Application of reagent for detecting expression quantity of CLIC3 gene in preparation of glioblastoma prognosis product

Abstract

The invention discloses application of a reagent for detecting CLIC3 gene expression quantity in preparation of glioblastoma prognosis products, and relates to the field of tumor molecular markers. Research finds that copy number variation and transcriptome expression level of the CLIC3 gene are greatly abnormal in patients with glioblastoma. The transcriptional level of the CLIC3 gene can be used for detecting the prognosis condition of glioblastoma with high sensitivity and high specificity, the prognosis evaluation capability of the CLIC3 gene is independent of tumor clinical staging, and the CLIC3 gene can be applied to primary and recurrent glioblastoma patients. Abnormal expression of the CLIC3 gene is related to hypoxia tumor microenvironment formed by rapid proliferation of tumors. CLIC3 gene expression evaluation can provide a powerful molecular biology basis for glioblastoma prognosis detection, provides important guidance for accurate layered treatment of patients, and has high clinical application value.

Description

Technical Field

[0001] The present invention belongs to the field of tumor molecular markers, and particularly relates to the application of a reagent for detecting the expression level of the CLIC3 gene in the preparation of a product for predicting the prognosis of glioblastoma. Background Art

[0002] Glioblastoma is one of the most common brain tumors, with a fast progression and a poor prognosis, and lacks good treatment methods. Moreover, its onset is relatively hidden, and early diagnosis is difficult. Patients generally come to the hospital for examination because they show various symptoms such as headache, vomiting, visual impairment, and limb weakness, and the tumor often has progressed to the middle and late stages. Glioblastoma grows invasively and can invade the surrounding normal brain tissue, resulting in damage to the patient's nerve function and significantly reducing the patient's quality of life and survival time.

[0003] At present, after glioblastoma patients receive the standard treatment plan (surgical resection, radiotherapy, and chemotherapy), they still face a relatively high risk of recurrence. Even with comprehensive treatment throughout the course, the overall survival period of the patients is not significantly improved. After the tumor recurs, it is easy to form resistance to radiotherapy and chemotherapy. The difficulty of reoperation is high, and it is difficult to completely remove the tumor surgically, mainly because the tumor boundary is unclear and it is difficult to distinguish from the normal brain tissue. Therefore, reliable molecular markers are urgently needed to optimize the prognosis of glioma patients.

[0004] Molecular markers for prognosis evaluation can provide important decision-making information for clinicians and assist them in making more informed judgments when formulating a disease management plan. Therefore, based on the high-throughput and multi-omics datasets of glioblastoma, screening and evaluating diagnostic biomarkers is an important means to optimize the stratified treatment of tumor patients and an important strategy to improve the prognosis of patients. Summary of the Invention

[0005] The purpose of the first aspect of the present invention is to provide the application of a substance for detecting the CLIC3 gene in the preparation of a product for screening, diagnosing, and / or predicting the prognosis of glioblastoma.

[0006] The purpose of the second aspect of the present invention is to provide a kit for diagnosing and / or predicting the prognosis of glioblastoma.

[0007] The purpose of the third aspect of the present invention is to provide a system for diagnosing and / or predicting the prognosis of glioblastoma.

[0008] In order to achieve the above purposes, the technical solutions adopted by the present invention are as follows:

[0009] The first aspect of the present invention provides the application of a substance for detecting the CLIC3 gene in the preparation of a product for screening, diagnosing, and / or predicting the prognosis of glioblastoma.

[0010] Furthermore, the substance for detecting the CLIC3 gene is a substance for detecting the expression level of the CLIC3 gene.

[0011] Furthermore, the material for detecting the CLIC3 gene includes primers and / or probes, gene chips and / or RNA sequencing related reagents for detecting the CLIC3 gene.

[0012] Furthermore, the primers for detecting the CLIC3 gene include quantitative PCR primers.

[0013] Furthermore, the quantitative PCR primers include a forward primer having a nucleotide sequence as shown in SEQ ID NO.2, and / or a reverse primer having a nucleotide sequence as shown in SEQ ID NO.3.

[0014] Furthermore, the gene chip includes a gene expression profile chip.

[0015] Furthermore, the RNA sequencing-related reagents include preparations required for RNA sequencing to detect the transcriptional expression level of CLIC3 gene in a sample.

[0016] Furthermore, the RNA sequencing-related reagent can detect the CLIC3 gene transcription expression level of the sample, and obtain the gene marker expression level TPM value (transcripts per million reads) by normalizing the CLIC3 gene transcription expression level of the sample.

[0017] Furthermore, the RNA sequencing includes next-generation sequencing.

[0018] Furthermore, the second-generation sequencing can target multiple transcripts of a gene at the same time, and the gene expression level can be obtained by adding up the sequencing values ​​of all transcripts.

[0019] Furthermore, each sample was grouped based on the median TPM, and the prognostic risk level was determined according to each cohort; when the TPM of the sample to be tested was ≤0.9, the sample was divided into a low-risk group, and when the TPM of the sample to be tested was >0.9, the sample was divided into a high-risk group.

[0020] Furthermore, the test samples of the glioblastoma screening, diagnosis and / or prognosis evaluation product include primary and recurrent glioblastoma tissue and / or cell samples.

[0021] Furthermore, the method for using the prognosis evaluation product includes: using a substance for detecting the CLIC3 gene to detect the sample to be tested to obtain the CLIC3 gene transcription expression level of the sample to be tested; normalizing the CLIC3 gene transcription expression level of the sample to be tested to obtain a gene expression level TPM value, when TPM≤0.9, dividing the sample into a low-risk group, and when TPM>0.9, dividing the sample into a high-risk group.

[0022] Further, the normalization process is performed using R software.

[0023] Further, the parameters used in the R software processing are based on the default parameters of the scale function.

[0024] Further, the product includes at least one of a reagent, a kit, a test strip, a system, and a chip.

[0025] In a second aspect of the present invention, there is provided a kit for diagnosing and / or prognosticating glioblastoma, comprising a probe and / or primer for specifically detecting the CLIC3 gene, a gene chip, or RNA sequencing-related reagents.

[0026] Further, the primer for specifically detecting the CLIC3 gene comprises a forward primer having a nucleotide sequence as shown in SEQ ID NO.2, and / or a reverse primer having a nucleotide sequence as shown in SEQ ID NO.3.

[0027] Further, the kit further comprises a primer set for detecting a reference gene.

[0028] Further, the reference gene includes the GAPDH gene.

[0029] Further, the primer set sequence for detecting the reference gene is as shown in SEQ ID NO:4 and SEQ ID NO:5.

[0030] In a third aspect of the present invention, there is provided a system for diagnosing and / or prognosticating glioblastoma, comprising:

[0031] A data acquisition module for acquiring the expression level of the CLIC3 gene of a patient;

[0032] A data analysis module for inputting the expression level of the CLIC3 gene into a risk scoring model to evaluate the diagnosis and / or prognosis of glioblastoma of the patient.

[0033] Compared with the prior art, the beneficial effects of the present invention are:

[0034] By detecting the expression level of the gene marker CLIC3 gene, the present invention can effectively predict the prognosis of glioblastoma patients, help clinicians with medication guidance, achieve precision medicine, and improve the survival rate of glioblastoma patients. It has been verified that by detecting the expression level of the CLIC3 gene, the prognosis of glioblastoma can be accurately predicted. It has a wide range of applications, high accuracy, a short experimental period, and has important clinical significance for the precise treatment of patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Statistical schematic diagram of CNV (copy number variation) of CLIC (chloride intracellular channel) family genes in tumor tissues of the TCGA-GBM dataset; among them, gain represents the acquired copy number variation; loss represents the deleted copy number variation; GBM represents glioblastoma;

[0036] Figure 2 Schematic diagram of the transcriptional expression differences of 6 genes in the CLIC family between normal brain tissues and glioma tissues; among them, GTEx represents the Genotype-Tissue Expression database; LGG represents low-grade glioma, "*" represents P < 0.05, "**" represents P < 0.01, "***" represents P < 0.001;

[0037] Figure 3 Schematic diagram of the prognostic risk assessment of the expression values of 6 genes in the CLIC family in the glioma cohort; among them, HR represents the hazard ratio; when HR > 1, it is a risk factor; when HR < 1, it is a protective factor; CI represents the confidence interval value;

[0038] Figure 4 Schematic diagram of the Kaplan-Meier survival curve of the CLIC3 gene involved in the present invention in glioblastoma of the TCGA-GBM dataset with overall survival as the evaluation index;

[0039] Figure 5 Schematic diagram of the ROC curve of the CLIC3 gene involved in the present invention in glioblastoma of the TCGA-GBM dataset with overall survival as the evaluation index;

[0040] Figure 6 Schematic diagram of the Kaplan-Meier survival curve of the CLIC3 gene involved in the present invention in glioblastoma of the CGGA_693 dataset with overall survival as the evaluation index;

[0041] Figure 7 Schematic diagram of the ROC curve of the CLIC3 gene involved in the present invention in glioblastoma of the CGGA_693 dataset with overall survival as the evaluation index;

[0042] Figure 8 Schematic diagram of the Kaplan-Meier survival curve of the CLIC3 gene involved in the present invention in glioblastoma of the GSE16011 dataset with overall survival as the evaluation index;

[0043] Figure 9 Schematic diagram of the ROC curve of the CLIC3 gene involved in the present invention in glioblastoma of the GSE16011 dataset with overall survival as the evaluation index;

[0044] Figure 10 Schematic diagram of the Kaplan-Meier survival curve of the CLIC3 gene involved in the present invention in glioblastoma in the GSE108474 dataset, with overall survival as the evaluation index;

[0045] Figure 11 Schematic diagram of the ROC curve of the CLIC3 gene involved in the present invention in glioblastoma in the GSE108474 dataset, with overall survival as the evaluation index;

[0046] Figure 12 Schematic diagram of the differential comparison of the transcriptional expression of the CLIC3 gene involved in the present invention in primary and recurrent glioblastomas in the GLASS dataset; where, initial is primary glioma, and recurrence is recurrent glioma;

[0047] Figure 13 Schematic diagram of the Kaplan-Meier survival curve of the CLIC3 gene involved in the present invention in primary glioblastoma in the GLASS dataset, with overall survival as the evaluation index;

[0048] Figure 14 Schematic diagram of the ROC curve of the CLIC3 gene involved in the present invention in primary glioblastoma in the GLASS dataset, with overall survival as the evaluation index;

[0049] Figure 15 Schematic diagram of the Kaplan-Meier survival curve of the CLIC3 gene involved in the present invention in recurrent glioblastoma in the GLASS dataset, with overall survival as the evaluation index.

[0050] Figure 16 Schematic diagram of the ROC curve of the CLIC3 gene involved in the present invention in recurrent glioblastoma in the GLASS dataset, with overall survival as the evaluation index; where, the ordinate in the ROC curve is sensitivity, and the abscissa is specificity; in the Kaplan-Meier survival curve, the ordinate is survival rate, and the abscissa is survival time;

[0051] Figure 17 Schematic diagram of the expression difference of the CLIC3 gene involved in the present invention in normal cell lines (HEB, normal human astrocyte cell line) and glioblastoma cell lines (U251 and U87), where, "*" means P < 0.05, and "**" means P < 0.01;

[0052] Figure 18Schematic diagram of the differential expression of the CLIC3 gene involved in the present invention in the core region and the marginal region of tumor tissues of glioblastoma patients; wherein, PID is the hidden patient information number; Boundary tumor is the marginal region of tumor tissues; Core tumor is the core region of tumor tissues, and "*" represents P < 0.05;

[0053] Figure 19 Schematic diagram of the differential expression of the protein corresponding to the CLIC3 gene involved in the present invention between normal brain tissues and gliomas in the HPA (Human Protein Atlas) database;

[0054] Figure 20 Schematic diagram of the differential expression of the CLIC3 gene involved in the present invention in single-cell sequencing data of glioma organoids under different treatment conditions, wherein, Stem-like is the stem-like cell state; Diff.-like is the differentiated-like cell state; Prolif.stem-like is the proliferative stem-like cell state; normoxia is the treatment condition of normal oxygen concentration; hypoxia is the treatment condition of hypoxic concentration; Irradiation is the treatment condition of radiation; 3d is the third day after treatment; 9d is the ninth day after treatment;

[0055] Figure 21 Schematic diagram of the expression correlation between the CLIC3 gene involved in the present invention and the hypoxia molecular marker HIF1A in the TCGA glioma dataset;

[0056] Figure 22 Schematic diagram of the expression correlation between the CLIC3 gene involved in the present invention and the hypoxia molecular marker FOSL2 in the TCGA glioma dataset;

[0057] Figure 23 Schematic diagram of the expression correlation between the CLIC3 gene involved in the present invention and the hypoxia molecular marker ANXA1 in the TCGA glioma dataset. Detailed implementation manners

[0058] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0059] Example 1: Screening of markers for the diagnosis and prognosis of glioblastoma

[0060] This embodiment provides a method for screening markers for the diagnosis and prognosis of glioblastoma, and the specific steps are as follows:

[0061] 1. Evaluate the copy number variations of 6 related genes in the CLIC family

[0062] Experimental method: Based on the UCSC Xena (https: / / xenabrowser.net / datapages / ) database, extract the dataset of copy number variations of TCGA-GBM. Use R language to extract the copy number variation data of 6 related genes (CLIC1, CLIC2, CLIC3, CLIC4, CLIC5, CLIC6) in the CLIC family for visualization and comparison.

[0063] Experimental results: As Figure 1 shown, it can be seen from the figure that there are certain proportions of copy number variations of 6 related genes in the CLIC family in the TCGA-GBM dataset (overall between 19% and 29%). Among them, the overall proportion of copy number variations of the CLIC3 gene is the highest (29%). CLIC1, CLIC2, and CLIC5 mainly show deletion copy number variations, while CLIC3, CLIC4, and CLIC6 mainly show acquired copy number variations.

[0064] 2. Compare the transcriptome expression differences of 6 related genes in the CLIC family between glioma tissues and normal brain tissues

[0065] Experimental method: Based on the UCSC Xena database, extract the transcriptome expression profiles of GTEx and TCGA-LGG+GBM datasets. Use R language to extract the transcriptome expression profile data of 6 related genes in the CLIC family for visualization and comparison.

[0066] Experimental results: As Figure 2 shown, it can be seen from the figure that there are significant differences in the expression of the transcriptome profiles of 6 related genes in the CLIC family between glioma tissues and normal brain tissues. Among them, CLIC1 and CLIC4 are significantly up-regulated in tumor tissues, while CLIC2, CLIC3, CLIC5, and CLIC6 are significantly down-regulated in tumor tissues.

[0067] 3. Evaluate the subcellular localization and protein secondary structure of the expression of 6 related genes in the CLIC family

[0068] Experimental methods: The subcellular localization of 6 related genes of the CLIC family was visualized based on the COMPARTMENTS (https: / / compartments.jensenlab.org / ) database; the visualization of the secondary protein structure was performed based on the cBioPortal database (http: / / www.cbioportal.org / ).

[0069] Experimental results: There were significant differences in the subcellular co-localization of 6 related genes of the CLIC family. Among them, CLIC1 was mainly distributed in the extracellular matrix and the nucleus, and CLIC3 was mainly distributed in the nucleus. The secondary protein structures of CLIC1, CLIC2, and CLIC3 were relatively similar, with the protein sizes all around 240 amino acids, and all contained two similar protein domains.

[0070] 4. Evaluate the prognostic risk of the transcriptome profiles of 6 related genes of the CLIC family

[0071] Experimental methods: The transcriptome expression profiles and corresponding clinical feature data of the TCGA-LGG+GBM dataset were extracted based on the UCSC Xena database, and the survival package in R language was used to perform univariate Cox risk assessment of the prognostic risk of the transcriptome profiles of 6 related genes of the CLIC family based on the overall survival time.

[0072] Experimental results: As Figure 3 shown, it can be seen from the figure that when the TCGA LGG+GBM was used as the analysis dataset, all 6 related genes of the CLIC family had significant prognostic risk significance. Among them, CLIC5 was a protective factor, and the others were risk factors. When the TCGA LGG was used as the analysis dataset, CLIC1, CLIC2, CLIC3, CLIC4, and CLIC6 all had significant prognostic risk significance, showing as risk factors. When the TCGA GBM was used as the analysis dataset, only CLIC1 and CLIC3 had significant prognostic risk significance, showing as risk factors, and CLIC3 had the highest risk value (HR = 1.822). Subsequently, the CLIC3 gene was used as a marker for the diagnosis and prognosis of glioblastoma for research.

[0073] The human CLIC3 gene is located on chromosome 9q34.3, with the GeneID (gene accession number) being 9022 in NCBI (National Center for Biotechnology Information, USA), and the complete transcript number in the GeneBank database being NM_004669.3. Its specific sequence is as follows:

[0074] CLIC3 (NM_004669.3) gene sequence:

[0075] GCGCCTGACCGCGGCAGCTCCCACCATGGCGGAGACCAAGCTCCAGCTGTTTGTCAAGGCGAGTGAGGACGGGGAGAGCGTGGGTCACTGCCCCTCCTGCCAGCGGCTCTTCATGGTCCTGCTCCTCAAGGGCGTACCTTTCACCCTCACCACGGTGGACACGCGCAGGTCCCCGGACGTGCTGAAGGACTTCGCCCCCGGCTCGCAGCTGCCCATCCTGCTCTATGACAGCGACGCCAAGACAGACACGCTGCAGATCGAGGACTTTCTGGAGGAGACGCTGGGGCCGCCCGACTTCCCCAGCCTGGCGCCTCGTTACAGGGAGTCCAACACCGCCGGCAACGACGTTTTCCACAAGTTCTCCGCGTTCATCAAGAACCCGGTGCCCGCGCAGGACGAAGCCCTGTACCAGCAGCTGCTGCGCGCCCTCGCCAGGCTGGACAGCTACCTGCGCGCGCCCCTGGAGCACGAGCTGGCGGGGGAGCCGCAGCTGCGCGAGTCCCGCCGCCGCTTCCTGGACGGCGACAGGCTCACGCTGGCCGACTGCAGCCTCCTGCCCAAGCTGCACATCGTCGACACGGTGTGCGCGCACTTCCGCCAGGCGCCCATCCCCGCGGAGCTGCGCGGCGTACGCCGCTACCTGGACAGCGCGATGCAGGAGAAAGAGTTCAAATACACGTGTCCGCACAGCGCCGAGATCCTGGCGGCCTACCGGCCCGCCGTGCACCCCCGCTAGCGCCCCACCCCGCGTCTGTCGCCCAATAAAGGCATCTTTGTCGGGAGTGAGGGTGTCCTGACATCTGAAGGGC(SEQ ID NO:1).

[0076] Example 2: Application of CLIC3 gene in the preparation of products for the prognosis of glioblastoma

[0077] 1. High expression of the CLIC3 gene is associated with the prognosis of glioblastoma. The specific verification steps are as follows:

[0078] Experimental method for evaluating the stratification effect of CLIC3 gene transcriptome profile on the overall survival prognosis of glioblastoma patients: (1) Extract the glioblastoma transcriptome data of TCGA-GBM, CGGA_693, GSE16011, and GSE108474 datasets from the database; annotate the gene names in the transcriptome expression profile files according to the sequencing platform; (2) Combine the mRNA expression values with the same gene names; (3) Use R software to perform preprocessing of normalization and standardization on the gene expression of each sample (based on the default parameters of the scale function); (4) Divide the samples into high-risk and low-risk groups according to the median of gene expression values; (5) Perform Kaplan-Meier survival analysis and ROC curve plotting on the high- and low-risk groups; According to the linear fitting between the expression value of the CLIC3 gene and the overall survival (OS), when TPM_CLIC3 ≤ 0.9, the sample is classified into the low-risk group, and when TPM_CLIC3 > 0.9, the sample is classified into the high-risk group.

[0079] Experimental results: Taking the overall survival as the evaluation index, in the TCGA-GBM dataset, the Kaplan-Meier survival curve shows that the overall survival of the high-risk group in the cohort is significantly lower than that of the low-risk group (P = 0.001), as Figure 4 shown; The AUC of the CLIC3 gene as a molecular marker for predicting the 1-year survival of tumor patients is 56.06%; The AUC for predicting the 2-year survival is 58.95%; The AUC for predicting the 3-year survival is 55.19%, as Figure 5 shown.

[0080] Taking the overall survival as the evaluation index, in the CGGA_693 dataset, the Kaplan-Meier survival curve shows that the overall survival of the high-risk group in the cohort is significantly lower than that of the low-risk group (P = 0.043), as Figure 6 shown; The AUC of the CLIC3 gene as a molecular marker for predicting the 1-year survival of tumor patients is 54.04%; The AUC for predicting the 2-year survival is 50.95%; The AUC for predicting the 3-year survival is 53.08%, as Figure 7 shown.

[0081] Taking the overall survival as the evaluation index, in the GSE16011 dataset, the Kaplan-Meier survival curve shows that the overall survival of the high-risk group in the cohort is significantly lower than that of the low-risk group (P = 0.037), as Figure 8 shown; The AUC of the CLIC3 gene as a molecular marker for predicting the 1-year survival of tumor patients is 53.64%; The AUC for predicting the 2-year survival is 58.58%; The AUC for predicting the 3-year survival is 54.57%, as Figure 9 shown.

[0082] Taking the overall survival as the evaluation index, in the GSE108474 dataset, the Kaplan-Meier survival curve showed that the overall survival of the high-risk group in the cohort was significantly lower than that of the low-risk group (P = 0.021), as Figure 10 shown; the AUC for predicting the 1-year survival of tumor patients with the CLIC3 gene as a molecular marker was 52.95%; the AUC for predicting the 2-year survival was 58.44%; the AUC for predicting the 3-year survival was 61.83%, as Figure 11 shown.

[0083] 2. The high expression of the CLIC3 gene is related to the recurrence and progression of glioblastoma. The specific verification steps are as follows:

[0084] (1) Evaluate the expression difference of the CLIC3 gene transcription level in the tumor tissues of primary and recurrent paired glioma patients

[0085] Experimental method: Extract the transcriptome expression profiles of the tumor tissues of primary and recurrent paired glioma patients in the GLASS dataset, and use R language to extract the transcriptional expression data of the CLIC3 gene for visualization and comparison.

[0086] Experimental results: As Figure 12 shown, there were significant differences in the transcriptional expression levels of the CLIC3 gene in different recurrence patterns, except for the recurrence pattern of primary G2 recurrence G2. Among them, the expression difference of the CLIC3 gene was the most significant in the recurrence pattern of primary G3 recurrence G4.

[0087] (2) Evaluate the stratification effect of the CLIC3 gene transcriptome profile on the overall survival prognosis of glioblastoma recurrence patients

[0088] Experimental method: 1) Extract the glioblastoma transcriptome data of the GLASS dataset; annotate the gene names of the transcriptome expression profile files according to the sequencing platform; 2) Combine the mRNA expression values with the same gene names; 3) Perform preprocessing of normalization and standardization on the gene expression of each sample; 4) Divide the samples into high-risk and low-risk groups according to the median of the gene expression values; 5) Perform Kaplan-Meier survival analysis and ROC curve plotting on the high- and low-risk groups; according to the linear fitting of the expression value of the CLIC3 gene and the overall survival (OS), when TPM_CLIC3 ≤ 0.9, the sample is divided into the low-risk group, and when TPM_CLIC3 > 0.9, the sample is divided into the high-risk group.

[0089] Experimental results: Taking the overall survival as the evaluation index, in the GLASS.I dataset, the Kaplan-Meier survival curve showed that the overall survival of the high-risk group in the cohort was significantly lower than that of the low-risk group (P = 0.00063), asFigure 13 As shown in the figure; the AUC for predicting the 1-year survival of tumor patients using the CLIC3 gene as a molecular marker was 56.71%; the AUC for predicting the 2-year survival was 58.27%; the AUC for predicting the 3-year survival was 58.84%, as Figure 14 shown.

[0090] Taking the overall survival as the evaluation index, in the GLASS.R dataset, the Kaplan-Meier survival curve showed that the overall survival of the high-risk group in the cohort was significantly lower than that of the low-risk group (P = 0.045), as Figure 15 shown; the AUC for predicting the 1-year survival of tumor patients using the CLIC3 gene as a molecular marker was 54.57%; the AUC for predicting the 2-year survival was 51.99%; the AUC for predicting the 3-year survival was 58.8%, as Figure 16 shown.

[0091] Example 3: Application of the CLIC3 gene in the preparation of products for detecting glioblastoma

[0092] 1. Use the cell line model to evaluate the expression of CLIC3 in glioma tissues

[0093] Experimental method:

[0094] (1) Culture normal glial cell line (HEB) and glioblastoma cell lines (U251 and U87);

[0095] (2) Quantitatively detect the relative mRNA expression levels of the CLIC3 gene in the normal glial cell line (HEB) and glioblastoma cell lines (U251 and U87) by RT-qPCR (real-time quantitative reverse transcription polymerase chain reaction) technology. GAPDH (glyceraldehyde-3-phosphate dehydrogenase) was selected as the internal reference, and the primer sequences used for RT-qPCR detection are shown in Table 1.

[0096] Table 1

[0097]

[0098]

[0099] Experimental results: As Figure 17 shown, it can be seen from the figure that the expression level of the CLIC3 gene in the tumor cell line is significantly lower than that in the normal glial cell line.

[0100] 2. Use the surgically resected tissues of glioma patients to evaluate the expression of CLIC3 in different regions

[0101] Experimental methods: (1) Collect the surgically resected tissues of glioma patients, and sample the core region and the marginal region of the tumor tissues respectively; (2) Quantitatively detect the relative expression level of CLIC3 gene mRNA by RT-qPCR (real-time quantitative reverse transcription polymerase chain reaction) technology. GAPDH (glyceraldehyde-3-phosphate dehydrogenase) is selected as the internal reference, and the primer sequences used for RT-qPCR detection are shown in Table 1.

[0102] Experimental results: As Figure 18 shown, it can be seen from the figure that the expression level of CLIC3 gene in the core region of glioma tumor tissues is significantly lower than that in the marginal region.

[0103] 3. Evaluate the difference in the protein expression levels of CLIC3 in glioma tissues and normal brain tissues

[0104] Experimental methods: Based on the HPA (https: / / www.proteinatlas.org / , Human Protein Atlas) database, extract the immunohistochemical results of CLIC3 protein in glioma and normal brain tissues and compare them.

[0105] Experimental results: As Figure 19 shown, it can be seen from the figure that the protein expression level of CLIC3 gene in tumor cell tissues is significantly lower than that in normal brain tissues.

[0106] 4. Evaluate the expression changes of CLIC3 under different cell states and treatment conditions based on the glioblastoma organoid model

[0107] Experimental methods: Collect the single-cell sequencing dataset (HF2354) of glioblastoma organoids, and use the Seurat package in R to visualize and compare the expression levels of CLIC3 gene under different cell states and treatment conditions.

[0108] Experimental results: As Figure 20 shown, it can be seen from the figure that the CLIC3 gene is mainly expressed in the single-cell population in the differentiated-like (Diff.-like) state, and both hypoxia and radiation induction conditions can up-regulate the transcriptome expression level of the CLIC3 gene.

[0109] 5. Hypoxic environment promotes the high expression of CLIC3 gene in glioblastoma.

[0110] Verify that the hypoxic environment promotes the high expression of CLIC3 gene in glioblastoma by evaluating the correlation between the expression levels of CLIC3 gene and hypoxia markers.

[0111] Experimental method: Based on the GEPIA database (an interactive analysis platform for gene expression level values) (http: / / gepia.cancer-pku.cn / ), the expression correlation between the transcriptional level of the CLIC3 gene and the hypoxia marker genes HIF1A, FOSL2, and ANXA1 was evaluated.

[0112] Experimental results: As Figures 21 - 23 shown, it can be seen from the figure that there is a certain correlation between the transcriptome expression level of the CLIC3 gene and HIF1A, FOSL2, and ANXA1. Among them, the expression correlation with ANXA1 is the highest, with a correlation R value of 0.29 and a P value less than 0.001.

[0113] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims involved.

Claims

1. Use of a substance for detecting the CLIC3 gene in the preparation of a product for glioblastoma screening, diagnosis, and / or prognosis evaluation.

2. The application according to claim 1, characterized in that: The substance for detecting the CLIC3 gene includes primers and / or probes for detecting the CLIC3 gene, gene chips, and / or RNA sequencing-related reagents.

3. The application according to claim 2, characterized in that: The primers for detecting the CLIC3 gene include quantitative PCR primers; Preferably, the quantitative PCR primers include a forward primer with a nucleotide sequence as shown in SEQ ID NO.2, and / or a reverse primer with a nucleotide sequence as shown in SEQ ID NO.

3.

4. The application according to claim 2, characterized in that: The gene chip includes a gene expression profile chip.

5. The application according to claim 1, wherein: The method of using the prognosis evaluation product includes: detecting a test sample with a substance for detecting the CLIC3 gene to obtain the transcriptional expression level of the CLIC3 gene in the test sample; normalizing the transcriptional expression level of the CLIC3 gene in the test sample to obtain the gene expression level TPM value. When TPM ≤ 0.9, the sample is classified into the low-risk group, and when TPM > 0.9, the sample is classified into the high-risk group.

6. The application according to claim 1, characterized in that: The test samples for the glioblastoma screening, diagnosis, and / or prognosis evaluation product include primary and recurrent glioblastoma tissues and / or cell samples.

7. The application according to claim 1, characterized in that: The product includes at least one of reagents, kits, test strips, systems, and chips.

8. A kit for the diagnosis and / or prognosis of glioblastoma, characterized in that: Comprising a probe and / or primer for specifically detecting the CLIC3 gene, a gene chip, or RNA sequencing-related reagents.

9. The kit according to claim 8, wherein: The primers for specifically detecting the CLIC3 gene include a forward primer with a nucleotide sequence as shown in SEQ ID NO.2, and / or a reverse primer with a nucleotide sequence as shown in SEQ ID NO.3; and / or, the kit further includes a primer set for detecting a reference gene; Preferably, the primer set sequence for detecting the reference gene is as shown in SEQ ID NO:4 and SEQ ID NO:

5.

10. A system for diagnosing and / or evaluating the prognosis of glioblastoma, characterized in that: Includes: A data acquisition module for acquiring the CLIC3 gene expression level of a patient; A data analysis module for inputting the CLIC3 gene expression level into a risk scoring model to evaluate the glioblastoma diagnosis and / or prognosis of the patient.

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