Biomarker composition for screening high-risk patient group for acute mortality after lung transplantation and uses thereof

Abstract

The present invention relates to a biomarker composition for screening a group at high risk of acute mortality after lung transplantation and uses thereof. As a result of investigating the correlation between the expression levels of proteins in serum before and after lung transplantation and clinical outcomes, it was confirmed that there was a statistically significant difference in serum abundance between individuals before and after lung transplantation. In addition, a novel prediction model for the risk of acute mortality after lung transplantation using three proteins in serum was investigated to exhibit a high AUC value. Accordingly, the biomarker of the present invention is expected to be useful for screening a group at high risk of acute mortality following lung transplantation.

Description

Biomarker composition for screening high-risk groups for acute death after lung transplantation and use thereof

[0001] The present invention relates to a biomarker composition for screening a high-risk group for acute death after lung transplantation and the use thereof.

[0002] The present invention claims priority based on Korean Patent Application No. 10-2025-0037019 filed on March 24, 2025, and all contents disclosed in the specification and drawings of said applications are incorporated by reference into the present application.

[0003] Lung transplantation is an established treatment option for patients with end-stage lung disease. Significant advancements in lung transplantation have been made in recent years since the first successful transplant was performed in the 1980s. However, the prognosis for lung transplantation still needs improvement compared to other solid organ transplants, and an imbalance exists between the supply and demand for lung transplants, as only 20% of potential donor lungs are suitable for transplantation. Consequently, much attention has been focused on selecting ideal candidates for lung transplantation during the pre-transplant period.

[0004] Cytokines are proteins that play a crucial role in the immune system; they are primarily secreted by immune cells and regulate immune responses through intercellular signaling. Cytokines are involved in various physiological processes such as inflammation, infection, and wound healing, and representative examples include interleukin, interferon, and tumor necrosis factor (TNF).

[0005] The primary functions of cytokines and inflammation-related proteins are to facilitate interactions between immune cells, enable them to fight pathogens by responding to infections or inducing inflammation, and play an important role in preventing autoimmune diseases or chronic inflammation by regulating immune responses through binding to receptors on cell membranes and activating intracellular signals.

[0006] Therefore, cytokine imbalance can lead to various diseases. Excessive secretion of cytokines and inflammation-related proteins can trigger an overactive inflammatory response, potentially causing autoimmune diseases; conversely, a deficiency can weaken the immune response, making one vulnerable to infection. For this reason, the regulation of cytokines and inflammation-related proteins is being studied as an important strategy in the treatment of immune diseases, yet little is known about research related to lung transplantation.

[0007] The object of the present invention is to provide a method for providing information for predicting the risk of acute death after lung transplantation, comprising the following steps:

[0008] S1) A step of analyzing the level of one or more proteins selected from the group consisting of FGF19 (Fibroblast Growth Factor 19), CCL19 (CC Motif Chemokine Ligand 19), and IL22RA1 (Interleukin-22 Receptor Subunit Alpha-1) or the mRNA thereof in a biological sample isolated from a subject.

[0009] Another object of the present invention is to provide a composition for predicting the risk of acute death after lung transplantation, comprising as an active ingredient a preparation for measuring the level of one or more proteins selected from the group consisting of the following or the mRNA thereof:

[0010] Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

[0011] Another objective of the present invention is to provide a kit for predicting the risk of acute death after lung transplantation, comprising a composition for predicting the risk of acute death after lung transplantation comprising, as an active ingredient, one or more proteins selected from the group formed above or a preparation for measuring the mRNA level thereof, and instructions.

[0012] Another object of the present invention is to provide a biomarker composition for predicting the risk of acute death after lung transplantation, comprising one or more active ingredients selected from the group consisting of the following:

[0013] Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

[0014]

[0015] However, the technical problems that the present invention aims to solve are not limited to those mentioned above, and other unmentioned problems will be clearly understood by those skilled in the art to which the present invention belongs from the description below.

[0016] The present invention provides a method for providing information for predicting the risk of acute death after lung transplantation, comprising the following steps:

[0017] S1) A step of analyzing the level of one or more proteins selected from the group consisting of FGF19 (Fibroblast Growth Factor 19), CCL19 (CC Motif Chemokine Ligand 19), and IL22RA1 (Interleukin-22 Receptor Subunit Alpha-1) or the mRNA thereof in a biological sample isolated from a subject.

[0018] In one embodiment of the present invention, the information providing method is,

[0019] S2) When compared to the level of protein or mRNA of the above substance in biological samples isolated from the control group,

[0020] The method may further include, but is not limited to, a step of predicting that the subject will die acutely after lung transplantation if the level of one or more proteins selected from the group consisting of FGF19 and CCL19 or their mRNA is decreased, or if the level of the IL22RA1 protein or its mRNA is increased.

[0021] In one embodiment of the present invention, the biological sample may be a biological sample isolated from a subject prior to lung transplantation, but is not limited thereto.

[0022] In one embodiment of the present invention, the biological sample may be any one selected from the group consisting of serum, whole blood, blood, and plasma, but is not limited thereto.

[0023] In one embodiment of the present invention, the acute death may be death within 3 months after lung transplantation, but is not limited thereto.

[0024] The present invention provides a composition for predicting the risk of acute death after lung transplantation, comprising as an active ingredient a preparation for measuring the level of one or more proteins selected from the group consisting of the following or the mRNA thereof:

[0025] Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

[0026] The present invention provides a kit for predicting the risk of acute death after lung transplantation, comprising a composition for predicting the risk of acute death after lung transplantation comprising, as an active ingredient, a preparation for measuring the level of one or more proteins selected from the group consisting of the following or the mRNA thereof, and instructions:

[0027] Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

[0028] In one embodiment of the present invention, the description may teach the above method of providing information, but is not limited thereto.

[0029] The present invention provides a biomarker composition for predicting the risk of acute death after lung transplantation, comprising one or more active ingredients selected from the group consisting of the following:

[0030] Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

[0031]

[0032] In addition, the present invention provides a method for treating a high-risk group for acute death after lung transplantation, comprising the following steps:

[0033] S1) A step of analyzing the level of one or more proteins selected from the group consisting of FGF19 (Fibroblast Growth Factor 19), CCL19 (CC Motif Chemokine Ligand 19), and IL22RA1 (Interleukin-22 Receptor Subunit Alpha-1) or the mRNA level thereof in a biological sample isolated from a subject;

[0034] S2) When compared to the level of protein or mRNA of the above substance in biological samples isolated from the control group,

[0035] A step of predicting that the subject will die acutely after lung transplantation if the level of one or more proteins selected from the group consisting of FGF19 and CCL19 or their mRNA is decreased, or the level of the IL22RA1 protein or its mRNA is increased; and

[0036] S3) A step of administering a pharmaceutically effective amount of a therapeutic agent to a subject predicted to die acutely after the lung transplant.

[0037] In addition, the present invention provides a use for predicting the risk of acute death after lung transplantation of a preparation that measures the level of one or more proteins or mRNA selected from the group consisting of the following:

[0038] Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

[0039] In addition, the present invention provides a use for manufacturing a preparation for predicting the risk of acute death after lung transplantation, which measures the level of one or more proteins or mRNA selected from the group formed above.

[0040] According to the biomarker composition for screening high-risk groups for acute death after lung transplantation and the use thereof, when investigating the association between the expression of proteins in serum before and after lung transplantation and clinical outcomes, a statistically significant difference in serum abundance was confirmed between individuals before and after lung transplantation, and a new predictive model for the risk of acute death after lung transplantation using three serum proteins was found to exhibit a high AUC value, the biomarker of the present invention is expected to be usefully utilized as a biomarker for screening high-risk groups for acute death after lung transplantation.

[0041] Figure 1 is a figure showing the serum protein analysis workflow using the Olink Inflammation panel.

[0042] Figure 2 shows a flowchart of the sample selection and matching process.

[0043] Figures 3a to 3c show the results of an analysis of the association between serum protein abundance levels before and after lung transplantation and survival rates after lung transplantation.

[0044] Figure 3a shows the distribution of serum protein abundance levels in recipients before and after lung transplantation.

[0045] Figure 3b shows the distribution of serum protein abundance levels in recipients before transplantation.

[0046] Figure 3c shows the distribution of serum protein abundance levels in recipients after transplantation.

[0047] (Here, the X-axis represents NPX (normalized protein expression) values, and the Y-axis represents -log10 (p-value for the difference between the two groups) along with the corresponding cytokine. Points indicating a statistically significant difference in expression between the two groups lie on the dotted horizontal line. Blue dots indicate low expression, and pink dots indicate high expression compared to the other group. Orange highlights indicate cytokines showing differences in samples before and after transplantation.)

[0048] Figures 4a to 4c relate to a predictive model for survivors after lung transplantation.

[0049] Figures 4a and 4b show the receiver operation characteristic curves of the model predicting survivors for (a) NGF, (b) IL-1A, (c) AXIN1, (d) IL-33, (e) IL-2, (f) CCL-3, (g) IL-10RA, and (h) IL-5, respectively, and Figure 4c shows (i) the sensitivity and specificity of the new prediction model.

[0050] Figure 5 analyzes the association between serum protein abundance levels before and after transplantation in survivors and graft dysfunction after lung transplantation.

[0051] The upper diagram of Fig. 5 shows the distribution of serum protein abundance levels before transplantation in survivors with and without functional impairment. In addition, the lower diagram of Fig. 5 shows the distribution of serum protein abundance levels after transplantation in survivors with and without functional impairment.

[0052] (Here, the X-axis represents NPX (normalized protein expression) values, and the Y-axis represents -log10 (p-value for association with graft dysfunction) along with the corresponding cytokine. Among survivors, points showing statistically significant differences in expression between rejection and cases without graft dysfunction lie on the dotted horizontal line. Blue dots indicate low expression in survivors with graft dysfunction, while pink dots indicate high expression in survivors with graft dysfunction. Orange highlights indicate cytokines showing differences between pre- and post-transplant samples.)

[0053] Figures 6a to 6c relate to a model predicting rejection after lung transplantation among survivors.

[0054] Figures 6a to 6c show the recipient operating characteristic curves of a model predicting rejection after lung transplantation in survivors for each of the five cytokine combinations, (a) GDNF, (b) NTF3, (c) IL-24, (d) TNFRSF9, (e) SCF, (f) IL-18R1, (g) CCL-25, (h) MCP-3, and (i) CXCL-1, as well as the sensitivity and specificity of a new prediction model.

[0055] Figures 7a and 7b relate to a model predicting rejection after lung transplantation among survivors.

[0056] Figure 7a shows the receiver operation characteristic curves of the model predicting death within 3 months after lung transplantation for (a) FGF19, (b) CCL19, (c) IL22RA1, and (d) TSLP, respectively, and Figure 7b shows the sensitivity and specificity of the new prediction model for the combination of the three serum proteins.

[0057] Despite the continuously increasing demand for lung transplants due to end-stage lung disease, donated lung resources remain significantly limited. Therefore, it is essential to efficiently allocate resources by predicting the risk of acute death after lung transplantation prior to the procedure and selecting a patient group suitable for transplantation. To this end, the inventors of this invention have conducted research to investigate the association between the expression of cytokines and inflammation-related proteins as biomarkers prior to lung transplantation and clinical outcomes. By confirming that the risk of acute death after lung transplantation can be predicted, the inventors have completed this invention.

[0058] The present invention provides a method for providing information for predicting the risk of acute death after lung transplantation, comprising the following steps:

[0059] S1) A step of analyzing the level of one or more proteins selected from the group consisting of FGF19 (Fibroblast Growth Factor 19), CCL19 (CC Motif Chemokine Ligand 19), and IL22RA1 (Interleukin-22 Receptor Subunit Alpha-1) or the mRNA thereof in a biological sample isolated from a subject.

[0060] Including all claims below, the information providing method in this specification is,

[0061] S2) When compared to the level of protein or mRNA of the above substance in biological samples isolated from the control group,

[0062] The method may further include, but is not limited to, a step of predicting that the subject will die acutely after lung transplantation if the level of one or more proteins selected from the group consisting of FGF19 and CCL19 or their mRNA is decreased, or if the level of the IL22RA1 protein or its mRNA is increased.

[0063] Including the full claims below, this specification analyzed pre- and 7-day post-lung transplant serum pairs of lung transplant recipients from a database collected prospectively from February 2020 to February 2024 and classified them into four groups using propensity score matching: survivors without graft dysfunction, survivors with graft dysfunction, survivors who did not survive within 3 months, and survivors who did not survive for 3 months or longer. For the lung transplant recipients, the association between changes in pre- and post-transplant serum proteins, namely cytokines and inflammation-related proteins, and clinical outcomes was explored. As a result, it was confirmed that there was a statistically significant difference in the abundance of several pre-transplant serum proteins, namely cytokines and inflammation-related proteins, between the acute death group and the survival group after lung transplantation.

[0064] Including all claims below, “FGF19 (Fibroblast Growth Factor 19)” is a growth factor that regulates bile acid synthesis in the liver and maintains metabolic balance. It transmits signals by binding to the FGFR4 receptor and is involved in blood sugar regulation, energy metabolism, and fat accumulation. It has a function that promotes hepatocyte proliferation, and its association with hepatocellular carcinoma is being studied.

[0065] In all claims below, “CCL19 (CC Motif Chemokine Ligand 19)” is a chemokine that regulates the migration of immune cells and plays an important role in immune responses and inflammatory processes. It functions to induce T cells and dendritic cells to migrate to lymph nodes by binding to the CCR7 receptor. Because it can be involved in the immune evasion mechanisms of cancer cells, it is an important subject of research in anticancer immunotherapy.

[0066] In all claims below, “L22RA1 (Interleukin-22 Receptor Subunit Alpha-1)” is a receptor for Interleukin-22 (IL-22) that serves to transmit immune signals. It is primarily expressed in epithelial cells such as those in the liver, lungs, and intestines, functions to aid in tissue protection and regeneration, and is known to have increased expression in certain cancers.

[0067] Including all claims below, this specification confirms that the four proteins in Fig. 7a are significantly reduced or increased in the serum before and after lung transplantation. In addition, according to the ROC analysis results of a model predicting the risk of acute death after lung transplantation using three of the four proteins in Fig. 7b, the AUC was found to be 0.920, demonstrating that the risk of acute death after lung transplantation can be predicted with excellent accuracy by analyzing the levels of three types of proteins in the serum before lung transplantation.

[0068] Including the full claims below, the serum levels of three types of serum proteins of the present invention, namely cytokines and inflammation-related proteins, have been analyzed. It has been confirmed that the risk of acute death after lung transplantation can be predicted based on the increase or decrease in the level of each substance, and in particular, that the most superior predictive effect of the risk of acute death after lung transplantation is achieved when all three types of proteins are combined. Accordingly, in one embodiment of the present invention, the level of the substance may more preferably refer to the protein level, but is not limited thereto.

[0069] In the present specification, including all claims below, it has been confirmed that the risk of acute death after lung transplantation can be predicted by analyzing the expression levels of three types of proteins of the present invention from the serum of a lung transplant recipient prior to transplantation. In the present specification, including all claims below, the biological sample may be serum isolated from the subject prior to lung transplantation, but is not limited thereto.

[0070] In this specification, including all claims below, “serum protein” may refer to serum proteins in a broad sense, including serum cytokines and inflammation-related proteins, and may be used interchangeably with “serum protein.” In the present invention, “serum cytokines” may be used interchangeably with “serum cytokines” or “cytokines.” Serum cytokines are signaling proteins present in the blood that regulate immune responses; they assist in interactions between immune cells and play a role in promoting or suppressing inflammatory responses. Their concentrations fluctuate in infections, autoimmune diseases, cancer, etc., serving as indicators of disease; however, since they can induce excessive immune responses such as cytokine storms, maintaining a balance may be important. In the present invention, “inflammation-related protein” may be used interchangeably with “serum inflammation-related protein” and may collectively refer to proteins present in the serum that perform functions related to inflammation.

[0071] Including all claims below, the biological sample may be a biological sample isolated from a subject prior to lung transplantation, but is not limited thereto.

[0072] Including all claims below, the biological sample may be any one selected from the group consisting of serum, whole blood, blood, and plasma, but is not limited thereto.

[0073] Including the full claims below, the biological sample described herein may be pretreated before use for detection or diagnosis. For example, this may include homogenization, filtration, distillation, extraction, concentration, inactivation of interfering components, addition of reagents, etc. The sample may be prepared to increase the detection sensitivity of protein markers, for example, the sample obtained from a subject may be pretreated using methods such as anion exchange chromatography, affinity chromatography, size exclusion chromatography, liquid chromatography, sequential extraction, or gel electrophoresis.

[0074] Including the entire claims below, the agent for measuring miRNA levels may be a primer, probe, oligonucleotide, antibody or antigen-binding fragment thereof that specifically binds to mRNA, a ligand, aptamer, peptide, receptor, agonist or antagonist, or a combination thereof, but is not limited thereto, and may mean any agent commonly used in the art.

[0075] Including all claims below, the preparation capable of measuring protein levels may be one or more selected from the group consisting of antibodies, peptides, aptamers, proteins, and compounds that specifically bind to said proteins, but is not limited thereto.

[0076] In the entirety of the following claims, the method for measuring mRNA levels is not limited to any specific mRNA measurement method known in the art, provided that it is by PCR, RNase protection assay, northern blotting, southern blotting, in situ hybridization, DNA chip, and / or RNA chip.

[0077] At this time, in the entire specification including the following claims, the method for measuring protein levels is not subject to any particular limitation as long as it is a protein measurement method known in the art, but can be measured by methods such as protein chip analysis, immunoassay, ligand binding assay, MALDI-TOF (Matrix Assisted LaSer Desorption / Ionization Time of Flight Mass Spectrometry) analysis, SELDI-TOF (Sulface Enhanced LaSer Desorption / Ionization Time of Flight Mass Spectrometry) analysis, radioimmunoassay, radioimmunodiffusion method, Ouchteroni immunodiffusion method, Rocket immunoelectrophoresis, tissue immunostaining, complement fixation assay, two-dimensional electrophoresis analysis, liquid chromatography-mass spectrometry (LC-MS), LC-MS / MS (liquid chromatography-mass spectrometry / mass spectrometry), Western blotting, ELISA (enzyme linked immunosorbent assay), FACS, etc.

[0078] In the entirety of the following claims, “the level is increased” means that something that was not previously detected is detected, or that the amount detected is greater than the normal level. For example, “the level is increased” means that the level of the experimental group is at least 1%, 2%, 3%, 4%, 5%, 10% or higher, e.g., 5%, 10%, 20%, 30%, 40%, or 50%, 60%, 70%, 80%, 90% or higher, and / or 0.5 times, 1.1 times, 1.2 times, 1.4 times, 1.6 times, 1.8 times or higher. Specifically, it may mean an increase of 1 to 1.5 times, 1.5 to 2 times, 2 to 2.5 times, 2.5 to 3 times, 3 to 3.5 times, 3.5 to 4 times, 4 to 4.5 times, 4.5 to 5 times, 5 to 5.5 times, 5.5 to 6 times, 6 to 6.5 times, 6.5 to 7 times, 7 to 7.5 times, 7.5 to 8 times, 8 to 8.5 times, 8.5 to 9 times, 9 to 9.5 times, 9.5 to 10 times, or 10 times or more compared to that of the control group, but is not limited thereto. A person skilled in the art can understand the meaning of the opposite term as having the opposite meaning in accordance with the above definition.

[0079] Including all claims below, the AUC value of the model for predicting the risk of acute death after lung transplantation when three types of serum proteins are combined may be 0.85 or higher, 0.86 or higher, 0.87 or higher, 0.88 or higher, 0.89 or higher, 0.9 or higher, 0.91 or higher, or 0.92 or higher, but is not limited thereto (p<0.001).

[0080] In addition, when three types of serum proteins are combined in the present specification, including all claims below, the sensitivity and specificity of the model for predicting the risk of acute death after lung transplantation may be 85% or more, 86% or more, 87% or more, 88% or more, 89% or more, or 90% or more, but are not limited thereto.

[0081] Including all claims below, the acute death described herein may be death within 3 months after lung transplantation, but is not limited thereto.

[0082] The term “method for providing information” as used herein, including all claims below, refers to a method for providing information regarding the diagnosis or prognosis prediction of a disease, particularly, in the present invention, the prediction of risk regarding a disease (acute death after lung transplantation). This method involves analyzing biological samples of an individual or confirming increases or decreases in the expression levels of the biomarkers of the present invention to obtain information regarding the onset or likelihood of onset (risk), prognosis, or risk prediction of the disease. For example, the method may include a method for providing information regarding whether there is a possibility of the disease of the present invention developing in an individual, whether the likelihood of said disease developing is relatively high, or whether said disease has already developed, by measuring the level of the biomarker according to the present invention and comparing it with a control group. Furthermore, through a method using the biomarkers of the present invention, it is possible to predict the risk of exacerbation due to the onset of the disease of the present invention, that is, whether the prognosis will be poor, and to predict the risk level. This may also be used as a method for providing information regarding the prevention and treatment of the disease of the present invention, or in the present invention, information regarding whether or not to perform a lung transplant. In particular, the term "disease" or "disease" in this specification, including the entire claim below, may mean acute death after lung transplantation.

[0083] In all claims below, the term “measurement” in this specification includes both detecting and confirming the presence (expression) of a target substance and detecting and confirming a change in the level of presence (expression level) of the target substance. The measurement may be performed without limitation, including both qualitative methods (analysis) and quantitative methods. The types of qualitative and quantitative methods for measuring the presence of a substance according to the present invention are well known in the art, and the experimental methods described in this specification are included therein.

[0084] In the entirety of the claims below, the term “analysis” may preferably include “measurement,” wherein the qualitative analysis may mean measuring and confirming the presence of a target substance, and the quantitative analysis may mean measuring and confirming a change in the presence level (expression level) or amount of the target substance. In the present invention, analysis or measurement may be performed without limitation by including both qualitative and quantitative methods, and preferably, quantitative measurement may be performed.

[0085] In the entire specification including the following claims, “prediction” may mean determining the susceptibility of an object to a specific disease or condition, determining whether an object currently has a specific disease or condition, and determining the prognosis of an object afflicted with a specific disease or condition (e.g., in the entire specification including the following claims, the subject of diagnosis is whether there is acute death after lung transplantation, or, if prognosis prediction is included, the prognosis for lung transplantation; in this case, poor prognosis may be acute death and may include both progression to acute death after lung transplantation), that is, predicting the degree of disease progression in the acute death group after lung transplantation of the present invention. It may mean predicting the probability of progression, deterioration, recurrence, maintenance, etc., of acute death after lung transplantation of the present invention through the increase or decrease in the level of the biomarker of the present invention. Or it may have a broad meaning that includes all of the therametrics (e.g., monitoring the condition of an object to provide information on therapeutic efficacy).

[0086] The present invention provides a composition for predicting the risk of acute death after lung transplantation, comprising as an active ingredient a preparation for measuring the level of one or more proteins selected from the group consisting of the following or the mRNA thereof:

[0087] Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

[0088] The present invention provides a kit for predicting the risk of acute death after lung transplantation, comprising a composition for predicting the risk of acute death after lung transplantation comprising, as an active ingredient, a preparation for measuring the level of one or more proteins selected from the group consisting of the following or the mRNA thereof, and instructions:

[0089] Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

[0090] Including all claims below, the present specification may teach the above method of providing information, but is not limited thereto.

[0091] In the entire specification including the following claims, “kit” refers to a tool that additionally includes a formulation or a substance for the function, storage, etc., of the kit to enable the use of the kit claimed in the present invention. In addition to the said substance, the kit of the present invention may include other components, compositions, solutions, devices, etc., that are typically required for the storage and processing methods thereof. As a specific example, each component may be applied one or more times without limitation on the number of times, there is no restriction on the order in which each substance is applied, and the application of each substance may proceed simultaneously or sequentially.

[0092] In all claims below, the kit may include a container; instructions; etc. The container may serve to package the material and may also serve to store and secure it. The material of the container may take the form, for example, a bottle, a tub, a sachet, an envelope, a tube, an ampoule, etc., and may be formed partially or wholly from plastic, glass, paper, foil, wax, etc. The container may be equipped with a cap that is initially part of the container or can be attached to the container by mechanical, adhesive, or other means and may be fully or partially detachable, and may also be equipped with a stopper that allows access to the contents by a needle. The kit may include an outer package, and the outer package may include instructions regarding the use of the components.

[0093] The present invention provides a biomarker composition for predicting the risk of acute death after lung transplantation, comprising one or more active ingredients selected from the group consisting of the following:

[0094] Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

[0095] In the entirety of the claims below, the term “biomarker” refers to a marker that can distinguish between normal and pathological states, predict prognoses such as treatment response, recovery from disease, or death, and is objectively measurable. It has been confirmed that the levels of biomarkers in biological samples of individuals with the disease of the present invention differ from the respective increases or decreases in levels compared to control groups (normal individuals or groups of individuals with acute death after lung transplantation). Thus, it has been proven that the biomarkers of the present invention can be used as biomarkers for predicting the risk of acute death after lung transplantation, which can be interchangeably referred to as the disease in the present invention.

[0096] In addition, the present invention may provide a diagnostic device for predicting or diagnosing the disease of the present invention. Specifically, the present invention has identified three types of biomarkers capable of predicting the risk of acute death after lung transplantation, which can be referred to as a diagnostic device for predicting or diagnosing the risk of acute death after lung transplantation. The measurement unit of the diagnostic device for predicting prognosis or diagnosing the present invention may measure the expression level of a protein using a preparation that measures the protein expression level of the biomarker according to the present invention on a biological sample obtained from a subject. By confirming the degree of protein expression using the preparation in the measurement unit, it is possible to diagnose whether the disease of the present invention (acute death after lung transplantation) is present.

[0097] Including all claims below, the diagnostic device of the present invention may further include a detection unit that predicts and outputs the occurrence of the disease of the present invention in a subject from the degree of expression of the protein obtained from the measurement unit.

[0098] Including all claims below, the detection unit in this specification can predict the occurrence of the disease of the present invention by generating and classifying information regarding the disease of the present invention according to the range of the expression level of the protein obtained from the measurement unit.

[0099]

[0100] In addition, the present invention provides a method for treating a high-risk group for acute death after lung transplantation, comprising the following steps:

[0101] S1) A step of analyzing the level of one or more proteins selected from the group consisting of FGF19 (Fibroblast Growth Factor 19), CCL19 (CC Motif Chemokine Ligand 19), and IL22RA1 (Interleukin-22 Receptor Subunit Alpha-1) or the mRNA level thereof in a biological sample isolated from a subject;

[0102] S2) When compared to the level of protein or mRNA of the above substance in biological samples isolated from the control group,

[0103] A step of predicting that the subject will die acutely after lung transplantation if the level of one or more proteins selected from the group consisting of FGF19 and CCL19 or their mRNA is decreased, or the level of the IL22RA1 protein or its mRNA is increased; and

[0104] S3) A step of administering a pharmaceutically effective amount of a therapeutic agent to a subject predicted to die acutely after the lung transplant.

[0105] In this specification, including all claims below, “therapeutic agent” may be a “therapeutic agent for the treatment of a group at risk of acute death after lung transplantation,” and refers to a therapeutic agent administered to subjects who are predicted to experience acute death after lung transplantation or who are classified as a high-risk group, for the purpose of preventing, delaying, or reducing the risk of acute death. The term “acute death” encompasses all death events occurring within three months of lung transplantation and may include, but is not limited to, cases where the cause is due to acute rejection, ischemia-reperfusion injury, acute pulmonary edema, infection, immune abnormalities, hemodynamic instability, or a combination thereof. Furthermore, the term “therapeutic agent” is not limited to a specific mechanism of action, pharmaceutical component, formulation, route of administration, or therapeutic strategy, and should be understood as a concept that includes all various therapeutic means and compositions as long as they can demonstrate an effect of reducing the risk of acute death after lung transplantation.

[0106] In addition, the present invention provides a use for predicting the risk of acute death after lung transplantation of a preparation that measures the level of one or more proteins or mRNA selected from the group consisting of the following:

[0107] Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

[0108] In addition, the present invention provides a use for manufacturing a preparation for predicting the risk of acute death after lung transplantation, which measures the level of one or more proteins or mRNA selected from the group formed above.

[0109] Preferred embodiments are presented below to aid in understanding the present invention. However, the following embodiments are provided merely to facilitate a better understanding of the invention, and the scope of the invention is not limited by the following embodiments.

[0110]

[0111] [Example]

[0112]

[0113] Sample collection

[0114] Samples were collected with ethylenediaminetetraacetic acid in the intensive care unit prior to arrival at the operating room and 7 days after transplantation. A total of three blood samples, each 4 mL in volume, were collected during a single blood draw and immediately stored on ice. The samples were centrifuged at 1600 rpm for 10 minutes. After the first centrifugation of the three blood collection tubes, the supernatant was carefully transferred to a 15 mL conical tube using a pipette. The combined plasma was then centrifuged a second time at 3000 rpm for 10 minutes. After the second centrifugation of the plasma, 4 mL of the aspirated supernatant was distributed into four 1.8 mL cryogenic vials, each containing 1 mL. The samples were immediately stored in a -80°C cryogenic freezer to ensure that the time elapsed from blood collection to freezer storage did not exceed 5 hours.

[0115]

[0116] Measurement of cytokines and inflammation-related proteins

[0117] To perform the relative quantification of 92 types of cytokines and inflammation-related proteins, the Olink Target 96 inflammation panel utilizing Olink’s Proximity Extension Assay (PEA) technique was used. The 92 types of proteins are as follows (Table 1).

[0118]

[0119]

[0120]

[0121] Briefly, the PEA technique involves synthesizing antibodies against two epitopes of a target protein and conjugating a single-stranded nucleotide complementary to the Fc terminus of each antibody. When the two types of antibodies bind to the target protein, the nucleotides, which are now closer together, form a complementary bond to form a double-stranded nucleotide, and the amount of the target protein is measured using a multiplexing technique with quantitative polymerase chain reaction (Quantitative PCR) (Fig. 1).

[0122]

[0123] Specifically, 1 µl of plasma sample, reaction buffer, Probe A, and Probe B were mixed and incubated overnight in a 96-well plate. Subsequently, PEA enzyme, solution, and PCR polymerase were mixed, and a primary polymerase chain reaction was performed to proceed with extension. Afterward, the solution was transferred to an integrated microfluidic chip and Olink ® Quantitative polymerase chain reaction was performed using the Signature Q100 instrument. The Ct values ​​for each protein were converted to Normalized Protein Expression (NPX), and statistical analysis was performed using these values.

[0124]

[0125] Statistical analysis

[0126] Data were presented as numbers and proportions for categorical variables, and as the mean ± standard deviation or median (interquartile range [IQR]) for continuous variables with normal or non-normal distributions. The chi-square test or Fisher's exact test was used to compare categorical variables, while Student's t-test or Mann-Whitney U test was used to compare continuous variables with normal or non-normal distributions. Volcano plots were used to visualize differences in cytokine expression between the two groups. The ratio of mean expression levels between the two groups was converted to a logarithmic scale and used as the X-axis value, and the statistical significance of the difference in mean expression levels between groups was converted to a logarithmic scale and used as the Y-axis value. To determine the predictive accuracy for cytokine expression, sensitivity, specificity, and the Area Under the Receiver Operational Curve (AUROC) were calculated for each cytokine. Finally, a model was constructed using variables with an AUROC value greater than 0.7. A two-sided p-value < 0.05 was considered to indicate significance. All analyses were performed using SPSS software ver. It was performed using 26.0 (IBM Corporation, Armonk, NY).

[0127]

[0128] Example 1. Sample Selection and Matching Process Flow

[0129] To derive pre-lung transplant biomarkers, a study cohort and patient selection were first performed (Fig. 2). Specifically, out of 108 adult recipients who received lung transplants at Asan Medical Center regardless of underlying disease from February 2020 to February 2024, 6 patients without pre-transplant samples were excluded, resulting in the final selection of 102 patients. The Institutional Review Board of Asan Medical Center approved the study protocol (Approval No. 2019-0981), and written informed consent was obtained from all patients. All procedures performed in the embodiments of this invention were conducted in accordance with the Guidelines for Clinical Good Practice and the Declaration of Helsinki. The statistical and clinical characteristics of the 102 selected patients are shown in Table 2 below (data are reported as numbers (percentages) or medians (interquartile ranges).

[0130]

[0131]

[0132] Subsequently, matching analysis was performed to minimize the influence of confounding factors. The included patients were classified into four groups using propensity score matching based on clinical outcomes: 1) survivors without graft dysfunction, 2) survivors with graft dysfunction, 3) survivors who did not survive within 3 months, and 4) survivors who did not survive for 3 months or longer.

[0133] The definition of graft dysfunction included primary graft dysfunction, acute rejection, and chronic lung graft dysfunction. Cases where the attending physician suspected acute rejection based on clinical findings and administered immunosuppressive therapy, even though pathological confirmation of acute rejection was not performed, were considered graft dysfunction. Additionally, survivors were defined as individuals who survived for at least one year after lung transplantation. Survival time was calculated as the period from lung transplantation to death.

[0134] In the matching procedure, group propensity scores calculated using a multivariate logistic regression model based on gender, age, and underlying diseases were used. Patients in the survivor group without graft dysfunction and the survivor group with graft dysfunction were matched 1:1 based on their propensity scores using an optimal no-replacement algorithm and a caliper width of 0.1. Next, patients who did not survive within 3 months were matched in a 1:1 ratio with cases of survivors with graft dysfunction. Finally, patients who did not survive for more than 3 months were also matched 1:1 with patients who did not survive within 3 months.

[0135] A pair of samples from the matched cohort, both before and after lung transplantation, were used for analysis. The clinical outcomes of the matched cohort are shown in Table 3 below (data are reported as numbers (percentages)).

[0136]

[0137]

[0138] Example 2. Analysis of the correlation between serum protein abundance levels before and after lung transplantation and survival rate after lung transplantation

[0139] For the samples of the recipients finally selected in Example 1, cytokine protein abundance before and after lung transplantation was analyzed to investigate the association with survival rate (or mortality rate) after lung transplantation. Proteins satisfying p<0.05, Fc≥1.2, and FC≤1.2 of the Student T-test in the volcano plot analysis were indicated.

[0140]

[0141] As a result, the distribution of serum protein abundance levels in deceased and surviving lung transplant recipients was confirmed as shown in Figure 3a. The distribution of serum protein abundance levels in deceased and surviving lung transplant recipients before transplantation was as shown in Figure 3b, and the distribution of serum protein abundance levels in deceased and surviving lung transplant recipients after transplantation was confirmed as shown in Figure 3c.

[0142] According to this, it was confirmed that 10 types of cytokines and inflammation-related proteins, IL1A, IL2, IL33, AXIN1, NGF, SULT1A1, IL10RA, CCL3, IL10RB, and IL17C, in serum prior to lung transplantation were statistically significantly increased or decreased. Specifically, the protein expression levels of IL1A, IL2, IL33, AXIN1, NGF, SULT1A1, and IL10RA decreased, while the protein expression levels of CCL3, IL10RB, and IL17C increased. In this case, SULT1A1 and IL10RB were identified as cytokines that showed differences in both pre- and post-lung transplant samples.

[0143]

[0144] Example 3. Establishment of a Survivor Prediction Model Before and After Lung Transplantation

[0145] In Example 2, proteins in the serum of deceased and surviving individuals after lung transplantation, as well as the protein abundance in the serum of deceased and surviving individuals before or after lung transplantation, were analyzed, and it was confirmed that 10 types of proteins significantly increased or decreased. In Example 3, a survival prediction model before and after lung transplantation was established, and the recipient operating characteristic curve of a model predicting survivors using pre-transplant protein markers, along with the sensitivity and specificity of the new prediction model, were analyzed. At this time, proteins presented in the ROC curve and interactive plot that had an AUC of 0.7 or higher and a significant P-value from the ROC analysis were selected and used in the final model.

[0146]

[0147] As a result, Figures 4a to 4c were confirmed. Specifically, Figures 4a and 4b show the results of analyzing the AUC values, sensitivity, and specificity for each of the eight types of cytokines and inflammation-related proteins: (a) NGF, (b) IL-1A, (c) AXIN1, (d) IL-33, (e) IL-2, (f) CCL-3, (g) IL-10RA, and (h) IL-5. In addition, Figure 4c shows the results of analyzing the AUC values, sensitivity, and specificity when the above eight types are combined.

[0148]

[0149] According to this, when 8 types of proteins were combined, the AUC value was found to be 0.850 (p<0.001), sensitivity was 85, and specificity was 80, confirming that combining 8 types of proteins in the serum prior to lung transplantation can predict mortality after lung transplantation with high accuracy.

[0150]

[0151] Example 4. Analysis of the correlation between serum cytokine and inflammation-related protein abundance levels before and after lung transplantation and the occurrence of graft dysfunction after lung transplantation

[0152] In Example 1, cytokine and inflammation-related protein abundances were analyzed for the samples of the finally selected recipients before and after lung transplantation to investigate the association with functional impairment after lung transplantation, namely, the occurrence of rejection.

[0153]

[0154] As a result, the distribution of cytokine and inflammation-related protein abundance levels in survivors with and without functional impairment after lung transplantation was confirmed as shown in Figure 5.

[0155] According to this, it was confirmed that the protein expression levels of NTF3, GDNF, CCL25, TNFRS9, and SCF in the serum before lung transplantation decreased, while the protein expression levels of IL24, IL18R1, MCP-3, and CXCL1 increased. At this time, it was confirmed that CCL25 and CXCL1 showed the same expression pattern in the serum before and after transplantation.

[0156]

[0157] Example 5. Establishment of a Predictive Model for Graft Dysfunction After Lung Transplantation in Survivors

[0158] In Example 4, the serum abundance of cytokines and inflammation-related proteins in lung transplant survivors with and without graft dysfunction was analyzed, and it was confirmed that nine types of proteins were significantly increased or decreased. In Example 5, a model for predicting rejection after lung transplantation among survivors was established, and the recipient operating characteristic curve of a model predicting survivors using protein markers prior to lung transplantation, as well as the sensitivity and specificity of the new prediction model, were analyzed.

[0159]

[0160] As a result, Figures 6a to 6c were confirmed. Specifically, Figures 6a to 6c show the results of analyzing the AUC values, sensitivity, and specificity for nine types of serum cytokines and inflammation-related proteins, namely (a) GDNF, (b) NTF-3, (c) IL-24, (d) TNFRSF9, (e) SCF, (f) IL-18R1, (g) CCL-25, (h) MCP-3, and (i) CXCL-1. Additionally, Figure 6c further shows the results of analyzing the AUC values, sensitivity, and specificity when five types—GDNF, NTF3, IL24, TNFRSF9, and IL18R1—which had the highest AUC values ​​among the nine types of serum cytokines and inflammation-related proteins, were combined.

[0161]

[0162] According to this, when five types of substances were combined, the AUC value was confirmed to be 1 (p<0.001), and the specificity and sensitivity were 100%, indicating that the ability to distinguish between the impaired group and the recovery group among lung transplant survivors was significantly superior.

[0163]

[0164] Example 6. Establishment of a model to predict mortality within 3 months after lung transplantation

[0165] In this embodiment, a predictive model for death within 3 months after lung transplantation, i.e., acute death, was established by analyzing proteins in the serum, and the receiver operating characteristic curve and the sensitivity and specificity of the new predictive model were analyzed.

[0166]

[0167] As a result, Figures 7a and 7b were confirmed. Specifically, Figure 7a shows the results of analyzing the AUC values, sensitivity, and specificity for four proteins, namely (a) FGF19, (b) CCL19, (c) IL22RA1, and (d) TSLP. In addition, Figure 7b shows the results of analyzing the AUC values, sensitivity, and specificity when combining three proteins—IL22RA1, RGF19, and CCL19—which had the highest AUC values ​​among the four cytokines and inflammation-related proteins.

[0168]

[0169] According to this, when three substances were combined, the AUC value was confirmed to be 0.920 (p<0.001), with a specificity of 90% and a sensitivity of 90%, indicating that the ability to predict death within 3 months after lung transplantation was significantly superior.

[0170]

[0171] The foregoing description of the present invention is for illustrative purposes only, and those skilled in the art will understand that other specific forms can be easily modified without altering the technical spirit or essential features of the present invention. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive.

[0172] According to the biomarker composition for screening high-risk groups for acute death after lung transplantation and the use thereof, when investigating the association between the expression of proteins in serum before and after lung transplantation and clinical outcomes, a statistically significant difference in serum abundance was confirmed between individuals before and after lung transplantation, and a new predictive model for the risk of acute death after lung transplantation using three serum proteins was found to show a high AUC value, the biomarker of the present invention is expected to be usefully utilized as a biomarker for screening high-risk groups for acute death after lung transplantation, thus having industrial applicability.

Claims

1. A method for providing information for predicting the risk of acute death after lung transplantation, comprising the following steps: S1) A step of analyzing the level of one or more proteins selected from the group consisting of FGF19 (Fibroblast Growth Factor 19), CCL19 (CC Motif Chemokine Ligand 19), and IL22RA1 (Interleukin-22 Receptor Subunit Alpha-1) or the mRNA thereof in a biological sample isolated from a subject.

2. In paragraph 1, the above method of providing information is, S2) When compared to the level of protein or mRNA of the above substance in biological samples isolated from the control group, A method for providing information, further comprising the step of predicting that a subject will die acutely after lung transplantation if the level of one or more proteins selected from the group consisting of FGF19 and CCL19 or the mRNA level thereof is decreased, or the level of the protein of IL22RA1 or the mRNA level thereof is increased.

3. In Paragraph 1, A method of providing information in which the above biological sample is a biological sample isolated from a subject prior to lung transplantation.

4. In Paragraph 1, A method for providing information, wherein the biological sample is any one selected from the group consisting of serum, whole blood, blood, and plasma.

5. In Paragraph 1, The above acute death is death within 3 months after lung transplantation, a method of providing information.

6. A composition for predicting the risk of acute death after lung transplantation, comprising as an active ingredient a preparation for measuring the level of one or more proteins selected from the group consisting of the following or the mRNA thereof: Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

7. A kit for predicting the risk of acute death after lung transplantation, comprising as an active ingredient a composition for measuring the level of one or more proteins selected from the group consisting of the following or a preparation thereof, and instructions: Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

8. In Paragraph 7, The above instructions are a kit that teaches the method of providing information according to Article 1 or Article 2.

9. A biomarker composition for predicting the risk of acute death after lung transplantation, comprising one or more active ingredients selected from the group consisting of the following: Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

10. Treatment method for high-risk groups for acute death after lung transplantation, including the following steps: S1) A step of analyzing the level of one or more proteins selected from the group consisting of FGF19 (Fibroblast Growth Factor 19), CCL19 (CC Motif Chemokine Ligand 19), and IL22RA1 (Interleukin-22 Receptor Subunit Alpha-1) or the mRNA level thereof in a biological sample isolated from a subject; S2) When compared to the level of protein or mRNA of the above substance in biological samples isolated from the control group, A step of predicting that the subject will die acutely after lung transplantation if the level of one or more proteins selected from the group consisting of FGF19 and CCL19 or their mRNA is decreased, or the level of the IL22RA1 protein or its mRNA is increased; and S3) A step of administering a pharmaceutically effective amount of a therapeutic agent to a subject predicted to die acutely after the lung transplant.

11. Use of preparations measuring the levels of one or more proteins or mRNA selected from the group consisting of the following for predicting the risk of acute death after lung transplantation: Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

12. Use for manufacturing a preparation for predicting the risk of acute death after lung transplantation, which measures the level of one or more proteins or mRNA selected from the group consisting of the following: Fibroblast Growth Factor 19 (FGF19), CC Motif Chemokine Ligand 19 (CCL19), and Interleukin-22 Receptor Subunit Alpha-1 (IL22RA1).

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