A method to aid in predicting the prognosis of interstitial lung disease or the effectiveness of treatment with antifibrotic drugs.

Abstract

The objective is to provide biomarkers that can predict the progression of interstitial lung disease and treatment response, as well as methods to assist in predicting the prognosis of interstitial lung disease or the effectiveness of treatment with antifibrotic drugs. [Solution] We found that the population of fibrotic macrophages was already increased in bronchoalveolar lavage fluid collected before confirming the progression of pulmonary fibrosis. Furthermore, through single-cell RNA sequencing analysis using blood, bronchoalveolar lavage fluid, and lung tissue from various interstitial lung disease patients, we identified a new subset of fibrotic macrophages important for fibrosis formation. We found that this subset increased in patients with progressive pulmonary fibrosis requiring antifibrotic drugs compared to before progression, and that this subset allows for the direct identification of the population of fibrotic macrophages present in the lungs at the protein level.

Description

[Technical Field]

[0001] The present invention relates to a method, a predictive biomarker, and a predictive kit for assisting in predicting the prognosis of interstitial lung disease (ILD) or the therapeutic effect of antifibrotic drugs. [Background technology]

[0002] Interstitial lung diseases, a general term for diseases affecting the interstitium of the lungs, have heterogeneous and diverse etiologies, and their disease progression and prognosis are patient- and underlying disease-specific, making the course of the disease currently unpredictable. Patent Document 1 discloses a method for diagnosing inflammatory lung diseases using procalcitonin in the blood as a marker, but it does not disclose a method for predicting the progression of interstitial lung diseases. Among interstitial lung diseases, progressive pulmonary fibrosis (PPF), a condition that causes progressive and irreversible fibrosis of the lungs, has a poor prognosis of 3-5 years (Non-Patent Document 1). However, there are no objective biomarkers to predict the progression or show treatment response in progressive pulmonary fibrosis, which poses challenges to optimizing diagnosis and treatment.

[0003] The inventors have used a pulmonary fibrosis model mouse to elucidate the interactions between immune and non-immune cells important for the development of fibrosis, as well as the series of processes involved (Non-Patent Literature 2, Non-Patent Literature 3). In recent years, single-cell RNA sequencing (scRNA-seq) analysis has revealed that progressive pulmonary fibrosis forms a diverse subset of immune and non-immune cells that differs from those in healthy lungs (Non-Patent Literature 4), and insights into the existence and function of fibrotic macrophages (FM), a group of macrophages involved in maintaining and promoting fibrosis, have also begun to emerge.

[0004] However, while fibrotic macrophages can now be identified and extracted through gene expression analysis, no have been identified in terms of protein expression, and therefore, fibrotic macrophages have not yet been clinically applied. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Special table number 2010-506146 [Non-patent literature]

[0006] [Non-Patent Document 1] Am J Respir Crit Care Med 2022; 205: e18-e47 [Non-Patent Document 2] Nature 2017; 541(7635): 96-101 [Non-Patent Document 3] Immunity 2020; 52(3): 542-56 e13 [Non-Patent Document 4] Sci Adv 2020; 6: eaba1972 [Overview of the project] [Problems that the invention aims to solve]

[0007] Regarding diagnostic techniques based on cell markers for evaluating fibrotic macrophage-like populations using serum-based blood tests, it is molecularly impossible to directly represent and evaluate fibrotic macrophage populations in serum because differentiation from bone marrow-derived cells to fibrotic macrophages is not completed in the circulating blood. Furthermore, while it is easy to develop kits for evaluating secreted cytokines in bronchoalveolar lavage fluid (BALF), these are not specific to fibrotic macrophages and similarly remain indirect evaluations. Moreover, since measuring serum markers of fibrotic macrophage-like populations and cytokines in bronchoalveolar lavage fluid are specialized tests, they are basically offered as contract services. The present invention aims to provide biomarkers that can predict the progression of interstitial lung disease and treatment response, as well as methods to assist in predicting the prognosis of interstitial lung disease or the therapeutic effect of antifibrotic drugs. [Means for solving the problem]

[0008] To solve the above problems, the inventors conducted extensive research and discovered that the population of fibrotic macrophages was already increased in bronchoalveolar lavage fluid collected before the progression of pulmonary fibrosis was confirmed. Furthermore, through single-cell RNA sequencing analysis using blood, bronchoalveolar lavage fluid, and lung tissue from various interstitial lung disease patients, they identified a new subset of fibrotic macrophages important for fibrosis formation. They found that this subset increased in patients with progressive pulmonary fibrosis requiring antifibrotic drugs compared to before progression, and that this subset allows for the direct identification of the population of fibrotic macrophages present in the lungs at the protein level, thus completing the present invention.

[0009] In other words, the present invention consists of the following. 1. A method for assisting in predicting the prognosis of interstitial lung disease (ILD) or the therapeutic effect of antifibrotic drugs, characterized by detecting fibrotic macrophages in a sample taken from a subject. 2. The method according to item 1, further comprising the step of determining the ratio of the number of fibrotic macrophages to the total number of cells in a sample taken from a subject. 3. The method according to paragraph 1 or 2 above, which indicates that the prognosis is poor or that there is a high probability that an antifibrotic drug will be effective when the ratio of the number of fibrotic macrophages is equal to or greater than a reference value determined based on the ratio of fibrotic macrophages to the total number of cells in a sample taken from a person with interstitial lung disease. 4. The method according to any one of items 1 to 3 above, comprising the step of measuring the expression level of a fibrotic macrophage-specific cell surface marker in a sample taken from the subject. 5. The method according to any one of items 1 to 4 above, which indicates that the prognosis is poor or that there is a high probability that an antifibrotic drug will be effective if the expression level of the fibrotic macrophage-specific cell surface marker is equal to or greater than a reference value determined based on the expression level of the fibrotic macrophage-specific surface marker in a sample taken from a person with interstitial lung disease. 6. The method according to any one of items 1 to 5 above, wherein the fibrotic macrophage-specific cell surface marker whose expression level is measured is a combination of MERTK and one or more selected from the group consisting of CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16. 7. The method according to any one of items 1 to 6 above, wherein the fibrotic macrophage-specific cell surface marker whose expression level is measured is a combination of MERTK, CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16. 8. The method according to any one of items 1 to 7 above, wherein the sample is lung tissue or bronchoalveolar lavage fluid (BALF). 9. The method according to any one of items 1 to 8 above, wherein the interstitial lung disease is progressive pulmonary fibrosis (PPF). 10. The method according to any one of items 1 to 9 above, wherein the expression level of the fibrotic macrophage-specific cell surface marker is measured using a substance capable of specifically binding to the fibrotic macrophage-specific surface marker. 11. The method according to any one of the preceding items 1 to 10, wherein the substance capable of specifically binding to the fibrotic macrophage-specific surface marker comprises any one or more antibodies selected from the group consisting of an anti-MERTK antibody, an anti-CMKLR1 antibody, an anti-FOLR2 antibody, an anti-CD163 antibody, an anti-CD11c antibody, an anti-CD14 antibody, and an anti-CD16 antibody. 12. The method according to any one of the preceding items 1 to 11, wherein the expression level of the fibrotic macrophage-specific surface marker is measured by flow cytometry. 13. A biomarker for predicting the prognosis of interstitial lung disease or the therapeutic effect of an anti-fibrotic drug, comprising any one or more proteins selected from the group consisting of MERTK, CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16. 14. A kit for predicting the prognosis of interstitial lung disease or the therapeutic effect of an anti-fibrotic drug, comprising a reagent containing a substance capable of specifically binding to a fibrotic macrophage-specific surface marker. 15. The kit according to item 14 above, wherein the fibrotic macrophage-specific cell surface marker is any one or more selected from the group consisting of MERTK, CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16.

Advantages of the Invention

[0010] According to the present invention, a biomarker capable of predicting the progression of the pathological condition and treatment responsiveness of interstitial lung disease, and a method for assisting in predicting the prognosis of interstitial lung disease or the therapeutic effect of an anti-fibrotic drug can be provided.

Brief Description of the Drawings

[0011] [Figure 1] Shows the results of single-cell transcriptome analysis of bronchoalveolar lavage fluid from untreated interstitial lung disease patients. UMAP1 and UMAP2 indicate the relative positions when high-dimensional single-cell transcriptome data is converted into two dimensions by Uniform Manifold Approximation and Projection. (Example 1) [Figure 2]The results of comparing the ratio of the number of fibrotic macrophage cluster cells in all clusters in the bronchoalveolar lavage fluid of untreated interstitial lung disease patients by Student's t-test are shown. Patients who did not develop progressive pulmonary fibrosis are shown on the left, and patients who developed progressive pulmonary fibrosis after bronchoalveolar lavage fluid collection are shown on the right. (Example 1) [Figure 3] The immunohistochemical results of tissue sections of patients with non-specific interstitial pneumonia (hereinafter sometimes simply referred to as "NSIP"), pleuroparenchymal fibroelastosis (hereinafter sometimes simply referred to as "PPFE"), hypersensitivity pneumonitis (hereinafter sometimes simply referred to as "HP"), and idiopathic pulmonary fibrosis (hereinafter sometimes simply referred to as "IPF") are shown. The scale bar indicates 100 μm. (Example 2) [Figure 4] The results of CyTOF analysis of surface markers of fibrotic macrophages obtained by analyzing the human single-cell RNA sequencing data of bronchoalveolar lavage fluid of untreated interstitial lung disease patients are shown. (Example 2) [Figure 5] The results of FACS analysis of surface markers of fibrotic macrophages obtained by analyzing the human single-cell RNA sequencing data of bronchoalveolar lavage fluid of untreated interstitial lung disease patients are shown. (Example 2) **BEST MODE FOR CARRYING OUT THE INVENTION**

[0012] The present invention relates to a method for assisting in predicting the prognosis of interstitial lung disease or the therapeutic effect of an antifibrotic drug (hereinafter sometimes referred to as "the method of the present invention").

[0013] The present invention also relates to a biomarker for predicting the prognosis of interstitial lung disease or the therapeutic effect of an antifibrotic drug (hereinafter sometimes referred to as "the biomarker of the present invention" or "the marker of the present invention").

[0014] In this invention, the "fibrotic macrophage-specific surface marker" is an indicator for predicting the prognosis and therapeutic effect of interstitial lung disease. The marker of this invention consists of one or more selected from the group consisting of MERTK (MER proto-oncogene tyrosine kinase), CMKLR1 (Chemerin Chemokine-Like Receptor 1), FOLR2 (Folate Receptor Beta), CD163 (cluster of differentiation 163), CD11c (cluster of differentiation 11c), CD14 (cluster of differentiation 14), and CD16 (cluster of differentiation 16). The combination of markers of this invention is not particularly limited. Macrophages are major immune cells in the lung, and in the context of this invention, macrophages present in fibrous tissue and involved in the progression of fibrosis are called "fibrotic macrophages." In the following examples, it has been confirmed that the marker of this invention is specifically highly expressed in fibrotic macrophages.

[0015] In the context of the present invention, "biomarker" or "marker" refers to, for example, an organic biomolecule that is present in a sample taken from a patient having a particular disease condition, compared to a comparable sample taken from a subject not having the disease condition (e.g., a negatively diagnosed, normal, or healthy subject).

[0016] In the present invention, the "subject" is a human or a non-human mammal (e.g., primates, dogs, cats, goats, horses, pigs, mice, rats, rabbits, etc.), preferably a human, for example, a human who has (or is at risk of developing) interstitial lung disease.

[0017] In this invention, "interstitial lung disease (ILD)" refers to a group of diseases occurring in the interstitium of the lungs, including interstitial pneumonia and pulmonary fibrosis. The disease state may remain the same for a long period of time or may change rapidly. Interstitial lung disease can progress gradually or rapidly, and symptoms can vary from very mild to moderate to very severe. Among interstitial lung diseases, progressive pulmonary fibrosis (PPF) is defined as the presence of at least two of three criteria in patients with interstitial lung disease accompanied by radiological pulmonary fibrosis of known or unknown causes other than idiopathic pulmonary fibrosis (IPF) within the past year: worsening of respiratory symptoms, decreased function, and radiological progression (Am J Respir Crit Care Med 2022; 205: e18-e47).

[0018] In this invention, "sample" refers to material obtained from a subject, and may be the specimen itself obtained from a living organism, or it may be prepared from the specimen by any known or future development method. Examples include lung tissue, bronchoalveolar lavage fluid, blood, pleural fluid, etc. Bronchoalveolar lavage fluid is collected in conventional pulmonary fibrosis examinations, a portion of which is used for the examination, and the remainder is discarded. The ability to utilize bronchoalveolar lavage fluid is advantageous for both medical facilities and patients, as it reduces the burden on them.

[0019] In this invention, "poor prognosis" means progression of interstitial lung disease fibrosis, worsening of symptoms, decline in respiratory function, and onset of progressive pulmonary fibrosis, while "good prognosis" means a decrease in the progression of interstitial lung disease fibrosis, improvement of symptoms, and improvement of respiratory function. "Antifibrotic drug is effective" means that administration of an antifibrotic drug has the effect of suppressing the progression of interstitial lung disease fibrosis, improving symptoms, and / or improving respiratory function.

[0020] The present invention is characterized by detecting fibrotic macrophages in a sample taken from a subject.

[0021] The method for detecting fibrotic macrophages is not particularly limited, but for example, they can be detected by gene expression analysis. In gene expression analysis, in addition to known markers that are expressed in macrophages in pulmonary fibrosis, markers that will be developed in the future may be used, for example, macrophage cluster-specific gene markers obtained by spatial transcriptome analysis of the pulmonary fibrotic region may be used. Known markers include those described in the literature (Sci Immunol. 2023 Apr 14;8(82):eadd8945), etc.

[0022] In one embodiment, the method of the present invention includes the step of determining the ratio of the number of fibrotic macrophages to the total number of cells in a sample taken from a subject.

[0023] The number of cells can be determined, for example, by calculating the proportion of cells in clusters identified as fibrotic macrophages through single-cell transcriptome analysis of a sample taken from the subject (total number of cells / total number of cells in the cluster).

[0024] If the ratio of fibrotic macrophages in the above process is greater than or equal to a reference value determined based on the ratio of fibrotic macrophages to the total number of cells in a sample taken from a person with interstitial lung disease, it indicates a poor prognosis or a high probability that antifibrotic drugs will be effective.

[0025] The above reference values ​​are based on data regarding the ratio of fibrotic macrophages to the total number of cells in samples taken from individuals with interstitial lung disease, and may be, for example, the mean or median ratio of fibrotic macrophages to the total number of cells in samples taken from individuals with interstitial lung disease. In one embodiment, for example, these values ​​may be established based on a comparison between a group of individuals with interstitial lung disease who have progressed to progressive pulmonary fibrosis and a group of individuals who have not progressed to progressive pulmonary fibrosis.

[0026] The antifibrotic agent in the present invention is not particularly limited, and examples include pirfenidone and nintedanib.

[0027] In one embodiment, the method of the present invention includes the step of measuring the expression level of a fibrotic macrophage-specific cell surface marker in a sample collected from a subject.

[0028] If the expression level of fibrotic macrophage-specific cell surface markers in the above process is above the reference value determined based on the expression level of fibrotic macrophage-specific surface markers in samples taken from individuals with interstitial lung disease, it indicates a poor prognosis or a high probability that antifibrotic drugs will be effective.

[0029] The above reference values ​​can be cutoff values ​​determined using various statistical analysis methods. For example, a multivariate logistic regression model can be used, with the expression levels of each marker as explanatory variables, to set a cutoff value for predicting the overall risk. Specifically, using a binary outcome of patients with interstitial lung disease—those who progressed to progressive pulmonary fibrosis and those who did not—the predictive performance of each marker and its combination can be evaluated using a logistic regression model with ROC curves and AUC, and the point where the Youden index (sensitivity + specificity - 1) is maximized can be set as the cutoff value. Furthermore, when using continuous variables such as survival time from the reference point as the outcome, it is also possible to determine the cutoff value using multivariate analysis such as a Cox proportional hazards model.

[0030] In the above process, the expression levels of one or more proteins selected from the group consisting of MERTK, CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16 are measured as fibrotic macrophage-specific cell surface markers.

[0031] In one embodiment, the expression levels of MERTK and one or more selected from the group consisting of CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16 are measured as fibrotic macrophage-specific cell surface markers.

[0032] In one embodiment, the expression levels of CMKLR1 and any one or more selected from the group consisting of MERTK, FOLR2, CD163, CD11c, CD14, and CD16 are measured as fibrotic macrophage-specific cell surface markers.

[0033] In one embodiment, the expression levels of FOLR2 and any one or more selected from the group consisting of MERTK, CMKLR1, CD163, CD11c, CD14, and CD16 are measured as fibrotic macrophage-specific cell surface markers.

[0034] In one embodiment, the expression levels of CD163 and one or more selected from the group consisting of MERTK, CMKLR1, FOLR2, CD11c, CD14, and CD16 are measured as fibrotic macrophage-specific cell surface markers.

[0035] In one embodiment, the expression levels of CD11c and one or more selected from the group consisting of MERTK, CMKLR1, FOLR2, CD163, CD14, and CD16 are measured as fibrotic macrophage-specific cell surface markers.

[0036] In one embodiment, the expression levels of CD14 and one or more selected from the group consisting of MERTK, CMKLR1, FOLR2, CD163, CD11c, and CD16 are measured as fibrotic macrophage-specific cell surface markers.

[0037] In one embodiment, the expression levels of CD16 and one or more selected from the group consisting of MERTK, CMKLR1, FOLR2, CD163, CD11c, and CD14 are measured as fibrotic macrophage-specific cell surface markers.

[0038] In one embodiment, the expression levels of a combination of MERTK, CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16 are measured as fibrotic macrophage-specific cell surface markers.

[0039] The method for measuring the expression level of fibrotic macrophage-specific surface markers is not particularly limited, and examples include immunological techniques such as flow cytometry, ELISA, immunohistochemistry, and Western blotting, with flow cytometry being preferred.

[0040] The expression levels of fibrotic macrophage-specific cell surface markers are measured using substances that can specifically bind to these markers.

[0041] In the present invention, "substances that can specifically bind to fibrillating macrophage-specific surface markers" include, for example, binding proteins, and specifically, anti-MERTK antibodies, anti-CMKLR1 antibodies, anti-FOLR2 antibodies, anti-CD163 antibodies, anti-CD11c antibodies, anti-CD14 antibodies, anti-CD16 antibodies, or fragments thereof. The antibodies may be antibody-modified products that include functional chemical modifications necessary for acquiring or maintaining specific binding activity with fibrillating macrophage-specific surface marker proteins, and / or chemical modifications for labeling necessary for detecting fibrillating macrophage-specific surface marker proteins.

[0042] The present invention relates to a kit for predicting the prognosis of interstitial lung disease or the therapeutic effect of antifibrotic drugs (hereinafter sometimes referred to as "the kit of the present invention").

[0043] The kit of the present invention includes a reagent containing a substance that can specifically bind to a surface marker specific to fibrotic macrophages.

[0044] The “reagent containing a substance that can specifically bind to a fibrillating macrophage-specific surface marker” in the present invention may, for example, be a reagent containing a substance that can bind to a fibrillating macrophage-specific surface marker protein, and more specifically, may be an antibody reagent containing one type of antibody that can bind to at least one antigen among MERTK, CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16, or may be an antibody cocktail reagent containing a mixture of multiple types of antibodies that can bind to different or the same antigen. For example, it may be an antibody reagent containing an anti-MERTK antibody, an anti-CMKLR1 antibody, an anti-FOLR2 antibody, an anti-CD163 antibody, an anti-CD11c antibody, an anti-CD14 antibody, an anti-CD16 antibody, or fragments of these antibodies, or it may be an antibody cocktail reagent containing any two or more antibodies selected from the group consisting of anti-MERTK antibody, anti-CMKLR1 antibody, anti-FOLR2 antibody, anti-CD163 antibody, anti-CD11c antibody, anti-CD14 antibody, and anti-CD16 antibody. Each antibody may be labeled with a fluorescent dye. Preferably, each antibody in a single antibody cocktail reagent is labeled with a fluorescent dye having a different peak wavelength in its fluorescence spectrum. The kit of the present invention may contain multiple types of antibody reagents and / or multiple types of antibody cocktail reagents.

[0045] The kit of the present invention may further include additional components that are effective for carrying out the method of the present invention. For example, it may further include means for taking a sample from a subject, means for preparing a sample, a control or reference sample, and / or instructions for use. [Examples]

[0046] The present invention will be described in more detail below with reference to examples to further the understanding of the present invention, but it goes without saying that the present invention is not limited to the examples described. The following examples were carried out in accordance with the Declaration of Helsinki and were approved by the Ethics Review Committee at Osaka University Hospital.

[0047] Bronchoalveolar lavage (BALF) samples and lung tissue were obtained from untreated interstitial lung disease (ILD) patients. Written informed consent was obtained from all participants.

[0048] (Example 1) Identification and analysis of fibrotic macrophages Spatial transcriptome analysis of lung tissue using the Visium Spatial Gene Expression platform (10x Genomics) identified macrophage clusters as clusters concentrated in fibrotic regions, and SPP1, TREM2, APOE, GPNMB, LYZ, MARCO, CD14, ITGAX, CHI3L1, SPI1, CD63, MMP9, CD163, and IL1RN were used as macrophage cluster-specific gene markers. Subsequently, single-cell transcriptome analysis of BALF from untreated interstitial lung disease patients was performed (sequencer: DNBSEQ-G400RS (MGI Tech, Shenzhen, China)). Single-cell RNA sequencing (scRNA-seq) was performed on BALF from a total of 20 patients. The scRNA-seq fastq files were processed using 10x Genomics Cell Ranger X.0.0 (Zheng GX, Terry JM, Belgrader P, Ryvkin P, Bent ZW, Wilson R et al. Massively parallel digital transcriptional profiling of single cells. Nat Commun 2017;8:14049) with default settings, and gene expression profiles of hash tags attached to cell barcodes were obtained. After filtering out poor-quality cells from all detected cells, dimensionality reduction and clustering were performed using UMAP. More specifically, the possibility of doublets was predicted and filtered using Scrublet (Wolock SL, Lopez R, Klein AM. Scrublet: computational identification of cell doublets in single-cell transcriptomic data. Cell Syst 2019;8:281-291.e9).The number of reads in the sample, the number of genes per barcode, and the mitochondrial gene concentration were fitted to a mixture distribution of two Gaussian distributions, and then filtered (Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O et al. Scikit-learn: machine learning in Python. J Mach Learn Res 2011;12:2825-2830). Batch effect correction was performed using BBKNN (Polanski K, Young MD, Miao Z, Meyer KB, Teichmann SA, Park JE. BBKNN: fast batch alignment of single cell transcriptomes. Bioinformatics. Park: BBKNN 2020;36:964-965), and the data was visualized using Leiden clustering (Traag VA, Waltman L, van Eck NJ. From Louvain to Leiden: guaranteeing well-connected communities. Sci Rep 2019;9:523), resulting in 24 clusters. Clusters that highly expressed known macrophage markers, as well as macrophage cluster-specific gene markers obtained by spatial transcriptome analysis, were identified as fibrotic macrophages (Figure 1).

[0049] Next, the scRNA-seq data was divided into two groups: those who later developed progressive pulmonary fibrosis (n=10) and those who did not (n=10). The proportion of fibrotic macrophage cluster cells (number of cells in fibrotic macrophage clusters / total number of cells after filtering) in all clusters after filtering was calculated, and the two groups were compared using Student's t-test. Patients with progressive pulmonary fibrosis were defined as those who met the following criteria between BALF collection and the scRNA-seq procedure, based on previously reported data (Flaherty KR, Wells AU, Cottin V, Devaraj A, Walsh SLF, Inoue Y, et al. Nintedanib in Progressive Fibrosing Interstitial Lung Diseases. N Engl J Med. 2019 Oct 31;381(18):1718-27). • Must be 20 years of age or older • High-resolution CT (HRCT) shows pulmonary fibrosis (including reticular opacities or traction bronchiectasis, regardless of the presence or absence of honeycomb lung findings) in more than 10% of the entire lung area. Patients diagnosed with ILD who, under appropriate disease management by a physician, meet any of the following criteria for progressive ILD within 24 months of the observation period: i) to iv) i) A decrease of 10% or more in the predicted percentage of forced vital capacity (%FVC) (relative change) is observed. ii) A decrease in %FVC of 5% or more but less than 10% (relative change) is observed, and respiratory symptoms worsen. iii) A decrease of 5% to less than 10% in %FVC (relative change) is observed, and an increase in fibrotic changes is observed on chest imaging. iv) Worsening of respiratory symptoms and increased fibrotic changes on chest imaging.

[0050] As a result, patients who progressed to progressive pulmonary fibrosis (BALF) had an increased number of fibrotic macrophages in their BALF compared to patients who did not progress to progressive pulmonary fibrosis (Figure 2). Since the fibrotic macrophage population was already increased in BALF collected before the progression of pulmonary fibrosis was confirmed, fibrotic macrophages can be used to predict the future progression of interstitial pneumonia in patients. Furthermore, since the response to immunosuppressants is generally poor and antifibrotic drugs become the appropriate treatment option when the lungs of interstitial pneumonia patients truly enter the fibrotic phase, it is also possible to predict the treatment response to antifibrotic drugs.

[0051] Furthermore, immunohistochemistry was performed on tissue sections from patients with nonspecific interstitial pneumonia (NSIP), pleural parenchymal fibroblastosis (PPFE), hypersensitivity pneumonitis (HP), and idiopathic pulmonary fibrosis (IPF). Each lung section, 4 μm thick, fixed in formalin and embedded in paraffin, was prepared using standard procedures. The tissue was immunostained in antibody diluent (DAKO) with rabbit anti-human CD11c antibody at a 1:150 dilution. EnVision+ System- HRP Labelled Polymer α-Rabbit (DAKO) and DAB (DAKO) were used as chromogenic agents. Counterstaining was performed using hematoxylin. The results revealed the presence of fibrotic macrophages across the disease spectrum (Figure 3).

[0052] (Example 2) Identification of fibrotic macrophage-specific surface markers Human single-cell RNA library preparation and sequencing Single-cell cells were collected from lung tissue as previously reported (Reyfman PA, Walter JM, Joshi N, et al. Single-Cell Transcriptomic Analysis of Human Lung Provides Insights into the Pathobiology of Pulmonary Fibrosis. Am J Respir Crit Care Med 2019; 199: 1517-36). The single-cell suspension was filtered through a 70 μm nylon mesh cell strainer (352350; Corning Inc., Corning, NY, USA) and centrifuged at 400 × g at 4°C for 10 minutes. After discarding the supernatant, the cells were washed with Dulbecco's phosphate-buffered saline (D-PBS), resuspended in D-PBS, and passed through a 40 μm nylon mesh cell strainer (352340; Corning Inc., Corning, NY, USA). The cell concentration was finalized to approximately 1,000 cells / mL. Using the Chromium Next GEM Single Cell 5' Reagent Kit v2 from 10x Genomics (10x Genomics, Pleasanton, CA, USA), 10,000 cells were loaded into a Chromium controller per reaction, and scRNA-seq was performed. Paired-end sequencing was performed using a DNBSEQ-G400RS sequencer (MGI Tech, Shenzhen, China) (read 1: 28 bp, read 2: 100 bp).

[0053] Preprocessing of human single-cell RNA sequencing and identification and analysis of fibrotic macrophage surface markers Human scRNA-seq data analysis was performed in the same manner as previously reported (Morita R, Kubota-Koketsu R, Lu X, et al. COVID-19 relapse associated with SARS-CoV-2 evasion from CD4+ T-cell recognition in an agammaglobulinemia patient. iScience. 2023; 26). The scRNA-seq fastq files were processed using 10× Genomics Cell Ranger 6.0.0 (Zheng GXY, Terry JM, Belgrader P, et al. Massively parallel digital transcriptional profiling of single cells. Nat Commun 2017; 8: 14049) with default settings to obtain gene expression profiles of hash tags attached to cell barcodes. Using the R package Seurat, single-cell objects were created after filtering with percent.mt < 15 & nFeature_RNA < 8000 & nFeature_RNA > 500, and then normalized to multiple BALF datasets. The top 3000 differential genes were combined and integrated using Harmony (I. Korsunsky, N. Millard, J. Fan, et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 2019: 1289-1296), and batch effects of the samples were corrected. Dimensionality reduction was performed using principal component analysis, and cell clustering was performed using 20 principal components and a resolution of 0.5.Annotation of fibrotic macrophages was performed manually using previously identified and newly identified genetic markers (Wendisch D, Dietrich O, Mari T, von Stillfried S, Ibarra IL, Mittermaier M, et al. SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis. Cell. 2021 Dec 22;184(26):6243-6261.e27;Morse C, Tabib T, Sembrat J, Buschur K, Bittar HT, Valenzi E, et al. Proliferating SPP1 / MERTK-expressing macrophages in idiopathic pulmonary fibrosis. Eur Respir J. 2019 Aug;54(2):1802441;Misharin AV, Morales-Nebreda L, Reyfman PA, Cuda CM, Walter JM, McQuattie-Pimentel AC, et al. Monocyte-derived alveolar macrophages drive lung fibrosis and persist in the lung over the life span. Journal of Experimental Medicine. 2017 Aug 7;214(8):2387-404). To explore surface markers for fibrotic macrophages, a statistically robust computational framework (COMET) for identifying candidate marker panels consisting of one or more genes was implemented in this population, creating a panel of surface markers for fibrotic macrophages. Furthermore, specific surface markers were ranked using an alternative method (sc2marker), and genes extracted in a similar manner to those obtained with COMET were listed.Each analysis was performed using multiple databases of surface protein markers (in silico human surfaceome (https: / / wlab.ethz.ch / surfaceome / ), The Human Protein Atlas (https: / / www.proteinatlas.org / )) (Delaney C, Schnell A, Cammarata LV, Yao‐Smith A, Regev A, Kuchroo VK, et al. Combinatorial prediction of marker panels from single‐cell transcriptomic data. Molecular Systems Biology. 2019 Oct;15(10):e9005; Li R, Banjanin B, Schneider RK, Costa IG. Detection of cell markers from single cell RNA-seq with sc2marker. BMC Bioinformatics. 2022 Jul 12;23(1):276).

[0054] Next, mass cytometry (CyTOF) and fluorescence-activated cell sorting (FACS) were performed to verify the expression levels and distribution of identification markers in BALF cells. CyTOF was performed using a Helios® mass cytometer (Fluidigm), and data was acquired using CyTOF software v6.7 (Fluidigm). FACS was performed using a FACSAria® III cell sorter (BD Biosciences), and data was acquired and analyzed using FACSDiva software (BD Biosciences) and FlowJo v10 (Tree Star). BALF samples were centrifuged at 4°C at 1,500 rpm for 3 minutes, and the supernatant was removed to collect the cell pellet. The cell pellet was washed twice with phosphate-buffered saline (PBS) and incubated with antibodies according to modality. In CyTOF, different metals were used for each antibody, as shown in Figure 4. 165 Ho, 167 Er,148 Nd, 159 Tb, 141 Pr, 163 Dy, 154 Sm, 160 Gd, 173 Yb, 174 labeled with Yb). Information on the antibodies used in CyTOF and FACS is shown below. (CyTOF) MERTK: Anti-Mer, Human, Goat-Poly(AF891; R&D Systems, Inc., MN, USA) CMKLR1: Anti-ChemR23, Human, Mouse-Mono(84939.111)(MAB362; R&D Systems, Inc., MN, USA) FOLR2: Mouse mab FOLR2 Ab (EM-35)(NBP2-62208; Novus Biologicals, Inc, CO, USA) CD163: Anti-Human CD163 MAb (Clone 215927)(MAB1607-100; R&D Systems, Inc., MN, USA) CD11c, CD;14, CD16: Maxpar™ Human PB Phenotyping Panel Kit(201304; Standard BioTools Inc., CA, USA) (FACS) MERTK: Brilliant Violet 421™ anti-human MERTK Antibody(367603; Biolegend, CA, USA) CMKLR1: Human ChemR23 PE-conjugated Antibody(FAB362P; R&D Systems, Inc., MN, USA) FOLR2: FOLR2 Antibody (EM-35) [Alexa Fluor™ 488] (NBP2-62208; Novus Biologicals, CO, USA) CD11c:PerCP / Cyanine5.5 anti-mouse CD11c Antibody(117328; Biolegend, CA, USA)

[0055] CyTOF and FACS results showed that MERTK, CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16 were specifically highly expressed in fibrotic macrophages, and were identified as the optimal combination of surface markers specific to fibrotic macrophages (Figures 4 and 5). [Industrial applicability]

[0056] Since the biomarker according to the present invention can be sufficiently detected with existing hospital equipment, results can be provided quickly through in-house testing without the burden of introducing new testing equipment or requiring clinical laboratory technicians to acquire new skills, thereby enabling early therapeutic intervention and leading to improved patient prognosis. Furthermore, since bronchoalveolar lavage (BAL) fluid samples, which were largely discarded in conventional BAL testing, can be utilized without waste, objective clinical strategies for treating interstitial lung disease can be provided without increasing patient invasiveness.

Claims

1. A method for predicting the prognosis of interstitial lung disease (ILD) or the therapeutic effect of antifibrotic drugs, characterized by detecting fibrotic macrophages in a sample taken from a subject.

2. The method according to claim 1, comprising the step of determining the ratio of the number of fibrotic macrophages to the total number of cells in a sample taken from a subject.

3. The method according to claim 2, wherein if the ratio of the number of fibrotic macrophages is greater than or equal to a reference value determined based on the ratio of fibrotic macrophages to the total number of cells in a sample taken from a person with interstitial lung disease, it indicates that the prognosis is poor or that there is a high probability that an antifibrotic drug will be effective.

4. The method according to claim 1, comprising the step of measuring the expression level of a fibrotic macrophage-specific cell surface marker in a sample taken from a subject.

5. The method according to claim 4, wherein if the expression level of the fibrotic macrophage-specific cell surface marker is greater than or equal to a reference value determined based on the expression level of the fibrotic macrophage-specific surface marker in a sample taken from a person with interstitial lung disease, it indicates that the prognosis is poor or that there is a high probability that an antifibrotic drug will be effective.

6. The method according to claim 4, wherein the fibrotic macrophage-specific cell surface marker whose expression level is measured is a combination of MERTK and one or more selected from the group consisting of CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16.

7. The method according to claim 4, wherein the fibrotic macrophage-specific cell surface marker whose expression level is measured is a combination of MERTK, CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16.

8. The method according to any one of claims 1 to 7, wherein the sample is lung tissue or bronchoalveolar lavage fluid (BALF).

9. The method according to any one of claims 1 to 7, wherein the interstitial lung disease is progressive pulmonary fibrosis (PPF).

10. The method according to claim 4, wherein the expression level of the fibrotic macrophage-specific cell surface marker is measured using a substance capable of specifically binding to the fibrotic macrophage-specific surface marker.

11. The method according to claim 10, wherein the substance capable of specifically binding to the fibrotic macrophage-specific surface marker comprises one or more antibodies selected from the group consisting of anti-MERTK antibody, anti-CMKLR1 antibody, anti-FOLR2 antibody, anti-CD163 antibody, anti-CD11c antibody, anti-CD14 antibody, and anti-CD16 antibody.

12. The method according to claim 4, wherein the expression level of the fibrotic macrophage-specific surface marker is measured by flow cytometry.

13. A biomarker for predicting the prognosis of interstitial lung disease or the efficacy of antifibrotic drugs, comprising one or more proteins selected from the group consisting of MERTK, CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16.

14. A kit for predicting the prognosis of interstitial lung disease or the therapeutic effect of antifibrotic drugs, comprising a reagent containing a substance that can specifically bind to a fibrotic macrophage-specific surface marker.

15. The kit according to claim 14, wherein the fibrotic macrophage-specific cell surface marker is one or more selected from the group consisting of MERTK, CMKLR1, FOLR2, CD163, CD11c, CD14, and CD16.

Images