein in the sample to be detected by adopting an LC-MS/MS mass spectrometry; when the protein expression intensity value of the TIAL1 protein in the sample is less than 131017834, the patient is judged to be a relapse patient, otherwise, the patient is judged to be a non-relapse patient after operation, and the false positive rate is 22.9%.

Example 4

The CFL1 protein is used as a marker for determining whether liver cancer is relapsed and is applied to the preparation of a liver cancer relapse determination reagent.

Application of the CFL1 specific nucleic acid probe in preparing a liver cancer recurrence diagnosis kit.

A kit for diagnosing liver cancer recurrence comprises a reagent for specifically detecting CFL1 protein; the reagent for specifically detecting the CFL1 protein is a probe which specifically recognizes the nucleic acid of the CFL1 protein.

A prognostic method for a marker of whether a patient with liver cancer has relapsed, comprising the steps of: detecting a protein expression quantity intensity value of the CFL1 protein in the sample to be detected by adopting an LC-MS/MS mass spectrometry; when the protein expression intensity value of the CFL1 protein in the sample is less than 6181959261, the patient is judged to be a relapse patient, otherwise, the patient is judged to be a non-relapse patient after operation, and the false positive rate is 22.9%.

The invention takes MRPL49 protein, CUTA protein, TIAL1 protein and CFL1 protein as biomarkers to diagnose liver cancer of a tested person, is simple and easy to implement, has safe and effective diagnosis process, is easy to be accepted by patients, has unified diagnosis standard and has less influence by subjective factors.

The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

Application of at least one protein selected from MRPL49 protein, CUTA protein, TIAL1 protein and CFL1 protein as a marker for determining whether liver cancer relapses in preparation of a liver cancer relapse determination reagent.
Application of at least one specific nucleic acid probe of MRPL49 specific nucleic acid probe, CUTA specific nucleic acid probe, TIAL1 specific nucleic acid probe and CFL1 specific nucleic acid probe in preparation of liver cancer recurrence diagnosis kit.
3. A kit for diagnosing liver cancer recurrence is characterized by comprising at least one reagent of a reagent for specifically detecting MRPL49 protein, a reagent for specifically detecting CUTA protein, a reagent for specifically detecting TIAL1 protein and a reagent for specifically detecting CFL1 protein.
4. The kit for diagnosing liver cancer recurrence according to claim 3, wherein the reagent for specifically detecting MRPL49 protein is a primer or a probe that specifically recognizes MRPL49 protein nucleic acid; the reagent for specifically detecting the CUTA protein is a primer or a probe for specifically recognizing the nucleic acid of the CUTA protein; the reagent for specifically detecting the TIAL1 protein is a primer or a probe which specifically recognizes the nucleic acid of the TIAL1 protein; the reagent for specifically detecting the CFL1 protein is a primer or a probe which specifically recognizes the CFL1 protein nucleic acid.
5. A method for predicting a marker for whether a patient with liver cancer has relapsed, comprising the steps of: and detecting the protein expression quantity intensity value of MRPL49 protein, CUTA protein, TIAL1 protein or CFL1 protein in the sample to be detected by adopting an LC-MS/MS mass spectrometry.
6. The method for predicting whether a patient with liver cancer will relapse according to claim 5, wherein the sample is judged to be a relapsed patient when the protein expression level of MRPL49 protein in the sample is less than 37923871, or not to be a relapse-free patient after surgery, and the false positive rate is 8.6%.
7. The method for predicting whether a patient with liver cancer will relapse according to claim 5, wherein the sample is judged to be a relapsed patient when the protein expression level of the CUTA protein is less than 382233711.7, or is judged to be a non-relapsed patient after surgery, and the false positive rate is 22.9%.
8. The method for predicting whether a patient with liver cancer will relapse according to claim 5, wherein the sample is classified as a relapsing patient when the protein expression level of TIAL1 protein is less than 131017834, or as a non-relapsing patient after surgery, and the false positive rate is 22.9%.
9. The method for predicting whether a patient with liver cancer will relapse according to claim 5, wherein the sample is judged to be a relapsed patient when the intensity value of the protein expression level of CFL1 protein is less than 6181959261, or not to be a relapse-free patient after surgery, and the false positive rate is 22.9%.