LanCL1 gene as target for typing and prognosis of glioma

Abstract

The invention relates to the technical field of biology, and provides a LanCL1 gene as a target for typing and prognosis of glioma. According to the application of the reagent for detecting LanCL1 gene expression in preparation of products for glioma molecular typing and prognosis prediction, molecular typing of glioma patients can be achieved, LanCL1 high expression is highly related to low malignancy and good prognosis, and clinical risk stratification, treatment decision and treatment assistance are facilitated.

Description

Technical Field

[0001] This application relates to the field of biotechnology, and in particular to the LanCL1 gene as a target for glioma subtyping and prognosis. Background Technology

[0002] Gliomas are among the most common malignant tumors of the central nervous system, especially glioblastoma (GBM), which is known for its high invasiveness, low survival rate, and high recurrence rate. Despite continuous advancements in comprehensive treatment methods such as surgical resection, radiotherapy, and chemotherapy, the overall prognosis for glioma patients remains unsatisfactory. One of the fundamental reasons for this is the high molecular heterogeneity of tumors; that is, the same type of glioma exists in multiple subtypes at the molecular level, leading to significant differences in treatment sensitivity and efficacy among different patients. Therefore, molecular subtyping and precision medicine have become important directions for the development of glioma research and treatment.

[0003] With the development of molecular biology and high-throughput omics technologies, an increasing number of molecular biomarkers are being used for glioma classification and prognostic prediction. For example, molecular features such as IDH1 / 2 mutations, 1p / 19q co-deletion, and MGMT promoter methylation have been incorporated into the latest glioma classification criteria of the World Health Organization (WHO). Although these biomarkers are of great significance in guiding clinical diagnosis and treatment, they still cannot fully reflect the biological behavior and treatment response of tumors.

[0004] In the process of tumorigenesis and development, changes in cellular metabolism and oxidative stress play a crucial role in regulating tumor cell proliferation, migration, and therapy sensitivity. In recent years, an increasing number of studies have focused on the role of redox homeostasis and its related signaling pathways in gliomas; however, incorporating metabolic and oxidative stress-related molecules into subtyping remains a technical challenge.

[0005] LanCL1 (lanthionine synthetase C-like protein 1) is a protein recently discovered that is closely related to cellular antioxidant capacity and metabolic regulation. Its biological role in neuroprotection and certain tumors has attracted attention, but its function and mechanism in gliomas remain unclear. Existing literature shows that LanCL1 has the function of regulating cell metabolism, apoptosis and proliferation in a variety of neurological diseases and tumors (such as breast cancer, liver cancer, prostate cancer, etc.) (see: [Chung, CH, et al., Biochemistry, 2007, 46(11):3262-9]; [Huang, C., et al., Dev Cell, 2014, 30(4):479-87]), but its research on molecular subtyping and prognostic prediction of gliomas is very limited. Summary of the Invention

[0006] To overcome the shortcomings of existing technologies, the purpose of this application is to provide a molecular biomarker that can be used for glioma treatment, subtyping, and prognostic detection. Using a genetic biomarker for glioma treatment, subtyping, and prognostic detection offers timeliness, specificity, and sensitivity, enabling the differentiation of different glioma subtypes. This allows the subtyping to not only encompass genetic characteristics but also reflect the tumor's metabolic and stress-regulatory status, thereby improving the biological rationality and clinical reference value of the subtyping. Furthermore, it optimizes the assessment of patient survival and risk levels, enhancing the precision of personalized diagnosis and treatment.

[0007] To achieve the above-mentioned objectives, the technical solution adopted in this application is as follows:

[0008] In the first aspect, this application provides the application of reagents for detecting LanCL1 gene expression in the preparation of products for molecular subtyping and prognostic prediction of gliomas.

[0009] Furthermore, the reagents for detecting LanCL1 gene expression include: detecting LanCL1 gene expression by qRT-PCR, Western blotting, in situ hybridization, detecting serum LanCL1 protein levels, RNA-seq sequencing, immunofluorescence, or mass spectrometry to achieve molecular subtyping and prognostic prediction of gliomas.

[0010] Furthermore, the reagent for detecting LanCL1 gene expression by qRT-PCR to achieve molecular subtyping and prognostic prediction of glioma includes at least one pair of primers that specifically amplify the LANCL1 gene; the reagent for detecting LANCL1 gene expression by Western blotting to achieve molecular subtyping and prognostic prediction of glioma includes an antibody that specifically binds to the LANCL1 protein.

[0011] Furthermore, the reagents used for qRT-PCR detection of LanCL1 gene expression to achieve molecular subtyping and prognostic prediction of gliomas include at least a pair of primers that specifically amplify the LANCL1 gene, as shown in SEQ ID NO.1 and SEQ ID NO.2.

[0012] Furthermore, the reagent used in the qRT-PCR detection of LanCL1 gene expression to achieve molecular subtyping and prognostic prediction of gliomas also includes β-actin as an internal control.

[0013] The product for preparing molecular subtyping and prognostic prediction of gliomas includes reagents for detecting LANCL1 gene expression; the reagents include primers and / or probes for detecting LANCL1 gene mRNA and antibodies for detecting LANCL1 protein.

[0014] The product for preparing molecular typing and prognosis prediction of gliomas will perform molecular typing of gliomas, and the typing threshold will be determined by median, ROC curve method, percentile quantile or machine learning algorithm.

[0015] The product for preparing molecular subtyping and prognostic prediction of glioma combines molecular subtyping of glioma with subtyping criteria and a multi-gene scoring model.

[0016] Secondly, this application provides the application of reagents for detecting LanCL1 gene expression in the preparation of products for predicting the prognosis of gliomas.

[0017] Furthermore, the reagents for detecting LanCL1 gene expression include: detecting LanCL1 gene expression by qRT-PCR, Western blotting, in situ hybridization, detecting serum LanCL1 protein levels, RNA-seq sequencing, immunofluorescence, or mass spectrometry to achieve molecular subtyping and prognostic prediction of gliomas.

[0018] The beneficial effects of this invention are as follows:

[0019] The reagent for detecting LanCL1 gene expression disclosed in this invention can be used to prepare products for molecular subtyping and prognostic prediction of gliomas, enabling molecular subtyping of glioma patients. High expression of LanCL1 is highly correlated with low malignancy and better prognosis, which helps in clinical risk stratification and treatment decisions, and is more conducive to the treatment of gliomas. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a graph showing the relationship between the relative expression level of LanCL1 and WHO classification and major pathological types in the TCGA dataset in this application embodiment;

[0022] Figure 2 This is a graph showing the relationship between the relative expression level of LanCL1 and important pathological features of glioma in the dataset of this application embodiment;

[0023] Figure 3 This is a diagram showing the results of LanCL1 expression being higher in glioma tissue samples than in peritumoral tissue in this application embodiment.

[0024] Figure 4 This is a graph showing the overall survival analysis of LanCL1 high and low expression groups in glioma tissue samples in this application embodiment. Detailed Implementation

[0025] To make the technical problems, technical solutions, and beneficial effects of this application clearer, the following detailed description is provided in conjunction with embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0026] The terminology used in the embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. The singular forms “a,” “the,” and “the” used in the embodiments of this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0027] Currently, most molecular subtyping of gliomas is based on molecular markers such as IDH1 / 2 mutations, 1p / 19q co-deletion, and MGMT methylation. While these subtyping methods are helpful for risk assessment and treatment decisions in some patients, they lack a comprehensive understanding of biological processes such as tumor metabolic status, cell cycle regulation, and oxidative stress responses, making it difficult to fully reveal the heterogeneity of gliomas. Furthermore, their predictive ability regarding tumor invasiveness, progression rate, and treatment response is limited, resulting in uncertainty in the subtyping, risk assessment, and prognosis of some patients.

[0028] This invention provides the application of reagents for detecting LanCL1 gene expression in the preparation of products for molecular subtyping and prognostic prediction of gliomas.

[0029] Reagents for detecting LanCL1 gene expression enable the differentiation of different glioma subtypes, allowing the classification to not only encompass genetic characteristics but also reflect the tumor's metabolic and stress-regulatory status, thereby improving the biological rationality and clinical reference value of the classification. The reagents for detecting LanCL1 gene expression can identify the high and low expression levels of the LanCL1 gene, and by analyzing its significant correlation with glioma malignancy and patient prognosis, the assessment of patient survival and risk level can be optimized, enhancing the precision of personalized diagnosis and treatment.

[0030] The specific procedures for using reagents to detect LanCL1 gene expression in LanCL1 molecular typing and prognostic testing are as follows:

[0031] 1. Subject of examination: Glioma tissue specimens (fresh surgical specimens or paraffin-embedded tissue).

[0032] 2. Detection method: The mRNA or protein expression level of LanCL1 was detected by molecular biology methods such as real-time quantitative PCR (qRT-PCR) and Western blotting (WB).

[0033] 3. Testing steps:

[0034] 3.1 Collect glioma tissue specimens from the patient (intraoperative rapid cryopreservation is preferred).

[0035] 3.2 Extract total RNA or protein (if using an RNA extraction kit, strictly follow the manufacturer's instructions).

[0036] 3.3 Perform qRT-PCR detection.

[0037] 3.4 Or perform Western blot detection.

[0038] 3.5 Data acquisition and quantitative analysis: The expression level was calculated using the ΔΔCt method, or relative quantitative analysis of WB was performed using digital image analysis software.

[0039] 3.6 Based on the test results, patients were divided into a LanCL1 high expression group and a low expression group (the median is recommended as the grouping threshold).

[0040] The reagent for detecting LanCL1 gene expression can enable molecular subtyping of glioma patients after LanCL1 gene expression detection. High LanCL1 expression is highly correlated with low malignancy and better prognosis, which helps in clinical risk stratification and treatment decisions.

[0041] In addition to quantitative real-time PCR (qRT-PCR) and Western blotting (WB), detection methods can also include in situ hybridization (ISH), RNA sequencing (RNA-seq), ELISA (e.g., for detecting serum LanCL1 protein levels), immunofluorescence, mass spectrometry, and other biochemical or molecular biological methods. Samples can be extended to include bodily fluid specimens such as blood and cerebrospinal fluid for liquid biopsy.

[0042] Among them: RNA-seq method:

[0043] Transcriptome research aims to explore gene function and structure at a macroscopic level, elucidating the molecular mechanisms underlying specific biological processes and disease development. Transcriptome sequencing (RNA-Seq) typically refers to second-generation high-throughput sequencing technology that performs cDNA sequencing, characterized by the rapid and accurate acquisition of the majority of transcripts from a specific tissue sample under specific conditions. As the foundation and starting point for gene function and structure research, transcriptome research plays a crucial role in elucidating genomic functional elements and clarifying their mechanisms of action. The transcriptome sequencing in this study was undertaken and completed by Beijing Novogene Technology Co., Ltd. (https: / / www.novogene.com / ). To minimize experimental bias, three replicates were used for each group.

[0044] The main steps of the experiment are as follows:

[0045] 1) RNA extraction and detection: Accurate detection of RNA integrity and total amount (Agilent 2100 Bioanalyzer);

[0046] 2) Library Construction and Quality Control: To construct the library using total RNA ≥1 μg, mRNA with polyA tails was enriched and randomly fragmented in lysis buffer using divalent cations. Using the fragmented mRNA as a template and random oligonucleotides as primers, the first strand of cDNA was synthesized in an M-MuLV reverse transcriptase system. The RNA strand was then treated with ribonuclease to ensure complete degradation. The second strand of cDNA was synthesized using deoxyribonucleotides under the action of DNA polymerase I. The purified double-stranded cDNA underwent end repair and A-tailing, and after ligation with sequencing adapters, cDNA of approximately 370–420 bp was screened using a nucleic acid purification kit. This cDNA was then used for PCR amplification, followed by purification of the PCR product using another nucleic acid purification kit, ultimately constructing the sample library. A quantitative real-time analyzer was used for preliminary quantification of the constructed library. The library was diluted to approximately 1.5 ng / µl, and its size was measured using a bioanalyzer. After passing the initial quantification, qRT-PCR was used to accurately quantify the effective concentration of the library to ensure its quality.

[0047] 3) Sequencing: After the RNA library passes the initial screening, the library at the required concentration is sequenced using Illumina, generating 150bp paired end reads. Amplification is then performed in the sequencing flow cell by adding four pre-labeled fluorescent deoxynucleotides, DNA polymerase, and adapter primers. During the extension of the complementary strand of each sequencing cluster, the addition of each fluorescently labeled deoxynucleotide releases a corresponding fluorescence signal. The computer software converts the captured fluorescence signal into sequencing peaks, thereby obtaining the sequence information of the target fragment.

[0048] 4) Data Analysis: Quality control is a prerequisite for data analysis. High-throughput sequencers are used to acquire image data from sequencing fragments, which is then processed, identified, and converted into sequence data. The raw sequencing data contains a small amount of sequence data with sequencing adapters or lower sequencing quality; this raw data is filtered to ensure the quality and reliability of the data analysis. Data analysis primarily focuses on differential expression analysis, differential gene enrichment analysis, gene set enrichment analysis, and differential gene-protein network interaction analysis.

[0049] Alternatives to LanCL1 expression level typing methods

[0050] ① The classification threshold can be not only the median, but also data-driven grouping methods such as ROC curve method, percentile quantiles (such as the top 25% and bottom 25%), and machine learning algorithms.

[0051] ② The typing criteria can be combined with a multi-gene scoring model, and LanCL1 can be used in conjunction with other related molecules for typing and prognosis.

[0052] The following description is based on specific embodiments.

[0053] Example 1

[0054] Differential expression of LanCL1 protein

[0055] 1. Sample Acquisition: Glioma tissue specimens were collected from the patient. All specimens were obtained with the approval of the organization's ethics committee. Clinical data for the tissue samples included: gender, age, tumor size, pathological grade (Edmonson), metastasis status, and recurrence status.

[0056] 2. Total RNA was extracted using the Trizol method.

[0057] 1) Prepare chloroform, EP tubes, 75% ethanol, Trizol reagent, DEPC water, mortar, homogenizer, blade, etc. in advance. All items should be treated with RNase removal and pre-cooled at 4°C in a low-temperature centrifuge.

[0058] 2) a. Tumor samples: Take out the glioma samples preserved in liquid nitrogen, cut about 50mg of tissue and grind it in a mortar containing liquid nitrogen, then transfer it to a 1.5ml EP tube, add 1ml of Trizol reagent, use a homogenizer to mix thoroughly, and let it stand on ice for 5min; b. Cell samples: Prepare the cells in advance, remove the culture medium, gently wash with PBS 2-3 times, add an appropriate amount of Trizol and mix well to fully lyse the adherent cells, transfer the lysis buffer to an EP tube, and let it stand on ice for 5min;

[0059] 3) Add 200 μl of chloroform, shake to mix, and let stand for 10 min. After the liquid surface is clearly separated into layers, centrifuge at 14000 rpm for 15 min at 4℃;

[0060] 4) After centrifugation, the contents of the EP tube are divided into 3 layers. Transfer the transparent upper layer of liquid from the EP tube to a new EP tube, add 500 μl of isopropanol, mix well, and let stand on ice for 30 min. Centrifuge at 14000 rpm for 10 min at 4℃.

[0061] 5) Discard the supernatant, add 1 ml of 75% ethanol to the tube, and wash the white flake precipitate at the bottom of the tube thoroughly;

[0062] 6) Centrifuge at 7500 rpm for 5 min at 4℃, remove the supernatant, repeat 3 times, remove the residual liquid in the tube, retain the precipitate, and let it dry at room temperature;

[0063] 7) When no obvious residual liquid is observed in the EP tube, add 50 μL of DEPC water to the tube to dissolve the precipitate;

[0064] 8) RNA quantification: A spectrophotometer is used to determine RNA purity and concentration. The OD260 / OD280 ratio is used to assess RNA purity; a ratio of 1.8-2.0 indicates no protein residue and high RNA purity. An RNA concentration greater than 300 ng / μl indicates high sample quality. RNA concentration and purity are labeled, and reverse transcription or storage at -80℃ is performed for later use.

[0065] 3. Perform qRT-PCR detection

[0066] 3.1 Reverse transcription reaction (cDNA synthesis)

[0067] (1) Remove genomic DNA;

[0068] After preparing the reaction mixture according to the following components, add the RNA sample and bring the volume to 10 μL with RNase-free dH2O. Incubate at room temperature for 30 min before proceeding to the next step.

[0069] Reagent Name Usage (ul)

[0070] 5×gDNA Eraser Buffer 2.0

[0071] gDNA Eraser 1.0

[0072] Total RNA 1μg

[0073] RNase-free dH2O up to 10

[0074] (2) Reverse transcription reaction;

[0075] Prepare the reaction solution according to Table 1. The final total reaction volume is 20 μl. Place the EP tube into the PCR instrument (Biorad) for reaction and set the parameters as follows: 37℃ for 15 min; 98℃ for 5 sec, 4℃ for 5 min. Finally, obtain cDNA.

[0076] Table 1

[0077] Reagent Name Dosage (μl) Genomic DNA removal reaction solution 10.0 Prime Script RT Enzyme Mix I 1.0 RT PrimerMix 1.0 5×Prime Script Buffer 24.0 <![CDATA[RNase Free dH2O]]> 4.0 Total Volume 20.0

[0078] 3.2 RT-PCR amplification reaction

[0079] The primer sequences for PCR amplification of LanCL1 are as follows:

[0080] TargetsForward 5′-3′

[0081] SEQ ID NO.1:TGAGTTCTCACAACGCTTGAC

[0082] Reverse 5′-3′

[0083] SEQ ID NO.2: CGAGGGTCTGCTGATTTCAGG

[0084] Internal reference β-actin

[0085] SEQ ID NO.3: CATGTACGTTGCTATCCAGGCCTCCTTAATGTCACG CACGAT

[0086] Prepare 10 μl of reaction solution as shown in Table 2, with 3 replicates for each gene detection. Place the reaction plate in a BioRad real-time quantitative PCR instrument, and set the amplification conditions as follows: 95℃ for 1 min; 40 PCR cycles (each cycle includes 95℃ pre-denaturation for 15 s; 60℃ denaturation for 15 s; 72℃ annealing extension for 45 s); analyze the melting curve and the specificity of the PCR amplification products, and detect the presence of dimers or other abnormal products in the products. Analyze the expression of the target gene using the 2-ΔΔCt method.

[0087] Table 2

[0088] Reagent Name Dosage (μl) SYBR premix Ex Taq 5.0 Primer reverse 0.4 Primer forward 0.4 cDNA 1.0 <![CDATA[DEPC H2O]]> 3.2

[0089] 4. Data acquisition and quantitative analysis: Expression levels were calculated using the ΔΔCt method, or relative quantitative analysis of Western blotting was performed using digital image analysis software; results are as follows: Figure 1-4 .

[0090] Depend on Figure 3 As can be seen: (A) Figure is Western blot (WB); Figure B is qRT-PCR. (B) RT-PCR detection of 98 glioma samples from West China Hospital (WCH) showed that the mRNA expression level of LanCL1 in GBM was significantly lower than that in low-grade glioma LGG.

[0091] Depend on Figure 4 It can be seen that: (A) The survival analysis results of the TCGA dataset show that the overall survival of the LanCL1 high expression group is significantly longer than that of the low expression group (Log-rank test, p<0.0001).

[0092] Example 2

[0093] The difference from Example 1 is that step 3 involves performing a protein immunoblotting detection, as detailed below:

[0094] 3.1 Preparation of polyacrylamide gel

[0095] 1) The gel ratio is related to the protein size, and the corresponding relationships are as follows: 4-40kDa-20%; 12-45kDa-15%; 10-70kDa-12.5%; 15-100kDa-10%-25-200kDa-8%;

[0096] 2) Select a suitable concentration of separating gel and pour the prepared and mixed separating gel into the gel plate gently to avoid generating air bubbles. Add sterile distilled water to the top of the separating gel until the gel plate is full, and let it stand at room temperature for 1 hour to allow it to fully solidify; pour off the distilled water, and use filter paper to blot dry any areas without gel, avoiding contact between the filter paper and the separating gel;

[0097] 3) Prepare an appropriate amount of 4% stacking gel, fill the gel plate with the separating gel, then insert the gel comb vertically and let it stand at room temperature for 1 hour to allow the stacking gel to fully solidify.

[0098] 3.2 Electrophoresis

[0099] After the stacking gel has completely solidified, carefully remove the gel comb and add 10 μl of protein sample to each well using a micropipette. Select 1-2 wells and add 2 μl of protein gradient labeling premix. Start electrophoresis at 80V. When the protein sample bands enter the boundary of the separating gel, adjust the voltage to 150V and continue electrophoresis. Stop electrophoresis when the bands are close to the bottom of the gel. The total time is approximately 90 minutes.

[0100] 3.3 Transfer

[0101] 1) Cut a PVDF membrane slightly larger than the strip area, mark the membrane number in the upper right corner to indicate the front and back sides, and soak it in methanol until ready for use;

[0102] 2) After the electrophoresis process is completed, carefully remove the glass plate, gently peel off the separating gel and place it in the transfer buffer to avoid damaging the gel block;

[0103] 3) Arrange the following layers in the transfer clamp in sequence: sponge - 3 layers of filter paper - PVDF membrane - gel - 3 layers of filter paper - sponge, removing air bubbles layer by layer to prevent air bubbles from affecting protein adhesion during the transfer process;

[0104] 4) Place the transfer clamp and the above-mentioned equipment into the electro-transfer tank (note that the transfer direction is opposite to the current direction), transfer with a current of 400mA for about 90 minutes, and then take out the PVDF membrane.

[0105] 3.4 Closure and Hybridization

[0106] 1) Prepare an appropriate amount of 5% skim milk with TBST as solvent in advance, immerse the successfully transferred PVDF membrane in it, and place it on a shaker at room temperature for 1 hour to seal it.

[0107] (2) Take out the PVDF membrane, add TBST, and place it on a shaker for oscillatory washing 3 times, 5 minutes each time. Cut according to the gradient marking position. The primary antibody is usually diluted at 1:1000 (adjust as appropriate when necessary). Take an appropriate amount of the diluted primary antibody and specific bands for plastic sealing. Incubate overnight at 4°C with gentle shaking on a shaker.

[0108] (3) After overnight incubation, take out the bands and recover the primary antibody. Add TBST and place it on a shaker for oscillatory washing 3 times, 10 minutes each time. The secondary antibody is usually diluted at 1:6000 - 8000. Add an appropriate amount of the secondary antibody and incubate with gentle shaking at room temperature for 2 hours.

[0109] 3.5 Chemiluminescent imaging

[0110] (4) Wash the bands incubated with the secondary antibody 3 times with TBST, 10 minutes each time;

[0111] (5) Prepare the A and B solutions of the ECL luminescent solution in a 1:1 ratio, mix well thoroughly, and use immediately after preparation;

[0112] (6) Place the PVDF membrane bands into the Qinxiang imager, evenly drop the ECL luminescent solution, expose to image and collect photos. The results are processed with the image software supporting the imaging system. The results are shown in Figure A in Figure 1 、 Figure 2 、 Figure 3 and Figure B in Figure 4 .

[0113] It can be seen from Figure 1 that the expression level of LanCL1 in low-grade gliomas is significantly higher than that in high-grade gliomas, and the expression level of LanCL1 in GBM is the lowest.

[0114] It can be seen from Figure 2 that in the TCGA, CGGA 325, CGGA 693, and West China Hospital (WCH) cohorts, the expression of LanCL1 in gliomas is lower than that in normal brain tissues. Figure (E) shows the analysis of the clinicopathological and molecular characteristics of the high-expression group and low-expression group of LanCL1 in gliomas: The analysis of the clinicopathological and molecular characteristics shows that the high expression of LanCL1 is significantly associated with lower-grade gliomas (WHO grade 2 and 3), especially more common in oligodendrogliomas or astrocytomas. In addition, the increased expression level of LanCL1 is also positively correlated with multiple known good prognosis biomarkers, including IDH1 mutation, 1p / 19q co-deletion, and MGMT promoter methylation.

[0115] Abbreviations: TCGA, The Cancer Genome Atlas; CGGA, Chinese Glioma Genome Atlas; WCH, West China Hospital.

[0116] Depend on Figure 3 As shown in Figure A, Western blot analysis of glioma samples from West China Hospital (WCH) revealed that the expression level of LanCL1 protein in the peritumoral tissue was significantly higher than that in the tumor tissue.

[0117] Depend on Figure 4 As shown in Figure B, the survival curves of 98 glioma patients at West China Hospital indicate that patients with high LanCL1 expression had a better prognosis (Log-rank test, p = 0.038).

[0118] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. Application of reagents for detecting LanCL1 gene expression in the preparation of products for molecular typing of gliomas.

2. The application according to claim 1, characterized in that, The reagents include: detection of serum LanCL1 protein levels by qRT-PCR, Western blotting, in situ hybridization, RNA-seq sequencing, immunofluorescence or mass spectrometry to detect LanCL1 gene expression in order to achieve molecular subtyping and prognostic prediction of gliomas.

3. The application according to claim 2, characterized in that, The reagent used to detect LanCL1 gene expression by qRT-PCR to achieve molecular subtyping and prognostic prediction of glioma includes at least one pair of primers that specifically amplify the LANCL1 gene. The reagents used to detect LANCL1 gene expression by protein immunoblotting for molecular subtyping and prognostic prediction of gliomas include antibodies that specifically bind to the LANCL1 protein.

4. The application according to claim 3, characterized in that, The reagents used for qRT-PCR detection of LanCL1 gene expression to achieve molecular subtyping and prognostic prediction of gliomas include at least a pair of primers that specifically amplify the LANCL1 gene, as shown in SEQ ID NO.1 and SEQ ID NO.

2.

5. The application according to claim 4, characterized in that, The reagents used in the qRT-PCR detection of LanCL1 gene expression for molecular subtyping and prognostic prediction of gliomas also include β-actin as an internal control.

6. The application according to claim 1, characterized in that, The product includes reagents for detecting LANCL1 gene expression; the reagents include primers and / or probes for detecting LANCL1 gene mRNA and antibodies for detecting LANCL1 protein.

7. The application according to claim 1, characterized in that, The product classifies gliomas into molecular types, using the median, ROC curve method, percentile quantile, or machine learning algorithm as the classification threshold.

8. The application according to claim 7, characterized in that, The product will perform molecular subtyping of gliomas, combining the subtyping criteria with a multi-gene scoring model.

9. Application of reagents for detecting LanCL1 gene expression in the preparation of products for predicting the prognosis of gliomas.

10. The application according to claim 9, characterized in that, The reagents include: detection of serum LanCL1 protein levels by qRT-PCR, Western blotting, in situ hybridization, RNA-seq sequencing, immunofluorescence or mass spectrometry to detect LanCL1 gene expression in order to achieve molecular subtyping and prognostic prediction of gliomas.

Images