Application of bladder cancer stem cell detection kit in screening and identifying bladder cancer stem cells

Abstract

The invention provides application of a bladder cancer stem cell detection kit in screening and identifying bladder cancer stem cells. The kit comprises cell membrane protein GPNMB. The method for screening the cell membrane protein GPNMB comprises the following steps: re-clustering tumor cells of bladder cancer tissue single cell sequencing data EPCAM < + > to obtain a plurality of cell populations. The quasi-timing sequence analysis studies the distribution condition of each group of cells on a quasi-timing sequence time axis, and analyzes the sequence of transformation and succession of each cell group. 10 BCSC molecular markers or key functional genes in bladder cancer research at present are taken, and the expression level and proportion of the 10 genes in the single cell analysis cell population are analyzed one by one. Through differential gene screening and characteristic surface protein analysis, cell membrane protein GPNMB is screened as a tumor stem cell specific surface marker of the group of cells. The technical problems that tumor stem cell surface markers in bladder cancer are deficient and are difficult to recognize and screen are solved.

Description

Technical Field

[0001] This invention relates to the field of tumor molecular biology, specifically to the field of biomarkers for screening and identifying bladder cancer stem cells, and particularly to the application of a bladder cancer stem cell detection kit in the screening and identification of bladder cancer stem cells. Background Technology

[0002] Bladder cancer (BC) is one of the most common malignant tumors worldwide. Cisplatin-based chemotherapy combined with gemcitabine (GC) is the standard treatment for MIBC and metastatic bladder cancer. Approximately 60% of patients show significant initial response to GC chemotherapy; however, this efficacy is difficult to sustain, with most cases recurring and developing resistance, resulting in a very poor prognosis. Recently, immunotherapy strategies, represented by immune checkpoint inhibitors (ICIs), have received widespread attention. However, the response rate of ICIs in metastatic bladder cancer is less than 30%, and retrospective cohort studies have shown that patients receiving immunotherapy alone have significantly lower survival rates compared to those receiving chemotherapy. Recent views suggest that ICIs combined with GC chemotherapy may be the future trend in MIBC and metastatic bladder cancer, but currently, GC remains the first-line chemotherapy drug. Therefore, reversing tumor resistance and inhibiting recurrence remain crucial issues that urgently need to be addressed in the clinical treatment of bladder cancer.

[0003] In recent years, increasing evidence suggests the presence of a population of difficult-to-eradicate cancer stem cells (CSCs) within tumor tissues. These cells possess high self-renewal and tumorigenic capabilities, and are key factors contributing to tumor initiation, high heterogeneity, treatment resistance, and relapse. For example, in the clinical treatment of acute myeloid leukemia (AML), relapse is common after achieving complete remission with chemotherapy; studies have found this to be caused by surviving CD34+ cancer stem cells after chemotherapy. A high proportion of CD34+CD38- cancer stem cells in AML patients is significantly associated with residual cell count and poor prognosis after treatment. In solid tumors, residual breast cancer tissue after endocrine therapy (letrozole) or chemotherapy (docetaxel) is specifically enriched with CD44+CD24-CSCs compared to pre-treatment samples. Similarly, CD133 expression is significantly increased in tumor tissues of rectal cancer patients after radiotherapy and chemotherapy, and patients with an upregulated proportion of CD133+ cells show significantly reduced histopathological tumor regression rate, disease-free survival, and overall survival. In bladder cancer, bladder cancer stem cells (BCSCs) are also closely associated with chemotherapy resistance. Studies have shown that CK14+ CSCs are significantly enriched in the tumor tissue of chemotherapy-resistant patients, and patients with CK14+ CSC enrichment have significantly reduced survival rates. A recent study found that the flavonoid derivative wyc0209 can reverse chemotherapy resistance in bladder urothelial carcinoma by targeting CD133+ CSCs. These studies indicate that BCSCs play a crucial role in tumor treatment resistance and recurrence, and may be the root cause of clinical treatment failure and recurrence in tumors, showing significant potential for application in the treatment of chemotherapy-resistant bladder cancer. Nevertheless, the specific molecular markers, origins, and plasticity of BCSCs remain inconclusive.

[0004] In bladder cancer, the bladder cancer cell line (BCSC) exhibits high heterogeneity and plasticity. Existing CSC surface markers, such as CD44, CK5, CK14, CD133, CD24, and CD47, cannot specifically characterize BCSCs, making it difficult to uncover key molecular features of BCSCs. In fact, for various tumors, including bladder cancer, further analysis and screening of CSC-specific surface markers is a prerequisite and key to exploring key CSC signaling pathways and developing precise targeting strategies. Summary of the Invention

[0005] 1. The technical problem to be solved: It provides biomarkers for bladder cancer stem cell screening, solving the technical problem of insufficient surface biomarkers for tumor stem cells in bladder cancer, making them difficult to identify and screen.

[0006] 2. Technical Solution: To address the above problems, this invention provides a bladder cancer stem cell detection kit for screening and identifying bladder cancer stem cells. The kit includes a novel biomarker for bladder cancer stem cells – the cell membrane protein GPNMB.

[0007] The method for screening the cell membrane protein GPNMB includes the following steps: Step S01: Re-cluster the tumor cells in the EPCAM+ single-cell sequencing data of bladder cancer tissue to obtain multiple cell populations.

[0008] Step S02: Pseudo-temporal analysis studies the distribution of each cell population on the pseudo-temporal time axis and analyzes the sequence of transformation and succession of each cell population.

[0009] Step S03: Select 10 BCSC molecular markers or key functional genes currently used in bladder cancer research, and analyze the expression level and proportion of these 10 genes in the cell population analyzed in the single cell above.

[0010] Step S04: Through differential gene screening and characteristic surface protein analysis, the cell membrane protein GPNMB was selected as a tumor stem cell-specific surface marker for this group of cells.

[0011] In step S01, the single-cell sequencing data of the bladder cancer tissue is obtained from the GEO database.

[0012] In step S01, the specific method for re-clustering is as follows: Step S11: Perform quality control, standardization, and normalization on the original gene expression matrix to eliminate technical noise and sequencing depth differences.

[0013] Step S12: Using the linear dimensionality reduction method of principal component analysis, extract the principal components that best represent the variation of the data from the high-dimensional space of tens of thousands of genes.

[0014] Step S13: Apply Louvain or Leiden clustering algorithms to cluster cells. By finding marker genes that are significantly highly expressed in each cell cluster and comparing them with known cell type-specific gene databases, manually annotate the biological identity of each cluster.

[0015] By re-clustering, 16 cell populations were obtained, such as Figure 1 As shown in Figure A.

[0016] In step S02, the pseudo-time series analysis involves inferring the differentiation trajectory or evolutionary process of cell subtypes during development based on the changes in gene expression levels of different cell subpopulations over time. The specific method is as follows: Step S21: Dimensionality reduction of the gene expression data screened by cell clustering.

[0017] Step S22: Starting with more immature cell types, combine the dimensionality reduction plot with pseudo-temporal information to draw a cell trajectory plot.

[0018] The more immature cell type is a stem cell or progenitor cell.

[0019] In step S03, the 10 BCSC molecular markers or key functional genes are: CD44, KRT14, KRT5, ALDH1A1, SOX2, OCT4, NANOG, TP63, THY1 and ITGA6.

[0020] 3. Beneficial effects: This invention utilizes a single-cell sequencing system for tumor tissue to accurately describe the molecular characteristics and differentiation state of tumor cells. It screens the transmembrane glycoprotein GPNMB, identifying its potential as a clinical biomarker for bladder cancer cell screening. Subsequent in vitro and in vivo experiments demonstrated the important function of GPNMB in identifying and screening bladder cancer cells. This invention provides a novel method for the identification and screening of clinical bladder cancer cells and offers a new therapeutic target for targeted therapy of bladder cancer, demonstrating promising clinical application prospects. Attached Figure Description

[0021] Figure 1 Yes: Single-cell transcriptome sequencing analysis of bladder cancer tissue revealed a type of GPNMB. + Stem cell-like bladder cancer initiating cell population. Figure 1 A is a t-SNE visualization of EPCAM in bladder cancer tissue. + Distribution of cells in different cell populations within a cell population; Figure 1 B is a pseudo-temporal analysis of the distribution of each cell population on the pseudo-temporal time axis, which analyzes the order of transformation and succession of each cell population; Figure 1 C is the evolutionary tree analysis of the evolutionary trajectory of each group of cells; Figure 1 D is an analysis of the expression levels and proportions of 10 widely studied BCSC molecular markers or key functional genes, including CD44, KRT14, KRT5, ALDH1A1, SOX2, OCT4, NANOG, TP63, THY1, and ITGA6, in various cell populations. Figure 1 E is a heatmap of 20 marker genes that are characteristically highly expressed in each cell population; Figure 1 F represents the expression abundance of GPNMB in each cell population.

[0022] Figure 2 Yes: GPNMB + Isolation of bladder cancer cells and functional identification of CSCs. Figure 2 A represents the use of dual-color immunofluorescence to detect the co-expression of GPNMB with CD44, SOX2, and OCT4 in bladder cancer tissue. Figure 2 B represents GPNMB in cells enriched with EPCAM magnetic beads via flow cytometry. + Tumor cell population; Figure 2 C is the RT-qPCR detection of GPNMB. + and GPNMB - Levels of CD44, SOX2, and OCT4 mRNA in bladder cancer cells; Figure 2 D is the Western blotting detection of GPNMB. + and GPNMB - Levels of CD44, SOX2, and OCT4 proteins in bladder cancer cells; Figure 2 E is a cell colony formation assay used to detect GPNMB. + and GPNMB - The clonal formation ability of bladder cancer cells; Figure 2 F is the cell spheroidization assay for GPNMB. + and GPNMB - The ability of bladder cancer cells to form spheroids; Figure 2 GH is used in limiting dilution tumorigenicity assays to evaluate GPNMB. + and GPNMB - In vivo tumorigenicity of bladder cancer cells. G: Images of tumors in each group; H: Bar chart of tumor weight analysis; Figure 2 I is GPNMB in cells enriched with EPCAM magnetic beads by flow cytometry. + CD44 + Tumor cell populations; Figure 2 J and K are bar charts used in the cell colony formation assay and cell spheroidization assay to assess the colony formation and cell spheroidization abilities of different groups of cells. J: Bar chart for cell colony formation assay; K: Bar chart for cell spheroidization assay. * P <0.05;** P <0.01; *** P <0.001. Detailed Implementation

[0023] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0024] This invention provides an application of a bladder cancer stem cell detection kit in the screening and identification of bladder cancer stem cells. The kit includes a novel biomarker for bladder cancer stem cells – the cell membrane protein GPNMB.

[0025] The method for screening the cell membrane protein GPNMB includes the following steps: Step S01: Re-cluster the tumor cells in the EPCAM+ single-cell sequencing data of bladder cancer tissue to obtain multiple cell populations.

[0026] In one embodiment, the single-cell sequencing data of the bladder cancer tissue is derived from the GEO database.

[0027] In one embodiment, 16 cell populations are obtained.

[0028] Step S02: A pseudo-time series analysis was conducted to study the distribution of each cell population along the pseudo-time series axis, analyzing the sequence of transformation and succession for each cell population. In three cell populations, most cells clustered at the differentiation initiation site, suggesting stem cell or progenitor cell characteristics, such as... Figure 1 As shown in B. Phylogenetic analysis also confirmed the above results, as shown in Figure B. Figure 1 As shown in C.

[0029] Step S03: To further confirm the stem cell characteristics of these cell groups, 10 BCSC molecular markers or key functional genes currently used in bladder cancer research were selected, and the expression levels and proportions of these 10 genes in the above single-cell analysis cell groups were analyzed one by one.

[0030] In one embodiment, the 10 BCSC molecular markers or key functional genes are: CD44, KRT14, KRT5, ALDH1A1, SOX2, OCT4, NANOG, TP63, THY1, and ITGA6.

[0031] In step S02, most of the three cell populations highly expressed BCSC-related functional genes such as CD44, ALDH1A1, SOX2, and OCT4, but did not overlap with cell populations containing CD44+ and KRT14+, suggesting that they may be a novel group of stem cell-like bladder cancer cells. Figure 1 D).

[0032] Step S04: Through differential gene screening and characteristic surface protein analysis, the transmembrane glycoprotein GPNMB was found to be specifically elevated in the above cell population, and the cell membrane protein GPNMB was selected as a tumor stem cell-specific surface marker for this cell population.

[0033] Immunofluorescence staining of bladder cancer tissue revealed that GPNMB in bladder cancer cells does indeed show a co-expression trend with BCSC-related genes such as CD44, SOX2, and OCT4. Figure 2 As shown in Figure A. GPNMB+ and GPNMB- bladder cancer cells were isolated from clinical bladder cancer tissue for further analysis, as follows... Figure 2 As shown in B.

[0034] Western blot and RT-qPCR experiments demonstrated that GPNMB+ bladder cancer cells significantly overexpressed CD44, SOX2, and OCT4. Figure 2As shown in CD. Cell spheroidization and colony formation assays also confirmed that GPNMB+ bladder cancer cells had significantly higher spheroidization and colony formation abilities than GPNMB- bladder cancer cells, such as... Figure 2 As shown in EF.

[0035] In mice, limiting dilution tumorigenesis assays demonstrated that GPNMB+ bladder cancer cells possessed stronger tumorigenicity, such as... Figure 2 As shown in GH, the above results indicate that GPNMB+ bladder cancer cells exhibit significant tumor stem cell characteristics. Since CD44 is currently widely used for screening BCSCs and various other tumor CSCs, the majority of the screened GPNMB+ bladder cancer cell population also highly expresses CD44.

[0036] To analyze the compositional relationship between GPNMB+ and CD44+ bladder cancer cells and to compare the stem cell function of GPNMB+CD44+ bladder cancer cells with other cell types, GPNMB+CD44+, GPNMB-CD44+, GPNMB+CD44-, and GPNMB-CD44- bladder cancer cells were further sorted from bladder cancer tissue. Figure 2 As shown in Figure I. Cell function experiments revealed the clonogenic ability of GPNMB+CD44+ bladder cancer cells, such as... Figure 2 J shows the cell's ability to form spheres, such as Figure 2 As shown in K, it was significantly higher than that of GPNMB-CD44+ bladder cancer cells, and compared with GPNMB-CD44- bladder cancer cells, GPNMB+CD44- bladder cancer cells showed higher stemness-related functions, such as... Figure 2 As shown in JK. These results indicate that GPNMB+ bladder cancer cells represent a novel BCSC population, and GPNMB is a more precise BCSC screening marker.

[0037] In one embodiment, the present invention analyzes EPCAM from single-cell sequencing data of bladder cancer tissue in the GEO database. + The epithelial cell communities were re-clustered for analysis. The specific method was as follows: First, the original gene expression matrix was quality-controlled, standardized, and normalized to eliminate technical noise and sequencing depth differences. Then, linear dimensionality reduction methods such as principal component analysis (PCA) were used to extract the principal components most representative of data variation from the high-dimensional space of tens of thousands of genes. Louvain or Leiden clustering algorithms were applied for cell clustering. By identifying significantly overexpressed marker genes in each cell cluster and comparing them with known cell type-specific gene databases, the biological identity of each cluster was manually annotated.

[0038] In one embodiment, in step S02, pseudo-time series analysis is used to infer the differentiation trajectory of cells or the evolution process of cell subtypes during development by analyzing the changes in gene expression levels of different cell subpopulations over time.

[0039] This invention uses the Monocle algorithm to first reduce the dimensionality of gene expression data selected by cell clustering in order to capture the developmental relationships between cells in a low-dimensional space. Then, starting with more immature cell types, such as stem cells or progenitor cells, the dimensionality reduction map is combined with pseudo-temporal information to draw a cell trajectory map, thereby intuitively observing the developmental path and relationships of cells.

[0040] GPNMB in tumor tissue of bladder cancer patients + Sorting of bladder cancer cells: Clinical tumor tissue specimens from bladder cancer patients were collected according to standard procedures. Fresh tissue was temporarily stored in tissue preservation solution and transported on ice to the laboratory cell laminar flow hood. First, impurities such as fat and mucous membrane on the surface of the bladder cancer tissue were removed, and the tissue was cut into 1mm pieces. 3 After washing with PBS, the tissue fragments were placed in DMEM cell culture medium (containing 2 mg / ml type I collagenase, 250 U / ml hyaluronidase, and DNase) and digested at 37°C for 1-2 h until the fragments were completely dissolved. A single-cell suspension was obtained by filtration through a 70 µm cell sieve. Cells were washed with DMEM medium and centrifuged at 400g for 10 min to obtain cell pellet. Cells were blocked with 1% BSA for 30 min. EPCAM was first enriched using magnetic beads coated with EPCAM antibody. + Tumor cells were incubated with PE-labeled GPNMB antibody for 30 min, and EPCAM cells were sorted by flow cytometry. + GPNMB + Cells and EPCAM + GPNMB - Cells and their purity were identified.

[0041] GPNMB + In vitro cell function identification of bladder cancer cells: Collected and cultured the EPCAM cells obtained above. + GPNMB + and EPCAM + GPNMB -Bladder cancer cells were first analyzed using Western blotting and RT-qPCR to detect the expression levels of stem cell-related molecules such as CD44, SOX2, and OCT4. Then, a cell spheroidization assay was performed to assess the difference in in vitro spheroidization ability between the two cell types. Specifically, both cell types were collected and plated in 24-well ultra-low adhesion plates (1250 cells per well). The culture medium was serum-free DMEM / F12 containing 2% B27, 1% N2, 20 ng / ml EGF, and 10 ng / ml bFGF. The cells were cultured in a cell culture incubator for approximately 7 days. Once the spheroids reached a suitable size, the number of spheroids with a diameter greater than 75 µm was observed and counted under a microscope. The clonogenic ability of cells was analyzed by a cell clonogenic assay. The specific method was as follows: cells were collected and plated into 12-well plates with 50 cells per well. DMEM medium containing 10% FBS was used to culture the cells for 5-8 days until the cell colonies were of suitable size. The culture medium was then discarded, the cells were fixed, stained with crystal violet, and the number of cell clones with more than 50 cells was observed and counted under a microscope.

[0042] GPNMB + In vivo tumorigenicity analysis of bladder cancer cells: EPCAM cells were collected using the methods described above. + GPNMB + and EPCAM + GPNMB - Bladder cancer cells were evaluated in nude mouse subcutaneous xenograft and orthotopic bladder cancer models using limiting dilution. + and GPNMB - In vivo tumorigenicity of bladder cancer cells. Subcutaneous xenograft model in nude mice: A suitable number of 6-8 week old male nude mice were purchased from the Institute of Model Animals, Nanjing University. GPNMB + Groups and GPNMB - Each group was set up with three cell number gradients (1×10⁻⁶). 4 5 x 10 pieces / each 3 Each / each and 1×10 3 Cell suspension containing fixed cells was mixed with matrix gel at a 1:1 ratio and injected into the axilla of nude mice (100 µl / mouse). Five mice were used per group for each cell number gradient. Tumor growth was monitored weekly. One month after tumor implantation, mice were euthanized, and tumors were collected. Tumor size and weight were compared among groups and cell number gradients. Mouse orthotopic bladder cancer model: A suitable number of 6-8 week old female nude mice were purchased from the Model Animal Institute of Nanjing University. GPNMB + Groups and GPNMB - Each group was set up with three cell number gradients (5×10). 3 Individual / piece, 1×10 3(20 µl / mouse and 500 cells / mouse) After anesthetizing the mice, the lower abdomen was opened, and a fixed number of cells (20 µl / mouse) were implanted into the bladder wall. The suture was then closed, and the mice were fed normally. Fifty days after tumor implantation, the mice were euthanized, and bladder tissue was collected to analyze the tumor size and weight of each group at each cell number gradient. The above methods for constructing mouse tumor-bearing models have been mastered.

[0043] GPNMB + / CD44 + Comparative analysis of bladder cancer cells: Since CD44 is currently widely used for screening BCSCs and various other tumor CSCs, and our screening of GPNMB... + Most bladder cancer cell populations also highly express CD44, which is important for analyzing GPNMB. + Bladder cancer cells and CD44 + We used the above-mentioned bladder cancer cell sorting method to sort GPNMB cells, comparing the compositional relationships of bladder cancer cells and the stem function of each group. + CD44 + Bladder cancer cells, GPNMB - CD44 + Bladder cancer cells, GPNMB + CD44 - Bladder cancer cells and GPNMB - CD44 - The difference in the specific methods for bladder cancer cells lies in the following: after obtaining the cell pellet, the cells are blocked with 1% BSA for 30 min, and then EPCAM is first enriched using magnetic beads coated with EPCAM antibody. + Tumor cells were selected and then incubated with APC-labeled CD44 antibody and PE-labeled GPNMB antibody before flow cytometry sorting. The proportion of cells in each group was analyzed. To compare the functional differences among the cell groups, cell spheroidization and colony formation assays were performed on the sorted cells to assess cell function in vitro, following the same method. The in vivo tumorigenic function of each cell group was assessed in nude mouse subcutaneous xenograft tumor and orthotopic bladder cancer models using limiting dilution.

Claims

1. The application of a bladder cancer stem cell detection kit in the screening and identification of bladder cancer stem cells, characterized in that: The kit includes a novel biomarker for bladder cancer stem cells – the cell membrane protein GPNMB.

2. The application as described in claim 1, characterized in that: The method for screening the cell membrane protein GPNMB includes the following steps: Step S01: Re-cluster the tumor cells in the EPCAM+ single-cell sequencing data of bladder cancer tissue to obtain multiple cell populations; Step S02: Pseudo-temporal analysis is used to study the distribution of each cell population on the pseudo-temporal time axis and to analyze the sequence of transformation and succession of each cell population. Step S03: Select 10 BCSC molecular markers or key functional genes currently used in bladder cancer research, and analyze the expression level and proportion of these 10 genes in the cell population analyzed in the single cell above. Step S04: Through differential gene screening and characteristic surface protein analysis, the cell membrane protein GPNMB was selected as a tumor stem cell-specific surface marker for this group of cells.

3. The application as described in claim 2, characterized in that: In step S01, the single-cell sequencing data of the bladder cancer tissue is obtained from the GEO database.

4. The application as described in claim 2, characterized in that: In step S01, the specific method for re-clustering is as follows: Step S11: Perform quality control, standardization, and normalization on the original gene expression matrix to eliminate technical noise and sequencing depth differences; Step S12: Using the linear dimensionality reduction method of principal component analysis, extract the principal components that best represent the variation of the data from the high-dimensional space of tens of thousands of genes; Step S13: Apply Louvain or Leiden clustering algorithms to cluster cells. By finding marker genes that are significantly highly expressed in each cell cluster and comparing them with known cell type-specific gene databases, manually annotate the biological identity of each cluster.

5. The application as described in claim 4: characterized in that: By re-clustering, 16 cell populations were obtained.

6. The application as described in claim 1, characterized in that: In step S02, the pseudo-time series analysis involves inferring the differentiation trajectory or evolutionary process of cell subtypes during development based on the changes in gene expression levels of different cell subpopulations over time. The specific method is as follows: Step S21: Dimensionality reduction of gene expression data selected by cell clustering; Step S22: Starting with more immature cell types, combine the dimensionality reduction plot with pseudo-temporal information to draw a cell trajectory plot.

7. The application as described in claim 6, characterized in that: The more immature cell type is a stem cell or progenitor cell.

8. The application as described in claim 2, characterized in that: In step S03, the 10 BCSC molecular markers or key functional genes are: CD44, KRT14, KRT5, ALDH1A1, SOX2, OCT4, NANOG, TP63, THY1 and ITGA6.

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