Use of immune response biomarkers in the prognostic evaluation of patients with cirrhosis treated with mesenchymal stromal cells

Abstract

The application provides an application of an immune response biomarker in prognosis evaluation of a liver cirrhosis patient treated by mesenchymal stromal cells, relates to the field of biological medical technology, and the immune response biomarker comprises MX1 positive mononuclear cells or / and LGALS2 positive mononuclear cells, potential biomarkers LGALS2 positive mononuclear cells and MX1 positive mononuclear cells for predicting the dose-effect relationship of MSC treatment are screened, the proportion of MX1 positive mononuclear cells at a baseline of the liver cirrhosis patient is significantly increased (P<0.01) compared with a healthy control, and the proportion of LGALS2 positive mononuclear cells is significantly reduced (P<0.05); the change trend of the biomarker under the MSC dose and the regulation effect on other immune cell subgroups are identified through sequencing analysis, the dose-effect relationship of the immune regulation mediated by MSC can be accurately reflected, and patients with a low recurrence risk in MSC treatment prognosis are identified.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of biological medicine technology, and in particular to application of an immune response biomarker in prognosis evaluation of mesenchymal stromal cells in treating liver cirrhosis patients. BACKGROUND

[0002] De-compensated liver cirrhosis (DLC) is the late stage of liver cirrhosis, and cirrhosis-associated immune dysfunction (CAID), which is a paradoxical combination of systemic inflammation and immune deficiency, is a key factor in the progression of DLC. Immune dysfunction makes patients prone to frequent and severe infections, and promotes bacterial translocation, thereby exacerbating liver damage, leading to multiple organ failure, and ultimately poor prognosis.

[0003] MSCs are considered promising cell therapy candidates due to their ease of access, low immunogenicity, differentiation potential, and strong immunomodulatory capacity. Since DLC is characterized by immune imbalance and progressive tissue damage, it becomes an ideal target for MSC therapy, as MSCs have the potential to restore immune homeostasis. Multiple clinical studies have recorded improvements in MELD score, prothrombin time, and liver function after MSC infusion. Although the immunomodulatory potential of MSCs has been recognized as a key therapeutic benefit, it is worth noting that the dose-dependent effect of MSCs in human DLC has not been systematically studied, and the dose-effect relationship of MSC-mediated immune modulation is still poorly understood. This knowledge gap is a major obstacle to effective clinical application of MSC therapy for DLC, and it is important to predict patient response to MSCs and select potential responders before treatment.

[0004] In view of this, the present application is proposed. SUMMARY

[0005] One of the purposes of the present application is to provide an immune response biomarker to at least solve the technical problem that there is a lack of an immune response biomarker that can reflect the dose-effect relationship of MSC-mediated immune modulation in the prior art.

[0006] The second purpose of the present application is to provide the application of the above-mentioned immune response biomarker in prognosis evaluation of mesenchymal stromal cells in treating liver cirrhosis patients or preparation of a prognosis monitoring kit for mesenchymal stromal cells in treating liver cirrhosis patients.

[0007] The third purpose of the present application is to provide the application of the above-mentioned immune response biomarker in preparation of a drug for immune modulation in mesenchymal stromal cells in treating liver cirrhosis patients.

[0008] The fourth purpose of the present application is to provide the application of the above-mentioned immune response biomarker in preparation of a drug for treating immune dysfunction in liver cirrhosis patients.

[0009] In order to achieve the above object of the present application, the following technical solutions are adopted:

[0010] In a first aspect, the present application provides an immune response biomarker, which comprises MX1 positive monocytes or / and LGALS2 positive monocytes.

[0011] Further, the MX1 positive monocytes have IFN stimulated gene expression characteristics.

[0012] Preferably, the LGALS2 positive monocytes are CD14 positive monocytes.

[0013] Preferably, the MX1 positive monocytes comprise CD14 positive / CD16 negative classical monocytes.

[0014] In a second aspect, the present application provides the use of the immune response biomarker as described above in prognosis evaluation of mesenchymal stromal cell treatment of liver cirrhosis patients or preparation of a prognosis monitoring kit for mesenchymal stromal cell treatment of liver cirrhosis patients.

[0015] Further, the prognosis evaluation comprises establishing a dose-effect relationship between the mesenchymal stromal cells and the immune response biomarker, obtaining the proportion of immune response biomarkers in peripheral blood at different treatment times, and performing prognosis evaluation according to the proportion of immune response biomarkers.

[0016] Preferably, the prognosis evaluation according to the proportion of immune response biomarkers comprises that, compared with before treatment, if the proportion of MX1 positive monocytes significantly decreases and the proportion of LGALS2 positive monocytes significantly increases, the treatment is effective and the risk of recurrence is low, otherwise the treatment is ineffective and the risk of recurrence is high.

[0017] Further, the prognosis evaluation comprises evaluating the immunoregulatory intensity of the mesenchymal stromal cells, or / and evaluating the improvement depth of the prognosis liver disease score.

[0018] Preferably, the dose of the mesenchymal stromal cells is ≥1.5×10 8 cells / time.

[0019] Preferably, the interval between administrations is ≤7 days.

[0020] Further, the effect comprises reducing the phagocytosis or antigen presentation function of MX1 positive monocytes.

[0021] Preferably, reducing the phagocytosis or antigen presentation function of MX1 positive monocytes comprises down-regulating the expression amount of at least one of pro-inflammatory cytokines, interleukin-15 or macrophage stimulating 1 of MX1 positive monocytes; or / and,

[0022] It upregulates the expression level of at least one of TNFSF10, TNFSF13, or TNFSF14.

[0023] Furthermore, the kit includes substances for detecting biomarkers of immune response;

[0024] Preferably, the monitoring method includes detecting the proportion of immune response biomarkers in peripheral blood at different time points after treatment.

[0025] Thirdly, the present invention provides the application of the above-mentioned immune response biomarkers in the preparation of medicaments for immunomodulation in the treatment of patients with cirrhosis using mesenchymal stromal cells.

[0026] Furthermore, the immune regulation includes activating the CD86-CTLA4 signaling axis and downregulating regulatory T cell activity; or / and,

[0027] ICAM1-mediated transendothelial migration promotes the recruitment of cytotoxic T cells while activating the immune activity of γδ T cells; or / and,

[0028] LGALS2 is enhanced by secreting ANXA1 protein. + Phagocytic function of monocytes;

[0029] Preferably, the immune response biomarker is an MX1-positive monocyte.

[0030] Fourthly, the present invention provides the application of the above-mentioned immune response biomarkers in the preparation of medicaments for treating immune dysfunction in patients with cirrhosis;

[0031] Preferably, the immune response biomarker is an MX1-positive monocyte.

[0032] The immune response biomarkers provided by this invention, through single-cell RNA sequencing or mass cytometry before and after treatment in clinical studies of MSC treatment of DLC patients with single or multiple escalating doses, screen for potential biomarkers predicting the dose-response relationship of MSC treatment, namely LGALS2-positive monocytes and MX1-positive monocytes. Compared with healthy controls, the proportion of baseline MX1-positive monocytes in cirrhotic patients was significantly increased (P<0.01), while the proportion of LGALS2-positive monocytes was significantly decreased. By sequencing analysis, the changing trends of biomarkers at the same MSC dose and their regulatory effects on other immune cell subsets can be identified, which can accurately reflect the dose-response relationship of MSC-mediated immune regulation and identify patients with a low risk of relapse after MSC treatment. Attached Figure Description

[0033] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0034] Figure 1 A flowchart illustrating the research design and participant grouping provided for this invention;

[0035] Figure 2 A graph showing the changes in Child-Pugh scores of participants before and after MSC treatment, provided by this invention.

[0036] Figure 3 This invention provides a dynamic landscape of single-cell immune cells in DLC patients treated with MSCs. Specifically, a) is a schematic diagram of multi-omics analysis of the clinical trial cohort and validation cohort; b) is a UMAP diagram of cell lines and subsets; c) is a dynamic box plot of major immune cell lines; e) is a UMAP diagram of monocyte subsets and CD14 / FCGR3A expression; f) is a heatmap of KEGG pathway feature scoring; f) is the dynamic proportion of monocyte subsets; g) is the proportion of LGALS2-positive and MX1-positive monocytes; h) is the dynamics of CCR-positive monocytes in CyTOF; i) is a violin plot of MX1-positive monocyte cytokine production scoring; and j) is a heatmap of gene expression in co-cultured MX1-positive monocytes.

[0037] Figure 4 This invention provides dynamic single-cell characteristics of DLC patients undergoing MSC treatment; where a is a t-SNE map of monocyte subsets annotated in CyTOF; b is the pseudo-time trajectory of Monocle3 (left) and Slingshot (right) for monocyte differentiation; c is a heatmap of gene expression along pseudo-time; d is a distribution density map of monocyte subsets along pseudo-time at time points after treatment in the healthy cohort, baseline, and low-high-dose, medium-high-dose, and ultra-high-dose groups; e is a heatmap of cytokines expressed by monocyte subsets; # indicates a significant difference between baseline and healthy individuals. * indicates a significant difference between time points after MSC treatment and baseline; f is MX1 grouped by changes in Child-Pugh score. + Box plot of dynamic changes in monocytes;

[0038] Figure 5This is a schematic diagram illustrating the analysis of other immune cells and their interaction with monocytes under MSC therapy provided by the present invention; wherein, a is the UMAP and dynamics of T cell subsets; b is the dynamics of T cell subsets in CyTOF; c is the ligand-receptor heatmap; d is the immune cell correlation pie chart; e is a schematic diagram of the timing of MSC immune regulation and the interaction with MX1 positive monocytes.

[0039] Figure 6 The following are the results of changes in other immune cells in DLC patients under MSC treatment, as provided by this invention: a. The left side shows the UMAP atlas of NK cell subsets, displaying the expression of NCAM1 and FCGR3A. The right side shows the dynamic changes of the major NK cell subsets. Cell proportions are calculated as a percentage of the total number of NK cells. b. The left side shows the tSNE atlas of NK cell subsets annotated by CyTOF, and the right side shows the dynamic changes of three NK cell subsets detected by CyTOF. c. The left side shows the UMAP atlas of B cell subsets, and the right side shows the dynamic changes of the major B cell subsets. Cell proportions are calculated as a percentage of the total number of B cells. d. The left side shows the tSNE atlas of B cell subsets annotated by CyTOF, and the right side shows the dynamic changes of three B cell subsets detected by CyTOF. **p<0.001, p<0.01, p<0.05 represent extremely significant, significant, and significant differences, respectively. Detailed Implementation

[0040] Unless otherwise defined herein, the scientific and technical terms used in conjunction with this invention shall have the meanings commonly understood by one of ordinary skill in the art. The meaning and scope of terms shall be clear; however, in any case of potential ambiguity, the definitions provided herein shall prevail over any dictionary or foreign definitions. In this application, unless otherwise stated, the use of "or" means "and / or". Furthermore, the use of the term "comprising" and other forms is non-limiting.

[0041] Generally, the nomenclature and techniques used in cell and tissue culture, molecular biology, immunology, microbiology, genetics, and protein and nucleic acid chemistry and hybridization, together with those described herein, are those well-known and commonly used in the art. Unless otherwise stated, the methods and techniques of the present invention are generally carried out according to conventional methods well-known in the art and described in various general and more specific references, which are cited and discussed throughout this specification. Enzymatic reactions and purification techniques are carried out according to the manufacturer's instructions, as commonly practiced in the art, or as described herein. The nomenclature, laboratory procedures, and techniques used in analytical chemistry, synthetic organic chemistry, and medical and medicinal chemistry, together with those described herein, are those well-known and commonly used in the art.

[0042] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] In one aspect, the present invention provides an immune response biomarker, which includes LGALS2 positive monocytes and / or MX1 ​​positive monocytes.

[0044] By performing single-cell RNA sequencing or mass cytometry before and after treatment in clinical studies of MSC treatment of DLC patients with single or multiple escalating doses, potential biomarkers for predicting the dose-response relationship of MSC treatment, LGALS2-positive monocytes and MX1-positive monocytes, were screened. Compared with healthy controls, the proportion of MX1-positive monocytes was significantly increased at baseline in cirrhotic patients (P<0.01), while the proportion of LGALS2-positive monocytes was significantly decreased. Sequencing analysis identified the trend of biomarker changes and their regulatory effects on other immune cell subsets at the same MSC dose, which can accurately reflect the dose-response relationship of MSC-mediated immune regulation and identify patients with a low risk of relapse after MSC treatment.

[0045] This invention reveals for the first time that MX1-positive monocytes are key regulatory targets and effector cells in MSC therapy for liver cirrhosis, and that the regulatory effect of MSC therapy on MX1-positive monocytes has a significant dose-related effect.

[0046] In some specific embodiments, the MX1-positive monocytes possess IFN-stimulated gene expression characteristics; in some specific embodiments, the LGALS2-positive monocytes are CD14-positive monocytes; in some specific embodiments, the MX1-positive monocytes include CD14-positive / CD16-negative classical monocytes.

[0047] According to another aspect of the present invention, the application of the above-mentioned immune response biomarkers in the prognostic assessment of patients with cirrhosis treated with mesenchymal stromal cells or in the preparation of a prognostic monitoring kit for patients with cirrhosis treated with mesenchymal stromal cells is also provided.

[0048] In some specific implementations, the prognostic assessment includes establishing a dose-response relationship between mesenchymal stromal cells and immune response biomarkers, obtaining the proportion of immune response biomarkers in peripheral blood at different treatment times, and conducting prognostic assessment based on the proportion of immune response biomarkers.

[0049] In some specific implementations, the prognostic assessment based on the proportion of immune response biomarkers includes, relative to pre-treatment levels, a significant decrease in the proportion of MX1-positive monocytes and a significant increase in the proportion of LGALS2-positive monocytes, indicating that the treatment is effective and the risk of relapse is low; otherwise, the treatment is ineffective and the risk of relapse is high.

[0050] In some specific implementations, the prognostic assessment includes assessing the intensity of immune regulation in mesenchymal stromal cells and / or assessing the depth of improvement in the prognostic liver disease score.

[0051] High-dose MSCs (≥1.5 × 10⁶ cells / dose) significantly reduced the proportion of MX1-positive monocytes and improved their biological function, with the effect lasting for 7 days. Low-dose (≤1.0 × 10⁶ cells / dose) had limited effects. In some specific embodiments, the dose of the mesenchymal stromal cells was ≥1.5 × 10⁶ cells / dose. 8 Cells / dose; in some specific implementations, the dosing interval is ≤7 days.

[0052] In some specific embodiments, the effects include reducing the phagocytic activity or antigen-presenting function of MX1-positive monocytes;

[0053] During MSC treatment of DLC, CCR4, CCR6, IL15, MST1, TNFSF10, TNFSF13, and TNFSF14 exhibit specific dose-dependent changes in MX1-positive monocytes. In some specific embodiments, reducing the phagocytic or antigen-presenting function of MX1-positive monocytes includes downregulating the expression of at least one of the pro-inflammatory cytokines, interleukin-15, or macrophage stimulation 1 in MX1-positive monocytes; and / or upregulating the expression of at least one of TNFSF10, TNFSF13, or TNFSF14.

[0054] In some specific embodiments, the kit includes substances for detecting biomarkers of immune response. In some specific embodiments, the substances for detecting immune response biomarkers include substances for detecting MX1-positive monocytes, and / or substances for detecting LGALS2-positive monocytes.

[0055] In some specific implementations, the monitoring method includes detecting the proportion of immune response biomarkers in peripheral blood at different time points after treatment.

[0056] By analyzing cell communication between MX1+ monocytes and other immune cell subsets, the role of MX1+ monocytes as an "immune regulatory center" in MSC therapy was revealed for the first time. According to another aspect of the present invention, the application of the above-mentioned immune response biomarkers in the preparation of drugs for immunomodulation in mesenchymal stromal cell therapy for patients with cirrhosis is also provided.

[0057] This invention reveals for the first time the core mechanism of stem cell therapy for cirrhosis through single-cell multi-omics technology: MX1+ monocytes, as immune regulatory hubs, significantly improve the immune imbalance in cirrhosis by dose-dependently regulating Treg activity, enhancing CD8+ T cell migration, and coordinating anti-inflammatory monocyte differentiation.

[0058] In some specific embodiments, the immunomodulation includes activating the CD86-CTLA4 signaling axis, downregulating regulatory T cell (Treg) activity, thereby relieving a state of excessive immunosuppression; and / or promoting cytotoxic T cell (CD86) migration via ICAM1-mediated transendothelial migration. + Teff recruits and simultaneously activates the immune activity of γδT cells via the APP-CD74 pathway (for the intrinsic immune activity of γδT cells); or / and enhances the phagocytic function of LGALS2+ monocytes by secreting ANXA1 protein to regulate anti-inflammatory monocytes.

[0059] In some specific embodiments, the immune response biomarker is an MX1-positive monocyte.

[0060] According to another aspect of the present invention, the use of the above-mentioned immune response biomarkers in the preparation of a medicament for treating immune dysfunction in patients with cirrhosis is also provided;

[0061] Preferably, the immune response biomarker is an MX1-positive monocyte.

[0062] The present invention will be further illustrated by the following examples. Unless otherwise specified, the materials in the examples are prepared according to existing methods or purchased directly from the market.

[0063] scRNA-seq: Single-cell RNA sequencing.

[0064] CyTOF: Time-of-flight mass cytometry.

[0065] Bulk RNAseq: Batch RNA sequencing.

[0066] Example: Dose-response relationship study of immune response biomarkers in MSC therapy for DLC

[0067] 1. Patient Recruitment

[0068] Stage Ia patients were recruited at the Fifth Medical Center of the PLA General Hospital from March 22, 2022 to July 5, 2023. After evaluating the Stage Ia data, recruitment for Stage Ib continued from August 22, 2023 to March 22, 2024. Patients aged 18–75 years with a Child-Pugh score of 7–12 and a diagnosis of DLC were included.

[0069] Diagnosis was based on clinical presentation, laboratory findings, imaging findings, and / or representative pathological results. In addition, patients must have at least one serious complication, such as hepatic encephalopathy, upper gastrointestinal bleeding due to esophageal or gastric varices, spontaneous bacterial peritonitis, or ascites. To prevent potential recompensation interference, this study excluded patients who had received antiviral therapy for HBV infection for less than 12 months, had received TIPS insertion within the past 6 months, or had received corticosteroid therapy for autoimmune cirrhosis for less than 6 months. To validate the immunological mechanisms identified in the above cohorts, this study also recruited 5 DLC patients who met the inclusion and exclusion criteria but had not received MSC therapy as independent study subjects for validation.

[0070] 2. Research Design

[0071] like Figure 1 As shown, this was an open-label, sequential, single-arm, dose-escalation phase Ia / Ib clinical trial, including single and multiple doses of MSCs according to the "3+3" rule. The sample size was based on a phase I dose-escalation design, prioritizing safety assessment while minimizing patient risk according to regulatory guidelines. In phase Ia, patients were assigned to one of four cohorts, each receiving a single dose of MSCs: cohort I received 5.0 × 10⁶ cells, cohort II received 1.0 × 10⁶ cells, cohort III received 1.5 × 10⁶ cells, and cohort IV received 2.0 × 10⁶ cells. Based on phase Ia data, the safety, efficacy, immunomodulatory effects, and duration of action of different doses of mesenchymal stem cells were evaluated. Phase Ib patients received three doses of MSCs, administered one week apart: cohort A received 1.0 × 10⁶ cells per dose, while cohort B received 2.0 × 10⁶ cells per dose. Follow-up assessments were conducted at baseline, day 3 (D3), day 7 (D7), day 14 (D14), and day 28 (D28).

[0072] 3. Sample Processing: Peripheral blood samples for scRNA-seq were collected at baseline, on days 3, 7, 14, and 28; samples for CyTOF staining were collected at baseline, on days 3, and 7. All samples were transported to the laboratory for processing within 12 hours at room temperature, or within 48 hours if stored at approximately 4°C. All samples were analyzed fresh and did not require freezing. Peripheral blood mononuclear cells (PBMCs) were separated using Ficoll density gradient centrifugation. Cell particles were resuspended in 5 ml of pre-chilled Fluorescence Activated Cell Sorting (FACS) buffer (1×phosphate-buffered PBS, supplemented with 0.5% bovine serum albumin) and centrifuged at 400×g for 5 minutes at 4°C. After discarding the supernatant, the microspheres were resuspended in FACS buffer. Cell counting was performed; samples subsequently analyzed required a cell count of at least 3×10⁻⁶. 6 The survival rate is higher than 85%.

[0073] 4. Single-cell transcriptome pretreatment:

[0074] The raw FASTQ file was mapped to the GRCh38 genome using Cell Ranger software (version 4.0.0) with default parameters. After alignment, a digital gene expression (DGE) matrix was generated. For each sample, a barcode file, a gene annotation file, and a raw counting matrix file were generated. The data was then imported into R (version 4.2.1) using the Seurat package (version 4.2.0). Genes expressed in cells with <10 cells and <200 gene features or 1000 read counts were excluded from the counting matrix. Cells with <10% mitochondrial genes were retained for further analysis. The counting matrix was then normalized using a logarithmic transformation, and the top 2000 variable features were selected for scaling and dimensionality reduction. To eliminate batch effects from samples collected at different time points and from different patients, the FastMNN method was applied to integrate all Seurat objects. Double-positive cells were removed using the DoubleFinder package (version 2.0.3). The proportion of double-positive cells increased by 0.8% for every additional 1000 cells in the sample. High-confidence duplexes were subsequently removed. Principal component analysis (PCA) was used for dimensionality reduction. The top 30 principal components were selected for clustering, and cell clusters were visualized using uniform manifold approximation and projection (UMAP). Cell subtypes were obtained using the FindNeighbors and FindCluster functions in Seurat. Finally, subtypes were labeled based on marker genes to obtain immune cell subtypes. Signaling pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) were downloaded using the msigdbr package version 7.5.1 to facilitate the calculation of single-cell feature scores. Then, the gene list for these pathways was provided using the AddModuleScore function in Seurat, and signature scores were calculated with default parameters. The average signaling pathway score for each cell subset was calculated using the AverageExpression function in Seurat.

[0075] Based on the expression levels of each receptor and ligand gene pair, potential interactions between the two cell types were inferred using CellChat methods. Receptors and ligands expressed in more than 20% of cells within the corresponding subclusters were included in the analysis. Visualization was performed using various built-in functions of the CellChat package (with default parameters).

[0076] 5. Mass cytometry staining and data acquisition

[0077] Antibody labeling was performed using the Maxpar Antibody-Conjugation Kit (Fluidigm), and the concentration of the labeled antibody was determined using NanoDrop. The concentration of the labeled antibody was adjusted to 200 mg / mL with antibody stabilization buffer and titrated to determine the optimal concentration. The obtained cells were washed with PBS and stained on ice for 5 minutes with 100 μL of 250 nM cisplatin (Fluidigm, South San Francisco, CA, USA) to remove dead cells. Cells were then incubated in Fc receptor blocking solution and stained on ice with a surface antibody mixture for 30 minutes. After washing with PBS, individual samples were labeled for 30 minutes using a unique barcode isotope combination. Cells were washed twice with FACS buffer and fixed overnight with 200 μL of intercalation medium (Maxpar Fix and Perm buffer containing 250 nM 191 / 193Ir, Fluidigm). Cells were then washed with FACS buffer and Perm buffer (eBioscience, San Diego, CA, USA) and stained on ice for 30 minutes with an intracellular antibody mixture. After staining, cells were washed and resuspended in deionized water, mixed with 20% EQ beads (Fluidigm), and analyzed using a Helios mass cytometer (Fluidigm). CyTOF experiments were performed by PLTTECH (Hangzhou, China). Signal intensity was adjusted for each channel prior to each batch loading according to the same head signals (140Ce, 151Eu, 153Eu, 165Ho, and 175Lu). All samples were normalized prior to analysis to prevent batch effects.

[0078] The raw data for each sample was encoded using a dual-filtering scheme and a unique quality marker barcode. FCS files from different batches were normalized using a header normalization method. Manual gating was performed using FlowJo software (FlowJo, Ashland, OR, USA) to exclude debris, dead cells, and duplicated cells, leaving only live, single immune cells. The X-shift clustering algorithm was applied to classify cells into different phenotypes based on marker expression levels. Each cluster was then annotated according to its marker expression pattern and visualized on a heatmap. The t-distributed random neighbor embedding (t-SNE) algorithm was used to analyze the high-dimensional data, enabling dimensionality reduction and visualization of cluster distributions, marker expression, and differences between group or sample types.

[0079] 6. Co-culture of mononuclear cells and MSCs and RNA sequencing

[0080] Peripheral blood (10 mL) was collected from patients in an independent validation cohort, and plasma and PBMCs were separated. CD14-positive monocytes were then purified from PBMCs using magnetic bead sorting (MACS). The separated monocytes were seeded into 0.4 μm Transwell inserts and placed in 12-well plates pre-seeded with MSCs at a 1:1 cell ratio. Co-culture was performed at 37°C for 24 hours. After incubation, monocytes were collected, and total RNA was extracted for RNA sequencing. Clean data was obtained by removing adapters and filtering out low-quality reads. Paired end reads were aligned to the human genome (UCSC hg38) using HISAT2 (version 2.1.0). Gene annotation and read counting were performed using HTSeq (version 0.11.2). Protein-coding genes were selected, and normalized expression values ​​were calculated using the DESeq2 package (version 1.32.0) on the R platform (version 4.1.0). The definition of MX1-positive monocyte-specific genes was based on two criteria: (1) expression in more than 30% of MX1-positive monocytes, and (2) a mean logarithmic fold change in expression between MX1-positive monocytes and other cells greater than 0.2. Gene Ontology (GO) biological process terminology was used to label the functions of MX1-positive monocyte-specific genes. Finally, differentially expressed genes after MSC co-culture were analyzed from three functional categories: (1) cytokine production, (2) phagocytosis, and (3) antigen processing and presentation, thereby exploring the effects of MSCs on MX1-positive monocytes and whether MX1-positive monocytes can transition to a healthy state.

[0081] 7. Statistical Analysis:

[0082] Continuous variables are summarized as mean ± standard deviation (SD), and categorical variables are summarized as frequency and percentage. Chi-square test or Fisher's exact test was used to compare categorical variables across different dose cohorts. t-test or Wilcoxon signed-rank test was used to compare continuous variables. Corresponding 95% confidence intervals (95% CI) are provided.

[0083] To analyze changes in cell proportions across multiple cohorts and time points, three statistical strategies were employed: (1) comparing changes in cell proportions across all patients at different time points using one-way ANOVA and paired t-tests; (2) comparing changes in cell proportions within each patient group at different time points, performing one-way ANOVA followed by paired t-tests for each patient group; and (3) using a linear mixed model to compare differences in cell proportions at different time points among different patient groups. A p-value < 0.05 was considered statistically significant. All clinical statistical analyses were performed using SAS 9.4 (SAS Institute, Cary, North Carolina, USA). The frequency of annotated cell populations was statistically analyzed using Student's t-tests via R platform (version 4.2.2).

[0084] 8. Baseline clinical characteristics, as shown in Table 1:

[0085] Table 1. Baseline demographic and clinical characteristics of patients

[0086]

[0087]

[0088] BMI = weight (kg) / height (m) 2 .

[0089] 9. Result 1: Safety assessment and Child-Pugh score results of the clinical cohort of MSC treatment for DLC.

[0090] like Figure 2 As shown, MSC infusion was well tolerated, and no adverse hemodynamic or respiratory changes were observed during or within 30 minutes of infusion. During the 28-day observation period, no dose-limiting toxicities, discontinuation due to adverse events, serious adverse events (SAEs), or suspected unexpected serious adverse reactions (SUSARs) occurred.

[0091] On day 28, 53.3% (n=8) of participants in phase Ia had a decreased Child-Pugh score, while 13.3% (n=2) had an increased Child-Pugh score, limited to cohorts I and II, with no increases reported in cohorts III and IV. In phase Ib, 88.9% (n=8) of participants had a decreased Child-Pugh score, with 3 cases in cohort A and 5 cases in cohort B; no increases in Child-Pugh scores were reported in either cohort. Overall, the high-dose group was more likely to experience a decreased Child-Pugh score in both phases.

[0092] 10. Result 2: Monocytes are the main effector cells in the peripheral blood immune cells of patients with cirrhosis treated with MSC.

[0093] This invention performed single-cell RNA sequencing (scRNA-seq) on peripheral blood mononuclear cell (PBMC) samples from patients in different dosing cohorts at five time points (baseline, day 3 [D3], day 7 [D7], day 14 [D14], and day 28 [D28]) (e.g. Figure 3 (As shown in Figure a). Simultaneously, PBMC data from 28 healthy donors in a public database were integrated to clarify the baseline characteristics of patients with cirrhosis-associated immune dysregulation (CAID). After rigorous quality control and batch effect correction, a total of 467,831 single cells were obtained (e.g., ...). Figure 3 (As shown in b). Through dimensionality reduction analysis and classical marker annotation, four major immune cell lineages were identified: T cells, B cells, NK cells, and monocytes, as well as other myeloid immune cells (such as...). Figure 3 (As shown in b). The above lineages can be further subdivided into higher-resolution subpopulations. By calculating the proportion of each cell lineage at baseline and its dynamic changes after MSC treatment, it was found that the proportion of monocytes and B cells increased at baseline, while the proportion of T cells and NK cells decreased (e.g., ...). Figure 3 (As shown in c). After MSC treatment, the proportions of the aforementioned cells gradually approached those of a healthy state, with the most significant recovery observed at time point D7. This conclusion was validated by CyTOF mass cytometry results, which indicated that among all immune cell subsets, monocytes showed the most significant difference between DLC patients and healthy individuals. This suggests that MSC treatment has the strongest effect on monocytes, while its impact on the proportions of other immune cells is limited, indicating that changes in monocytes are the main mechanism by which MSCs exert their immunomodulatory function.

[0094] 11. Result 3: Characteristic analysis of five monocyte subsets.

[0095] This invention annotates and analyzes five monocyte subsets (e.g. Figure 3(See figure d) to elucidate changes in monocyte subsets during MSC treatment. Results showed that multifunctional proteoglycan-positive (VCAN+, c35) monocytes, galactolectin 2-positive (LGALS2+, c36) monocytes, and myxovirus resistance protein 1-positive (MX1+, c38) monocytes all highly expressed CD14 and lowly expressed Fcγ receptor IIIa (FCGR3A, CD16), consistent with classic monocyte characteristics. MX1+ monocytes also showed high expression of interferon-stimulated genes (ISGs). MHC class II molecule DPβ+ (HLA-DPB+, c37) monocytes simultaneously expressed FCGR3A and CD14 (transitional monocytes), while FCGR3A+ (c39) monocytes highly expressed FCGR3A (CD16) and lowly expressed CD14, corresponding to non-classical monocytes. KEGG pathway analysis revealed that MX1+ monocytes exhibited higher immune activity, with their highly expressed genes enriched in the chemokine receptor (CCR), mitogen-activated protein kinase (MAPK), and transforming growth factor-β (TGF-β) pathways (such as...). Figure 3 (as shown in e).

[0096] 12. Result 4: Characteristics of MX1+ monocytes and LGALS2+ monocytes in patients with cirrhosis and their response to MSC therapy.

[0097] Cell proportion analysis showed that MX1+ monocytes were significantly higher at baseline than in healthy controls, while LGALS2+ monocytes were significantly lower (e.g., ...). Figure 3 (As shown in f). After MSC treatment, both subgroups showed a trend toward a healthy state, but differences existed between different cohorts: in the high-dose cohort, MSCs effectively reduced MX1+ monocytes and increased LGALS2+ monocytes, with the most significant effect at day 7; the modulatory effect was moderate at the medium-dose cohort; while no significant changes were observed in the low-dose cohort (e.g., Figure 3 As shown in g). Subpopulations with high expression of CCR4 and CCR6 were also identified in CyTOF data, corresponding to MX1+ monocytes (e.g., as shown in g). Figure 4 As shown in Figure a), the proportion of this subgroup decreases at D3 and D7 (e.g., Figure 3 (as shown in h).

[0098] Compared with healthy controls, the proportion of MX1-positive monocytes was significantly increased in DLC patients at baseline (P<0.01), while the proportion of LGALS2-positive monocytes was significantly decreased (P<0.05).

[0099] 13. Result 5: High-dose MSC treatment effectively promoted the differentiation of monocytes from VCAN+ monocyte population (differentiation origin) to FCGR3A+ monocyte population (terminal state).

[0100] Monocle3 pseudo-time series analysis and Slingshot validation showed that VCAN+ monocytes are the initiation point of differentiation, while FCGR3A+ monocytes represent the terminal state (e.g., ...). Figure 4 (As shown in b). As differentiation progresses, cells gradually overexpress MHC class II molecules, such as... Figure 4 As shown in Figure c, MHC class II molecules include HLA-DRA, HLA-DRB1, HLA-DQA1, HLA-DPA1, and HLA-DMA. At baseline, FCGR3A+ monocytes exhibit earlier phenotypic characteristics than healthy cells (e.g., ...). Figure 4 As shown in d), MSC treatment can promote differentiation into the terminal phenotype, especially in the high-dose cohort.

[0101] 14. Result 6: High-dose MSC treatment effectively exerted an immunomodulatory effect on MX1+ monocytes, and this effect was correlated with clinical outcomes.

[0102] MX1+ monocytes showed decreased cytokine secretion after MSC treatment, with the most significant decrease observed in the high-dose cohort, and the strongest effect observed on day 7 (e.g., Figure 3 (As shown in i). Further analysis showed that MSC treatment downregulated the expression of pro-inflammatory factors (IL15 and MST1) that were previously elevated in DLC patients at baseline in MX1+ monocytes, but increased the expression of tumor necrosis factor superfamily members (TNFSF10, TNFSF13, TNFSF14), which are known to activate T cells (e.g., ...). Figure 4 (as shown in e).

[0103] Validated through an independent cohort experiment (batch RNA-seq of peripheral blood CD14+ monocytes co-cultured with MSCs from 5 DLC patients), using scRNA-seq as a reference, it was found that co-culturing MX1+ monocytes with MSCs downregulated cytokine production, phagocytosis, and expression of antigen-presenting-related genes, confirming the immunomodulatory effect of MSCs on MX1+ monocytes (e.g., Figure 3 (As shown in the middle j). Furthermore, analysis of patients divided into four groups (+1 / +2, 0, -1, -2) based on changes in Child-Pugh scores showed that: in the "+1 / +2" group, the proportion of MX1+ monocytes returned to above baseline at D7; in the "0" group, it exceeded baseline at D14; in the "-1" group, it was below baseline at D3, and comparable to baseline at D7 / D14; while in the "-2" group, it remained below baseline at all post-treatment time points (e.g., ...). Figure 4 As shown in f), the proportion of MX1+ monocytes is associated with clinical outcomes.

[0104] Therefore, the dose-effect of MX1+ monocytes was most pronounced in the high-dose group (≥1.5×10 cells / dose), and this effect lasted for 7 days, while there was no significant effect in the medium and low-dose groups.

[0105] 15. Result 7: MX1+ monocytes mediate the immunomodulatory function of MSCs, playing a "central role in immunomodulation" in MSC therapy for liver cirrhosis.

[0106] This invention analyzed other immune cell subsets that were abnormally prevalent in DLC patients and responded to MSC therapy. 223,953 T cells were divided into 17 subsets (e.g., Figure 5 (As shown in Figure a). Regulatory CD4+ T cells (c5_CD4Treg_FOXP3) and effector CD8+ T cells (c10_CD8Teff_NKG7) were both elevated at baseline. Following MSC treatment, CD4Treg gradually decreased on days 3 and 7, while the proportion of CD8Teff was not directly suppressed. CyTOF also identified corresponding subsets ( Figure 5 As shown in Figure b), the patients with an increased proportion of CD4Treg were mostly from the high-dose group, and the trend of CD8Teff was consistent with that of scRNA-seq.

[0107] Among the eight NK cell subsets, c22_NK_GZMK was identified as CD56bright NK cells (e.g., Figure 6 As shown in (a), the baseline proportion of this subgroup was higher than that of healthy individuals. Notably, the proportion of this subgroup decreased in cohort I, while it increased in cohorts II / III / IV (as shown in (a)). Figure 6 (As shown in b). Of the nine B cell subsets, two naive B cell subsets (c26_NaiveB_IL4R and c27_NaiveB_TCL1A) and germinal center B cells (c33_gcB_CD38) showed elevated baseline levels, while three memory B cell subsets (c29_MemB_AIM2, c30_MemB_TNFRSF13B and c31_MemB_FCRL5) showed decreased levels (e.g., as shown in b). Figure 6 (As shown in c). Initial B cells remained stable after MSC treatment and gradually decreased on D3 / D7 (e.g., Figure 6 (As shown in c and d).

[0108] Intercellular communication analysis revealed that, compared with healthy controls, the signal transduction and reception intensities of all immune cell subsets were increased at baseline, and decreased after MSC treatment (e.g., Figure 3(As shown in a). MX1+ monocytes primarily act as signal transducers, while CD8Teff is the primary receiver. Among the signals emitted by MX1+ monocytes, the galactolectin pathway is enhanced in DLC patients but decreases at D7 in cohort II / IV; the resistin pathway is decreased in patients but increases at D3 / D7 in cohort IV (e.g., ...). Figure 3 (As shown in b and c). Ligand-receptor pair analysis shows (e.g.) Figure 5 c and Figure 3 As shown in Figure d), at baseline, MX1+ monocytes can promote transendothelial migration of CD4Treg, CD8Teff, γδT cells, and LGALS2+ monocytes via intercellular adhesion molecule-1 (ICAM1), and interact with other subsets through the amyloid precursor protein (APP)-CD74 axis. MX1+ monocytes also enhance the inhibitory function of CD4Tregs through CD86-CTLA4 and strengthen the chemotactic and phagocytic abilities of LGALS2+ monocytes through annexin A1 (ANXA1). At D3 / D7 after MSC treatment, the chemotactic activity of MX1+ monocytes decreased while their antigen-presenting ability increased, and they could regulate CD4Treg function through IL16-CD4. Correlation analysis showed (e.g.) Figure 5 As shown in Figure d), MX1+ monocytes are positively correlated with CD4Treg, γδT cells, and naive B cells, and negatively correlated with CD8Teff, LGALS2+ monocytes, and memory B cells. Based on these findings, a schematic diagram of the mechanism by which MSCs regulate immune cells was drawn (e.g., Figure 5 (as shown in e).

[0109] 16. Result 8: MX1 positive monocytes are associated with clinical response.

[0110] Patients in groups I, II, and IV were divided into four subgroups based on changes in Child-Pugh scores (i.e., +1 / +2, 0, -1, -2), and changes in the proportion of MX1-positive monocytes were analyzed. Results showed that in the "+1 / +2" group, the proportion of MX1-positive monocytes increased from baseline by D7, while in the "0" group, this proportion increased by D14. In contrast, patients in the "-1" group had a lower proportion of MX1-positive monocytes on D3 than at baseline, while the proportions on D7 and D14 were comparable to baseline. In contrast, the proportions on D7 and D14 in the "-1" group did not differ significantly from baseline. More importantly, in the "-2" group, the proportion of MX1-positive monocytes remained lower than baseline at all four time points post-treatment. These findings suggest that the degree of MSC-mediated MX1+ monocyte suppression is positively correlated with the depth of improvement in liver function.

[0111] Application scenario description:

[0112] 1. Precise regulation and optimization of immune balance in DLC patients for clinical use

[0113] In this invention, MSC therapy primarily regulates MX1 in DLC patients. + The changes in the proportion of monocytes were consistent with changes in Child-Pugh scores; patients with larger score reductions after treatment also had lower levels of MX1-positive monocytes, indicating that MX1... + Monocytes are the target and biomarker of MSC therapy response.

[0114] Further evidence demonstrates that higher MSC doses elicit stronger immunomodulatory effects, reflected in significant regulation of immune cell subsets crucial for CAID pathogenesis. These effects persisted for 7 days post-treatment but diminished by day 14, highlighting the importance of optimizing dosage and treatment intervals. MX1 was identified. + Monocytes are key immune mediators, and the dose of mesenchymal stromal cells should be ≥1.5 × 10⁻⁶. 8 Cells / dose is a reasonable dosage for DLC patients, administered once every 7 days for 3 times. It can be used in trials or actual treatment of DLC with MSCs to guide efficacy research.

[0115] 2. MX1 + Monocytes, as biomarkers for predicting or monitoring treatment response, can be detected by flow cytometry to measure the proportion of these cells in peripheral blood and their changes after MSC infusion, thus predicting the therapeutic effect on liver cirrhosis. For example, peripheral blood can be collected before infusion to rapidly identify and quantify MX1. + Monocyte subsets; subsequently, based on the dynamic changes in the proportion and functional status of this subset under different doses, the dose-response relationship described in this invention is established, according to MX1. + The proportion of monocytes can be used to predict the therapeutic effect of MSCs, thereby allowing for timely adjustments to the treatment plan to achieve precise regulation of the immune balance in DLC patients and optimize clinical efficacy.

[0116] 3. MX1 + Monocytes, as the center of immune regulation, regulate other cells in various applications.

[0117] This invention analyzed other immune cell subsets that were abnormally proportioned in DLC patients and responded to MSC therapy, demonstrating that MX1+ monocytes mediate the immunomodulatory function of MSCs. For example, during MSC therapy for DLC patients, MX1+ monocytes act as key signaling nuclei, coordinating systemic immune balance through multiple ligand-receptor pathways. In MSC-induced immune remodeling, MX1+ monocytes play a crucial role in restoring systemic immune homeostasis by coordinating various subsets such as Tregs, effector T cells, and B cells.

[0118] 4. Given MX1 +The correlation between monocytes and liver disease scores was evaluated by assessing MX1. + The proportion and function of monocytes can assess the severity of cirrhosis and cirrhosis-related immune dysfunction.

[0119] 5. MX1 + Monocytes can serve as targets and biomarkers for various treatment methods (chemotherapy, cell therapy, etc.) to treat cirrhosis-related immune dysfunction, including MSC therapy.

[0120] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. Application of immune response biomarkers in the preparation of a prognostic monitoring kit for mesenchymal stromal cell therapy in patients with cirrhosis; The immune response biomarkers include MX1-positive monocytes and / or LGALS2-positive monocytes.

2. The application according to claim 1, characterized in that, The MX1 positive monocytes exhibit IFN-stimulated gene expression characteristics and active TGF-β and CCR pathway expression.

3. The application according to claim 1, characterized in that, The LGALS2-positive monocytes are CD14-positive / CD16-negative monocytes.

4. The application according to claim 1, characterized in that, The MX1-positive monocytes include CD14-positive / CD16-negative classical monocytes.

5. The application according to claim 1, characterized in that, The kit includes substances for detecting biomarkers of immune response.

6. The application according to claim 1, characterized in that, The prognostic monitoring method includes detecting the proportion of immune response biomarkers in peripheral blood at different time points after treatment.

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