CN113025719A

CN113025719A - Biomarker for predicting liver cancer recurrence and application thereof

Info

Publication number: CN113025719A
Application number: CN202110427104.0A
Authority: CN
Inventors: 汪丽燕; 李滨
Original assignee: Affiliated Hospital of Guilin Medical University
Current assignee: Affiliated Hospital of Guilin Medical University
Priority date: 2021-04-20
Filing date: 2021-04-20
Publication date: 2021-06-25
Anticipated expiration: 2041-04-20
Also published as: CN113025719B

Abstract

The invention discloses a biomarker for predicting liver cancer recurrence and application thereof, wherein the biomarker comprises NAV3, PIGM and/or ZNF 483. The invention also discloses a related reagent and a kit. The invention also discloses application of the biomarker in constructing a calculation model for predicting liver cancer recurrence. The research of the invention provides a new strategy and thought for predicting the recurrence of the liver cancer.

Description

Biomarker for predicting liver cancer recurrence and application thereof

Technical Field

The invention belongs to the field of biological medicines, and particularly relates to a biomarker for predicting liver cancer recurrence and application thereof.

Background

Liver cancer is one of the most common malignant tumors, and the investigation of the world health organization in 2008 shows that there are about 748000 newly diagnosed liver cancer cases worldwide and about 695000 death cases in the same period. Liver cancer can be classified as early, intermediate, late and terminal liver cancer, as defined by imaging tumor size and number of nodules. The liver cancer can be classified into primary liver cancer, hepatic angiosarcoma, cholangiocystic adenocarcinoma, hepatoblastoma and the like according to different cell types. The primary liver cancer can be divided into 3 types of cholangiocellular carcinoma, hepatocellular carcinoma and mixed hepatocellular carcinoma and cholangiocellular carcinoma. The most common is liver cell type liver cancer, which accounts for over 90% of primary liver cancer. Liver cell type liver cancer can be classified into the following 5 types according to macroscopic morphology: diffuse type, massive type, nodular type and small cancer type.

Although the treatment technology of liver cancer is continuously improved, such as surgical resection, liver transplantation, radiotherapy and chemotherapy, the overall 5-year survival rate of liver cancer patients is not obviously improved yet. The main cause of death of liver cancer is recurrence, the recurrence mechanism of liver cancer is clarified, and the prevention of recurrence is the root for improving the survival rate of liver cancer patients. From the viewpoint of molecular biology, liver cancer is a genetic disease, because some chromosomal DNA damage causes gene mutation, including oncogenes, cancer suppressor genes, apoptosis genes, cell cycle regulatory genes, and genes maintaining the stability of cellular genome (such as DNA replication, DNA repair, and chromosome segregation genes), and the like, which are a multi-stage gradual evolution process.

In order to predict the recurrence of liver cancer as early as possible, a large number of basic and laboratory studies are carried out domestically and abroad, more and more studies are now dedicated to the study on molecular markers related to the recurrence of liver cancer, and it is expected that the molecular mechanism of the recurrence of liver cancer can be clarified from the perspective of molecular biology and the molecular markers capable of accurately predicting the recurrence of liver cancer can be found out, so that the medicine capable of effectively preventing and treating the recurrence of liver cancer can be developed.

Disclosure of Invention

The invention aims to provide a biomarker for predicting liver cancer recurrence, and has important significance for disclosing a molecular mechanism of the liver cancer recurrence and preventing and treating the liver cancer recurrence.

In a first aspect, the invention provides a product for predicting recurrence of liver cancer, the product comprising reagents for detecting biomarkers comprising NAV3, PIGM and/or ZNF 483.

Further, the biomarkers include ZNF483 and NAV 3.

Further, the biomarkers include ZNF483 and PIGM.

Further, the biomarkers include a combination of NAV3, PIGM, and ZNF 483.

In the present invention, NAV3 (gene ID: 89795) includes NAV3 gene and its encoded protein and its homologue, mutation, and isoform. The term encompasses full-length, unprocessed NAV3, as well as any form of NAV3 that results from processing in the cell. The term encompasses naturally occurring variants (e.g., splice variants or allelic variants) of NAV 3.

In the present invention, PIGM (Gene ID: 93183) includes the PIGM gene and its encoded protein and homologs, mutations, and isoforms. The term encompasses full-length, unprocessed PIGM, as well as any form of PIGM derived from processing in a cell. The term encompasses naturally occurring variants (e.g., splice variants or allelic variants) of PIGM.

In the present invention, ZNF483 (gene ID: 158399) includes ZNF483 gene and its encoded protein and homologs, mutations, and isoforms. The term encompasses full length, unprocessed ZNF483, as well as any form of ZNF483 that results from processing in a cell. The term encompasses naturally occurring variants (e.g., splice variants or allelic variants) of ZNF 483.

By "biomarker" is meant a compound, preferably a metabolite, that is differentially present (i.e., increases or decreases) in a biological sample of a subject or group of subjects having a first phenotype (e.g., having the disease) as compared to a biological sample of a subject or group of subjects having a second phenotype (e.g., not having the disease). Biomarkers can be differentially present at any level, but are generally present at levels that increase by at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 100%, at least 110%, at least 120%, at least 130%, at least 140%, at least 150%, or more; or generally at a level that is at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, or 100% (i.e., absent). The biomarkers are preferably present differentially at statistically significant levels (i.e., p-value less than 0.05 and/or q-value less than 0.10 as determined using the Welch T test or Wilcoxon rank sum test).

By "level" of one or more biomarkers is meant the absolute or relative amount or concentration of the biomarker in the sample.

By "sample" or "biological sample" is meant a biological material isolated from a subject. The biological sample may contain any biological material suitable for detecting a desired biomarker, and may comprise cellular and/or non-cellular material of the subject. The sample may be from any suitable biological tissue or fluid, such as liver tissue, blood, plasma, urine, or cerebrospinal fluid.

By "subject" is meant any animal, but preferably a mammal, such as a human, monkey, mouse, rabbit or rat.

Furthermore, the product comprises a chip, a kit and test paper.

Further, the chip comprises a gene chip and a protein chip, the gene chip comprises a solid phase carrier and a probe fixed on the solid phase carrier, preferably, the probe comprises a probe for detecting the transcription level of the biomarker; the protein chip comprises a solid phase carrier and an antibody which is fixed on the solid phase carrier and is specifically combined with the protein coded by the biomarker; the kit comprises a gene detection kit and a protein immunodetection kit; the gene detection kit comprises a reagent for detecting the transcription level of the biomarker; the protein immunoassay kit comprises an antibody specifically binding to a protein encoded by the biomarker; the strip includes reagents for detecting the level of transcription of the biomarker.

The kit of the invention can be accompanied with instructions for using the kit, wherein the instructions describe how to use the kit for detection, how to judge the recurrence of the liver cancer by using the detection result and how to select a treatment scheme.

The components of the kit may be packaged in aqueous medium or in lyophilized form. Suitable containers in the kit generally include at least one vial, test tube, flask, pet bottle, syringe, or other container in which a component may be placed and, preferably, suitably aliquoted. Where more than one component is present in the kit, the kit will also typically comprise a second, third or other additional container in which the additional components are separately disposed. However, different combinations of components may be contained in one vial. The kit of the invention will also typically include a container for holding the reactants, sealed for commercial sale. Such containers may include injection molded or blow molded plastic containers in which the desired vials may be retained.

In a second aspect, the invention provides the use of a reagent for the detection of a biomarker comprising NAV3, PIGM and/or ZNF483 in the manufacture of a product for predicting liver cancer recurrence.

Further, the biomarkers include ZNF483 and NAV 3.

Further, the biomarkers include ZNF483 and PIGM.

Further, the biomarkers include a combination of NAV3, PIGM, and ZNF 483.

Further, the reagent comprises a reagent for detecting the expression level of the biomarker by RT-PCR, real-time quantitative PCR, immunodetection, in situ hybridization, a chip or a high-throughput sequencing platform.

Further, the reagent for detecting the expression level of the biomarker by RT-PCR comprises a primer for specifically amplifying the biomarker; the reagent for detecting the expression level of the biomarker through real-time quantitative PCR comprises a primer for specifically amplifying the biomarker; the reagent for detecting the expression level of the biomarker by immunoassay comprises an antibody that specifically binds to a protein encoded by the biomarker; the reagent for detecting the expression level of the biomarker by in situ hybridization comprises a probe hybridized with a nucleic acid sequence of the biomarker; the reagent for detecting the expression level of the biomarker by the chip comprises a protein chip and a gene chip, wherein the protein chip comprises an antibody specifically bound with the protein coded by the biomarker, and the gene chip comprises a probe hybridized with a nucleic acid sequence of the biomarker.

Antibodies that specifically bind to the protein encoded by the biomarker include monoclonal antibodies, polyclonal antibodies. The antibodies include intact antibody molecules, any fragment or modification of an antibody (e.g., chimeric antibody, scFv, Fab, F (ab') 2, Fv, etc., so long as the fragment retains the ability to bind to the biomarker-encoding protein.

The term "monoclonal antibody" refers to an antibody from a population of substantially homogeneous antibodies. A population of substantially homogeneous antibodies comprises antibodies that are substantially similar and bind to the same epitope, except for variants that may normally occur during the production of a monoclonal antibody. These variants are usually present in only small amounts. Generally, monoclonal antibodies are obtained by a method comprising selecting a single antibody from a plurality of antibodies. For example, the selection process may be the selection of a unique clone from a plurality of clones, such as a library of hybridoma clones, phage clones, yeast clones, bacterial clones, or other recombinant DNA clones. For example, the selected antibody can be further altered to increase affinity for the target ("affinity maturation"), to humanize the antibody, to improve its product in cell culture, and/or to reduce its immunogenicity in the subject.

As used herein, a "probe" means an oligonucleotide molecule (e.g., a nucleotide sequence) that is at least partially complementary to a target nucleic acid sequence and thereby capable of hybridizing to the target nucleic acid sequence. In some cases, the probe may be referred to as a "capture probe". The probes may be naturally occurring in purified restriction digests or produced by synthetic, recombinant, or PCR amplification. The probe may be single-stranded or double-stranded. Probes can be used for detection, identification and isolation of sequences of specific genes. In embodiments of the invention, the probe may comprise a plurality of different probes. The probe may, for example, be dissolved in any suitable inorganic or organic solution, including but not limited to aqueous solutions, Phosphate Buffered Saline (PBS), EB buffer, TE buffer (10mM Tris-HCl and 1mM EDTA, pH 8.0), and the like.

The specific method of design and synthesis of the probe is not limited, and may be performed using any suitable method in the art, depending on the target nucleic acid sequence. For example, probes tailored to the target nucleic acid sequence of interest can be ordered from commercial companies (including but not limited to ThermoFisherScientific, Agilent, Nimblegen, IDT, etc.).

The length of the probe is not limited, it may vary, and is generally dependent on the experimental design. For example, the average length of the probe may be from about 20 to about 200 nucleotides, from about 50 to about 200 nucleotides, from about 20 to about 100 nucleotides, preferably from about 40 to about 85 nucleotides, preferably from about 45 to about 75 nucleotides, e.g., 45 nucleotides, but may alternatively be more than 200 nucleotides, e.g., about 250 nucleotides or longer.

In a third aspect, the invention provides the use of a biomarker for the construction of a computational model for predicting liver cancer recurrence, wherein the biomarker comprises NAV3, PIGM and/or ZNF 483.

As the skilled artisan will appreciate, the measurement of two or more markers may be used to improve the diagnostic question in the survey. The biochemical markers may be determined individually, or in one embodiment of the invention, they may be determined simultaneously, for example using a chip or bead-based array technology. The concentration of the biomarkers is then interpreted independently, for example using individual retention of each marker, or a combination thereof.

In the present invention, the step of associating a marker level with a certain likelihood or risk may be carried out and carried out in different ways. Preferably, the measured concentrations of the gene and one or more other markers are mathematically combined and the combined value is correlated to the underlying diagnostic problem. The determination of marker values may be combined by any suitable prior art mathematical method.

Further, the biomarkers include ZNF483 and NAV 3.

Further, the biomarkers include ZNF483 and PIGM.

Further, the biomarkers include a combination of NAV3, PIGM, and ZNF 483.

Furthermore, the calculation model takes NAV3 and/or PIGM and/or ZNF483 expression level as input variable, and carries out calculation by a bioinformatics method to output the risk probability of liver cancer recurrence.

In a fourth aspect, the present invention provides a composition comprising one or more of the following agents:

(1) an agent that promotes NAV3 expression;

(2) an agent that inhibits the expression of PIGM;

(3) an agent that inhibits expression of ZNF 483.

Further, the agent comprises an agent that promotes NAV3 expression and an agent that inhibits ZNF483 expression.

Further, the agent includes an agent that inhibits the expression of PIGM and an agent that inhibits the expression of ZNF 483.

Further, the agent includes an agent that promotes NAV3 expression, an agent that inhibits PIGM expression, and an agent that inhibits ZNF483 expression.

In a fifth aspect, the present invention provides a use of the composition of the fourth aspect in the preparation of a medicament for preventing and/or treating liver cancer recurrence.

In preparing the medicaments of the invention, the active ingredient is generally mixed with, or diluted with, excipients or enclosed in a carrier which may be in the form of a capsule or sachet. When the excipient serves as a diluent, it can be a solid, semi-solid, or liquid material that acts as a vehicle, carrier, or medium for the active ingredient. Thus, the medicament may be in the form of tablets, pills, powders, solutions, syrups, sterile injectable solutions, and the like. Examples of suitable excipients include lactose, dextrose, sucrose, sorbitol, mannitol, starch, microcrystalline cellulose, polyvinylpyrrolidone, cellulose, water, and the like. The preparation may further comprise a humectant, an emulsifier, a preservative (such as methyl and propyl hydroxybenzoate), a sweetener, etc.

The invention has the advantages and beneficial effects that:

the invention discovers for the first time that the recurrence of the liver cancer can be predicted by detecting the expression levels of NAV3, PIGM and ZNF483 genes, so that clinicians are guided to provide prevention schemes or treatment schemes for subjects, and the diagnosis is carried out by adopting biomarkers, so that the kit has timeliness, sensitivity and specificity.

Drawings

FIG. 1 is a ROC graph of NAV3, PIGM, ZNF483 combined diagnosis in the training set to predict recurrence of liver cancer.

FIG. 2 is a ROC graph of NAV3, PIGM and ZNF483 combined diagnosis in the validation set to predict recurrence of liver cancer.

Detailed Description

The technical solutions of the present invention are further illustrated by the following specific examples, which do not represent limitations to the scope of the present invention. Insubstantial modifications and adaptations of the present invention by others of the concepts fall within the scope of the invention.

Example 1 screening of Gene differentially expressed in recurrence of liver cancer

1. Data source

Chip data and clinical information of the GSE76427 data set were downloaded from GEO as a training set, and the sample size was 63:45 for relapse. And (3) downloading RNA-seq data and clinical information of liver cancer recurrence from a TCGA database as a verification set, wherein the sample size is non-recurrence and recurrence is 203: 168.

2. Data pre-processing

Joint processing, trimming and quality control are carried out on raw data by using fastp software, software default parameters are used for analysis, and high-quality sequencing data are output for subsequent analysis. Linker processing utilizes fastp software to default paired-end sequence automatic detection mode. The analyzed clean data was aligned to the human reference genome, version grch38.d1.vd1, using the Voom method, using ICGC software.

The GEO data was normalized by the RMA method, and annotated by a Platform file, and a plurality of probes corresponded to the same gene, and the average value was taken as the expression level of the gene.

3. Differential expression analysis

Differential expression analysis was performed using the "limma" package in R software, with screening criteria for differential genes being adj. pvalue < 0.05.

4. Results

NAV3 significantly reduced the expression level in the liver cancer relapse sample of GEO and TCGA compared to the liver cancer non-relapse sample (p 0.004 in GEO and 0.006 in TCGA); the expression level of PIGM is remarkably up-regulated in liver cancer recurrence samples of GEO and TCGA (p is 0.013 in GEO and 0.042 in TCGA); ZNF483 is obviously up-regulated in the liver cancer recurrence sample of GEO and TCGA (p is 0.019 in GEO and p is 0.000 in TCGA).

Example 2 diagnostic Performance validation

1. Experimental methods

Receiver Operating Curves (ROCs) were plotted using the R package "pROC" (version 1.15.0), AUC values, sensitivity and specificity were analyzed, and the diagnostic efficacy of the markers alone or in combination was judged. When the diagnosis efficiency of the index combination is judged, logistic regression is carried out on the expression level of each gene, the probability of whether each individual suffers from cancer is calculated through a fitted regression curve, different probability division threshold values are determined, and the sensitivity, specificity, accuracy and the like of the combined detection scheme are calculated according to the determined probability division threshold values.

2. Results of the experiment

NAV3, PIGM, ZNF483 alone or in combination in the training and validation sets as shown in tables 1 and 2 and figures 1 and 2, NAV3, PIGM, ZNF483 in combination showed higher diagnostic efficacy in both the training and validation sets, AUC values of 0.725 and 0.713, respectively, and sensitivity and specificity in the training sets of 0.644 and 0.778, respectively. The sensitivity and specificity of the validation set were 0.750 and 0.591, respectively.

TABLE 1 AUC values of genes in training set

Gene	AUC
		NAV3	0.615
PIGM	0.649
		ZNF483	0.635
NAV3+ZNF483	0.683
		PIGM+ZNF483	0.679
NAV3+PIGM+ZNF483	0.725

TABLE 2 AUC values of genes in the validation set

The above description of the embodiments is only intended to illustrate the method of the invention and its core idea. It should be noted that, for those skilled in the art, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications will also fall into the protection scope of the claims of the present invention.

Claims

1. A product for predicting recurrence of liver cancer, the product comprising an agent for detecting a biomarker comprising NAV3, PIGM and/or ZNF483, preferably the biomarker comprises ZNF483 and NAV3, preferably the biomarker comprises ZNF483 and PIGM, preferably the biomarker comprises a combination of NAV3, PIGM and ZNF 483.

2. The product of claim 1, wherein the product comprises a chip, a kit, or a strip.

3. The product of claim 2, wherein the chip comprises a gene chip and a protein chip, the gene chip comprises a solid phase carrier and probes immobilized on the solid phase carrier, the probes comprise probes for detecting the transcription level of the biomarker; the protein chip comprises a solid phase carrier and an antibody which is fixed on the solid phase carrier and is specifically combined with the protein coded by the biomarker; the kit comprises a gene detection kit and a protein immunodetection kit; the gene detection kit comprises a reagent for detecting the transcription level of the biomarker; the protein immunoassay kit comprises an antibody specifically binding to a protein encoded by the biomarker; the strip includes reagents for detecting the level of transcription of the biomarker.

4. Use of a detection reagent for a biomarker comprising NAV3, PIGM and/or ZNF483, preferably the biomarker comprises ZNF483 and NAV3, preferably the biomarker comprises ZNF483 and PIGM, preferably the biomarker comprises a combination of NAV3, PIGM and ZNF483, in the manufacture of a product for predicting liver cancer recurrence.

5. The use of claim 4, wherein the reagents comprise reagents for detecting the expression level of the biomarker by RT-PCR, real-time quantitative PCR, immunodetection, in situ hybridization, a chip or a high throughput sequencing platform.

6. The use of claim 5, wherein the reagent for detecting the expression level of the biomarker by RT-PCR comprises a primer for specifically amplifying the biomarker; the reagent for detecting the expression level of the biomarker through real-time quantitative PCR comprises a primer for specifically amplifying the biomarker; the reagent for detecting the expression level of the biomarker by immunoassay comprises an antibody that specifically binds to a protein encoded by the biomarker; the reagent for detecting the expression level of the biomarker by in situ hybridization comprises a probe hybridized with a nucleic acid sequence of the biomarker; the reagent for detecting the expression level of the biomarker by the chip comprises a protein chip and a gene chip, wherein the protein chip comprises an antibody specifically bound with the protein coded by the biomarker, and the gene chip comprises a probe hybridized with a nucleic acid sequence of the biomarker.

7. Use of a biomarker comprising NAV3, PIGM and/or ZNF483, preferably the biomarker comprises ZNF483 and NAV3, preferably the biomarker comprises ZNF483 and PIGM, preferably the biomarker comprises a combination of NAV3, PIGM and ZNF483, in the construction of a computational model for the prediction of liver cancer recurrence.

8. The use of claim 7, wherein the computational model is operated by bioinformatics using the biomarker expression level as an input variable to output a probability of risk of liver cancer recurrence.

9. A composition comprising one or more of the following agents:

(1) an agent that promotes NAV3 expression;

(2) an agent that inhibits the expression of PIGM;

(3) an agent that inhibits expression of ZNF 483;

preferably, the agent comprises an agent that promotes NAV3 expression and an agent that inhibits ZNF483 expression; preferably, the agent comprises an agent that inhibits the expression of PIGM and an agent that inhibits the expression of ZNF 483; preferably, the agent comprises an agent that promotes NAV3 expression, an agent that inhibits PIGM expression, and an agent that inhibits ZNF483 expression.

10. Use of the composition of claim 9 in the preparation of a medicament for the prevention and/or treatment of liver cancer recurrence.