A quantitative bladder cancer molecular typing method and device

Abstract

The present invention discloses a quantitative bladder cancer molecular typing method and device, the method comprising: obtaining gene expression data of bladder cancer patients; extracting the expression amount of Basal subtype-related genes and the expression amount of Luminal subtype-related genes according to the gene expression data; calculating the Basal-l umi na l score of the bladder cancer patient according to the expression amount of the Basal-l umi na l gene and the expression amount of the Luminal subtype-related gene; comparing the Basal-l umi na l score and the Basal-l umi na l score critical value to determine the molecular typing result of the bladder cancer patient. By adopting the present invention, a new quantitative index is formulated to comprehensively and accurately describe the molecular subtype characteristics of bladder cancer.

Description

Technical Field

[0001] The present invention relates to the field of quantitative bladder cancer molecular typing, and in particular to a bladder cancer molecular typing method and device. Background Art

[0002] Background introduction of bladder cancer and current status of research on molecular classification of bladder cancer: Bladder cancer is the 10th most common malignant tumor in the world and the most common malignant tumor in the urinary system. According to whether the tumor invades the bladder wall muscle layer, bladder cancer can be divided into non-muscle-invasive bladder cancer (NMIBC, 75%) and muscle-invasive bladder cancer (MIBC, 25%). There are obvious differences in the treatment methods and prognosis of NMIBC and MIBC patients. At present, there are many molecular classification methods for bladder cancer named by different centers, mainly including TCGA classification, Lund classification, UNC classification, MDA classification and EUA classification. These molecular classifications further reveal the occurrence and development of bladder cancer and the heterogeneity of bladder cancer. Although these molecular classifications have differences in the number of groups and subtype naming, there are certain associations and overlaps among various molecular classifications. According to the above molecular classifications, bladder cancer can be roughly divided into basal type (Basal) and luminal type (Luminal). The Basal subtype originates mainly from basal cells, which contain tumor stem cells, have squamous cell carcinoma-like differentiation or sarcoma-like differentiation, overexpression of EGFR and high invasiveness, and the patient's prognosis is worse; the Luminal subtype originates from urothelial cells, surrounded by basal cells, has FGFR3 gene activation mutations, and the tumor grows in a papillary manner, and the patient's prognosis is better. The results of these molecular typing can predict the patient's prognosis, but cannot fully reflect the molecular biological characteristics of bladder cancer and guide the individualized treatment of bladder cancer.

[0003] The current molecular classification of bladder cancer has the following shortcomings: (1) The current research on molecular classification of bladder cancer mainly focuses on muscle-invasive bladder cancer (MIBC), and lacks research on molecular subtypes of bladder cancer as a whole (NMIBC and MIBC). (2) Bladder cancer has the characteristics of dual centrality in space and time, that is, the bladder cancer tissue of the same patient may have multiple types of molecular subtypes, and the current molecular classification of bladder cancer is a qualitative result, which cannot quantitatively, accurately and completely describe the biological characteristics of bladder cancer. Summary of the invention

[0004] The embodiment of the present invention provides a quantitative bladder cancer molecular typing method and device, and formulates a new quantitative index to comprehensively and accurately describe the molecular subtype characteristics of bladder cancer.

[0005] The first aspect of the embodiment of the present application provides a quantitative bladder cancer molecular typing method, comprising:

[0006] Obtain gene expression data from bladder cancer patients;

[0007] Extracting the expression levels of Basal subtype-related genes and Luminal subtype-related genes according to the gene expression data;

[0008] Calculating the Basal-luminal score of the bladder cancer patient according to the expression levels of the Basal subtype-related genes and the expression levels of the Luminal subtype-related genes;

[0009] The Basal-luminal score and the Basal-luminal score cutoff value are compared to determine the molecular typing result of the bladder cancer patient.

[0010] In a possible implementation of the first aspect, calculating the Basal-luminal score of the bladder cancer patient according to the expression levels of the Basal subtype-related genes and the expression levels of the Luminal subtype-related genes specifically includes:

[0011] performing kernel density estimation on the gene expression data using a gene set variation analysis algorithm;

[0012] sorting the gene expression levels of the bladder cancer patients according to the kernel density estimation results;

[0013] Performing rank statistics on the Basal subtype-related genes and the Luminal subtype-related genes;

[0014] After using the rank statistic, the gene set variation analysis enrichment score is obtained to obtain the Basal score and Luminal score of the bladder cancer patient;

[0015] After Z-score correction is performed on the Basal score and the Luminal score, the Basal score is divided by the Luminal score to obtain the Basal-luminal score of the bladder cancer patient.

[0016] In a possible implementation of the first aspect, after calculating the Basal-luminal score of the bladder cancer patient according to the expression levels of the Basal subtype-related genes and the expression levels of the Luminal subtype-related genes, the method further includes:

[0017] Obtain prognostic information and gene expression data for bladder cancer patients;

[0018] According to the prognostic information and gene expression data of the bladder cancer patients, the Basal-luminal score critical value is determined by the "survminer" R language package.

[0019] In a possible implementation of the first aspect, comparing the Basal-luminal score and the Basal-luminal score cutoff value to determine the molecular typing result of the bladder cancer patient specifically includes:

[0020] If the Basal-luminal score is greater than or equal to the Basal-luminal score cutoff value, the molecular classification of the bladder cancer patient is a Basal-related subtype;

[0021] If the Basal-luminal score is less than the Basal-luminal score critical value, the molecular classification of the bladder cancer patient is a luminal-related subtype.

[0022] In a possible implementation manner of the first aspect, the Basal subtype-related genes include CK5 / 6 genes and CK14 genes; the Luminal subtype-related genes include GATA3 genes, Foxa1 genes and CK20 genes.

[0023] A second aspect of the embodiment of the present application provides a quantitative bladder cancer molecular typing device, comprising:

[0024] A data acquisition module, used to acquire gene expression data of bladder cancer patients;

[0025] An expression extraction module, used to extract the expression levels of Basal subtype-related genes and Luminal subtype-related genes according to the gene expression data;

[0026] A scoring module, used to calculate the Basal-luminal score of the bladder cancer patient according to the expression level of the Basal subtype-related gene and the expression level of the Luminal subtype-related gene;

[0027] The typing module is used to compare the Basal-luminal score and the Basal-luminal score critical value to determine the molecular typing result of the bladder cancer patient.

[0028] In a possible implementation of the second aspect, calculating the Basal-luminal score of the bladder cancer patient according to the expression levels of the Basal subtype-related genes and the expression levels of the Luminal subtype-related genes, specifically includes:

[0029] performing kernel density estimation on the gene expression data using a gene set variation analysis algorithm;

[0030] sorting the gene expression levels of the bladder cancer patients according to the kernel density estimation results;

[0031] Performing rank statistics on the Basal subtype-related genes and the Luminal subtype-related genes;

[0032] After using the rank statistic, the gene set variation analysis enrichment score is obtained to obtain the Basal score and Luminal score of the bladder cancer patient;

[0033] After Z-score correction is performed on the Basal score and the Luminal score, the Basal score is divided by the Luminal score to obtain the Basal-luminal score of the bladder cancer patient.

[0034] In a possible implementation manner of the second aspect, the method further includes a critical value calculation module, which is used to:

[0035] Obtain prognostic information and gene expression data for bladder cancer patients;

[0036] According to the prognostic information and gene expression data of the bladder cancer patients, the Basal-luminal score critical value is determined by the "survminer" R language package.

[0037] In a possible implementation of the second aspect, comparing the Basal-luminal score and the Basal-luminal score cutoff value to determine the molecular typing result of the bladder cancer patient specifically includes:

[0038] If the Basal-luminal score is greater than or equal to the Basal-luminal score cutoff value, the molecular classification of the bladder cancer patient is a Basal-related subtype;

[0039] If the Basal-luminal score is less than the Basal-luminal score critical value, the molecular classification of the bladder cancer patient is a luminal-related subtype.

[0040] In a possible implementation of the second aspect, the Basal subtype-related genes include CK5 / 6 genes and CK14 genes; the Luminal subtype-related genes include GATA3 genes, Foxa1 genes and CK20 genes.

[0041] Compared with the prior art, the embodiment of the present invention provides a quantitative bladder cancer molecular typing method and device, which collects gene sets related to Basal and Luminal in advance, performs gene set variation analysis (GSVA) ​​based on the transcriptomic data of these gene sets to calculate the Basal-luminal score critical value, and then calculates the new bladder cancer molecular subtype score (Basal-luminal score) in combination with the gene expression data of the specific patient. According to the size of the Basal-luminal score, the molecular biological characteristics of bladder cancer are confirmed, and the molecular typing tendency and tendency amount are judged.

[0042] In addition, the Basal-luminal score can be used to quantitatively and intuitively determine the patient's prognosis and the sensitivity of bladder cancer patients to drug treatment. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of a flow chart of a quantitative bladder cancer molecular typing method provided by one embodiment of the present invention;

[0044] Figure 2 This is a schematic diagram of the classic immunohistochemical staining results of Basal subtype and Luminal subtype provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Please refer to Figure 1 The embodiment of the present invention provides a quantitative bladder cancer molecular typing method, comprising:

[0047] S10. Obtain gene expression data of bladder cancer patients.

[0048] S11. Extracting the expression levels of Basal subtype-related genes and Luminal subtype-related genes based on the gene expression data.

[0049] S12. Calculate the Basal-luminal score of the bladder cancer patient according to the expression levels of the Basal subtype-related genes and the expression levels of the Luminal subtype-related genes.

[0050] S13. Compare the Basal-luminal score and the Basal-luminal score cutoff value to determine the molecular typing result of the bladder cancer patient.

[0051] In this embodiment, the construction process of the Basal-luminal score is as follows: through literature retrieval, a gene list related to the molecular subtype of bladder cancer was collected. The genes related to the luminal subtype include CYP2J2, ERBB2, ERBB3, FGFR3, FOXA1, GATA3, GPX2, KRT18, KRT19, KRT20, KRT7, KRT8, PPARG, XBP1, SNX31, UPK1A, UPA1B and UPK2; the genes related to the Basal subtype include CD44, CDH3, KRT1, KRT5, KRT14, KRT16, KRT17, KRT6A, KRT6B, KRT6C, IL36G, COL17A1, STAT3, EGFR, HIF1A, SERPINB3 and SERPINB4. Then, the Basal score and Luminal score of each patient were calculated using the genes related to the Basal subtype and Luminal subtype by Gene Set Variation Analysis (GSVA). The Basal score and Luminal score were then Z-score corrected. After that, the Basal score of each patient was divided by the Luminal score to finally obtain the Basal-luminal score of each patient.

[0052] Compared with the prior art, the embodiment of the present invention provides a quantitative bladder cancer molecular typing method, which collects gene sets related to Basal and Luminal in bladder cancer molecular typing in advance, performs gene set variation analysis (GSVA) ​​based on the transcriptomic data of these gene sets to calculate the Basal score and the Luminal score, and finally calculates a new bladder cancer molecular subtype score (Basal-luminal score). According to the size of the Basal-luminal score, the molecular biological characteristics of bladder cancer are confirmed, and the molecular typing tendency and tendency amount are judged.

[0053] From the perspective of immunohistochemistry, the relationship between the Basal-luminal score and the molecular classification of bladder cancer can be verified:

[0054] As a feasible example, fresh tumor tissue from bladder cancer patients was taken, dehydrated and paraffin-embedded. Each wax block was sliced ​​15 times in a row, each slice was about 4 μm thick, and placed in a constant temperature oven at 70°C for 15 minutes. After the slices were dewaxed, they were rinsed with PBS 3 times, 2 minutes each time. Then the slices were placed in an antigen repair box, soaked in 0.01 mol citrate buffer, and then placed in a microwave oven for continuous heating for 15 minutes, and cooled to room temperature. Rinse again with PBS 3 times, 2 minutes each time. Add 50 μl of peroxidase blocker to the slices, incubate at room temperature in the dark for 15 minutes, and then rinse the slices with PBS 3 times, 2 minutes each time. Remove the PBS solution on the slices, add goat serum to the slices for blocking, incubate at room temperature in the dark for 20 minutes, remove the excess serum on the slices, do not wash, and add 50 μl of various primary antibodies shown in Table 1 to the slices. After incubation at room temperature for 20 minutes, wash them with PBS 3 times, 3 minutes each time. Remove the PBS solution on the slices, add 50μl of the corresponding secondary antibody to the slices, incubate in a 37℃ incubator for 40min, and wash with PBS oscillation 4 times, 5min each time. Use the DAB colorimetric kit to develop the slices. For negative staining, use hematoxylin pathological staining solution to stain the slices for about 30 to 40s, then dehydrate and make the slices transparent. Finally, seal the slices with neutral gum and wait for the slices to dry at room temperature. Observe the staining of the slices under a microscope and take pictures. The production companies and dilution ratios of the antibodies required for immunohistochemistry are shown in Table 1.

[0055] Table 1 List of antibodies required for immunohistochemistry

[0056]

[0057] See also Figure 2 Analysis of immunohistochemical staining results showed that the expression levels of Basal subtype-related genes CK5 / 6 and CK14 were significantly increased in bladder cancer patients with high Basal-luminal score group, and significantly decreased in bladder cancer patients with low Basal-luminal score group; while the expression levels of Luminal subtype-related genes GATA3, Foxa1 and CK20 were significantly increased in bladder cancer patients with low Basal-luminal score group, and significantly decreased in bladder cancer patients with high Basal-luminal score group.

[0058] Exemplarily, the calculating the Basal-luminal score of the bladder cancer patient according to the expression level of the Basal subtype-related gene and the expression level of the Luminal subtype-related gene specifically includes:

[0059] The gene set variation analysis algorithm is used to perform kernel density estimation on the gene expression data.

[0060] The gene expression levels of the bladder cancer patients are ranked according to the kernel density estimation results.

[0061] Rank statistics were performed on the Basal subtype-related genes and the Luminal subtype-related genes.

[0062] After the rank statistic, the gene set variation analysis enrichment score was obtained, and the Basal score and Luminal score of the bladder cancer patient were obtained.

[0063] After Z-score correction is performed on the Basal score and the Luminal score, the Basal score is divided by the Luminal score to obtain the Basal-luminal score of the bladder cancer patient.

[0064] The reason why the Basal score is divided by the Luminal score to obtain the Basal-luminal score in this embodiment is because it is a high-risk prognostic indicator for bladder cancer patients, that is, the higher the Basal-luminal score, the worse the prognosis of bladder cancer patients. In general, clinical practice tends to construct a high-risk indicator in which the higher the score, the worse the prognosis of the patient. This is more in line with clinical thinking, more conducive to raising the vigilance of clinical physicians, and conducting more rigorous follow-up and treatment of high-risk patients. If the Luminal score is divided by the Basal score, the Luminal-basal score obtained is a favorable prognostic factor for bladder cancer patients, that is, the higher the Luminal-basal score, the better the prognosis of bladder cancer patients, and the lower the Luminal-basal score, the worse the prognosis of bladder cancer patients. Such a result is not good for raising the vigilance of clinical physicians.

[0065] Exemplarily, after calculating the Basal-luminal score of the bladder cancer patient according to the expression level of the Basal subtype-related gene and the expression level of the Luminal subtype-related gene, the method further includes:

[0066] Obtain prognostic information and gene expression data for bladder cancer patients;

[0067] According to the prognostic information and gene expression data of the bladder cancer patients, the Basal-luminal score critical value is determined by the "survminer" R language package.

[0068] This example uses R software (version 3.6.1, https: / / www.r-project.org / ) and SPSS software (version 23) for statistics. This study determines the molecular subtypes of bladder cancer patients based on the gene expression data of bladder cancer patients. The "BLCAsubtyping" R language package (https: / / github.com / cit-bioinfo / BLCAsubtyping) was used to determine the results of the six molecular subtypes of TCGA, Lund, UNC, MDA, CIT and Baylor of bladder cancer patients; the "consensusMIBC" R language package (https: / / github.com / cit-bioinfo / consensusMIBC) was used to determine the results of the EUA molecular subtypes of bladder cancer patients. Through the above method, the results of a total of 7 molecular subtypes for each bladder cancer patient were determined, and the correlation between Basal-luminalscore and these 7 molecular subtypes was verified.

[0069] The prognostic value of the Basal-luminal score was comprehensively evaluated by Kaplan-Meier analysis (log-rank test), univariate and multivariate Cox analysis, and meta-analysis. For each acquired database, the critical value of the Basal-luminal score was determined by the "survminer" R language package, and bladder cancer patients were divided into high Basal-luminal group and low Basal-luminal group for Kaplan-Meier analysis (log-rank test). Based on the hazard ratio (HR) of the univariate cox analysis of the Basal-luminal score for each database and the 95% confidence interval (CI) of the HR, the meta-analysis method was further used to comprehensively evaluate the prognostic value of the Basal-luminal score. The I2 statistic and the χ2-based Q test were used to explore the heterogeneity of the meta-analysis. If I 2 If the heterogeneity was less than 25% and the P value of the Q test was greater than 0.05, the meta-analysis was considered to have low heterogeneity and a fixed-effects model was used for meta-analysis; otherwise, a random-effects model was used for meta-analysis.

[0070] It should be noted that the public databases used in this embodiment include: The Cancer Genome Atlas (TCGA, https: / / portal.gdc.cancer.gov) constructed by the National Cancer Institute of the United States contains multi-omics data of various human tumors, which are open to all tumor researchers for free download. Download clinical information, prognostic information and RNA sequencing data (FPKM value) of bladder cancer patients from the TCGA database (https: / / portal.gdc.cancer.gov), and finally the database has 405 bladder cancer patients included in the embodiment of the present invention as samples for analysis. The Gene Expression Omnibus (GEO, https: / / www.ncbi.nlm.nih.gov / geo / ) stores high-throughput gene expression data of various diseases, which is open to researchers for download and use. Download databases containing prognostic information and gene expression data of bladder cancer patients from the database, including GSE13507, GSE31684, GSE32894, GSE48057 and GSE48277. This example also incorporates the data of the IMvigor210 cohort for subsequent research.

[0071] RNA sequencing was used to process the database data: RNA was extracted from tumor tissues of bladder cancer patients using the Trizol method. KAPA RNA HyperPrep Kit and RiboErase (HMR) were used. The extracted RNA was used to construct strand-specific RNA sequencing libraries using the Agilent Bioanalyzer 2100 system (Agilent, USA). The final library was sequenced on the Illumina NovaSeq 6000 platform at the GloriousMed Clinical Laboratory (Shanghai, China).

[0072] Exemplarily, comparing the Basal-luminal score and the Basal-luminal score cutoff value to determine the molecular typing result of the bladder cancer patient specifically includes:

[0073] If the Basal-luminal score is greater than or equal to the Basal-luminal score cutoff value, the molecular classification of the bladder cancer patient is a Basal-related subtype;

[0074] If the Basal-luminal score is less than the Basal-luminal score critical value, the molecular classification of the bladder cancer patient is a luminal-related subtype.

[0075] Exemplarily, the Basal subtype-related genes include CK5 / 6 genes and CK14 genes; the Luminal subtype-related genes include GATA3 genes, Foxa1 genes and CK20 genes.

[0076] Specifically, based on the largest public pharmacogenomics database, the Genomics of Drug Sensitivity in Cancer database (GDSC, https: / / www.cancerrxgene.org / ), the IC50 of four chemotherapy drugs (gemcitabine, docetaxel, paclitaxel and cisplatin) for each bladder cancer patient in TCGA was predicted. These four drugs are commonly used chemotherapy drugs for bladder cancer. The prediction process is implemented by the "pRRophetic" R language package, and the IC50 is predicted based on the ridge regression of the R language package.

[0077] According to the size of the Basal-luminal score, the prognosis of patients and the sensitivity of bladder cancer patients to drug treatment can be quantitatively and intuitively judged. The higher the Basal-luminal score, the more sensitive bladder cancer patients are to gemcitabine, docetaxel, paclitaxel and cisplatin; the higher the Basal-luminal score, the worse the prognosis of bladder cancer patients.

[0078] An embodiment of the present application provides a quantitative bladder cancer molecular typing device, including a data acquisition module, an expression measurement module, a scoring module and a typing module.

[0079] The data acquisition module is used to acquire gene expression data of bladder cancer patients.

[0080] The expression extraction module is used to extract the expression levels of Basal subtype-related genes and Luminal subtype-related genes according to the gene expression data.

[0081] A scoring module is used to calculate the Basal-luminal score of the bladder cancer patient according to the expression level of the Basal subtype-related gene and the expression level of the Luminal subtype-related gene.

[0082] The typing module is used to compare the Basal-luminal score and the Basal-luminal score critical value to determine the molecular typing result of the bladder cancer patient.

[0083] Exemplarily, the Basal-luminal score of the bladder cancer patient is calculated according to the expression level of the Basal subtype-related gene and the expression level of the Luminal subtype-related gene, specifically comprising:

[0084] performing kernel density estimation on the gene expression data using a gene set variation analysis algorithm;

[0085] sorting the gene expression levels of the bladder cancer patients according to the kernel density estimation results;

[0086] Performing rank statistics on the Basal subtype-related genes and the Luminal subtype-related genes;

[0087] After using the rank statistic, the gene set variation analysis enrichment score is obtained to obtain the Basal score and Luminal score of the bladder cancer patient;

[0088] After Z-score correction is performed on the Basal score and the Luminal score, the Basal score is divided by the Luminal score to obtain the Basal-luminal score of the bladder cancer patient.

[0089] Exemplarily, a critical value calculation module is also included, which is used to:

[0090] Obtain prognostic information and gene expression data for bladder cancer patients;

[0091] According to the prognostic information and gene expression data of the bladder cancer patients, the Basal-luminal score critical value is determined by the "survminer" R language package.

[0092] Exemplarily, comparing the Basal-luminal score and the Basal-luminal score cutoff value to determine the molecular typing result of the bladder cancer patient specifically includes:

[0093] If the Basal-luminal score is greater than or equal to the Basal-luminal score cutoff value, the molecular classification of the bladder cancer patient is a Basal-related subtype;

[0094] If the Basal-luminal score is less than the Basal-luminal score critical value, the molecular classification of the bladder cancer patient is a luminal-related subtype.

[0095] Exemplarily, the Basal subtype-related genes include CK5 / 6 genes and CK14 genes; the Luminal subtype-related genes include GATA3 genes, Foxa1 genes and CK20 genes.

[0096] Compared with the prior art, the embodiment of the present invention provides a quantitative bladder cancer molecular typing device, which pre-collects gene sets related to the Basal and Luminal subtypes in the molecular typing of bladder cancer, performs gene set variation analysis (GSVA) ​​based on the transcriptomic data of these gene sets to calculate the Basal-luminal score critical value, and then calculates the score and Luminal score in combination with the gene expression data of the specific patient, and finally calculates the new bladder cancer molecular subtype score (Basal-luminal score), confirms the molecular biological characteristics of bladder cancer according to the size of the Basal-luminal score, and judges the molecular typing tendency and tendency amount.

[0097] In addition, the Basal-luminal score can be used to quantitatively and intuitively determine the patient's prognosis and the sensitivity of bladder cancer patients to drug treatment.

[0098] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be described again here.

[0099] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A quantitative bladder cancer molecular typing method, characterized in that: include: Obtain gene expression data from bladder cancer patients; Extracting the expression levels of Basal subtype-related genes and Luminal subtype-related genes according to the gene expression data; The Basal-luminal score of the bladder cancer patient is calculated according to the expression levels of the Basal subtype-related genes and the expression levels of the Luminal subtype-related genes, specifically comprising: performing kernel density estimation on the gene expression data using a gene set variation analysis algorithm; ranking the gene expression levels of the bladder cancer patients according to the kernel density estimation results; performing rank statistics on the Basal subtype-related genes and the Luminal subtype-related genes; after the rank statistics, obtaining the gene set variation analysis enrichment score to obtain the Basal score and Luminal score of the bladder cancer patient; after performing Z-score correction on the Basal score and the Luminal score, dividing the Basal score by the Luminal score to obtain the Basal-luminal score of the bladder cancer patient; The Basal-luminal score and the Basal-luminal score cutoff value are compared to determine the molecular typing result of the bladder cancer patient.

2. The quantitative bladder cancer molecular typing method according to claim 1, characterized in that: After calculating the Basal-luminal score of the bladder cancer patient according to the expression levels of the Basal subtype-related genes and the expression levels of the Luminal subtype-related genes, the method further includes: Obtain prognostic information and gene expression data for bladder cancer patients; According to the prognostic information and gene expression data of the bladder cancer patients, the Basal-luminal score critical value is determined by the "survminer" R language package.

3. The quantitative molecular typing method for bladder cancer according to claim 1, characterized in that: Comparing the Basal-luminal score and the Basal-luminal score cutoff value to determine the molecular typing result of the bladder cancer patient specifically includes: If the Basal-luminal score is greater than or equal to the Basal-luminal score cutoff value, the molecular classification of the bladder cancer patient is a Basal-related subtype; If the Basal-luminal score is less than the Basal-luminal score critical value, the molecular classification of the bladder cancer patient is a luminal-related subtype.

4. The quantitative molecular typing method for bladder cancer according to claim 1, characterized in that: The Basal subtype-related genes include CK5 / 6 gene and CK14 gene; the Luminal subtype-related genes include GATA3 gene, Foxa1 gene and CK20 gene.

5. A quantitative bladder cancer molecular typing device, characterized in that: include: A data acquisition module, used to acquire gene expression data of bladder cancer patients; An expression extraction module, used to extract the expression levels of Basal subtype-related genes and Luminal subtype-related genes according to the gene expression data; A scoring module, for calculating the Basal-luminal score of the bladder cancer patient according to the expression levels of the Basal subtype-related genes and the expression levels of the Luminal subtype-related genes, specifically comprising: performing kernel density estimation on the gene expression data using a gene set variation analysis algorithm; ranking the gene expression levels of the bladder cancer patients according to the kernel density estimation results; performing rank statistics on the Basal subtype-related genes and the Luminal subtype-related genes; after the rank statistics, obtaining the gene set variation analysis enrichment score to obtain the Basal score and Luminal score of the bladder cancer patient; after performing Z-score correction on the Basal score and the Luminal score, dividing the Basal score by the Luminal score to obtain the Basal-luminal score of the bladder cancer patient; The typing module is used to compare the Basal-luminal score and the Basal-luminal score critical value to determine the molecular typing result of the bladder cancer patient.

6. The quantitative bladder cancer molecular typing device according to claim 5, characterized in that: Also included is a critical value calculation module for: Obtain prognostic information and gene expression data for bladder cancer patients; According to the prognostic information and gene expression data of the bladder cancer patients, the Basal-luminal score critical value is determined by the "survminer" R language package.

7. The quantitative bladder cancer molecular typing device according to claim 5, characterized in that: Comparing the Basal-luminal score and the Basal-luminal score cutoff value to determine the molecular typing result of the bladder cancer patient specifically includes: If the Basal-luminal score is greater than or equal to the Basal-luminal score cutoff value, the molecular classification of the bladder cancer patient is a Basal-related subtype; If the Basal-luminal score is less than the Basal-luminal score critical value, the molecular classification of the bladder cancer patient is a luminal-related subtype.

8. The quantitative bladder cancer molecular typing device according to claim 5, characterized in that: The Basal subtype-related genes include CK5 / 6 gene and CK14 gene; the Luminal subtype-related genes include GATA3 gene, Foxa1 gene and CK20 gene.

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