Biomarker related to bladder cancer and application thereof

Abstract

The invention discloses a biomarker related to bladder cancer and application of the biomarker, the biomarker is tRF-1: 28-chrM.Ser-TGA and / or tiRNA-1: 34-Glu-CTC-1-M2, the biomarker can be used for preparing products for diagnosis and / or prognosis evaluation of bladder cancer early-stage high-risk patients, and the biomarker belongs to the technical field of biological medicine. The biomarker is obtained through RNA sequencing screening and has higher sensitivity and specificity as the biomarker, qRT-PCR verification and ROC curve analysis verification prove that tRF-1: 28-chrM.Ser-TGA and tiRNA-1: 34-Glu-CTC-1-M2 can be used for excellently distinguishing bladder cancer patients from normal people, and can be used for preparing the bladder cancer marker. The biomarker can be used as an early diagnostic biomarker and a new therapeutic target for bladder cancer patients, and has great clinical value and practical significance for early clinical diagnosis of bladder cancer, evaluation of related therapeutic targets and improvement of the survival rate of patients.

Description

Technical Field

[0001] The present invention belongs to the field of biomedicine technology, and specifically relates to a biomarker associated with bladder cancer and an application thereof. Background Art

[0002] Bladder cancer (BLCA) is one of the common malignant tumors of the urinary system. According to the latest global tumor statistics published by CA-Cancer J Clin in 2024, the incidence of bladder cancer ranks among the top ten malignant tumors, with 614,000 cases and more than 220,000 deaths. In China, the incidence of 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 very complex, and is affected by both internal genetic factors and external environmental factors. So far, the pathogenic factors that have been studied clearly mainly include three categories: smoking, occupational exposure to chemicals, and chronic infection. Early screening and early treatment can significantly improve the survival rate of patients with bladder cancer. However, bladder cancer usually does not cause any obvious symptoms in the early stages, and patients often develop into advanced cancer due to delayed diagnosis. At present, the detection methods of bladder cancer mainly include imaging examinations, urine tests, endoscopy and pathological biopsy. Among them, cystoscopy combined with histopathological examination is the gold standard for bladder cancer diagnosis. However, this method is obviously invasive and costly, and cannot become a routine screening method. Non-invasive screening methods mainly focus on urine exfoliated cytology and fluorescence in situ hybridization. Such methods can detect the presence of bladder cancer to a certain extent, but due to their low sensitivity and specificity, they cannot be used for large-scale screening, so they have not become an effective and broad-spectrum bladder cancer screening method.

[0004] Therefore, there is an urgent need to develop a convenient and effective method for diagnosing bladder cancer to achieve early diagnosis and intervention treatment of bladder cancer and provide comprehensive guidance for its precision medicine. Summary of the invention

[0005] The purpose of the present invention is to provide a tsRNA biomarker for assisting the diagnosis of bladder cancer in order to address the problems of existing bladder cancer diagnostic technologies being highly invasive, costly, or having low sensitivity and poor specificity. The method of the present invention for assisting the diagnosis of bladder cancer using tsRNA biomarkers does not require invasive examinations of patients, has low costs, high sensitivity and good specificity.

[0006] To achieve the above purpose, 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 the 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 use of the biomarkers in the preparation of products for diagnosing bladder cancer is also within the protection scope of the present invention.

[0010] Wherein, the product is a biochip or a kit; the biochip contains molecular probes for quantitatively detecting the biomarker; and the kit contains reagents for detecting the expression amount of the biomarker.

[0011] The present invention also discloses a bladder cancer diagnosis kit, which comprises reagents for detecting the expression amounts of the biomarkers tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2.

[0012] Wherein, the reagent comprises a primer pair for detecting the expression amount of the biomarker according to claim 1; the nucleotide sequences of the forward primer and the reverse primer for detecting the expression amount of the tRF-1:28-chrM.Ser-TGA are shown as SEQ ID NO.3 and SEQ ID NO.4, respectively; the forward primer and the reverse primer for detecting the expression amount of the tiRNA-1:34-Glu-CTC-1-M2 are shown as SEQ ID NO.5 and SEQ ID NO.6, respectively.

[0013] Wherein, the reagents include reagents and enzymes used for real-time fluorescence quantitative reverse transcription PCR.

[0014] Wherein, the kit comprises reagents used for RNA extraction.

[0015] The kit comprises a standard product of tRF-1:28-chrM.Ser-TGA and a standard product of tiRNA-1:34-Glu-CTC-1-M2.

[0016] Wherein, the detection sample of the kit is plasma.

[0017] Evaluation criteria for diagnosing bladder cancer using the tsRNA biomarker of the present invention: when the patient's plasma tRF-1:28-chrM.Ser-TGA or tiRNA-1:34-Glu-CTC-1-M2 is significantly expressed compared with that of healthy controls, it can be suspected to be diagnosed with bladder cancer; when the patient's plasma tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 are both significantly expressed compared with healthy controls, it can be highly suspected to be diagnosed with bladder cancer; the tsRNA biomarker of the present invention is only used as an auxiliary means for diagnosing bladder cancer, and it is still recommended to combine imaging examinations (such as ultrasound, CT, magnetic resonance imaging, MRI, etc.), laboratory tests or endoscopy for further diagnosis.

[0018] The present invention first screens out differentially expressed tsRNA in the plasma of BLCA patients and healthy people through RNA sequencing, and then obtains tsRNA with diagnostic value through population verification, and finally finds two tsRNA biomarkers: tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 can be used as biomarkers for early diagnosis of bladder cancer, and screens and verifies the high expression of these two tsRNAs in the plasma of bladder cancer patients through small RNA sequencing and real-time quantitative PCR. Further PCR detection and ROC analysis verification confirmed that these two tsRNAs are highly expressed in bladder cancer tissues and cells and have specific associations. PCR detection found that the increase in the levels of these two tsRNAs is related to the occurrence and development of bladder cancer. The expression levels of these two tsRNAs increase with the increase in the malignancy of the tumor, and their expression levels in other urinary system tumors and non-tumor tissues are not significantly different from normal tissues. Cell experiments also further illustrate that these two tsRNAs are likely to be released from bladder cancer cells and stably exist in plasma or culture medium. Cell experiments also further verify the mechanism of action of these two tsRNAs in bladder cancer cell lines. Inhibition of these two tsRNAs can significantly reduce the proliferation and migration ability of bladder cancer cells. The present invention also verifies the in vivo effects of these two tsRNAs in a bladder cancer xenograft model, and finds that treatment with these two tsRNAs significantly promotes tumor growth. Using target prediction tools and Targetscan to analyze the target genes of plasma tsRNA tRF-1:28chrM.Ser-TGA and tsRNA tiRNA-1:34-Glu-CTC-1-M2, it is found that these two tsRNAs may have the ability to promote lipid metabolism in tumor cells.

[0019] Beneficial effects:

[0020] (1) The two tsRNA biomarkers tRF-1:28chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 of the present invention are highly expressed in bladder cancer tissues and cells and are specifically associated with the occurrence and development of bladder cancer. Cell experiments also further show that these two tsRNAs are likely to be released from bladder cancer cells and stably exist in plasma or culture medium. Therefore, the use of the tsRNA biomarkers of the present invention to diagnose bladder cancer can greatly improve the sensitivity, specificity and accuracy of bladder cancer diagnosis, and contribute to the auxiliary diagnosis of bladder cancer.

[0021] (2) The expression levels of the 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 medical personnel during disease examination compared with invasive examinations such as microscopy.

[0023] (4) The bladder cancer diagnostic kit of the present invention uses fluorescent quantitative 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, repeatable and highly practical. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments, and the above and / or other advantages of the present invention will become more clear.

[0025] Figure 1 The figures are statistical graphs of the analysis of differentially expressed plasma tsRNA between BLCA patients and healthy controls in Example 1; wherein, Figure A is a scatter plot of differentially expressed tsRNA in the plasma of BLCA patients and healthy controls; Figure B is a heat map of the abundance of 19 most significantly differentially expressed tsRNAs between BLCA patients and healthy controls; Figure C is a statistical graph of the distribution of plasma tsRNA subtypes between BLCA patients and healthy controls, in which the X-axis represents the source of tRNA and the Y-axis represents the amount of tsRNA.

[0026] Figure 2 This is a statistical graph of the expression levels of 11 differentially expressed tsRNAs in the training set of Example 1; in the figure, *** indicates p<0.001, **** indicates p<0.0001, and ns indicates no significant difference.

[0027] Figure 3 This is a statistical graph of 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 figure indicates p<0.001, and **** indicates p<0.0001.

[0028] Figure 4 Schematic diagram of the structure of tsRNA and tRNA-derived fragments and statistical diagram 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 system diseases in Example 2; wherein, Figure A is a schematic diagram of the structure of tRNA, tRNA-derived fragment tRF and tRNA-derived stress-induced RNA tiRNA; Figure B is a schematic diagram of the predicted structure of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2; Figure C is a statistical diagram 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 system diseases; *** in the figure indicates p<0.001.

[0029] Figure 5 The ROC curves of tRF-1:28-chrM.Ser-TGA and / or tiRNA-1:34-Glu-CTC-1-M2 in Example 2 for diagnosing bladder cancer are shown in Figure 2; wherein, Figure A is the ROC curve of tRF-1:28-chrM.Ser-TGA for diagnosing bladder cancer; Figure B is the ROC curve of tiRNA-1:34-Glu-CTC-1-M2 for diagnosing bladder cancer; and Figure C is the ROC curve of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 for the combined diagnosis of bladder cancer.

[0030] Figure 6The figures are statistical graphs of the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in bladder cancer tumor tissues and healthy tissues in Example 3, and a correlation analysis graph of the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in BLCA tissues and their paired plasma; wherein, Figure A is a statistical graph of the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in bladder cancer tumor tissues and healthy non-cancerous tissues; Figure B is a correlation analysis graph of the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in BLCA tissues and their paired plasma of bladder cancer patients; **** in the figure indicates p<0.0001.

[0031] Figure 7 The expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in different bladder cancer cell lines in Example 3 are statistical graphs; wherein, Figure A is a statistical graph of the expression levels of tRF-1:28-chrM.Ser-TGA in different bladder cancer cell lines; Figure B is a statistical graph of the expression levels of tiRNA-1:34-Glu-CTC-1-M2 in different bladder cancer cell lines; in the figure, * indicates p<0.05, ** indicates p<0.01, *** indicates p<0.001, **** indicates p<0.0001, and ns indicates no significant difference.

[0032] Figure 8 Figure 4 is a statistical graph of the expression 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 is a statistical graph of the expression of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in the plasma of patients with bladder cancer at different stages, and Figure B is a statistical graph of the expression of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in the plasma of patients with low-grade and high-grade bladder cancer. Figure 2 is a statistical graph showing the expression levels of r-TGA and tiRNA-1:34-Glu-CTC-1-M2. Figure C is a statistical graph showing the expression levels of tsRNA in the plasma of bladder cancer patients with or without lymph node metastasis. Figure D is a statistical graph showing the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in different bladder cancer cell lines. In the figure, * indicates p<0.05, ** indicates p<0.01, *** indicates p<0.001, and **** indicates p<0.0001.

[0033] Fig. 9 The results of the effects of tsRNA inhibitors on the proliferation and migration ability of bladder cancer cell umuc-3 in Example 4 are statistical graphs; wherein, Figure A is a statistical graph of cell proliferation after bladder cancer cell line umuc-3 was transfected with tsRNA inhibitors; Figure B is a microscope image of cell migration after bladder cancer cell line umuc-3 was transfected with tsRNA inhibitors, and the scale bar in the figure is 50 μm; Figure C is a statistical graph of the relative migration rate of cells after bladder cancer cell line umuc-3 was transfected with tsRNA inhibitors; *** in the figure indicates p<0.001.

[0034] Fig.10 The results of the effects of tsRNA mimics on the proliferation and migration ability of bladder cancer cell line 5637 in Example 4 are statistical graphs; wherein, Figure A is a statistical graph of cell proliferation after bladder cancer cell line 5637 is transfected with tsRNA mimics; Figure B is a microscope image of cell migration after bladder cancer cell line 5637 is transfected with tsRNA mimics, and the scale bar in the figure is 50 μm; Figure C is a statistical graph of the relative migration rate of cells after bladder cancer cell line 5637 is transfected with tsRNA mimics; *** in the figure indicates p<0.001.

[0035] Fig.11 Figure 5 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 bladder cancer xenograft model mice in Example 5; wherein, Figure A is a schematic diagram showing the process of constructing a bladder cancer xenograft model mouse; Figure B is an image of tumor tissue in each group of mice after 2 weeks of tsRNA treatment; Figure C is a statistical graph showing tumor weight after 2 weeks of tsRNA treatment; Figure D is a statistical graph showing the weight of mice during tsRNA treatment, and Figure E is a statistical graph showing the average volume of tumor tissue in each group of mice during tsRNA treatment; in the figures, * indicates p<0.05, and ** indicates p<0.001.

[0036] Fig.12 The figures are statistical graphs of the effects of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in Example 5 on the levels of triglycerides, total cholesterol and free fatty acids in the plasma and tumors of mice with bladder cancer xenograft model; Figure A is a statistical graph of the levels of triglycerides, total cholesterol and free fatty acids in the plasma of mice with bladder cancer xenograft model after tsRNA treatment; Figure B is a statistical graph of the levels of triglycerides, total cholesterol and free fatty acids in the tumors of mice with bladder cancer xenograft model after tsRNA treatment; in the figures, * indicates p<0.05, ** indicates p<0.01, and *** indicates p<0.001.

[0037] Fig.13Figure 5 is a statistical graph showing the effects of the tRF-1:28-chrM.Ser-TGA inhibitor and the tiRNA-1:34-Glu-CTC-1-M2 inhibitor on bladder cancer tumors in bladder cancer xenograft model mice in Example 5; wherein, Figure A is an image of tumor tissue in each group of mice after 2 weeks of treatment with the tsRNA inhibitor; Figure B is a statistical graph of tumor weight after 2 weeks of treatment with the tsRNA inhibitor; Figure C is a statistical graph of mouse body weight during treatment with the tsRNA inhibitor; Figure D is a statistical graph of the average volume of tumor tissue in each group of mice during treatment with the tsRNA inhibitor; in the figure, * indicates p<0.05, and ** indicates p<0.01.

[0038] Fig.14 The figures are statistical graphs of the effects of tRF-1:28-chrM.Ser-TGA inhibitor and tiRNA-1:34-Glu-CTC-1-M2 inhibitor in Example 5 on the levels of triglycerides, total cholesterol and free fatty acids in plasma and tumors of mice with bladder cancer xenograft models; wherein, Figure A is a statistical graph of the levels of triglycerides, total cholesterol and free fatty acids in mouse plasma after treatment with the tsRNA inhibitor; Figure B is a statistical graph of the levels of triglycerides, total cholesterol and free fatty acids in mouse tumor tissues after treatment with the tsRNA inhibitor; in the figures, * indicates p<0.05, ** indicates p<0.01, and *** indicates p<0.001. DETAILED DESCRIPTION

[0039] The present invention is further described below based on the following examples. It should be understood that the following embodiments are only used to illustrate the present invention, but not to limit the present invention.

[0040] If the specific techniques or conditions are not specified in the examples, they are carried out according to the techniques or conditions described in the literature in the field or according to the product instructions. If the manufacturers of the reagents or instruments are not specified, they are all conventional products that can be purchased through regular channels.

[0041] The patient plasma samples and tissue samples used in the following examples are all derived from patients diagnosed with the disease in the Drum Tower Hospital Affiliated to Nanjing University Medical School. Before the patient receives any treatment procedure, these samples are collected according to standard medical procedures and immediately stored in an ultra-low temperature refrigerator at -80 ° C until the subsequent relevant analysis and detection. At the same time, the samples of healthy controls are obtained from the Health Examination Center of the Drum Tower Hospital Affiliated to Nanjing University Medical School, and are collected according to the same strict standard procedures. All tissue samples used in the present invention have been subjected to professional pathological testing and analysis to accurately confirm their properties and states. The sample collection and use and other related matters involved in the present invention have been approved by the Ethics Committee of the Drum Tower Hospital Affiliated to Nanjing University Medical School, and all patients or healthy people participating in the study have voluntarily signed the informed consent form after fully understanding the content, purpose and possible risks of the research, ensuring the legality and compliance of the entire sample collection and use process and the full respect and protection of the rights and interests of patients.

[0042] Example 1 Screening of tsRNA biomarkers

[0043] 1. Verify whether tsRNA profiles in plasma 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 of more than 2 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 subsequently treated with TRIzol reagent for homogenization and RNA extraction.

[0047] (2) Pretreatment of tsRNA

[0048] Deacetylates 3′-aminoacyl to 3′-OH for 3′ adaptor ligation, removes 3′-cP (2′,3′-cyclic phosphate) to 3′-OH for 3′ adaptor ligation, phosphorylates 5′-OH to 5′-P for 5′ adaptor ligation, and demethylates m1A and m3C to promote efficient reverse transcription.

[0049] (3) tsRNA library construction and sequencing

[0050] RNA biotypes to be sequenced were size selected using an automated gel cutter, and libraries were evaluated and quantified using an Agilent BioAnalyzer 2100. For standard small RNA sequencing on an Illumina NextSeq instrument, a 50 bp single-read sequencing type was used.

[0051] The above-mentioned tsRNA pretreatment, tsRNA library construction and sequencing were entrusted to Shenzhen BGI Genomics Service Co., Ltd.

[0052] The results are as follows Figure 1 As shown, a total of 425 tsRNAs were identified to be differentially expressed between bladder cancer patients and healthy controls, of which 107 tsRNAs were upregulated and 318 tsRNAs were downregulated. The top 19 significantly differentially expressed upregulated tsRNAs were highlighted.

[0053] 2. Identification of differentially expressed tsRNA biomarkers in the plasma of BLCA patients

[0054] RT-qPCR was used to detect the expression levels of 11 plasma tsRNAs among the 19 significantly different tsRNAs marked above in an independent training cohort (training set) consisting of 24 bladder cancer patients and 24 healthy controls (to ensure effective amplification and detection, the primer design of the RT-qPCR experiment needs to target sequences within a certain length range. Due to the length limit of the target sequence, only 11 of the tsRNAs can be evaluated for expression by RT-qPCR) to verify the sequencing results of 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 isolated from 100 μL of plasma from each subject using Trizol LS reagent (Invitrogen, a subsidiary of Thermo Fisher Scientific) and dissolved in 20 μL of DEPC water.

[0056] (2) The total RNA sample (2 μL) of each experimental subject obtained in step (1) was reverse transcribed into complementary DNA (cDNA) by reverse transcription polymerase chain reaction (RT-PCR) using miRNA 1st Strand cDNA Synthesis Kit (by stem-loop) (purchased from Nanjing Novogene Biotechnology Co., Ltd., catalog number MR-101-02). The specific experimental steps are as follows:

[0057] a. Removal of genomic DNA from total RNA samples: Prepare the reaction solution shown in Table 1 in an RNase-free centrifuge tube. After the reaction solution is prepared, gently pipette and mix well, and place in a 42°C water bath for 2 min.

[0058] Table 1 Reaction solution (10 μL)

[0059]

[0060] b. Reverse transcription of total RNA after genomic DNA removal into cDNA: Prepare RT-PCR reaction system in RNase-free centrifuge tube, the system is shown in Table 3, vortex mix after system is prepared, then put into PCR instrument for RT-PCR reaction, the RT-PCR reaction procedure is shown in Table 4, and cDNA is obtained after the reaction is completed. The primer sequences required for reverse transcription of 11 plasma tsRNA into cDNA are shown in Table 5.

[0061] Table 3 Reverse transcription reaction configuration system (20 μL)

[0062]

[0063] Table 4 Reverse transcription reaction procedure

[0064]

[0065] Table 5 Stem-loop primer sequences required for reverse transcription of tsRNA into cDNA

[0066]

[0067]

[0068] (3) Using miRNAUniversal SYBR qPCR Master Mix (purchased from Nanjing Novozyme Biotechnology Co., Ltd., catalog number MQ101-01) in a 7300 real-time fluorescence quantitative PCR system (ABI, Japan), the cDNA obtained in step (2) was used as a template to perform real-time fluorescence quantitative PCR (qPCR) to detect the expression levels of 11 tsRNAs in the plasma of each bladder cancer patient and healthy control. The specific experimental steps are: configure the qPCR reaction system for quantitative detection. After the system is configured, vortex and mix thoroughly, and place it in the qPCR instrument for qPCR reaction. The qPCR reaction system and reaction procedure are shown in Table 6 and Table 7, respectively. The primer sequences required for the cDNA qPCR reaction corresponding to the 11 tsRNAs are shown in Table 8.

[0069] Table 6 qPCR reaction system

[0070]

[0071] Table 7 qPCR reaction procedure

[0072]

[0073]

[0074] Table 8 Primer sequences required for tsRNA qPCR reaction

[0075]

[0076] (4) In order to accurately quantify 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 using this standard curve.

[0077] The expression of 11 target tsRNAs in bladder cancer patients and healthy controls in the training set was statistically analyzed. Figure 2 As shown, it was verified that the expression levels of two tsRNAs: tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 were significantly different between bladder cancer patients and healthy controls, so two tsRNA biomarkers were identified: tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2.

[0078] The differential expression of these two tsRNAs (tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2) was further verified in a larger plasma sample cohort (validation set) consisting of 80 bladder cancer patients and 60 healthy controls. The specific quantitative experimental steps were the same as those of the training set above.

[0079] 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 the healthy control group.

[0080] Example 2 Sensitivity and specificity of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 to BLCA

[0081] In order to verify that the upregulated expression of plasma tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 is specifically associated with bladder cancer, we used RT-qPCR to detect the expression levels of these two tsRNAs in the plasma of patients with other urinary diseases (20 patients with urinary stones, 20 patients with prostate cancer, and 20 patients with renal cancer), and compared them with the expression levels of these two tsRNAs in healthy controls (20 subjects). The specific experimental steps are the same as those of the training set in Example 1.

[0082] 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).

[0083] The experimental results are as follows Figure 4 and Figure 5 As shown, Figure 4 Figure C in the middle shows that the abnormal expression of these two tsRNAs is unique to bladder cancer. Figure 5 The ROC curves showed that both tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 showed high AUC values ​​(0.88 and 0.80, respectively), with tRF-1:28-chrM.Ser-TGA having a sensitivity of 58.33% and a specificity of 91.67%, and tiRNA-1:34-Glu-CTC-1-M2 having a sensitivity of 41.67% and a specificity of 92.7%. In the joint analysis, the combination of the two tsRNAs had a higher AUC (0.93, 95% CI 0.85-0.99) than any single tsRNA, with a sensitivity of 45.8% and a specificity of 95.7%. Previous studies have shown that urine cytology for diagnosing bladder cancer showed an area under the curve (AUC) of 0.694, and both individual tsRNAs and combined tsRNAs showed superior diagnostic performance in detecting bladder cancer compared with urine cytology. These results suggest 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.

[0084] Example 3 Verification of the increase in tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in plasma from BLCA tumor cells

[0085] In order to study whether the upregulation of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in plasma is specifically derived from bladder tumor tissue, we detected their expression levels in bladder tumor tissue (sample size is 60) relative to adjacent non-cancerous tissue (sample size is 36), and the expression levels of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in bladder cancer tissue and its paired plasma from the same bladder cancer patient (sample size is 10) were analyzed for correlation. At the same time, the expression of these two tsRNAs in the culture medium of various bladder cancer cell lines (5637, T24, UMUC3, J82) was further evaluated.

[0086] The experimental results are as follows Figure 6 and Figure 7 As shown, the results showed that the tsRNA levels in tumor tissues were significantly increased compared to adjacent non-cancerous tissues. In in vitro experiments, the expression levels of these tsRNAs were positively correlated with the number of cells and culture time. These in vitro and in vivo experimental results indicate that these two tsRNAs are likely to be released from bladder cancer cells and stably exist in plasma or culture medium.

[0087] Example 4 Correlation between tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in BLCA and Bladder Cancer Development

[0088] In order to explore whether the increase in the levels of two tsRNA tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 in the tumor tissue and plasma of BLCA patients is related to the occurrence and development of BLCA, the expression of two tsRNAs in the plasma of BLCA patients at different stages of the disease (T0-T1 stage sample size 16, ≥T2 stage sample size 10), bladder cancer patients of different grades (low grade, high grade) and bladder cancer patients with or without lymph node metastasis was detected. In addition, 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 also analyzed. Finally, to further elucidate the effects of these two tsRNAs on BLCA cells, these two tsRNA mimics (artificially synthesized tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 oligonucleotides) and oligonucleotide inhibitors of these two tsRNAs 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 (whose expression differences were not significant between bladder cancer patients and healthy controls), were randomly selected, and their mimics and inhibitors were used as negative controls to explore the proliferation and migration abilities of bladder cancer cells using CCK8 and cell scratch experiments.

[0089] The experimental results are as follows Figure 8 , Fig. 9 and Fig.10 As shown, the levels of these two tsRNAs in the plasma of patients with low-grade bladder cancer and early bladder cancer were significantly lower than those in patients with high-grade and advanced bladder cancer. qRT-PCR results showed that the expression of these two tsRNAs in umuc-3 and J82 bladder cancer cells with high malignancy was higher than that in 5637 and T24 bladder cancer cells with low malignancy, which once again confirmed that the expression of these two tsRNAs increased with the increase of the malignancy of tumor cells. Further study of the relationship between the expression of the two tsRNAs and lymph node metastasis showed that the plasma tsRNA expression of patients with lymph node metastasis was significantly higher than that of patients without metastasis. The results of CCK-8 and cell scratch experiments showed that the inhibition of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 significantly reduced the proliferation and migration ability of bladder cancer cells, while transfection mimics produced the opposite effect.

[0090] The above results show that the expression of tsRNA biomarkers tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 increases with the malignancy of tumor cells. Further exploration and confirmation by CCK-8 and cell scratch experiments showed that tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 significantly promoted the proliferation and migration of bladder cancer cells, and may act as tumor-promoting factors. The above results provide a basis for the use of tsRNA as a potential biomarker for the diagnosis and staging of bladder cancer, and at the same time confirm its biological function in bladder cancer.

[0091] 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

[0092] The present invention verifies the in vivo effects of these two tsRNAs in mice through a bladder cancer xenograft model. BLCA subcutaneous xenograft models (T24-BLCA subcutaneous xenograft model mice and UMUC3-BLCA subcutaneous xenograft model mice) were constructed in BALB / c nude mice by subcutaneous injection of bladder cancer cells T24 and UMUC3, respectively. The mice were raised under normal conditions for 2 to 3 weeks to allow the tumor to grow. When the tumor volume of the mice reached 50 to 80 mm 3 At the time of treatment, T24-BLCA subcutaneous xenograft model mice were randomly divided into 3 groups (blank control group, mimic 1 group and mimic 2 group), and UMUC3-BLCA subcutaneous xenograft model mice were randomly divided into 3 groups (blank control group, inhibitor 1 group and inhibitor 2 group), with 5 mice in each group. Mimic 1 group and mimic 2 group were injected intratumorally with tRF-1:28-chrM.Ser-TGA mimic and tiRNA-1:34-Glu-CTC-1-M2 mimic, respectively, inhibitor 1 group and inhibitor 2 group were injected intratumorally with tRF-1:28-chrM.Ser-TGA inhibitor and tiRNA-1:34-Glu-CTC-1-M2 inhibitor, respectively, and blank control group was injected with PBS buffer, with an injection dose of 1 nmol per mouse, once every 2 days for 2 weeks. During the treatment period, tumor volume (V = length × width^2 × 0.52) and body weight were evaluated every 3 days. After 14 days, the mice were sacrificed, plasma was collected from each mouse, and the tumors were removed, weighed, and analyzed.

[0093] The target prediction tools RNAhybrid and Targetscan (www.targetscan.org / vert_80 / ) were used to analyze the target genes of each mouse plasma tsRNA tRF-1:28chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to identify biological processes related to tsRNA target genes (p<0.05, false discovery rate (FDR)<0.05). Finally, after the mouse model was 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 detected. The experimental results are as follows Figures 11 to 14 shown.

[0094] Fig.11 and Fig.12 The results showed that the explant tumor volume of the tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-GluCTC-1-M2 groups was significantly larger than that of the NC group, and there was no significant difference in the body weight of the three groups of mice. 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 levels of triglycerides, total cholesterol, and free fatty acids in tumors and plasma.

[0095] Fig.13 and Fig.14 The results showed that the transplanted 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. In addition, there was no significant difference in the body weight of mice between the three groups. Compared with the control group, tsRNA inhibitor treatment significantly inhibited tumor proliferation after 2 weeks. In terms of lipid metabolism, the results showed that tRF-1:28-chrM.Ser-TGA inhibitor and tiRNA-1:34-Glu-CTC-1-M2 inhibitor could significantly reduce triglyceride, total cholesterol and free fatty acid levels in tumors and plasma.

[0096] The above results indicate that the two tsRNAs may regulate tumor progression by promoting lipid metabolism. The detection of tRF-1:28-chrM.Ser-TGA and tiRNA-1:34-Glu-CTC-1-M2 is expected to identify early high-risk bladder cancer patients, which will help timely treatment, improve the quality of life, and reduce the economic burden on patients and society.

[0097] The present invention provides a biomarker related to bladder cancer and its application ideas and methods. There are many methods and ways to implement the technical solution. The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the protection scope of the present invention. All components not specified in this embodiment can be implemented by existing technologies.

Claims

1. A biomarker associated with bladder cancer, characterized in that: The biomarkers are tsRNA: tRF-1:28-chrM.Ser-TGA and / or tiRNA-1:34-Glu-CTC-1-M2; The nucleotide sequences of the 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. Use of the biomarker according to claim 1 in the preparation of a product for diagnosing bladder cancer.

3. The use according to claim 2, characterized in that: The product is a biochip or a kit.

4. A bladder cancer diagnostic kit, characterized in that: The kit comprises a reagent for detecting the expression amount of the biomarker as claimed in claim 1.

5. The bladder cancer diagnostic kit according to claim 4, characterized in that The kit comprises a primer pair for detecting the expression amount of the biomarker according to claim 1.

6. The bladder cancer diagnostic kit according to claim 5, characterized in that The nucleotide sequences of the forward primer and reverse primer for detecting the expression amount of tRF-1:28-chrM.Ser-TGA are shown in SEQ ID NO.3 and SEQ ID NO.4, respectively; the forward primer and reverse primer for detecting the expression amount of tiRNA-1:34-Glu-CTC-1-M2 are shown in SEQ ID NO.5 and SEQ ID NO.6, respectively.

7. The bladder cancer diagnostic kit according to claim 4, characterized in that: The kit comprises reagents and enzymes used for real-time fluorescence quantitative reverse transcription PCR.

8. The bladder cancer diagnostic kit according to claim 4, characterized in that: The kit comprises reagents for RNA extraction.

9. The bladder cancer diagnostic kit according to claim 4, characterized in that: The kit contains a standard of tRF-1:28-chrM.Ser-TGA and a standard of tiRNA-1:34-Glu-CTC-1-M2.

10. The bladder cancer diagnostic kit according to claim 4, characterized in that: The test sample of the kit is plasma.

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