Biomarker for detecting renal cell carcinoma

Abstract

The invention provides a biomarker capable of specifically detecting renal cell carcinoma. The present invention finds that ACD-RCC has improved sialylation (sialic acid modification) compared to cc-RCC by means of a technique for collecting a cancer-specific region from a pathological tissue sample under a microscope and by means of a multi-omics analysis such as a lectin array or RNAseq, and on the basis of this, the cancer-specific region can be identified by means of a glycoproteomics analysis including mass spectrometry. A glycoprotein group having a sugar chain structure having a specific sugar chain modification, in particular a sialic acid modification, among proteomes for identifying cancer tissue of renal cell carcinoma is provided as a novel renal cell carcinoma-specific biomarker.

Description

Technical Field

[0001] The present invention relates to biomarkers for the detection of renal cell carcinoma. Background Art

[0002] Renal cell carcinoma (RCC) ranks 14th among all cancers worldwide, with a prevalence of 2.4% (as of 2020). However, the incidence of RCC is particularly high among dialysis patients compared to healthy controls, compared to other cancer types. The standardized incidence ratios for dialysis patients compared to healthy controls are reported to be 9.7 (95% CI: 8.3-11.2) for men and 11.0 (95% CI: 8.2-14.4) for women in Japan (Non-Patent Document 1), 5.4 (95% CI: 4.3-6.7) in Oceania (Non-Patent Document 2), and 4.03 (95% CI: 3.88-4.19) in the United States (Non-Patent Document 3). Against this backdrop, the development of acquired cystic kidney disease (ACKD), considered a non-hereditary disease, contributes to an increased incidence of RCC. ACKD is a non-hereditary cystic disease with a high prevalence, accounting for 7-22% of patients with renal failure before the introduction of blood purification therapy, 60% of patients with a dialysis history of 2-4 years, and over 90% of patients with a dialysis history of 8 years or more (Non-Patent Document 4). It is believed that the higher standardized incidence rate is also reflected in the longer duration of dialysis and the smaller number of kidney transplants in Japanese dialysis patients compared to those in Europe and the United States. Furthermore, the concept of acquired cystic kidney disease-associated renal cell carcinoma (ACD-RCC) (Non-Patent Document 4) has been established as a histotype of renal cell carcinoma that specifically develops in dialysis kidneys. This was also published in the fourth edition (2016) of the WHO Classification of Renal Cell Tumors and continued to be used in the fifth edition (2022). ACD-RCC exhibits follicular, cribriform, microcystic, and cystic morphologies, with eosinophilic granular cytoplasm and moderately to highly dysmorphic nuclei. Immunohistochemical characteristics include positive expression of α-methyl-acyl-coenzyme A (AMACR), a RCC marker, and MME (CD10), while negative expression of CK7 (Non-Patent Literature 5), but no specific marker has been established. A report of 66 cases (Non-Patent Literature) showed that ACD-RCC was the most common type of renal cell carcinoma in dialysis patients, accounting for 36%, followed by clear cell papillary renal cell carcinoma at 23%. Furthermore, clear cell renal cell carcinoma (cc-RCC), which accounts for over 70% of renal cancer in healthy individuals, was found at 18%, followed by papillary renal cell carcinoma (15%) and chromophobe renal cell carcinoma (8%). A Japanese report on the clinical pathology of renal cell carcinoma in 291 dialysis patients, reflecting the WHO 2016 report, was published.The incidence of ACD-RCC (as a comparison, the incidence of cc-RCC, which accounts for the majority of non-dialysis cases, was recorded) was 7.6% (76.1%) before 10 years of dialysis, but reversed to 43.6% (38.1%) after 10 to 15 years of dialysis, and reached 50.7% (21.6%) after 15 to 20 years of dialysis, indicating a high frequency (Non-Patent Document 6). Currently, the number of dialysis patients in Japan is estimated to reach 345,000, and the number is estimated to reach 4 million worldwide. The number of dialysis patients in Asia is particularly increasing (the number of dialysis patients in China was 235,000 in 2011, but will increase to 693,000 in 2020), so the number of renal cell carcinoma cases is expected to rise in the future. Early detection is crucial in cancer treatment, but no tumor markers specific for renal cell carcinoma have been established for either dialysis or non-dialysis patients. Therefore, the diagnosis of renal cell carcinoma mainly relies on the incidental findings of imaging diagnosis, and preoperative biopsy diagnosis (tissue diagnosis) is not implemented except for special exceptions. Since there is no tumor marker effective for tracking, the tracking after treatment is still centered on imaging examination. In dialysis cases, due to the increased risk of renal cell carcinoma, although the evidence level is low, in fact, all patients undergo regular CT examinations (at least once a year). What makes diagnosis difficult in dialysis cases is ACKD lesions (cysts), which are difficult to obtain contrast effects in dynamic CT. Therefore, ACD-RCC is particularly difficult to diagnose by imaging. Although specific imaging features have not yet been found, it is generally believed that there is a slight enhancement on CT, a low signal on T2 on MRI, and restricted diffusion (restricted diffusion) is found in diffusion-weighted images (non-patent literature 7). Although there are reports that contrast ultrasound (non-patent literature 8) of perfluorobutane microbubbles and PET-CT are useful for imaging diagnosis of dialysis renal cancer (non-patent literature 9), they remain in the research of a few cases.

[0003] Existing technology

[0004] Non-patent literature 1: Clin. Pract. 2004: 97; c11-6

[0005] Non-patent document 2: Nephrol. Dial. Transplant. 2009: 24; 3225-31

[0006] Non-patent document 3: AM. J. Kidney Dis. 2015: 65; 763-72

[0007] Non-patent literature 4: Am. J. Surg. Pathol. 2006; 30: 141-53

[0008] Non-patent literature 5: Arch. Pathol. Lab. Med. 2017; 141: 600-6

[0009] Non-patent literature 6: Pathol. Int. 2018; 68: 543-9

[0010] Non-patent literature 7: Abdom Radiol (NY). 2022; 47(8), 2858-2866.

[0011] Non-patent literature 8: Medicine (Baltimore). 2019; 98: e18053

[0012] Non-patent literature 9: Clin. Exp. Nephrol. 2011; 15: 136-40 Summary of the Invention

[0013] Currently, no tumor markers have been reported that are specific for renal cell carcinoma, regardless of whether patients are on dialysis or not. The present invention was made in response to this situation, and its technical problem is to provide a biomarker that can specifically detect renal cell carcinoma, particularly in patients on dialysis.

[0014] The technical solutions of the present invention for solving the above technical problems are as follows:

[0015] [1] A biomarker for detecting renal cell carcinoma, comprising a glycoprotein derived from renal tissue having sialylated sugar chains whose expression is increased due to cancerous transformation.

[0016] [2] The biomarker according to [1], wherein the glycoprotein derived from renal tissue includes a glycoprotein derived from renal tubular epithelial cells.

[0017] [3] The biomarker according to [1] or [2], wherein the renal tissue-derived glycoprotein comprises one or more glycoproteins selected from the group consisting of GPNMB, Megalin, ACE2, and MME.

[0018] [4] The biomarker according to any one of [1] to [3], wherein the renal cell carcinoma is renal cell carcinoma in a dialysis patient.

[0019] [5] A method for detecting a biomarker, comprising: detecting the biomarker according to any one of claims 1 to 4 in vitro in a test sample obtained from a subject.

[0020] [6] The detection method according to [5], which comprises a sandwich ELISA method.

[0021] [7] The detection method according to [5] or [6], wherein the test sample is serum.

[0022] [8] A diagnostic kit for renal cell carcinoma comprising a unit for detecting the biomarker according to any one of [1] to [4].

[0023] [9] The kit according to [8],

[0024] The detection unit comprises an antibody that binds to the kidney tissue-derived glycoprotein having sialylated sugar chains, and a lectin that binds to the sialylated sugar chains.

[0025]

[10] A method for searching for a renal cell carcinoma marker, comprising the step of investigating changes in the sugar chain structure of a glycoprotein derived from renal tissue.

[0026]

[11] The search method according to

[10] , comprising analysis using a lectin array or protein immunoblotting.

[0027] In addition, the present invention also provides an invention with the following technical solutions.

[0028] [1] A method for diagnosing renal cell carcinoma, comprising: detecting a biomarker in a subject, wherein the biomarker comprises a glycoprotein derived from renal tissue having sialylated sugar chains whose expression is increased due to cancerous transformation.

[0029] [2] Use of a glycoprotein derived from kidney tissue having sialylated sugar chains whose expression is increased due to cancerous transformation as a biomarker for diagnosing renal cell carcinoma.

[0030] [3] A combination of one or more glycoproteins selected from the group consisting of GPNMB, Megalin, ACE2, and MME, which have sialylated sugar chains whose expression is enhanced by cancerous transformation.

[0031] [4] A diagnostic kit for renal cell carcinoma, characterized by comprising the following (1) and (2), wherein either one of (1) and (2) is immobilized on a support and the other is labeled.

[0032] (1) Lectins that recognize sugar chains in glycoproteins derived from renal tissue that have sialylated sugar chains whose expression is increased due to cancerous development,

[0033] (2) An antibody that binds to at least one glycoprotein selected from GPNMB, Megalin, ACE2, and MME.

[0034] According to the present invention, a biomarker capable of specifically detecting renal cell carcinoma can be provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 Schematic diagram of the process for comprehensively analyzing sugar chain modifications by using laser microdissection to collect cancer-specific regions of renal cell carcinoma and applying the extracted glycoproteins to a lectin microarray. This method allows analysis of sugar chain modifications in specific regions of renal cell carcinoma, compared to analysis of bulk specimens. Lectin microarrays enable highly sensitive comparative analysis of sugar chains, so this method can also be applied to samples enriched by immunoprecipitation using specific antibodies (antibody overlay-lectin microarray method, Antibody overlay·Lectin Microarray), which are antibodies specific for candidate molecules (core proteins) extracted by mass spectrometry. In this case, the amount of protein used is around a few nanograms to tens of nanograms, and statistical analysis of the obtained signal values ​​(Student's t test) can be performed to select lectins that show significant differences. This allows the simultaneous listing of antibodies and lectins that recognize specific glycoproteins.

[0036] Figure 2 The results of sugar chain analysis using laser microdissection-lectin microarray analysis of formalin-fixed paraffin-embedded (FFPE) thin sections are presented. A comparison of sugar chain modifications in the cancerous sites of ACD-RCC and cc-RCC, the two most common histotypes of renal cell carcinoma in dialysis patients, revealed that ACD-RCC showed significantly more numerous sugar chain modifications, including sialic acid.

[0037] Figure 3 Proteins extracted from frozen tissue specimens of ACD-RCC and cc-RCC cancerous sites were subjected to reductive alkylation and trypsin digestion for peptide fragmentation. Glycopeptides were then enriched using an amide column. The samples were analyzed using IGOT-LC / MS to analyze the locations of glycan attachment, and proteins with N-linked glycans were identified.

[0038] The IGOT-LC / MS method is a method that involves enzymatically removing the sugar chains from glycopeptides bound to N-type sugar chains and then analyzing the peptide portion using LC / MS for identification. 18 O) using peptide-N-glycosidase, the asparagine residues at the glycosylation position are converted to aspartic acid residues, at which point the oxygen-18 ( 18O) will be incorporated into the peptide, so the glycosylation site is labeled with a stable isotope. This method is called the IGOT method (Isotope-coded Glycosylation Site-specific Tagging). Because multiple sugar chains with different structures are unevenly bound to the same site on the same protein, glycopeptides with a single structure are less abundant than non-sugar-modified peptides. This is one of the reasons why glycopeptides are difficult to identify. The IGOT-LC / MS method is a method that can identify glycosylation sites with high sensitivity by cutting off the sugar chains of the glycopeptide sample, instead of losing information related to its diversity, in exchange for improving the sensitivity of glycopeptide detection.

[0039] Figure 4A Proteins extracted from frozen tissue specimens of cancerous sites of ACD-RCC and cc-RCC were reductively alkylated and digested with trypsin to generate peptide fragments, and then glycopeptides were enriched by passing through an amide column. The samples were analyzed by LC / MS, and the resulting MS / MS spectra were analyzed using the glycopeptide identification software Byonic. Candidate molecules (proteins) that are sialylated (sialic acid modified) only in ACD-RCC were recorded. Byonic identified the MS / MS spectra based on the further fragmentation of data-dependent selected glycopeptide ions in the mass spectrometry device using a protein amino acid sequence database and a sugar chain component database. Fragmentation can be performed using high-energy collision-induced dissociation (HCD) and electron transfer dissociation (ETD).

[0040] Figure 4BProteins extracted from frozen tissue specimens of cancerous sites of ACD-RCC and cc-RCC were reductively alkylated and digested with trypsin to generate peptide fragments, and then glycopeptides were enriched using an amide column. The samples were analyzed by LC / MS, and the resulting MS spectra were analyzed using the Glycan heterogeneity-based Relational Identification of Glycopeptidesignals on the Elution profile (Glyco-RIDGE method). Candidate molecules (proteins) that are sialylated (sialic acid modified) only in ACD-RCC were recorded. A group of glycopeptides with the same core peptide but different sugar chain compositions eluted at similar retention times during LC separation. The Glyco-RIDGE method is a method for detecting glycopeptide ions based on the mass difference caused by this elution characteristic and sugar chain heterogeneity. The sugar chain composition can be predicted based on the precise difference between the mass of the detected glycopeptide and the mass of the previously obtained core peptide. The core peptide information required for this analysis (LC elution time, mass, signal intensity, peptide sequence, and glycosylation sites) can be obtained using the IGOT-LC / MS method. Glycopeptides have weaker signal intensities than typical peptides, making it often impossible to obtain MS / MS spectra using data-dependent methods, or even to obtain MS / MS spectra sufficient for analysis. The Glyco-RIDGE method, which predicts glycopeptides based on a core peptide list and MS1 spectrum information, allows for highly sensitive identification of glycopeptides compared to conventional MS / MS-dependent analysis methods.

[0041] Figure 5A The results of immunohistochemical staining for GPNMB, Megalin, ACE2, and MME were obtained from surgical specimens of patients undergoing dialysis for renal cancer. (i) ACD-RCC and (ii) cc-RCC (two cases each) are shown. In cases where GPNMB was strongly positive, there was a tendency for other molecules to be weakly positive, while in cases where GPNMB was weakly positive or negative, there was a tendency for other molecules to be strongly positive.

[0042] Figure 5B Results of multiple fluorescence staining for MME, MAH, and SNA were obtained using surgical specimens from ACD-RCC and cc-RCC renal tissue samples from patients undergoing dialysis for renal cancer. Arrows indicate sites where MME and SNA (a lectin that recognizes α-2,6-sialic acid) merge. These changes are observed in cysts and renal cell carcinoma tissue (more pronounced in ACD-RCC than in cc-RCC), but not in normal renal tissue.

[0043] Figure 6These are the results of Western blotting of GPNMB, Megalin, and MME using ACD-RCC samples.

[0044] Figure 7 These are the results of t-tests performed after comparative sugar chain analysis of GPNMB and megalin using antibody-coated lectin microarrays. Each value is expressed as a P value, with values ​​of P < 0.05 considered significantly different and marked in gray. "#DIV / 0!" indicates that no signal was generated in either protein, making the analysis impossible.

[0045] Figure 8 These are the results of Western immunoblotting of GPNMB using serum samples.

[0046] Figure 9 The results (NET intensity) of immunoprecipitation-lectin array analysis of GPNMB using serum samples are shown. Results that were significantly different at P < 0.05 in a paired t-test are circled with bold frames.

[0047] Figure 10 The results of immunoprecipitation-lectin array analysis of GPNMB using serum samples (MeanNormalize) are shown. Cases judged to be significantly different at P < 0.05 in a paired t-test are circled with bold frames. DETAILED DESCRIPTION

[0048] Hereinafter, one embodiment of the present invention will be described in detail. The present invention is not limited to the following embodiments and can be implemented by applying appropriate changes within the scope that does not hinder the effects of the present invention. When a specific description recorded for one embodiment is also applicable to other embodiments, its description may be omitted in other embodiments. In this specification, "X to Y" indicating a numerical range means "above X and below Y".

[0049] The present inventors, based on the technology of collecting cancer-specific areas from pathological tissue specimens under a microscope, multi-omics analysis such as lectin arrays, found that ACD-RCC was more sialylated (sialic acid modified) than cc-RCC. Based on this, by glycosylation proteomics including mass spectrometry analysis, a glycoprotein group with a sugar chain structure containing sialic acid modification was identified from the protein group of renal cell carcinoma cancer tissue, which will be used as a new renal cell carcinoma-specific biomarker (glycopeptide and glycoprotein). As an existing technology for effectively utilizing sugar chain analysis in the diagnosis of renal cell carcinoma, a cancer grading technology corresponding to the amount of glycoprotein on the cell surface (Japanese Patent Publication No. 2019-106214) and a technology for detection using glycoprotein SIMA 135 (Japanese Patent Publication No. 2013-128709) can be listed, but none of them are directly related to the present invention.

[0050] [Biomarkers]

[0051] A biomarker according to one embodiment of the present invention comprises a glycoprotein derived from kidney tissue having sialylated sugar chains whose expression is enhanced due to cancerous transformation, and can be used to detect renal cell carcinoma.

[0052] Renal cell carcinoma

[0053] In an embodiment, renal cell carcinoma includes not only renal cell carcinoma, but also cystic epithelium, which is considered to be a precancerous lesion. Renal cell carcinoma includes acquired cystic kidney disease-associated renal cell carcinoma, clear cell renal cell carcinoma, clear cell papillary renal cell carcinoma, papillary renal cell carcinoma, chromophobe cell renal cell carcinoma, etc. The biomarker of this embodiment has an excellent effect on the detection of renal cancer arising in the dialysis kidney (dialysis renal cancer), especially the detection of acquired cystic kidney disease-associated renal cell carcinoma (ACD-RCC). ACD-RCC has the highest incidence rate (36%) among renal cancers in dialysis kidneys. In addition, reports also show that the incidence rate of ACD-RCC increases with the increase in the number of years of dialysis. ACD-RCC, which occurs frequently in dialysis renal cancer, is difficult to diagnose by imaging. Therefore, in the case where renal cell carcinoma is dialysis renal cancer, or in the case where renal cell carcinoma is ACD-RCC, the usefulness of the biomarker of this embodiment is higher. Therefore, this embodiment is ideal for dialysis renal cancer among renal cell carcinomas, and is even more ideal for ACD-RCC.

[0054] On the other hand, normal renal tissue refers to renal tissue that does not contain lesions. In one embodiment, normal renal tissue refers to renal tissue that does not contain lesions caused by renal cell carcinoma (including cystic epithelium that is considered to be a precancerous lesion).

[0055] The nephron is the unit responsible for filtering and reabsorbing plasma in the kidneys. There are approximately 2 million nephrons in each kidney. The nephron is composed of the renal corpuscle (glomerulus and Bowman's capsule), responsible for filtration, and the renal tubule, responsible for reabsorption. The walls of the glomerular capillary loops are composed of the glomerular basement membrane (GBM), podocytes covering the outer side of the GBM (the urinary cavity side), and glomerular endothelial cells covering the inner side of the basement membrane. Mesangial cells support the capillary loops. Afferent and efferent arterioles enter and exit the vascular pole, where epithelial cells and podocytes on the wall side of Bowman's capsule interact with each other. The vascular pole contains the paraglomerular apparatus, which is composed of distal tubular epithelial cells forming the macula densa, extraglomerular mesangial cells, and smooth muscle cells of the afferent and paraglomerular arterioles and efferent arterioles. The blood that comes out from the superficial glomerulus of the cortex enters the pararenal tubule capillaries that follow the movement of the cortical renal tubules, and the blood that comes out from the deep glomerulus of the cortex enters the straight vasa toward the deep part of the medulla. The arcuate arteries and veins, interlobar arteries and veins, and renal arteries and veins are responsible for the inflow and reflux of blood. Bowman's capsule is composed of the proximal convoluted tubule, Henle's loop (proximal straight tubule, thin descending limb, thin ascending limb, distal straight tubule), distal convoluted tubule, connecting tubule, cortical collecting duct, and medullary collecting duct from the renal tubule pole that transfers to the renal tubule. Nephrocyte refers to the cell that constitutes the kidney, including the cells (including collecting duct cells) that constitute the above-mentioned renal tubules, each cell of the glomerulus, the wall epithelial cells of Bowman's capsule, the fibroblasts or dendritic cells present in the interstitium, the inflammatory cells that infiltrate, the vascular cells of blood vessels or lymphatic vessels, the nerve cells etc. The renal tubular cells (or tubular epithelial cells) include cells that form the lumen of the proximal tubule to the loop of Henle, the distal tubule, the collecting duct, and the renal papilla.

[0056] The glycoprotein derived from kidney tissue refers to a protein found in kidney tissue and having sugar chains, and the glycoprotein derived from renal tubular epithelial cells refers to a protein found in renal tubular epithelial cells and having sugar chains.

[0057] In renal tubular epithelial cells, the origin of renal cell carcinoma, sialic acid modification of the sugar chains of these glycoproteins is suppressed. On the other hand, glycoproteins with sialic acid-modified sugar chains have been observed in renal tubular epithelial cells that have become cancerous or cystic. Furthermore, based on results from tissue staining, it is possible that glycoproteins with sialic acid-modified sugar chains are also confined to the proximal renal tubules, where sialylation is suppressed. Therefore, glycoproteins derived from renal tissue with sialylated sugar chains can be used as biomarkers for the specific diagnosis of renal cell carcinoma. Furthermore, by investigating changes in the sugar chain structure of glycoproteins derived from renal tissue, renal cell carcinoma markers can be identified.

[0058] In renal cells, for example, as a sugar chain structure that is suppressed in the proximal renal tubule, a sugar chain structure modified with sialic acid (sialylation) can be listed. Sialylation (sialic acid modification) means that in an N-linked sugar chain, sialic acid is bonded to the 6th or 3rd position of the non-reducing terminal galactose, and in an O-linked sugar chain, sialic acid is bonded to the 6th position of N-acetylgalactosamine, the 3rd position of the non-reducing galactose terminal of Core1 (T), or the 3rd or 6th position of the non-reducing terminal galactose on the extended chain side of Core2. Sialic acid is a derivative of neuraminic acid composed of 9 carbons and having an amino group and a carboxyl group. Representative substances include N-acetylneuraminic acid (Neu5Ac), N-glycolylneuraminic acid (Neu5Gc), and deaminoneuraminic acid (Kdn). Generally speaking, sialic acid is present at the ends (non-reducing ends) of sugar chains such as N-linked sugar chains, O-linked sugar chains, and glycolipids, and participates in various biological reactions.

[0059] Examples of renal tissue-derived glycoproteins having sialylated sugar chains whose expression is enhanced by cancer include ITGA3 (Integrin alpha-3), TINAGL1 (Tubulointerstitial nephritis antigen-like protein), PSAP (Prosaposin), TMED9 (Transmembrane emp24 domain-containing protein 9), MPO (Myeloperoxidase), LRP2 (Low-density lipoprotein receptor-related protein 2, MEGALIN), GPNMB (Transmembrane glycoprotein Nonmetastatic Melanoma Protein B), PLD3 (5'-3' exonuclease), and glycoprotein kinase B (Glycine max). PLD3), APMAP (Adipocyte plasma membrane glycoprotein 2), LAMP2 (Lysosome-associated membrane glycoprotein 2), INSR (Insulin receptor), DPP4 (Dipeptidyl peptidase 4), SORT1 (Sortilin), ACE (Angiotensin-converting enzyme), ACE2 (Angiotensin-converting enzyme 2), DPEP1 (Dipeptidase 1), LGALS3BP (Galectin-3-binding protein), GGTLC2 (Glutathione hydrolase light chain 2), CD63 (CD63 antigen, CD63 antigen), MGAM (maltase-glucoamylase,intestinal), PIGR (Polymeric immunoglobulin receptor), YBX1 (Y-box-binding protein 1), HRG (Histidine-rich glycoprotein), PKD1 (Polycystin-1), FCGRT (IgG receptor FcRn large subunit p51), CPD (Carboxypeptidase D), IL1R1 (Interleukin-1 receptor type 1), BTN3A1 (Butyrophilin subfamily 3 member A1), FBN1 (Fibrillin-1), HLA-A (HLA class I histocompatibility antigen, A-2 alpha chain), chian), CUBN (intrinsic factor-cobalamin receptor, Cubilin), ENPEP (Glutamyl aminopeptidase, Glutamyl aminopeptidase), LAMP1 (Lisosome-associated membrane glycoprotein 1), ANPEP (Aminopeptidase N, Aminopeptidase N), MME (Neprilysin, CD10), HLA-DPB1 (HLA class II histocompatibility antigen DPβ1 chain, HLA class II histocompatibility antigen,These glycoproteins include DP beta 1 chain, GLB1L (beta-galactosidase-1-like protein), FGB (fibrinogen beta chain), MMRN1 (multimerin-1), APOB (apolipoprotein B-100), HSPG2 (basement membrane-specific heparan sulfate proteoglycan 2), IGHM (immunoglobulin heavy chain constant region μ), and THBS1 (thrombospondin-1). These glycoproteins are found even in normal tissues, including renal tubular epithelium, but due to differences in their sugar chain modifications, they can be used as biomarkers for the detection of renal cell carcinoma. One or more combinations of these glycoproteins can be selected from this group as biomarkers for the detection of renal cell carcinoma. One embodiment of the present invention provides a combination of two or more glycoproteins selected from these cell surface glycoprotein groups. These combinations can be used to detect renal cell carcinoma.

[0060] In one embodiment, the renal tissue-derived glycoprotein having sialylated sugar chains whose expression is enhanced due to cancerous transformation is one or more proteins selected from the group consisting of GPNMB, Megalin, ACE2, and MME.

[0061] GPNMB is a transmembrane glycoprotein involved in various cellular processes, including cell adhesion, migration, and immune response control. This suggests that it may be involved in slowing cell proliferation and regulating metastatic capacity in tumor tissues.

[0062] Megalin, also known as low-density lipoprotein receptor-related protein 2 (LRP-2), is a large transmembrane receptor protein involved in various intracellular processes, including endocytosis, protein transport, and signal transduction. Megalin is particularly well-known for its role in the renal tubules, where it contributes to the reabsorption of proteins from the glomerular filtrate. This process is crucial for maintaining protein balance in the blood and preventing the loss of valuable proteins through urine. Megalin is also present in other tissues and organs, such as the nervous system, lungs, and intestines, where it participates in various physiological functions.

[0063] ACE2 is a membrane protein that plays an important role in the levothyroxine-angiotensin-aldosterone system (RAAS), a hormone system that regulates blood pressure and fluid balance. ACE2 has the catalytic function of cleaving angiotensin I into angiotensin 1-9 and angiotensin II into angiotensin 1-7, which has a vasodilatory effect. ACE2 is well known for being found in various human organs. Based on its organ-specific and cell-specific expression, it has been shown to be related to the regulation of the cardiovascular system, renal function, and reproductive function. Furthermore, it is a functional receptor for the spike glycoprotein of human coronavirus HCoV-NL63 and human severe acute respiratory syndrome coronavirus SARS-CoV and SARS-CoV-2, the latter being the pathogen of coronavirus disease-2019 (COVID-19).

[0064] MME functions as a neutral endopeptidase in type II transmembrane glycoproteins. It cleaves peptide chains at the amino side of hydrophobic residues, inactivating several peptide hormones, including glucagon, enkephalin, substance P, neurotensin, oxytocin, and bradykinin. A common acute lymphoblastic leukemia antigen, a key cell surface marker in the diagnosis of human acute lymphoblastic leukemia (ALL), is present in leukemic precursor B cells, which account for 85% of ALL cases.

[0065] One or a combination of two or more selected from these cell surface glycoproteins can be used as a biomarker for detecting renal cell carcinoma. In addition, one embodiment of the present invention provides a combination of two or more glycoproteins selected from the group consisting of GPNMB, Megalin, ACE2, and MME, which have sialylated sugar chain structures that are overexpressed due to canceration. These combinations can be used to detect renal cell carcinoma. Specific combinations include GPNMB and Megalin, GPNMB and ACE2, GPNMB and MME, Megalin and ACE2, Megalin and MME, ACE2 and MME, GPNMB and Megalin and ACE2, GPNMB and Megalin and MME, GPNMB and ACE2 and MME, Megalin and ACE2 and MME, GPNMB and Megalin and ACE2 and MME, etc. By detecting two or more combinations selected from these cell surface glycoprotein groups, the accuracy of diagnosis can be further improved.

[0066] In one embodiment, the biomarker can be used as a serum or tissue diagnostic marker for detecting renal cell carcinoma or its precursor lesion, cystic lesions. Furthermore, the biomarker can be used in either a single or multiplexed detection system, with a cutoff value set according to the intended use.

[0067] The biomarker of this embodiment not only detects tissues, but also more simply exerts the excellent effect of being able to detect renal cell carcinoma with higher specificity by detecting blood such as serum. Furthermore, the biomarker of this embodiment can determine the different tissue types of renal cell carcinoma regardless of dialysis cases or non-dialysis cases by performing comparative analysis of sugar chains. In addition, it can also determine the pathological state of ACKD (cystic lesions) that is considered to be a precancerous lesion in dialysis cases. In addition, compared with existing renal cell carcinoma markers, the biomarker of this embodiment has a high diagnosis rate because it uses both protein sites and sugar chain modification sites as measurement objects, and can evaluate the treatment effect and recurrence of renal cell carcinoma through monitoring technology that can be used to examine trace amounts of serum.

[0068] The biomarker of this embodiment can be the presence or absence of the aforementioned renal tissue-derived glycoproteins with sialylated sugar chains whose expression is increased due to canceration, or can also be their quantitative level. Specifically, in this embodiment, the presence or quantitative level of renal cell glycoproteins with sugar chain structures not found in normal renal tissue can be used to detect renal cell carcinoma. The quantitative level can be an absolute value of the amount of glycoproteins with sialylated sugar chains whose expression is increased due to canceration, or a relative value relative to any comparison object.

[0069] [Detection method]

[0070] A biomarker detection method according to one embodiment of the present invention comprises detecting a biomarker in vitro in a sample obtained from a subject (test sample), the biomarker comprising a glycoprotein derived from renal tissue having sialylated sugar chains whose expression is enhanced by canceration.

[0071] As long as any of the above-mentioned "biomarkers" listed above, which contain sialylated sugar chains that are expressed more frequently due to canceration, can be detected, the assay can be performed using methods known to those skilled in the art. For example, lectin array analysis, ELISA analysis, and immunohistochemical staining can be used. The sandwich assay described below is particularly preferred.

[0072] In the sandwich method, it is desirable to use a substance that specifically binds to the protein portion of the glycoprotein together with the lectin, and it is desirable to use an antibody as the substance that binds to such a protein portion.

[0073] A specific method is to immobilize an antibody that binds to a glycoprotein of renal tubular epithelial cells on a support. Next, the test sample is covered to form a complex between the target protein and the antibody. Furthermore, a labeled antibody or lectin is added to form a further complex. By detecting the formed complex, the target protein can be detected. As another method, instead of immobilizing the antibody on a support, multiple lectins containing lectins can be immobilized on a support and the labeled antibody can be allowed to act on the covered test sample for detection. These tests can be performed on more than two biomarkers.

[0074] When immunohistochemical staining is used, two or more biomarkers can be detected simultaneously. Specifically, tissue sections are prepared and multiplexed using specific antibodies against each biomarker labeled with a different pigment, or using specific antibodies against each biomarker and labeled binary antibodies against each specific antibody. This allows for simultaneous staining and detection of each biomarker.

[0075] Detection of biomarkers may include measuring the presence or level of the above-mentioned renal tissue-derived glycoprotein having a sialylated sugar chain structure whose expression is increased due to canceration.

[0076] In this embodiment, the "subject" refers to a person for examination, that is, a person who provides a sample to be examined. The subject may be a mammal or an animal other than a mammal. The mammal may be a human or a non-human animal. The non-human animal species may be, for example, monkeys, dogs, cats, horses, cows, pigs, sheep, goats, rabbits, guinea pigs, hamsters, mice, and / or rats, and are not limited to livestock, pets, or experimental animals. Mammals are ideal, and humans are even more ideal. In addition, the subject may be a patient with a certain disease or a healthy person. Ideally, the subject may be a person who may have renal cell carcinoma or a patient with renal cell carcinoma. The subject may also be a person who may have or has a disease other than renal cell carcinoma.

[0077] The biomarker detected by the detection method of this embodiment is excellently effective in detecting renal cancer occurring in the dialysis kidney (dialysis renal cancer), particularly in detecting acquired cystic kidney disease-associated renal cell carcinoma (ACD-RCC).

[0078] While ACD-RCC has been reported to occur more frequently (36%) in patients on dialysis and to increase with the number of years on dialysis, imaging diagnosis is difficult. Therefore, the detection method of this embodiment is particularly useful in patients on dialysis, making it ideal for patients on dialysis to be examined.

[0079] It is well known that the likelihood of dialysis patients developing ACD-RCC increases as the dialysis period becomes longer. Therefore, the detection method of this embodiment can be performed regularly on dialysis patients to detect ACD-RCC.

[0080] Here, the test sample may include a partial tissue fragment of renal tissue collected from a subject during biopsy or surgery, a tissue fragment derived from a renal lesion, or body fluids such as ascites or cells collected from urine. The test subject is not particularly limited, and the determination of renal cell carcinoma can be applied to a wide range of individuals in need.

[0081] In addition, the subject's body fluids such as blood, lymph, medullary fluid, bile, urine, saliva, and body cavity fluid can be used, and the serum separated from the blood collected from the subject can be used as the test sample. This is less burdensome for the subject and can also shorten the test time, which is more ideal.

[0082] The test fluid can be used immediately after collection, or it can be frozen or refrigerated for a certain period of time and then thawed as needed. In this embodiment, when serum is used, a sufficient amount of biomarkers can be detected by using a volume of 10 μL to 100 μL, 20 μL to 80 μL, 30 μL to 70 μL, 40 μL to 60 μL, or 45 μL to 55 μL.

[0083] [Renal Cell Carcinoma Diagnostic Kit]

[0084] In one embodiment of the present invention, a renal cell carcinoma diagnostic kit comprises a unit for detecting a biomarker comprising a glycoprotein derived from renal tissue having sialylated sugar chains whose expression is enhanced due to canceration. Examples of the detection unit include a lectin that binds to a glycoprotein derived from renal tissue having sialylated sugar chains whose expression is enhanced due to canceration, and / or an antibody that binds to a renal cell glycoprotein having sialylated sugar chains whose expression is enhanced due to canceration.

[0085] (1) Lectins that recognize biomarkers

[0086] The lectin used in the renal cell carcinoma diagnostic kit is not particularly limited as long as it is a lectin that recognizes the biomarker of the present embodiment. Examples thereof include LTL (Lotus tetragonolobus lectin), PSA (Pisum sativum agglutinin), LCA (Lens culinaris agglutinin), UEA-I (Ulex europaeus agglutinin-I), AOL (Aspergillus oryzae lectin), AAL (Aleuria aurantia lectin), MAL-I (biotinylated Maackia amurensis lectin), SNA (Sambucus nigra agglutinin), and SSA (Sambucus sieboldiana agglutinin). agglutinin), TJA-I (Trichosanthes japonica agglutinin-I), PHA-L (Phaseolus vulgaris leukoagglutinin),

[0087] ECA (Erythrina cristagalli agglutinin), RCA120 (Ricinus communis agglutinin), PHA-E (Phaseolus vulgaris rythroagglutinin), DSA (Datura stramonium agglutinin), GSL-II (Griffonia simplicifolia lectin-II), NPA (Narcissus pseudonarcissus agglutinin), ConA (Concanavarin A), GNA (Galanthus nivalis agglutinin), HHL (Hippeastrum hybrid lectin), ACG (Galactoses, Agrocybe agglutinin). cylindracea galectin), TxLC-I (Tulipa gesneriana agglutinin), BPL (Bauhinia purpurea alba lectin), TJA-II (Trichosanthes japonica agglutinin-II), EEL (Euonymus europaeus lectin), ABA (Agaricus bisporus agglutinin), LEL (Lycopersicon esculentum lectin), STL (Solanum tuberosum lectin), UDA (Urtica dioica agglutinin), PWM (Pokweed mitogen), PNA (Jacalin, Peanut agglutinin), agglutinin), WFA (Wisteria floribunda agglutinin), ACA (Amaranthus caudatus agglutinin), MPA (Maclura pomifera agglutinin), HPA (Helix pomatia agglutinin),Agglutinin), VVA (Vicia villosa agglutinin), DBA (Dolichos biflorus agglutinin), SBA (Soybean agglutinin), Calsepa, PTL-I (Psophocarpus tetragonolobus lectin-I), MAH (Maackia amurensis hemagglutinin), WGA (Wheat germ agglutinin), GSL-I A4 (Griffonia simplicifolia lectin-I A4), and GSL-I B4 (Griffonia simplicifolia lectin-I B4). MAL-I, SNA, SSA, TJA-I, MAH, and WGA are particularly preferably used.

[0088] Information on other lectins can be obtained from the Lectin Frontier Database (LfDB) and the like.

[0089] The lectin used in this embodiment may be of natural origin or a recombinant lectin produced by recombinant technology from a prokaryotic or eukaryotic host (e.g., bacterial cells, yeast cells, higher plant cells, insect cells, and mammalian cells). Furthermore, the lectin may be a fragment as long as its binding properties are maintained.

[0090] (2) Antibodies that bind to renal cell glycoproteins with sialylated sugar chains whose expression is increased due to cancer

[0091] As the antibody contained in the renal cell carcinoma diagnostic kit, as long as it is an antibody that binds to the protein region of the renal cell glycoprotein having sialylated sugar chains that are expressed hyperactively due to canceration, or to the region containing sugar chains, there is no particular limitation. The antibody can be a polyclonal antibody, but a monoclonal antibody is more ideal. As long as its antigen binding activity is not impaired, it can also be an antibody fragment such as Fab. For example, anti-GPNMB antibodies, anti-Megalin antibodies, anti-ACE2 antibodies, anti-MME antibodies, or combinations thereof can be used.

[0092] In the detection of biomarkers, it is ideal to use both an antibody that specifically binds to the protein portion of a glycoprotein and a lectin. In one embodiment, a renal cell carcinoma diagnostic kit comprises the following (1) and (2), wherein either (1) or (2) is immobilized on a support and the other is labeled.

[0093] (1) Lectins that recognize glycoproteins derived from renal tissue that have sialylated sugar chains whose expression is increased due to cancerous transformation,

[0094] (2) An antibody that binds to at least one glycoprotein selected from GPNMB, Megalin, ACE2, and MME.

[0095] Antibodies specific for renal tissue-derived glycoproteins with sialylated sugar chains whose expression is increased due to cancerous transformation can be prepared using conventional methods using the glycoprotein as a biomarker antigen. Furthermore, specific antibodies that recognize both the sugar chain and protein portions of the glycoprotein can be prepared using the CasMab method (Cas Mab: Kato Y et al., Sci Rep. 2014 Aug 1;4:5924. doi:10.1038 / srep05924). While such antibodies are highly effective for detecting renal cell carcinoma markers and diagnosing renal cell carcinoma on their own, their accuracy can be further improved by combining them with antibodies that specifically bind to either the sugar chain or protein portion.

[0096] [Diagnostic Method]

[0097] A diagnostic method according to one embodiment of the present invention is a method for diagnosing renal cell carcinoma, comprising detecting a biomarker in a subject, wherein the biomarker comprises a glycoprotein derived from renal tissue having sialylated sugar chains whose expression is increased due to cancerous transformation. In one embodiment, the diagnostic method may include a step of determining the likelihood that the subject has renal cell carcinoma based on the detected biomarker.

[0098] One embodiment of the present invention is a data collection method for diagnosing renal cell carcinoma, comprising detecting a biomarker in a subject, wherein the biomarker comprises a glycoprotein derived from renal tissue having sialylated sugar chains whose expression is increased due to cancerous transformation. Based on the data collected by this data collection method, renal cell carcinoma in the subject can be diagnosed. That is, one embodiment of the method for diagnosing renal cell carcinoma in a subject includes this data collection method.

[0099] The biomarker detection method can be the method described in the above-mentioned detection method. By detecting a biomarker containing a glycoprotein derived from renal tissue having sialylated sugar chains whose expression is increased due to cancerous transformation, renal cell carcinoma can be diagnosed with higher accuracy than before.

[0100] In one embodiment, a diagnostic method or data collection method for renal cell carcinoma in a subject may be a method comprising the following steps: before implementing any detection method recorded in the above-mentioned "detection method" in the subject, implementing a biomarker detection method according to the above-mentioned "detection method" in one or more renal cell carcinoma patients, and obtaining a baseline value of the biomarker based on the level of the biomarker in the renal cell carcinoma patient.

[0101] In another embodiment, the diagnostic method or data collection method for renal cell carcinoma in a subject may be a method comprising the following steps: before implementing any detection method recorded in the above-mentioned “detection method” of this embodiment in the subject, a biomarker detection method is implemented in accordance with the above-mentioned “detection method” of this embodiment in one or more renal cell carcinoma patients and one or more healthy persons, to obtain the baseline value of the biomarker in the renal cell carcinoma patient and the baseline value (normal value) of the biomarker in the healthy person.

[0102] According to these methods, when the biomarker values ​​of the subject are the same as the baseline values ​​of the biomarkers of patients with renal cell carcinoma, it can be determined based on the data that the subject has renal cell carcinoma, or that the likelihood of having renal cell carcinoma is high. Alternatively, when the biomarker values ​​of the subject are different from the baseline values ​​of the biomarkers of patients with renal cell carcinoma, it can be determined based on the data that the subject does not have renal cell carcinoma, or that the likelihood of having renal cell carcinoma is low.

[0103] Furthermore, if the biomarker values ​​of the subject differ from normal values, the subject can be determined to have renal cell carcinoma or to have a high probability of having renal cell carcinoma based on the data. Alternatively, if the biomarker values ​​of the subject are the same as normal values, the subject can be determined to not have renal cell carcinoma or to have a low probability of having renal cell carcinoma based on the data.

[0104] In one embodiment, when a biomarker level in a subject is elevated compared to a normal value, the subject can be determined to have renal cell carcinoma based on the data, or can be determined to have a high probability of having renal cell carcinoma.

[0105] In another embodiment, a method for diagnosing or collecting data on renal cell carcinoma in a subject may include performing any of the detection methods described in the above "Detection Method" of this embodiment on the same subject.

[0106] According to this method, if a subject's biomarkers change at a certain point in time compared to a previous time point, the subject can be determined to have renal cell carcinoma, or to have a high probability of having renal cell carcinoma, based on this data. For example, this method can be used to monitor the subject's renal cell carcinoma through regular monitoring.

[0107] In one embodiment, if a subject's biomarker level increases at a certain point in time compared to a previous time point, the subject can be determined to have renal cell carcinoma, or to have a high probability of having renal cell carcinoma, based on this data. This is because biomarker expression in samples obtained from renal cell carcinoma patients tends to be higher than that in samples obtained from healthy individuals.

[0108] Here, the reference value or normal value may be the average value or median value of the biomarker measured over time in subjects of the same group or the same subject, or may be a reference range or normal range arbitrarily set based on the measured value of the biomarker.

[0109] In addition, regarding the reference value or normal value, practitioners in this field can appropriately determine a value that can determine whether a subject has renal cell carcinoma with desired sensitivity and / or specificity based on biomarkers measured over time in subjects in the same group or in the same subject.

[0110] Furthermore, the phrase "a biomarker in a subject is the same as a baseline value or a normal value" means, for example, that there is no significant difference from the baseline value or the normal value after any statistical processing. The phrase "a biomarker in a subject is different from a baseline value or the normal value" means, for example, that there is a significant difference from the baseline value or the normal value after any statistical processing. The phrase "a biomarker in a subject is elevated compared to a baseline value" means, for example, that the level of the biomarker in a sample obtained from the subject is significantly elevated compared to the baseline value after any statistical processing.

[0111] Statistical processing methods can reasonably be selected from methods that are well known to practitioners in this industry.

[0112] In one embodiment, the diagnostic method or data collection method described above can be combined with other data collection methods for diagnosing renal cell carcinoma or other diagnostic methods for renal cell carcinoma. Examples of other diagnostic methods include dynamic CT, MRI, and abdominal echocardiography.

[0113] [Pharmaceutical ingredients]

[0114] One embodiment of the present invention is a pharmaceutical composition for treating renal cell carcinoma, comprising an antibody or protein as an active ingredient and optionally a pharmaceutically acceptable carrier and / or excipient. Specific active ingredients include antibodies that specifically bind to a biomarker containing a glycoprotein derived from renal tissue that has sialylated sugar chains whose expression is increased due to cancerous transformation, conjugates of such antibodies with pharmaceutical agents, and small to medium-molecule chemical substances derived from natural or synthetic sources.

[0115] The above active ingredients can be incorporated into known carriers capable of kidney-specific delivery. Alternatively, liposome delivery using pH-sensitive liposomes capable of endoplasmic reticulum-specific delivery is also desirable.

[0116] In addition, the following mainly describes the formulation of antibodies, proteins, etc., as well as specific administration methods, dosages, etc.

[0117] The route of administration can be oral or parenteral. In the case of parenteral administration, subcutaneous or intravenous injection is ideal. Nasal administration such as nasal sprays, transdermal administration, inhalation administration, suppositories, etc. are also possible. Antibodies or proteins can be administered to patients via intravenous injection, subcutaneous injection, oral delivery, liposome delivery, or intranasal administration, and can then accumulate throughout the patient's body, kidneys, or renal cells.

[0118] “Pharmaceutically acceptable carriers and / or excipients” are known to practitioners in this industry and include any type of encapsulating materials or formulation excipients such as non-toxic solid, semi-solid or liquid fillers, diluents, liposomes, etc.

[0119] One embodiment of the present invention relates to a method for treating renal cell carcinoma, comprising administering the above-mentioned pharmaceutical composition.

[0120] Another embodiment of the present invention relates to the use of an antibody that binds to a biomarker comprising a glycoprotein of renal tubular epithelial cells having sialylated sugar chains whose expression is enhanced by cancerous transformation, in the production of a therapeutic drug for renal cell carcinoma.

[0121] 1. Acquisition of new biomarkers

[0122] 1-1. Biomarkers for the diagnosis of renal cell carcinoma

[0123] The composition and structural diversity of sugar chains on proteins secreted by cells are controlled based on the expression balance of hundreds of sugar chain-related genes and vary according to the differentiation of cells and the degree of progression of cancer. Glycoproteins whose sugar chain structures have changed can be used as tumor markers. Therefore, an exploration of sugar chain-related tumor markers based on glycoproteomics was carried out. The marker exploration process based on proteomics is divided into three stages. In stage 1, candidate molecules are identified through large-scale analysis. In stage 2, candidate molecules are verified / screened by quantitative analysis. In addition, in stage 3, verification tests are performed. The exploration of sugar chain-related markers based on glycoproteomics is also based on the above process.

[0124] Glycopeptides specifically identified using the lectin capture IGOT method in samples or cancer cell lines from renal cell carcinoma patients and healthy human samples can be used as candidate renal cell carcinoma markers. These glycopeptides are then validated (verified) using comparative glycan analysis techniques, including comparative glycan proteomics of stable isotope-introduced glycopeptides, to identify those that demonstrate strong utility as marker glycopeptides.

[0125] Furthermore, by performing verification (certification) on glycoproteins containing candidate glycopeptide sequences using comparative sugar chain analysis techniques including antibody overlay-lectin microarray methods, substances that demonstrate usefulness can be identified as specific biomarkers.

[0126] 1-2. Methods for obtaining biomarkers

[0127] 1-2-1. Large-scale identification of glycoproteins

[0128] Large-scale selective capture and concentration of glycopeptides can be broadly categorized into various methods, including (i) using probes with affinity for sugar chains, (ii) utilizing chemical reactions with sugar chains (Zhang H. et al. Nat Biotechnol 21, 660-666 (2003)), and (iii) introducing tags with affinity for sugar chains. Using probes is ideal. The following describes methods using probes in detail.

[0129] (1) Probe-based capture: Lectins and anti-sugar chain antibodies can be used as probes. Specifically, glycoproteins are first captured from the upper layer of a culture medium of a renal cell carcinoma cell line using a probe lectin or antibody probe. Glycoproteins are then captured from the serum of healthy individuals using the probe lectin or antibody probe. Lectins other than the probe lectin are then used to comprehensively capture glycoproteins.

[0130] (2) Probe lectins can be selected primarily through statistical analysis of sugar chain profiles using the aforementioned lectin microarray. Alternatively, probes can be selected based on sugar chain gene expression profiles (real-time quantitative PCR results) and literature information (which can also predict which probe lectins should be used). Essentially, selection is based on statistical analysis of the profiles, and the rationality of the selection is determined based on the binding specificity of the selected lectin.

[0131] The preparation of antibody probes can be carried out after the structure of the antigen (sugar chain) is clarified, but this is not a necessary condition. Antibody probes can also be prepared when the structure of the antigen sugar chain (or glycopeptide) is unknown.

[0132] (3) The lectin used for comprehensive capture varies depending on the distribution of sugar chain structures in the sample to be used as a control in the screening of biomarkers. For example, when serum is used as a control, it is known that most of the sugar chains on serum glycoproteins are double-stranded sugar chains that are sialylated. If sialidase treatment is performed, it is believed that most of the serum glycoproteins (peptides) can be comprehensively captured by the lectin (RCA 120) from the hippocampus (Ricinus communis), so RCA 120 can be used. In addition, sialic acid recognition lectins are not used to avoid the influence of sialic acid separation caused by human manipulation and time-dependent degradation of the sample. When the sample used as a control is not serum, for example, when it is other body fluids, other lectins can be selected. In addition, it is also possible to comprehensively capture by hydrophilic interaction chromatography or gel filtration without using lectins.

[0133] 1-2-2. Identification of glycopeptides or glycoproteins

[0134] The captured glycoprotein can be analyzed for candidate substances (glycopeptides) by the Lec-IGOT-LC / MS method described in, for example, Japanese Patent Publication No. 2004-233303 (Patent No. 4220257) and Nature Protocols 1, 3019-3027 (2006).

[0135] (1) Sugar chain excision and stable isotope labeling of glycosylation sites

[0136] The glycopeptide group that becomes the sample is recaptured with the same probe from the peptide group obtained by digesting the glycoprotein group captured by the probe with protease. Alternatively, the probe can be directly captured from the crude peptide group obtained by protease digestion without separating the crude protein mixture of the sample. The obtained glycopeptide group is treated with an enzyme such as glycopeptidase in water labeled with isotope oxygen to dissociate the sugar chain. As a result, the asparagine at the sugar chain binding site becomes aspartic acid, and the isotope oxygen in the water ( 18O) is incorporated into the peptide. This process of labeling the sugar chain binding site with an isotope is called ectopic protein-encoded protein site-specific incorporation (IGOT).

[0137] (2) LC / MS shotgun analysis of labeled peptides

[0138] The IGOT-labeled peptides were separated by LC and introduced into MS, and the peptide sequences were fully identified by tandem mass spectrometry.

[0139] (3) Peptide identification

[0140] For example, the MS / MS ion search method described in Section 3-6-2 on Amino Acid Sequence Analysis of Mass Spectrometry in the Standard Technical Collection (edited by the Japan Patent Office) can be used to search by comparing the MS / MS peptide analysis results of the obtained peptide mixture with the MS / MS spectra registered in the database. The following amino acid modifications are considered in the search: oxidation of the side chain of methionine residues, pyrrolation (deamidation, cyclization) of amino-terminal glutamine, deamination of the amino terminal (carbamidocysteine), and deamidation of the side chain of asparagine residues (where stable isotope oxygen is incorporated).

[0141] (4) Identification of sugar chain binding sites

[0142] Among the peptides identified by MS / MS ion search, peptides with deamidation (stable isotope incorporation) of the asparagine residue side chain and containing the consensus sequence for N-linked glycan addition (Asn-Xaa-[Ser / Thr], where Xaa is not Pro) were designated as candidate glycopeptides. (Xaa is Lys / Arg; if the identified peptide sequence is cleaved at this position, such peptides are also included if the residue following Xaa can be confirmed to be [Ser / Thr] based on the overall protein amino acid sequence.) The asparagine residue in the consensus sequence of this glycopeptide was designated as the glycan attachment site. In cases where there are multiple consensus sequences, the number of deamidated (labeled) asparagine residues is less than that in the consensus sequence, and the labeled sites cannot be identified from the MS / MS spectrum, these labeled sites (glycosylation positions) are recorded together, and cases where differentiation is indistinguishable are marked.

[0143] 1-2-3. Screening of candidate glycopeptides as diagnostic markers for renal cell carcinoma

[0144] Candidate glycopeptides as diagnostic markers for renal cell carcinoma can be identified by laser microdissection of tissue from cancer-specific areas of renal cell carcinoma using a cancer probe (lectin) and the large-scale glycopeptide identification methods described in 1-2-1 and 1-2-2 above. The identified glycopeptides can serve as initial candidates for the sugar chain marker.

[0145] In this case, the approximate amount of the glycopeptide or its change can be estimated by comparing the signal intensity of the labeled peptide in LC / MS analysis.

[0146] The candidate glycopeptides identified in this way can be used as biomarkers for the diagnosis of renal cell carcinoma in various disease states after validation experiments. Furthermore, glycoproteins containing these peptide sequences can also be used as biomarkers for the diagnosis of renal cell carcinoma after validation experiments in the protein state.

[0147] 1-2-4. Validation of biomarker candidates for the diagnosis of renal cell carcinoma

[0148] Validation of candidate biomarkers for the diagnosis of renal cell carcinoma can be based on i) IGOT labeling of glycopeptides captured by probe lectins from cancer-specific regions of renal cell carcinoma and comparison of signal intensities of each labeled peptide during LC / MS analysis, ii) recognized comparative quantitative proteomics using stable isotopes for glycoproteins captured by probe lectins from cancer-specific regions of renal cell carcinoma, iii) quantitative detection of glycoproteins containing glycopeptide sequences captured by probe lectins from cancer-specific regions of renal cell carcinoma by antibodies, and iv) comparison of sugar chain profiles of glycoproteins containing glycopeptide sequences captured from cancer-specific regions of renal cell carcinoma using antibody-lectin microarrays, etc.

[0149] More specifically, i) IGOT labeling of glycopeptides captured using a probe lectin from a cancer-specific region of renal cell carcinoma from a renal cell carcinoma patient, followed by comparison of the signal intensities of each labeled peptide during LC / MS analysis: The sample (serum) proteins were individually reductively alkylated and then trypsin-digested. The resulting peptide mixture was subjected to affinity chromatography using a probe lectin to capture the glycopeptides. These glycopeptides were then labeled using the aforementioned IGOT method, and the approximate total amount was combined and individually analyzed by LC / MS. Spectra of the labeled peptides were acquired, using the mass-to-charge ratio and elution position of the identified glycopeptides as a reference, and their signal intensities were compared.

[0150] ii) Comparative quantitative proteomics using stable isotopes for glycoproteins captured with probe lectins from cancer-specific regions of renal cell carcinoma: Glycoproteins captured with probe lectins from serum samples were reductively alkylated and then digested with trypsin. The resulting peptides were stable isotope-labeled at differential sites (guanidation of Lys side chain amino groups using 13C / 15N dual-labeled methylisourea) and analyzed by LC / MS. Spectra of each identified peptide were analyzed, and by comparing signal intensities, variations between samples could be quantitatively estimated. Based on variations in the amount of proteins with cancerous sugar chains, the specificity of each marker candidate could be verified and screened for each disease condition.

[0151] iii) Immunological quantitative detection of target glycoproteins (glycoproteins containing the glycopeptide sequences described in 1-2-4) captured from cancer-specific regions of renal cell carcinoma using a probe lectin: Glycoproteins captured from this serum sample using a probe lectin are subjected to, for example, SDS-PAGE, membrane transfer, and immunological detection by Western blotting. Comparison of the signal intensities of the resulting bands allows quantitative estimation of variations between samples. Based on variations in the amount of proteins with cancerous sugar chains, the specificity of each marker candidate can be verified and screened.

[0152] iv) Comparison of sugar chain profiles using antibody-coated lectin microarrays and the like for glycoproteins captured from cancer-specific regions of renal cell carcinoma (glycoproteins containing the glycopeptide sequences described in 1-2-4): Samples are collected from cancer-specific regions of renal cell carcinoma. Candidate glycoproteins for diagnosing renal cell carcinoma are concentrated and purified from the collected sample by immunoprecipitation using antibodies, and then selected using antibody-coated lectin arrays. Lectin microarrays in which multiple lectins are immobilized can be used. More specifically, the lectin microarray described in Kuno A. et al., Nat. Methods 2, 851-856 (2005) or LecChip manufactured by GPBioscience can be used.

[0153] This allows comprehensive analysis of the sugar chain structure of glycopeptides or glycoproteins, analysis of changes in sugar chain structure between samples, and use of substances showing changes as biomarkers for the diagnosis of renal cell carcinoma.

[0154] 2. Detection of glycoproteins as a biomarker for the diagnosis of renal cell carcinoma

[0155] 2-1. Protein detection

[0156] Various recognized proteomics methods can be used to detect sugar chain marker glycoproteins. For example, one-dimensional or two-dimensional gel electrophoresis can be used to separate the captured proteins, and the detection intensity of the target (staining, fluorescence, etc.) can be compared with that of a standard sample for quantification. As a detection method using a mass spectrometer, the captured protein group can be digested with a protease, and the resulting peptides can be analyzed and detected by LC / MS. For quantification, various methods using stable isotope labeling (ICAT, MCAT, iTRAQ, SILAC method, etc.) and non-labeled simple quantitative methods (peptide counting method, area accumulation method, etc.) can be used in combination. In addition, as described later, quantification can also be performed by ELISA method.

[0157] 2-2. Lectin microarray

[0158] 2-2-1. Glycan profiling based on lectin microarray

[0159] (1) Lectin microarray

[0160] Lectin microarrays are arrays in which multiple discriminant (probe) lectins with different specificities are immobilized (arrayed) side by side on a single substrate, allowing for simultaneous analysis of which lectins interact with and to what extent the complex carbohydrates being analyzed are interacting. Lectin arrays allow for the acquisition of information necessary to infer sugar chain structure in a single analysis, and the operational steps from sample preparation to scanning can be completed quickly and easily. Sugar chain mapping systems such as mass spectrometry cannot directly analyze glycoproteins and must be pre-processed to form glycopeptides or free sugar chains. Lectin microarrays, on the other hand, offer the advantage of enabling direct analysis simply by introducing a fluorescent substance directly into the core protein. Lectin microarray technology was developed by the present inventors, and its principles and fundamentals are described, for example, in Kuno A. et al. Nat. Methods 2, 851-856 (2005).

[0161] By extracting cancer-specific regions of renal cell carcinoma using laser microdissection, it is possible to analyze sugar chain modifications in renal cell carcinoma-specific regions compared to analysis of bulk specimens. Lectin microarrays enable highly sensitive comparative sugar chain analysis and can fully analyze protein adjustments of approximately 10 to 100 nanograms. They can also be applied to samples enriched by immunoprecipitation using specific antibodies for candidate molecules (core proteins) extracted through mass analysis (antibody fluorescent lectin microarray method). In this case, the amount of protein used is on the order of a few nanograms to tens of nanograms, and statistical analysis (Student's t-test) of the obtained signal values ​​allows the selection of lectins with significant differences. This allows the simultaneous listing of antibodies and lectins that recognize specific glycoproteins.

[0162] As lectins used in lectin arrays, for example, a lectin array in which 45 types of lectins are immobilized on a substrate (LecChip manufactured by GP Bioscience) is already commercially available.

[0163] (2) Statistical analysis of sugar chain profiles using lectin arrays

[0164] Lectin arrays are now used not only for purified standards but also as a practical technology capable of quantitative comparative glycan profiling of mixed samples such as serum and cell lysates. Comparative glycan profiling of cell surface glycans has been particularly successful (Ebe, Y. et al. J. Biochem. 139, 323-327 (2006); Pilobello, KT et al. Proc Natl Acad Sci USA. 104, 11534-11539 (2007); Tateno, H. et al. Glycobiology 17, 1138-1146 (2007)).

[0165] Data mining based on statistical analysis of sugar chain profiles can be performed by, for example, the methods described in "Kuno A, et al. J Proteomics Bioinform. 1, 68-72 (2008)" or "Matsuda A, et al. Biochem Biophys Res Commun. 370, 259-263 (2008)".

[0166] (3) Antibody fluorescent lectin microarray method

[0167] The lectin microarray platform, as described above, is a simple and efficient application method. Rather than directly labeling the subject with fluorescent markers, this method indirectly introduces fluorescent markers into the subject via antibodies, allowing for simultaneous analysis of multiple samples. (Kuno A, Kato Y, Matsuda A, Kaneko MK, Ito H, Amano K, Chiba Y, Narimatsu H, Hirabayashi J. Mol Cell Proteomics. 8, 99-108 (2009)).

[0168] For example, if the target is glycoprotein, the sugar chain portion can be recognized by the lectin on the lectin microarray. Therefore, by overlaying the core protein portion with an antibody, the glycoprotein can be detected specifically and with high sensitivity without labeling or highly purifying the target glycoprotein.

[0169] (4) Lectin coverage-antibody microarray method

[0170] This method uses an antibody microarray, instead of a lectin microarray, in which antibodies against core proteins are immobilized (arrayed) in parallel on a substrate such as a glass substrate. This method requires antibodies corresponding to the number of markers to be detected. It also requires the identification of lectins that detect sugar chain changes.

[0171] 2-3. Lectin-antibody sandwich immunoassay

[0172] Based on the results of the lectin array, a simple and inexpensive sandwich assay can be designed. Essentially, a sandwich assay using two antibodies can be applied by replacing one of the antibodies with a lectin. Therefore, this method can also be applied to automated assays using existing automated detection equipment. The only point that must be considered is the reaction between the sandwich antibody and the lectin. Antibodies have at least two N-linked sugar chains. Therefore, when the lectin used to identify the sugar chains on the antibody, background noise generated by their binding reaction will be generated during the sandwich assay. To suppress the generation of this noise signal, methods of introducing modifications to the sugar chain portion of the antibody or using only Fabs that do not contain sugar chain portions are conceivable, but any recognized method is sufficient. Examples of methods for modifying sugar chain moieties include Chen S et al., Nat Methods. 4, 437-44 (2007), Comunale MA et al., J Proteome Res. 8, 595-602 (2009), and methods using Fab include Matsumoto H et al., Clin Chem Lab Med 48, 505-512 (2010).

[0173] 3. Methods for detecting renal cell carcinoma using new renal cell carcinoma diagnostic biomarker candidates

[0174] A method for detecting renal cell carcinoma in one embodiment of the present invention includes a specific method for detecting renal cell carcinoma by detecting a novel candidate biomarker for diagnosing renal cell carcinoma (hereinafter, a lectin that specifically reacts with a novel candidate biomarker for diagnosing renal cell carcinoma will be referred to as lectin "A").

[0175] For example, as a detection unit for a new renal cell carcinoma diagnostic biomarker candidate having a sugar chain that specifically reacts with lectin "A", there can be mentioned: (1) a combination of a unit for detecting the nucleoprotein by (i) detecting the sugar chain that specifically reacts with lectin "A" and (ii) detecting the portion other than the sugar chain (nucleoprotein) of the renal cell carcinoma diagnostic biomarker. And (2) an antibody specific for the renal cell carcinoma diagnostic biomarker having a sugar chain that specifically binds to lectin "A", and an antibody having the vicinity of the sugar chain binding portion as an extension. Here, the method for detecting the sugar chain that specifically reacts with lectin "A" and the unit for detecting the core protein can be a unit for measuring the sugar chain that specifically reacts with lectin "A" and a unit for measuring the core protein, respectively.

[0176] For example, by using antibodies against nuclear proteins and lectin "A" to detect new biomarker candidates for the diagnosis of renal cell carcinoma, renal cell carcinoma patients can be distinguished from healthy controls and detected. Preferably, an antibody coverage method using a lectin array is used ("Kuno A, Kato Y, Matsuda A, Kaneko MK, Ito H, Amano K, Chiba Y, Narimatsu H, Hirabayashi J. Mol Cell Proteomics. 8, 99-108 (2009)"). As a method that allows for simpler detection, a lectin-antibody sandwich immunoassay can be used (Kuno A et al Scientific Reports 2013; https: / / doi.org / 10.1038 / srep01065, Kuno A et al Scientific Reports 3, Article number: 1065 (2013)).

[0177] 3-1. For example, as a specific method for detecting renal cell carcinoma using a biomarker candidate for diagnosing renal cell carcinoma having a sugar chain that specifically reacts with lectin "A", the following can be listed: 1) a process of measuring a biomarker for diagnosing renal cell carcinoma or a fragment thereof (peptide containing a sugar chain modification site) having a sugar chain that specifically reacts with lectin "A" in a sample collected from a subject in vitro. 2) a process of measuring a biomarker for diagnosing renal cell carcinoma or a fragment thereof (peptide containing a sugar chain modification site) having a sugar chain that specifically reacts with lectin "A" in a sample collected from a healthy person in vitro. 3) a process of measuring a biomarker for diagnosing renal cell carcinoma or a fragment thereof (peptide containing a sugar chain modification site) having a sugar chain that specifically reacts with lectin "A" in a sample collected from a renal cell carcinoma patient in vitro. And

[0178] 4) A method for detecting renal cell carcinoma can be listed as comprising the following steps: comparing the measurement results of a biomarker for diagnosing renal cell carcinoma or a fragment thereof (peptide containing a sugar chain modification site) having a sugar chain that specifically reacts with lectin "A" obtained from a subject with the measurement results of a biomarker for diagnosing renal cell carcinoma or a fragment thereof (peptide containing a sugar chain modification site) having a sugar chain that specifically reacts with lectin "A" obtained from a healthy person or a renal cell carcinoma patient, and comprising the step of distinguishing the subject as having renal cell carcinoma when the measurement result of the subject is closer to the measurement value of the renal cell carcinoma patient.

[0179] (2) This can be performed using a unit for measuring a novel candidate biomarker for diagnosing renal cell carcinoma or a fragment thereof, specifically, using an antibody against the novel candidate biomarker for diagnosing renal cell carcinoma or a fragment thereof, preferably using a lectin-antibody sandwich ELISA or an antibody-coated lectin array method.

[0180] Alternatively, the concentration of a candidate biomarker for diagnosing renal cell carcinoma having sugar chains that specifically react with lectin "A" or a fragment thereof (peptide containing a sugar chain modification site) can be measured, and examples thereof include antibody-coated lectin array methods using a lectin array, LC-MS, immunoassays, enzyme activity assays, capillary electrophoresis, etc. Preferred are qualitative or quantitative methods such as LC-MS, enzyme immunoassays using monoclonal or polyclonal antibodies specific for a candidate biomarker for diagnosing renal cell carcinoma having sugar chains that specifically react with lectin "A," or a fragment thereof, double antibody sandwich ELISA, colloidal gold methods, radioimmunoassays, latex agglutination immunoassays, fluorescent immunoassays, Western blotting, immunohistochemistry, and surface plasmon resonance (SPR) methods.

[0181] More specifically, quasi-quantification can also be achieved through Western blotting using lectin "A" and candidate antibodies for renal cell carcinoma diagnostic biomarkers. In qualitative measurements, the phrase "higher results in the test subject" refers to qualitatively demonstrating the presence of a higher number of sugar chains specifically reactive with lectin "A" in the test subject sample than in a healthy individual. Furthermore, this also includes lectin methods and mass spectrometry, which are direct methods for measuring sugar chains independent of antibodies.

[0182] 4. Preparation of novel specific polyclonal and / or monoclonal antibodies using novel renal cell carcinoma diagnostic biomarker candidates or fragments thereof

[0183] In the method for detecting renal cell carcinoma using the new renal cell carcinoma diagnostic biomarker, polyclonal antibodies and / or monoclonal antibodies specific for renal cell carcinoma diagnostic biomarkers can be used if they are readily available. However, if they are not readily available, they can be prepared as follows.

[0184] 4.1. Antibody Preparation

[0185] The novel biomarker for diagnosing renal cell carcinoma in one embodiment of the present invention can be used to prepare polyclonal antibodies or monoclonal antibodies for detecting renal cell carcinoma.

[0186] For example, antibodies against fragments of candidate biomarkers for the diagnosis of new renal cell carcinoma can be prepared using well-known methods. Freund's complete adjuvant can also be administered simultaneously to enhance antibody production. Alternatively, a peptide containing the binding site for the X sugar chain can be synthesized and covalently bound to commercially available keyhole limpet hemocyanin (KLH) before administration to animals. Furthermore, granulocyte-macrophage colony stimulating factor (GM-CSF) can also be administered simultaneously to enhance antibody production.

[0187] Alternatively, monoclonal antibodies against candidate biomarkers for the diagnosis of renal cell carcinoma can be prepared, for example, by the method of Keller and Mill Schtein (Nature Vol. 256, pp. 495-497 (1975)). For example, monoclonal antibodies can be prepared by fusing antibody-producing cells obtained from an animal immunized with an antigen with myeloma cells to prepare hybridomas, and then selecting clones producing anti-X antibodies from the resulting hybridomas.

[0188] Specifically, an adjuvant is added to the obtained candidate antigen-based biomarker for diagnosing renal cell carcinoma. Examples of the adjuvant include Freund's complete adjuvant and Freund's incomplete adjuvant, and several of these may be mixed.

[0189] The antigen obtained as described above is administered to mammals, such as mice, rats, horses, monkeys, rabbits, goats, and sheep. Any conventional immunization method can be used, but it is typically performed by intravenous, subcutaneous, or intraperitoneal injection. The interval between immunizations is not particularly limited, but immunizations are preferably performed at intervals of several days to several weeks, preferably 4 to 21 days.

[0190] Antibody-producing cells are collected 2 to 3 days after the final immunization. Examples of antibody-producing cells include spleen cells, lymph node cells, and peripheral blood cells.

[0191] As myeloma (myeloma) cells fused with antibody-producing cells, strains derived from various animals such as mice, rats, and humans, which are commonly available to practitioners in this industry, are used. As the cell strain used, a cell strain with drug resistance, which cannot survive in a selective culture medium (such as HAT culture medium) in an unfused state and can survive only in a fused state, is used. 8-azaguanine resistant strains are generally used, which lack hypoxanthine-guanine-phosphoribosyltransferase and cannot grow in hypoxanthine-aminopterin-thymidine (HAT) culture medium.

[0192] Mie scatter cells preferably use various well-known cell lines, such as P3 (P3x 63Ag 8.653) (J. Immunol. 123, 1548-1550 1979)), P3x 63Ag8U.1 (Current Topics in Microbiology and Immunology 81, 1-7 (1978)), NS-1 (Kohler, G. and Milstein, C., Eur. J. Immunol. 6, 511-519 (1976)), MPC-11 (Margulies, DH et al., Cell 8, 405 (1976)), SP 2 / 0 (Shulman, M. et al., Nature 276, 269 (1978)), FO (de. St. Groth, SF et al., Cell 8, 405 (1976)), al., J. Immunol. Methods 35, 1-21 (1980)), S194 (Trowbridge, IS, J. Exp. Med. 148, 313-323 (1978)), R 210 (Galfre, G. et al., Nature 277, 131-133 (1979)), etc.

[0193] Next, the myeloma cells and antibody-producing cells are subjected to cell fusion. Cell fusion is performed in an animal cell culture medium such as MEM, DMEM, or RPME-1640 medium, with the myeloma cells and antibody-producing cells mixed at a ratio of 1:1 to 1:10 in the presence of a fusion promoter at 30 to 37°C for 1 to 15 minutes. In order to promote cell fusion, fusion promoters or fusion viruses such as polyethylene glycol, polyvinyl alcohol, or Sendai virus with an average molecular weight of 1,000 to 6,000 can be used. Alternatively, antibody-producing cells and myeloma cells can be fused using a commercially available cell fusion device that is electrically stimulated (e.g., electroporation).

[0194] Screening for target hybridomas from cells after cell fusion. Examples of such methods include selective proliferation of cells in a selective culture medium. Specifically, a cell suspension is diluted with an appropriate culture medium and then seeded onto a microtiter plate. A selective culture medium (HAT culture medium, etc.) is then added to each well, and the culture medium is subsequently replaced with another culture medium at will. As a result, cells can be grown as hybridomas.

[0195] Hybridomas are screened by limiting dilution, fluorescence-activated cell sorting, etc., to ultimately obtain monoclonal antibody-producing hybridomas. Monoclonal antibodies can be isolated from the obtained hybridomas by conventional cell culture methods, ascites formation methods, etc.

[0196] Example

[0197] The present invention will be described in more detail below with reference to the following examples, but the present invention is not limited to these examples.

[0198] [Example 1]

[0199] Selection of glycopeptide biomarkers using glycoproteomics (IGOT-LC / MS method)

[0200] 1. Large-scale identification of glycoproteins

[0201] 1) Preparation of peptide samples

[0202] Frozen specimens of cancer tissues diagnosed as ccRCC and ACD-RCC in patients with renal cell carcinoma undergoing dialysis were crushed using a ball mill, and then lysis buffer (20 mM, pH 7.5, Tris-HCL 1% Triton-X 100) was added and cooled on ice for 30 minutes. Subsequently, ultrahigh-speed centrifugation (100,000 g, 60 minutes) was performed at 4°C to recover the precipitate. The precipitate was washed with ice-cold pH 7.4 PBS. Washing was performed twice.

[0203] Phase transfer surfactant (PTS) (12 mM sodium deoxycholate, 12 mM sodium N-lauroylsarcosinate, 100 mM Tris-HCl (pH 9.0)) was added to the precipitate to a protein concentration of approximately 5 to 10 μg / mL. Dithiothreitol (DTT) in an amount equal to the protein weight was dissolved in a small amount of phase transfer surfactant and added. The reaction was allowed to proceed at room temperature for 1 hour (reduction of disulfide bonds). Next, iodoacetamide (2.5 times the protein weight) was dissolved in a small amount of phase transfer surfactant and added. The reaction was allowed to proceed at room temperature for 1 hour under light-shielding conditions (S-alkylation). After the reaction, lysyl endopeptidase (sequencing grade or higher) at 1 / 200 of the protein weight was added. After reacting at 37°C for 1 hour, trypsin (sequencing grade or higher) at 1 / 100 of the protein weight was added and the reaction was allowed to proceed at 37°C overnight (approximately 16 hours) (digestion).

[0204] TFA was added to the enzymatically digested peptide to a final concentration of 1% to precipitate PTS, and the precipitate was removed by filtration using a 0.22 μm PTFE filter.

[0205] 2) Capture and purification of glycopeptides

[0206] Acetonitrile was added to the sample peptide to a final concentration of 75%, and applied to an amide column equilibrated with water-acetonitrile (25:75) containing 0.1% TFA. After washing, water-acetonitrile (1:1) containing 0.1% TFA was passed through the column to elute the glycopeptide.

[0207] 3) Glycan excision and stable isotope labeling of glycosylation sites (IGOT)

[0208] The purified glycopeptide was frozen and centrifuged under reduced pressure to completely remove the solvent. Water labeled with the stable isotope oxygen-18 (H2 18 Peptide-N-glycanase (glycopeptidase F, PNGase) prepared with labeled water was added thereto and reacted at 37°C overnight.

[0209] 4) LC / MS shotgun analysis of labeled peptides

[0210] The reaction solution was diluted with 0.1% formic acid and analyzed by LC / MS shotgun method. At this time, in order to obtain high separation ability, high reproducibility and high sensitivity for detection, a nanoflow LC system was used. The injected peptide was temporarily captured on a capture column (reversed phase C18 silica gel carrier) for the purpose of desalting. After cleaning, it was separated by a concentration gradient method of an organic solvent (acetonitrile) using a frit-free microcolumn (inner diameter 75 or 150 μm × 100 or 50 mm L) in the shape of a spray chip filled with the same resin. The eluate was ionized by an electrospray interface and directly introduced into a mass spectrometer. Mass spectrometry analysis was performed in positive ion mode and data-dependent acquisition method. An MS1 ​​spectrum was collected every 3 seconds. During this period, ions that could obtain MS / MS spectra were selected, and they were fragmented in turn by high-energy collision-induced dissociation (HCD) to measure the MS / MS spectrum.

[0211] 5) Peptide retrieval based on MS / MS-ion search method

[0212] Thousands of MS / MS spectra were smoothed and centered to create peak lists (mgf files). Based on this data, peptides were identified by MS / MS ion search using a protein amino acid sequence database. The search engine used was Mascot from Matrix Science. The search parameters used were the fragmentation method used (trypsin digestion), MisclriageTolerance: 2, fixed modification: carbamoylmethylation of cysteine, variable modification: pyroglutamination of N-terminal glutamine (terminal glutamine), deamination of N-terminal amino group (terminal cysteine), oxidation (methionine), absorption 18 Deamidation of O (asparagine: glycosylation position), tolerance of MS spectrum: 7 ppm, tolerance of MS / MS spectrum: 0.02 Da.

[0213] 6) Identification of glycopeptides

[0214] A search was conducted under the above conditions, and the following identification and confirmation processing was performed based on the results.

[0215] (1) The accuracy score of the identification (the probability of coincidence by chance: the expected value) is 0.05 or the expected value of the false discovery rate is 1%, whichever is smaller.

[0216] (2) The identified peptides contain Asn modifications (conversion to Asp and 18 O absorption), the number of which does not exceed the number of consensus sequences in the peptide, and the modification site is on the consensus sequence.

[0217] 2. Steps for Screening Marker Glycopeptides

[0218] 1) Glycopeptides were collected using an amide column from a tryptic digest of proteins collected from a sample of a cancer-specific region of renal cell carcinoma associated with acquired cystic kidney disease in a dialysis patient. These peptides were then identified using the aforementioned IGOT-LC / MS method. The identified glycopeptides were used as biomarker glycopeptides for the diagnosis of early-stage renal cell carcinoma.

[0219] 2) Next, glycopeptides were captured and identified using the same amide column using samples collected from cancer-specific regions of clear cell renal cell carcinoma in dialysis patients. The identified glycopeptides were used as initial standard glycopeptides for renal cell carcinoma diagnosis.

[0220] 3) These glycopeptide lists were compared with each other, and the following classification and screening were performed.

[0221] (i) The initial renal cell carcinoma diagnostic biomarker glycopeptides of 1) were compared with the initial renal cell carcinoma diagnostic standard glycopeptides of 2), and the protein group identified only in 1) was used as the marker glycopeptide.

[0222] (ii) For non-overlapping peptides, peptides identified only from samples of renal cell carcinoma associated with acquired cystic kidney disease in dialysis renal cancer patients were screened as "biomarker glycopeptides for the diagnosis of renal cell carcinoma."

[0223] As shown above, the marker glycopeptides screened are defined not only by the amino acid sequence, but also by the modifications of the peptide part, especially the glycosylation position, which are combined to define the marker glycopeptides. Figure 3 shown.

[0224] 3. Marker glycoprotein

[0225] From the sequences of the marker glycopeptides identified and screened in 2., the glycoprotein containing the sequence was determined.

[0226] [Example 2]

[0227] Glycopeptide biomarker selection by Byonic

[0228] Glycoproteins extracted from frozen tissue specimens of cancerous sites of ACD-RCC and cc-RCC were reductively alkylated and trypsin-digested to fragment the peptides. Glycopeptides were then enriched using an amide column. This sample was analyzed by LC / MS. A nanoflow LC system was used to achieve high resolving power, high reproducibility, and high sensitivity. The injected peptides were temporarily trapped on a capture column (reversed-phase C18 silica-based support) for desalting purposes. After washing, they were separated using a spray chip-shaped frit-free microcolumn (75 or 150 μm inner diameter × 100 or 50 mm L) filled with the same resin using an organic solvent (acetonitrile) concentration gradient method. The eluate was ionized using an electrospray interface and directly introduced into the mass spectrometer. Mass spectrometry analysis was performed in positive ion mode using data-dependent acquisition. An MS1 ​​spectrum was acquired every 3 seconds. During this time, ions suitable for MS / MS spectra were selected and sequentially fragmented using high-energy collision-induced dissociation (HCD) to measure the MS / MS spectrum. When a signal from N-acetylhexosamine at m / z 204 was observed as a fragment, this ion was fragmented using electron transfer dissociation (ETD) with the assistance of HCD to obtain an EThcD spectrum. Glycopeptide analysis was performed on the thousands of MS / MS spectra obtained using Byonic, a large-scale glycopeptide identification software from Protein Metrics.

[0229] The search parameters used were the fragmentation method used (trypsin digestion), tolerance: 2, fixed modification: carbamidomethylation of cysteine, variable modifications: pyroglutamylation of N-terminal glutamine (terminal glutamine), deamination of N-terminal amino groups (terminal cysteine), oxidation (methionine), MS spectrum tolerance: 7 ppm, MS / MS spectrum tolerance: 0.02 Da. Fragmentation methods: HCD and EThcD. Some of the results are shown below. Figure 4A shown.

[0230] [Example 3]

[0231] Selection of glycopeptide biomarkers using the Glyco-RIDGE method

[0232] Glycoproteins extracted from frozen tissue specimens of ACD-RCC and cc-RCC cancerous sites were subjected to reductive alkylation and peptide fragmentation using trypsin digestion. Glycopeptides were then enriched using an amide column. The resulting MS1 multivalent ion signals were deconvoluted to monovalent ions, and the glycan structures attached to the peptides were predicted using the Glyco-RIDGE method.

[0233] Sugar chain structure prediction was performed using Grable software developed by the National Institute of Advanced Industrial Science and Technology. Monoisotopic signals were searched for signals with an intensity of 10 or greater over the entire analysis time range, using Grable's default settings. Among the monoisotopic signals found, signal pairs with different monosaccharide or disaccharide masses were accurately searched within the LC elution time set as follows. When signal pairs were found, these pairs were linked to detect clusters. Hex (m / z 162.0528), HexNAc (m / z 203.0794), dHex (m / z 146.0579), Hex+HexNAc (m / z 365.1322), Hex+HexNAc+dHex (m / z 511.1901): -3 to 0.1 minutes, NeuAc (m / z 291.0954): 1 to 5 minutes, with a mass tolerance of 5 ppm.

[0234] Next, the mass of the glycopeptides obtained by clustering is compared with the mass of the core peptide, and peptides with masses that are different from those of the sugar chain composition are searched (matched). The information of the core peptide uses the results of IGOT-LC / MS of the same sample obtained under the same analytical conditions. The parameters in the matching are set as follows. The number of constituent sugars is Hex, HexNAc: 0 to 12, dHex, NeuAc: 0 to 4, and the allowable error of the mass is 5ppm. For the predicted sugar chain components, a separate list of sugar chain feature points is used to evaluate their accuracy. Part of the results is shown below. Figure 4B shown.

[0235] [Example 4]

[0236] Immunostaining

[0237] (1) Immunohistochemical staining

[0238] Formalin-fixed paraffin-embedded (FFPE) specimens from the cancerous site and surrounding areas of renal cell carcinoma patients on dialysis were collected to examine the expression of GPNMB, Megalin, ACE2, and MME in renal cell carcinoma tissues and cystic lesions.

[0239] First, slide specimens cut into 3 μm thickness were deparaffinized and then washed with distilled water.

[0240] Immunohistochemical staining for GPNMB, megalin, and ACE2 was performed using an automated staining device, the Histone Analyzer (manufactured by Nichirei Biosciences). Antigen activation was performed using the PT-Link antigen activation device. CD10 (MME) staining was activated using an Agilent Technologies Omnis dedicated kit (EnVision FLEX, High pH Dako Omnis).

[0241] As primary antibodies, the following were used.

[0242] Anti-GPNMB polyclonal antibody ("AF 2550", manufactured by Bio-Techne)

[0243] Anti-Megalin monoclonal antibody ("sc-515772", manufactured by Santa Cruz Biotechnology)

[0244] Anti-ACE2 monoclonal antibody ("sc-390851", manufactured by Santa Cruz Biotechnology)

[0245] Anti-CD10 (MME) monoclonal antibody (for immunohistochemistry (IHC): GA 648; for fluorescent multiplex staining: IR 648), manufactured by Agilent Technologies, Inc.: for mechanical staining only)

[0246] As labeled lectins, the following lectins were used.

[0247] SNA lectin (SAMBUCS NIGRA (ELDERBERRY) BARK LECTIN ("B-1305" (natural product), manufactured by Vector Laboratories))

[0248] MAH lectin (Maackia amurensis lectin II ("B-1265" (natural product), manufactured by Vector Laboratories))

[0249] Representative staining results (IHC) of GPNMB, Megalin, ACE2 and MME are shown in Figure 2. Figure 5AThe results show that there are cases where GPNMB is weakly positive or negative but Megalin, ACE2, and MME are strongly positive, and cases where GPNMB is strongly positive but Megalin, ACE2, and MME are weakly positive. When observing glomeruli, renal tubules, cyst epithelium, ACD-RCC, and cc-RCC using fluorescent multiple staining, MME is not sialylated in normal tissues, but Figure 5B As shown, colocalized regions of fluorescence staining for MME and SNA were observed in cystic epithelial and cancerous tissues, confirming that MME is sialylated, as recognized by SNA. This suggests that specific sugar chain modifications (sialylation) not found in normal tissues may occur during precancerous lesions, suggesting its usefulness as a marker for acquired cystic diseases.

[0250] Based on the obtained results, the expression of GPNMB, Megalin, ACE2, and MME was evaluated. IHC evaluation was performed according to the evaluation criteria (Table 1) of the HER2 Pathological Diagnosis Guidelines for Breast and Gastric Cancer, Second Edition (Japanese Society of Pathology) https: / / www.kanehara-shuppan.co.jp / books / detail.html?isbn=9784307050548.

[0251] Table 1

[0252]

[0253] The evaluation results are shown in Table 2.

[0254] Table 2

[0255]

[0256] As shown in the staining results, MME expression was found in most cases of both ACD-RCC and cc-RCC, which is consistent with previous reports (Non-Patent Document 5). Regarding GPNMB, Megalin, and ACE2, cases with strong GPNMB positive results showed negative to equivocal expression of Megalin and ACE2, while cases with negative GPNMB showed a tendency to be positive for Megalin and ACE2. This is consistent with the following literature showing that GPNMB exhibits stem cell characteristics.

[0257] ·C.Chen, Y.Okita, Y.Watanabe, F.Abe, MAFikry, Y.Ichikawa, H.Suzuki, A.Shibuya, M.Kato, Glycoprotein nmb Exposed on the Surface of Dormatt BreastCancer Cells and Induces Stem Cell-like Properties., Cancer Res78 (2018) 6424-6435.

[0258] ·C.Wang, Y.Okita, L.Zheng, Y.Shinkai, L.Manevich, JMChin, T.Kimura, H.Suzuki, Y.Kumagai, M.Kato, Glycoprotein non-metastic melanoma protein Bfunctions with growth factor signaling to induce tumorigenesis through serinephosphorylation., Cancer Sci 112 (2021) 4187-4197.

[0259] At the tissue level, the presence of sugar-chain-modified MMEs identified by SNA was confirmed in both ACD-RCC and cc-RCC (including cystic lesions), but was more pronounced in ACD-RCC. Furthermore, the sugar-chain-modified MMEs identified by SNA were not confirmed in normal tissue.

[0260] (2) Protein immunoblotting

[0261] To verify the differences in the amounts of GPNMB, MME, and megalin between ACD-RCC and cc-RCC, the following experiment was conducted using cancerous tissues from 12 randomly selected renal cancer patients.

[0262] (Enrichment of target molecules in tissue samples using antibodies against each molecule)

[0263] Frozen tissue from the cancerous sites (T) of 12 renal cancer cases (cc-RCC: #1, #2, #3, #4, #5, #11, #12 and ACD-RCC #6, #7, #8, #9, #10) was solubilized according to conventional methods, and the resulting solution was used as tissue lysate. The solubilization buffer used was phosphate-buffered saline (PBSTx) containing 1% protease inhibitor (Protease Inhibitor Cocktail, Animal Component Free, manufactured by Sigma-Aldrich) and 1% Triton X-100. The total protein content in the tissue lysate was quantified using the Micro BCA Protein Assay Kit (manufactured by Thermo Fisher Scientific) based on the conventional BCA method. Therefore, using a protein amount equivalent to 50 μg as the total protein amount of each sample, immunoprecipitation was performed according to the methods of Kuno et al. and Wagatsuma et al. (Kuno A et al. Molecular & Cellular Proteomics 8(1), 99-108 (2009), Wagatsuma T et al Frontiers in Oncology 10, 338 (2020)).

[0264] a)GPNMB

[0265] In the immunoprecipitation described above, 10 μL of streptavidin-immobilized magnetic beads (Dynabeads MyneStreptavidin T1, manufactured by DYNAL) were used for pre-clearing. This 10 μL of magnetic beads and 500 ng of biotinylated GPNMB antibody (Human Osteoactivin / GPNMB Biotinylated Antibody, manufactured by R&D Systems) were pre-coupled prior to reaction with tissue lysate. Twenty μg of pre-cleared tissue lysate was mixed with the pre-coupled product and allowed to react overnight. The beads were cleared three times with 1% PBSTx. To elute the molecules captured by the beads, 20 μL of TBS buffer containing 0.2% SDS was added to the precipitated magnetic bead pellet and heated at 95°C for 10 minutes. The magnetic beads were captured by a dedicated magnet for recovery, and 20 μL of the above-mentioned magnetic beads were added to the resulting supernatant. The biotinylated antibody dissolved together with the protein was captured and removed from the magnetic beads by heating, and the supernatant finally obtained was used as a GPNMB eluate (GPNMB enrichment). Using half the amount of the eluate, protein immunoblotting was performed according to a conventional method. In addition, a 5-20% gradient polyacrylamide gel was used in the electrophoresis gel, the above-mentioned biotinylated antibody was used in the primary antibody detected, and streptavidin-HRP and a detection substrate (Immno Star LD, Fujifilm Wako Pure Chemical Industries, Ltd.) were used in the detection.

[0266] b)MME

[0267] In the immunoprecipitation described above, 20 μL of streptavidin-immobilized magnetic beads were used for pre-clearing. For immunoprecipitation, 10 μL of these beads and 400 ng of biotinylated anti-MME antibody (MME, CD10 antibody, Proteintech) were pre-conjugated prior to reaction with tissue lysate. 50 μg of pre-cleared tissue lysate was mixed with the pre-conjugated solution and allowed to react overnight. Furthermore, since the anti-MME antibody binds to heat-denatured MME, SDS was added to the tissue lysate prior to the binding reaction to a final concentration of 0.2%, followed by heating at 95°C for 5 minutes. The beads were washed three times with 1% PBSTx. To elute the molecules captured by the beads, 20 μL of TBS buffer containing 0.2% SDS was added to the precipitated magnetic beads and heated at 95°C for 10 minutes. The magnetic beads were captured by a dedicated magnet for recovery, and 40 μL of the magnetic beads were added to the obtained supernatant. The biotinylated antibody dissolved with the protein was captured and removed from the magnetic beads by heating, and the supernatant finally obtained was used as the MME eluate (MME enrichment). Half of the amount of the eluate was used for protein immunoblotting according to conventional methods. In addition, a 5-20% gradient polyacrylamide gel was used in the electrophoresis gel, the biotinylated antibody was used as the detection primary antibody, and streptavidin-HRP and detection substrate were used in the detection.

[0268] c) Megalin

[0269] In the above-mentioned immunoprecipitation, the amount of streptavidin-immobilized magnetic beads used in pre-clearing was 10 μL. In the immunoprecipitation, 10 μL of these magnetic beads and 500 ng of biotinylated anti-Megalin antibody (Megalin (H-10), manufactured by Santa Cruz Biotechnology) were used and pre-coupled before reacting with the tissue lysate. The tissue lysate equivalent to 20 μg after pre-clearing was mixed with the above-mentioned pre-coupled substance and reacted overnight. In addition, the anti-Megalin antibody used binds to the heat-denatured Megalin, so the magnetic beads were recovered with a magnet before the binding reaction. After the supernatant was recovered as the unbound fraction, the beads were washed three times with 1% PBSTx. In order to elute the molecules captured by the magnetic beads, 20 μL of TBS buffer containing 0.2% SDS was added to the magnetic bead particles after precipitation and heated at 95°C for 10 minutes. The magnetic beads were captured by a dedicated magnet for recovery, and 20 μL of the above-mentioned magnetic beads were added to the obtained supernatant. The biotinylated antibody dissolved with the protein was captured and removed from the magnetic beads by heating, and the resulting supernatant was used as a Megalin eluate (Megalin enrichment). Half the amount of the eluate was used for protein immunoblotting according to conventional methods. In addition, a 5-20% gradient polyacrylamide gel was used in the electrophoresis gel, the above-mentioned biotinylated antibody was used in the detection of the primary antibody, and streptavidin-HRP and a detection substrate were used in the detection.

[0270] like Figure 6 As shown, there was no significant difference in the expression of Megalin between ACD-RCC and cc-RCC in GPNMB and MME. Megalin tended to be expressed at higher levels in the ACD-RCC patient group.

[0271] [Example 5]

[0272] Antibody Coverage-Lectin Microarray

[0273] Next, in order to verify whether the qualitative difference between ACD-RCC and cc-RCC of GPNMB, MME, and Megalin can be presented by the difference in reaction with the 45 lectins on the lectin array, the GPNMB, MME, and Megalin eluates obtained by the above method were enriched, and lectin array analysis (antibody coverage method) was performed according to the method of Kuno et al. Molecular & Cellular Proteomics 8 (1), 99-108 (2009), Wagatsuma T et al Frontiers in ology 10, 338 (2020)). The lectin array chip used at this time was the commercially available chip LecChip ver 1.0 (manufactured by Gliko Technic).

[0274] Each sample (GPNMB, MME, and Megalin eluate enrichment) was placed on the aforementioned lectin array chip ver. 1.0. Appropriate amounts (equivalent to 7.5 μg of GPNMB, 25 μg of MME, and 7.5 μg of Megalin enrichment, as the total protein amount during IP) were collected from the immunoprecipitated solution and allowed to react at 20°C for at least 10 hours. To prevent noise from binding of lectins to sugar chains on the detection antibody on the unreacted substrate, 2 μL of a human serum-derived IgG solution (Sigma-Aldrich) was added and allowed to react for 30 minutes. Then, 50 ng of the above-mentioned biotinylated antibody (however, 100 μg of GPNMB) was added and reacted at 20°C for 1 hour, followed by the addition of 200 ng of Cy3-labeled streptavidin and the reaction at 20°C for 30 minutes. After washing the remaining fluorescent substance with PBSTx, the array was scanned using GlycoStationReader 1200 (manufactured by GlikoTechnic) to detect the binding signal. In each molecule, a t-test was performed to infer whether the signals of the 45 lectins showed significant differences between ACD-RCC and cc-RCC. The results are as follows: Figure 7 Furthermore, MME generated lectin array signals in only 4 of 12 samples and therefore was not included in the statistical analysis.

[0275] Lectins with P < 0.05 were judged to be significantly different, and the P value bars are indicated in gray. Among GPNMB, SNA, SSA, and TJA-I, which are α2,6 sialic acid recognition lectins, showed significantly higher values ​​in ACD-RCC. In addition, in megalin, 2 to 3 of the 5 ACD-RCC patients showed high values, but due to large variations, no statistically significant difference was shown. As shown by immunohistological verification, the relationship between GPNMB and megalin expression is negatively correlated. Therefore, there are many cases in which GPNMB values ​​are high in the 12 cases this time, making it considered that verification of megalin is more difficult. Therefore, we look forward to further verification in the future by increasing the number of samples to confirm the case group showing significant differences.

[0276] [Example 6]

[0277] Lectin microarray and western blotting using serum samples

[0278] Regarding GPNMB, which showed the most significant difference, the following experiment was conducted using sera collected before and after surgery from 6 randomly selected dialysis renal cancer patients.

[0279] A total of 12 samples of serum from 6 cases (#1 to 6) of renal cancer patients before and after surgery were used as the liquid volume, and 40 μL was used to perform immunoprecipitation according to the enrichment method of the above-mentioned tissue lysate. In the immunoprecipitation, the streptavidin-immobilized magnetic beads used for pre-clearing were in an amount of 10 μL. 10 μL of the magnetic beads and 500 ng of biotinylated GPNMB antibody were used in the immunoprecipitation and pre-coupled before reacting with the serum dilution solution. An amount equivalent to 40 μg of serum after pre-clearing was mixed with the above-mentioned pre-conjugate and reacted overnight. The beads were washed 3 times with 1% PBSTx. In order to dissolve the molecules captured by the magnetic beads, 20 μL of TBS buffer containing 0.2% SDS was added to the magnetic bead particles after precipitation and heated at 95°C for 10 minutes. The magnetic beads were captured by recycling a special magnet, and 20 μL of the above-mentioned magnetic beads were added to the resulting supernatant. The biotinylated antibody dissolved together with the protein was captured and removed from the magnetic beads by heating, and the resulting supernatant was used as a GPNMB eluate (GPNMB enrichment). A quarter of the amount of the eluate was used for protein immunoblotting according to a conventional method. In addition, a 5-20% gradient polyacrylamide gel was used in the electrophoresis gel, the above-mentioned biotinylated antibody was used in the detection of the primary antibody, and streptavidin-HRP and a detection substrate were used in the detection.

[0280] The results are as follows Figure 8 In most cancer patients, the amount of GPNMB increases compared to healthy individuals. Although it varies depending on the case, it has been confirmed that the amount of GPNMB decreases substantially after surgery compared to before surgery.

[0281] Next, in order to verify whether the qualitative changes in GPNMB in the serum before and after surgery can be presented as differences in the reaction with the 45 lectins on the lectin array, the GPNMB eluate obtained by the above method was enriched and the lectin array was analyzed (antibody coverage method) using the same method as tissue lysis. Each sample (GPNMB eluate enrichment) was placed in the above-mentioned lectin array chip ver 1.0, and an appropriate amount (as the serum volume when implementing IP, GPNMB is equivalent to 10 μL of enrichment) was applied from the immunoprecipitation solution, and the binding reaction was carried out at 20°C for more than 10 hours. In order to avoid noise caused by the binding of lectins to sugar chains on the detection antibodies on the unreacted substrate, 2 μL of IgG solution from human serum (made by Sigma-Aldrich) was added and allowed to react for 30 minutes. Then, 100 ng of the biotinylated antibody was added and reacted at 20°C for 1 hour. Then, 200 ng of Cy3-labeled streptavidin was added and reacted at 20°C for 30 minutes. After washing the remaining fluorescent substance with PBSTx, the array was scanned using a GlycoStationReader 1200 to detect the binding signal. The P value was calculated by paired test for each signal of each lectin with paired images before and after the operation. The results are as follows: Figure 9 As shown. The ones circled in bold are those with P<0.05. The α2,6 sialic acid recognition lectins SNA and SSA found in the search process showed a significant decrease in signal in the postoperative specimens. Furthermore, the signal of the lectin DSA, which is difficult to distinguish between preoperatively and postoperatively in each case, was normalized as a benchmark. Figure 10 As shown, this tendency becomes more obvious.

[0282] The above results indicate that at least GPNMB can be detected in the serum of patients or healthy individuals and is useful as a serum biomarker, particularly as a serum renal cancer marker in dialysis patients.

[0283] Possible industrial applications

[0284] The biomarker of this embodiment can specifically detect renal cell carcinoma and can therefore be suitably used in methods for detecting renal cell carcinoma and in the production of diagnostic kits for renal cell carcinoma, and has industrial applicability.

Claims

A biomarker for detecting renal cell carcinoma, comprising a renal tissue-derived glycoprotein having sialylated sugar chains whose expression is increased due to cancerous transformation.

2. The biomarker according to claim 1, wherein The renal tissue-derived glycoprotein includes a renal tubular epithelial cell-derived glycoprotein.

3. The biomarker according to claim 1 or 2, wherein The renal tissue-derived glycoprotein comprises one or more glycoproteins selected from the group consisting of GPNMB, Megalin, ACE2, and MME.

4. The biomarker according to any one of claims 1 to 3, wherein The renal cell carcinoma is renal cell carcinoma in dialysis patients.

5. A method for detecting a biomarker, comprising: The biomarker according to any one of claims 1 to 4 is detected in vitro in a test sample obtained from a subject. The detection method according to claim 5 , comprising a sandwich ELISA method.

7. The detection method according to claim 5 or 6, wherein The test sample is serum.

8. A diagnostic kit for renal cell carcinoma, comprising a unit for detecting the biomarker according to any one of claims 1 to 4.

9. The kit according to claim 8, wherein The detection unit comprises an antibody that binds to the kidney tissue-derived glycoprotein having sialylated sugar chains, and a lectin that binds to the sialylated sugar chains.

10. A method for searching for a renal cell carcinoma marker, comprising investigating changes in the sugar chain structure of a glycoprotein derived from kidney tissue. The retrieval method according to claim 10 , comprising analysis using a lectin array or Western blot.

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