A biomarker associated with bladder cancer and uses thereof
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NANJING DRUM TOWER HOSPITAL
- Filing Date
- 2025-02-11
- Publication Date
- 2026-06-02
Smart Images
Figure CN119842905B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of biomedical technology, specifically relating to a biomarker related to bladder cancer and its application. Background Technology
[0002] Bladder cancer (BLCA) is one of the most common malignant tumors of the urinary system. According to the latest global cancer statistics released by CA-Cancer J Clin in 2024, bladder cancer ranks among the top ten malignant tumors in terms of incidence, with 614,000 new cases and over 220,000 deaths. In China, bladder cancer ranks eighth among male malignant tumors, and its incidence and mortality rates are rising year by year.
[0003] The pathogenesis of bladder cancer is highly complex, influenced by both intrinsic genetic factors and extrinsic environmental factors. To date, the most clearly understood causative factors fall into three main categories: smoking, occupational exposure to chemicals, and chronic infections. Early screening and treatment can significantly improve the survival rate of bladder cancer patients. However, bladder cancer often does not cause any obvious symptoms in its early stages, frequently leading to delayed diagnosis and progression to advanced stages. Currently, bladder cancer detection methods mainly include imaging examinations, urine tests, endoscopy, and pathological biopsy. Cystoscopy combined with histopathological examination is currently the gold standard for bladder cancer diagnosis. However, this method is significantly invasive and costly, preventing it from becoming a routine screening method. Non-invasive screening methods mainly focus on urine cytology and fluorescence in situ hybridization. These methods can detect the presence of bladder cancer to some extent, but due to their low sensitivity and specificity, they cannot be used for large-scale screening and therefore have not become effective broad-spectrum bladder cancer screening methods.
[0004] Therefore, there is an urgent need to develop a convenient and effective diagnostic method for bladder cancer to enable early diagnosis and intervention, and to provide comprehensive guidance for precision medicine. Summary of the Invention
[0005] The purpose of this invention is to address the problems of existing bladder cancer diagnostic techniques being highly invasive, costly, or having low sensitivity and poor specificity, by providing a tsRNA biomarker for the auxiliary diagnosis of bladder cancer. The method of using tsRNA biomarkers to assist in the diagnosis of bladder cancer in this invention does not require invasive examinations for patients, and is low in cost, highly sensitive, and has good specificity.
[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:
[0007] A biomarker associated with bladder cancer, wherein the biomarker is tsRNA: tRF-1:28-chrM.Ser-TGA and / or tiRNA-1:34-Glu-CTC-1-M2;
[0008] The nucleotide sequences of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 are shown in SEQ ID NO.1 and SEQ ID NO.2, respectively.
[0009] The application of the aforementioned biomarkers in the preparation of products for diagnosing bladder cancer is also within the scope of protection of this invention.
[0010] The product is a biochip or a reagent kit; the biochip contains molecular probes for quantitative detection of the biomarker; the reagent kit contains reagents for detecting the expression level of the biomarker.
[0011] The present invention also discloses a bladder cancer diagnostic kit, the kit comprising reagents for detecting the expression levels of the biomarkers tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2.
[0012] The reagent comprises primer pairs for detecting the expression level of the biomarker of claim 1; the nucleotide sequences of the forward and reverse primers for detecting the expression level of tRF-1:28-chrM.Ser-TGA are shown in SEQ ID NO.3 and SEQ ID NO.4, respectively; the forward and reverse primers for detecting the expression level of tiRNA-1:34-Glu-CTC-1-M2 are shown in SEQ ID NO.5 and SEQ ID NO.6, respectively.
[0013] The reagents include reagents and enzymes used in real-time quantitative reverse transcription PCR.
[0014] The kit contains reagents for RNA extraction.
[0015] The kit contains standards for tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2.
[0016] The test sample for the kit is plasma.
[0017] Evaluation criteria for diagnosing bladder cancer using the tsRNA biomarkers of this invention: When a patient's plasma tRF-1:28-chrM.Ser-TGA or tiRNA-1:34-Glu-CTC-1-M2 is significantly expressed compared to healthy controls, bladder cancer can be suspected; when both tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 are significantly expressed compared to healthy controls, bladder cancer can be highly suspected. The tsRNA biomarkers of this invention are only used as an auxiliary means of bladder cancer diagnosis, and it is still recommended to combine them with imaging examinations (such as ultrasound, CT, MRI, etc.), laboratory examinations, or endoscopy for further confirmation.
[0018] This invention first screened differentially expressed tsRNAs in the plasma of BLCA patients and healthy individuals using RNA sequencing. Then, through population validation, diagnostically valuable tsRNAs were obtained. Ultimately, two tsRNA biomarkers, tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2, were identified as potential biomarkers for early diagnosis of bladder cancer. High expression of these two tsRNAs in the plasma of bladder cancer patients was screened and validated using small RNA sequencing and real-time quantitative PCR. Further PCR detection and ROC analysis confirmed the high expression and specific association of these two tsRNAs in bladder cancer tissues and cells. PCR detection revealed that elevated levels of these two tsRNAs were associated with the occurrence and development of bladder cancer; their expression levels increased with increasing tumor malignancy. Furthermore, their expression levels in other urinary system tumors and non-tumor tissues were not significantly different from those in normal tissues. Cellular experiments further demonstrated that these two tsRNAs are likely released from bladder cancer cells and stably exist in plasma or culture medium. Cellular experiments also further verified the mechanism of action of these two tsRNAs in bladder cancer cell lines; inhibiting these two tsRNAs significantly reduced the proliferation and migration ability of bladder cancer cells. This invention also verified the in vivo effects of these two tsRNAs in a bladder cancer xenograft model, finding that treatment with these two tsRNAs significantly promoted tumor growth. Analysis of the target genes of plasma tsRNA tRF-1:28chrM.Ser-TGA and tsRNA tiRNA-1:34-Glu-CTC-1-M2 using target prediction tools and Targetscan revealed that these two tsRNAs may have the ability to promote lipid metabolism in tumor cells.
[0019] Beneficial effects:
[0020] (1) The two tsRNA biomarkers of the present invention, tRF-1:28chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2, are highly expressed in bladder cancer tissues and cells and are specifically associated with the occurrence and development of bladder cancer. Cell experiments further demonstrate that these two tsRNAs are likely to be released from bladder cancer cells and are stably present in plasma or culture medium. Therefore, using the tsRNA biomarkers of the present invention to diagnose bladder cancer can greatly improve the sensitivity, specificity and accuracy of bladder cancer diagnosis and help in the auxiliary diagnosis of bladder cancer.
[0021] (2) The expression levels of biomarkers tRF-1:28chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 are correlated with the progression of bladder cancer and are expected to serve as evaluation indicators for monitoring the course of bladder cancer and predicting prognosis.
[0022] (3) The present invention can diagnose bladder cancer by detecting the expression level of biomarkers in plasma samples, which greatly reduces the pain of patients during disease examination compared with invasive examinations such as endoscopy.
[0023] (4) The bladder cancer diagnostic kit of the present invention uses real-time fluorescence PCR technology to quantitatively detect the expression levels of two tsRNA biomarkers, tRF-1:28chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2, in plasma to assist in the diagnosis of bladder cancer. The operation method is simple, reproducible, and highly practical. Attached Figure Description
[0024] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, and the advantages of the present invention in the above and / or other aspects will become clearer.
[0025] Figure 1 The following are statistical graphs showing the differentially expressed plasma tsRNAs between BLCA patients and healthy controls in Example 1: Graph A is a scatter plot of differentially expressed tsRNAs in the plasma of BLCA patients and healthy controls; Graph B is a heatmap of the abundance of 19 differentially expressed tsRNAs between BLCA patients and healthy controls; Graph C is a statistical graph showing the distribution of plasma tsRNA subtypes in healthy controls, where the X-axis represents the source of tsRNAs and the Y-axis represents the quantity of tsRNAs; Graph D is a statistical graph showing the distribution of plasma tsRNA subtypes in BLCA patients, where the X-axis represents the source of tsRNAs and the Y-axis represents the quantity of tsRNAs.
[0026] Figure 2 This is a statistical graph showing the expression levels of 11 differentially expressed tsRNAs in the training set of Example 1; *** in the graph indicates... p<0.001, **** indicates p <0.0001, ns indicates no significant difference.
[0027] Figure 3 This is a statistical graph showing the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in the validation set of Example 1; *** in the graph indicates p <0.001, **** indicates p <0.0001.
[0028] Figure 4 Figure A shows schematic diagrams of the structures of tsRNA and tRNA-derived fragments, as well as statistical graphs of the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in the plasma of patients with bladder cancer and other urinary tract diseases in Example 2. Figure A shows schematic diagrams of the structures of tRNA, tRNA-derived fragment tRF, and tRNA-derived stress-induced RNA tiRNA; Figure B shows schematic diagrams of the predicted structures of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2; Figure C shows statistical graphs of the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in the plasma of patients with bladder cancer and other urinary tract diseases. *** in the figures indicates... p <0.001.
[0029] Figure 5 Figure 2 shows the ROC curves of tRF-1:28-chrM.Ser-TGA and / or tiRNA-1:34-Glu-CTC-1-M2 in diagnosing bladder cancer. Figure A shows the ROC curve of tRF-1:28-chrM.Ser-TGA in diagnosing bladder cancer; Figure B shows the ROC curve of tiRNA-1:34-Glu-CTC-1-M2 in diagnosing bladder cancer; and Figure C shows the ROC curve of the combined diagnosis of bladder cancer using tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2.
[0030] Figure 6Figure A shows the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in bladder cancer tumor tissue and healthy tissue in Example 3, and the correlation analysis of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 expression levels in BLCA tissue and its paired plasma. Figure B shows the correlation analysis of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 expression levels in bladder cancer tumor tissue and healthy non-cancer tissue; **** in the figures indicates... p <0.0001.
[0031] Figure 7 Figure 3 shows the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in different bladder cancer cell lines. Figure A shows the expression level of tRF-1:28-chrM.Ser-TGA in different bladder cancer cell lines; Figure B shows the expression level of tiRNA-1:34-Glu-CTC-1-M2 in different bladder cancer cell lines. * indicates... p <0.05, ** indicates p <0.01, *** indicates p <0.001, **** indicates p <0.0001, ns indicates no significant difference.
[0032] Figure 8 Figure 4 shows the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in the plasma of different bladder cancer patients and different bladder cancer cell lines. Figure A shows the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in the plasma of bladder cancer patients at different stages; Figure B shows the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in the plasma of low-grade and high-grade bladder cancer patients; Figure C shows the expression level of tsRNA in the plasma of bladder cancer patients with and without lymph node metastasis; and Figure D shows the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in different bladder cancer cell lines. * indicates... p<0.05, ** indicates p <0.01, *** indicates p <0.001, **** indicates p <0.0001.
[0033] Figure 9 This is a statistical graph showing the effect of the tsRNA inhibitor on the proliferation and migration of bladder cancer cells umuc-3 in Example 4. Figure A shows the cell proliferation of bladder cancer cell line umuc-3 after transfection with the tsRNA inhibitor; Figure B shows a microscopic image of cell migration of bladder cancer cell line umuc-3 after transfection with the tsRNA inhibitor (scale bar is 50 μm); Figure C shows the relative migration rate of bladder cancer cell line umuc-3 after transfection with the tsRNA inhibitor. *** in the figures indicates... p <0.001.
[0034] Figure 10 This is a statistical chart showing the effects of tsRNA mimicry on the proliferation and migration of bladder cancer cells 5637 in Example 4. Figure A shows the proliferation of bladder cancer cell line 5637 after transfection with tsRNA mimicry; Figure B shows a microscopic image of cell migration after transfection with tsRNA mimicry (scale bar is 50 μm); Figure C shows the relative migration rate of bladder cancer cell line 5637 after transfection with tsRNA mimicry. *** in the figures indicate... p <0.001.
[0035] Figure 11 This is a statistical graph showing the effects of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 on bladder cancer tumors in mice using a xenograft model in Example 5. Figure A shows the schematic diagram of the bladder cancer xenograft model mouse construction process; Figure B shows tumor tissue images of mice in each group after 2 weeks of tsRNA treatment; Figure C shows the tumor weight statistics after 2 weeks of tsRNA treatment; Figure D shows the mouse body weight statistics during tsRNA treatment; and Figure E shows the average tumor tissue volume statistics of mice in each group during tsRNA treatment. * indicates... p <0.05, ** indicates p <0.001.
[0036] Figure 12Figure 5 shows the statistical analysis of triglyceride, total cholesterol, and free fatty acid levels in the plasma and tumors of bladder cancer xenograft model mice treated with tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2. Figure A shows the statistical analysis of triglyceride, total cholesterol, and free fatty acid levels in the plasma of bladder cancer xenograft model mice after tsRNA treatment; Figure B shows the statistical analysis of triglyceride, total cholesterol, and free fatty acid levels in the tumors of bladder cancer xenograft model mice after tsRNA treatment. * indicates... p <0.05, ** indicates p <0.01, *** indicates p <0.001.
[0037] Figure 13 This is a statistical graph showing the effects of tRF-1:28-chrM.Ser-TGA inhibitor and tiRNA-1:34-Glu-CTC-1-M2 inhibitor on bladder cancer tumors in a mouse xenograft model, as described in Example 5. Figure A shows tumor tissue images of mice in each group after 2 weeks of tsRNA inhibitor treatment; Figure B shows tumor weight after 2 weeks of tsRNA inhibitor treatment; Figure C shows mouse body weight during tsRNA inhibitor treatment; and Figure D shows the average tumor volume of mice in each group during tsRNA inhibitor treatment. * indicates... p <0.05, ** indicates p <0.01.
[0038] Figure 14 Figure 5 shows the statistical graphs of the levels of triglycerides, total cholesterol, and free fatty acids in the plasma and tumors of mice with bladder cancer xenograft model mice treated with tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2. Figure A shows the statistical graphs of the levels of triglycerides, total cholesterol, and free fatty acids in the plasma of mice after treatment with tsRNA inhibitors; Figure B shows the statistical graphs of the levels of triglycerides, total cholesterol, and free fatty acids in the tumor tissue of mice after treatment with tsRNA inhibitors. * indicates... p <0.05, ** indicates p <0.01, *** indicates p <0.001. Detailed Implementation
[0039] The present invention will be further described below with reference to the following embodiments. It should be understood that the following embodiments are for illustrative purposes only and are not intended to limit the present invention.
[0040] For any specific techniques or conditions not specified in the examples, the techniques or conditions described in the literature in this field, or the product instructions, shall be followed. Reagents or instruments whose manufacturers are not specified are all conventional products that can be purchased through legitimate channels.
[0041] The patient plasma and tissue samples used in the following embodiments were all obtained from diagnosed patients at Gulou Hospital Affiliated to Nanjing University School of Medicine. These samples were collected according to standard medical procedures before the patients underwent any treatment procedures and were immediately and properly stored in an ultra-low temperature freezer at -80°C until subsequent analysis and testing. Meanwhile, samples from healthy controls were obtained from the Health Examination Center of Gulou Hospital Affiliated to Nanjing University School of Medicine, collected according to the same stringent standard procedures. All tissue samples used in this study underwent professional pathological testing and analysis to accurately confirm their properties and condition. The sample collection and use involved in this invention have been approved by the Ethics Committee of Gulou Hospital Affiliated to Nanjing University School of Medicine, and all participating patients or healthy individuals voluntarily signed informed consent forms after fully understanding the research content, purpose, and potential risks, ensuring the legality and compliance of the entire sample collection and use process and the full respect and protection of patients' rights.
[0042] Example 1: Screening of tsRNA biomarkers
[0043] 1. To verify whether plasma tsRNA profiles can serve as biomarkers for BLCA.
[0044] Small RNA sequencing was performed on plasma RNA samples from 20 bladder cancer patients and 20 healthy controls (discovery set). tsRNAs with a fold change greater than 2 in expression level between BLCA patients and healthy controls were considered differentially expressed.
[0045] (1) RNA sample preparation
[0046] Plasma samples were collected from 20 BLCA patients and 20 healthy controls, and then treated with TRIzol reagent for homogenization and RNA extraction.
[0047] (2) Pretreatment of tsRNA
[0048] The 3′-aminoacyl group is deacetylated to 3′-OH for 3′ linker ligation, 3′-cP (2′,3′-cyclic phosphate) is removed to 3′-OH for 3′ linker ligation, 5′-OH is phosphorylated to 5′-P for 5′ linker ligation, and m1A and m3C are demethylated to promote efficient reverse transcription.
[0049] (3) tsRNA library construction and sequencing
[0050] An automated gel cutter was used to select the size of the RNA biotypes to be sequenced, and the library was evaluated and quantified using an Agilent BioAnalyzer 2100. For standard small RNA sequencing on the Illumina NextSeq instrument, 50 bp single-read sequencing was used.
[0051] The preprocessing of tsRNA, as well as the construction and sequencing of the tsRNA library, were outsourced to Shenzhen BGI Genomics Co., Ltd.
[0052] The results are as follows Figure 1 As shown, a total of 425 tsRNAs were differentially expressed between bladder cancer patients and healthy controls. Among them, 107 tsRNAs were upregulated and 318 tsRNAs were downregulated. The top 19 significantly upregulated tsRNAs were highlighted.
[0053] 2. Identification of differentially expressed tsRNA biomarkers in the plasma of BLCA patients
[0054] The expression levels of 11 plasma tsRNAs among the 19 significantly differentially expressed tsRNAs highlighted above were detected using RT-qPCR in an independent training cohort (training set) consisting of 24 bladder cancer patients and 24 healthy controls. (To ensure effective amplification and detection, the primers for the RT-qPCR experiment needed to target sequences within a certain length range. Due to the target sequence length limitation, only 11 tsRNAs could be evaluated for expression levels by RT-qPCR.) This was to validate the sequencing results from step 2. The specific experimental steps are as follows:
[0055] (1) Plasma samples were collected from 24 bladder cancer patients and 24 healthy controls. Total RNA was separated from 100 μL of plasma from each person using Trizol LS reagent (Invitrogen, a brand of Thermo Fisher Scientific) and dissolved in 20 μL of DEPC water.
[0056] (2) Using the miRNA 1st Strand cDNA Synthesis Kit (by stem-loop) (purchased from Nanjing Novizan Biotechnology Co., Ltd., catalog number MR-101-02), the total RNA samples (2 μL) of each experimental subject obtained in step (1) were reverse transcribed into complementary DNA (cDNA) by reverse transcription polymerase chain reaction (RT-PCR). The specific experimental steps are as follows:
[0057] a. Removal of genomic DNA from total RNA samples: Prepare the reaction solution as shown in Table 1 in RNase-free centrifuge tubes. After preparation, gently mix the solution by pipetting with a 20 μL pipette and incubate at 42°C for 2 min.
[0058] Table 1 Reaction solution (10 μL)
[0059]
[0060] b. Reverse transcription of total RNA (with genomic DNA removed) into cDNA: An RT-PCR reaction system was prepared in an RNase-free centrifuge tube as shown in Table 3. After preparation, the system was vortexed and then placed in a PCR instrument for RT-PCR. The RT-PCR reaction program is shown in Table 4. cDNA was obtained after the reaction. The primer sequences required for reverse transcription of 11 plasma tsRNAs into cDNA are shown in Table 5.
[0061] Table 3. Reverse transcription reaction preparation system (20 μL)
[0062]
[0063] Table 4 Reverse transcription reaction procedure
[0064]
[0065] Table 5. Stem-loop primer sequences required for tsRNA reverse transcription to cDNA
[0066]
[0067] (3) Using miRNA Universal SYBR qPCR Master Mix (purchased from Nanjing Novizan Biotechnology Co., Ltd., catalog number MQ101-01), the expression levels of 11 tsRNAs in the plasma of bladder cancer patients and healthy controls were detected by real-time quantitative PCR (qPCR) in a 7300 real-time quantitative PCR system (ABI, Japan) with cDNA obtained in step (2) as a template. The specific experimental steps were as follows: the qPCR reaction system was prepared for quantitative detection. After the system was prepared, it was thoroughly vortexed and mixed, and then placed in the qPCR instrument for qPCR reaction. The qPCR reaction system and reaction program are shown in Table 6 and Table 7, respectively. The primer sequences required for the cDNA qPCR reaction of the 11 tsRNAs are shown in Table 8.
[0068] Table 6 qPCR reaction system
[0069]
[0070] Table 7 qPCR reaction procedure
[0071]
[0072] Table 8 Primer sequences required for tsRNA qPCR reaction
[0073]
[0074] (4) In order to perform accurate quantitative analysis of tsRNA, a set of oligonucleotide chain standards of 11 target tsRNAs with known concentrations (ranging from 1 pmol / L to 10 nmol / L) were reverse transcribed and amplified to establish a standard curve, and then the target tsRNA was absolutely quantified by the standard curve.
[0075] The expression of 11 target tsRNAs in bladder cancer patients and healthy controls in the training set was statistically analyzed, and the results are as follows: Figure 2 As shown, two tsRNAs, tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2, were found to have significantly different expression levels between bladder cancer patients and healthy controls. Therefore, two tsRNA biomarkers, tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2, were identified.
[0076] Further validation of the differential expression of these two tsRNAs (tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2) was conducted in a larger plasma sample cohort (validation set) consisting of 80 bladder cancer patients and 60 healthy controls. The specific quantitative experimental procedures were the same as those for the training set.
[0077] The results are as follows Figure 3 As shown, the expression levels of two tsRNAs (tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2) in the plasma of bladder cancer patients were significantly upregulated and significantly higher than those in healthy controls.
[0078] Example 2: Sensitivity and specificity of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 for BLCA
[0079] To verify the specific association between upregulation of plasma tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 expression and bladder cancer, we used RT-qPCR to detect the expression levels of these two tsRNAs in the plasma of 20 patients with other urinary tract diseases (20 patients with urinary tract stones, 20 patients with prostate cancer, and 20 patients with renal cell carcinoma), and compared them with the expression levels of these two tsRNAs in healthy controls (20 individuals). The specific experimental procedures were the same as those for the training set in Example 1.
[0080] Meanwhile, to evaluate the diagnostic value of plasma tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2, we performed ROC analysis on a total of 228 plasma samples, including the discovery set (20 bladder cancer patients and 20 healthy controls), the training set (24 bladder cancer patients and 24 healthy controls), and the validation set (80 bladder cancer patients and 60 healthy controls).
[0081] Experimental results are as follows Figure 4 and Figure 5 As shown, Figure 4 Figure C shows that the abnormal expression of these two tsRNAs is specific to bladder cancer. Figure 5 ROC curves showed that both tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 exhibited high AUC values (0.88 and 0.80, respectively). tRF-1:28-chrM.Ser-TGA showed a sensitivity of 58.33% and a specificity of 91.67%, while tiRNA-1:34-Glu-CTC-1-M2 showed a sensitivity of 41.67% and a specificity of 92.7%. In combined analysis, the combination of the two tsRNAs had a higher AUC (0.93, 95% CI 0.85–0.99) compared to any single tsRNA, with a sensitivity of 45.8% and a specificity of 95.7%. Previous studies have shown that urine cytology for bladder cancer diagnosis showed an area under the curve (AUC) of 0.694, and both the two individual tsRNAs and the combined tsRNAs demonstrated superior diagnostic performance in detecting bladder cancer compared to urine cytology. These results indicate that elevated levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in plasma have good diagnostic value for bladder cancer.
[0082] Example 3: Verification that elevated levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in plasma originate from BLCA tumor cells.
[0083] To investigate whether the upregulation of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in plasma specifically originates from bladder tumor tissue, we examined their expression levels in bladder tumor tissue (sample size 60) relative to adjacent non-cancer tissue (sample size 36). We also performed correlation analysis on the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in bladder cancer tissue and their paired plasma from the same bladder cancer patient (sample size 10). Furthermore, we evaluated the expression of these two tsRNAs in the culture media of various bladder cancer cell lines (5637, T24, UMUC3, J82).
[0084] Experimental results are as follows Figure 6 and Figure 7 As shown, the results indicate that the level of tsRNA in tumor tissue was significantly increased compared to adjacent non-cancerous tissue. In in vitro experiments, the expression levels of these tsRNAs were positively correlated with cell number and culture time. These in vitro and in vivo experimental results suggest that these two tsRNAs are likely released from bladder cancer cells and stably exist in plasma or culture medium.
[0085] Example 4: Correlation between tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in BLCA and bladder cancer development
[0086] This invention aims to investigate whether elevated levels of two tsRNAs, tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2, in tumor tissue and plasma of BLCA patients are related to the occurrence and development of BLCA. The expression of these two tsRNAs in the plasma of BLCA patients at different disease stages (16 samples for T0-T1 stage, 10 samples for ≥T2 stage), patients with different grades of bladder cancer (low-grade and high-grade), and patients with bladder cancer with and without lymph node metastasis was examined. Furthermore, the expression of these two tsRNAs in low-grade BLCA cell lines 5637 (G2, -) and T24 (G3, pTa), and two high-grade cell lines UMUC3 (-, pT2-4) and J82 (G3, pT3) was analyzed. Finally, to further elucidate the effects of these two tsRNAs on BLCA cells, the mimics of these two tsRNAs (synthetically synthesized tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 oligonucleotides) and their oligonucleotide inhibitors were introduced into BLCA cells 5637 and UMUC-3, respectively. Two tsRNAs, tRNA-Val-AAC-2-1 and tRF-30:43-Glu-CTG-1-M6 (which showed no significant difference in expression between bladder cancer patients and healthy controls), were randomly selected. Using their mimics and inhibitors as negative controls, the proliferation and migration abilities of bladder cancer cells were investigated using CCK8 and cell scratch assays.
[0087] Experimental results are as follows Figure 8 , Figure 9 and Figure 10 As shown, the levels of these two tsRNAs in the plasma of patients with low-grade and early-stage bladder cancer were significantly lower than those in patients with high-grade and late-stage bladder cancer. qRT-PCR results showed that the expression levels of these two tsRNAs in high-grade bladder cancer cells umuc-3 and J82 were higher than those in low-grade bladder cancer cells 5637 and T24, further confirming that the expression levels of these two tsRNAs increase with the malignancy of tumor cells. Further investigation into the relationship between the expression of these two tsRNAs and lymph node metastasis revealed that plasma tsRNA expression in patients with lymph node metastasis was significantly higher than in patients without metastasis. CCK-8 and cell scratch assays showed that inhibiting tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 significantly reduced the proliferation and migration abilities of bladder cancer cells, while transfection with mimics produced the opposite effect.
[0088] In summary, the results indicate that the expression levels of the tsRNA biomarkers tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 increase with the malignancy of tumor cells. Further investigation using CCK-8 and cell scratch assays confirmed that tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 significantly promote the proliferation and migration of bladder cancer cells, potentially acting as tumor-promoting factors. These results provide a basis for utilizing tsRNA as a potential biomarker for the diagnosis and staging of bladder cancer, and also confirm its biological function in bladder cancer.
[0089] Example 5: tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 may promote cancer by affecting lipid metabolism in vivo.
[0090] This invention validated the in vivo effects of these two tsRNAs in mice using a bladder cancer xenograft model. Subcutaneous BLCA xenograft models (T24-BLCA and UMUC3-BLCA models) were established in BALB / c nude mice by subcutaneous injection of T24 and UMUC3 bladder cancer cells, respectively. The mice were fed under normal conditions for 2-3 weeks to allow tumor growth. When the tumor volume reached 50-80 mm... 3 T24-BLCA subcutaneous xenograft mice were randomly divided into three groups (blank control group, mimic group 1, and mimic group 2), and UMUC3-BLCA subcutaneous xenograft mice were randomly divided into three groups (blank control group, inhibitor group 1, and inhibitor group 2), with five mice in each group. Mimic group 1 and mimic group 2 received intratumoral injections of tRF-1:28-chrM.Ser-TGA mimic and tiRNA-1:34-Glu-CTC-1-M2 mimic, respectively. Inhibitor group 1 and inhibitor group 2 received intratumoral injections of tRF-1:28-chrM.Ser-TGA inhibitor and tiRNA-1:34-Glu-CTC-1-M2 inhibitor, respectively. The blank control group received PBS buffer. The injection dose was 1 nmol per mouse, administered every two days for two weeks. During treatment, tumor volume (V = length × width^2 × 0.52) and body weight were assessed every three days. After 14 days, the mice were euthanized, their plasma was collected, and the tumors were removed, weighed, and analyzed.
[0091] The target genes of tsRNA tRF-1:28chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in mouse plasma were analyzed using the target prediction tools RNAhybrid and Targetscan (www.targetscan.org / vert_80 / ). Furthermore, the biological processes associated with tsRNA target genes were identified using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). p <0.05, false discovery rate (FDR) <0.05). Finally, after mouse models were treated with two target tsRNA mimics and two target tsRNA inhibitors, the levels of triglycerides, total cholesterol, and free fatty acids in mouse plasma and tumor tissues were measured. The experimental results are as follows: Figures 11-14 As shown.
[0092] Figure 11 and Figure 12 The results showed that the explant tumor volume in the tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-GluCTC-1-M2 groups was significantly larger than that in the NC group, and there was no significant difference in body weight among the three groups. Compared with the control group, tsRNA treatment significantly promoted tumor growth after 2 weeks. These results indicate that the two tsRNAs can accelerate the development of bladder cancer in vivo. In addition, KEGG annotation showed that the predicted target genes of the two tsRNAs were enriched in physiological processes and signaling pathways related to lipid metabolism, such as triglyceride and cholesterol metabolism and fatty acid synthesis. Therefore, the levels of triglycerides, total cholesterol, and free fatty acids in mouse plasma and tumor tissues after tsRNA treatment were detected, and the results showed that the two tsRNAs could significantly increase the content of triglycerides, total cholesterol, and free fatty acids in tumors and plasma.
[0093] Figure 13 and Figure 14 The results showed that the tumor volume in the tRF-1:28-chrM.Ser-TGA inhibitor and tiRNA-1:34-Glu-CTC-1-M2 inhibitor groups was significantly smaller than that in the control group. Furthermore, there was no significant difference in mouse body weight among the three groups. Compared with the control group, treatment with the tsRNA inhibitor for 2 weeks significantly inhibited tumor proliferation. Regarding lipid metabolism, the results showed that the tRF-1:28-chrM.Ser-TGA inhibitor and tiRNA-1:34-Glu-CTC-1-M2 inhibitor significantly reduced the levels of triglycerides, total cholesterol, and free fatty acids in tumors and plasma.
[0094] In summary, these results suggest that the two tsRNAs may regulate tumor progression by promoting lipid metabolism. Detection of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 may help identify high-risk bladder cancer patients in the early stages, facilitating timely treatment, improving quality of life, and reducing the economic burden on patients and society.
[0095] This invention provides a biomarker related to bladder cancer and its application, along with a method and approach. Many methods and approaches exist for implementing this technical solution; the above description is merely a preferred embodiment. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this invention, and these improvements and modifications should also be considered within the scope of protection of this invention. All components not explicitly stated in this embodiment can be implemented using existing technologies.
Claims
1. The application of a quantitative detection reagent for bladder cancer biomarkers in the preparation of products for diagnosing bladder cancer; characterized in that, The biomarkers mentioned are tsRNA: tRF-1:28-chrM.Ser-TGA and / or tiRNA-1:34-Glu-CTC-1-M2; The nucleotide sequences of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 are shown in SEQ ID NO.1 and SEQ ID NO.2, respectively.
2. The application according to claim 1, characterized in that, The product is a biochip or a reagent kit.
3. The application according to claim 1, characterized in that, The quantitative detection reagent contains primer pairs for detecting the expression level of the biomarker.
4. The application according to claim 3, characterized in that, The nucleotide sequences of the forward and reverse primers for detecting the expression level of tRF-1:28-chrM.Ser-TGA are shown in SEQ ID NO.3 and SEQ ID NO.4, respectively; the forward and reverse primers for detecting the expression level of tiRNA-1:34-Glu-CTC-1-M2 are shown in SEQ ID NO.5 and SEQ ID NO.6, respectively.
5. The application according to claim 1, characterized in that, The quantitative detection reagent includes reagents and enzymes used in real-time quantitative reverse transcription PCR.
6. The application according to claim 1, characterized in that, The quantitative detection reagent includes reagents used for RNA extraction.
7. The application according to claim 1, characterized in that, The quantitative detection reagent contains tRF-1:28-chrM.Ser-TGA standard and tiRNA-1:34-Glu-CTC-1-M2 standard.
8. The application according to claim 1, characterized in that, The sample to be tested by the quantitative detection reagent is plasma.