CN117646068A - Tumor marker and application thereof in preparation of gastric cancer diagnosis product - Google Patents
Tumor marker and application thereof in preparation of gastric cancer diagnosis product Download PDFInfo
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Abstract
The invention discloses a tumor marker and application thereof in preparing gastric cancer diagnosis products, belonging to the field of epigenetic and oncology. The invention studies 6 RNA editing sites of 4 genes in tumor mucosa and adjacent normal mucosa of GC patient: the editing level of F11R chr1:160996561, F11R chr1:160996562, PSMD12:chr17:67338769, ERO1A:chr14:52643014, IGFBP7:chr4:57110068 and IGFBP7:chr4:57110120 are obviously different, the 4 different genes are related to the occurrence and the development of cancer, and the combination of RNA editing has high accuracy for diagnosing the occurrence of GC.
Description
Technical Field
The invention relates to a tumor marker and application thereof in preparing a gastric cancer diagnosis product, belonging to the field of epigenetic and oncology.
Background
Gastric Cancer (GC) is the most common cancer at 5 and the cause of cancer death at 4 worldwide in 2020. Timely diagnosis is the key of GC treatment and prognosis, and cell secretions such as hormone, enzymes, proteins and the like, for example carcinoembryonic antigen (CEA) and Alpha Fetoprotein (AFP) are often used as markers for gastric cancer diagnosis in the prior art. At present, although the tumor markers are still clinically used, the sensitivity and the accuracy of the tumor markers are difficult to meet the clinical requirements.
More and more studies have shown that small changes in epigenetic regulation play an important role in tumors. Epigenetic is a genetic branch discipline that leads to heritable gene expression or cell phenotype changes without nucleotide sequence changes in the study gene, and mainly includes DNA methylation, histone modification, non-coding RNA, RNA editing, genomic imprinting, and the like. RNA editing belongs to one of epigenetic science, and is an important post-transcriptional epigenetic regulation that alters RNA sequences. The most common type of RNA editing is adenosine-inosine (a-I) conversion mediated by the ADAR family of adenosine deaminases. RNA editing can increase the diversity of the transcriptome or proteome and potentially alter the stability and transport of the encoded protein sequence or RNA. Research shows that RNA editing plays an important regulatory role in the processes of tumor, immunity and the like. In GC, ADAR1 and ADAR2 are major members of the ADAR family, exerting oncogenic and oncostatic effects, respectively, through their catalytic deaminase domains. The A-I editing level is significantly inversely related to the survival rate of GC patients, indicating that RNA editing is of great significance for cancer treatment.
In conclusion, in GC diagnostics, there is a need to discover and study more novel GC markers, thereby providing more ways for GC diagnostics.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a GC molecular marker based on RNA editing level and application thereof, wherein the GC molecular marker has obvious difference in RNA editing level in tumor mucosa and adjacent normal mucosa of a GC patient.
The invention provides a GC molecular marker based on an RNA editing level, which takes human reference genome hg38 as a benchmark, and comprises the following RNA editing sites: F11R:chr1:160996561, F1R:chr1: 160996562, PSMD12:chr17:67338769, ERO1A:chr14:52643014, IGFBP7:chr4:57110068 and IGFBP7:chr4:57110120.
In one embodiment of the invention, the RNA editing site: F11Rchr1: 160996561 is position 160996561 on chromosome 1 of NCBI accession number NC_ 000001.11; F11Rchr1: 160996562 is position 160996562 on chromosome 1 of NCBI accession number NC_ 000001.11; PSMD12 chr17 67338769 is position 67338769 on chromosome 17 of NCBI accession NC_ 000017.11; ERO1A chr14:52643014 is position 52643014 on chromosome 14, NCBI accession number NC_ 000014.9; IGFBP7 chr4:57110068 is position 57110068 on chromosome 4 of NCBI accession No. NC_ 000004.12; IGFBP7 chr4:57110120 is position 57110120 on chromosome 4 of NCBI accession No. NC_ 000004.12.
The invention also provides application of the GC molecular marker in preparing a product for detecting or diagnosing gastric cancer; the product detects or diagnoses gastric cancer by detecting the RNA editing level of a molecular marker.
In one embodiment of the invention, the sample for said detection or diagnosis comprises gastric cells ex vivo.
In one embodiment of the invention, the product detects or diagnoses gastric cancer by the following formula:
n＝-2.161-0.004x 1 +0.092x 2 +0.011x 3 +0.016x 4 +0.060x 5 -0.296x 3 ；
cut-off value: p1=0.726, greater than this value was diagnosed as tumor;
x 1 ～x 6 F11R: chr1:160996561, F11R: chr1:160996562, PSMD12: chr17:67338769, ERO1A: chr14:52643014, IGFBP7: chr4:57110068, IGFBP7: chr4:57110120.
In one embodiment of the invention, the RNA editing level is determined using RT-PCR or Sanger sequencing.
In one embodiment of the invention, the RNA editing level is determined using transcriptome sequencing analysis.
In one embodiment of the invention, the detection or diagnosis combines the editing levels of 6 total differential RNA editing sites of the differential genes F11R, PSMD, ERO1A and IGFBP7 genes in the results of transcriptome sequencing for detecting or diagnosing GC.
In one embodiment of the invention, the steps of detecting or diagnosing GC are as follows:
(1) Collecting tumor tissue and other control tissue samples and clinical data of the patient,
(2) Verification of RNA editing differences in tumor tissues: data of tissue RNA editing is obtained through public data analysis and data analysis after transcriptome sequencing, and differences of RNA editing in GC and paracancerous normal tissues are verified.
In one embodiment of the invention, the inventors collect standard-compliant tissue samples with standard procedures (SOPs), collect complete clinical data with the system, and the like, and verify with high throughput sequencing methods. In particular, the experimental method studied mainly comprises the following parts:
1. selection of study samples:
(1) GC cases with clear diagnosis of pathology;
(2) Collecting GC tissue samples of patients;
(3) Paracancerous normal control tissue samples were collected.
2. Database data analysis
(1) GC transcriptome sequencing data;
(2) RNA editing analysis;
(3) Screening differential genes and differential RNA editing sites in GC tissues and paracancerous normal tissue control samples;
3. transcriptome sequencing
(1) Tumor and normal tissue sample RNA;
(2) RNA editing analysis;
(3) Comparison of the differences in RNA editing levels in the F11R, PSMD, ERO1A and IGFBP7 genes in GC tissues versus paracancerous normal tissue control samples.
In one embodiment of the invention, the logistics regression analysis was performed on the level differences of 6 RNA editing sites in tumor and non-tumor respectively to obtain the formula:
(1) Tumor and non-tumor diagnosis:
n＝-2.161-0.004x 1 +0.092x 2 +0.011x 3 +0.016x 4 +0.060x 5 -0.296x 3
cut-off value: p1=0.726, greater than this value was diagnosed as tumor;
x 1 ～x 6 RNA editing levels of F11R: chr1:160996561, F11R: chr1:160996562, PSMD12: chr17:67338769, ERO1A: chr14:52643014, IGFBP7: chr4:57110068, IGFBP7: chr4:57110120, respectively.
In one embodiment of the invention, the product comprises a biochip, kit, or device for detecting gastric cancer.
In one embodiment of the present invention, the biochip comprises a solid support and oligonucleotide probes immobilized on the solid support in order, the oligonucleotide probes specifically corresponding to the GC molecular markers described above.
In one embodiment of the present invention, the device comprises means for specifically detecting the above RNA editing site: one or more devices of F11R: chr1:160996561, F11R: chr1:160996562, PSMD12: chr17:67338769, ERO1A: chr14:52643014, IGFBP7: chr4:57110068, and IGFBP7: chr4:57110120 editing level.
In one embodiment of the present invention, the kit contains a reagent for detecting the expression level of the molecular marker.
The beneficial effects are that:
(1) The invention discovers that the RNA editing levels of sites F11R: chr1:160996561, F11R: chr1:160996562, PSMD12: chr17:67338769, ERO1A: chr14:52643014, IGFBP7: chr4:57110068, IGFBP7: chr4:57110120 have significant differences between a tumor group and a control group, and provides a tumor marker for detecting GC based on the RNA editing level differences of the 6 site combinations based on the editing sites.
(2) The RNA editing level difference based on the 6 site combinations can effectively diagnose and detect gastric cancer: in crowd 1, the area under the ROC curve of the classifier constructed with the editing sites is 0.911, the sensitivity is 85.7%, and the specificity is 84.1%. The diagnostic efficacy of the 6 RNA editing sites screened in the crowd 1 is verified by the crowd 2, and the verification result shows that the area under the ROC curve of the classifier constructed by the editing sites in the crowd 2 is 0.966, the sensitivity is 89.5%, and the specificity is 91.7%.
(3) The authenticity of the classifier generated by combining the editing level difference of 6 RNA editing sites is superior to that of the classifier generated by combining the 4 gene expression level differences corresponding to the 6 sites, the method is simpler in operation technology, lower in detection cost, less susceptible to control samples, and more stable in result.
Drawings
Fig. 1: there were significant differences in GC tissues and normal tissues of patients in group 1 at 6 RNA editing sites (p < 0.05).
Fig. 2: there were significant differences in GC tissues and normal tissues of patients in group 2 for 6 RNA editing sites (p < 0.05).
Fig. 3: ROC curve analysis showed the diagnostic performance of the combination of 6 RNA editing sites in population 1 in GC tissue and paracancerous normal tissue.
Fig. 4: ROC curve analysis showed the diagnostic performance of the combination of 6 RNA editing sites in population 2 in GC tissue and paracancerous normal tissue.
Detailed Description
The instrument used in the present invention is as follows
| Instrument name | Manufacturer' s |
| Electric tissue grinder (OSE-Y30) | TIANGEN BIOTECH (BEIJING) Co.,Ltd. |
| Vertical automatic pressure steam sterilizer (G54 DWS) | ZEALWAY (XIAMEN) INSTRUMENT Co.,Ltd. |
| Freezing high-speed centrifuge (Legend Micro 21R) | U.S., thermo Fisher |
| Ice machine (IMS-20) | CHANGSHU XUEKE ELECTRIC Co.,Ltd. |
| Medical cold storage and freezing refrigerator (HYCD-205) | QINGDAO HAIER SPECIAL ELECTRICAL APPLIANCE Co.,Ltd. |
| Electronic balance (Scout Pro) | OHAUS INSTRUMENT (CHANGZHOU) Co.,Ltd. |
| Pipettor (1000/200/100/10/2.5 mu L) | Germany, eppendorf |
| -80 ℃ refrigerator (902) | U.S., thermo Fisher |
| -20 ℃ refrigerator (DW-25L 262) | U.S., thermo Fisher |
| NANODROP ONE | U.S., thermo Fisher |
The experimental reagent and consumable used in the invention are as follows
| Reagent consumable name | Manufacturer' s |
| Absolute ethyl alcohol | Shanghai national pharmaceutical Congress chemical reagent Co., ltd |
| RNase-free EP tube | Wuxi Naisi Life Technology Co., Ltd. |
| RNase-free pipette tip | Axygen in the United states |
| EP pipe (1.5/2.0 mL) | Axygen in the United states |
| Pipette tip (1000/200/10 mu L) | Axygen in the United states |
| Chloroform (chloroform) | Sinopharm Group Chemical Reagent Co., Ltd. |
| Phosphate buffer (0.01 mol/L, pH 7.2-7.4) | Beijing Soilebao Biotech Co.Ltd |
| Isopropyl alcohol | Sinopharm Group Chemical Reagent Co., Ltd. |
| Tissue RNA extraction kit | TIANGEN BIOTECH (BEIJING) Co.,Ltd. |
Example 1: sample collection and processing
231 GC patients (crowd 1) are clinically collected, tumor tissues and normal tissues beside the cancer (fresh tumor tissues and normal tissues beside the cancer at the farthest position (more than 5 cm) from the tumor in an operation area) are taken, after biopsy tissues are obtained, RNA extraction is carried out on one part of tissues, the other part of tissues are put into a freezing tube and placed into liquid nitrogen for freezing, the frozen tissues in the liquid nitrogen are transferred to a refrigerator at the temperature of minus 80 ℃ for long-term storage, clinical data of the patients are collected by the system, and diagnosis efficacy analysis is carried out by taking crowd 1 as an experimental set. In addition, 38 GC patients (crowd 2) were collected, tumor tissues and normal tissues beside the cancer (fresh tumor tissues and normal tissues beside the cancer at the position farthest from the tumor (more than 5 cm) in the operation area) were taken, and treated in a crowd 1 mode, and the results obtained in the experimental set were verified and analyzed by taking crowd 2 as a verification set. The GC patient condition statistics are shown in tables 1 and 2.
Table 1: crowd 1GC patient condition statistics
Table 2: crowd 2GC patient condition statistics
Example 2: RNA extraction transcriptome sequencing
1. Taking tumor tissues and tissues of a normal part beside a cancer, obtaining transcriptome samples to be sequenced through RNA extraction, and obtaining the RNA editing level of each sample through transcriptome sequencing analysis, wherein the method comprises the following specific steps:
extraction of RNA from gastric mucosa tissue:
taking out the tumor tissue and the biopsy tissue of the normal tissue beside the cancer of the GC patient frozen in a refrigerator at the temperature of minus 80 ℃, placing the tissue in a biosafety cabinet, melting the tissue on ice, and cutting part of the tissue into an EP tube without RNase by using forceps and scissors which are soaked in DEPC water and then sterilized after the tissue is dissolved. Tissue was minced in an EP tube, added to 200ul trizol, and kept on ice. Before the next sample is sheared, the forceps and the scissors are soaked in 75% ethanol, then the forceps and the scissors are burned on an alcohol lamp, and after the forceps and the scissors are cooled, the next biopsy tissue is sheared.
(1) Grinding the tissue soaked in the Trizol by using a tissue grinder until the tissue and the Trizol are fully fused, adding 800 uLTrilzol into an EP tube for uniform mixing, and extracting RNA after the tissue is further dissolved in the Trizol;
(2) Adding nucleic acid extract into the Trizol dissolved with tissues according to the volume of 20%, covering the centrifugal tube cover, mixing until the solution is emulsified to be milky white, and standing for 5 minutes at room temperature;
(3) Centrifuging at 12000g for 15 minutes at 4 ℃, and removing the EP tube from the centrifuge;
(4) Then sucking the supernatant, transferring the supernatant to a new EP tube (without sucking out a white middle layer), adding half of isopropyl alcohol of Trizol volume into the sucked supernatant, fully mixing the EP tube upside down, standing for 10min at room temperature, and centrifuging for 10min at 12000g and 4 ℃;
(5) After discarding the supernatant, adding 75% ethanol with the same volume as Trizol, washing the tube wall upside down, 7500g, centrifuging at 4deg.C for 5min, and discarding the supernatant carefully;
(6) And opening an EP tube cover in an ultra-clean workbench, drying at room temperature, and adding a proper amount of DEPC water to dissolve RNA precipitate after alcohol is completely volatilized to obtain GC tissue and paracancerous normal tissue sample RNA.
2. Transcriptome sequencing
(1) Acquisition of RNA sequencing data:
crowd 1 collected 231 total primary tumor tissue and paracancerous normal tissue. Patients with complete staging data were 231, 85 with low staging and 146 with high staging. Crowd 2 collected 38 pairs of primary tumor tissue and paracancerous normal tissue. Patients with complete staging data were 38, with low staging 0 and high staging 38.
(2) Alignment of RNA sequencing data:
quality control qualified sequencing reads (reads) are analyzed by using FASTQC software, RNA STAR (version 2.7.0 e) software is used for comparing the genome sequence of hg38 of a person, RNA splice joints are analyzed, map is positioned on the genome, and a comparison result file in BAM format is generated;
(3) Identification and annotation of RNA editing sites:
RNA single nucleotide variation (single nucleotide variant, SNV) recognition standard is set to be more than or equal to 25 base mass, the sequencing depth is more than or equal to 10, the U base (converted into T base in RNA sequencing) depth is more than or equal to 2 and the editing frequency is more than or equal to 1% by using VarScan (version 2.4) software to carry out RNA single nucleotide variation (single nucleotide variant, SNV) recognition and recognition on the calibrated BAM file, and false positive variation is filtered by using a fpfilter command of VarScan and default parameters. SNV annotation was performed using Ensembl Variant Effect Predictor (VEP, https:// www.ensembl.org/VEP);
(4) Statistical analysis:
comparison of RNA editing levels or gene expression levels between groups between samples was performed using paired or paired Kruskal-Wallis (KW) nonparametric assays. P <0.05 was used as a significant difference screening criteria.
The results show that: the RNA editing levels of F11R chr1:160996561, F11R chr1:160996562, PSMD12:chr17:67338769, ERO1A:chr14:52643014, IGFBP7:chr4:57110068, IGFBP7:chr4:57110120 were significantly different in the tumor group and the control group (FIGS. 1, 2), and the RNA editing levels of F11R, PSMD12, ERO1A genes were significantly increased in the tumor group.
Example 3: generation and validation of RNA differential editing site composition on tumor factor diagnostic classifier
In the published data we first used SPSS software to determine predictors by logistic regression of the edit levels of 6 RNA edit sites (F11R: chr1:160996561, F11R: chr1:160996562, PSMD12: chr17:67338769, ERO1A: chr14:52643014, IGFBP7: chr4:57110068, IGFBP7: chr4: 57110120) in crowd 1, set predictors as test variables, set state variables as 0 and 1, set the tumor tissue group as 1 in tumor and non-tumor tissue analysis, and use SPSS software to make ROC curves, resulting in FIG. 3, as shown, with areas under the ROC curves AUC of 0.911, respectively. The point closest to the upper left corner, i.e. the about sign maximum, is selected as the cutoff. The cut-off value (cut off value) is a judgment criterion, which is a boundary value for judging test positives and negatives. The sensitivity was 85.7% at the cut-off value in FIG. 3 and the specificity was 84.1%.
Crowd 2 was selected and diagnostic efficacy of the 6 RNA editing sites screened in crowd 1 (F11R: chr1:160996561, F11R: chr1:160996562, PSMD12: chr17:67338769, ERO1A: chr14:52643014, IGFBP7: chr4:57110068, IGFBP7: chr4: 57110120) was validated. The above 6 RNA editing sites (F11R: chr1:160996561, F11R: chr1:160996562, PSMD12: chr17:67338769, ERO1A: chr14:52643014, IGFBP7: chr4:57110068, IGFBP7: chr4: 57110120) were regressed to obtain predicted values, the predicted values were set to check variables, the state variables were set to 0 and 1, the tumor tissue group was set to 1 in tumor and non-tumor tissue analyses, and SPSS software was used to make a ROC curve, resulting in FIG. 4, as shown in the figure, with an area under the ROC curve AUC of 0.966. The point closest to the upper left corner, i.e. the about sign maximum, is selected as the cutoff. The cut-off value (cut off value) is a judgment criterion, which is a boundary value for judging test positives and negatives. The sensitivity was 89.5% at the cut-off value in FIG. 4 and the specificity was 91.7%.
As shown in tables 3 and 4, the classifier in which the editing levels of the 6 RNA editing sites of the 4 genes were generated individually, the classifier in which the mRNA expression levels of the 4 genes were combined, and the classifier in which the editing levels of the 6 RNA editing sites were combined were not effective in judging the occurrence of GC. And the difference in RNA editing level of F11R and ERO1A is used for judging that the effect of GC occurrence is better than the difference in mRNA expression level. In crowd 1, the authenticity of GC occurrence was judged to be 91.1% respectively using a classifier generated by RNA editing level differences of 6 site combinations. In addition, the classifier generated at the RNA editing level was slightly more realistic than the classifier generated at the difference from the mRNA expression level.
Table 3: expression of 6 RNA editing sites as independent indicators and 4 Gene expression levels independent and combined in diagnostic GC tissues and paracancerous Normal tissues in group 1 (AUC: area under ROC curve)
Table 4: expression of 6 RNA editing sites as independent indicators and 4 gene expression levels independent and combined in GC tissues and paracancerous normal tissues in group 2 (AUC: area under ROC curve)
Example 4: diagnosis of tumor factors by RNA differential editing site composition
1. Selecting crowd 1, and carrying out logistic regression analysis on the level difference of 6 RNA editing sites in tumor and non-tumor respectively to obtain the formula:
(1) Tumor and non-tumor diagnosis:
n＝-2.161-0.004x 1 +0.092x 2 +0.011x 3 +0.016x 4 +0.060x 5 -0.296x 3
cut-off value: p1=0.726, greater than this value was diagnosed as tumor;
x 1 ～x 6 RNA editing levels of F11R: chr1:160996561, F11R: chr1:160996562, PSMD12: chr17:67338769, ERO1A: chr14:52643014, IGFBP7: chr4:57110068, IGFBP7: chr4:57110120, respectively.
2. Judging whether the tissue contains tumor factors or not or judging whether the tissue is tumor tissue or not by using the obtained formula
According to the method, a plurality of subjects in the verification sample crowd 2 are detected respectively, and each RNA editing level is substituted into the formula above, so that tumor diagnosis is carried out. The results showed that the results obtained by the detection using the method of the present application were consistent with the pathological diagnosis results.
Example 1: selecting a tissue sample of a patient 1, extracting RNA of tumor intestinal mucosa tissue, detecting the RNA editing level and the gene expression level, and carrying the RNA editing level and the gene expression level into a formula to obtain P1=0.972, wherein the P1=0.726 is larger than a cutoff value, and judging that the tumor is consistent with the actual situation.
Example 2: selecting a tissue sample of a patient 2, extracting RNA of tumor intestinal mucosa tissue, detecting the RNA editing level and the gene expression level, and carrying the RNA editing level and the gene expression level into a formula to obtain P1=0.963, wherein the P1=0.726 is larger than a cutoff value, and judging that the tumor is consistent with the actual situation.
Example 3: selecting a tissue sample of a patient 3, extracting RNA of tumor intestinal mucosa tissue, detecting the RNA editing level and the gene expression level, and carrying the RNA editing level and the gene expression level into a formula to obtain P1=0.922, wherein the P1=0.726 is larger than a cutoff value, and judging that the tumor is consistent with the actual situation.
Example 4: selecting a tissue sample of a patient 4, extracting RNA of a normal control intestinal mucosa tissue, detecting the RNA editing level and the gene expression level, and carrying the RNA editing level and the gene expression level into a formula to obtain P1=0.273, wherein the P1=0.726 is smaller than a cutoff value, and judging that the sample is normal and accords with the actual situation.
While the invention has been described with reference to the preferred embodiments, it is not limited thereto, and various changes and modifications can be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. Use of a reagent for detecting RNA editing level of a molecular marker, wherein the molecular marker comprises the following adenosine-inosine (a-I) RNA editing site f11r: chr1:160996561, f1r: chr1:160996562, PSMD12: chr17:67338769, ERO1A: chr14:52643014, IGFBP7: chr4:57110068, and IGFBP7: chr4:57110120, based on human reference genome hg38, in the preparation of a product for detecting or diagnosing gastric cancer; the product detects or diagnoses gastric cancer by detecting the RNA editing level of a molecular marker.
2. The use according to claim 1, wherein the RNA editing site: F11Rchr1: 160996561 is position 160996561 on chromosome 1 of NCBI accession number NC_ 000001.11; F11Rchr1: 160996562 is position 160996562 on chromosome 1 of NCBI accession number NC_ 000001.11; PSMD12 chr17 67338769 is position 67338769 on chromosome 17 of NCBI accession NC_ 000017.11; ERO1A chr14:52643014 is position 52643014 on chromosome 14, NCBI accession number NC_ 000014.9; IGFBP7 chr4:57110068 is position 57110068 on chromosome 4 of NCBI accession No. NC_ 000004.12; IGFBP7 chr4:57110120 is position 57110120 on chromosome 4 of NCBI accession No. NC_ 000004.12.
3. The use according to claim 1, wherein the sample for said detection or diagnosis comprises gastric cells ex vivo.
4. The use according to claim 1, wherein the product detects or diagnoses gastric cancer by the formula:
n＝-2.161-0.004x 1 +0.092x 2 +0.011x 3 +0.016x 4 +0.060x 5 -0.296x 3 ；
cut-off value: p1=0.726, above which gastric cancer is diagnosed;
x 1 ～x 6 RNA editing levels of F11R: chr1:160996561, F11R: chr1:160996562, PSMD12: chr17:67338769, ERO1A: chr14:52643014, IGFBP7: chr4:57110068, IGFBP7: chr4:57110120, respectively.
5. The use of claim 1, wherein the RNA editing level is determined using RT-PCR or Sanger sequencing.
6. The use of claim 1, wherein the RNA editing level is determined using transcriptome sequencing analysis.
7. The use according to claim 1, wherein the product comprises a biochip, kit, or device for detecting or diagnosing gastric cancer.
8. The use according to claim 7, wherein the biochip comprises a solid support and oligonucleotide probes immobilized in order on the solid support, the oligonucleotide probes specifically corresponding to molecular markers.
9. The use according to claim 7, wherein said device comprises specific detection of said RNA editing site: one or more devices of RNA editing levels of F11R: chr1:160996561, F11R: chr1:160996562, PSMD12: chr17:67338769, ERO1A: chr14:52643014, IGFBP7: chr4:57110068, and IGFBP7: chr4:57110120.
10. The use according to claim 7, wherein the kit contains a reagent for detecting the expression level of the molecular marker.
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