Biomarker for renal cell cancer detection

Abstract

Provided is a biomarker capable of specifically detecting renal cell cancer. Based on our finding that sialylation (sialic acid modification) is accentuated in the case of acquired cystic kidney disease associated renal cell carcinoma (ACD-RCC) compared to clear cell renal cell carcinoma (cc-RCC) from techniques in which cancer-specific regions are collected under a microscope from histopathology samples and diverse omics analyses such as lectin arrays and RNAseq, we have identified, by glycoproteomics that includes mass spectrometry, a glycoprotein group having a sugar chain structure containing a specific glycosylation, in particular, a sialylation, among protein groups from cancer tissue of renal cell cancer, and this glycoprotein group is provided as a new biomarker specific for renal cell cancer.

Description

Biomarkers for detecting renal cell carcinoma

[0001] The present invention relates to a biomarker for detecting renal cell carcinoma.

[0002] The incidence rate of renal cell carcinoma among all cancers in the global population was 2.4% (2020), ranking 14th. However, the incidence rate of renal cancer in dialysis patients is particularly high compared to healthy individuals and other cancer types. The standardized incidence ratio (SIR) relative to healthy individuals has been 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). Behind this, it has been shown that the occurrence of acquired cystic kidney disease (ACKD), which is considered a non-genetic disease, contributes to the increased incidence of renal cell carcinoma. ACKD is a non-hereditary cystic disease that is observed in 7-22% of patients with renal failure before the introduction of blood purification therapy, with a high incidence rate of 60% in those with 2-4 years of dialysis and over 90% in those with 8 years or more of dialysis (Non-Patent Document 4). The longer duration of dialysis in Japanese dialysis patients compared to Western countries and the low number of kidney transplants are thought to be factors that reflect the high standardized incidence rate mentioned above. Furthermore, the concept of acquired cystic kidney disease-associated renal cell carcinoma (ACD-RCC) (Non-Patent Document 4) has been established as a histological type of renal cell carcinoma that occurs specifically in dialysis kidneys, and was included in the WHO Classification of Renal Cell Tumors, 4th Edition (2016) and continued in the 5th Edition (2022). ACD-RCC exhibits alveolar, cribriform, microcystic, and cystic morphology, often with eosinophilic granular cytoplasm and moderate to severe nuclear atypia. Immunohistochemistry is characterized by positive results for α-methyl-acyl-coenzyme A (AMACR), RCC markers, MME (CD10), etc., and negative results for CK7 (Non-Patent Document 5), but no specific marker has been established. ACD-RCC is the most common type of renal cancer in dialysis recipients, accounting for 36%, followed by clear cell papillary renal cell carcinoma (23%), clear cell renal cell carcinoma (cc-RCC), which accounts for over 70% of renal cancers in healthy individuals, at 18%, papillary renal cell carcinoma (15%), and chromophobe renal cell carcinoma (8%), according to a report of 66 cases (Non-Patent Document 4).A Japanese study reported a clinicopathological analysis of 291 cases of renal cell carcinoma in dialysis patients, reflecting the WHO 2016 guidelines. The incidence of ACD-RCC (compared to the incidence of cc-RCC, which accounts for the majority of non-dialysis cases) was 7.6% (76.1%) in patients with up to 10 years of dialysis, then 43.6% (38.1%) in patients with 10 to 15 years of dialysis, with the incidence rate rising to 50.7% (21.6%) in patients with 15 to 20 years of dialysis (Non-Patent Document 6). There are currently 345,000 dialysis patients in Japan and an estimated 4 million worldwide, with a rapid increase in the number of dialysis patients, particularly in Asia (the number of dialysis patients in China increased from 235,000 in 2011 to 693,000 in 2020). Therefore, the incidence of renal cell carcinoma is expected to continue to increase. Early detection is crucial in cancer treatment, but no tumor markers specific to renal cell carcinoma have yet been established, regardless of whether the patient is on dialysis or not. For this reason, the diagnosis of renal cell carcinoma is based on incidental detection through diagnostic imaging, and preoperative biopsy (tissue diagnosis) is not performed except in special cases. Because there are no effective tumor markers for follow-up, imaging tests are the primary focus of posttreatment follow-up. Because the risk of developing renal cell carcinoma is increased in dialysis patients, regular CT scans (at least once per year) are generally performed on all patients, despite low evidence. ACKD lesions (cysts) make diagnosis difficult in dialysis patients. ACD-RCC, which does not readily exhibit contrast enhancement on dynamic CT, is particularly challenging for diagnostic imaging. While no specific imaging findings have been identified, mild enhancement is generally observed on CT scans, and T2-enhanced MRI scans and restricted diffusion are observed on diffusion-weighted images (Non-Patent Document 7). While there are reports that contrast-enhanced ultrasound using perflubutane microbubbles (Non-Patent Document 8) and PET-CT scans are useful for the diagnostic imaging of dialysis-related renal carcinoma (Non-Patent Document 9), these studies have only examined a small number of cases.

[0003] Clin. Pract. 2004: 97; c11-6Nephrol. Dial. Transplant. 2009: 24; 3225-31AM. J. Kidney Dis. 2015: 65; 763-72Am. J. Surg. Pathol. 2006; 30: 141-53Arch. Pathol. Lab. Med. 2017; 141: 600-6Pathol. Int. 2018; 68: 543-9Abdom Radiol (NY). 2022; 47(8), 2858-2866.Medicine (Baltimore). 2019; 98: e18053Clin. Exp. Nephrol. 2011; 15: 136-40

[0004] At present, no established tumor markers specific to renal cell carcinoma have been reported, regardless of whether the patient is on dialysis or not. The present invention was made in light of the above circumstances, and aims to provide a biomarker that can specifically detect renal cell carcinoma, particularly in patients on dialysis.

[0005] The present invention, which solves the above-mentioned problems, comprises the following: [1] A biomarker for detecting renal cell carcinoma, comprising a glycoprotein derived from renal tissue having a sialylated sugar chain that is increased with carcinogenesis. [2] The biomarker according to [1], wherein the glycoprotein derived from renal tissue comprises a glycoprotein derived from renal tubular epithelial cells. [3] The biomarker according to [1] or [2], wherein the glycoprotein derived from renal tissue comprises one or more glycoproteins selected from the group consisting of GPNMB, Megalin, ACE2, and MME. [4] The biomarker according to any one of [1] to [3], wherein the renal cell carcinoma is renal cell carcinoma in a dialysis patient. [5] A method for detecting a biomarker, comprising in vitro detection of the biomarker according to any one of [1] to [4] in a test sample obtained from a subject. [6] The detection method according to [5], comprising a sandwich ELISA method. [7] The detection method according to [5] or [6], wherein the test sample is serum. [8] A diagnostic kit for renal cell carcinoma, comprising means for detecting the biomarker according to any one of [1] to [4]. [9] The kit according to [8], wherein the detecting means comprises an antibody that binds to the glycoprotein derived from kidney tissue having the sialylated sugar chain, and a lectin that binds to the sialylated sugar chain.

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

[11] The method for searching according to

[10] , comprising analysis by lectin array or Western blotting.

[0006] The present invention also relates to the following inventions: [1] A method for diagnosing renal cell carcinoma, comprising detecting a biomarker in a subject, the biomarker comprising a glycoprotein derived from renal tissue having a sialylated sugar chain that is increased with carcinogenesis. [2] Use of a glycoprotein derived from renal tissue having a sialylated sugar chain that is increased with carcinogenesis as a biomarker for diagnosing renal cell carcinoma. [3] A combination of one or more glycoproteins selected from the group consisting of GPNMB, Megalin, ACE2, and MME, each having a sialylated sugar chain that is increased with carcinogenesis. [4] A diagnostic kit for renal cell carcinoma, comprising the following (1) and (2), wherein either (1) or (2) is immobilized on a support, and the other is labeled: (1) a lectin that recognizes the sugar chain of a glycoprotein derived from renal tissue having a sialylated sugar chain that is increased with carcinogenesis, and (2) an antibody that binds to at least one glycoprotein selected from GPNMB, Megalin, ACE2, and MME.

[0007] According to the present invention, a biomarker capable of specifically detecting renal cell carcinoma can be provided.

[0008] This diagram shows the flow of comprehensive analysis of glycosylation in cancer-specific regions of renal cell carcinoma (RCC) samples obtained by laser microdissection, followed by application of extracted glycoproteins to a lectin microarray. This method allows for more accurate analysis of glycosylation in RCC-specific regions than bulk specimen analysis. Because lectin microarrays enable highly sensitive comparative glycosylation analysis, they can also be applied to samples enriched by immunoprecipitation using specific antibodies against candidate molecules (core proteins) extracted by mass spectrometry (antibody overlay lectin microarray method). The applied protein amounts range from a few nanograms to a few tens of nanograms, and statistical analysis of the resulting signal values ​​(Student's t-test) allows for the selection of lectins that show significant differences. This allows for the simultaneous listing of antibodies and lectins that recognize specific glycoproteins. The results of glycosylation analysis using laser microdissection lectin microarrays on thin sections of formalin-fixed, paraffin-embedded (FFPE) samples are shown. When comparing the glycosylation of cancerous tissues of ACD-RCC and cc-RCC, the two most common histological types of renal cell carcinoma in dialysis patients, ACD-RCC showed significantly more glycosylation, including sialic acid. Proteins extracted from frozen tissue specimens of cancerous tissues of ACD-RCC and cc-RCC were subjected to reductive alkylation and peptide fragmentation by trypsin digestion, and glycopeptides were enriched using an amide column. These samples were analyzed by IGOT-LC / MS to analyze the glycosylation site and identify proteins with N-glycans. The IGOT-LC / MS method enzymatically removes the glycosylation from glycopeptides with N-glycans, and then analyzes and identifies the peptide portion by LC / MS. When the glycosylation is enzymatically removed, water labeled with stable isotope oxygen-18 (H) is added to the glycopeptide. ２ １８ When peptide-N-glycosidase is used in the glycosylation process, the asparagine residue at the glycosylation site is converted to an aspartic acid residue, and oxygen-18 ( １８O) is incorporated into the peptide, thereby labeling the glycosylation site with a stable isotope. This method is called IGOT (Isotope-Coded Glycosylation Site-Specific Tagging). Because various glycans with different structures are heterogeneously attached to the same site on the same protein, glycopeptides with a single structure are rarer than non-glycosylated peptides. This is one of the reasons why glycopeptide identification is difficult. The IGOT-LC / MS method cleaves the glycans of glycopeptide samples, losing information about their diversity, but improving glycopeptide detection sensitivity, enabling highly sensitive identification of glycosylation sites. Proteins extracted from frozen tissue specimens of ACD-RCC and cc-RCC cancers were subjected to reductive alkylation and trypsin digestion to fragment peptides, and glycopeptides were enriched using an amide column. These samples were analyzed by LC / MS, and the resulting MS / MS spectra were analyzed using the glycopeptide identification software Byonic. This section lists candidate molecules (proteins) identified as sialylated (sialic acid modified) only in ACD-RCC. Byonic identifies glycopeptide ions by further fragmenting them in a mass spectrometer, using a protein amino acid sequence database and a glycan composition database. High-energy collision-induced dissociation (HCD) and electron transfer dissociation (ETD) are available for fragmentation. Proteins extracted from frozen tissue specimens of ACD-RCC and cc-RCC cancer sites were subjected to reductive alkylation and trypsin digestion to fragment peptides, followed by glycopeptide enrichment using an amide column. These samples were analyzed by LC / MS, and the resulting MS spectra were analyzed using Glyco-RIDGE (Glycan heterogeneity-based Relational Identification of Glycopeptide Signals on the Elution Profile) analysis. The following shows candidate molecules (proteins) identified as sialylated (sialic acid modified) only in ACD-RCC. A group of glycopeptides with the same core peptide but different glycan compositions elutes at similar retention times in LC separation.The Glyco-RIDGE method detects glycopeptide ions based on these elution characteristics and mass differences resulting from glycan heterogeneity. Glycopeptide composition can be predicted from the accurate 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 site) can be obtained using the IGOT-LC / MS method. Because glycopeptides have weaker signal intensity than normal peptides, data-dependent methods often fail to obtain MS / MS spectra or do not provide sufficient MS / MS spectra for analysis. Because the Glyco-RIDGE method can predict glycopeptides from a core peptide list and MS1 spectral information, it can identify glycopeptides with higher sensitivity than conventional analytical methods that rely on MS / MS. These results were obtained by immunohistochemical staining of GPNMB, Megalin, ACE2, and MME in surgical specimen tissue from a renal cancer patient undergoing dialysis. (i) ACD-RCC and (ii) cc-RCC (two cases each) are shown. Cases showing strong GPNMB positivity tended to show weak positivity for other molecules, while cases showing weak positivity or negative GPNMB tended to show strong positivity for other molecules. Histofluorescent multi-staining was performed on renal tissue from dialysis patients with renal cancer: ACD-RCC and cc-RCC. The arrow indicates the area where MME and SNA (a lectin that recognizes α-2,6 sialic acid) merge. This change was observed in cyst and renal cell carcinoma tissue (stronger in ACD-RCC than in cc-RCC), but not in normal renal tissue. Western blot analysis of GPNMB, Megalin, and MME was performed on ACD-RCC samples. These are the results of a t-test performed after comparative glycan analysis of GPNMB and Megalin using an antibody overlay lectin microarray. Each value indicates a P value, with P<0.05 being considered a significant difference and marked in gray. "#DIV / 0!" indicates that no signal was observed in either sample, making the test impossible. These are the results of a Western blot performed on GPNMB using a serum sample. These are the results of immunoprecipitation-lectin array analysis of GPNMB using a serum sample (NET intensity).Results determined to be significantly different at P<0.05 in the paired t-test are enclosed in a bold frame. Results (Mean Normalized) of immunoprecipitation-lectin array for GPNMB using serum samples. Results determined to be significantly different at P<0.05 in the paired t-test are enclosed in a bold frame.

[0009] An embodiment of the present invention will be described in detail below. The present invention is not limited to the following embodiment, and can be carried out by making appropriate modifications within the scope that does not impair the effects of the present invention. When a specific description given for one embodiment also applies to other embodiments, that description may be omitted in other embodiments. In this specification, the expression "X to Y" indicating a numerical range means "at least X and at most Y."

[0010] The present inventors have found, through techniques for collecting cancer-specific regions from pathological tissue specimens under a microscope and through multi-omics analyses such as lectin arrays, that sialylation (sialic acid modification) is enhanced in ACD-RCC compared to cc-RCC. Based on this finding, glycoproteomics, including mass spectrometry, has been used to identify, among proteins in renal cell carcinoma cancer tissue, glycoproteins with glycan structures containing sialic acid modifications, and these have been provided as novel renal cell carcinoma-specific biomarkers (glycopeptides and glycoproteins). Prior art utilizing glycoanalysis for the diagnosis of renal cell carcinoma includes a technique for grading cancer according to the amount of glycoprotein on the cell surface (Japanese Patent Publication No. 2019-106214) and a technique utilizing detection of the glycoprotein SIMA135 (Japanese Patent Publication No. 2013-128709), but neither of these techniques is directly related to the present invention.

[0011] [Biomarker] In one embodiment of the present invention, the biomarker comprises a glycoprotein derived from renal tissue having a sialylated sugar chain that is increased during carcinogenesis, and can be used to detect renal cell carcinoma.

[0012] [Renal Cell Carcinoma] In the embodiment, renal cell carcinoma includes not only renal cell carcinoma but also cystic epithelium, which is considered to be a precancerous lesion of renal cell carcinoma. Renal cell carcinoma includes acquired cystic paranephropathy-associated renal cell carcinoma, clear cell renal cell carcinoma, clear cell papillary renal cell carcinoma, papillary renal cell carcinoma, chromophobe renal cell carcinoma, etc., and the biomarker of the present embodiment is highly effective in detecting renal cancer occurring in dialysis kidneys (dialysis kidney carcinoma), particularly acquired cystic paranephropathy-associated renal cell carcinoma (ACD-RCC). ACD-RCC is the most common type of renal cancer in dialysis kidneys (36%), and it has been reported that the incidence of ACD-RCC increases with the number of years of dialysis. ACD-RCC, which occurs frequently among dialysis kidney carcinomas, is difficult to diagnose with imaging, and therefore the biomarker of the present embodiment is highly useful when the renal cell carcinoma is dialysis kidney carcinoma or when the renal cell carcinoma is ACD-RCC. Therefore, the renal cell carcinoma is preferably dialysis renal carcinoma, and more preferably ACD-RCC. On the other hand, normal renal tissue means renal tissue that does not contain lesions. In one embodiment, normal renal tissue means kidney tissue that does not contain lesions caused by renal cell carcinoma (including cystic epithelium that is thought to be a precancerous lesion).

[0013] The kidneys contain approximately 2 million nephrons, functional units responsible for plasma filtration and reabsorption. Nephrons consist of the renal corpuscle (glomerulus and Bowman's capsule), which is responsible for filtration, and the renal tubule, which is responsible for reabsorption. The glomerular capillary loop wall is composed of the glomerular basement membrane (GBM), podocytes, which cover the outside of the GBM (urinary cavity side), and glomerular endothelial cells, which cover the inside of the basement membrane. Mesangial cells support the capillary loop. Afferent and efferent arterioles enter and exit the vascular pole, where parietal epithelial cells of Bowman's capsule and podocytes migrate to each other. The juxtaglomerular apparatus at the vascular pole is composed of distal tubular epithelial cells that form the macula densa, extraglomerular mesangial cells, smooth muscle cells of the afferent arteriole, juxtaglomerular cells, and smooth muscle cells of the efferent arteriole. Blood leaving the superficial cortical glomerulus enters the peritubular capillaries that accompany the cortical tubule, while blood leaving the deep cortical glomerulus enters the vasa recta, which travels deep into the medulla. The arcuate artery and vein, interlobar artery and vein, and renal artery and vein are responsible for the inflow and return of blood. From the pole of the renal tubule, where Bowman's capsule transitions into the tubule, the renal tubule is composed of the proximal convoluted tubule, the loop of Henle (proximal straight tubule, thin descending limb, thin ascending limb, distal straight tubule), the distal convoluted tubule, the connecting tubule, the cortical collecting duct, and the medullary collecting duct. Renal cells refer to the cells that make up the kidney, including the cells that make up the renal tubules (including collecting duct cells), the cells of the glomerulus, the parietal epithelial cells of Bowman's capsule, fibroblasts and dendritic cells present in the interstitium, infiltrating inflammatory cells, vascular cells of the blood and lymphatic vessels, and neurons. Renal tubular cells (or renal tubular epithelial cells) include cells that form the lumen from the proximal tubule to the loop of Henle, distal tubule, collecting duct, and renal papilla. Renal tissue-derived glycoproteins refer to proteins that are expressed in renal tissue and have a sugar chain, and renal tubular epithelial cell-derived glycoproteins refer to proteins that are expressed in renal tubular epithelial cells and have a sugar chain.

[0014] In renal tubular epithelial cells, which are considered to be the base of renal cell carcinoma, sialic acid modification of the sugar chains of their glycoproteins is suppressed. On the other hand, glycoproteins with sialic acid-modified sugar chains are observed in cancerous or cystic renal tubular epithelial cells. Furthermore, based on the results of tissue staining and other methods, glycoproteins with sialic acid-modified sugar chains may be localized to proximal tubules, where sialylation is suppressed. Therefore, glycoproteins derived from renal tissue with sialylated sugar chains can be used as diagnostic biomarkers specific to renal cell carcinoma. Furthermore, renal cell carcinoma markers can be searched for by examining changes in the sugar chain structure of glycoproteins derived from renal tissue.

[0015] Among kidney cells, examples of sugar chain structures that are suppressed in, for example, the proximal tubule include sugar chain structures modified with sialic acid (sialylated). Sialylation (sialic acid modification) means that in N-linked sugar chains, sialic acid is bound to the 6th or 3rd position of the non-reducing terminal galactose, and in O-linked sugar chains, sialic acid is bound to the 6th position of N-acetylgalactosamine, the 3rd position of the non-reducing terminal galactose of Core 1 (T), or the 3rd or 6th position of the non-reducing terminal galactose on the extended chain side of Core 2. Sialic acid is a modified form of neuraminic acid that consists of nine carbon atoms and has an amino group and a carboxylic acid, and representative examples include N-acetylneuraminic acid (Neu5Ac), N-glycolylneuraminic acid (Neu5Gc), and deaminoneuraminic acid (Kdn). Generally, sialic acid is present at the sugar chain terminal (non-reducing terminal) of N-linked sugar chains, O-linked sugar chains, glycolipids, etc., and is involved in various biological reactions.

[0016] Specific examples of glycoproteins derived from kidney tissues that have sialylated sugar chains that are increased during carcinogenesis include ITGA3 (Integrin alpha-3), TINAGL1 (Tubulointerstitial nephritis antigen-like), 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 PLD3), APMAP (Adipocyte plasma membrane glycoprotein 2), LAMP2 (Lysosome-associated membrane glycoprotein 2), INSR (Insulin receptor), and 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), 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 type1), BTN3A1 (Butyrophilin subfamily 3 member A1), FBN1 (Fibrillin-1), HLA-A (HLA class I histocompatibility antigen, A-2 alpha chian), CUBN (Cubilin), ENPEP (Glutamyl aminopeptidase), LAMP1 (Lisosome-associated membrane glycoprotein) 1), ANPEP (Aminopeptidase N), MME (Neprilysin, CD10), HLA-DPB1 (HLA class II histocompatibility antigen, 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 constant Examples of glycoproteins include THBS1 (Thrombospondin-1), THBS1 (Thrombospondin-1), and THBS1 (Thrombospondin-1). These glycoproteins are also expressed in normal tissues, including renal tubular epithelium, and can be used as biomarkers for detecting renal cell carcinoma due to differences in their glycosylation. One or more combinations selected from the group consisting of these glycoproteins can be used as biomarkers for detecting renal cell carcinoma. One embodiment of the present invention relates to a combination of two or more glycoproteins selected from the group consisting of these cell surface glycoproteins. These combinations can be used to detect renal cell carcinoma. In one embodiment, the renal tissue-derived glycoprotein having a sialylated glycan that is increased with carcinogenesis is one or more proteins selected from the group consisting of GPNMB, Megalin, ACE2, and MME.GPNMB is a transmembrane glycoprotein involved in various cellular processes, including cell adhesion, migration, and immune response regulation. Its possible involvement in tumor tissues in delaying cell proliferation and regulating metastatic potential has been suggested. 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 known for its role in the renal tubule, where it functions in the reabsorption of proteins from the glomerular filtrate. This process is crucial for maintaining the balance of proteins 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 intestine, where it is involved in various physiological functions. ACE2 is a membrane protein that plays an important role in the renin-angiotensin-aldosterone system (RAAS), a hormonal system that regulates blood pressure and fluid balance. ACE2 catalyzes the cleavage of angiotensin I to angiotensin 1-9 and angiotensin II to angiotensin 1-7, which have vasodilatory properties. ACE2 is known to be expressed in various human organs, and its organ- and cell-specific expression suggests its possible involvement in regulating the cardiovascular system, renal function, and reproductive function. Furthermore, it is the functional receptor for the spike glycoproteins of the human coronavirus HCoV-NL63 and the human severe acute respiratory syndrome coronaviruses SARS-CoV and SARS-CoV-2, the latter of which is the causative agent of coronavirus disease 2019 (COVID-19). MME functions as a neutral endopeptidase in type II transmembrane glycoproteins. It cleaves peptides at the amino side of hydrophobic residues, inactivating several peptide hormones, including glucagon, enkephalins, substance P, neurotensin, oxytocin, and bradykinin. It is a common acute lymphoblastic leukemia antigen that is an important cell surface marker in the diagnosis of human acute lymphoblastic leukemia (ALL), and is present on leukemic cells of the pre-B phenotype, which accounts for 85% of ALL cases.One or a combination of two or more selected from the group consisting of these cell surface glycoproteins can be used as a biomarker for detecting renal cell carcinoma. One embodiment of the present invention relates to a combination of two or more glycoproteins selected from the group consisting of GPNMB, megalin, ACE2, and MME, which have a sialylated glycan structure that is enhanced with carcinogenesis. 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, megalin and ACE2, GPNMB, megalin and MME, GPNMB, ACE2 and MME, megalin, ACE2 and MME, GPNMB, megalin, ACE2 and MME, and the like. The accuracy of diagnosis can be further improved by detecting a combination of two or more selected from the group consisting of these cell surface glycoproteins.

[0017] In one embodiment, the biomarker can be used as a serum diagnostic marker or tissue diagnostic marker to detect renal cell carcinoma or its precancerous lesion, cystic transformation. Note that the marker can be used in either a single test system or a multiplex test system, and the cutoff value can be set depending on the application.

[0018] The biomarker of this embodiment has the excellent effect of enabling the detection of renal cell carcinoma easily and with high specificity by testing not only tissues but also blood such as serum. Furthermore, the biomarker of this embodiment enables the identification of different histological types of renal cell carcinoma, regardless of whether the patient is on dialysis or not, and the pathology of ACKD (cystic kidney disease), which is considered a precancerous lesion in dialysis patients, by performing comparative glycosylation analysis. Furthermore, compared to existing renal cell carcinoma markers, the biomarker of this embodiment has a high diagnostic accuracy because it measures both protein sites and glycosylation sites, and can evaluate the therapeutic effect and recurrence of renal cell carcinoma using a monitoring technique that allows testing with a small amount of serum.

[0019] The biomarker of this embodiment may be the presence or absence of a glycoprotein derived from renal tissue having a sialylated sugar chain that is increased with carcinogenesis, or the quantitative level thereof. That is, in this embodiment, the presence or absence or quantitative level of a renal cell glycoprotein having a sugar chain structure not present in normal renal tissue can be used to detect renal cell carcinoma. The quantitative level may be the absolute value of the amount of a glycoprotein having a sialylated sugar chain that is increased with carcinogenesis, or a relative value relative to any comparator.

[0020] [Detection Method] In one embodiment of the present invention, a biomarker detection method comprises in vitro detection of a biomarker, including a renal tissue-derived glycoprotein having a sialylated glycan that is increased with carcinogenesis, in a sample (test sample) obtained from a subject. Detection can be performed as appropriate according to methods well known to those skilled in the art, as long as it can detect any of the renal tissue-derived glycoproteins having a sialylated glycan that is increased with carcinogenesis described above in [Biomarker]. For example, lectin array analysis, ELISA analysis, and immunohistochemical staining can be applied. In particular, the sandwich method described below is preferably applied. In the sandwich method, a substance that specifically binds to the protein portion of the glycoprotein is preferably used together with a lectin, and an antibody is preferably used as the substance that binds to such a protein portion. Specifically, an antibody that binds to a glycoprotein of renal tubular epithelial cells is immobilized on a support. The test sample is then overlaid to form a complex between the target protein and the antibody. A labeled antibody or lectin is then added to form a further complex. The target protein can be detected by detecting the formed complex. As another method, instead of immobilizing an antibody on a support, multiple lectins, including lectins, can be immobilized on a support and then the overlaid test sample can be subjected to detection by reacting a labeled antibody with the immobilized lectin. This detection may be performed for two or more types of biomarkers. When immunohistochemical staining is used, two or more types of biomarkers can also be detected simultaneously. Specifically, tissue sections are prepared and subjected to multiple staining using specific antibodies for each biomarker, each labeled with a different dye, or by using specific antibodies for each biomarker and labeled secondary antibodies for each specific antibody, thereby simultaneously staining and detecting the respective biomarkers.

[0021] The detection of the biomarker may include measuring the presence or absence of a glycoprotein derived from kidney tissue having a sialylated sugar chain structure that is increased in the above-mentioned cancerous transformation, or measuring the level thereof.

[0022] In this embodiment, the term "subject" refers to a person who is subjected to testing, i.e., a person who provides a test sample. The subject may be a mammal or other animal. The mammal may be a human or a non-human animal. Non-human animal species may be, for example, monkeys, dogs, cats, horses, cows, pigs, sheep, goats, rabbits, guinea pigs, hamsters, mice, and / or rats. While not limited by their intended use as livestock, pets, or laboratory animals, mammals are preferred, and humans are more preferred. The subject may also be either a patient with a disease or a healthy individual. Preferably, the subject is a person who may be suffering from renal cell carcinoma or a renal cell carcinoma patient. The subject may also be a person who may be suffering from or has a disease other than renal cell carcinoma. The biomarker detected by the detection method of this embodiment is highly effective in detecting renal cancer occurring in dialysis-treated kidneys (dialysis-treated renal cancer), particularly in detecting acquired cystic kidney-associated renal cell carcinoma (ACD-RCC). ACD-RCC is a common type of dialysis-associated renal cancer (36%), and it has been reported that the incidence of ACD-RCC increases with the number of years of dialysis, but imaging diagnosis is difficult. Therefore, the detection method of this embodiment is highly useful when the subject is a dialysis patient, and therefore the subject is preferably a dialysis patient. It is known that the risk of developing ACD-RCC increases with the length of dialysis. Therefore, for example, dialysis patients may be monitored by periodically performing the detection method of this embodiment.

[0023] The test sample may be a tissue fragment of a portion of renal tissue collected from a subject during biopsy or surgery, or a tissue fragment derived from a lesion of renal tissue. It may also be a body cavity fluid such as ascites, or cells collected from urine. The subject is not particularly limited, and the determination of whether or not a person has renal cell carcinoma can be widely applied to those who need it. Body fluids such as blood, lymph, cerebrospinal fluid, bile, urine, saliva, and body cavity fluid from the subject can be used. Preferably, serum obtained by separating blood collected from the subject is used as the test sample, as this reduces the burden on the subject and shortens the testing time. The test fluid may be used immediately after collection, or it may be stored for a certain period of time by freezing or refrigeration, and then thawed or otherwise processed as necessary before use. In this embodiment, when serum is used, a sufficient amount of biomarker 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.

[0024] [Renal cell carcinoma diagnostic kit] In one embodiment of the present invention, the renal cell carcinoma diagnostic kit is a renal cell carcinoma diagnostic kit comprising a means for detecting a biomarker comprising a renal tissue-derived glycoprotein having a sialylated sugar chain that is increased with carcinogenesis. The detection means may include a lectin that binds to a renal tissue-derived glycoprotein having a sialylated sugar chain that is increased with carcinogenesis, and / or an antibody that binds to a renal cell glycoprotein having a sialylated sugar chain that is increased with carcinogenesis.

[0025] (1) Lectins that recognize biomarkers 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 this embodiment. For example, Lotus tetragonolobus lectin (LTL), Pisum sativum agglutinin (PSA), Lens culinaris agglutinin (LCA), Ulex europaeus agglutinin-I (UEA-I), Aspergillus oryzae lectin (AOL), Aleuria aurantia lectin (AAL), Maackia amurensis lectin (MAL-I), Sambucus nigra agglutinin (SNA), Sambucus sieboldiana agglutinin (SSA), Trichosanthes japonica agglutinin-I (TJA-I), Phaseolus vulgaris leukoagglutinin (PHA-L), Erythrina cristagalli agglutinin (ECA), Ricinus communis agglutinin (RCA120), Phaseolus vulgaris erythroagglutinin (PHA-E), Datura stramonium agglutinin (DSA), Griffonia simplicifolia lectin-II (GSL-II), Narcissus pseudonarcissus agglutinin (NPA), Concanavalin A (ConA), Galanthus nivalis agglutinin (GNA), Hippeastrum hybrid lectin (HHL), Agrocybe cylindracea galectin (ACG), Tulipa gesneriana agglutinin (TxLC-I), Bauhinia purpurea alba lectin (BPL), Trichosanthes japonica agglutinin-II (TJA-II), Euonymus europaeus lectin (EEL), Agaricus bisporus agglutinin (ABA),Lycopersicon esculentum lectin (LEL), Solanum tuberosum lectin (STL), Urtica dioica agglutinin (UDA), Poakweed mitogen (PWM), Jacalin, Peanut agglutinin (PNA), Wisteria floribunda agglutinin (WFA), Amaranthus caudatus agglutinin (ACA), Maclura pomifera agglutinin (MPA), Helix pomatia agglutinin (HPA), Vicia villosa agglutinin (VVA), Dolichos biflorus agglutinin (DBA), Soybean agglutinin (SBA), Calsepa, Psophocarpus tetragonolobus lectin-I (PTL-I), Maackia amurensis hemagglutinin (MAH), Wheat germ agglutinin (WGA), Griffonia simplicifolia lectin-I A4 (GSL-I A4), Griffonia simplicifolia lectin-I Examples of lectins include B4 (GSL-I B4). In particular, MAL-I, SNA, SSA, TJA-I, MAH, and WGA can be preferably used. Information on other lectins is available from the Lectin Frontier Database (LfDB) and the like. The lectins used in this embodiment may be naturally derived, or may be recombinant lectins produced by recombinant technology from prokaryotic or eukaryotic hosts (including, for example, bacterial cells, yeast cells, higher plant cells, insect cells, and mammalian cells). Furthermore, lectins may be fragments as long as they maintain their binding ability.

[0026] (2) Antibodies that bind to renal cell glycoproteins with sialylated sugar chain structures that are increased with carcinogenesis The antibodies included in the renal cell carcinoma diagnostic kit are not particularly limited as long as they bind to a protein region of a renal cell glycoprotein with sialylated sugar chains that are increased with carcinogenesis, or to a region containing a sugar chain. The antibodies may be polyclonal antibodies, but monoclonal antibodies are preferred, and may also be antibody fragments such as Fab, as long as their antigen-binding activity is not impaired. For example, anti-GPNMB antibodies, anti-Megalin antibodies, anti-ACE2 antibodies, anti-MME antibodies, or combinations thereof may be used.

[0027] In detecting a biomarker, it is preferable to use a lectin in combination with an antibody that specifically binds to the protein portion of a glycoprotein. In one embodiment, the renal cell carcinoma diagnostic kit is a kit comprising the following (1) and (2), in which either (1) or (2) is immobilized on a support and the other is labeled: (1) a lectin that recognizes a glycoprotein derived from kidney tissue that has a sialylated sugar chain that is increased with carcinogenesis, and (2) an antibody that binds to at least one glycoprotein selected from GPNMB, Megalin, ACE2, and MME.

[0028] Antibodies specific to glycoproteins derived from renal tissues that have sialylated glycans that are enhanced by carcinogenesis can be produced by standard methods using the glycoprotein as a biomarker as an antigen. Furthermore, specific antibodies that simultaneously recognize the glycans and protein portions of the glycoprotein can also be produced using the CasMab method (CasMab: Kato Y et al., Sci Rep. 2014 Aug 1; 4: 5924. doi: 10.1038 / srep05924). While such antibodies can be used alone extremely effectively for detecting renal cell carcinoma markers and diagnosing renal cell carcinoma, accuracy can be further improved by using them in combination with antibodies that specifically bind to the glycan portion or the protein portion.

[0029] [Diagnostic Method] A diagnostic method according to one embodiment of the present invention is a method for diagnosing renal cell carcinoma, comprising detecting a biomarker comprising a glycoprotein derived from renal tissue having a sialylated sugar chain that is increased with carcinogenesis in a subject. In one embodiment, the diagnostic method may comprise a step of determining the possibility that the subject is affected with renal cell carcinoma based on the detected biomarker of the subject.

[0030] A data collection method according to one embodiment of the present invention is a method for collecting data for diagnosing renal cell carcinoma, comprising detecting a biomarker comprising a glycoprotein derived from renal tissue having a sialylated sugar chain that is increased with carcinogenesis in a subject. Renal cell carcinoma can be diagnosed in a subject based on data collected by the data collection method. That is, a method for diagnosing renal cell carcinoma in a subject according to one embodiment comprises the data collection method.

[0031] The biomarker detection method can be the same as the detection method described above. By detecting a biomarker containing a glycoprotein derived from kidney tissue that has a sialylated sugar chain that is increased with carcinogenesis, renal cell carcinoma can be diagnosed with higher accuracy than conventional methods.

[0032] In one embodiment, the method for diagnosing renal cell carcinoma in a subject or the method for collecting data may include, before performing any of the detection methods described in the above [Detection Method] on the subject, performing the biomarker detection method in one or more renal cell carcinoma patients according to the above [Detection Method], and obtaining reference values ​​for the biomarkers based on the levels of the biomarkers in the renal cell carcinoma patients. In another embodiment, the method for diagnosing renal cell carcinoma in a subject or the method for collecting data may include, before performing any of the detection methods described in the above [Detection Method] of this embodiment on the subject, performing the biomarker detection method in one or more renal cell carcinoma patients and one or more healthy subjects according to the above [Detection Method] of this embodiment, and obtaining reference values ​​for the biomarkers in renal cell carcinoma patients and reference values ​​(normal values) for the biomarkers in healthy subjects. According to these methods, if the biomarkers in the subject are the same as the reference values ​​for the biomarkers in renal cell carcinoma patients, the subject may be determined to have renal cell carcinoma or may be determined to have a high likelihood of having renal cell carcinoma based on the data. Alternatively, if the subject's biomarker differs from the reference value of the biomarker in renal cell carcinoma patients, the subject may be determined to be free of renal cell carcinoma or to have a low likelihood of being affected by renal cell carcinoma based on the data. Furthermore, if the subject's biomarker differs from the normal value, the subject may be determined to be affected by renal cell carcinoma or to have a high likelihood of being affected by renal cell carcinoma based on the data. Alternatively, if the subject's biomarker is the same as the normal value, the subject may be determined to be free of renal cell carcinoma or to have a low likelihood of being affected by renal cell carcinoma based on the data. In one embodiment, if the subject's biomarker is elevated compared to the normal value, the subject may be determined to be affected by renal cell carcinoma or to have a high likelihood of being affected by renal cell carcinoma based on the data.

[0033] In another embodiment, a method for diagnosing renal cell carcinoma in a subject or a method for collecting data may include performing any of the detection methods described in the above "Detection Method" of this embodiment on the same subject. According to this method, if a subject's biomarker shows a change at a certain time point compared to a previous time point, the subject may be determined to have renal cell carcinoma or may be determined to have a high probability of having renal cell carcinoma based on the data. For example, this method can be used to monitor the subject's renal cell carcinoma development through regular monitoring. In one embodiment, if a subject's biomarker shows an increase at a certain time point compared to a previous time point, the subject may be determined to have renal cell carcinoma or may be determined to have a high probability of having renal cell carcinoma based on the data. This is because the expression of biomarkers in samples obtained from renal cell carcinoma patients tends to be higher than in samples obtained from healthy individuals.

[0034] Here, the reference value or normal value may be the average or median value of a biomarker measured over time in subjects of the same group or the same subject, or a reference range or normal range arbitrarily established based on the measured values ​​of the biomarker. Alternatively, the reference value or normal value may be a value that can determine the presence of renal cell carcinoma in a subject with the desired sensitivity and / or specificity based on biomarkers measured over time in subjects of the same group or the same subject, as appropriate, determined by a person skilled in the art. Furthermore, a biomarker in a subject being the same as the reference value or normal value may mean, for example, that there is no significant difference from the reference value or normal value as determined by any statistical processing. A biomarker in a subject being different from the reference value or normal value may mean, for example, that there is a significant difference from the reference value or normal value as determined by any statistical processing. A biomarker in a subject being elevated compared to the reference value means, for example, that the level of the biomarker in a sample obtained from the subject is significantly elevated compared to the reference value as determined by any statistical processing. A statistical processing method can be appropriately selected by a person skilled in the art according to well-known methods.

[0035] In one embodiment, the diagnostic method or data collection method described above can be performed in combination with other methods of collecting data for diagnosing renal cell carcinoma or other methods of diagnosing renal cell carcinoma, such as dynamic CT, MRI, abdominal ultrasound, etc.

[0036] [Pharmaceutical Composition] In one embodiment of the present invention, a pharmaceutical composition for treating renal cell carcinoma contains 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 biomarkers containing renal tissue-derived glycoproteins with sialylated glycans that are elevated in carcinogenesis, conjugates of such antibodies with drugs, and naturally occurring or synthetic small to medium-molecular chemicals. The active ingredient may be incorporated into a known vector capable of kidney-specific delivery. Liposome delivery methods, such as pH-sensitive liposomes that enable endoplasmic reticulum-specific delivery, are also preferred. The following description will primarily focus on formulations of antibodies or proteins, as well as specific administration methods and dosages. The route of administration may be oral or parenteral. Parenteral administration is preferably subcutaneous or intravenous injection. Administration via nasal sprays or other nasal routes, transdermal administration, inhalation, suppositories, and other routes may also be used. The antibody or protein may be administered to a patient by intravenous injection, subcutaneous injection, oral delivery, liposome delivery, or intranasal delivery, and then accumulate in the patient's systemic system, kidney, or renal cells. "Pharmaceutically acceptable carriers and / or excipients" are known to those skilled in the art and include any type of non-toxic solid, semi-solid, or liquid filler, diluent, encapsulating material, or formulation auxiliary, such as liposomes. One embodiment of the present invention relates to a method for treating renal cell carcinoma, comprising administering the pharmaceutical composition described above. 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 with sialylated sugar chains that is increased in cancerous transformation, in the manufacture of a medicament for treating renal cell carcinoma.

[0037] 1. Acquisition of New Biomarkers 1-1. Biomarkers for Diagnosing Renal Cell Carcinoma The composition and structural diversity of glycans on proteins secreted by cells is controlled by the expression balance of hundreds of glycan-related genes and fluctuates depending on the degree of cell differentiation and cancer progression. Glycoproteins with changing glycan structures can be used as tumor markers. Therefore, glycoproteomics is being used as a platform for the search for glycan-related tumor markers. In a proteomics-based marker discovery pipeline, candidate molecules are identified through large-scale analysis in Phase 1. Candidate molecules are verified and narrowed down through quantitative analysis in Phase 2. Further validation testing is conducted in Phase 3. Glycoproteomics-based glycan-related marker discovery is also based on the above pipeline. Using specimens or cancer cell lines from renal cell carcinoma patients and specimens from healthy individuals, glycopeptides specifically identified in the former by the lectin-catch IGOT method can be used as candidate markers for renal cell carcinoma. These glycopeptides can be validated using comparative glycopeptide glycan analysis techniques, including comparative glycoproteomics of stable isotope-introduced glycopeptides, to identify marker glycopeptides that are highly likely to be useful. Furthermore, glycoproteins containing the candidate glycopeptide sequences can be validated using comparative glycopeptide analysis techniques, including antibody overlay and lectin microarray techniques, to identify biomarkers that are highly likely to be useful.

[0038] 1-2. Biomarker Acquisition Methods 1-2-1. Large-Scale Identification of Glycoproteins Large-scale selective collection and enrichment of glycopeptides can be broadly divided into methods using probes with affinity for glycans, (ii) methods utilizing chemical reactions with glycans (Zhang H. et al., Nat Biotechnol 21, 660-666 (2003)), and (iii) methods incorporating affinity tags into glycans. Probes are preferred. Probe-based methods are described in detail below. (1) Probe-based collection: Lectins or anti-glycan antibodies can be used as probes. Specifically, glycoproteins are first collected from the culture supernatant of a renal cell carcinoma-derived cell line using a probe lectin or antibody probe. Next, glycoproteins are collected from the serum of healthy individuals using the probe lectin or antibody probe, while comprehensive collection of glycoproteins is performed using lectins other than the probe lectin. (2) Probe lectins can be selected primarily through statistical analysis of glycoprotein profiles using the lectin microarray described above. Probes can also be selected based on the expression profile of glycogenes (results of real-time quantitative PCR) and literature information (some of which can predict the appropriate probe lectin). Basically, selection is based on statistical analysis of the profile, and the appropriateness of the selection is determined based on the binding specificity of the selected lectin. Antibody probes can be prepared after clarifying the structure of the antigen (glycan), but this is not a requirement; they can also be prepared without knowing the structure of the antigen glycan (or glycopeptide). (3) The lectin used for comprehensive collection, when narrowing down biomarkers, varies depending on the distribution of glycan structures in the control sample. For example, when using serum as a control, it has been found that most glycans on serum glycoproteins are sialylated biantennary glycans. Therefore, RCA120, a lectin derived from castor bean (Ricinus communis), can be used because it is believed that most serum glycoproteins (peptides) can be comprehensively collected by sialidase treatment. The reason why sialic acid-recognizing lectins are not used is to avoid the influence of artificial manipulation and elimination of sialic acid due to deterioration of the sample over time.If the control sample is not serum, for example, if it is another body fluid, a different lectin can be selected. Alternatively, comprehensive collection can be performed without using a lectin, using hydrophilic interaction chromatography or gel filtration.

[0039] 1-2-2. Identification of Glycopeptides or Glycoproteins The captured glycoproteins can be analyzed for candidate glycopeptides using the Lec-IGOT-LC / MS method described in, for example, JP 2004-233303 A (Patent No. 4220257) or Nature Protocols 1, 3019-3027 (2006). (1) Glycosylation and Stable Isotope Labeling at the Glycosylation Position The sample glycopeptide group is recaptured with the same probe from the peptide group obtained by protease digestion of the glycoprotein group captured with the probe. Alternatively, the sample crude protein mixture can be directly captured with the probe from the crude peptide group obtained by protease digestion without separating it. The resulting glycopeptide group is treated with an enzyme such as glycopeptidase in isotope-labeled water to dissociate the glycans. As a result, asparagine at the glycan-binding site becomes aspartic acid, and at this time, the isotope oxygen ( １８O) is incorporated into peptides. Labeling the glycan binding site with an isotope in this manner is called isotope-coded glycosylation site-specific tagging (IGOT). (2) LC / MS shotgun analysis of labeled peptides: IGOT-labeled peptides are separated by LC and introduced into MS, and the peptide sequences are comprehensively identified by tandem mass spectrometry. (3) Peptide identification: For example, using the MS / MS ion search method described in Section 3-6-2-2 Amino Acid Sequence Analysis of the Standard Technology Collection (edited by the Japan Patent Office), MS / MS peptide measurement results of the obtained peptide mixture can be compared with MS / MS spectra registered in a database for search. The search takes into account the following amino acid modifications: oxidation of the side chain of methionine residues, pyrolysis (deamidation, cyclization) of amino-terminal glutamine, deamination of the amino terminus (carbamidomethylcysteine), and deamidation of the side chain of asparagine residues (where stable oxygen isotope incorporation occurs). (4) Identification of Glycosylation Sites Among peptides identified by the MS / MS ion search method, peptides in which deamidation (stable isotope incorporation) has occurred in the side chain of an asparagine residue and which contain a consensus sequence for N-linked glycosylation (Asn-Xaa-[Ser / Thr], where Xaa is not Pro) are designated as candidate glycopeptides (if Xaa is Lys / Arg and the identified peptide sequence is cleaved at this position, the amino acid sequence of the entire protein is referenced, and if it is confirmed that the residue following Xaa is [Ser / Thr], this peptide is also included). The asparagine residue in the consensus sequence of this glycopeptide is designated as the glycosylation site. If there are multiple consensus sequences, the number of deamidated (labeled) asparagine residues is smaller than the consensus sequence, and the labeling site cannot be identified from the MS / MS spectrum, the labeling sites (glycosylation sites) are listed together, and a statement that they cannot be distinguished is noted.

[0040] 1-2-3. Narrowing Down Candidate Glycopeptides for Renal Cell Carcinoma Diagnostic Markers Candidate glycopeptides for renal cell carcinoma diagnostic markers can be identified by laser microdissection of tissue from cancer-specific regions 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 be used as initial candidates for the glycosylation marker. The approximate amount of glycopeptide or its change can be estimated by comparing the signal intensities of the labeled peptides in LC / MS analysis. The candidate glycopeptides narrowed down in this way can be used as diagnostic biomarkers for renal cell carcinoma targeting various pathological conditions after validation experiments. Furthermore, glycoproteins containing the peptide sequences can also be used as diagnostic biomarkers for renal cell carcinoma after validation experiments in the protein state.

[0041] Validation of candidate biomarkers for diagnosing renal cell carcinoma Validation of candidate biomarkers for diagnosing renal cell carcinoma can be carried out based on the following: i) comparison of the signal intensities of each labeled peptide when glycopeptides captured with a probe lectin from a cancer-specific region of renal cell carcinoma are labeled with IGOT and analyzed by LC / MS; ii) known comparative quantitative proteomics using stable isotopes for glycoproteins captured with a probe lectin from a cancer-specific region of renal cell carcinoma; iii) antibody-based quantitative detection of glycoproteins containing the sequences of glycopeptides captured with a probe lectin from a cancer-specific region of renal cell carcinoma; and iv) comparative glycochain profiling using antibody overlay / lectin microarrays or the like for glycoproteins containing the sequences of glycopeptides captured from a cancer-specific region of renal cell carcinoma. More specifically, i) glycopeptides collected with a probe lectin from cancer-specific regions of renal cell carcinoma in renal cell carcinoma patients are labeled with IGOT and analyzed by LC / MS, and the signal intensities of each labeled peptide are compared: the above sample (serum) proteins are each reductively alkylated and then digested with trypsin. The resulting peptide mixture is subjected to affinity chromatography using the probe lectin to collect glycopeptides. These are then labeled using the above-mentioned IGOT method, and the approximate total amounts are combined and individually analyzed by LC / MS. Using the mass-to-charge ratio and elution position of the identified glycopeptides as a reference, spectra of the labeled peptides are obtained, and their signal intensities are compared. ii) Comparative quantitative proteomics using stable isotopes for glycoproteins captured with a probe lectin from cancer-specific regions of renal cell carcinoma: Glycoproteins captured with a probe lectin from the serum sample were reductively alkylated and then digested with trypsin. The resulting peptides were differentially labeled with stable isotopes (guanidination of the Lys side chain amino group using 13C / 15N-doubly labeled methylisourea) and analyzed by LC / MS. The spectra of each identified peptide were analyzed, and the variation between samples could be quantitatively estimated by comparing signal intensities. The significance of each marker candidate for each pathology could be confirmed and narrowed down based on the quantitative variation of proteins with cancerous glycans.iii) Immunological quantitative detection of target glycoproteins (glycoproteins containing the glycopeptide sequences described in 1-2-4) for glycoproteins captured with a probe lectin from cancer-specific regions of renal cell carcinoma: Glycoproteins captured with the probe lectin from the serum sample are subjected to, for example, SDS-PAGE, and then immunologically detected by Western blotting after membrane transfer. By comparing the signal intensities of the resulting bands, the variation between samples can be quantitatively estimated. The significance of each candidate marker can be confirmed and narrowed down based on the quantitative variation of proteins with cancerous glycans. iv) Comparative glycosylation profiling using antibody-overlay lectin microarrays, etc., 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. From the collected samples, candidate biomarker glycoproteins for diagnosing renal cell carcinoma are enriched and purified by antibody-based immunoprecipitation, and candidate biomarkers for diagnosing renal cell carcinoma can be selected using antibody-overlay lectin arrays. As the lectin microarray, a lectin microarray in which multiple lectins are immobilized can be used, and more specifically, the lectin microarray described in Kuno A. et al., Nat. Methods 2, 851-856 (2005) or LecChip manufactured by GP Biosciences can be used. In this way, the glycan structures of glycopeptides or glycoproteins can be comprehensively analyzed, and the presence or absence of changes in glycan structure between samples can be analyzed, and those that show changes can be used as biomarkers for diagnosing renal cell carcinoma.

[0042] 2. Detection of Renal Cell Carcinoma Diagnostic Biomarker Glycoproteins 2-1. Protein Detection Various known proteomics techniques can be used to detect glycosylation marker glycoproteins. For example, collected proteins can be separated using one- or two-dimensional gel electrophoresis, and the detection intensity (staining, fluorescence, etc.) of target spots can be compared with a standard sample for quantification. A mass spectrometer-based detection method involves digesting collected proteins with proteases and analyzing and detecting the resulting peptides using LC / MS. Quantification can be achieved using a variety of methods utilizing stable isotope labeling (e.g., ICAT, MCAT, iTRAQ, SILAC) and simple, label-free quantification methods (e.g., peptide counting, area integration, etc.). Furthermore, as described below, ELISA can also be used for quantification.

[0043] 2-2. Lectin Microarray 2-2-1. Glycosylation Profiling Using Lectin Microarray (1) Lectin Microarray Lectin microarrays are arrays of multiple discriminant (probe) lectins with different specificities immobilized in parallel on a single substrate, enabling simultaneous analysis of the extent to which each lectin interacts with a target glycoconjugate. Using a lectin array, the information necessary for estimating glycan structure can be obtained in a single analysis, and the process from sample preparation to scanning is quick and simple. Glycosylation profiling systems such as mass spectrometry cannot analyze glycoproteins directly; they must first be processed into glycopeptides or free glycans. In contrast, lectin microarrays have the advantage that they can be analyzed directly by simply introducing a fluorophore 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). Laser microdissection of renal cell carcinoma cancer-specific regions allows for analysis of glycosylation in renal cell carcinoma-specific regions, compared to bulk specimen analysis. Lectin microarrays enable highly sensitive comparative glycosylation analysis, enabling sufficient analysis with protein preparation amounts of approximately 10–100 nanograms. They can also be applied to samples enriched by immunoprecipitation using specific antibodies against candidate molecules (core proteins) extracted by mass spectrometry (antibody overlay lectin microarray method). In this case, the amount of protein applied is on the order of a few nanograms to a few tens of nanograms, and statistical analysis of the resulting signal values ​​(Student's t-test) allows for the selection of lectins that show significant differences. This makes it possible to simultaneously list antibodies and lectins that recognize specific glycoproteins. For example, a lectin array (LecChip, manufactured by GP Biosciences) with 45 types of lectins immobilized on a substrate is already commercially available as a lectin array.(2) Statistical analysis of glycan profiles using lectin arrays Lectin arrays have now become a practical technology that allows quantitative comparative glycan profiling of not only purified samples but also mixed samples such as serum and cell lysates. In particular, comparative glycan profiling of cell surface glycans has made remarkable progress (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)). Furthermore, data mining by statistical analysis of glycan profiles can be performed, for example, by the method 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)." (3) Antibody Overlay Lectin Microarray Method The lectin microarray platform is basically as described above, and for detection, the analyte is not directly labeled with fluorescence or the like, but rather a fluorescent group or the like is indirectly introduced into the analyte via an antibody, thereby simplifying and speeding up the simultaneous analysis of multiple analytes (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)). For example, if a glycoprotein is the target, the glycan portion is recognized by a lectin on the lectin microarray, and by overlaying an antibody against the core protein portion on top of it, the glycoprotein can be detected specifically and with high sensitivity without labeling or highly purifying the target glycoprotein.(4) Lectin overlay / antibody microarray method This method uses an antibody microarray in which antibodies against core proteins are immobilized (arrayed) in parallel on a substrate such as a glass substrate instead of a lectin microarray. The number of antibodies required is equal to the number of markers to be investigated. It is necessary to determine in advance the lectin that will detect changes in glycans.

[0044] 2-3. Lectin-Antibody Sandwich Immunological Detection Based on the results of lectin arrays, a simple and inexpensive sandwich detection method can be designed. Essentially, the protocol for sandwich detection using two antibodies can be applied by simply replacing one of the antibodies with a lectin. Therefore, this method is also amenable to automation using existing automated immunodetection equipment. The only consideration is the reaction between the antibody used in the sandwich and the lectin. Antibodies have at least two N-linked glycans. Therefore, if the lectin used recognizes glycans on the antibody, background noise resulting from the binding reaction will be generated during sandwich detection. Possible methods for suppressing this noise signal include modifying the glycan moiety on the antibody or using only Fabs that do not contain glycans. These methods can be performed using known techniques. Methods for modifying sugar chain moieties include, for example, Chen S et al., Nat Methods. 4, 437-44 (2007) and Comunale MA et al., J Proteome Res. 8, 595-602 (2009), and methods using Fab include, for example, Matsumoto H et al., Clin Chem Lab Med 48, 505-512 (2010).

[0045] 3. Method for Detecting Renal Cell Carcinoma Using a Novel Candidate Biomarker for Diagnosis of Renal Cell Carcinoma The method for detecting renal cell carcinoma in one embodiment of the present invention encompasses a method for specifically detecting renal cell carcinoma, comprising detecting a novel candidate biomarker for diagnosing renal cell carcinoma (hereinafter, a lectin that specifically reacts with a certain candidate biomarker for diagnosing renal cell carcinoma will be referred to as lectin "A"). For example, means for detecting a novel candidate biomarker for diagnosing renal cell carcinoma having a sugar chain that specifically reacts with lectin "A" include: (1) a combination of (a) a means for detecting a sugar chain that specifically reacts with lectin "A" and (b) a means for detecting the core protein by a means for detecting a portion other than the sugar chain of the renal cell carcinoma diagnostic biomarker (core protein); and (2) an antibody specific to a renal cell carcinoma diagnostic biomarker having a sugar chain that specifically binds to lectin "A," the antibody having an epitope near the sugar chain binding portion. Here, the means for detecting glycans that specifically react with lectin "A" and the means for detecting core proteins may be means for measuring glycans that specifically react with lectin "A" and means for measuring core proteins, respectively. For example, by detecting novel candidate biomarkers for diagnosing renal cell carcinoma using an antibody against core protein and lectin "A," renal cell carcinoma patients can be distinguished from healthy individuals. Preferably, an antibody overlay method using a lectin array can be 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)). A simpler detection method is the lectin-antibody sandwich immunological detection method (Kuno A et al. Scientific Reports 2013; https: / / doi.org / 10.1038 / srep01065, Kuno A et al. Scientific Reports 3, Article number: 1065 (2013)).

[0046] 3-1. For example, specific methods for detecting renal cell carcinoma using candidate diagnostic biomarkers for renal cell carcinoma having sugar chains that specifically react with lectin "A" include: 1) measuring a diagnostic biomarker for renal cell carcinoma having sugar chains that specifically react with lectin "A" or a fragment thereof (peptide containing a glycosylation site) in a sample collected ex vivo from a subject; 2) measuring a diagnostic biomarker for renal cell carcinoma having sugar chains that specifically react with lectin "A" or a fragment thereof (peptide containing a glycosylation site) in a sample collected ex vivo from a healthy subject; 3) measuring a diagnostic biomarker for renal cell carcinoma having sugar chains that specifically react with lectin "A" or a fragment thereof (peptide containing a glycosylation site) in a sample collected ex vivo from a patient with renal cell carcinoma; and 4) A method for detecting renal cell carcinoma, comprising the steps of: comparing the measurement results of a diagnostic biomarker for renal cell carcinoma having a sugar chain that specifically reacts with lectin "A" or a fragment thereof (a peptide containing a glycosylation site) obtained from a subject with the measurement results of a diagnostic biomarker for renal cell carcinoma having a sugar chain that specifically reacts with lectin "A" or a fragment thereof (a peptide containing a glycosylation site) obtained from a healthy subject or a patient with renal cell carcinoma; and identifying the subject as having renal cell carcinoma if the measurement results of the subject are closer to the measurement results of the patient with renal cell carcinoma.

[0047] (2) A method for measuring a novel candidate biomarker for diagnosing renal cell carcinoma or a fragment thereof can be used, specifically, using an antibody against the candidate biomarker for diagnosing renal cell carcinoma or a fragment thereof. Lectin-antibody sandwich ELISA or antibody overlay lectin array method can be preferably used. Furthermore, the concentration of a candidate biomarker for diagnosing renal cell carcinoma or a fragment thereof (a peptide containing a glycosylation site) having a sugar chain that specifically reacts with lectin "A" can also be measured. Examples of methods for measuring this include antibody overlay lectin array method using a lectin array, LC-MS, immunoassay, enzyme activity assay, and capillary electrophoresis. Preferably, qualitative or quantitative techniques such as LC-MS, enzyme immunoassay, two-antibody sandwich ELISA, gold colloid method, radioimmunoassay, latex agglutination immunoassay, fluorescent immunoassay, Western blotting, immunohistochemistry, and surface plasmon resonance (hereinafter referred to as SPR) using monoclonal or polyclonal antibodies specific to a novel renal cell carcinoma diagnostic biomarker candidate or a fragment thereof having a glycan that specifically reacts with lectin "A" can be used. More specifically, semi-quantitation can also be performed by Western blotting using lectin "A" and an anti-renal cell carcinoma diagnostic biomarker candidate antibody. In qualitative measurements, the phrase "when the measurement result of the subject is higher" refers to a case where it is qualitatively demonstrated that a greater amount of the novel renal cell carcinoma diagnostic biomarker candidate having a glycan that specifically reacts with lectin "A" is present in the subject sample than in a normal subject sample. Furthermore, lectin methods and mass spectrometry, which are direct methods for measuring glycans without using antibodies, are also included.

[0048] 4. Preparation of Novel Specific Polyclonal and / or Monoclonal Antibodies Using Novel Renal Cell Carcinoma Diagnostic Biomarker Candidates or Fragments Thereof In a method for detecting renal cell carcinoma that utilizes a novel renal cell carcinoma diagnostic biomarker, polyclonal and / or monoclonal antibodies specific to the renal cell carcinoma diagnostic biomarker can be used if they are readily available; however, if they are not readily available, they can be prepared, for example, as described below.

[0049] 4.1. Antibody Preparation The novel renal cell carcinoma diagnostic biomarker of one embodiment of the present invention can be used to prepare polyclonal or monoclonal antibodies for detecting renal cell carcinoma. For example, antibodies against fragments of candidate novel renal cell carcinoma diagnostic biomarkers can be prepared by well-known methods. Antibody production can also be boosted by coadministration of Freund's complete adjuvant. Alternatively, a peptide containing a binding site to which an X glycan is attached can be synthesized, covalently linked to commercially available keyhole limpet hemocyanin (KLH), and administered to an animal. Granulocyte-macrophage colony-stimulating factor (GM-CSF) can also be coadministered to boost antibody production. For example, monoclonal antibodies against candidate novel renal cell carcinoma diagnostic biomarkers can be prepared by the method of Keller and Milstein (Nature Vol. 256, pp. 495-497 (1975)). For example, hybridomas can be prepared by cell fusion of antibody-producing cells obtained from an animal immunized with an antigen with myeloma cells, followed by selection of clones producing anti-X antibodies from the resulting hybridomas. Specifically, an adjuvant is added to the resulting candidate biomarker for diagnosing renal cell carcinoma. Examples of adjuvants include Freund's complete adjuvant and Freund's incomplete adjuvant, and these may be mixed. The antigen obtained as described above is administered to mammals, such as mice, rats, horses, monkeys, rabbits, goats, and sheep. While any known immunization method can be used, immunization is typically performed by intravenous injection, subcutaneous injection, or intraperitoneal injection. The interval between immunizations is not particularly limited, and immunizations are performed every few days to several weeks, preferably every 4 to 21 days. 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. As the myeloma cells to be fused with antibody-producing cells, established cell lines derived from various animals such as mice, rats, and humans, and generally available to those skilled in the art, are used.The cell line used is one that is drug-resistant and cannot survive in a selective medium (e.g., HAT medium) in an unfused state, but can survive only in a fused state. Generally, an 8-azaguanine-resistant line is used, which is hypoxanthine-guanine-phosphoribosyltransferase-deficient and cannot grow in hypoxanthine-aminopterin-thymidine (HAT) medium. Myeloma cells can be any of various known cell lines, such as P3 (P3x63Ag8.653) (J. Immunol. 123, 1548-1550 1979), P3x63Ag8U. 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 8,405-415(1976)), SP2 / 0(Shulman, M. et al., Nature 276,269-270(1978)), FO(de St.Groth, SF et al., J. Immunol. Methods 35, 1-21(1980)), S194(Trowbridge, IS, J. Exp. Med. 148, 313-323 (1978)), R210 (Galfre, G. et al., Nature 277, 131-133 (1979)) is preferably used. Next, the above-mentioned myeloma cells and antibody-producing cells are subjected to cell fusion. Cell fusion is carried out by contacting myeloma cells and antibody-producing cells at a mixing ratio of 1:1 to 1:10 in an animal cell culture medium such as MEM, DMEM, or RPME-1640 medium in the presence of a fusion promoter at 30 to 37°C for 1 to 15 minutes. To promote cell fusion, fusion promoters or fusion viruses such as polyethylene glycol or polyvinyl alcohol with an average molecular weight of 1,000 to 6,000 or Sendai virus can be used. Alternatively, antibody-producing cells and myeloma cells can be fused using a commercially available cell fusion device that utilizes electrical stimulation (e.g., electroporation).The desired hybridomas are selected from the cells after cell fusion treatment. Examples of methods include a method utilizing selective cell growth in a selective medium. Specifically, the cell suspension is diluted with an appropriate medium and plated on a microtiter plate. A selective medium (e.g., HAT medium) is added to each well, and the selective medium is then appropriately replaced and cultured. The resulting cells can be obtained as hybridomas. Screening of hybridomas is performed by limiting dilution, fluorescence-activated cell sorting, or the like, to ultimately obtain monoclonal antibody-producing hybridomas. Methods for collecting monoclonal antibodies from the obtained hybridomas include conventional cell culture methods and ascites formation methods.

[0050] The present invention will be explained in more detail below by showing examples, but the interpretation of the present invention is not limited to these examples.

[0051] Example 1: Selection of glycopeptide biomarkers by glycoproteomics (IGOT-LC / MS method)

[0052] 1. Large-scale identification of glycoproteins 1) Preparation of peptide samples Frozen cancer tissue samples from dialysis renal cancer patients diagnosed with ccRCC and ACD-RCC were disrupted using a bead crusher, and then lysis buffer (20 mM, pH 7.5, Tris-HCl 1% Triton-X 100) was added and the mixture was cooled on ice for 30 minutes. Subsequently, ultra-high speed centrifugation (100,000 g, 60 minutes) was performed at 4°C to collect the precipitate. The precipitate was washed with ice-cold pH 7.4 PBS. Washing was performed twice. The precipitate was then solubilized with a phase transfer surfactant (PTS) (12 mM sodium deoxycholate, 12 mM sodium N-lauroylsarcosinate, 100 mM Tris-HCl (pH 9.0) was added to a protein concentration of approximately 5-10 μg / mL, and dithiothreitol (DTT) was dissolved in a small amount of phase-transfer solubilizer in an amount equal to the protein weight. The mixture was allowed to react for 1 hour at room temperature (to reduce disulfide bonds). Next, iodoacetamide (2.5 times the protein weight) was dissolved in a small amount of phase-transfer solubilizer and added, and the mixture was allowed to react for 1 hour at room temperature in the dark (S-alkylation). After the reaction, lysyl endopeptidase (sequencing grade or higher) was added at 1 / 200 the protein weight and reacted at 37°C for 1 hour. Then, trypsin (sequencing grade or higher) was added at 1 / 100 the protein weight and reacted overnight (approximately 16 hours) at 37°C (digestion). TFA was added to the digested peptide to a final concentration of 1%, and PTS was precipitated. The precipitate was then filtered through a 0.22 μm PTFE filter to remove the precipitate.

[0053] 2) Collection and purification of glycopeptides Acetonitrile was added to the sample peptide to a final concentration of 75%, and the mixture was applied to an amide column equilibrated with water-acetonitrile (25:75) containing 0.1% TFA. After washing, the glycopeptides were eluted by passing water-acetonitrile (1:1) containing 0.1% TFA through the column.

[0054] 3) Glycosylation and glycosylation site stable isotope labeling (IGOT) The purified glycopeptide was frozen and centrifuged under reduced pressure to completely remove the solvent. Then, water labeled with stable isotope oxygen-18 (H ２ １８Peptide-N-glycanase (glycopeptidase F, PNGase) prepared with labeled water was added to the mixture, and the mixture was allowed to react overnight at 37°C.

[0055] 4) LC / MS Shotgun Analysis of Labeled Peptides. The reaction mixture was diluted with 0.1% formic acid and analyzed by LC / MS shotgun analysis. A nanoflow LC system was used to achieve high resolution, reproducibility, and sensitivity. The injected peptides were first collected on a trap column (reverse-phase C18 silica gel support) for desalting purposes. After washing, they were separated using a fritless microcolumn (75 or 150 μm internal diameter x 100 or 50 mm L) packed with the same resin and shaped like a spray tip, using a concentration gradient of organic solvent (acetonitrile). The eluate was ionized via an electrospray interface and directly introduced into the mass spectrometer. Mass analysis was performed in positive ion mode using data-dependent acquisition. MS1 spectra were acquired every 3 seconds, during which ions capable of acquiring MS / MS spectra were selected. These ions were then sequentially fragmented by high-energy collision-induced dissociation (HCD) and MS / MS spectra were obtained.

[0056] 5) Peptide search using MS / MS-ion search method Thousands of MS / MS spectra obtained were individually smoothed and centered to create a peak list (mgf file). Based on this data, peptides were identified using a protein amino acid sequence database by MS / MS ion search method. Mascot from Matrix Science was used as the search engine. Search condition parameters included the fragmentation method used (trypsin digestion), number of allowed miscleavages: 2, fixed modification: carbamidomethylation of cysteine, variable modification: pyroglutamylation of N-terminal glutamine (terminal glutamine), deamination of the N-terminal amino group (terminal cysteine), oxidation (methionine), １８ Deamidation with O incorporated (asparagine: glycosylation site), MS spectrum tolerance: 7 ppm, MS / MS spectrum tolerance: 0.02 Da was used.

[0057] 6) Identification of glycopeptides Searches were performed under the above conditions, and the following identification confirmation process was performed based on the results obtained. (1) The score of the likelihood of identification (probability of coincidence: Expect value) was 0.05 or less, or the Expect value at which the False Discover Rate was 1%, whichever is smaller. (2) The identified peptides were Asn-modified (converted to Asp, and １８ O incorporation), the number of which does not exceed the number of consensus sequences in the peptide, and the modification site is on the consensus sequence.

[0058] 2. Procedure for Narrowing Down Marker Glycopeptides 1) Glycopeptides were collected on an amide column from a tryptic digest of proteins prepared from a sample collected from a cancer-specific region of paraneoplastic renal cell carcinoma associated with acquired cystic kidney disease in a patient receiving dialysis. The glycopeptides were then identified using the IGOT-LC / MS method described above. The identified glycopeptides were designated as biomarker glycopeptides for diagnosing early-stage renal cell carcinoma. 2) Next, glycopeptides were collected on the same amide column from a sample collected from a cancer-specific region of clear cell renal cell carcinoma in a patient receiving dialysis. The identified glycopeptides were designated as reference glycopeptides for diagnosing early-stage renal cell carcinoma. 3) These glycopeptide lists were compared with each other and classified and narrowed down as follows: (i) The biomarker glycopeptides for diagnosing early-stage renal cell carcinoma in 1) were compared with the reference glycopeptides for diagnosing early-stage renal cell carcinoma in 2), and the protein groups identified only in 1) were designated as marker glycopeptides. (ii) Of the peptides that did not overlap, those identified only in samples of acquired cystic kidney-associated renal cell carcinoma (RCC) from dialysis-treated renal cancer patients were selected and designated as "biomarker glycopeptides for diagnosing renal cell carcinoma." The marker glycopeptides selected and narrowed down as described above were defined not only by their amino acid sequences but also by clarifying the modifications of the peptide moiety, particularly the glycosylation site. Some of these are shown in Figure 3.

[0059] 3. Marker glycoproteins Based on the sequences of the marker glycopeptides identified and selected in 2., glycoproteins containing these sequences were identified.

[0060] Example 2: Selection of Glycopeptide Biomarkers Using Byonics. Glycoproteins extracted from frozen tissue specimens of ACD-RCC and cc-RCC cancers were subjected to reductive alkylation and trypsin digestion to fragment peptides, followed by enrichment of glycopeptides using an amide column. These samples were analyzed by LC / MS. A nanoflow LC system was used to achieve high resolution, reproducibility, and high sensitivity. The injected peptides were first collected on a trap column (a reversed-phase C18 silica gel support) for desalting purposes. After washing, they were separated using a fritless microcolumn (75 or 150 μm internal diameter x 100 or 50 mm L) with a spray tip packed with the same resin using a concentration gradient method with an organic solvent (acetonitrile). The eluate was ionized via an electrospray interface and directly introduced into a mass spectrometer. Mass spectrometry was performed in positive ion mode using data-dependent acquisition. MS1 spectra were acquired every 3 seconds, during which ions capable of obtaining MS / MS spectra were selected. These ions were then sequentially fragmented by high-energy collision-induced dissociation (HCD) and MS / MS spectra were measured. When a fragment signal derived from N-acetylhexosamine at m / z 204 was observed, the ion was fragmented by electron transfer dissociation (ETD) with the aid of HCD to obtain an EThcD spectrum. Glycopeptide analysis was performed on the thousands of MS / MS spectra obtained using Protein Metrics' Byonic software, a large-scale glycopeptide identification program. The search parameters were the fragmentation method used (trypsin digestion), the number of miscleavages allowed: 2, fixed modification: carbamidomethylation of cysteine, variable modifications: pyroglutamation of N-terminal glutamine (terminal glutamine), deamination of N-terminal amino group (terminal cysteine), oxidation (methionine), MS spectrum tolerance: 7 ppm, and MS / MS spectrum tolerance: 0.02 Da. Fragmentation methods: HCD and EThcD. A portion of the results is shown in Figure 4A.

[0061] Example 3: Selection of glycopeptide biomarkers using the Glyco-RIDGE method. Glycoproteins extracted from frozen tissue specimens of ACD-RCC and cc-RCC cancer sites were subjected to reductive alkylation and trypsin digestion to fragment peptides, followed by enrichment of glycopeptides using an amide column. These samples were analyzed by LC / MS. The resulting multivalent ion signals from MS1 were deconvoluted to singly charged ions, and the glycan structures attached to the peptides were predicted using the Glyco-RIDGE method. GRable, developed at the National Institute of Advanced Industrial Science and Technology, was used for the prediction of glycan structures. Signals with an intensity of 10 or higher were targeted across the entire analysis time range, and a search for monoisotopic signals was performed using the default GRable parameter settings. Among the monoisotopic signals searched for, pairs of signals with an exact monosaccharide or disaccharide mass difference were searched for within the LC elution time set below. If pairs were found, the information was linked to detect clusters (clustering). 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 min, NeuAc (m / z 291.0954): 1 to 5 min, mass tolerance: 5 ppm. Next, the masses of the glycopeptides obtained by clustering were compared with the mass of the core peptide to search for peptides with differences in glycan composition (matching). Information on the core peptide was obtained using the results of IGOT-LC / MS of the same sample obtained under the same analytical conditions. The parameter settings for matching are as follows: The number of constituent sugars was set to 0-12 for Hex and HexNAc, 0-4 for dHex and NeuAc, and the mass tolerance was set to 5 ppm. The predicted sugar chain composition was evaluated for accuracy using a separately prepared glycan point list. Some of the results are shown in Figure 4B.

[0062] Example 4: Immunostaining (1) Immunohistochemical Staining Formalin-fixed, paraffin-embedded (FFPE) specimens of the tumor and its surrounding area excised from a patient with renal cell carcinoma undergoing dialysis were used to examine the expression of GPNMB, Megalin, ACE2, and MME in renal cell carcinoma tissue and cystic lesions. First, slide specimens were sliced ​​to a thickness of 3 μm, deparaffinized, and washed with distilled water. Immunohistochemical staining for GPNMB, Megalin, and ACE2 was performed using an automated Histostainer (Nichirei Biosciences). Antigen retrieval was performed using the PT-Link antigen retrieval device. CD10 (MME) staining was performed using an Agilent Technologies Omnis-specific kit (EnVision FLEX, High pH Dako Omnis).

[0063] The following primary antibodies were used: anti-GPNMB polyclonal antibody ("AF2550", manufactured by Bio-Techne); anti-Megalin monoclonal antibody ("sc-515772", manufactured by Santa Cruz Biotechnology); anti-ACE2 monoclonal antibody ("sc-390851", manufactured by Santa Cruz Biotechnology); anti-CD10 (MME) monoclonal antibody (immunohistochemical staining (IHC): GA648; for fluorescent multiplex staining: IR648), manufactured by Agilent Technologies; for use exclusively with mechanical staining).

[0064] The following lectins were used as labeled lectins: SNA lectin (SAMBUCS NIGRA (ELDERBERRY) BARK LECTIN (B-1305 (natural product), Vector Laboratories)) MAH lectin (Maackia amurensis lectin II (B-1265 (natural product), Vector Laboratories))

[0065] Representative IHC staining results for GPNMB, megalin, ACE2, and MME are shown in Figure 5A. These results suggest that there are cases in which GPNMB is weakly positive or negative and megalin, ACE2, and MME are strongly positive, and cases in which GPNMB is strongly positive and megalin, ACE2, and MME are weakly positive. When glomeruli, tubules, cystic epithelium, ACD-RCC, and cc-RCC were observed with multiple fluorescent staining, MME was not sialylated in a manner recognized by SNA in normal tissues. However, as shown in Figure 5B, in cystic epithelium and cancer, areas where the fluorescent staining of MME and SNA merged were observed, confirming that MME was sialylated in a manner recognized by SNA. In other words, it is possible that specific glycosylation (sialylation) that is not present in normal tissues may occur at the time of precancerous lesions, suggesting that they may be useful as markers for acquired cystic diseases.

[0066] Furthermore, based on the obtained results, the expression of GPNMB, Megalin, ACE2, and MME was evaluated. The evaluation items (Table 1) for IHC evaluation were set in accordance with the HER2 Pathological Diagnostic Guidelines for Breast Cancer and Gastric Cancer, 2nd Edition (Japanese Society of Pathology) https: / / www.kanehara-shuppan.co.jp / books / detail.html?isbn=9784307050548. The evaluation results are shown in Table 2. As seen from the staining results, MME expression was observed in most cases of both ACD-RCC and cc-RCC, which is consistent with previous reports (Non-Patent Document 5). Looking at GPNMB, megalin, and ACE2, cases with strongly positive GPNMB showed negative to equivocal megalin and ACE2, while cases with negative GPNMB tended to be positive for megalin and ACE2. This is consistent with the following literature, which suggests that GPNMB indicates stemness:・C. Chen, Y. Okita, Y. Watanabe, F. Abe, MA Fikry, Y. Ichikawa, H. Suzuki, A. Shibuya, M. Kato, Glycoprotein nmb Is Exposed on the Surface of Dormant Breast Cancer Cells and Induces Stem Cell-like Properties., Cancer Res 78 (2018) 6424-6435. ・C. Wang, Y. Okita, L. Zheng, Y. Shinkai, L. Manevich, JM Chin, T. Kimura, H. Suzuki, Y. Kumagai, M. Kato, Glycoprotein non-metastatic melanoma protein B functions with growth factor signaling to induce tumorigenesis through its serine phosphorylation., Cancer Sci 112 (2021) 4187-4197. At the tissue level, the presence of glycosylated MME recognized by SNA was confirmed in both ACD-RCC and cc-RCC (including cystic lesions), but was more prominent in ACD-RCC cases. However, glycosylated MME recognized by SNA was not detected in normal tissues.

[0067] (2) Western Blot To verify the quantitative differences in GPNMB, MME, and megalin between ACD-RCC and cc-RCC, the following experiment was carried out using cancer tissues from 12 randomly selected renal cancer patients.

[0068] (Enrichment of target molecules in tissue specimens using antibodies against each molecule) Frozen tumor tissues (T) from 12 renal cancer patients (cc-RCC: #1, 2, 3, 4, 5, 11, 12 and ACD-RCC #6, 7, 8, 9, 10) were solubilized according to standard methods to obtain tissue lysates. The solubilization buffer used was phosphate-buffered saline (PBSTx) containing 1% protease inhibitor (Protease Inhibitor Cocktail, Animal Component Free, Sigma-Aldrich) / 1% Triton X-100. The total protein content in the tissue lysates was quantified using a Micro BCA Protein Assay Kit (ThermoFisher), based on the standard BCA method. Using a total protein amount equivalent to 50 μg 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)).

[0069] a) GPNMB In the above immunoprecipitation, 10 μL of streptavidin-immobilized magnetic beads (Dynabeads MyOne Streptavidin T1, DYNAL) were used for preclearance. For immunoprecipitation, 10 μL of these magnetic beads and 500 ng of biotinylated GPNMB antibody (Human Osteoactivin / GPNMB Biotinylated Antibody, R&D Systems) were used, preconjugated before reaction with tissue lysate. A 20 μg portion of the precleared tissue lysate was mixed with the preconjugate and incubated overnight. The beads were washed three times with 1% PBSTx. To elute each molecule captured by the magnetic beads, 20 μL of 0.2% SDS-containing TBS buffer was added to the magnetic bead pellet after precipitation, followed by heating at 95°C for 10 minutes. The magnetic beads were trapped using a dedicated recovery magnet, and 20 μL of the magnetic beads were added to the obtained supernatant. The biotinylated antibody eluted along with the protein of interest by heating was trapped and removed by the magnetic beads, and the final supernatant was designated as GPNMB eluate (GPNMB enriched). Western blotting was performed using half of the eluate according to standard methods. A 5-20% gradient polyacrylamide gel was used as the electrophoresis gel, and the biotinylated antibody described above was used as the primary detection antibody. Streptavidin-HRP and a detection substrate (ImmnoStarLD, Fujifilm Wako Pure Chemical Industries, Ltd.) were used for detection.

[0070] b) MME In the above immunoprecipitation, 20 μL of streptavidin-immobilized magnetic beads were used for preclearance. For immunoprecipitation, 10 μL of the magnetic beads and 400 ng of biotinylated anti-MME antibody (MME, CD10 antibody, Proteintech) were used. These were preconjugated before reaction with tissue lysate. 50 μg of the precleared tissue lysate was mixed with the preconjugated material and incubated overnight. Since the anti-MME antibody used binds to heat-denatured MME, SDS was added to the tissue lysate solution to a final concentration of 0.2% before the binding reaction and heated at 95°C for 5 minutes. The beads were washed three times with 1% PBSTx. To elute each molecule captured by the magnetic beads, 20 μL of 0.2% SDS-containing TBS buffer was added to the magnetic bead pellet after precipitation and heated at 95°C for 10 minutes. The magnetic beads were trapped using a dedicated recovery magnet, and 40 μL of the magnetic beads were added to the obtained supernatant. The biotinylated antibody eluted along with the protein of interest by heating was trapped and removed by the magnetic beads, and the final obtained supernatant was designated as the MME eluate (MME enriched). Western blotting was performed using half of the eluate according to standard methods. A 5-20% gradient polyacrylamide gel was used as the electrophoresis gel, the biotinylated antibody was used as the primary detection antibody, and streptavidin-HRP and a detection substrate were used for detection.

[0071] c) Megalin In the above immunoprecipitation, 10 μL of streptavidin-immobilized magnetic beads were used for preclearance. For immunoprecipitation, 10 μL of these magnetic beads and 500 ng of biotinylated anti-Megalin antibody (Megalin (H-10), Santa Cruz Biotechnology) were used. These were preconjugated before reaction with tissue lysate. A 20 μg portion of the precleared tissue lysate was mixed with the preconjugated material and allowed to react overnight. Since the anti-Megalin antibody used binds to heat-denatured Megalin, the magnetic beads were collected with a magnet before the binding reaction. The supernatant was collected as the unbound fraction, and the beads were washed three times with 1% PBSTx. To elute each molecule captured by the magnetic beads, 20 μL of 0.2% SDS-containing TBS buffer was added to the magnetic bead pellet after precipitation, and the mixture was heated at 95°C for 10 minutes. The magnetic beads were trapped using a dedicated recovery magnet, and 20 μL of the magnetic beads were added to the obtained supernatant. The biotinylated antibody eluted along with the protein of interest by heating was trapped and removed by the magnetic beads, and the final supernatant was designated as Megalin eluate (Megalin Enriched). Western blotting was performed using half of the eluate according to standard methods. A 5-20% gradient polyacrylamide gel was used as the electrophoresis gel, the biotinylated antibody was used as the primary detection antibody, and streptavidin-HRP and a detection substrate were used for detection.

[0072] As shown in Figure 6, no significant quantitative difference was observed between ACD-RCC and cc-RCC in GPNMB and MME. Megalin showed a tendency to be expressed at a higher level in the ACD-RCC patient group.

[0073] Example 5: Antibody Overlay Lectin Microarray Next, to verify whether the qualitative differences between ACD-RCC and cc-RCC using GPNMB, MME, and Megalin could be detected as differences in their reactivity with 45 types of lectins on a lectin array, the GPNMB, MME, and Megalin eluate enriched obtained by the above method was used to perform lectin array analysis (antibody overlay method) 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)). The lectin array chip used was the commercially available chip LecChip ver1.0 (manufactured by Glycotechnica).

[0074] An appropriate amount of each sample (GPNMB, MME, and Megalin eluate-enriched) from the immunoprecipitated solution (enriched from 7.5 μg of GPNMB, 25 μg of MME, and 7.5 μg of Megalin, as total protein amounts at the time of IP) was applied to the above-mentioned lectin array chip ver. 1.0, and the binding reaction was carried out for 10 hours or more at 20°C. To prevent the sugar chains on the detection antibody from binding to unreacted lectin on the substrate and generating noise, 2 μL of human serum-derived IgG solution (Sigma-Aldrich) was added and the reaction was carried out for 30 minutes. Subsequently, 50 ng of the biotinylated antibody (except for GPNMB, which was 100 μg) was added and incubated for 1 hour at 20°C. 200 ng of Cy3-labeled streptavidin was then added and incubated for 30 minutes at 20°C. After washing away excess fluorescent material with PBSTx, binding signals were detected by array scanning using a GlycoStation Reader 1200 (Glycotechnica). A t-test was performed to estimate whether the signals of 45 lectins for each molecule showed significant differences between ACD-RCC and cc-RCC. The results are shown in Figure 7. Since lectin array signals were generated in only 4 of the 12 MME specimens, statistical analysis was not performed.

[0075] Lectins with a P value of <0.05 were considered to have significant differences, and the P value column is shown in gray. For GPNMB, the α2,6 sialic acid-recognizing lectins SNA, SSA, and TJA-I showed significantly elevated levels in ACD-RCC. Megalin levels were elevated in 2-3 of the 5 ACD-RCC patients, but due to the large variability, no statistically significant difference was observed. As shown in the immunohistological verification, there is a negative correlation between GPNMB and Megalin expression. Therefore, the high levels of GPNMB in the 12 cases in this study made it difficult to verify Megalin. Therefore, further verification with a larger number of samples is expected to identify case groups showing significant differences.

[0076] Example 6 Lectin Microarray and Western Blot Using Serum Samples Regarding GPNMB, which showed the most significant difference, the following experiment was carried out using serum collected pre- and post-operatively from six randomly selected patients with renal cancer undergoing dialysis.

[0077] A total of 12 samples of pre- and post-operative serum from six renal cancer patients (#1-6) were used in a volume of 40 μL, and immunoprecipitation was performed according to the tissue lysate enrichment method described above. For immunoprecipitation, 10 μL of streptavidin-immobilized magnetic beads were used for preclearance. For immunoprecipitation, 10 μL of the magnetic beads and 500 ng of biotinylated GPNMB antibody were used, preconjugated before reaction with serum dilutions. A 40 μg portion of precleared serum was mixed with the preconjugate and incubated overnight. The beads were washed three times with 1% PBSTx. To elute each molecule captured by the magnetic beads, 20 μL of 0.2% SDS-containing TBS buffer was added to the precipitated magnetic bead pellet and heated at 95°C for 10 minutes. The magnetic beads were trapped using a dedicated collection magnet, and 20 μL of the above magnetic beads were added to the obtained supernatant. The biotinylated antibody eluted along with the protein of interest by heating was trapped and removed by the magnetic beads, and the final obtained supernatant was designated as GPNMB eluate (GPNMB-enriched). Western blotting was performed using one-fourth of the eluate according to standard methods. A 5-20% gradient polyacrylamide gel was used as the electrophoresis gel, and the above biotinylated antibody was used as the primary detection antibody. Detection was performed using streptavidin-HRP and a detection substrate. The results are shown in Figure 8. In most cancer patients, GPNMB levels were elevated compared to healthy controls, and a decrease in GPNMB levels after surgery compared to before surgery was generally confirmed, although this varied depending on the case.

[0078] Next, to verify whether qualitative changes in serum GPNMB before and after surgery could be detected as differences in reactivity with 45 lectins on a lectin array, lectin array analysis (antibody overlay method) was performed using the enriched GPNMB eluate obtained by the above method in the same manner as for tissue lysates. An appropriate amount of each sample (enriched GPNMB eluate) from the immunoprecipitated solution (enriched GPNMB equivalent to 10 μL of serum solution at the time of IP) was applied to the above lectin array chip version 1.0 and allowed to react for 10 hours or more at 20°C. To prevent binding of glycans on the detection antibody to unreacted lectins on the substrate and resulting in noise, 2 μL of human serum-derived IgG solution (Sigma-Aldrich) was added and allowed to react for 30 minutes. Subsequently, 100 ng of the biotinylated antibody was added and incubated for 1 hour at 20°C. Then, 200 ng of Cy3-labeled streptavidin was added and incubated for 30 minutes at 20°C. After washing away excess fluorescent material with PBSTx, binding signals were detected by array scanning using a GlycoStation Reader 1200. The signals of each lectin were plotted against pre- and post-operative data, and P values ​​were calculated using a paired test. The results are shown in Figure 9. Lectins enclosed in bold frames show P values ​​< 0.05. SNA and SSA, α2,6 sialic acid-recognizing lectins discovered during the research process, showed a significant signal decrease in post-operative samples. Furthermore, when the signal of the lectin DSA, which showed little difference between pre- and post-operative data in each case, was normalized to 1, this tendency became even more pronounced, as shown in Figure 10.

[0079] From the above, it was demonstrated that at least GPNMB can be detected in the serum of patients or healthy individuals, and that it is useful as a serum biomarker, particularly as a serum renal cancer marker for dialysis patients.

[0080] The biomarker of this embodiment can specifically detect renal cell carcinoma, and therefore can be suitably used in methods for detecting renal cell carcinoma and in the manufacture of renal cell carcinoma diagnostic kits, and has industrial applicability.

Claims

1. A biomarker for detecting renal cell carcinoma, comprising GPNMB having a sialylated glycan that is increased during carcinogenesis.

2. The biomarker of claim 1, wherein the renal cell carcinoma is renal cell carcinoma in a dialysis patient.

3. A method for detecting a biomarker, comprising detecting the biomarker according to claim 1 or 2 in vitro in a test sample obtained from a subject.

4. The detection method according to claim 3, comprising a sandwich ELISA method.

5. The detection method according to claim 3 , wherein the test sample is serum.

6. A renal cell carcinoma diagnostic kit comprising a means for detecting the biomarker of claim 1 or 2.

7. The kit according to claim 6, wherein the means for detecting comprises an antibody that binds to GPNMB having a sialylated sugar chain, and a lectin that binds to the sialylated sugar chain.

8. A method for searching for renal cell carcinoma markers, which comprises examining changes in the sugar chain structure of glycoproteins derived from kidney tissue.

9. The search method according to claim 8, which comprises analysis by lectin array or Western blotting.