A method for verifying tbcb glioblastoma and cell proliferation
By combining TBCB gene knockdown and transcriptome analysis with DisGeNET disease enrichment and public database validation, the instability and high cost of molecular target screening for glioblastoma in existing technologies have been resolved, realizing an efficient and direct validation method, and improving validation efficiency and the stability of conclusions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHONGQING MEDICAL UNIVERSITY
- Filing Date
- 2026-03-05
- Publication Date
- 2026-06-09
AI Technical Summary
Existing technologies for screening molecular targets and biomarkers for glioblastoma suffer from problems such as poor stability of candidate molecules, weak association with the disease, and lack of systematic verification mechanisms, resulting in high false positive rates, long cycles, and high costs, making it difficult to form an efficient screening pathway.
Using the TBCB gene as a starting point, DisGeNET disease enrichment analysis was performed using the knockdown transcriptome data. The significant correlation between TBCB and GBM was verified by combining public databases. The effect on cell proliferation was verified by EdU experiments on U87 cells, thus realizing a closed-loop process from mechanism discovery to functional verification.
This approach enables direct disease targeting of glioblastoma, strengthens the evidence chain of the validation method, improves validation efficiency and the stability of conclusions, and reduces the costs of blind screening and repeated validation.
Smart Images
Figure CN122177227A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the fields of bioinformatics and tumor molecular biology, specifically relating to a method for verifying TBCB glioblastoma and cell proliferation. Background Technology
[0002] Glioblastoma (GBM) is a highly malignant primary brain tumor. Currently, the screening process for its molecular targets or biomarkers still has many limitations, mainly manifested in the poor stability of candidate molecules, weak association with disease background, and lack of systematic validation mechanisms.
[0003] Existing technologies mainly rely on the following methods: (1) Differential expression screening methods based on public databases, such as extracting expression data of GBM and normal brain tissue or low-grade glioma from databases such as TCGA, CGGA or GEO, and screening candidate genes through differential analysis, survival analysis or tumor grade correlation analysis. Although this method is low-cost, it is easily affected by sample heterogeneity, batch effect and threshold setting, resulting in a high false positive rate, and the results mostly remain at the correlation level, making it difficult to clarify causal relationships. (2) Methods based on gene perturbation combined with transcriptome sequencing and pathway enrichment, usually by knocking down or overexpressing the target gene and then performing RNA-seq, and then using enrichment analysis such as GO or KEGG to infer its biological function. The output of this method is mostly a description of pathway entries, which is difficult to directly point to specific disease entities such as "glioblastoma", making the results disconnected from the clinical disease background. (3) In vitro functional verification methods represented by EdU, CCK-8, and clonogenicity can assess the impact of candidate genes on phenotypes such as cell proliferation, but their verification process depends on the effectiveness of the front-end screening results. Without precise disease targeting and clinical data support, it is often necessary to verify a large number of candidate molecules one by one, resulting in long cycles, high costs, and difficulty in forming an efficient screening path.
[0004] In summary, current technologies have not yet formed a standardized and reusable research route that can organically link "transcriptome changes after gene perturbation → clear identification of disease items → joint verification of multiple public cohorts → phenotypic confirmation of in vitro functional experiments". Summary of the Invention
[0005] In view of this, the purpose of this invention is to provide a method for verifying TBCB glioblastoma and cell proliferation. Using the TBCB gene as a starting point, DisGeNET disease enrichment analysis is performed using the transcriptome data after its knockdown to clarify the association between this gene and GBM-related disease entries. Then, the significant correlation between TBCB and GBM is verified using public databases. Finally, its effect on cell proliferation is verified through the EdU experiment on U87 cells, thus achieving a closed-loop process from mechanism discovery to functional verification.
[0006] To achieve the above objectives, the present invention provides the following technical solution: This invention discloses a method for verifying TBCB glioblastoma and cell proliferation, comprising the following steps: S1. Constructing a TBCB knockdown model: Select the normal C8-D1A astrocyte cell line and transfect it with siRNA for knockdown; set up a negative control group and an experimental group respectively, where the negative control group was a non-target sequence and the experimental group was a TBCB-target sequence. Within 24-72 hours after transfection, the decrease in TBCB expression was detected by qRT-PCR and / or Western blot. S2, RNA-seq: Total RNA was extracted from the negative control group and the experimental group, respectively. After quality control, library construction and sequencing were performed to obtain raw data. It is recommended that each group have no less than 3 biological replicates. S3. Analyze differential expression: Perform differential analysis on the expression matrix to obtain the DEGs set, and set the fold change threshold used when screening differentially expressed genes; S4. Enrichment of DisGeNET Diseases: DEGs were input into DisGeNET for disease enrichment, and the enrichment significance and ranking of each disease entry were calculated. When glioblastoma and astrocytoma-related entries were significantly enriched, it was determined that the transcriptomic changes induced by TBCB knockdown were highly correlated with the GBM disease network. S5. Validate public databases: Obtain GBM and control sample expression data from GEO, TCGA, and CGGA, and compare the expression differences of TBCB in GBM and controls; perform Kaplan-Meier analysis according to the high and low expression levels of TBCB to strengthen the clinical evidence chain; S6. Verification of EdU proliferation: Control transfection and TBCB knockdown transfection were performed in U87 cells respectively; EdU was added and incubated for 0.5-4 hours after knockdown for 48-72 hours; after fixation and permeabilization, Click reaction labeling and nuclear staining were performed, and fluorescence images were collected; the proportion of EdU positive cells was counted and statistically compared; when there was a significant difference between the EdU positive rate of the knockdown group and the control group, it proved that TBCB knockdown would affect the proliferation of U87 cells.
[0007] Furthermore, in step S1, the effective threshold for knocking down is set to any one of a decrease of ≥30%, ≥50%, or ≥70%.
[0008] Furthermore, in step S4, when disease enrichment occurs, it is performed using a hypergeometric test and FDR correction; significant enrichment of glioblastoma and astrocytoma related entries refers to the statistical significance ranking after FDR correction, specifically the top 5-20.
[0009] Furthermore, in step S6, the concentration of EdU added 48-72 hours after knockdown is 5-20 μM; the proportion of EdU-positive cells is calculated as the number of EdU-positive cells / the total number of cells.
[0010] Furthermore, in step S3, the threshold can be set to any one of |Fold change|≥1.2 / 1.5 / 2.0, and the P value or the corrected P value <0.05 or 0.01.
[0011] The beneficial effects of this invention are as follows: 1. The verification method of this invention is more directly targeted to diseases: by using DisGeNET disease enrichment, the DEGs set is directly mapped to specific disease items such as "glioma / glioma", avoiding only staying at the pathway level.
[0012] 2. The verification method of this invention has a more complete evidence chain: it superimposes multi-cohort verification from public databases on the basis of disease entry pointing, thereby improving the stability and reproducibility of the conclusions.
[0013] 3. The verification method of this invention has high verification efficiency: the functional confirmation can be completed quickly using the EdU experiment of U87 and U251 cells, reducing the cost of blind screening and repeated verification.
[0014] 4. The verification method of this invention is universal and scalable: the method framework can be transferred to other candidate genes (simply by replacing TBCB) for the discovery and functional verification of tumor-related genes.
[0015] Other advantages, objectives, and features of the invention will be set forth in the following description and will be apparent to those skilled in the art in some respects, or may be learned by practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description
[0016] To make the objectives, technical solutions, and beneficial effects of this invention clearer, the following figures are provided for illustration: Figure 1 This is a flowchart illustrating the technical route of the present invention; Figure 2 This is a diagram showing the disease enrichment results of the DisGeNET algorithm in this invention. Figure 3 This is a verification diagram of the public database of this invention; Figure 4 This is a flowchart of the EdU proliferation experiment of the present invention; Figure 5 The figure shows the experimental results of EdU in this invention. Detailed Implementation
[0017] like Figures 1-5As shown, this invention discloses a method for verifying TBCB glioblastoma and cell proliferation.
[0018] S1 and TBCB knockdown model construction: C8-D1A normal astrocyte cell line was selected for transient siRNA transfection. A negative control group (non-targeted sequence) and an experimental group (targeting TBCB) were then set up. Within 48 hours of transfection, qRT-PCR was used to detect the decrease in TBCB expression; the effective knockdown threshold could be set as a decrease of ≥30%. S2, RNA-seq: Total RNA was extracted from the negative control group and the experimental group, respectively. After quality control, library construction and sequencing were performed to obtain raw data. It is recommended that each group have no less than 3 biological replicates. S3. Differential Expression Analysis: Perform differential analysis on the expression matrix to obtain the DEGs set. The threshold can be set to one of |Fold change|≥1.5 and the p-value <0.05. S4, DisGeNET disease enrichment: DEGs were input into DisGeNET for disease enrichment, hypergeometric test and FDR correction were performed, and the enrichment significance and ranking of each disease item were calculated. When the entries related to glioblastoma and astrocytoma were significantly enriched and ranked high, it was determined that the transcriptomic changes induced by TBCB knockdown were highly correlated with the GBM disease network.
[0019] S5, Public Database Validation: GBM and control sample expression data were obtained from GEO, TCGA, and CGGA. The expression difference of TBCB in GBM and control was compared. Grade correlation or prognostic correlation analysis can be performed. Kaplan-Meier analysis was performed according to the grouping of TBCB expression levels to enhance the clinical evidence chain. S6, EdU proliferation verification: Control transfection and TBCB knockdown transfection were performed in U87 cells respectively. After knockdown, EdU at a final concentration of 10 μM was added and incubated for 2 hours 48-72 hours. After fixation and permeabilization, Click reaction labeling and nuclear staining were performed, and fluorescence images were collected. The proportion of EdU-positive cells was counted and statistically compared. If there was a significant difference between the EdU-positive rate of the knockdown group and the control group, it would prove that TBCB knockdown would affect the proliferation of U87 cells.
[0020] Verification method: First, a TBCB knockdown model of the C8-D1A normal astrocyte cell line was constructed, and the decrease in TBCB expression was confirmed by qRT-PCR and / or Western blot within 48 hours after transfection (verification step S1). Subsequently, RNA-seq was performed on the knockdown group and the control group to obtain expression matrices (validation step S2), and differential expression analysis was conducted to screen DEGs (validation step S3). The DEGs were input into DisGeNET for disease enrichment analysis (validation step S4), and then the expression differences of TBCB in GBM and control samples and the prognostic correlation with Kaplan-Meier were validated using public databases such as GEO, TCGA, and CGGA (validation step S5). Finally, the EdU incorporation experiment of U87 glioma cells was used to compare the proportion of EdU-positive cells in the knockdown group and the control group to verify the difference in cell proliferation (verification step S6).
[0021] Results Explanation: like Figure 2 As shown, according to the disease enrichment results of DisGeNET, the DEGs generated after TBCB knockdown can be significantly enriched in DisGeNET with disease entries related to glioblastoma / astrocytoma, and the relevant entries are ranked high, suggesting that "transcriptome changes caused by TBCB knockdown" are highly correlated with the GBM disease network, which corresponds to the judgment criteria in step S4.
[0022] (2) such as Figure 3 As shown, the validation results from public databases indicate that TBCB is expressed at a higher level in GBM samples compared to control samples; and when Kaplan-Meier analysis was performed according to the grouping of TBCB expression levels, the high expression group was associated with poorer survival outcomes, which strengthens the chain of evidence at the clinical cohort level and corresponds to the judgment criteria in step S5.
[0023] (3) such as Figure 4 and Figure 5 As shown, the EdU proliferation verification results indicate that after knocking down TBCB in U87 cells, the proportion of EdU-positive cells was statistically different from that in the control group, indicating that knocking down TBCB affects the proliferation capacity of U87 cells, which corresponds to the judgment criteria in step S6.
[0024] Finally, it should be noted that the above preferred 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 through the above preferred embodiments, those skilled in the art should understand that various changes can be made to it in form and detail without departing from the scope defined by the claims of the present invention.
Claims
1. A method for verifying TBCB glioblastoma and cell proliferation, characterized in that: Includes the following steps, S1. Constructing a TBCB knockdown model: Select the normal C8-D1A astrocyte cell line and transfect it with siRNA for knockdown; set up a negative control group and an experimental group respectively, where the negative control group was a non-target sequence and the experimental group was a TBCB-target sequence. Within 24-72 hours after transfection, the decrease in TBCB expression was detected by qRT-PCR and / or Western blot. S2, RNA-seq: Total RNA was extracted from the negative control group and the experimental group, respectively. After quality control, library construction and sequencing were performed to obtain raw data. It is recommended that each group have no less than 3 biological replicates. S3. Analyze differential expression: Perform differential analysis on the expression matrix to obtain the DEGs set, and set the fold change threshold used when screening differentially expressed genes; S4. Enrichment of DisGeNET Diseases: DEGs were input into DisGeNET for disease enrichment, and the enrichment significance and ranking of each disease entry were calculated. When glioblastoma and astrocytoma-related entries were significantly enriched, it was determined that the transcriptomic changes induced by TBCB knockdown were highly correlated with the GBM disease network. S5. Validate public databases: Obtain GBM and control sample expression data from GEO, TCGA, and CGGA, and compare the expression differences of TBCB in GBM and controls; perform Kaplan-Meier analysis according to the high and low expression levels of TBCB to strengthen the clinical evidence chain; S6. Verification of EdU proliferation: Control transfection and TBCB knockdown transfection were performed in U87 cells respectively; EdU was added and incubated for 0.5-4 hours after knockdown for 48-72 hours; after fixation and permeabilization, Click reaction labeling and nuclear staining were performed, and fluorescence images were collected; the proportion of EdU positive cells was counted and statistically compared; when there was a significant difference between the EdU positive rate of the knockdown group and the control group, it proved that TBCB knockdown would affect the proliferation of U87 cells.
2. The method for verifying TBCB glioblastoma and cell proliferation according to claim 1, characterized in that: In step S1, the effective threshold for knocking down is set to any one of the following: a decrease of ≥30%, ≥50%, or ≥70%.
3. The method for verifying TBCB glioblastoma and cell proliferation according to claim 2, characterized in that: In step S4, when diseases are enriched, hypergeometric tests are performed and FDR correction is applied; significant enrichment of glioblastoma and astrocytoma related entries refers to the statistical significance ranking after FDR correction, specifically the top 5-20.
4. The method for verifying TBCB glioblastoma and cell proliferation according to claim 3, characterized in that: In step S6, EdU is added at a concentration of 5-20 μM 48-72 hours after knockdown; the proportion of EdU-positive cells is calculated as the number of EdU-positive cells / the total number of cells.
5. The method for verifying TBCB glioblastoma and cell proliferation according to claim 4, characterized in that: In step S3, the threshold can be set to any one of |Fold change|≥1.2 / 1.5 / 2.0, and the P value or the corrected P value <0.05 or 0.01.