Protein composition for diagnosing and distinguishing glioblastoma and low-grade glioma and application thereof

By detecting differential protein markers between glioblastoma and low-grade glioma, especially IGLV1-47 and IGKV2-28, the problem of misdiagnosis of glioblastoma as low-grade glioma in existing technologies has been solved, improving the accuracy and safety of diagnosis.

CN121656572APending Publication Date: 2026-03-13蚌埠市第三人民医院(蚌埠市中心医院)
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-16
Publication Date
2026-03-13

AI Technical Summary

Technical Problem

Current technology is prone to misdiagnosing glioblastoma and low-grade glioma, especially misdiagnosing glioblastoma as low-grade glioma, which leads to difficulties in clinical treatment.

Method used

Proteins such as IGLV1-47, IGKV2-28, IGKV3D-15, SLC30A7, IGKV3D-20, IGKV3-15, PABPC4L, PSMG4, and SDK1 were used as biomarkers to differentiate glioblastoma from low-grade glioma by detecting the expression levels of these proteins.

Benefits of technology

It improves the diagnostic accuracy of glioblastoma and low-grade glioma, reduces the probability of misdiagnosis, and provides a new direction for clinical diagnosis.

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Abstract

The invention provides a protein composition for diagnosing and distinguishing glioblastoma and low-grade glioma and application of the protein composition, and relates to the technical field of clinical medicine detection. The protein composition is at least one of IGLV1-47, IGKV2-28, IGKV3D-15, SLC30A7, IGKV3D-20, IGKV3-15, PABPC4L, PSMG4 and SDK1 (Sodium Dodecyl Ketone), and the protein composition is at least one of the following components. According to the invention, the defects in the prior art are overcome, the glioblastoma and the low-grade glioma can be more accurately distinguished by determining the differential proteins of the glioblastoma and the low-grade glioma in the tumor tissue and adopting the differential proteins as markers, and a new direction is provided for clinical diagnosis.
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Description

Technical Field

[0001] This invention relates to the field of clinical medical testing technology, specifically to a protein composition for diagnosing and differentiating glioblastoma from low-grade glioma and its application. Background Technology

[0002] Glioblastoma is a highly malignant primary brain tumor, belonging to the most aggressive type of astrocytoma. It is commonly found in the cerebral hemispheres and is characterized by rapid growth and a high recurrence rate. Low-grade gliomas, on the other hand, are well-differentiated gliomas with relatively low malignancy. They mainly include grade I and II gliomas in the World Health Organization (WHO) classification of tumors of the central nervous system. In clinical diagnosis, the two usually need to be differentiated and graded by combining imaging, pathological, and molecular testing results to determine the subsequent treatment methods.

[0003] While existing detection methods generally reduce the risk of misdiagnosis between glioblastoma and low-grade glioma, there are still instances where glioblastoma is misdiagnosed as low-grade glioma. For example, some glioblastomas may be missed, or they may be misdiagnosed as low-grade gliomas due to atypical morphological features. This poses significant challenges to actual clinical treatment. Therefore, it is crucial to identify new detection directions and methods based on the differences in proteins detected in tumor tissues of glioblastoma and low-grade glioma. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a protein composition for diagnosing and differentiating glioblastoma from low-grade glioma and its application. By identifying differentially expressed proteins between glioblastoma and low-grade glioma in tumor tissue and using these differentially expressed proteins as biomarkers, glioblastoma and low-grade glioma can be more accurately distinguished, providing a new direction for clinical diagnosis.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A protein composition for diagnosing and differentiating glioblastoma from low-grade glioma, said protein composition being at least one of IGLV1-47, IGKV2-28, IGKV3D-15, SLC30A7, IGKV3D-20, IGKV3-15, PABPC4L, PSMG4, and SDK1.

[0006] Compared to low-grade glioma controls, elevated expression levels of the protein marker composition indicated a risk of glioblastoma in the subjects.

[0007] The identification reagent for a protein marker composition used to diagnose and differentiate glioblastoma from low-grade glioma is used in the preparation of a product for differentiating glioblastoma from low-grade glioma, wherein the identification reagent is a reagent for identifying the content of any one or more proteins, including IGLV1-47, IGKV2-28, IGKV3D-15, SLC30A7, IGKV3D-20, IGKV3-15, PABPC4L, PSMG4, and SDK1, in tumor tissue samples.

[0008] Products used for diagnosing and differentiating glioblastoma from low-grade gliomas, wherein the products contain the aforementioned identification reagents.

[0009] Preferably, the product is a test strip, reagent kit, chip, antigen-antibody conjugate, probe, or test strip.

[0010] This invention provides a protein composition for diagnosing and differentiating glioblastoma from low-grade glioma and its application, which has the following advantages compared with the prior art: This invention screens tumor tissue samples from glioblastoma and low-grade glioma, identifying nine significantly elevated proteins in glioblastoma samples compared to low-grade glioma samples: IGLV1-47, IGKV2-28, IGKV3D-15, SLC30A7, IGKV3D-20, IGKV3-15, PABPC4L, PSMG4, and SDK1. These protein differences can further differentiate glioblastoma from low-grade glioma, providing a new direction for clinical diagnosis, reducing the probability of misdiagnosis, and improving diagnostic accuracy and safety. Attached Figure Description

[0011] Figure 1 This is a heatmap showing the visualization between samples in an embodiment of the present invention; Figure 2 This is a bar chart showing the number of proteins quantified in the samples in this embodiment of the invention; Figure 3 This is a heatmap showing the union correlation of differentially expressed proteins in patients with glioblastoma and patients with low-grade glioma in this embodiment of the invention. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0013] Example: Obtaining differentially expressed proteins: 1. Sample Acquisition: We collected paraffin-embedded tumor tissue blocks (named GBM1-6) from 6 patients diagnosed with glioblastoma. There were 4 females and 2 males, aged 54-79 years, with a mean age of 69.5 years.

[0014] Three cases were tumor paraffin blocks from patients with low-grade gliomas (named LGG1, LGG2, and LGG3), aged 17, 39, and 72 years, with an average age of 42.7 years, and all were male; 2. Protein extraction: After dewaxing, the samples were transferred to 1.5 ml centrifuge tubes, and 4 volumes of lysis buffer (1% SDS, 1% protease inhibitor) were added. The samples were then sonicated and lysed. After centrifugation at 12000 g for 10 min at 4 ℃, cell debris was removed, and the supernatant was transferred to new centrifuge tubes for protein concentration determination using a BCA assay kit.

[0015] 3. Pancreatic enzyme hydrolysis: Equal volumes of protein from each sample were digested enzymatically. The volumes were adjusted to be uniform using lysis buffer. One volume of pre-chilled acetone was added, and the mixture was vortexed. Four volumes of pre-chilled acetone were then added, and the mixture was incubated at -20°C for 2 hours. The precipitate was centrifuged at 4500g for 5 minutes, the supernatant was discarded, and the precipitate was washed 2-3 times with pre-chilled acetone. After drying the precipitate, 200 mM TEAB was added, and the precipitate was sonicated to disperse it. Trypsin was added at a ratio of 1:50 (protease: protein, m / m), and the mixture was incubated overnight. Dithiothreitol (DTT) was added to a final concentration of 5 mM, and the mixture was reduced at 56°C for 30 minutes. Iodoacetamide (IAA) was then added to a final concentration of 11 mM, and the mixture was incubated at room temperature in the dark for 15 minutes.

[0016] 4. Liquid chromatography-mass spectrometry analysis: Peptides were dissolved in mobile phase A of liquid chromatography and then separated using a NanoElute ultra-high performance liquid chromatography (UHPLC) system. Mobile phase A was an aqueous solution containing 0.1% formic acid and 2% acetonitrile; mobile phase B was an acetonitrile-water solution containing 0.1% formic acid. The liquid phase gradient settings were: 0-24 min, 6%-24% B; 24-32 min, 24%-35% B; 32-36 min, 35%-80% B; 36-40 min, 80% B, with the flow rate maintained at 500 nl / min. After separation by the UHPLC system, the peptides were injected into a Capillary ion source for ionization and then subjected to tempSTOF Pro mass spectrometry for data acquisition. The ion source voltage was set to 1.75 kV, and the precursor ion and secondary fragments of the peptides were detected and analyzed using TOF. The data acquisition mode uses the data-independent parallel cumulative serial fragmentation (dia-PASEF) mode. The primary mass spectrometry scan range is set to 300-1500 m / z. After acquiring one primary mass spectrometer, 20 PASEF mode acquisitions are performed. The secondary mass spectrometry scan is in the range of 400-850 m / z, with each window being 7 m / z.

[0017] 5. Analysis based on protein function enrichment: (1) Calculate the Pearson correlation coefficient between each pair of samples based on the intensity values ​​of all samples, and draw a visual heatmap. Figure 1 This coefficient measures the correlation between two sets of data. The redder the color, the closer the Pearson correlation coefficient is to 1, and the stronger the correlation between the two samples. (2) To demonstrate the quantification depth of each sample, we counted the number of proteins quantified in each sample and plotted a bar chart (e.g., Figure 2 (As shown).

[0018] (3) Draw an expression heatmap of the union of differentially expressed proteins in all glioblastoma patients and low-grade glioma patients (quantitative values ​​are required in at least 2 / 3 of the total samples). Figure 3 This section displays the relative expression levels of multiple differentially expressed proteins in different samples, showing the clustering relationships of their relative expression levels. Each row represents one differentially expressed protein, and each column represents one sample. Red indicates high expression, blue indicates low expression, and gray indicates samples where expression cannot be quantified.

[0019] (4) Upregulated proteins were screened from all differentially expressed proteins and mass spectrometry was performed. The ratio of protein spectrum signal intensity of upregulated proteins in glioblastoma patients and low-grade glioma patients was calculated and statistically analyzed. A value ≥5 was considered significantly upregulated. After removing common proteins, a total of 9 proteins were screened: IGLV1-47, IGKV2-28, IGKV3D-15, SLC30A7, IGKV3D-20, IGKV3-15, PABPC4L, PSMG4, and SDK1. The following table shows the ratio of protein signal intensity for each protein in the glioblastoma patient group and the low-grade glioma patient group: These upregulated proteins showed significant differences between glioblastoma and low-grade glioma patients, which could provide a new direction for subsequent diagnosis to differentiate glioblastoma from low-grade glioma.

[0020] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A protein composition for diagnosing and differentiating glioblastoma from low-grade glioma, characterized in that, The protein composition is at least one of IGLV1-47, IGKV2-28, IGKV3D-15, SLC30A7, IGKV3D-20, IGKV3-15, PABPC4L, PSMG4, and SDK1.

2. The protein marker composition according to claim 1, characterized in that: Compared to low-grade glioma controls, elevated expression levels of the protein marker composition indicated a risk of glioblastoma in the subjects.

3. The use of an identification reagent for a protein marker composition used to diagnose and differentiate glioblastoma from low-grade glioma in the preparation of a product for differentiating glioblastoma from low-grade glioma, characterized in that: The identification reagent is used to identify the content of any one or more proteins, including IGLV1-47, IGKV2-28, IGKV3D-15, SLC30A7, IGKV3D-20, IGKV3-15, PABPC4L, PSMG4, and SDK1, in tumor tissue samples.

4. A product for diagnosing and differentiating glioblastoma from low-grade glioma, characterized in that: The product contains the identification reagent as described in claim 3.

5. The product according to claim 4, characterized in that: The products mentioned are test strips, reagent kits, chips, antigen-antibody conjugates, probes, or test strips.