Application and Method of a Metabolic Marker

Abstract

This invention discloses the application and method of metabolic biomarkers. It includes the application of metabolic biomarkers in the preparation of drugs for detecting the efficacy of immunotherapy for liver cancer, and a method for using metabolic biomarkers to detect the efficacy of immunotherapy for liver cancer. This invention uses metabolic biomarkers with high specificity, universality, and reliability as markers, and animal experiments have demonstrated that specific inhibition of the metabolic biomarkers of this invention can enhance the efficacy of immunotherapy for liver cancer, showing clinical translational potential.

Description

Technical Field

[0001] This invention relates to a metabolic biomarker, and more specifically to the application and method of a metabolic biomarker. Background Technology

[0002] The diagnosis of liver cancer relies on imaging examinations (such as ultrasound, CT, and MRI) and serum biopsy (such as alpha-fetoprotein AFP). Pathological biopsy can also serve as a definitive diagnostic method. Treatment options for liver cancer depend on the progression of the cancer and mainly include surgical resection, liver transplantation, local ablation therapy (such as radiofrequency ablation and microwave ablation), transarterial chemoembolization (TACE), molecular targeted therapy, and immunotherapy. In recent years, many treatment options have emerged for advanced liver cancer that is no longer an option for surgery, including photothermal therapy, targeted drugs, and immunotherapy.

[0003] Liver cancer possesses a strong ability to evade the immune system, altering the tumor microenvironment and suppressing the activity of immune cells to protect tumor cells from attack. The goal of immunotherapy is to activate or enhance the immune system, enabling it to effectively recognize and eliminate tumor cells. Immune checkpoint inhibitors work by blocking the binding of inhibitory immune checkpoint molecules (such as PD-1, PD-L1, and CTLA-4) to their ligands, thereby relieving the suppression of T cells and restoring their tumor-killing function. Clinical trials have shown that immune checkpoint inhibitors can significantly prolong the overall survival of liver cancer patients, with some patients exhibiting durable responses to treatment. However, some patients remain unresponsive to immunotherapy, and it may even accelerate the progression of liver cancer. Therefore, developing novel predictive biomarkers to assess which patients will benefit from immunotherapy is crucial for improving the success rate of immunotherapy.

[0004] Sphingolipid metabolism plays a crucial role in the development and progression of cancer, particularly in regulating multiple physiological processes such as cell proliferation, apoptosis, differentiation, and autophagy. As a bioactive lipid, sphingolipids are closely associated with tumor proliferation, metastasis, and chemotherapy resistance in various malignant tumors, including liver cancer. In liver cancer, imbalances in sphingolipid metabolism often promote tumor cell survival. For example, certain sphingosine and its derivatives, such as sphingosine-1-phosphate (S1P), can promote tumor proliferation and anti-apoptotic activity by activating growth signaling pathways. Therefore, metabolic biomarkers of sphingolipid metabolism have significant potential value in predicting the efficacy of cancer immunotherapy and in predicting patient survival prognosis. Summary of the Invention

[0005] To address the problems existing in the background art, the present invention aims to provide an application and method for the metabolic marker S1P. To achieve the above and other related objectives, the present invention has demonstrated, at the clinical, animal, and molecular levels, that the metabolic marker S1P is significantly increased in the serum and tissues of liver cancer patients unresponsive to immunotherapy. Therefore, by detecting the level of the metabolic marker S1P in isolated liver cancer serum sample solutions, the effectiveness of immunotherapy for liver cancer can be detected, providing a new approach for detecting the effectiveness of liver cancer immunotherapy. The first aspect of the present invention provides an application of a metabolic marker. The second aspect of the present invention provides a method for detecting the efficacy of liver cancer immunotherapy.

[0006] The technical solution adopted in this invention is:

[0007] I. Application of a metabolic biomarker

[0008] The application of the metabolic biomarkers in the preparation of drugs for detecting the effectiveness of immunotherapy for liver cancer.

[0009] The immunotherapy for liver cancer used was transarterial chemoembolization combined with programmed death receptor-1 (TACE+PD-1) monoclonal antibody therapy.

[0010] The metabolic markers are sphingolipid metabolites.

[0011] The metabolic marker is sphingosine-1-phosphate, a sphingolipid metabolite.

[0012] The drug contains detection reagents and instruments for detecting the expression levels of metabolic markers.

[0013] II. A method for detecting the efficacy of immunotherapy for liver cancer

[0014] The method includes: obtaining an isolated hepatocellular carcinoma serum sample solution, detecting the expression level of metabolic markers in the hepatocellular carcinoma serum sample solution, determining whether the expression level is greater than a preset expression threshold, and then predicting the effectiveness of hepatocellular carcinoma immunotherapy: if the expression level is greater than the expression threshold, hepatocellular carcinoma immunotherapy is predicted to be ineffective; if the expression level is less than or equal to the expression threshold, hepatocellular carcinoma immunotherapy is predicted to be effective.

[0015] Experimental tests showed that the levels of the metabolic marker sphingosine-1-phosphate (S1P) in the serum of liver cancer patients and in the lysate of liver cancer tissue were significantly higher than those in benign controls of healthy individuals.

[0016] Typically, after TACE+PD-1 monoclonal antibody treatment, liver cancer patients who respond to the treatment show tumor shrinkage on CT images, while those who do not respond show no change or increase in tumor size on CT images.

[0017] In experiments, this invention found that metabolic differences in the serum of liver cancer patients who did not respond to treatment and those who did respond showed that the sphingolipid signaling pathway was significantly enriched in the serum metabolites of patients who did not respond to treatment.

[0018] Specifically, the metabolic marker S1P was significantly higher in the serum of patients who did not respond to treatment than in the serum of patients who did respond to treatment in patients who received TACE+PD-1 monoclonal antibody therapy.

[0019] The metabolic marker sphingosine (sphingosine is a precursor of sphingosine 1-phosphate, and sphingosine kinase catalyzes the phosphorylation of sphingosine to S1P) showed no significant difference in serum levels between patients who did not respond to treatment and those who did respond to treatment after TACE+PD-1 monoclonal antibody therapy.

[0020] The metabolic marker sphingomyelin (a major component of cell membranes, which is converted into S1P by various kinases) showed no significant difference in serum levels between patients who did not respond to treatment and those who did respond to treatment after TACE+PD-1 monoclonal antibody therapy.

[0021] Experiments using receiver operating characteristic (ROC) curves from both liver cancer patients and non-liver cancer patients to evaluate the efficacy of the metabolic biomarker S1P in predicting the effectiveness of TACE+PD-1 monoclonal antibody therapy showed an area under the curve (AUC) of 0.9167, indicating that the metabolic biomarker S1P has high sensitivity and specificity as a predictor.

[0022] The metabolic marker is sphingosine phosphate, a sphingolipid metabolite.

[0023] The expression levels of the metabolic markers were quantitatively detected using enzyme-linked immunosorbent assay (ELISA).

[0024] The method further includes: the liver cancer serum sample solution is derived from a human liver cancer patient treated with transarterial chemoembolization combined with programmed death receptor-1 monoclonal antibody.

[0025] The response type of a liver cancer patient to monoclonal antibody therapy is determined by judging whether the expression level is greater than a preset expression threshold: if the expression level is greater than the expression threshold, the patient is predicted to be non-responsive to transarterial chemoembolization combined with programmed death receptor-1 monoclonal antibody therapy; if the expression level is less than or equal to the expression threshold, the patient is predicted to be responsive to transarterial chemoembolization combined with programmed death receptor-1 monoclonal antibody therapy.

[0026] The metabolic marker S1P is significantly positively correlated with tumor-associated macrophages (TAMs) and Tregs, which are tumor immunosuppressive components, and negatively correlated with CD8+ T cells, which are immune activating components. The above correlation is used to reflect the tumor status and immunotherapy status in patients with liver cancer through the metabolic marker S1P.

[0027] The method further includes: judging the prognosis of liver cancer immunotherapy by determining whether the expression level is greater than a preset expression threshold: if the expression level is greater than the expression threshold, the recurrence-free survival and overall survival are shorter and the prognosis is worse; if the expression level is less than or equal to the expression threshold, the recurrence-free survival and overall survival are longer and the prognosis is better.

[0028] The beneficial effects of this invention are:

[0029] This invention provides an application and method for the metabolic biomarker S1P, establishing a practical, sensitive, and specific immunological detection method for serum S1P. The research of this invention demonstrates that S1P is a metabolic biomarker with high specificity, versatility, reliability, and ease of widespread application for detecting the efficacy of liver cancer immunotherapy. Furthermore, compared to obtaining cancer tissue samples through biopsy to detect S1P expression, ex vivo serum samples are easier to obtain, facilitating the detection of S1P levels. The detection method for S1P is also simpler and easier to promote and apply in clinical settings or primary care hospitals. In addition, the method for detecting the efficacy of liver cancer immunotherapy using S1P established in this invention provides a reliable biological basis for liver cancer detection, offering assistance to current clinical data-based detection methods. Attached Figure Description

[0030] Figure 1 A diagram illustrating the classification of patients into those who respond to treatment and those who do not.

[0031] Figure 2 A schematic diagram illustrating the process of collecting serum for metabolomics sequencing and enrichment analysis.

[0032] Figure 3 A schematic diagram illustrating the differences in the levels of biomarkers related to sphingolipid metabolism across different groups;

[0033] Figure 4 A schematic diagram illustrating the assessment of the sensitivity and specificity of TACE+PD-1 monoclonal antibody therapy using the metabolic biomarker S1P.

[0034] Figure 5 The levels of the metabolic marker S1P were significantly higher than those in the control group with benign liver disease.

[0035] Figure 6This is a schematic diagram showing a trend of shorter relapse-free survival in the group with high levels of the metabolic marker S1P compared to the group with low levels of the metabolic marker S1P.

[0036] Figure 7 A schematic diagram illustrating that the serum and tissue levels of the metabolic marker S1P in the advanced liver cancer group were significantly higher than those in the early-stage group;

[0037] Figure 8 This is a schematic diagram illustrating the significant shorter overall survival in the group with high levels of the metabolic biomarker S1P compared to the group with low levels of the metabolic biomarker S1P.

[0038] Figure 9 A schematic diagram to show that the level of the metabolic marker S1P in tissues is positively correlated with the number of tumor-associated macrophages and Tregs, which are anti-tumor immunosuppressive components, and negatively correlated with the number of CD8+ T cells, which are anti-tumor immune activating components.

[0039] Figure 10 A schematic diagram illustrating the feasibility of combining the S1P inhibitor fingolimod with a PD-1 monoclonal antibody in an animal model of liver cancer.

[0040] Figure 11 The diagram illustrates how PD-1 monoclonal antibody alone did not significantly inhibit the progression of liver cancer, while the metabolic marker S1P inhibitor fingolimod alone could slightly inhibit the progression of liver cancer. However, the combination of the metabolic marker S1P inhibitor and PD-1 monoclonal antibody significantly inhibited the progression of liver cancer and significantly prolonged the survival of mice.

[0041] Figure 12 This diagram illustrates the safety implications of combining S1P inhibitors (metabolite markers) with PD-1 monoclonal antibodies.

[0042] Figure 13 This is a schematic diagram showing that the spleen size and mass of mice in each group did not change significantly.

[0043] Figure 14 This is a schematic diagram illustrating how the serum metabolic marker S1P can be used as a metabolic marker to detect the effectiveness of immunotherapy. Detailed Implementation

[0044] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] The embodiments of the present invention are as follows:

[0046] This invention collects CT imaging data of patients undergoing clinical trials of TACE+PD-1 monoclonal antibody therapy in accordance with medical ethics principles, classifying patients into treatment-responsive and non-responsive groups (see...). Figure 1 In patients who responded to treatment, the tumor lesions shrank significantly after treatment, while in patients who did not respond, the tumor lesions did not shrink or even increased in size.

[0047] First, serum samples were collected from patients for metabolomics sequencing and enrichment analysis (see...). Figure 2 Compare the differences in the levels of sphingolipid metabolism-related markers in different groups (see...) Figure 3 The results showed that the sphingolipid metabolism pathway was the most significantly enriched pathway.

[0048] Then, the area under the receiver acceptance curve (AUC) was used to evaluate the predictive sensitivity and specificity of the metabolic biomarker S1P for TACE+PD-1 monoclonal antibody therapy (see [link to relevant documentation]). Figure 4 The results showed that AUC = 0.9167, p < 0.0001, indicating that the metabolic marker S1P had high predictive sensitivity and specificity.

[0049] Tissues and serum were collected from controls of liver cancer and benign liver diseases. The levels of the metabolic marker S1P were detected using enzyme-linked immunosorbent assay (ELISA). The results showed that the levels of the metabolic marker S1P in the serum and cancer tissues of liver cancer patients were significantly higher than those in controls of benign liver diseases (see...). Figure 5 Furthermore, in clinical cohorts of liver cancer patients, the group with high levels of the metabolic marker S1P tended to have shorter recurrence-free survival than the group with low levels of the metabolic marker S1P (p = 0.06, see...). Figure 6 The overall survival of the group with high levels of the metabolic marker S1P was significantly shorter than that of the group with low levels of the metabolic marker S1P (p<0.05, see below). Figure 8 This indicates that the serum metabolic marker S1P can be used as a metabolic marker for detecting post-treatment metabolic changes.

[0050] Patients with liver cancer were divided into an early-stage group (stages I and II) and an advanced-stage group (stages III and IV). The expression levels of the metabolic marker S1P in serum and cancer tissues of both groups were detected using enzyme-linked immunosorbent assay (ELISA). The results showed that the serum and tissue levels of the metabolic marker S1P in the advanced-stage liver cancer group were significantly higher than those in the early-stage group (see...). Figure 7 This indicates that the serum metabolic marker S1P can serve as a metabolic marker for liver cancer staging.

[0051] Multiplex immunohistochemical staining was used to stain tumor-associated macrophages, Tregs, and CD8+ T cells in hepatocellular carcinoma tissue. The results showed that the level of the metabolic marker S1P in the tissue was positively correlated with the number of tumor-associated macrophages and Tregs, which are anti-tumor immunosuppressive components, and negatively correlated with the number of CD8+ T cells, which are anti-tumor immune activating components (see...). Figure 9This indicates that the serum metabolic marker S1P can serve as a metabolic marker for detecting the effectiveness of immunotherapy.

[0052] The feasibility of a therapy combining the S1P inhibitor fingolimod with a PD-1 monoclonal antibody was validated in an animal model of liver cancer (see [link to study]. Figure 10 PD-1 monoclonal antibodies alone did not significantly inhibit the progression of liver cancer. The S1P inhibitor fingolimod alone slightly inhibited liver cancer progression, while the combination of an S1P inhibitor and a PD-1 monoclonal antibody significantly inhibited liver cancer progression and significantly prolonged the survival of mice (see [link to original text]). Figure 11 Quantitative analysis of liver cancer was then performed, and the results showed that the combination of the metabolic marker S1P inhibitor and PD-1 monoclonal antibody significantly reduced the number of liver cancers in the mouse model, while the body weight of the mice in each group did not change significantly, indicating that the combination of the metabolic marker S1P inhibitor and PD-1 monoclonal antibody has a certain degree of safety (see...). Figure 12 ).

[0053] To further evaluate the safety of the combination of the metabolic marker S1P inhibitor and PD-1 monoclonal antibody, the spleens of mice in each intervention group were compared. The results showed that there were no significant changes in spleen size and mass among the groups (see [link to relevant documentation]). Figure 13 ).

[0054] To further evaluate the efficacy of the combination of the metabolic marker S1P inhibitor and PD-1 monoclonal antibody, flow cytometry analysis was performed on hepatocellular carcinoma tissues from a mouse model. The results showed that the combination of the metabolic marker S1P inhibitor and PD-1 monoclonal antibody reduced the number of M2 tumor-associated macrophages and Treg cells, increased the number of CD8+ T cells, and enhanced the function of CD8+ T cells, manifested by upregulation of GZMB in CD8+ T cells. This indicates that the serum metabolic marker S1P can serve as a metabolic marker for detecting the efficacy of immunotherapy (see...). Figure 14 ).

[0055] This invention first discovered that in the serum of liver cancer patients, those unresponsive to immunotherapy had higher levels of the metabolic marker S1P than those who did respond, demonstrating that the metabolic marker S1P can serve as a biomarker to predict the effectiveness of immunotherapy for liver cancer. Furthermore, animal experiments verified that elevated levels of the S1P metabolite discovered in this invention are associated with poor prognosis, and that inhibiting the metabolic marker S1P in combination with a PD-1 monoclonal antibody can effectively inhibit the progression of liver cancer, providing potential clinical value for immunotherapy of liver cancer.

[0056] This invention also included biological analysis and clinical performance evaluation:

[0057] 1) Collect serum and tissue samples from liver cancer patients and other patients who received TACE+PD-1 monoclonal antibody therapy at one hospital, and perform the following biological analyses (metabolic sequencing, enrichment analysis, enzyme-linked immunosorbent assay (ELISA) and animal experiments) and clinical assessment (comparison of clinical CT images); other patients were patients with benign diseases, and blood samples were also required for subsequent testing during the testing process.

[0058] 2) Metabolomics sequencing technology was used to process patient samples that responded to and did not respond to TACE+PD-1 monoclonal antibody therapy, and enrichment analysis was performed to obtain differential metabolomics pathways.

[0059] 3) The level of the metabolic marker S1P in the serum and tissues of patients with liver cancer was measured using enzyme-linked immunosorbent assay (ELISA).

[0060] 4) Use multiple immunostaining to quantify the cell counts of various immune components in the tissues of liver cancer patients.

[0061] Through the above steps, the correlation between the level of the metabolic marker S1P in the serum and tissues of liver cancer patients and the efficacy of TACE+PD-1 monoclonal antibody therapy was analyzed. The results showed that the metabolic marker S1P was highly expressed in the serum and tissues of the group unresponsive to TACE+PD-1 monoclonal antibody therapy, and its expression increased with the progression of liver cancer stage (see [link to study]). Figure 7 ).like Figure 9 As shown, the level of the metabolic marker S1P is positively correlated with the antitumor immunosuppressive components TAMs and Tregs, but negatively correlated with the antitumor immune activating component CD8+ T cells. This demonstrates that the metabolic marker S1P can serve as a predictor of the effectiveness of immunotherapy for liver cancer.

[0062] This invention also included animal experiments, in which several C57 mice with hepatocellular carcinoma were divided into four groups: a negative control group without intervention, a group treated only with the S1P inhibitor Fingolimod, a group treated only with PD-1 monoclonal antibody, and a group treated with a combination of the S1P inhibitor Fingolimod and PD-1 monoclonal antibody. Blood, liver tissue, and spleen were collected from the C57 mice with hepatocellular carcinoma for analysis.

[0063] a) Serum and cancer tissue were extracted from mice in each group, and the level of S1P, a metabolic marker, was detected in each of the four groups using enzyme-linked immunosorbent assay (ELISA).

[0064] b) Extract cancer tissues from each group of mice and disperse them into single cells. Use tissue flow cytometry to detect the composition of the immune microenvironment in the cancer tissues of each of the four groups.

[0065] c) Extract the spleens of mice from each group, observe the morphology and size of the spleens, weigh them and analyze them;

[0066] The animal experiments showed that liver cancer in mice treated with the combination of the S1P inhibitor Fingolimod and PD-1 monoclonal antibody was significantly suppressed, and the mice in the combination treatment group had the longest survival time.

[0067] In b) above, after using tissue techniques, mice treated with the combination of the S1P inhibitor Fingolimod and PD-1 monoclonal antibody showed a significant decrease in the number of M2 tumor-associated macrophages (the antitumor immunosuppressive component), a significant decrease in the number of Tregs (the antitumor immunosuppressive component), and a significant increase in the number of CD8+ T cells (the antitumor immune activating component). Furthermore, GZMB, a marker associated with the antitumor function of CD8+ T cells, was also significantly upregulated in CD8+ T cells. In c) above, after removing the spleens from each group of mice, no significant differences were observed in the spleens of the groups visually, and spleen quality analysis showed no significant differences in spleen quality among the groups.

[0068] In this invention, the metabolic biomarker S1P is used as a metabolic biomarker to detect the efficacy of liver cancer immunotherapy and to determine the prognosis of liver cancer immunotherapy, as follows:

[0069] Assessing the efficacy of immunotherapy for liver cancer: It has been found that liver cancer patients with high serum levels of the metabolic marker S1P tend not to benefit from TACE+PD-1 monoclonal antibody immunotherapy. Serum samples were collected from patients, and the level of the serum metabolic marker S1P was detected using enzyme-linked immunosorbent assay (ELISA). Based on the level of serum S1P, the potential benefit of patients from TACE+PD-1 monoclonal antibody immunotherapy was predicted.

[0070] Assessing the prognosis of liver cancer immunotherapy:

[0071] (1) The level of the metabolic marker S1P was detected by enzyme-linked immunosorbent assay (ELISA).

[0072] (2) For patients who have been diagnosed with liver cancer and have indications for immunotherapy, serum samples were collected and sent to the laboratory for testing.

[0073] (3) The laboratory used enzyme-linked immunosorbent assay (ELISA) to detect the level of metabolic marker S1P and provided feedback on the detection results of metabolic marker S1P.

[0074] (4) Based on the level of the metabolic marker S1P in serum, predict and evaluate the effect of immunotherapy on liver cancer patients.

[0075] This invention demonstrates high levels of the metabolic marker S1P in liver cancer patients who did not respond to TACE+PD-1 monoclonal antibody therapy in both animals and humans, verifying the feasibility of using S1P as a metabolic marker to predict the effectiveness of immunotherapy in liver cancer patients. Through clinical sample information, it verifies that serum S1P can be used to predict the effectiveness of liver cancer immunotherapy and evaluates the clinical value of serum S1P as a prognostic marker. Therefore, by detecting the level of the metabolic marker S1P in the serum of individual liver cancer patients, the effectiveness of liver cancer immunotherapy can be predicted, providing a new approach for the comprehensive treatment of liver cancer.

[0076] This invention provides the use of serum metabolic marker S1P as a metabolic marker to predict the effectiveness of immunotherapy for liver cancer and to determine the prognosis of immunotherapy for liver cancer.

[0077] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. An application of a metabolic biomarker, characterized in that: The application of the metabolic biomarkers in the preparation of products for detecting the effectiveness of immunotherapy for liver cancer; The metabolic markers are sphingolipid metabolites; The metabolic marker is sphingosine-1-phosphate; The immunotherapy for liver cancer involved transarterial chemoembolization combined with programmed death receptor-1 monoclonal antibody therapy.

2. The application of a metabolic biomarker according to claim 1, characterized in that: The product includes detection reagents and instruments for detecting the expression levels of metabolic biomarkers.

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