Method for evaluating the smoking index and its use in the treatment and evaluation of bladder cancer

Abstract

The application provides a method for evaluating smoker index and application thereof in bladder cancer treatment and evaluation. The application has carried out in-depth research on the pathogenesis and development mechanism of bladder cancer, found that smoking is a risk factor highly correlated with bladder cancer, and constructed a quantifiable model-smoker index which can be used for system evaluation of the smoking state of patients, so that the prognosis and survival state of bladder cancer patients can be more accurately predicted and evaluated through analysis of the expression level of specific markers in the body of the subjects. The application clarifies the correlation between CGB5 and bladder cancer, and can effectively inhibit the proliferation, migration and other activities of bladder cancer cells by inhibiting the expression of CGB5. The application provides a new drug treatment target for human to conquer bladder cancer, thereby providing a new direction for subsequent drug research and development, clinical treatment and the like, and has very high social value and market application prospect.

Description

Technical Field

[0001] This invention belongs to the field of biomedicine and relates to a method for evaluating the smoker index and its application in the treatment and evaluation of bladder cancer. Background Technology

[0002] Statistics show that the age-standardized prevalence of daily smoking worldwide is as high as 15.2%. Smoking has long been one of the greatest threats to global public health because it increases the risk of various chronic diseases, such as coronary artery disease, chronic obstructive pulmonary disease, myocardial infarction, stroke, and cancer. Furthermore, smoking is considered a carcinogenic factor for many cancers, including lung cancer, laryngeal cancer, esophageal cancer, pancreatic cancer, kidney cancer, oral and pharyngeal cancer, stomach cancer, and endometrial cancer, leading to poor cancer-related prognoses.

[0003] Bladder cancer (BLCA) is one of the most common cancers and a leading cause of cancer-related mortality worldwide. Current consensus generally considers smoking a modifiable risk factor associated with bladder cancer, with an attributable risk of approximately 50% in the general population. An analysis of 83 studies found that current smokers have a higher risk of developing bladder cancer than never-smokers, with a combined relative risk (RR) of 3.47, compared to 2.04 for former smokers. These data suggest that quitting smoking may help reduce the risk of bladder cancer.

[0004] However, whether smoking affects the prognosis and survival of bladder cancer remains controversial. One study reported that lifelong smoking increases the risk of urothelial carcinoma progressing to more malignant types and has a worse prognosis. Conversely, another meta-analysis found no significant association between smoking status and overall cancer survival, recurrence rate, or cancer-specific mortality. Therefore, investigating and clarifying the potential relationship between smoking and the prognosis and survival of bladder cancer is of great significance. Summary of the Invention

[0005] The purpose of this invention is to address the technical problems in the prior art where the relationship between smoking and the prognosis and survival rate of bladder cancer is unclear, making early prevention and assessment difficult. This invention provides a kit for evaluating a smoker index and its application. The kit detects and analyzes the expression levels of smoking-related biomarkers in the subject's body, thereby determining the risk of bladder cancer or predicting the prognosis and survival rate of bladder cancer patients. It can effectively predict the occurrence and development of bladder cancer, thereby screening high-risk groups for reasonable early prevention, and designing personalized treatment plans and predicting the health status of patients with bladder cancer, significantly reducing the probability and severity of the disease and minimizing harm to human health.

[0006] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution.

[0007] The first aspect of this invention provides the use of CGB5 inhibitors in the preparation of medicaments for the prevention and / or treatment of bladder cancer.

[0008] It should be understood that, unless otherwise specified, in the context of this invention, the CGB5 inhibitor refers to a substance capable of specifically downregulating the expression level of CGB5 and / or the transcriptional level of its mature mRNA and / or the expression level or activity of CGB5 protein. For example, methods such as antisense oligonucleotides, siRNA, shRNA, sgRNA, antagomiRs, miRNA sponges, miRNA Erasers, target masking, and / or multi-target methods can be used to downregulate the expression level and / or activity of TMEM238, as long as they can reduce the level and / or activity of CGB5.

[0009] Preferably, the CGB5 inhibitor is selected from siRNA designed based on the CGB5 gene.

[0010] Preferably, the siRNA designed based on the CGB5 gene is selected from one or more of si-1, si-2, and si-3, wherein the sequence of si-1 is: ggugugcaacuaccgcgautt; the sequence of si-2 is: ggcucucagcugucaaugutt; and the sequence of si-3 is: ccaggacuccucuuccucatt.

[0011] A second aspect of the present invention provides the use of a reagent for detecting CGB5 expression levels in the preparation of products for the auxiliary diagnosis and / or prognostic assessment of bladder cancer.

[0012] Preferably, the reagent for detecting CGB5 expression level includes primer pairs for detecting CGB5 gene expression level and / or reagents for detecting the protein content encoded by CGB5 gene.

[0013] Preferably, the forward primer sequence of the primer pair for detecting CGB expression level is: ctcaccccagcatcctacaa, and the reverse primer sequence is: acatctccatccttggtgcg.

[0014] Preferably, the reagent for detecting the protein content encoded by the CGB5 gene is selected from CGB5 monoclonal antibodies and / or CGB polyclonal antibodies.

[0015] It should be understood that, unless otherwise specified, in the context of this invention, the primers and / or primer pairs refer to PCR primers used to synthesize the CGB5 gene cDNA strand in PCR, thereby detecting the expression level of the CGB5 gene. Besides the primers and / or primer pairs listed in this invention, those skilled in the art are fully capable of designing corresponding primers and / or primer pairs based on the CGB5 gene sequence using conventional methods and techniques in the art, including but not limited to molecular biology, and screening the designed primers and / or primer pairs using conventional experimental methods, as long as they can specifically detect the CGB5 expression level. Furthermore, the antibody reagents used to detect the protein content encoded by the CGB5 gene can be obtained commercially by those skilled in the art, or can be designed independently based on the CBG5 gene sequence and / or protein structure.

[0016] A third aspect of the present invention provides a kit for evaluating a smoker index, comprising reagents for detecting the expression level of biomarkers, said biomarkers being selected from one or more of SPANXC, CHGA, CGB5, SOSTDC1, DSG1, TUBB2B, SLC7A11, NTRK2, RGMA, UBD, GPR25, and CTSE.

[0017] Preferably, the markers consist of SPANXC, CHGA, CGB5, SOSTDC1, DSG1, TUBB2B, SLC7A11, NTRK2, RGMA, UBD, GPR25, and CTSE.

[0018] Preferably, the reagent for detecting the expression level of the biomarker includes primer pairs for detecting the expression level of the biomarker gene and / or reagents for detecting the protein content encoded by the biomarker gene.

[0019] As stated above, unless otherwise specified, in the context of this invention, the primers and / or primer pairs refer to PCR primers used to synthesize the cDNA strands of each biomarker gene in PCR, thereby detecting the expression level of each biomarker gene. Besides the primers and / or primers listed in this invention, those skilled in the art are fully capable of designing corresponding primers and / or primer pairs based on the gene sequences of each biomarker using conventional methods and techniques in the field, including but not limited to molecular biology, and screening the designed primers and / or primer pairs using conventional experimental methods, as long as they can specifically detect the expression level of each biomarker. Furthermore, the antibody reagents used to detect the protein content encoded by each biomarker gene can be obtained commercially by those skilled in the art, or can be designed independently based on the gene sequence and / or protein structure of each biomarker.

[0020] Preferably, the kit further includes one or more of PCR enzyme, PCR buffer, dNTPs, and fluorescent substrate.

[0021] Preferably, the fluorescent substrate is selected from Syber Green or fluorescently labeled probes.

[0022] The fourth aspect of the present invention provides the use of the above-described kit for evaluating the smoker index in the preparation of products for the auxiliary diagnosis and / or prognostic assessment of bladder cancer.

[0023] The fifth aspect of this invention provides a method for evaluating a smoker index, comprising the following steps:

[0024] (1) The expression levels of biomarkers in the subjects were detected, and the biomarkers were selected from one or more of SPANXC, CHGA, CGB5, SOSTDC1, DSG1, TUBB2B, SLC7A11, NTRK2, RGMA, UBD, GPR25, and CTSE;

[0025] (2) The smoker index is calculated using the following formula:

[0026]

[0027] Where N is the total number of selected markers; Coef i These are the coefficients of each marker.

[0028] Preferably, the markers consist of SPANXC, CHGA, CGB5, SOSTDC1, DSG1, TUBB2B, SLC7A11, NTRK2, RGMA, UBD, GPR25, and CTSE.

[0029] Preferably, the reagent for detecting the expression level of the biomarker includes primer pairs for detecting the expression level of the biomarker gene and / or reagents for detecting the protein content encoded by the biomarker gene.

[0030] To clarify the potential relationship between smoking and bladder cancer prognosis, the inventors of this invention conducted extensive research, classifying the smoking history of cancer patients according to the Cancer Genome Atlas (TCGA) project. They analyzed differentially expressed genes between non-smokers and current smokers in bladder cancer patients, identifying differentially expressed genes (DESeq2|fold change|>2, p<0.05). Subsequently, they constructed a smoking-related reference index, termed the "smoker-index," using LASSO and Cox regression, and used this index to predict and assess the prognosis and survival of bladder cancer patients. This index model incorporates 12 biomarkers: SPANXC, CHGA, CGB5, SOSTDC1, DSG1, TUBB2B, SLC7A11, NTRK2, RGMA, UBD, GPR25, and CTSE. The smoker-index of the subjects was calculated using the following formula:

[0031] Where N is the total number of selected markers; Coef i These are the coefficients of each marker.

[0032] Finally, through in vitro and in vivo experiments, the potential link between the smoker index and bladder cancer prognosis was verified from multiple perspectives, clarifying the impact of smoking on bladder cancer prognosis.

[0033] The present invention has the following technical advantages over the prior art:

[0034] (1) This invention has conducted in-depth research on the pathogenesis and development mechanism of bladder cancer, found that smoking is a risk factor highly associated with bladder cancer, and based on the analysis of multiple biomarkers in bladder cancer patients, constructed a quantifiable model that can be used to systematically evaluate the smoking status of patients - the Smoker Index. Thus, by analyzing the expression level of specific biomarkers in the subjects, the prognosis and survival status of bladder cancer patients, especially those with a history of smoking, can be more accurately predicted and evaluated.

[0035] (2) Among the biomarkers included in the Smoker Index of this invention, the inventors identified CGB5 as the biomarker with the highest association with bladder cancer and the highest carcinogenicity, and further studied the relationship between CGB5 and the occurrence and development of bladder cancer. The association between CGB5 and bladder cancer was clarified; inhibiting CGB5 expression can effectively inhibit the proliferation, colony formation, migration, and invasion of bladder cancer cells, thus clarifying that CGB5 can serve as a key target for clinical treatment and / or auxiliary diagnosis of bladder cancer.

[0036] (3) This invention, by revealing the correlation between the smoker index and CGB5 and bladder cancer, has significant practical implications for addressing the challenges of inter-individual differences in clinical efficacy and the lack of prognostic assessment in bladder cancer, and for better achieving precision treatment. It provides a new drug target for conquering bladder cancer, thus offering a new direction for subsequent drug development and clinical treatment, and possesses extremely high social value and market application prospects. Attached Figure Description

[0037] Figure 1 This is a schematic diagram showing the results of an analysis of smoking history in patients within the TCGA-BLCA population.

[0038] Figure 2 This is a schematic diagram illustrating the differences in survival rates among three groups of patients with different smoking histories.

[0039] Figure 3 This diagram illustrates the overall survival differences between patients with high and low smoking indices in the TCGA-BLCA population.

[0040] Figure 4 This diagram illustrates the differences in production results between patients with different smoking histories and patients with different smoking indices.

[0041] Figure 5 This provides an overview of the distribution of patients in the TCGA-BLCA population based on the smoking index.

[0042] Figure 6 This is a heatmap of the expression of the 12 genes included in the Smokers Index.

[0043] Figure 7 This is a schematic diagram illustrating the differences in smoker index among patients at different pathological stages.

[0044] Figure 8 Differences in smoker index among patients with different clinically diagnosed tumor stages.

[0045] Figure 9 This is a schematic diagram illustrating the results of a univariate Cox analysis used to examine the validity of the smoker index.

[0046] Figure 10 This is a schematic diagram illustrating the results of multivariate Cox analysis used to examine the effectiveness of the smoker index.

[0047] Figure 11 This is a schematic diagram showing the survival results of different smoker index subgroups in the GSE13507 population.

[0048] Figure 12 This is a schematic diagram illustrating the overall survival differences between patients in the high-index and low-index groups within the GSE13507 population.

[0049] Figure 13 The distribution of patients in the GSE13507 group based on the smoker index.

[0050] Figure 14 A heatmap of genes associated with the smoking index in the GSE13507 population.

[0051] Figure 15 This is a schematic diagram showing the differences in smoking index among patients with different clinically diagnosed tumor stages in the GSE13507 group.

[0052] Figure 16 This is a schematic diagram showing the differences in smoking index among patients with and without progression in the GSE13507 group.

[0053] Figure 17 This is a schematic diagram illustrating the survival outcomes in each smoker index subgroup within the IMVigor210 immunotherapy population.

[0054] Figure 18 This is a schematic diagram illustrating the overall survival difference between high-index and low-index patients in the IMVigor210 immunotherapy population.

[0055] Figure 19 The distribution of patients in the IMVigor210 immunotherapy population based on the smoker index.

[0056] Figure 20 A heatmap of genes associated with the smoking index in the IMVigor210 immunotherapy population.

[0057] Figure 21 This is a schematic diagram showing the differences in smoker index among patients with different clinically diagnosed tumor stages in the IMVigor210 immunotherapy group.

[0058] Figure 22 This is a schematic diagram showing the differences in smoking index among patients with and without progression in the IMVigor210 immunotherapy group.

[0059] Figure 23 To investigate the association between CGB5 expression and overall survival in the TCGA-BLCA and IMVigor210 populations.

[0060] Figure 24 This is a schematic diagram showing the results of the inhibition of CGB5 expression in bladder cancer cells by three specific siRNAs.

[0061] Figure 25 This is a schematic diagram illustrating the effect of CGB5 inhibitors on the proliferation of bladder cancer cells.

[0062] Figure 26This is a schematic diagram illustrating the effect of CGB5 inhibitors on the clonogenic ability of bladder cancer cells.

[0063] Figure 27 This is a schematic diagram illustrating the effect of CGB5 inhibitors on bladder cancer migration.

[0064] Figure 28 A schematic diagram showing the CGB5 expression results in BLCA patients of different grades. Detailed Implementation

[0065] To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0066] Unless otherwise specified, cell lines including UM-UC-3 and BIIU87 listed in this invention context were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA) and cultured in MEM (Gibco, 11095080) or RPMI-1640 (Gibco, 11875093) medium with 10% fetal bovine serum (ZetaLife, Z7186FBS-500) and 1% penicillin antibody (Gibco, 15140-122) at 37°C and 5% CO2. All cell lines were identified by short tandem repeat analysis at the China Center for Type Culture Collection (Wuhan) and their presence of mycoplasma contamination was verified using a PCR detection kit (Shanghai Biothrive Sci). They were also cryopreserved in liquid nitrogen for subsequent experiments. All reagents used in this invention were commercially available. Informed consent was obtained from patients for all clinical specimens used, and the relevant procedures and methods complied with medical ethics requirements and Good Clinical Practice (GCP) guidelines. The experimental methods used in this invention, such as model construction, bioinformatics analysis, DNA extraction, genome sequencing, primer design, PCR, Western blot, tumor cell culture, cell migration assay, cell survival assay, and immunohistochemistry, are all conventional methods and techniques in this field.

[0067] Representative results from biological experiments were selected from replicates and presented in the contextual figures. Data were displayed as mean ± SD and mean ± SEM as specified in the figures. All experiments were repeated at least three times. Data were analyzed using GraphPad Prism 9.0 or SPSS 22.0 software. Standard medical statistical methods such as t-tests, chi-square tests, and ANOVA were used to compare differences in means between two or more groups. p < 0.05 was considered statistically significant.

[0068] Example 1: Screening of Biomarkers

[0069] To clarify the impact of smoking on the prognosis of BLCA patients, bladder cancer patients in the TCGA-BLCA population were first divided into three groups according to their smoking status: non-smokers, ever-smokers, and current-smokers. Among the three groups, the proportion of patients in the ever-smokers group was approximately equal (50%), while the proportions in the other two groups were similar (non-smokers (28%), current-smokers (22%)) (see [link to relevant documentation]). Figure 1 Subsequently, a Kaplan-Meier (KM) survival analysis was performed on the three groups of patients to investigate the differences in survival status among them. The results showed that bladder cancer patients in the still-smoking group had the worst survival rate (median survival time of 26.6 months), while bladder cancer patients in the never-smoking group had the most favorable survival (median survival time of 54.6 months), more than twice that of the still-smoking group; the survival rate of bladder cancer patients in the former-smoking group was between the other two groups (median survival time of 31.4 months) (see...). Figure 2 ).

[0070] Furthermore, gene transcription data from patients in both the non-smoking and smoking groups were analyzed to identify differentially expressed genes (DEGs) between the two groups. Functional enrichment analysis of these DEGs was then performed to preliminarily clarify their potential mechanisms with bladder cancer. Subsequently, a model named the "Smoker Index" was established using LASSO-Cox regression and 10-fold cross-validation. This model incorporated 12 biomarkers: SPANXC, CHGA, CGB5, SOSTDC1, DSG1, TUBB2B, SLC7A11, NTRK2, RGMA, UBD, GPR25, and CTSE. The Smoker Index for each group was calculated using the following formula:

[0071] Where N is the total number of selected markers; Coef i The coefficients for each biomarker are shown in Table 1 below.

[0072] Table 1. Coef coefficients of 12 biomarkers

[0073]

[0074] Based on the median index score obtained from the calculation, the groups were divided into two subgroups: a high index group and a low index group. KM analysis was then performed on both groups, and the results are as follows: Figure 3 As shown in the figure. The results showed that the overall survival (OS) of bladder cancer patients in the high-index group was significantly lower than that in the low-index group (p < 0.0001). Furthermore, analysis of smoking status in the high-index and low-index groups revealed that regardless of the index score, the survival rate of long-term smokers was significantly lower than that of non-smokers; while in the non-smoker group, patients with low index scores showed better survival outcomes than those with high index scores, and the same trend was observed in the group of patients who were still smoking (see [reference]). Figure 4 ). Figure 5 The graph shows an overview of the index scores of the TCGA-BLCA population. Patients are ranked according to their index scores in the upper box, while the lower box shows each patient's status (death or survival). It is clear from the graph that patients in the high-index group have a higher mortality rate than patients in the low-index group. Figure 6 The heatmap shows the expression differences of 12 genes between the high-index and low-index subgroups.

[0075] Analysis of the Smoker Index and some clinical characteristics of BLCA (pathological T grade and tumor stage) revealed a significant difference in index scores between patients with T2 and T3 or T4 grades (p < 0.01), and the Smoker Index score increased significantly with increasing T stage (see [link to relevant documentation]). Figure 7 A similar trend in smoker index scores was observed in tumor staging analysis of bladder cancer patients (see [link to relevant documentation]). Figure 8 ).

[0076] Finally, univariate and multivariate Cox regression analyses were performed on the above groups of bladder cancer patients to clarify the clinical value of the smoker index. The results are as follows: Figure 9-10 As shown in the figure. The results showed that in univariate Cox regression analysis, the smoker index was significantly better than other factors, such as tumor stage, pathological T grade, pathological N grade, pathological M grade, disease type (papillary or non-papillary), age, etc., with a hazard ratio (HR) of 4; while in multivariate Cox regression analysis, only the smoker index showed a statistically significant HR value.

[0077] Example 2

[0078] To validate the external validity of the smoker index, a dataset (GSE13507) from the GEO database was used as a validation dataset. Analysis revealed a significant difference in mortality rates between the two groups; specifically, the mortality rate of the low smoker index group was significantly lower than that of the high smoker index group (see [link to analysis]). Figure 11 KM analysis showed the same trend in both the high-index and low-index groups, namely, that patients in the high-index group had worse overall survival (OS) compared to the low-index group (see [link to KM analysis]). Figure 12 ). Figure 13 The data shows the smoker index scores and survival status of GSE13507 patients, arranged in ascending order of smoker index scores. Figure 14 This showed the expression of 12 genes in each GSE13507 sample and the expression differences between groups, with results similar to those described above. Subsequently, an association analysis between the smoker index score and the patient's T stage revealed that patients with any T stage higher than T1 had significantly higher smoker index scores than T1 patients. Similarly, patients with disease progression had significantly higher index scores than those without progression (see [link to relevant documentation]). Figure 15-16 ).

[0079] Since immunotherapy plays a crucial role in bladder cancer treatment, the effectiveness of the smoker index of this invention was further validated in the classic IMvigor210 population. According to the GSE13507 dataset, in the IMvigor210 population, the mortality rate of patients in the low smoker index group was significantly lower than that in the high smoker index group (p < 0.01) (see...). Figure 17 KM analysis showed that for patients who received immunotherapy, the high-index group had a worse overall survival (OS) compared to the low-index group (see [link]). Figure 18 ). Figure 19 The image shows the distribution of index scores for the IMvigor210 population combined with survival data. Figure 20 The middle section shows the expression of 12 genes in each sample of the IMvigor210 population and the expression differences between groups, with most genes showing low expression. Subsequently, the smoker index scores of patients with different TCGA subtypes and different immunophenotypes were analyzed, and the results are as follows: Figure 21-22 As shown in the figure. The results showed that the smoker index scores of patients with type III and type IV were significantly higher than those of patients with type I and type II; there were significant differences in the smoker index among the three different immune phenotypes, with patients with the inflammatory phenotype having the highest smoker index scores.

[0080] Example 3

[0081] Analysis of 12 biomarkers associated with the smoker index revealed that CGB5 was one of the highest risk factors for cancer; therefore, CGB5 was selected for further research. KM survival analysis using patients with high and low CGB5 expression in the TCGA-BLCA population showed that patients with high CGB5 expression had a worse prognosis than those with low CGB5 expression. Studies in the IMvigor210 population yielded results consistent with those in the TCGA-BLCA population (see [link to study]). Figure 23 Therefore, it can be clearly seen that CGB5 is a key target in the progress of BLCA.

[0082] To verify the effect of CGB5 on the occurrence and development of BLCA, three siRNAs were designed and synthesized based on the CGB5 sequence, with the following sequences: si-1: ggugugcaacuaccgcgautt; si-2: ggcucucagcugucaaugutt; si-3: ccaggacuccucuuccucatt. These siRNAs were transfected into UM-UC-3 and BIU-87 cells, respectively. Western blotting was used to detect the effect of the three siRNAs on the expression level of CGB5 protein in bladder cancer cells. The specific steps are as follows:

[0083] (1) After the cells were transfected and cultured for 24 hours, the original culture medium was discarded and PBS was added to wash the cells twice.

[0084] (2) Add cell lysis buffer (containing PMSF) and lyse on ice for 30 min.

[0085] (3) Transfer cells to sterile centrifuge tubes and centrifuge at 12,000 rpm for 10 min at 4 °C. Collect the supernatant to obtain cell lysis buffer and extract total cell protein according to the kit instructions (Shanghai Beyotime Biotechnology Co., Ltd.). Measure the protein concentration of each group using the BCA protein quantification method (Thermo). Dilute each group of proteins to the same concentration using cell lysis buffer, add 5× loading buffer at a volume ratio of 4:1, mix, and denature at 98 °C for 5 min.

[0086] (4) Extract 20 μg of total protein, perform 10% SDS-PAGE gel electrophoresis (100V, 90 min), transfer membrane at a constant current of 300 mA for 100 min to PVDF membrane; block with 5% BSA at room temperature on a shaker for 2 h, incubate with CBG5 primary antibody (1:1000) at 4℃ overnight, wash 3 times with TBST for 5 min each time, dilute the secondary antibody (1:20000) with blocking buffer, and incubate at room temperature for 1 h; wash 3 times with TBST for 7 min each time, expose with ECL luminescence kit (Santa Cruz) in an exposure instrument, use internal control β-actin as control, and analyze the net optical density value of the bands using a gel image processing system (Image-Pro Plus 6.0).

[0087] Test results as follows Figure 24 As shown in the figure. The results showed that all three siRNAs could significantly inhibit the expression of CGB5 in bladder cancer cells.

[0088] Subsequently, si-1 and si-2, which showed more significant inhibitory effects, were selected for cell proliferation and colony formation experiments. The specific steps of the cell proliferation experiment are as follows:

[0089] (1) UM-UC-3 and BIU-87 cells transfected with si-1 or si-2 in the logarithmic growth phase, and UM-UC-3 and BIU-87 cells transfected with blank vector (si-NC) were taken as controls. They were digested with trypsin and counted. The appropriate cell density was selected according to the doubling time of each cell type and seeded into 96-well plates (3 replicates).

[0090] (2) The cells were cultured in a 37°C incubator and collected at 24h, 48h, 72h, 96h and 120h respectively. 10μL of CCK-8 was added to each well, and the culture plate was incubated in the incubator for 1-4h. The absorbance at 450nm was measured to evaluate the cell proliferation status.

[0091] The steps of the clone formation experiment are as follows:

[0092] (1) Transfect CGB5-targeting siRNAs (si-1 and si-2) into UM-UC-3 and BIU-87 cells, respectively;

[0093] (2) When the cells grow to the logarithmic phase, digest them with trypsin and count them. Select the appropriate cell density according to the doubling time of various cells, and seed them into a dish containing 10 mL of 37℃ pre-warmed culture medium. Gently rotate the dish to disperse the cells evenly and place it in a cell culture incubator at 37℃, 5% CO2 and saturated humidity.

[0094] (3) When visible clones appear in the culture dish, stop the culture, discard the supernatant, carefully wash twice with PBS, add 1 mL of methanol containing 0.5% crystal violet to each well, and stain for 30 min; discard the methanol and wash off the residual methanol with water; cell clones can then be observed; under a microscope, a number of cells > 50 is considered a valid clone.

[0095] Experimental results are as follows Figure 25-26 As shown in the figure. The results showed that, compared with the blank vector si-NC group, the proliferation and colony formation ability of bladder cancer cells were significantly reduced after silencing the CGB5 gene with siRNA. That is, inhibiting the expression of CGB5 can significantly inhibit the proliferation and colony formation of bladder cancer cells, and the difference is statistically significant.

[0096] Subsequently, the effect of CGB5-targeting siRNA on the migration ability of bladder cancer cells was investigated. The specific steps are as follows:

[0097] The 8μm pore size chambers and 24-well plates of Corning Transwell Migration were used.

[0098] (1) Place the chamber in a 24-well plate and add 1 mL of basal culture medium to each well to moisten it.

[0099] (2) After trypsin digestion of cells in the logarithmic growth phase, the cells were resuspended in basal medium to form a cell suspension, counted, and the cell density was adjusted to 5 × 10⁶ cells / year. 5 per mL.

[0100] (3) Remove and discard the basal culture medium from the transwell chamber and the 24-well plate. Add 200 μL of cell suspension to the upper chamber of the transwell chamber and 600 μL of complete culture medium (basal culture medium + 10% fetal bovine serum) to the lower chamber of the 24-well plate.

[0101] (4) Place the culture plate in a CO2 incubator at 37°C and continue to incubate for 14 hours.

[0102] (5) Remove the chamber, rinse twice with PBS, fix with 4% paraformaldehyde in a 24-well plate for 20 min, and stain with crystal violet solution for 15 min.

[0103] (6) Carefully wipe away the cells in the upper layer of the microporous membrane of the chamber with a cotton swab and take a picture under an inverted microscope.

[0104] The results are as follows: Figure 27 As shown in the figure. The results showed that, compared with the control group (si-NC), inhibiting CGB5 expression using si-1 or si-2 significantly reduced the migration ability of bladder cancer cells (p < 0.001). Immunohistochemical analysis of pathological samples from bladder cancer patients showed that the expression level of CGB5 in bladder cancer tissues from high-grade bladder cancer patients was significantly higher than that from low-grade bladder cancer patients (see [reference]). Figure 28 Furthermore, CGB5 is primarily located in the cytoplasm. In summary, CGB5 is clearly one of the targets highly associated with the occurrence and development of bladder cancer; inhibiting CGB5 expression can effectively suppress the growth and metastasis of bladder cancer.

[0105] Blackhead adenocarcinoma (BLCA) is one of the five most common cancers in the United States and a leading cause of cancer-related mortality worldwide. Smoking is a recognized key risk factor for BLCA. However, the relationship between BLCA prognosis and smoking remains unclear. This invention constructs a "smoker index" model through a series of studies to evaluate the association between smoking and BLCA, its prognosis, and survival. KM analysis and Cox regression model analysis of the TCGA-BLCA population revealed that patients with a high smoker index had a worse overall survival (OS) than those with a low smoker index. These results were further validated using an external validation dataset (GSE13507). Subsequently, analysis of the IMvigo210 population revealed a similar effect of the smoker index on the efficacy of bladder cancer immunotherapy. The KM curve showed that patients with a high smoker index had a worse OS than those with a low smoker index, suggesting that a higher index may predict a weaker response to immunotherapy. This further demonstrates that smoking-related characteristics may be more reliable than other indicators in predicting prognosis.

[0106] To further validate the effectiveness of the smoker index, the central gene CGB5, which had the highest coefficient in the model, was selected for further study. Results showed that CGB5 is mainly located in the cytoplasm of BLCA tissues and cells, and a series of in vitro experiments demonstrated that CGB5 knockout effectively reduced proliferation and migration in BLCA. This invention successfully constructed and validated a smoker index model containing 12 genes, enabling reasonable and effective prediction of the prognosis and reproductive status of BLCA patients. Simultaneously, a series of high-risk sites associated with BLCA were identified, especially CGB5. Inhibiting CGB5 expression effectively suppressed the proliferation, colony formation, and migration of bladder cancer cells, thus clarifying that CGB5 can serve as a key target for clinical treatment and / or auxiliary diagnosis of bladder cancer. This has significant practical implications for addressing the challenges of inter-individual differences in clinical efficacy and prognostic assessment gaps in bladder cancer, and for achieving better precision treatment. This provides a new drug therapeutic target for conquering bladder cancer, offering a new direction for subsequent drug development and clinical treatment, and possesses extremely high social value and market application prospects.

[0107] The above detailed embodiments provide a specific description of the analytical methods involved in this invention. It should be noted that the above description is only intended to help those skilled in the art better understand the methods and ideas of this invention, and is not intended to limit the scope of the invention. Without departing from the principles of this invention, those skilled in the art can make appropriate adjustments or modifications to this invention, and such adjustments and modifications should also fall within the protection scope of this invention.

Claims

1. The use of CGB5 inhibitors in the preparation of medicaments for the prevention and / or treatment of bladder cancer, characterized in that, The CGB5 inhibitor is selected from siRNA designed based on the CGB5 gene; the siRNA designed based on the CGB5 gene is selected from one or more of si-1, si-2, and si-3, wherein the sequence of si-1 is: ggugugcaacuaccgcgautt; the sequence of si-2 is: ggcucucagcugucaaugutt; and the sequence of si-3 is: ccaggacuccucuuccucatt.

2. Application of reagents for detecting CGB5 expression levels in the preparation of products for the auxiliary diagnosis and / or prognostic assessment of bladder cancer.

3. The application according to claim 2, characterized in that, The reagents for detecting CGB5 expression levels include primer pairs for detecting CGB5 gene expression levels and / or reagents for detecting the protein content encoded by the CGB5 gene.

4. A kit for evaluating a smoker's index, characterized in that, It includes reagents for detecting the expression level of biomarkers, said biomarkers being selected from one or more of SPANXC, CHGA, CGB5, SOSTDC1, DSG1, TUBB2B, SLC7A11, NTRK2, RGMA, UBD, GPR25, and CTSE.

5. The reagent kit according to claim 4, characterized in that, The reagents for detecting biomarker expression levels include primer pairs for detecting biomarker gene expression levels and / or reagents for detecting the protein content encoded by biomarker genes.

6. The use of the kit for evaluating the smoker index according to any one of claims 4-5 in the preparation of products for the auxiliary diagnosis and / or prognostic assessment of bladder cancer.

7. A method for evaluating a smoker index, characterized in that, Includes the following steps: (1) The expression levels of biomarkers in the subjects were detected, and the biomarkers were selected from one or more of SPANXC, CHGA, CGB5, SOSTDC1, DSG1, TUBB2B, SLC7A11, NTRK2, RGMA, UBD, GPR25, and CTSE; (2) The smoker index is calculated using the following formula: Smoker Index = ; Where N is the total number of selected markers; Coef i The coefficients of each marker; The Coef coefficients for each marker are as follows: CGB5: 0.150851951; SOSTDC1: 0.104874398; DSG1: 0.077113133; RGMA: 0.051161927; TUBB2B: 0.050026655; NTRK2: 0.047149307; SLC7A11: 0.043720056; SPANXC: 0.030706914; CHGA: 0.004426844; UBD: -0.048233709; GPR25: -0.135824303; CTSE: -0.152489252.

8. The method according to claim 7, characterized in that, The reagents for detecting biomarker expression levels include primer pairs for detecting biomarker gene expression levels and / or reagents for detecting the protein content encoded by biomarker genes.

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