Ul16 binding protein 2 as a marker for colorectal cancer

Abstract

This invention relates to the field of biomedical technology, specifically to the application of UL16-binding protein 2 (ULBP2) as a biomarker for colorectal cancer (CRC). Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of ULBP2 expression. The results showed that ULBP2 was significantly highly expressed in CRC tissues, and the high expression level was significantly associated with a shortened overall survival (OS), demonstrating its good diagnostic and prognostic value. Functional experiments showed that knockdown of the ULBP2 gene significantly reduced the survival and proliferation of HCT-8 and LoVo cells, and effectively inhibited tumor cell migration, indicating that ULBP2 inhibitors have good application prospects in the development of colorectal cancer therapeutics. This invention provides a new biomarker and therapeutic target for the diagnosis, prognosis, and treatment of colorectal cancer.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, and in particular to UL16 binding protein 2 as a biomarker for colorectal cancer. Background Technology

[0002] Colorectal cancer (CRC) is one of the most common malignant tumors of the digestive tract worldwide, with its incidence and mortality rates continuing to rise in recent years, posing a serious threat to human health. Despite significant advancements in surgery, radiotherapy, chemotherapy, targeted therapy, and immunotherapy, many patients are diagnosed at an advanced stage due to atypical early symptoms, resulting in a generally unsatisfactory prognosis. Therefore, there is an urgent need to identify highly sensitive and specific biomarkers to aid in the early diagnosis, prognostic assessment, and monitoring of treatment efficacy for colorectal cancer.

[0003] UL16-binding protein 2 (ULBP2) is a non-classical MHC class I related molecule and a ligand for the NKG2D receptor. It is primarily expressed on the surface of virus-infected cells and tumor cells under stress. Recent studies have found that ULBP2 is highly expressed in various tumor tissues and is closely related to the tumor immune microenvironment, tumor cell immune escape, and patient prognosis. Although the function of ULBP2 as an NKG2D ligand in tumor immunity is gradually being recognized, its expression characteristics and clinical application value in colorectal cancer have not yet been fully studied and utilized.

[0004] Therefore, there is an urgent need to provide a detection and application scheme for colorectal cancer biomarkers based on ULBP2, in order to build more sensitive and specific diagnostic tools and personalized treatment evaluation systems, thereby improving the early detection rate and treatment outcomes for patients. Summary of the Invention

[0005] The purpose of this invention is to provide the application of UL16-binding protein 2 as a biomarker for colorectal cancer, thereby addressing the problems mentioned in the background art. The specific technical solution is as follows:

[0006] The first objective of this invention is to provide an application of a tumor marker in the preparation of colorectal cancer diagnostic products or prognostic products, wherein the tumor marker is UL16-binding protein 2, and the gene sequence of ULBP2 is shown in SEQ ID NO.1:

[0007] (SEQ ID NO.1).

[0008] The second objective of this invention is to provide the application of an inhibitor of UL16-binding protein 2 in the preparation of a drug for treating colorectal cancer.

[0009] Preferably, the inhibitor comprises siRNA that binds to UL16-binding protein 2.

[0010] Preferably, the siRNA of UL16 binding protein 2 is either ULBP2siRNA-89 or ULBP2siRNA-139;

[0011] The sequence of the ULBP2 siRNA-89 is: CACTCTCTTTGCTATGACA (SEQ ID NO.2);

[0012] The sequence of the ULBP2 siRNA-139 is: ACGGTGGTGTGCGGTTCAA (SEQ ID NO.3).

[0013] A third objective of this invention is to provide a reagent for detecting the expression level of UL16-binding protein 2 as an application in the preparation of a reagent for predicting the efficacy of colorectal cancer treatment.

[0014] Preferably, the reagent for detecting the expression level of UL16-binding protein 2 includes primers ULBP2F and ULBP2R; wherein,

[0015] The sequence of ULBP2-F is: GCCGCTACCAAGATCCTTCT (SEQ ID NO.7);

[0016] The sequence of ULBP2-R is: TCATCCACCTGGCCTTGAAC (SEQ ID NO.8).

[0017] Beneficial effects:

[0018] This invention evaluated the diagnostic performance of ULBP2 using receiver operating characteristic (ROC) curve analysis, showing that UL16-binding protein 2 (ULBP2) has significant diagnostic value in colorectal cancer (CRC). Clinical sample analysis indicated that ULBP2 expression levels were significantly elevated in CRC patients, and high expression was significantly associated with decreased overall survival (OS), suggesting good prognostic potential. In functional experiments, ULBP2 gene siRNA knockdown significantly inhibited the proliferation and survival of HCT-8 and LoVo colorectal cancer cells, suggesting its crucial role in tumor cell maintenance. Furthermore, ULBP2 inhibition also significantly reduced tumor cell migration, indicating that UL16-binding protein 2 inhibitors have significant application prospects in anti-tumor drug development. Therefore, ULBP2 can not only serve as a diagnostic and prognostic biomarker for colorectal cancer but also as a therapeutic target for developing therapeutic drugs that intervene in its expression or function, possessing broad clinical application value. Attached Figure Description

[0019] Figure 1 This is a volcano plot showing the differential expression of the ULBP2 gene in the TCGA CRC dataset, GSE9348 dataset, GSE23878 dataset, GSE41328 dataset, and GSE41657 dataset in Example 1. Figure 1 A corresponds to the TCGA CRC dataset. Figure 1 B corresponds to the GSE9348 dataset. Figure 1 C corresponds to the GSE23878 dataset. Figure 1 D corresponds to the GSE41328 dataset. Figure 1 E corresponds to the GSE41657 dataset;

[0020] Figure 2 The Venn diagram was generated using the results of differential expression analysis and regression analysis in Example 1;

[0021] Figure 3 This is a box image of the ULBP2 expression analysis performed on normal tissue samples and tumor samples from the TCGA CRC dataset and four GEO datasets in Example 1.

[0022] Figure 4 This is a paired image of normal tissue samples and tumor samples in the TCGA CRC dataset in Example 1;

[0023] Figure 5 The graph shown in Example 2 is a graph illustrating the relationship between ULBP2 expression and gender, age, weight, and body mass index (BMI) output by the R package software. Figure 5 A is a diagram showing the relationship between gender and sex. Figure 5 B is a graph showing the relationship between age and other factors. Figure 5 C is a graph showing the relationship between C and body weight. Figure 5 D is a graph showing the relationship between body mass index (BMI);

[0024] Figure 6 This is a graph showing the relationship between ULBP2 expression and different pathological stages, output by the R package software in Example 2.

[0025] Figure 7 The ROC curves of ULBP2 in the TCGA CRC, GSE9348, GSE23878, GSE41328 and GSE41657 datasets in Example 2;

[0026] Figure 8 The graph shows the overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) of the ULBP2 high expression group and low expression group in Example 3.

[0027] Figure 9 This is a univariate Cox regression analysis plot of the TCGA CRC dataset and ULBP2 expression in Example 3;

[0028] Figure 10 This is a multivariate Cox regression analysis plot of the TCGA CRC dataset and ULBP2 expression in Example 3;

[0029] Figure 11 The statistical graph for the survival regression analysis of the GSE17536 and GSE29621 datasets using the log-rank test in Example 3;

[0030] Figure 12 Box plot of ULBP2 gene promoter methylation levels in tumor and normal tissue samples from the TCGA CRC dataset in Example 4;

[0031] Figure 13 Box plots showing the methylation levels of the ULBP2 gene promoter after grouping the COAD and READ datasets according to AJCC stages in Example 4;

[0032] Figure 14 Box plots showing the methylation levels of the ULBP2 gene promoter after grouping the COAD and READ datasets by regional lymph node metastasis in Example 4;

[0033] Figure 15 This is a bar chart showing the ULBP2 mRNA expression rate in NCM-460, HCT-8, and LoVo cells in Example 5.

[0034] Figure 16 This is a bar chart showing the expression rate of ULBP2 mRNA in HCT-8 and LoVo cells after transfection with ULBP2-specific small interfering RNA in Example 5.

[0035] Figure 17 This is a line graph showing the absorbance of HCT-8 and LoVo cells after transfection in Example 5;

[0036] Figure 18 Optical microscope image of HCT-8 cells in Example 6;

[0037] Figure 19 Optical microscope image of LoVo cells in Example 6;

[0038] Figure 20 The percentage of wound closure for HCT-8 cells and LoVo cells at different culture times in Example 6;

[0039] Figure 21 Immunohistochemical staining images of colorectal cancer tissue specimens and normal tissue samples in Example 7;

[0040] Figure 22 Immunohistochemical staining images of colorectal cancer tissue specimens at different AJCC stages in Example 7. Specific Implementation

[0041] The application of UL16-binding protein 2 as a biomarker for colorectal cancer, as proposed in this invention, will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of this invention will become clearer from the following description. It should be noted that the drawings are all in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of this invention.

[0042] Example 1

[0043] Obtain the relevant dataset:

[0044] Data from the Colorectal Adenocarcinoma (COAD) and Rectal Adenocarcinoma (READ) projects were downloaded from TCGA (https: / / portal.gdc.cancer.gov / ), forming a CRC dataset containing 51 normal samples and 647 tumor samples. TCGA datasets for other common digestive system tumors, including hepatocellular carcinoma (LIHC), esophageal carcinoma (ESCA), pancreatic adenocarcinoma (PAAD), and gastric adenocarcinoma (STAD), were also downloaded from the TCGA database. The CRC dataset and the TCGA dataset together constitute the TCGA dataset. The CRC dataset was also used. Additionally, four GEO datasets containing both normal and tumor samples were downloaded from the GEO database (www.ncbi.nlm.nih.gov / geo): GSE9348 (12 normal samples and 70 tumor samples), GSE23878 (24 normal samples and 35 tumor samples), GSE41328 (5 normal samples and 5 tumor samples), and GSE41657 (12 normal samples and 76 tumor samples); as well as two datasets containing prognostic information: GSE17536 (177 tumor samples) and GSE29621 (65 tumor samples).

[0045] Differential gene screening:

[0046] Differential expression analysis was performed on the TCGA CRC dataset using the R package "DESeq2" software. The results are as follows: Figure 1 As shown in Figure A, there are 7157 upregulated genes in the TCGA CRC dataset;

[0047] Differential expression analysis was performed on four GEO datasets (GSE9348, GSE23878, GSE41328, and GSE41657) using the R package "limma". Differentially expressed genes were selected based on the following criteria: the logarithm of the gene expression change (base 2 logarithmic transformation) was greater than 1.5, and the adjusted p-value (after multiple hypothesis testing) was less than 0.05. The results are as follows: Figure 1 B to Figure 1E. The results showed that there were 722 in GSE9348, 198 in GSE23878, 212 in GSE41328, and 327 in GSE41657.

[0048] Survival regression analysis was performed on the TCGA CRC dataset using the R package "survival" software. Cox regression was applied for statistical analysis, with overall survival (OS) as the primary outcome. Relevant indicators were selected based on the following criteria: hazard ratio (HR) greater than 1 and the probability value (P value) obtained from the statistical test less than 0.05. The survival regression analysis results showed that 959 genes met the criteria of HR > 1 and p < 0.05.

[0049] Using the differential expression analysis and regression analysis results described above, Venn diagrams were generated to show overlapping genes in six analyses: the TCGA CRC dataset analysis, the four GEO dataset analyses, and the overall survival analysis. Figure 2 As shown, only ULBP2 completely overlaps;

[0050] ULBP2 expression analysis was performed on normal tissue samples and tumor samples from the TCGA CRC dataset and four GEO datasets. The results are as follows: Figure 3 As shown in the above dataset, the expression of ULBP2 in tumor samples was significantly higher than that in normal tissue samples. Further paired analysis of normal tissue samples and tumor samples in the TCGA CRC dataset yielded the following results: Figure 4 As shown, ULBP2 expression in tumor samples was significantly higher than in paired normal tissue samples.

[0051] Example 2

[0052] This embodiment analyzes the correlation between ULBP2 expression and clinicopathological features.

[0053] The associations between ULBP2 expression and clinical factors, including age, sex, weight, body mass index (BMI), and pathological stage, were analyzed using the R packages "stats" and "car". The results are as follows: Figure 5-6 As shown, for reference Figure 5 The results showed that ULBP2 expression was not related to age, sex, weight, or body mass index (BMI) in CRC patients. Figure 6 The results showed that, compared with normal samples, ULBP2 expression was significantly higher in various pathological classifications, including T, N and M stages;

[0054] The diagnostic performance of ULBP2 expression was evaluated using receiver operating characteristic (ROC) analysis. The TCGA CRC dataset and four GEO datasets were analyzed using the R package "pROC". The results were visualized using the R package "ggplot2". Figure 7 As shown, the area under the curve (AUC) of ULBP2 in the TCGA CRC, GSE9348, GSE23878, GSE41328 and GSE41657 datasets were 0.982 (95% confidence interval [CI]: 0.973–0.991), 0.671 (95% CI: 0.490–0.853), 0.693 (95% CI: 0.557–0.829), 1.000 (95% CI: 1.000–1.000), and 0.900 (95% CI: 0.803–0.998), respectively. These results indicate that ULBP2 expression, i.e., UL16-binding protein 2 expression, has significant diagnostic value in CRC.

[0055] Example 3

[0056] This embodiment analyzes the correlation between ULBP2 expression and prognosis.

[0057] Based on median ULBP2 expression levels, CRC patients were divided into high-expression and low-expression groups. Survival regression analysis was performed on the TCGA CRC dataset using the R package "survival," with the log-rank test as the statistical method. Prognostic outcomes included overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFI). The analysis results are as follows: Figure 8 As shown, compared with low expression, high ULBP2 expression was associated with significantly worse OS, DSS, and PFI. To further identify factors influencing CRC prognosis, univariate and multivariate Cox regression analyses were performed on the TCGA CRC dataset and ULBP2 expression using the R package "survival" to assess the prognostic significance of ULBP2 in CRC. The results of the univariate Cox regression analysis are shown below. Figure 9 As shown, univariate analysis revealed that ULBP2 expression, along with traditional TNM staging (T, N, M stages), was significantly associated with CRC prognosis. Multivariate Cox regression analysis results are as follows... Figure 10 As shown, multivariate Cox regression confirmed that these variables are independent prognostic factors for CRC, highlighting the role of ULBP2 in CRC prognosis. Finally, to verify the generalizability and reliability of the role of ULBP2 in CRC prognosis, survival regression analysis was performed on the GSE17536 and GSE29621 datasets using the log-rank test to assess overall survival (OS). The results are as follows: Figure 11As shown, in the GSE17536 and GSE29621 datasets, high ULBP2 expression in CRC patients was associated with significantly poor OS, further illustrating the significant association between high ULBP2 expression and significantly poor OS.

[0058] Example 4

[0059] This embodiment analyzes the correlation between ULBP2 gene promoter methylation level and tumor stage.

[0060] UALCAN (http: / / ualcan.path.uab.edu / ) is an interactive web portal for in-depth analysis of TCGA gene expression data. In this embodiment, UALCAN is used to analyze the methylation level of the ULBP2 gene promoter in the TCGA CRC dataset. By analyzing the methylation level of the ULBP2 gene promoter in tumor samples and normal tissue samples from the TCGA CRC dataset, the results are as follows: Figure 12 As shown, the methylation level of the ULBP2 gene promoter in tumor samples was significantly higher than that in normal tissue samples. Furthermore, tumor samples from the COAD dataset were divided into stages I, II, III, and IV according to the AJCC staging system, and the ULBP2 gene promoter methylation level was compared with that of normal tissue samples. The results are as follows: Figure 13 As shown, in the COAD dataset, the ULBP2 promoter methylation level was significantly higher in stages I, II, III, and IV compared to the normal group. Similarly, tumor samples from the READ dataset were staged according to AJCC and the ULBP2 gene promoter methylation level was compared with that of normal tissue samples, and the results are as follows. Figure 13 As shown, in the READ dataset, the ULBP2 promoter methylation level was significantly higher in stages I, II, III, and IV compared to the normal group. Furthermore, tumors in the TCGA CRC dataset were divided into N0, N1, and N2 based on regional lymph node metastasis, and the ULBP2 gene promoter methylation level was compared with that of normal tissue samples. The results are as follows: Figure 14 As shown, in the COAD and READ datasets, ULBP2 promoter methylation was elevated in groups N0, N1, and N2, indicating its association with lymph node metastasis.

[0061] Example 5

[0062] This implementation example validates the inhibitory effect of ULBP2 siRNA on tumor cell proliferation by knocking down ULBP2.

[0063] Human normal colonic epithelial cell line NCM-460 and human colorectal adenocarcinoma cell lines HCT-8 and LoVo were purchased from the Beijing Beina Innovation Biotechnology Research Institute, China. All cell lines were cultured under standard conditions: NCM-460 cells were cultured in DMEM high-glucose medium supplemented with 10% fetal bovine serum, while HCT-8 and LoVo cells were cultured in RPMI-1640 medium supplemented with 10% FBS. Cells were cultured in a humidified incubator at 37°C and 5% CO2. ULBP2 mRNA expression in NCM-460, HCT-8, and LoVo cells was detected by real-time polymerase chain reaction (qRT-PCR), and the results are as follows: Figure 15 As shown, ULBP2 mRNA expression in HCT-8 and LoVo cells was significantly higher than that in normal colonic epithelial cells NCM-460. Furthermore, to perform gene knockdown experiments, HCT-8 and LoVo cells were transfected with ULBP2-specific small interfering RNA (siRNA) using Lipofectamine 3000 reagent according to the manufacturer's instructions. The siRNA sequence used is as follows:

[0064] NC:TTCTCCGAACGTGTCACGTTT (SEQ ID NO.4)

[0065] ULBP2 siRNA-89:CACTCTCTTTGCTATGACA (SEQ ID NO.2)

[0066] ULBP2 siRNA-139:ACGGTGGTGTGCGGTTCAA (SEQ ID NO.3)

[0067] After transfection, cells were collected for qRT-PCR detection, and the results are as follows: Figure 16 As shown, ULBP2-specific siRNA was used to perform siRNA-mediated knockdown in HCT-8 and LoVo cells. qRT-PCR results confirmed that ULBP2 mRNA expression was significantly reduced after transfection with ULBP2siRNA-89 and ULBP2 siRNA-139 compared to the negative control (NC), indicating that ULBP2 knockdown was successful.

[0068] Total RNA was extracted from HCT-8 cells using VeZol reagent, and 1 µg of total RNA was reverse transcribed into cDNA using HiScript II Q RT SuperMix. qRT-PCR was performed using β-actin primers (β-actin-F, β-actin-R) and ULBP2 primers (ULBP2-F, ULBP2-R), with β-actin serving as an internal control. The relative expression level of the ULBP2 gene was calculated. The primers for qRT-PCR analysis were designed and synthesized by Shanghai Sangon Biotech Co., Ltd., and are as follows:

[0069] β-actin-F: TGGACCCAGCACAATGAA (SEQ ID NO.5)

[0070] β-actin-R: CTAAGTCATAGTCCGCCTAGAAGCA (SEQ ID NO.6)

[0071] ULBP2-F:GCCGCTACCAAGATCCTTCT (SEQ ID NO.7)

[0072] ULBP2-R: TCATCCACCTGGCCTTGAAC (SEQ ID NO.8)

[0073] The effect of ULBP2 knockdown on the proliferation of HCT-8 and LoVo colorectal cancer cells was evaluated using a CCK-8 cell proliferation assay kit. Transfected cells (3 × 10⁻⁶ cells) were then... 3 Cells were seeded in 96-well plates, with 100 µL of complete RPMI-1640 medium added to each well. Cells were cultured overnight to allow adhesion. At 0, 24, 48, and 72 hours post-transfection, 10 µL of CCK-8 reagent was added to each well, and the plates were incubated at 37°C for 2 hours. Absorbance was measured at 450 nm using an Epoch microplate spectrophotometer. Cell proliferation was calculated based on absorbance values, and comparisons were made between groups to assess the effect of ULBP2 knockdown. Results are shown below. Figure 17 As shown, compared with the negative control group, ULBP2 knockdown significantly reduced the survival rate of HCT-8 and LoVo cells, i.e., inhibited the proliferation of HCT-8 and LoVo colorectal cancer cells, indicating that the inhibitor of UL16 binding protein 2 has a positive inhibitory effect on proliferation in the preparation of drugs for the treatment of colorectal cancer.

[0074] Example 6

[0075] This embodiment evaluates cell migration efficiency through cell experiments.

[0076] HCT-8 and LoVo cells transfected with negative control NC, ULBP2 siRNA-89, and ULBP2 siRNA-139 were seeded into the wells of 6-well plates and cultured to 90% confluence. Scratch wounds were created in the cell monolayer using a sterile 200µL pipette tip, followed by washing with phosphate-buffered saline to remove debris and incubation in medium containing 3% serum. Cell migration was monitored at 0, 24, 48, and 72 hours using an optical microscope. Images were taken at each time point, and the wound area was quantified using ImageJ software. Optical microscopy images of HCT-8 cells are shown below. Figure 18 As shown, optical microscopic images of LoVo cells are as follows: Figure 19 As shown, the wound closure percentage was calculated to assess cell migration ability, and the results are as follows. Figure 20 As shown in the figure, compared with the negative control, the migration rate of HCT-8 and LoVo cells was significantly reduced after ULBP2 knockdown, indicating that the inhibitor of UL16 binding protein 2 has a positive effect on inhibiting tumor cell migration in the preparation of drugs for the treatment of colorectal cancer.

[0077] Example 7

[0078] This example illustrates the immunohistochemical staining analysis of ULBP2 in colorectal cancer tissue.

[0079] Immunohistochemical staining (IHC) was used to evaluate ULBP2 protein expression in colorectal cancer tissue specimens commercially provided by Shanghai Zhuoli Biotechnology Co., Ltd. The staining procedure followed established standard operating procedures. Specifically, formalin-fixed paraffin-embedded colorectal cancer tissue was cut into 4µm thick sections, dewaxed with xylene, gradually rehydrated with ethanol of different concentrations, and subjected to antigen retrieval in a microwave oven using citrate buffer (pH 6.0). After non-specific binding was blocked with normal goat serum, the sections were incubated overnight at 4°C with rabbit anti-ULBP2 recombinant antibody. The immunoreaction was then detected using 3,3′-diaminoaniline as a chromogenic substrate, followed by hematoxylin counterstaining to highlight the cell nuclei. ULBP2 protein levels were assessed using an automated Visio Morph system. The results are as follows: Figure 21 As shown, the staining intensity of ULBP2 protein in colorectal cancer tissue specimens was higher than that in adjacent normal tissue samples. In this embodiment, colorectal cancer tissue specimens were also grouped by IHC according to AJCC stage (I, II, III, IV), and the results are as follows. Figure 22 As shown, the ULBP2 protein staining area gradually increases with the increase of stage level, and is positively correlated with AJCC stage.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. The application of UL16-binding protein 2 inhibitors in the preparation of drugs for treating colorectal cancer, characterized in that, The inhibitor is a siRNA of UL16 binding protein 2, and the siRNA of UL16 binding protein 2 is either ULBP2siRNA-89 or ULBP2siRNA-139. The sequence of the ULBP2 siRNA-89 is shown in SEQ ID NO.2; The sequence of the ULBP2 siRNA-139 is shown in SEQ ID NO.3.

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