A predictive biomarker of human colorectal cancer metastasis related to hypoxic microenvironment tbc1d8 and application thereof

Abstract

This invention discloses the application of TBC1D8, a member of the TBC1 domain family, in the preparation of predictive biomarkers for prognosis and immunotherapy responsiveness in human colorectal cancer patients. This invention evaluated the correlation between TBC1D8 levels and clinical characteristics and its biological functions using next-generation sequencing results from the TCGA database and in vitro and in vivo experiments. The results showed that elevated TBC1D8 levels were associated with poor prognosis in colorectal cancer patients. Experimental studies also observed that TBC1D8 is associated with a hypoxic microenvironment and may participate in regulating the malignant phenotype of colorectal cancer cells and tumor cell stemness. Furthermore, TBC1D8 is closely related to the infiltration of immunosuppressive macrophages; experiments showed that knocking down TBC1D8 significantly inhibited the differentiation and infiltration of immunosuppressive macrophages. Therefore, TBC1D8 can serve as a prognostic biomarker for colorectal cancer patients and may also be a novel therapeutic target for human colorectal cancer.

Description

Technical Field

[0001] This invention relates to a member of the TBC1 domain family, specifically TBC1D8, a predictive biomarker for the prognosis of human colorectal cancer, and belongs to the field of biomedical technology. Background Technology

[0002] Colorectal cancer (CRC) is a tumor of the gastrointestinal system, ranking third in incidence among malignant tumors and second in cancer mortality. Its pathogenesis appears to involve multiple factors and steps, including genetics, diet, and lifestyle. Statistics show that this tumor frequently recurs and metastasizes, particularly spreading to the liver, lungs, bones, ovaries, and peritoneum; the five-year survival rate for these patients is approximately 10%. Treatment methods for CRC include chemotherapy, surgery, radiotherapy, and molecular targeted therapy. Molecular targeted therapy for CRC has become a hot topic. The number of molecularly stratified treatment regimens is increasing, as is the use of biomarkers to guide prediction and treatment decisions. Therefore, identifying novel biomarkers and targets for treating CRC is essential for improving disease prognosis.

[0003] The TBC (Tre-2 / Bub2 / Cdc16, TBC) domain is a conserved amino acid sequence composed of domains from the tumor gene Tre-2 and the yeast cell cycle regulator genes Bub2 and Cdc16. Members of the TBC domain family exhibit strong conservation and high homology. The TBC domain is often linked in tandem with other domains related to cell membrane function, indicating that the biological functions of TBC domain proteins are closely related to the cell membrane and may mediate the occurrence and development of cancer or other diseases. In fact, some of these proteins have been found to be associated with tumor development. High levels of TBC1D7 have been observed in some lung cancers and are associated with poor patient prognosis. RNAi interference with TBC1D7 in lung cancer cells inhibited cell growth; conversely, overexpression of TBC1D7 promoted lung cancer cell proliferation and tumor formation in mice. TBC1D16 also appears to be a driver gene for melanoma; its overexpression can promote cell growth and gene expression, affect vesicle transport, and further influence melanoma development. Studies have shown that TBC1D8 is significantly upregulated in aggressive ovarian cancer cells, driving ovarian cancer development and metabolic reprogramming. However, research on its role in CRC is scarce. This study aims to fill this gap. Summary of the Invention

[0004] Objective of the Invention: The technical problem to be solved by this invention is to overcome the low accuracy of existing biomarkers for predicting the prognosis of colorectal cancer patients and their insufficient ability to predict metastasis in colorectal cancer patients. Through in-depth research on TBC1D8, this invention, through screening of a large amount of transcriptome data and clinical specimens and experimental verification, demonstrates that TBC1D8 can serve as a predictive biomarker for human colorectal cancer metastasis, or as a component of a kit for predicting or screening human colorectal cancer or its metastasis.

[0005] Technical solution: To achieve the above objectives, the technical solution adopted by this invention is as follows:

[0006] A predictive biomarker for human colorectal cancer or human colorectal cancer metastasis, characterized in that it belongs to the cytochrome C oxidase family Gene Cards Gene Symbol: COX4I2.

[0007] A predictive biomarker for immunotherapy responsiveness in human colorectal cancer, characterized in that it belongs to the TBC1 domain family member Gene Cards Gene Symbol:TBC1D8.

[0008] A kit for predicting the prognosis of human colorectal cancer or assessing the prognosis of immunotherapy, comprising the TBC1D8 protein.

[0009] The amino acid sequence of the TBC1D8 protein described in this invention is as follows:

[0010]

[0011] Beneficial effects:

[0012] This invention, through extensive experimental screening and in-depth research on the TBC1D8 protein, addresses the limited research on the relationship between the TBC domain and tumors to date. In this study, the invention identified the oncogeneic role of TBC1 domain family member 8 (TBC1D8) in colorectal cancer (CRC) using the Least Absolute Contraction and Selection Operator (LASSO) and Cox regression analysis, demonstrating that TBC1D8 may independently predict CRC outcomes. Functional enrichment and single-cell analysis showed that TBC1D8 levels are associated with hypoxia. Experiments also confirmed that knocking down TBC1D8 significantly suppressed the malignant phenotype of colorectal cancer cells, weakened cell stemness-related indicators, and showed a positive correlation between TBC1D8 levels and M2 macrophage infiltration. Co-culture experiments confirmed that a co-culture model established after TBC1D8 knockdown and macrophages also showed that low TBC1D8 expression significantly inhibited the infiltration of immunosuppressive M2 macrophages. In summary, these results indicate that the TBC1D8 gene is involved in the development of colorectal cancer, and its potential molecular mechanisms may include hypoxia-related and immunosuppressive cell infiltration. Therefore, the TBC1D8 protein can serve as a prognostic biomarker for rectal cancer or as a screening marker for immunotherapy, and it also has significant application value as a therapeutic target. Attached Figure Description

[0013] Figure 1 TBC1D8 expression, as an indicator of overall survival and progression-free interval, was determined using the Minimal Absolute Contraction and Selection Operator (LASSO) and Cox regression analysis in the Cancer Genome Atlas (TCGA) cohort. (A) Based on the LASSO-Cox model of TCGA-color adenocarcinoma (COAD), the hyperparameter λ was obtained through 10 cross-validations using the minimum standard, with the optimal λ producing two non-zero coefficients (n=480). (B) Cross-validation of selected tuning parameters. (CF) Univariate (C and E) and multivariate (D and F) Cox regression analyses were performed on overall survival (C and D) and disease-free survival (E and F) to understand the relationship between TBC1D8 and TBC1D17 levels and clinicopathological parameters related to CRC prognosis in TCGA-COAD (n=480). (GH) Overall survival (OS) (G), disease-specific survival (DSS) (H), and progression-free interval (PFI) based on median TBC1D8 levels in TCGA-COAD (n=480).

[0014] Figure 2 The level of TBC1D8 in colorectal cancer (CRC) and its relationship with clinicopathological parameters.

[0015] (A) TBC1D8 expression levels between CRC tissues and paired adjacent normal tissues in TCGA-COAD. Wilcoxon test performed (n=41). (BC) Differences in TBC1D8 gene expression between CRC cases and normal controls in GSE10950 (n=48) (B) and GSE37182 (n=172) (C). Wilcoxon test performed. (DF) Correlation between TBC1D8 mRNA levels in CRC patients based on TCGA-COAD and (D), T phase (n=477) (E), N phase (n=478) (F), and M phase (n=411). (GI) Diagnostic operating characteristic (ROC) curves based on TBC1D8 and carcinoembryonic antigen (CEA) levels [H, TCGA (n=521); I, GSe10950 (n=48); j, GSE37182 (n=172)]. (J) Immunohistochemical (IHC) analysis of TBC1D8 in CRC tissues based on Human Protein Atlas (HPA) (magnification, ×2, scale bar = 500 μm). (KM)TBC1D8 expression in different CRC cell lines was analyzed using (K) Cancer Cell Line Encyclopedia (CCLE) and (L, M) Western blot. One-way ANOVA was performed. Data in the bar charts are the mean (SME) of three independent experiments. *P < 0.05. (N) IHC staining quantification of TBC1D8 (n = 30) based on samples from this invention, showing differential expression between adjacent normal and colorectal cancer tissues. t-tests were performed (magnification ×200, scale bar = 50 μm; magnification ×400, scale bar = 20 μm).

[0016] (NS: not significant, *P<0.05, **P<0.01, ***P<0.001, ***P<0.0001).

[0017] Figure 3 Protein-protein interaction (PPI) network and enrichment analysis.

[0018] (A) Based on the GENEMANIA database, TBC1D8 exhibits physical interactions, co-expression, co-localization, predicted common pathways, genetic interactions, and common protein domains with neighboring genes. Each node represents a gene. Node size represents the intensity of the interaction, and line color represents the type of interaction. (B) Volcano plot of differentially expressed genes (DEGs) induced by TBC1D8 level changes. Yellow dots indicate upregulation; blue dots indicate downregulation; the x-axis represents expression difference (log2-fold change); the y-axis represents the significance of the difference (log10padj). (C) Cell atlas visualization of the network of TBC1D8 and significantly related genes. Darker colors and larger sizes indicate higher levels of detail. (D) The highest-scoring central module analyzed by Molecular Complex Detection (MCODE). Darker colors and larger sizes indicate higher levels of detail. (E) The "Cluster Analyzer" R package was used. Gene Ontology (GO)_biology_process (BP) enrichment analysis was performed based on this module. (FG) TBC1D8 gene set enrichment analysis (GSEA). (F) Enriched gene set in KEGG and Reactome collections of samples with high TBC1D8 expression. (G) Enriched gene set in GO collections of samples with high TBC1D8 expression. Only genomes with normal P < 0.05 and false discovery rate (FDR) < 0.1 are considered significant and are shown in the figure (x-axis represents the distribution of log fold change (logFC) corresponding to the core molecule in each genome).

[0019] Figure 4 We investigated the differentially enriched gene set related to TBC1D8 expression using the Gene Set Variation Analysis (GSVA) ​​algorithm based on the TCGA and Gene Expression Synthesis (GEO) datasets.

[0020] (A, B) Heatmaps showing hierarchical clustering of enrichment scores obtained through Gene Set Variation Analysis (GSVA) ​​based on dataset enrichment profiles. A: TCGA; B: GSE37182. (C, D) Volcano plots of differentially enriched gene sets in CRC patients with different TBC1D8 expression in the (TCGA) and (GSE37182) datasets, analyzed by GSVA using the "limma" R package (C: TCGA, n=480; D: GSE37182, n=84). Blue nodes indicate downregulation, and red nodes indicate upregulation. (E, F) Relationship between TBC1D8 and hypoxia-related genes based on TCGA (n=480) (E) and GSE37182 (n=84) (F). Yellow indicates a positive relationship, and blue indicates a negative relationship; darker colors indicate stronger correlations. (*P<0.05, **P<0.01)

[0021] Figure 5TBC1D8 single-cell analysis based on the Tumor Immune Single Cell Central (TISCH) database.

[0022] (A) Functional relevance of TBC1D8 in CRC patients. (BK)(B, G) Cellular components based on (B)GS139555 and (G)GS146771. (C, H) Uniform manifold approximation and projection (UMAP) plots showing the expression of TBC1D8 clusters based on (C)GSE139555 and (H)GSE146771. (D, I) Enrichment fractions of genes from the Hallmark hypoxia gene set in single cells based on gene set variation analysis based on (D)GSE139555 and (I)GSE146771.

[0023] (E, J) show the UMAP plots of the CRC cell landscape. Different cell types were subjected to quality control, dimensionality reduction, and clustering based on (E)GS139555 and (H)GS146771. (F, K)Violin plots of CRC cell cluster marker genes and TBC1D8 in different cell types were constructed based on (F)GSE139555 and (K)GSE146771.

[0024] Figure 6 TBC1D8 can be induced by hypoxia, thereby promoting tumor proliferation and enhancing tumor stemness.

[0025] (A) Schematic model of the potential role of TBC1D8 in CRC. (BC) Effect of cobalt chloride-induced hypoxia on TBCD18 expression. (DE) Transfection efficiency (%) as shown by green fluorescent protein (GFP) expression and western blotting (magnification, ×400, scale bar = 20 μm). (F) Colony-forming ability of CRC cells transfected with NC and sh-TBC1D8 constructs, as shown by colony formation assay (magnification, ×1, scale bar = 1000 μm). (G) Schematic diagram of subcutaneous tumor model. (H) Xenograft mouse tumors (n = 6 mice per group). (I) Xenograft tumor volume measured twice weekly and xenograft tumor weight at the end of the study. (J) IHC staining of Ki-67 protein in mouse xenograft tumor tissue (magnification, ×100, scale bar = 100 μm; magnification ×200, scale bar = 20 μm). All IHC scores were performed in a double-blind, triple-repeat manner. Statistical analysis was conducted with all experiments repeated at least three times independently. (K) Cell spheroidization assay (magnification, ×100, scale bar = 100 μm). (L) Measurement of the number and size of cell spheroids. All experiments were repeated independently at least three times. (M) Relative expression of SOX2 under hypoxic conditions was detected by Western blot (n = 3 replicates). (N) Relative expression levels of SOX2 in CRC cells transfected with NC and sh-TBCID8 were detected by Western blot analysis (n = 3 replicates). All data were obtained using SEM. *p < 0.05 **p < 0.01 ***p < 0.001. One-way ANOVA was used. All experiments were repeated independently at least three times.

[0026] Figure 7 The effects of TBC1D8 on immune infiltration and immunotherapy.

[0027] (A) Effect of TBC1D8 expression on immunosuppressive macrophages. (B) Relationship between TBC1D8 levels and the degree of immune infiltration, from TIMER. (C, D) Relationship between TBC1D8 and (C) M2 macrophage markers and (D) M1 macrophage marker levels. (E) Proportion of tumor-initiating cells in CRC samples. From CIBERSORT-based GSE10950 and GSE37182 data. (F) Relationship between TBC1D8 levels and macrophage abundance based on CIBERSORT (from GSE10950 and GSE37182 data). (G) Diagram of co-culture system. (H) Double immunofluorescence staining of M2 macrophage markers CD206 (red) and CD163 (green); cell nuclei stained with DAPI (blue) (magnification, ×400, scale bar = 20 μm) (n = 3 replicates). (I) Immunofluorescence intensity (mean SEM) (n = 3 replicates). All data are SEM*p<0.05**p<0.01***p<0.001. Detailed Implementation

[0028] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. After reading the present invention, any modifications of the present invention in various equivalent forms by those skilled in the art will fall within the scope defined by the appended claims.

[0029] Example 1: Determining the prognostic value of TBC domain family members

[0030] This invention selected 44 members of the TBC domain family for LASSO regression to identify target genes for subsequent studies. Cross-validation was performed in ten rounds to prevent overfitting. Figure 1 A and B). Ordinal Cox regression (univariate and multivariate) showed that TBC1D8 was significantly associated with CRC prognosis, and it was identified as the research target. Figure 1 Finally, Kaplan-Meier survival curves showed that patients with higher TBC1D8 levels had shorter overall survival (OS) and progression-free survival (PFI) (P<0.05). Figure 1 These results indicate that TBC1D8 is closely related to the progress of CRC and has potential research value.

[0031] Example 2: Expression Analysis of TBC1D8

[0032] This invention found no significant association between TBC1D8 levels and TNM stage. Figure 2 DF). Recipient operating characteristic curve (ROC) measures the ability of TBC1D8 to distinguish CRC from normal tissue, with carcinoembryonic antigen (CEA) used as a positive reference. Figure 2The GI plot shows the area below the curve. The Human Protein Atlas (HPA) shows that TBC1D8 is primarily cytoplasmic or membrane-associated (CPA). Figure 2 J). Figure 2 K shows the results from the CCLE database, with cellular TBC1D8 transcriptome expression levels arranged in descending order (HT-29, HCT 116, LoVo, SW620, RKO, and SW480). Figure 2 Western blotting, as shown by L and M, yielded consistent results. Subsequently, IHC demonstrated TBC1D8 overexpression in CRC tissues compared to healthy tissues. This invention used our own CRC samples to detect TBC1D8 protein expression. The mean H scores for TBC1D8 in CRC and adjacent normal tissues were 104.17 ± 5.79 and 52.58 ± 3.54, respectively. Figure 2 The results strongly suggest that imbalanced TCB1D8 gene expression can lead to CRC.

[0033] Example 3: Predicting the Functions and Interactions of TBC1D8

[0034] This invention uses GeneMANIA to construct a network connecting genes adjacent to TBC1D8. This reveals various relationships, including interactions, co-locations, and common pathways. Figure 3 A). Genes co-expressed with TBC1D8 in TCGA-COAD were examined using R"limma". Figure 3 B). A total of 521 differentially expressed genes (DEGs) were used in the assembly of the protein-protein interaction network (PPI). Within this network, SOX2, as the hub gene based on cytoHubba, scored the highest. Figure 3 C). Enrichment analysis based on SOX2 as a core subnetwork suggests that this network may be involved in "regulation of peptidase activity", "cell-to-cell adhesion via serous membrane adhesion molecules", "humoral immune responses", "maintenance of the gastrointestinal epithelium", "digestive system processes", and "regulation of the transmembrane receptor protein serine / threonine kinase signaling pathway". Figure 3 D and E). GSEA of the entire PPI showed that TBC1D8 may be associated with hypoxia, angiogenesis, and matrix degradation. Figure 3 (F and G). These findings provide evidence for the relationship between TBC1D8 and cancer-related signaling pathways. This prompted further investigation into the molecular mechanisms of this invention.

[0035] Example 4: Genomic Variation Analysis (GSVA) ​​Based on TBC1D8 Expression

[0036] The above results indicate that TBC1D8 may be closely related to the hypoxia phenotype. Therefore, this invention performed GSVA based on marker genomes to further analyze the potential involvement of TBC1D8 in cancer-related pathways. Figure 4 AB shows the GSVA score distribution of CRC samples in TCGA and GSE37182. Differential score analysis based on the median TBC1D8 level shows that "HYPOXIA" was active in the high TBC1D8 group in both cohorts (P<0.05). Figure 4 CD). The relationship between TBC1D8 and hypoxia-related genes was also examined. Figure 4 This further suggests that TBC1D8 plays an important role in adapting to hypoxia.

[0037] Example 4: Single-cell level analysis of TBC1D8

[0038] This invention aims to further explore the association between TBC1D8 and hypoxia using single-cell datasets. The CancerSEA database revealed a positive correlation between TBC1D8 levels and hypoxia (R = 0.31, P < 0.05). Figure 5 A). The tumor microenvironment (TME) is composed of cancer-associated fibroblasts, myofibroblasts, immune cells, and other components. To further investigate the relationship between TBC1D8 expression distribution and hypoxia, this invention explored the CRC single-cell datasets GSE139555 and GSE146771. Figure 5 B and G represent the cellular components of these two datasets, respectively. This invention observed that cells expressing TBC1D8 were enriched in hypoxia-related genes. Figure 5 CD, 5H-I), and found that TBC1D8 was expressed in both immune and stromal cell single-cell subsets (CD, 5H-I), and found that TBC1D8 was expressed in both immune and stromal cell single-cell subsets. Figure 5 EF, 5J-K).

[0039] Example 5: TBC1D8 can be induced by hypoxia to promote tumor proliferation and tumor stem formation.

[0040] Enrichment and single-cell analyses suggest that TBC1D8 may be associated with hypoxia. Given that its core gene is SOX2, which is involved in the development and maintenance of cancer cell stemness, this invention proposes that TBC1D8 may also be related to tumor cell stemness. Figure 6 A possible mechanism was proposed in A. Based on the above results, preliminary experimental verification was conducted in this invention. To simulate the hypoxic microenvironment conditions of tumors, this invention induced a hypoxic environment using CoCl2. The results showed that with the extension of CoCl2 treatment time, the expression of TBC1D8 gradually increased ( Figure 6High levels of TBC1D8 were observed in HCT116 and HT-29 cells, so these cells were used for further investigation. Transfection efficiency was confirmed by GFP intensity and Western blotting. Figure 6 DE). Silencing TBC1D8 reduces clone formation ( Figure 6 F). A schematic diagram of the subcutaneous tumor model is shown below. Figure 6 G. Furthermore, TBC1D8 knockout inhibited the growth of xenograft tumors in vivo ( Figure 6 IHC staining of xenograft tumors showed that, with the knockout of TBC1D8, the expression of Ki-67 on the cell membrane was significantly decreased. Figure 6 J). It is documented that tumor spheroid formation is related to the stemness of cancer cells. Quantification of tumor spheroids showed that after TBC1D8 knockout, the number of tumor spheroids in CRC cells ( Figure 6 K) and size ( Figure 6 L) were significantly reduced. Compared with normoxic conditions, the expression level of SOX2 was significantly increased after exposure to hypoxia ( Figure 6 M). After TBC1D8 knockout, the expression level of SOX2 was significantly downregulated ( Figure 6 This result indicates that TBC1D8 plays an important role in connecting hypoxic and CRC cells to stem cell characteristics.

[0041] Example 6: The effect of TBC1D8 expression on the immune microenvironment

[0042] In this section, the invention explores the relationship between immune infiltration and the pathogenesis of CRC. The relationship between TBC1D8 and infiltration was examined using the EPIC algorithm. This indicates that when TBC1D8 is strongly expressed, the levels of macrophages, neutrophils, CD8 T cells, and T helper cells are higher. Figure 7 A). TIMER has also been used to explore the potential correlation between TBC1D8 levels and immune cell infiltration. Figure 7B). The levels of TBC1D8 and CD8+ T cells (R = 0.345, P = 9.13e-13), CD4+ T cells (R = 0.215, P = 1.32e-05), macrophages (R = 0.233, P = 2.24e-06), neutrophils (R = 0.394, P = 2.21e-16), dendritic cells (R = 0.353, P = 2.94e-13), and B cells (R = 0.153, P = 2.04e-03) were analyzed. This invention further analyzed the relationship between TBC1D8 and macrophage polarization based on TCGA-COAD. TBC1D8 showed similarities to MS4A4A (R = 0.210, P < 0.001), VSIG4 (R = 0.210, P < 0.001), MRC1 (R = 0.270, P < 0.001), CD163 (R = 0.320, P < 0.001), MSR1 (R = 0.220, P < 0.001), IRF5 (R = 0.120, P = 0.010), and PTGS2 (R = 0.250, P < 0.001), but was not associated with NOS2 (P = 0.580). Figure 7 Finally, this invention further utilized GSE10950 and GSE37182 to find that CRC patients with high TBC1D8 expression had a higher degree of M2 macrophage infiltration (CD). Figure 7 This series of results indicates a positive correlation between TBC1D8 expression and M2 macrophage infiltration. To further investigate the effect of TBC1D8 expression on M2 macrophage abundance in CRC, this invention established a tumor-macrophage co-culture model using a Transwell non-contact co-culture unit (EF). Figure 7 G). This invention observed that TBC1D8 knockout significantly downregulated the surface markers (CD206 and CD163) of M2 tumor-associated macrophages (TAMs) in THP-1 macrophages. Figure 7 (HI). The results of this invention indicate that TBC1D8 can exert an immunosuppressive function by promoting the proliferation of M2 macrophages.

[0043] The above experimental results show that TBC1D8, as an oncogene, is closely related to hypoxia and can promote the malignant phenotype of colorectal cancer cells and promote the progression of CRC. Therefore, TBC1D8 protein can be used as a biomarker for predicting the prognosis of rectal cancer or for screening for immunotherapy, and it can also be used as a therapeutic target.

[0044] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. Application of TBC1D8 protein in the preparation of predictive biomarkers for the prognosis of human colorectal cancer patients.

2. Application of TBC1D8 protein in the preparation of a kit for predicting the prognosis of human colorectal cancer.

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