Application of L-1-pyrrolino-3-hydroxy-5-carboxylic acid as a serum biomarker

Abstract

This invention discloses the application of L-1-pyrrolline-3-hydroxy-5-carboxylic acid as a serum biomarker, specifically its use in the preparation of a kit for evaluating the therapeutic effect of mesenchymal stem cells (MSCs) on primary sclerosing cholangitis (PSC). The serum biomarker was obtained through multi-timepoint differential metabolite identification, key enzyme and gene validation, correlation screening, and machine learning screening. The invention also discloses P4HA2 as a potential target of mesenchymal stem cells. This invention provides a reference basis for subsequent clinical decision-making in mesenchymal stem cell transplantation therapy and offers new theoretical and data support for mesenchymal stem cell therapy for PSC.

Description

Technical Field

[0001] This invention belongs to the field of medical technology and relates to the application of L-1-pyrrolline-3-hydroxy-5-carboxylic acid as a serum biomarker, specifically involving the screening and application of biomarkers for evaluating the efficacy of human placental-derived mesenchymal stem cell therapy in a mouse model of primary sclerosing cholangitis. Background Technology

[0002] Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease characterized by damage to the intrahepatic or extrahepatic bile ducts, or both. The disease process often involves the interaction of inflammation, fibrosis, and cholestasis. To date, several drugs targeting bile components, immunomodulation, fibrosis, or the gut microbiome have been used in PSC patients, but liver transplantation remains the only curative treatment. However, several factors must be considered before liver transplantation, including the recipient's age, comorbidities, extrahepatic tumors, and economic factors, and the risk of relapse within 10 years after transplantation is approximately 20%. Therefore, a new treatment method is urgently needed.

[0003] Mesenchymal stem cells (MSCs) are stromal cells with self-renewal capacity and exhibiting multi-lineage differentiation, which can be isolated from various tissues. In recent years, cell therapy, especially human placental-derived MSC therapy, has become a promising treatment method due to its abundant source, simple isolation methods, strong proliferative capacity, and low immunogenicity, attracting significant research attention. Placental-derived MSCs (hP-MSCs) are located in the fetal membranes of the full-term placenta and can be easily and non-invasively collected. Current research has explored the therapeutic potential of MSCs in mouse and organoid models of primary sclerosing cholangitis (PSC), finding that MSCs can improve PSC-induced bile duct hyperplasia, pericholangiofibrosis, and inflammation. These results, to some extent, validate the safety and efficacy of this treatment. However, it remains unclear how MSCs affect the metabolic patterns within PSC models. Furthermore, individual responses to MSC treatment vary significantly; not everyone responds positively to cell therapy. Therefore, identifying biomarkers that can be used to assess the preclinical safety and efficacy of MSC transplantation for PSC treatment is crucial; however, currently, no biomarkers for the efficacy of mesenchymal stem cell therapy in primary sclerosing cholangitis have been reported. Summary of the Invention

[0004] The first objective of this invention is to address the shortcomings of the prior art by providing the use of L-1-pyrroline-3-hydroxy-5-carboxylic acid as a serum biomarker in the preparation of a kit for evaluating the therapeutic effect of mesenchymal stem cells on primary sclerosing cholangitis.

[0005] Preferably, the content of L-1-pyrrolidone-3-hydroxy-5-carboxylic acid is positively correlated with the severity of primary sclerosing cholangitis.

[0006] As a preferred option, the target of mesenchymal stem cells in the treatment of primary sclerosing cholangitis is the proline 4-hydroxylase encoding gene P4HA2.

[0007] Preferably, the kit uses serum as the test sample.

[0008] A second objective of this invention is to provide a kit for evaluating the therapeutic effect of mesenchymal stem cells on primary sclerosing cholangitis, the kit comprising a reagent for detecting L-1-pyrrolline-3-hydroxy-5-carboxylic acid.

[0009] A third object of the present invention is to provide the use of a reagent for detecting L-1-pyrrolline-3-hydroxy-5-carboxylic acid in the preparation of products for evaluating the therapeutic effect of mesenchymal stem cells on primary sclerosing cholangitis.

[0010] Preferably, the product includes a reagent kit, a chip, and a test strip.

[0011] The beneficial effects of this invention are:

[0012] This invention provides a novel serum biomarker, L-1-pyrrolline-3-hydroxy-5-carboxylic acid, which can be used to evaluate the therapeutic effect of mesenchymal stem cells (MSCs) on primary sclerosing cholangitis (PSC). Through serum metabolomics analysis and molecular biological experiments, this invention identifies the main altered metabolic pathways and substances in the body after MSC transplantation. Molecular biological verification of key enzymes and genes in these metabolic pathways reveals potential targets for MSC therapy. Through multi-timepoint metabolomics data analysis, and further screening using correlation analysis and machine learning, L-1-pyrrolline-3-hydroxy-5-carboxylic acid was ultimately obtained as a biomarker for evaluating the efficacy of MSC therapy for PSC. This provides a reference for subsequent clinical decision-making regarding MSC transplantation therapy. Attached Figure Description

[0013] Figure 1 These are multivariate statistical results of metabolomic characteristics labeled with two isotopes. A is a two-dimensional PCA score plot labeled with DNS; B is a two-dimensional PCA score plot labeled with DmPA; C is a three-dimensional OPLS-DA score plot labeled with DNS; and D is a three-dimensional OPLS-DA score plot labeled with DmPA.

[0014] Figure 2 This is a bubble chart based on the quantitative enrichment of metabolic pathways of 41 differentially screened metabolites.

[0015] Figure 3 This is the relative expression result of liver mRNA of the proline 4-hydroxylase encoding gene P4HA2.

[0016] Figure 4 The results are the correlation analysis results of L-1-Pyrroline-3-hydroxy-5-carboxylic acid with ALT, AST and ALP, where A is ALT, B is AST and C is ALP.

[0017] Figure 5 It represents the relative content of L-1-Pyrroline-3-hydroxy-5-carboxylic acid at four time points: 8 weeks, 10 weeks, 12 weeks, and 16 weeks.

[0018] Figure 6 The results are based on machine learning analysis of the metabolic characteristics of L-1-Pyrroline-3-hydroxy-5-carboxylic acid. A is the training set, and B is the test set. Detailed Implementation

[0019] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings. It should be noted that the specific embodiments are only a detailed description of the present invention and should not be regarded as a limitation of the present invention.

[0020] Example 1

[0021] MDR2 - / - Mice are currently the most commonly used transgenic PSC animal model, and their liver morphological changes are highly similar to those of human sclerosing cholangitis. This invention uses MDR2- / - Mice simulating PSC, with 12 MDR2 mice in the normal group. + / + MDR2 mice were divided into three groups: the model group and the treatment group, with 15 mice in each group. - / - Mice. Using 8 weeks of age as baseline, at 8 weeks, the normal control group and the model group were injected via tail vein with 100 μL of phosphate-buffered saline (PBS), while the treatment group was injected via tail vein with 5 × 10⁻⁶ μL of PBS. 5 hP-MSCs / 100μL PBS. Serum samples were collected from mice at 8, 10, 12, and 16 weeks of age, and then analyzed by LC-MS. Subsequent experimental validations were performed based on metabolic pathways.

[0022] 1. Serum sample pretreatment: Serum and methanol were mixed at a ratio of 1:3 and incubated at -80°C for 5 minutes to allow for complete reaction. The mixture was then removed and centrifuged at 15,000 rpm for 30 minutes at 4°C. The supernatant was lyophilized to obtain a powder containing serum metabolites. Additionally, 80 μL of each sample was aspirated for use as a mixed sample. The metabolite powder from the mixed sample was obtained using the same procedure and stored at -80°C. DmPA-labeled samples were extracted with 150 μL of ethyl acetate.

[0023] 2. Danylation labeling: using 12 C-dansyl chloride labeling of individual samples, using 13 C-Dansulfonyl chloride / labeled mixed sample (Pooled sample). A total of 25 μL of metabolic extract was mixed with 12.5 μL of sodium carbonate / sodium bicarbonate buffer (0.5 M, pH 9.5) and 12.5 μL of acetonitrile. After vortexing, 25 μL of freshly prepared... 12 C-dansyl chloride solution (20 mg / mL) or 13 C-Dansulfonyl chloride solution (20 mg / mL) was vortexed and centrifuged for 10-15 s. The reaction system was then placed in a 40°C water bath for 1 hour. To completely quench any remaining dansulfonyl chloride, 5 μL of sodium hydroxide solution (250 mM) was added after the reaction was complete, and the mixture was incubated at 40°C for another 10 minutes. Finally, 25 μL of formic acid was added to consume excess NaOH and acidify the solution.

[0024] DmPA marking: 12 C-DmPA labeling of individual samples, using 13 C-DmPA labeled mixed samples. Triethylamine (TEA) was added to 22.5 μL of serum metabolites dissolved in 80% ACN solution, vortexed, and then 12.5 μL of [unspecified ingredient] was added. 12 C-DmPA or 13 C-DmPA (20 mg / mL) was mixed again, centrifuged for 10-15 seconds, and then reacted at 80°C for 1 hour.

[0025] Both of the above-mentioned quality control (QC) samples were prepared by mixing samples of the same molar mass. 12 C mark and 13 The mixture of C-labeled samples was prepared.

[0026] 3. LC-UV: An LC-UV quantification step is performed before quality analysis to control the amount of sample used for metabolomic comparison (i.e., sample normalization).

[0027] The liquid chromatography setup conditions are as follows:

[0028] Liquid Chromatography Instrument: Ultra-high performance liquid chromatograph equipped with a photodiode array detector (Agilent, Palo Alto, CA)

[0029] Ultraviolet detector: 338nm

[0030] Chromatographic column: ACQUITY UPLC BEH C18 reversed-phase column (2.1 mm × 5 cm, particle size: 1.7 μm; pore size: )

[0031] Sample manager temperature setting: 4℃

[0032] Injection volume: 1 μL

[0033] Column temperature: 45℃

[0034] Mobile phase A: FA / H2O (0.1:99.9, v / v)

[0035] Mobile phase B: FA / ACN (0.1:99.9, v / v)

[0036] Flow rate: 500 μL / min

[0037] The gradient elution program was as follows: t = 0 min, 5% B; t = 1.00 min, 5% B; t = 1.01 min, 98% B; t = 2.00 min, 98% B; t = 2.50 min, 5% B; t = 6.00 min, 5% B.

[0038] 4. LC-MS detection: Based on the results of LC-UV quantification, 12 C and 13 C-labeled mixed samples were detected by a combination of ultra-high performance liquid chromatography and electrospray ionization time-of-flight mass spectrometry.

[0039] The conditions are set as follows:

[0040] Mobile phase A: H2O / FA ​​(99.9:0.1, v / v)

[0041] Mobile phase B: ACN / FA (99.9:0.1, v / v)

[0042] Gradient elution program: t=0 min, 25% B; t=10 min, 99% B; t=13 min, 99% B; t=13.1 min, 25% B; t=16 min, 25% B.

[0043] Before starting the test of the target samples, five consecutive QC samples are tested to evaluate the repeatability and stability of the instrument. All samples are arranged in random order, and one QC sample, one blank sample, and one [other sample] are tested after every 10 runs of the target samples. 12 A C-labeled standard sample and one quality control sample. All mass spectra in this experiment were obtained in positive ion mode. The peak pairs in the mass spectra represent metabolites with different labels, because all 12 Each C-labeled sample was in equal quantity 13 Using a C-labeled mixed sample as a reference, the relative concentration differences of metabolites in the sample can be obtained by comparing peak intensities.

[0044] 5. LC-MS Raw Data Processing: Raw data from LC-MS is processed using IsoMS, normalizing identical peak pairs detected from multiple samples. A zero-fill program is used to search for and fill missing values. Measurements are then performed using IsoMS-Quant. 12 C- / 13 C-paired chromatographic peak-intensity ratio. Finally, a CSV file containing information such as metabolite retention time, mass-to-charge ratio, peak intensity ratio, and relative metabolite content is generated.

[0045] 6. Metabolomics Characterization Analysis:

[0046] (1) Multivariate statistics: PCA and OPLS-DA analyses were performed using SMICA 14.1. PCA analysis was used to assess the overall trend of change, including the QC sample, while OPLS-DA analysis was used to distinguish between groups.

[0047] (2) Preliminary screening of differentially expressed metabolites: Using Excel, differential peak pairs were screened at each time point (10w, 12w, and 16w) except baseline, with |FC| < 1.2 and P < 0.05 as thresholds, between the control group and the model group, and between the model group and the treatment group. Then, at the same time point, the intersection of the two differential peak pairs was taken to obtain three differential peak pairs at different time points. The differential metabolite peak pairs were compared with the dansyl standard library and the HMDB database based on mass-to-charge ratio and retention time to identify the differentially expressed metabolites. The intersection of the three differential metabolites was then taken again, and substances showing differences at ≥2 consecutive time points were considered significant, thus obtaining the initially screened differential substances.

[0048] 7. Quantitative enrichment analysis of metabolic pathways: The differentially identified substances were enriched into pathways based on the KEGG database, and the metabolic pathways with significant impact were inferred based on the P-value and Rich Factor.

[0049] 8. Experimental verification: The key enzymes and genes in the metabolic pathway will be verified at the molecular biology level to further discover the potential targets of MSCs.

[0050] 9. Correlation analysis: Spearman correlation analysis was performed on the differentially metabolites obtained from the initial screening and liver enzymes (ALT, AST and ALP). Differential substances were screened with a correlation coefficient |ρ| < 0.6 and P < 0.05 as the standard to obtain a potential biomarker candidate list.

[0051] 10. Metabolite time trend analysis: The differential metabolites obtained above were screened again. Metabolites that showed a trend of convergence between the treatment group and the control group at ≥2 consecutive time points were considered as potential efficacy biomarkers.

[0052] 11. Machine Learning: After removing samples from the baseline time point, the remaining samples from the model group and the treatment group were randomly divided into training and test sets at a 2:1 ratio. A logistic regression model was built using the training set to distinguish between the model group and the treatment group. The test set data was then input for validation. The feasibility of this potential biomarker was evaluated based on metrics such as AUC, accuracy (CA), sensitivity, and specificity.

[0053] result

[0054] After CIL LC-MS analysis, 1698 peak pairs were detected in the DNS-tagged samples, and 1854 peak pairs were detected in the DmPA-tagged samples. Metabolites containing amino / phenolic hydroxyl groups corresponding to the DNS tag and metabolites containing carboxyl groups corresponding to the DmPA tag were matched with the database, yielding 1338 (78.9%) and 1467 (79.1%) results, respectively. 12 C- / 13 C-peaks were identified or deduced.

[0055] The clustering of quality control (QC) samples on the multivariate statistical PCA score plot indicates good stability and repeatability during LC-MS operation, suggesting high data reliability. Furthermore, the three data groups show a clear distinguishing trend. The OPLS-DA score plot shows significant differentiation among the three data groups, further validating these results. This indicates changes in amine / phenolic compounds and carboxyl-containing compounds after MSC transplantation. Figure 1 A, 1B, 1C, and 1D)

[0056] After initial screening, 41 differentially expressed metabolites were identified. Pathway enrichment revealed the presence of the arginine and proline metabolism pathway, and the enriched substances included L-1-pyrroline-3-hydroxy-5-carboxylic acid, a degradation product of hydroxyproline. qPCR validation of the gene encoding proline 4-hydroxylase, a key enzyme in this pathway, showed a decrease in its expression level after MSC treatment. This suggests that MSCs may reduce collagen production by decreasing proline 4-hydroxylase levels, thereby alleviating liver fibrosis symptoms in patients with post-hepatic sclerosis (PSC). Figure 2 , Figure 3 )

[0057] Correlation analysis was performed on 41 differentially expressed metabolites obtained from the initial screening and three liver enzymes (ALT, AST, and ALP). The results showed that the correlation coefficients (ρ) between the hydroxyproline metabolite L-1-Pyrroline-3-hydroxy-5-carboxylic acid and the three liver enzymes were all greater than 0.06, with P values ​​less than 0.05. Furthermore, the trend of its relative content over time showed that it met the requirements for biomarkers in this invention. Therefore, this substance can be considered a potential biomarker for therapeutic efficacy. Figure 4 A, 4B, 4C and Figure 5 )

[0058] A machine learning model was built to evaluate the potential biomarker, and the results were as follows: Figure 6 We successfully established a logistic regression model using the training set, with an area under the curve (AUC) of 0.873 and a accuracy (CA) of 0.833. The optimal cut-off value based on the training set was 0.509. Validation was then performed using the test set data, yielding AUC and CA values ​​of 0.889 and 0.800, respectively. Based on the confusion matrix, the sensitivity and specificity of this metabolite as a biomarker were calculated to be 0.867 and 0.667, respectively. Therefore, L-1-Pyrroline-3-hydroxy-5-carboxylic acid can serve as a potential biomarker for evaluating the efficacy of MSC therapy in treating PSC.

Claims

1. The application of a reagent for detecting L-1-pyrrolline-3-hydroxy-5-carboxylic acid in the preparation of a product for evaluating the therapeutic effect of mesenchymal stem cells on primary sclerosing cholangitis in mice, characterized in that, The sample used for testing was mouse serum.

2. The application according to claim 1, characterized in that, The products include reagent kits, chips, and test strips.

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