Application of detection reagent for GDF15 in extracellular vesicles in preparation of prostate cancer diagnosis and / or staging kit

Abstract

The invention belongs to the technical field of in-vitro diagnostic reagents, and particularly relates to application of a detection reagent for GDF15 protein in extracellular vesicles in preparation of a prostate cancer diagnosis and / or staging kit. According to the invention, enrichment and proteomics detection are carried out on plasma EVs of patients with prostatic cancer (PCa) and benign prostatic hyperplasia (BPH), and through bioinformatics analysis, a potential EV protein marker GDF15 which can be used for early diagnosis of PCa is screened for the first time. The GDF15 protein is verified in a plurality of groups of new clinical queues by further adopting an immunological technology and a targeted quantitative mass spectrometry technology, and the distinguishing ability of the GDF15 protein to PCa and BPH and the distinguishing ability of the GDF15 protein to different PCa stages are determined. The method is expected to promote noninvasive precise diagnosis of clinical PCa, and has a good application prospect.

Description

Technical Field

[0001] The present invention belongs to the technical field of in vitro diagnostic reagents, and particularly relates to the use of a reagent for detecting GDF15 in extracellular vesicles in the preparation of a kit for diagnosing and / or staging prostate cancer. Background Art

[0002] Prostate cancer (PCa) is a common malignant tumor in men and is the most common cancer in men. Achieving early diagnosis and staging of prostate cancer can not only improve its clinical decision-making, greatly reduce the over-diagnosis and over-treatment of prostate cancer, but also further elaborate the related pathogenesis and improve the treatment effect, which has important clinical and social value.

[0003] However, the pathogenesis of PCa has not been fully understood, and there is a lack of highly specific diagnostic and treatment markers. At present, the gold standard for diagnosing PCa is prostate biopsy, and the previous screening is mainly based on digital rectal examination (DRE) and serum prostate-specific antigen (PSA) detection. However, biopsy is invasive and traumatic, and there are problems such as misdiagnosis or missed diagnosis; while serum PSA detection has the problem of low specificity. Therefore, there is an urgent clinical need for specific, sensitive and non-invasive biomarkers to assist PSA in the early and accurate diagnosis and staging of prostate cancer, including differentiating prostate cancer from benign prostatic diseases and discriminating different types of prostate cancer (aggressive and indolent cancers).

[0004] Extracellular vesicles (EVs) are an important source of novel biomarkers and are closely related to the occurrence, progression, angiogenesis, metastasis and immune escape of tumors. At present, a series of RNAs and proteins in EVs have the potential for PCa diagnosis. For example, it has been reported that PSA in plasma exosomes has a significantly better ability to distinguish PCa from benign prostatic hyperplasia (BPH) than plasma PSA. Proteins such as ITGA3, ITGB1, TMEM256, Rab3B, LAMTOR1, FABP5 in urine-derived EVs, and proteins such as Claudin 3, EpCAM, Survivin, ephrinA2 in plasma / serum-derived EVs are also potential markers for PCa diagnosis and grading discrimination. However, due to the limited number of clinical cohort samples used in previous studies (usually ≤60 cases), the consistency of the results is not strong, and the discovered candidate markers still need to be verified in a larger cohort. In addition, in order to achieve better diagnostic performance, there is still a need to develop more new EV protein diagnostic markers in this field.

[0005] Growth differentiation factor 15 (GDF15), also known as macrophage inhibitory cytokine 1 (MIC-1), NSAID-activated gene protein 1 (NAG-1), placental TGF-β (PTGFB), placental bone morphogenetic protein and prostate differentiation factor (PDF), is an endocrine hormone and a member of the transforming growth factor-β (TGF-β) superfamily. As a stress-responsive cytokine, GDF15 is widely involved in the pathogenesis of various diseases such as obesity, diabetes, non-alcoholic fatty liver disease, inflammation, cardiovascular diseases, and cancer, and is also an important drug development target. Currently, serum GDF15 has also been reported to have the potential to distinguish prostate cancer (PCa) from benign prostate diseases and to identify different-risk PCa, and combining it with prostate-specific antigen (PSA) or other markers can improve the diagnostic ability for PCa (The Lancet Oncology 2015, 16(16): 1667-1676.; PLOS ONE 2015, 10(4): e0122249.; Scientific Reports 2017, 7(1): 16824.; Theranostics 2021, 11(13): 6214-6224.). However, there are still some controversies regarding the changes in serum GDF15 levels in PCa, and its diagnostic sensitivity and specificity lack comprehensive clinical evaluation, thus limiting its clinical application. Moreover, there are no relevant reports on the research and evaluation of the biological role and diagnostic ability of GDF15 protein in extracellular vesicles (EVs). Summary of the Invention

[0006] In view of the problems in the prior art, the present invention provides a new extracellular vesicle protein biomarker, and further provides the use of a reagent for detecting GDF15 in extracellular vesicles in the preparation of a prostate cancer diagnosis and / or staging kit.

[0007] Use of a reagent for detecting GDF15 in extracellular vesicles in the preparation of a prostate cancer diagnosis and / or staging kit.

[0008] Preferably, the reagent includes a reagent for extracting extracellular vesicles, a reagent for lysing extracellular vesicles, and a reagent for detecting GDF15.

[0009] Preferably, the reagent for extracting extracellular vesicles is selected from the reagent for extracting extracellular vesicles by TiO2 affinity capture method;

[0010] and / or, the reagent for detecting GDF15 is selected from western blot detection reagent, ELISA detection reagent or PRM-MS detection reagent.

[0011] Preferably, the extracellular vesicles are extracted from plasma samples.

[0012] Preferably, the staging is T staging of prostate cancer; or, the staging is to distinguish prostate cancer patients with different Gleason scores.

[0013] The present invention also provides a prostate cancer diagnosis and / or staging kit, which is characterized in that it includes a reagent for detecting GDF15 in extracellular vesicles.

[0014] Preferably, the reagent includes a reagent for extracting extracellular vesicles, a reagent for lysing extracellular vesicles, and a reagent for detecting GDF15.

[0015] Preferably, the reagent for extracting extracellular vesicles is selected from the reagents for extracting extracellular vesicles by TiO2 affinity capture method;

[0016] And / or, the reagent for detecting GDF15 is selected from western blot detection reagent, ELISA detection reagent or PRM-MS detection reagent.

[0017] Preferably, the extracellular vesicles are extracted from plasma samples.

[0018] Preferably, the staging is T staging of prostate cancer; or, the staging is to distinguish prostate cancer patients with different Gleason scores.

[0019] The key of the present invention lies in that it is determined that the content of GDF15 in human EVs is significantly correlated with the risk of prostate cancer, and it has the ability to stage prostate cancer. Therefore, the risk of prostate cancer can be judged by detecting the content of GDF15 in human EVs. As for the specific means of detecting GDF15 in EVs, various means disclosed in the prior art can be adopted, not limited to the specific detection means selected in the embodiments of the present invention. Any method capable of detecting the content of GDF15 in human EVs can be used for the diagnosis and staging of prostate cancer.

[0020] The present invention provides a new prostate cancer EVs protein biomarker and a new prostate cancer diagnosis and / or staging kit, which can realize the effective diagnosis and staging of prostate cancer; and can use plasma as the detection sample, with very low harm to patients. The present invention has good application prospects.

[0021] Obviously, based on the above content of the present invention, according to the common general knowledge and customary means in the art, without departing from the above basic technical idea of the present invention, various other forms of modifications, substitutions or changes can be made.

[0022] The following is a further detailed description of the above content of the present invention in the form of specific embodiments. However, this should not be construed as limiting the scope of the above subject matter of the present invention to the following examples. All technologies implemented based on the above content of the present invention fall within the scope of the present invention. Brief Description of the Drawings

[0023] Figure 1 It is a flow chart of the discovery and verification experiment of EVs protein markers for prostate cancer diagnosis.

[0024] Figure 2 It is the qualitative identification information of plasma EVs proteomics in prostate cancer. (a) The overlap of 1183 plasma EVs proteins identified with the EVs databases VesiclePedia and ExoCarta. (b) The top 100 proteins with EVs abundance in the plasma EVs proteins identified. (c) The results of GO enrichment analysis of the proteins identified. (d) The results of tissue expression and disease enrichment analysis of the proteins identified. (e) The abundance distribution of the proteins identified in plasma. (f) The number of tissue-specific proteins and prostate-specific proteins identified.

[0025] Figure 3 It is the quantitative analysis result of plasma EVs proteomics in prostate cancer. (a) PLS-DA analysis of the two groups of prostate cancer and benign prostatic hyperplasia. (b) Hierarchical clustering analysis and GO_biological process enrichment analysis of 72 proteins with statistical differences in the two groups of PCa and BPH. (c) Volcano plot of protein fold change and corrected p-value. (d) Abundance distribution of differentially expressed proteins in plasma. (e) Correlation analysis of differentially expressed proteins with PSA index.

[0026] Figure 4 It is the screening of candidate markers for prostate cancer diagnosis. (a) Box plot of the mass spectrometry intensity distribution of GDF15 protein in the two groups of BPH and PCa samples. (b) ROC analysis of GDF 15 protein and its AUC value. (c) Box plot of the serum concentration distribution of clinical total PSA in the two groups of BPH and PCa samples. (d) ROC analysis of clinical PSA index and its AUC value.

[0027] Figure 5Verification of DIA-MS quantitative results of GDF15 protein. (a) Schematic diagram of the processed forms of GDF15 protein. (b) Full-length sequence of GDF15 protein, with the signal peptide region, propeptide region, and mature region covered in light red, blue, and yellow respectively, and the sequence marked in red being the sequence of this protein identified by mass spectrometry. (c) WB was used to detect the existence form of GDF15 protein in plasma and EVs and the abundance difference between the PCa and BPH groups. (d) (e) WB was used to compare the abundance difference of GDF15 protein in EVs between the PCa and BPH groups. (f) (g) WB was used to compare the abundance difference of GDF15 protein in plasma between the PCa and BPH groups. (h) ELISA was used to compare the abundance difference of GDF15 protein in EVs between the PCa and BPH groups. *, p < 0.05; n.s., not significant; Student t-test.

[0028] Figure 6 WB cohort verification of GDF15 protein. (a) WB was used to detect the abundance difference of EVs GDF15 between PCa and BPH in the verification cohort. (b) WB was used to detect the level difference of plasma GDF15 between PCa and BPH in the verification cohort. (c) Quantitative comparison of WB optical density values. (d) ROC analysis of EVs GDF15, plasma GDF15, and PSA and the corresponding AUC values.

[0029] Figure 7 ELISA and PRM-MS cohort verification of GDF15 protein. (a) ELISA was used to detect the abundance difference of EVs GDF15 between PCa and BPH in the verification cohort. (b) PRM-MS was used to compare the abundance difference of EVs GDF15 between PCa and BPH in the verification cohort. (c) Correlation analysis of the quantitative results of ELISA and PRM-MS.

[0030] Figure 8 ELISA was used to compare the abundance difference of plasma EV GDF15 in different stages of PCa. (a) Final color development map detected by ELISA. (b) Absorbance values of plasma EV GDF15 detected by ELISA in different T stages of PCa.

[0031] Figure 9 Representative diagrams of immunohistochemical staining results of GDF15 in (a, b) BPH and PCa tissues. (c) Proportion of the positive area of GDF15 in BPH and PCa tissues. PCa was divided into four groups with Gleason scores of 6 (GS6), 7 (GS7), 8 (GS8), and 9 (GS9). Detailed implementation methods

[0032] In the following examples and experimental examples, reagents and raw materials not specifically described are all commercially available products.

[0033] Discrimination ability of GDF15 in EVs from Example 1 for PCa and BPH

[0034] I. Experimental methods

[0035] 1. Main materials and equipment

[0036] Dithiothreitol (DTT), iodoacetamide (IAA), urea, ammonia water, trifluoroacetic acid (TFA), formic acid (FA) and acetonitrile (ACN) were purchased from Merck. Sequencing-grade trypsin and LysC enzyme were purchased from Beijing Meizhiyuan Biotechnology Co., Ltd. TiO2 microspheres were purchased from GL Science. Rabbit anti-human GDF15 antibody was purchased from Abcam (ab206414). iRT standard peptides were purchased from Shanghai Yisuan Biotechnology Co., Ltd. Human GDF15 ELISA detection kit was purchased from Boster Biological (EK0767). Other reagents were all from ThermoFisher or Sigma. The experimental water was Milli-Q purified water.

[0037] High-speed centrifuge, vacuum centrifugal dryer and Orbitrap Fusion Lumos LC-MS were purchased from ThermoFisher. WB chemiluminescence imager was purchased from Shanghai Tianneng.

[0038] 2. Clinical plasma sample information

[0039] Plasma from prostate cancer and benign prostatic hyperplasia patients was sourced from the biobank of West China Hospital, Sichuan University. All patients were diagnosed by prostate biopsy, and the clinical information, including key information such as age, total PSA, free PSA, etc., was collected and sorted out completely, and interfering information, such as having undergone chemotherapy, etc., was excluded. All patients signed the informed consent form for the clinical study and applied for ethics.

[0040] 3. Isolation of plasma EVs from PCa and BPH patients using TiO2 microspheres

[0041] The plasma of patients with prostate cancer (n = 40) and benign prostatic hyperplasia (n = 40) was thawed on ice, mixed well respectively, and then centrifuged (4°C, 13,000 g, 10 min). The TiO2 microspheres were dispersed evenly with TBS. Each 100 μL solution contained 2 mg of microspheres and was divided into 80 portions, 100 μL per portion, that is, 2 mg of microspheres per portion. 100 μL of plasma supernatant was taken from each sample and added to the lid of the centrifuge tube containing the microsphere solution, then mixed uniformly, and then incubated with rotation at room temperature for 10 min for the enrichment of EVs. After the enrichment was completed, centrifugation was carried out (4°C, 300 g, 1 min), the supernatant was removed, and the microspheres were washed three times with TBS solution, 200 μL each time, for 5 min each time. Finally, the washing solution was completely removed, and the microspheres were stored at -80°C.

[0042] 4. Proteomic detection of plasma EVs in PCa and BPH patients

[0043] 15 μL of urea solution containing 10 mM DTT was added to the TiO2 microspheres loaded with EVs, vortexed and sonicated at 4°C for 20 min to lyse the EVs and extract proteins. Then centrifugation was carried out (4°C, 13,000 g, 10 min), and the protein supernatant was transferred to a new centrifuge tube and incubated at 37°C for 4 h to reduce disulfide bonds. Subsequently, IAA was added to a final concentration of 20 mM, and the reaction was carried out in the dark at 25°C for 30 min to block free sulfhydryl groups. After the reaction was completed, the solution was diluted 8-fold with 50 mM ammonium bicarbonate solution, and then 0.5 μg of LysC enzyme was added and incubated at 37°C for 3 h for pre-protease digestion. Finally, 0.5 μg of trypsin was added and the digestion was carried out overnight at 37°C. The resulting peptide solution was acidified with TFA solution to a final concentration of 1%, and desalted with an SPE tip packed with C18 filler. The purified peptide solution was dried completely under vacuum.

[0044] All samples were detected on an Orbitrap Fusion Lumos liquid chromatography-mass spectrometry instrument, and the acquisition mode was the DIA mode. The dried peptides were reconstituted with 10 μL of 0.1% FA aqueous solution, and the synthetic iRT standard peptide mixture was added. Then, 1 μL of each sample was taken and mixed as a quality control sample. 1.0 μg of peptides were loaded, and separation was performed using an EASY-nLC 1200 UPLC system. The chromatographic column was a C18 column (1.9 μm, 75 μm × 25 cm), the flow rate was 300 nL / min, the mobile phase was 0.1% FA water (phase A) and 0.1% FA 80% ACN (phase B), and the separation gradient was 0 - 4 min, 3 - 8% phase B; 4 - 60 min, 8 - 28% phase B; 60 - 70 min, 28 - 38% phase B; 70 - 71 min, 38 - 95% phase B; 71 - 78 min, 95% phase B. The mass-to-charge ratio acquisition range for the first-order mass spectrometry was 350 - 1500. In the DIA acquisition mode, each cycle included one full scan plus 42 segmented windows. The specific mass spectrometry parameters were as follows: the MS1 Orbitrap resolution was 60,000, the scanning range was 350 - 1500, the RF lens was 40%, the AGC target was 4.0E5, and the maximum injection time was 50 ms. The MS2 HCD collision energy was 30%, the Orbitrap resolution was 15,000, the scanning range was 150 - 2000, the RF lens was 40%, the AGC target was 3.0E5, and the maximum injection time was 22 ms. Every 10 samples, a sample quality control and a HeLa cell peptide quality control were inserted to monitor the instrument status.

[0045] 5. Proteomics Data Processing and Bioinformatics Analysis

[0046] We used Spectronaut software (version 16; Biognosys) to process the raw mass spectrometry data for protein identification and quantification. The database search mode was Direct DIA analysis, and the database used was Swissprot (human; 2020_08; 20,368 entries). The iRT standard peptides were used for retention time correction. Trypsin and LysC were set as proteases, the number of missed cleavage sites was set to 2, cysteine carbamidomethylation (+57.02 Da) was set as a fixed modification, methionine oxidation (+15.99 Da) and protein N-terminal acetylation (+42.01 Da) were set as variable modifications, and the FDR for PSM, peptide, and protein identification was all set to <1%. Bioinformatics analyses, including data normalization, missing value imputation, hypothesis testing, partial least squares discriminant analysis, hierarchical clustering analysis, volcano plot analysis, GO enrichment analysis, ROC analysis, etc., were all performed using the Wukong Cloud Data Analysis Platform based on the R language and R software (version 4.1.0).

[0047] 6. Screening and validation of candidate biomarkers

[0048] Based on the AUC value of the ROC curve, we screened out growth differentiation factor 15 (GDF15) as a candidate biomarker and further validated it.

[0049] (1) WB validation

[0050] First, in a new set of cohorts (validation cohort 1, 20 PCa cases, 20 BPH cases), WB was used to detect GDF15 in plasma EVs and plasma to examine the differences between the PCa and BPH groups. The specific operation was as follows: For the EVs enriched by TiO2, 20 μL of gel loading buffer containing SDS and DTT was added, vortexed thoroughly, and boiled at 95 degrees for 10 min for protein extraction and denaturation. Then, centrifugation was performed (4 degrees, 13,000 g, 10 min), and 2 μL of the supernatant was taken from each sample and mixed evenly as a quality control sample to correct the errors in each WB experiment operation and development, thus facilitating the comparison of experimental results from different batches. For plasma samples, 1 μL of plasma was taken from each sample, 19 μL of loading buffer was added, and the same heating denaturation and centrifugation were carried out, and 2 μL of the supernatant was taken from each and mixed to form a quality control sample.

[0051] For each sample, 10 μL of equal volume was loaded, and SDS-PAGE gel electrophoresis was performed (constant voltage of 120 V, 70 min). Each gel contained one quality control sample and eight experimental samples. After electrophoresis, the proteins were electrotransferred from the gel to a PVDF membrane (constant current of 350 mA, 90 min). The membrane was blocked with TBST solution containing 5% (w / v) non-fat milk powder at room temperature for 1 h, and then incubated with rabbit anti-human GDF15 antibody overnight at 4 °C. After incubation, the membrane was washed four times with TBST for 5 min each time, and then incubated with horseradish peroxidase-conjugated secondary antibody (room temperature, 1 h). After washing the membrane four times with TBST, enhanced chemiluminescence solution was used to develop and image the protein bands. Finally, ImageJ software (version 1.4) was used to process the images and extract the optical density values. The protein optical density values of each sample were normalized relative to the quality control sample in the same run to obtain the relative intensity.

[0052] (2) ELISA verification

[0053] In a new set of cohorts (validation cohort 2, PCa 37, BPH 33), ELISA was used to detect GDF15 in plasma EVs and investigate its differences between the PCa and BPH groups. Specifically, for the EVs enriched by TiO2, 20 μL of mild lysis buffer (mainly composed of 20 mM Tris, 150 mM NaCl, 1% Triton X-100, 1% NP-40, pH 7.5 and protease inhibitor cocktail) was added, vortexed thoroughly, and sonicated at 4 °C for 20 min to lyse and extract proteins. Then, centrifugation was performed (4 °C, 13,000 g, 10 min), the supernatant was transferred to a new centrifuge tube, and diluted to 100 μL with the sample diluent in the ELISA kit for ELSIA detection. The subsequent operation steps were carried out completely according to the kit instructions, and finally, the absorbance at 450 nm was measured using a microplate reader.

[0054] (3) PRM-MS verification

[0055] The validation cohort 2 was also used to target and detect the peptides of GDF15 by PRM-MS to examine the differences between the PCa and BPH groups. Specifically, the SpectroDive software (version 10.4; Biognosys) was first used to process the original DIA-MS mass spectrometry data collected in Part 4 for library construction, selection of peptide parent-child ion pairs, and determination of the peptide parameters for PRM-MS detection. Then, the peptide samples were prepared according to the sample pretreatment steps of proteomics in Part 4. After reconstitution, iRT standard peptides were added, and 1 μL of each solution was also taken and mixed into a quality control sample. All samples were detected on an Orbitrap Fusion Lumos liquid chromatography-mass spectrometry instrument in the PRM mode. 1.0 μg of peptides were loaded, and separation was performed using an EASY-nLC 1200 UPLC system with a C18 column (1.9 μm, 75 μm × 25 cm), a flow rate of 300 nL / min, and mobile phases of 0.1% FA water (phase A) and 0.1% FA 80% ACN (phase B). The separation gradient was shorter than that of DIA-MS, being 0 - 30 min, 5 - 28% phase B; 30 - 35 min, 28 - 38% phase B; 35 - 35.5 min, 38 - 95% phase B; 35.5 - 43 min, 95% phase B. PRM was in the time schedule acquisition mode with a total of 27 peptides, and the retention time window was set at ±2 min. The specific mass spectrometry parameters were as follows: the MS1 Orbitrap resolution was 60,000, the scan range was 350 - 1550, the RF lens was 40%, the AGC target was 1.0E6, and the maximum injection time was 100 ms. For MS2, the quadrupole isolation window was m / z 1.6, the HCD collision energy was 30%, the Orbitrap resolution was 15,000, the scan range was 150 - 1800, the RF Lens was 40%, the AGC target was 5.0E5, and the maximum injection time was 80 ms. Every 10 samples, a sample quality control and a HeLa cell peptide quality control were inserted to monitor the instrument status. The finally obtained original mass spectrometry data was processed using the SpectroDive software to export the intensity data of proteins and peptides.

[0056] II. Experimental Results

[0057] 1. Qualitative Analysis of Proteomics of Prostate Cancer Plasma EVs

[0058] The discovery cohort for plasma EVs proteomics analysis consisted of a total of 80 samples, including 40 in the PCa group and 40 in the BPH group.

[0059] The experimental procedure was as Figure 1As shown, in this example, the TiO2 affinity capture method was used to extract EVs. The plasma used for each sample was 100 μL, the TiO2 was 2 mg, and the incubation condition was to rotate and mix evenly at room temperature for 10 min. It can be seen that this method uses less materials, is simple and fast to operate, and is suitable for high-throughput analysis of clinical large cohort samples. The obtained EVs were lysed and pretreated with proteins to obtain peptide segments, and then DIA mode was used for mass spectrometry detection.

[0060] A total of 1183 proteins were identified, of which 1026 proteins belonged to EV proteins ( Figure 2 a), and 79 common high-abundance EV proteins were identified ( Figure 2 b). GO analysis also showed that the main cellular components enriched by these proteins were extracellular exosomes, the molecular function was calcium ion binding, and the biological processes included signal transduction, immune response, etc., all of which were closely related to the properties and functions of EVs ( Figure 2 c). At the same time, we also performed tissue expression and disease enrichment analysis of these proteins. The results showed that these proteins were mainly related to plasma and were closely related to liver and prostate diseases ( Figure 2 d). The abundances of these proteins in plasma also covered the regions from high abundance to low abundance ( Figure 2 e). We further compared with the Human Protein Atlas database to view the tissue specificity of these proteins ( Figure 2 f). A total of 229 tissue-specific proteins were identified, including 113 liver-specific ones because many proteins in plasma are derived from the liver, and 3 prostate-specific ones. These proteins have also been found in prostate cancer urine exosomes in previous studies. The above qualitative information indicates that the proteins we identified can better reflect the characteristics of the samples.

[0061] 2. Quantitative analysis of proteomics of plasma EVs in prostate cancer

[0062] We continued to view the quantitative information of the proteins. Through statistical analysis, we found 72 proteins with statistical differences, that is, the corrected p-value < 0.05. These proteins were used for PLS-DA analysis to view the discrimination between the PCa and BPH groups. Due to the particularity of clinical samples, first, there may be strong heterogeneity among individuals within the same group. Second, the two disease states of PCa and BPH themselves have certain similarities, so theoretically, it is difficult to distinguish between them. And as Figure 3 a shows, in this study, PCa and BPH showed significant differences and could be clearly divided into two groups. In addition, hierarchical clustering analysis also showed that although there was a certain degree of heterogeneity within the group, the PCa and BPH groups still showed obvious discrimination ( Figure 3b). Meanwhile, we examined the functions of the up- and down-regulated proteins and found that the proteins down-regulated in PCa were mainly involved in biological processes such as platelet degranulation, receptor-mediated endocytosis, and blood coagulation, while the up-regulated proteins were mainly involved in processes such as extracellular matrix organization, skeletal system development, regulation of cell migration, and regulation of immune response. These are all related to blood and extracellular matrix and are also common functions of EVs.

[0063] We further incorporated fold change information to screen for differentially expressed proteins, setting the adjusted p-value < 0.05 and fold change > 1.5 or < 0.667 as the screening criteria, and obtained 27 differentially expressed proteins, including 18 up-regulated proteins and 9 down-regulated proteins ( Figure 3 c). These proteins can all be used as potential PCa-related biomarkers.

[0064] We examined the abundances of these 27 proteins in plasma. As Figure 3 shown in d, these proteins were mainly distributed in the medium and high abundance regions, which is very beneficial for the subsequent verification of our biomarkers. In addition, we also performed a correlation analysis of these 27 proteins with the clinical PSA index to examine their correlation with PSA ( Figure 3 e). The results showed that only four proteins had a significant correlation with PSA (p < 0.05). Among them, three proteins, such as GDF15, had a positive correlation with PSA, but the correlation was weak (correlation coefficient r = 0.20 - 0.35). This suggests that these three proteins may have a certain complementarity with PSA in the diagnosis of prostate cancer and may be able to assist in PSA diagnosis.

[0065] 3. Screening of candidate EV protein biomarkers for prostate cancer diagnosis

[0066] Generally speaking, up-regulated proteins are more suitable as diagnostic biomarkers, so we focused on up-regulated proteins. To further screen for EV biomarkers, we compared the 18 up-regulated proteins with the EV database and screened out 12 EV proteins. Subsequently, we performed ROC analysis to evaluate the diagnostic ability of these proteins and summarized the area under the ROC curve (AUC) of each protein to compare their diagnostic effects. Among them, the GDF15 protein had an AUC value of 0.908, showing the best performance ( Figure 4 a and b). And the preliminary results showed that GDF15 had a better diagnostic ability than the classic PSA ( Figure 4 c and d). Combining the weak positive correlation between GDF15 and PSA above, we initially regarded it as a candidate biomarker.

[0067] 4. Verification of candidate EV protein biomarkers

[0068] GDF15 protein was selected as a candidate biomarker and verified. First, we confirmed the proteomic quantitative results of the discovery cohort.

[0069] There are multiple splicing and processing forms of GDF15 protein, including full-length GDF15 with a signal peptide, Pro-GDF15 with a propeptide, mature dimers and monomers ( Figure 5 a and b). Generally speaking, the main form circulating in plasma is the cleaved mature dimer. WB results showed that the main form of GDF15 in plasma is the mature dimer, with a small amount of Pro-GDF15; different from plasma, mature dimers exist in EVs, and at the same time, there is also obvious Pro-GDF15, and the content of the latter is even more than that of the former. In addition, there is a small amount of mature monomer in some PCa plasma EVs ( Figure 5 c). These differences may be related to the biosynthetic pathway of EVs. Correspondingly, the peptide segments of this protein identified by mass spectrometry in EVs also have sequences in both the propeptide region and the mature region ( Figure 5 b), which is consistent with the WB results. Further, five PCa and BPH samples were randomly selected from the discovery cohort to verify the quantitative results of DIA-MS. WB results showed that GDF15 in EVs was significantly different between the two groups, and its content was higher in the PCa group ( Figure 5 d and e), which is consistent with the trend of mass spectrometry quantitative results. Interestingly, the content of this protein in the plasma of the two groups is similar and there is no significant difference ( Figure 5 f and g).

[0070] At the same time, we also used an ELSIA kit to compare the content of GDF15 protein in EVs of the two groups, and the level of the PCa group was also higher ( Figure 5 h), which is consistent with the WB and proteomic detection results. Taken together, we confirmed the GDF15 quantitative results of proteomics.

[0071] To further determine the diagnostic potential of GDF15 protein, we conducted a more in-depth verification in a new clinical cohort.

[0072] First, we used traditional WB to compare the content differences of plasma GDF15 and plasma EVs GDF15 between the PCa and BPH groups. The WB validation cohort included 40 samples, 20 for each of PCa and BPH. It can be preliminarily seen from the WB figure that the content of EVs_GDF15 protein in the PCa group is generally higher than that in the BPH group, while the plasma GDF15 content in the two groups is similar. Figure 6a and b). Further, the gray values of the Western blots were quantitatively compared. The pooled samples of all samples were used as quality controls, namely EVs QC and Plasma QC. The gray value of each Western blot was normalized with reference to the QC sample of that time, so as to obtain the relative intensity of each sample. As shown in Figure 6 c, the abundance of GDF15 protein in EVs of the PCa group was significantly higher than that in the BPH group, while there was no significant difference in its levels in the plasma of the two groups. It can be seen that GDF15 in plasma cannot be used as an effective diagnostic marker for prostate cancer, which also reflects the superiority of analyzing EVs. Subsequently, we performed ROC analysis with the WB intensity values ( Figure 6 d), and the results showed that the diagnostic effect of GDF15 protein in EVs was similar to the previous mass spectrometry quantitative results, superior to plasma GDF15 protein, and also superior to the clinical PSA index, preliminarily verifying the ability of this protein to distinguish PCa and BPH.

[0073] Furthermore, we used two highly efficient verification methods for protein markers, ELISA and PRM-MS, to verify the diagnostic ability of GDF15 protein in the second validation cohort. The validation cohort 2 included 70 samples, among which, 37 were PCa and 33 were BPH. The ELISA test results showed ( Figure 7 a) that there were obvious differences between the PCa and BPH groups, and the content of GDF15 in EVs of the PCa group was significantly higher than that in the BPH group. At the same time, we also found that compared with the BPH group, the distribution range of the detection values in the PCa group was wider, indicating stronger intra-group heterogeneity. The trend presented by the PRM-MS test results was similar to that of ELISA ( Figure 7 b), and the protein abundance in the PCa group also increased significantly, and its intra-group heterogeneity was stronger. And the results of ELISA and PRM-MS had a strong correlation (correlation coefficient was 0.909, Figure 7 c), which also indicated the reliability of these two orthogonal detection methods, and at the same time verified the ability of GDF15 protein to distinguish PCa and BPH.

[0074] In summary, in this example, according to the detection results of the plasma EVs proteomics of PCa patients, proteins that were different from those of patients with benign prostatic hyperplasia were screened out. By comparing the performance of these proteins in PCa diagnosis (ROC analysis), the best candidate marker, GDF15 protein, was determined. The diagnostic ability of GDF15 protein was verified in a new clinical cohort, and it was found that GDF15 in plasma could not be used as a diagnostic marker for prostate cancer, while GDF15 in EVs could be used for prostate cancer diagnosis.

[0075] Example 2 Discrimination Ability of GDF15 for Different Stages of PCa

[0076] I. Experimental Method

[0077] 1. Main materials and equipment

[0078] The TiO2 microspheres were purchased from GL Science. The rabbit anti-human GDF15 antibody was purchased from Abcam (ab206414). The human GDF15 ELISA detection kit was purchased from Boster Biological Technology (EK0767). Other reagents were all from ThermoFisher or Sigma. The experimental water was Milli-Q purified water. The high-speed centrifuge was purchased from ThermoFisher. The slide scanner was Olympus VS200.

[0079] 2. Clinical sample information

[0080] The plasma of prostate cancer patients was sourced from the biobank of West China Hospital, Sichuan University. The radical prostatectomy tissue specimens of prostate cancer and benign prostatic hyperplasia patients were from the Department of Pathology, West China Hospital, Sichuan University. All patients were diagnosed by prostate biopsy, and the clinical information, including key information such as age, total PSA, free PSA, etc., was collected and sorted out completely, and interfering information such as having received chemotherapy was excluded. All patients signed the informed consent form for the clinical study and applied for ethics.

[0081] 3. Isolation of EVs from plasma of PCa patients using TiO2 microspheres

[0082] The plasma of prostate cancer patients at different stages (T2, n = 8; T3a, n = 6; T3b, n = 8) was thawed on ice, mixed well respectively, and then centrifuged (4°C, 13,000 g, 10 min). The TiO2 microspheres were dispersed evenly with TBS, with 2 mg of microspheres in every 100 μL of solution, divided into 22 portions, 100 μL per portion, that is, 2 mg of microspheres per portion. 100 μL of plasma supernatant was taken from each sample and added to the lid of the centrifuge tube containing the microsphere solution, then mixed uniformly, and then incubated with rotation at room temperature for 10 min for the enrichment of EVs. After the enrichment was completed, centrifugation was carried out (4°C, 300 g, 1 min), the supernatant was removed, and the microspheres were washed three times with TBS solution, 200 μL each time, for 5 min each time. Finally, the washing solution was completely removed, and the microspheres were stored at -80°C.

[0083] 4. ELISA detection of plasma EV GDF15

[0084] The ELISA detection steps of plasma EV GDF15 in PCa patients at different stages were the same as those in part (2) "ELISA verification" of part 6 in "1. Experimental methods" of Example 1.

[0085] 5. Immunohistochemical detection of the expression of GDF15 in BPH and PCa tissues

[0086] Surgical radical tissue specimens of formalin-fixed paraffin-embedded PCa and BPH patients were first sectioned and then baked at 65 °C for 2 h. The baked sections were dewaxed in xylene and then rehydrated in ethanol with different concentration gradients. After antigen repair and blocking of the tissue sections, they were incubated overnight at 4 °C with GDF15 antibody diluted 1:100. After incubation, they were washed three times with PBS and then incubated with HRP-conjugated secondary antibody. After washing again with PBS, diaminobenzidine was added for color development, and then hematoxylin counterstaining, dehydration and mounting were performed. The stained sections were scanned and imaged with an Olympus VS200 slide scanner at a magnification of 20 times. The acquired images were viewed using Olympus OlyVIA software (version 4.1) and processed using Fiji software (version 1.54f) to obtain the area of the GDF15-positive region and the area of the glandular region, and then the former was divided by the latter to obtain the proportion of the GDF15-positive region area, which can be used for quantitative comparison of the expression levels of GDF15 in different tissues.

[0087] II. Experimental results

[0088] As Figure 8 shown, the discrimination ability of plasma EV GDF15 for different stages of PCa was preliminarily investigated by ELISA experiment. The results showed that the content of GDF15 in plasma EV was significantly higher at the T3a stage than at the T2 and T3b stages, showing the potential for stage discrimination.

[0089] In addition, immunohistochemistry was used in this experimental example to examine the expression of GDF15 in the prostate tissues of BPH and PCa patients. The results showed that GDF15 was mainly distributed in the duct cells of the prostate gland and was also partially secreted into the amyloid bodies. It can be seen from the stained pictures that GDF15 was highly expressed in PCa tissues, while the expression level was low in BPH ( Figure 9 a and b). We further quantitatively calculated the proportion of the GDF15-positive region area in BPH and PCa tissues. Among the PCa groups, they were further divided into four groups according to the Gleason score, namely 6 points (GS6), 7 points (GS7), 8 points (GS8) and 9 points (GS9). The quantitative results showed that the expression level of GDF15 in PCa tissues was significantly higher than that in BPH. More importantly, the expression levels of GDF15 in the 7-point and 8-point PCa groups were significantly higher than those in the 6-point group ( Figure 9 c), showing its ability to distinguish different pathological stages of PCa.

[0090] In summary, as can be seen from the results of this example, the content of GDF15 in plasma EVs can be used to distinguish PCa patients in the T3a stage from those in other stages; and the level of GDF15 in prostate tissue can be used to distinguish PCa patients with different Gleason scores. Therefore, the content of GDF15 can be used for staging discrimination of PCa patients.

[0091] Example 3 Prostate Cancer Diagnosis and / or Staging Kit

[0092] I. Kit Composition

[0093] Detection kit (for 10 people):

[0094] The WB detection kit consists of three parts: reagents for extracting extracellular vesicles, reagents for lysing extracellular vesicles, and reagents for detecting GDF15. Among them,

[0095] The reagents for extracting extracellular vesicles include:

[0096] Component Specification <![CDATA[TiO2 microspheres]]> 20 mg / tube 10×TBS buffer 1 mL / tube

[0097] The reagents for lysing extracellular vesicles include:

[0098]

[0099] The reagents for detecting GDF15 include:

[0100]

[0101] II. Kit Usage Method

[0102] For the usage method of the kit, refer to Part 3 and Part 6 of "I. Experimental Method" in Example 1.

[0103] Example 4 Prostate Cancer Diagnosis and / or Staging Kit

[0104] I. Kit Composition

[0105] Detection kit (for 10 people):

[0106] The ELISA detection kit consists of three parts: reagents for extracting extracellular vesicles, reagents for lysing extracellular vesicles, and reagents for detecting GDF15. Among them,

[0107] The reagents for extracting extracellular vesicles include:

[0108]

[0109]

[0110] The reagents for lysing extracellular vesicles include:

[0111]

[0112] The reagents for detecting GDF15 include:

[0113] Component Specification ELISA kit One

[0114] II. Method for using the kit

[0115] The method for using the kit refers to Part 3 and Part 6 of the "I. Experimental method" section in Example 1.

[0116] Example 5 Prostate cancer diagnosis and / or staging kit

[0117] I. Composition of the kit

[0118] Detection kit (for 10 people):

[0119] The PRM-MS detection kit consists of three parts: reagents for extracting extracellular vesicles, reagents for lysing extracellular vesicles, and reagents for detecting GDF15. Among them,

[0120] The reagents for extracting extracellular vesicles include:

[0121] Component Specification <![CDATA[TiO2 microspheres]]> 20 mg / tube 10×TBS buffer 1 mL / tube

[0122] The reagents for lysing extracellular vesicles include:

[0123]

[0124] The reagents for detecting GDF15 include:

[0125]

[0126]

[0127] II. Method for using the kit

[0128] The method for using the kit refers to Part 3 and Part 6 of the "I. Experimental method" section in Example 1.

[0129] As can be seen from the above examples, the present invention provides an EV protein marker GDF15, which can be used for the early diagnosis of PCa and can stage PCa. The present invention can promote the non-invasive and accurate diagnosis of PCa in clinical practice and has good application prospects.

Claims

Use of a reagent for detecting GDF15 in extracellular vesicles in the preparation of a kit for diagnosing and / or staging prostate cancer.

2. The use according to claim 1, wherein: The reagent includes a reagent for extracting extracellular vesicles, a reagent for lysing extracellular vesicles, and a reagent for detecting GDF15.

3. The use according to claim 2, characterized in that: The reagent for extracting extracellular vesicles is selected from reagents for extracting extracellular vesicles by TiO2 affinity capture method; and / or, the reagent for detecting GDF15 is selected from western blot detection reagents, ELISA detection reagents or PRM-MS detection reagents.

4. The use according to claim 1, characterized in that: The extracellular vesicles are extracted from plasma samples.

5. The use according to claim 1, characterized in that: The staging is to perform T staging on prostate cancer; or, the staging is to distinguish prostate cancer patients with different Gleason scores.

6. A prostate cancer diagnosis and / or staging kit, characterized in that: It includes a reagent for detecting GDF15 in extracellular vesicles.

7. The kit according to claim 6, characterized in that: The reagent includes a reagent for extracting extracellular vesicles, a reagent for lysing extracellular vesicles, and a reagent for detecting GDF15.

8. The kit according to claim 7, characterized in that: The reagent for extracting extracellular vesicles is selected from reagents for extracting extracellular vesicles by TiO2 affinity capture method; and / or, the reagent for detecting GDF15 is selected from western blot detection reagents, ELISA detection reagents or PRM-MS detection reagents.

9. The kit according to claim 1, characterized in that: The extracellular vesicles are extracted from plasma samples.

10. The kit according to claim 1, characterized in that: The staging is to perform T staging on prostate cancer; or, the staging is to distinguish prostate cancer patients with different Gleason scores.

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