Method for detecting N-glycome of cerebrospinal fluid of PCNSL patient and related kit

Abstract

The invention discloses a method for detecting N-glycome of cerebrospinal fluid of a PCNSL patient and a related kit, belongs to the field of biological medicines, and is used for researching the N-glycome of the PCNSL patient and developing and preparing related diagnostic products. The method comprises the following steps: extracting cerebrospinal fluid of a PCNSL patient, removing cells, denaturing and reducing protein, cutting N-sugar by using PNGase F, labeling the N-sugar by using 2-aminobenzamide, carrying out HILIC liquid chromatography and mass spectrometry detection, and analyzing a detection result. According to the method, the N-glycome of the cerebrospinal fluid of the PCNSL patient can be accurately represented and systematically classified, further scientific research on the diagnosis and treatment relationship between the cerebrospinal fluid and the PCNSL, the pathology of the PCNSL and the related pharmacology is facilitated, and the method can also be used for developing kits, instruments, equipment and software for diagnosis or prognosis evaluation of the PCNSL.

Description

Technical Field

[0001] The present invention belongs to the field of biomedicine, and particularly relates to a method for detecting the N-glycome in the cerebrospinal fluid of patients with primary central nervous system lymphoma (PCNSL) and a related kit. Background Art

[0002] N-glycomics focuses on the study of N-linked glycosylation modifications of proteins, that is, the molecular mechanism, structural characteristics, and their roles in biology and diseases in which sugar chains bind to proteins through asparagine (Asn) residues. By analyzing the composition, structure, and dynamic changes of N-linked glycans in specific tissues or body fluids of an organism, N-glycomics can reveal how glycosylation modifications affect protein functions, cell-cell communication, and disease occurrence.

[0003] Primary central nervous system lymphoma (PCNSL) is a subtype of peripheral non-Hodgkin lymphoma (NHL) that originates from the central nervous system (CNS), mainly confined to the brain, retina, eyes, or spinal cord. It accounts for about 2.4% to 4.9% of all primary CNS tumors, and the median age of onset is 65 years.

[0004] Currently, there are mainly two systems for evaluating the prognosis of PCNSL. In a retrospective study involving 105 PCNSL patients, the International Extranodal Lymphoma Study Group (IELSG) identified several factors associated with poor prognosis, including age over 60 years, poor Eastern Cooperative Oncology Group (ECOG) performance status, elevated cerebrospinal fluid protein and serum lactate dehydrogenase (LDH) levels, and deep brain region involvement. For patients with 0 or 1 risk factors, the two-year survival rate was 80%, while for patients with 2 or 3 risk factors, it dropped to 48%; and the two-year survival rate of patients with 4 or 5 risk factors was the lowest, only 15%. In another prognostic model, PCNSL patients were divided into three groups according to age and performance status: (1) <50 years old; (2) ≥50 years old and Karnofsky Performance Status (KPS) ≥70; (3) ≥50 years old and KPS <70. It was found that there were significant differences in overall survival (OS) and disease-free survival (DFS) among these three groups of patients. Age and performance status were consistent predictors of prognosis, while neurocognitive dysfunction was an independent negative prognostic factor. Elevated interleukin-10 levels in cerebrospinal fluid were considered both a prognostic indicator and a diagnostic biomarker. Overall, the existing prognostic indicators provide limited guidance for the diagnosis and prognosis assessment of PCNSL, presenting significant challenges to clinical practice.

[0005] Serum N-glycomics has become an important diagnostic and prognostic tool for various diseases, including infectious diseases, tumors, age-related diseases, and autoimmune diseases. Currently, there is a significant lack of scientific research on the N-glycome of PCNSL. Summary of the Invention

[0006] To solve the problem of N - glycome research in PCNSL patients, we conducted a study on the N - glycome of cerebrospinal fluid (CSF) from PCNSL patients and established a method for detecting the N - glycome of CSF from PCNSL patients and related kits based on the research results.

[0007] The technical solution of the present invention is as follows: A method for detecting the N - glycome of cerebrospinal fluid from PCNSL patients, comprising the following steps: Extract cerebrospinal fluid from PCNSL patients, remove cells, denature proteins using surfactant RapiGest SF, reduce proteins using TCEP, cleave N - glycans with PNGase F, label N - glycans with 2 - aminobenzamide (2 - AB), and perform HILIC liquid chromatography analysis and mass spectrometry analysis.

[0008] Specifically, collect 1 mL of cerebrospinal fluid (CSF) sample obtained by lumbar puncture in a centrifuge tube and immediately place it on ice. The collected CSF is then centrifuged at a rate of 2,000 × g for 5 minutes at 4°C to remove cells. The obtained supernatant is approximately 900 µL, and then the sample is transferred to a new tube and stored in a - 80°C ultra - low temperature freezer for further experiments.

[0009] Exchange 500 µL of CSF with 50 mmol / L ammonium bicarbonate solution in an ultrafiltration centrifuge tube (0.5 mL / 3 kD), concentrate it to 100 µL, and then transfer it to a new EP tube. Add 5 µL of 10% (W / V) RapiGest SF solution (surfactant) and 5 µL of 80 mmol / L TCEP solution, and heat at 95°C for 15 minutes and cool at room temperature.

[0010] Incubate the sample with PNGase F at 37°C for 24 hours for deglycosylation. Precipitate the deglycosylated sample with 2 volumes of ice - cold reagent E for 30 minutes, then centrifuge at 14,000 × g for 30 minutes, obtain the supernatant and transfer it to a new sample tube, and evaporate to dryness.

[0011] Using the GlycoProfile™ 2-AB Labeling Kit (provided by Sigma-Aldrich, catalog number PP0520), the operation was carried out according to the kit instructions. The released N-glycans were labeled with 2-aminobenzamide (2-AB) at 65 °C for 4 hours. The excess labeling reagent was removed using a HILIC SPE column (provided by Agela Corporation). The eluate containing the labeled N-glycans was then transferred to a new sample tube and evaporated to dryness. The labeled N-glycans were redissolved in 70% aqueous acetonitrile. After centrifugation at 14,000 × g for 10 minutes at 4 °C, the sample was transferred to a high-recovery glass vial (Waters, Milford, MA, USA) and prepared for LC-MS / MS analysis.

[0012] The liquid chromatography analysis method was as follows: A 2.1 x 150 mm BEH Glycan (HILIC) column (Waters, Milford, MA, USA) was used in combination with an Acquity UPLC system equipped with a Waters temperature control module and a Waters Acquity fluorescence detector. The column temperature was set at 60 °C. Two buffer solutions were used as the mobile phase. Mobile phase A was 30 mM ammonium formate with a pH of 4.5, and mobile phase B was pure acetonitrile. A 70-minute linear gradient was performed at a flow rate of 0.5 mL / min. The concentration of buffer A at the start of the gradient was 22%, which gradually increased to 40% within 50 minutes, then rose to 70%, and finally returned to 22% to end. The elution of N-glycans was measured by fluorescence detection with an excitation wavelength of 330 nm and a detection wavelength of 420 nm.

[0013] The described HILIC (Hydrophilic Interaction Chromatography) is a liquid chromatography technique mainly used for separating strongly polar compounds and is commonly used in glycan profiling.

[0014] The mass spectrometry analysis method was as follows: 2-AB labeled sugars were detected by Waters Xevo G2-S system (Waters, Milford, MA, USA) in ESI+ mode, with low collision energy set to 6 V and elevated collision energy (from 18 V to 35 V) to acquire precursor ions (MS) and their corresponding fragmentation data (MS / MS). The scan time was set to 0.5 s (total duty cycle was 1 s), and the desolvation gas and source temperatures were maintained at 450°C and 120°C. The capillary and cone voltages were set to 3000 V and 40 V, respectively, and the transfer collision energy was set to 6 V. The flow rates of desolvation and cone gas were 800 L / h and 100 L / h, respectively. The m / z scan range was 650–2500. The raw data were processed by Waters MassLynx MaxEnt 3 software to obtain deconvoluted mass data.

[0015] The results of liquid chromatography and mass spectrometry are processed as follows: N-glycan peaks (GPs) are classified according to the relative intensity of the glycan peaks (GPs), expressed as a percentage (%) of the total glycan peak area. The classification of these glycan peaks is based on the similarity of their structure or composition. By examining the significant glycan components within the peaks, distinct peaks were identified, including 65 N-glycans (54 sugar groups) with unique structures or isomers, named GP1 to GP54. The description of each glycan peak is shown in Table 1, and the structure is shown in Figures 1 to 3 According to the similar structures or composition characteristics of sugar peak members, they are divided into 19 sugar subclasses in total: M, TG, BiS, BiA, TriA, TetrA, HA, S0, S1, S2, S3, S4, TS, cF, Ftria, cFtria, cFa, cFn, and oaF. The description of each subclass is shown in Table 2.

[0016] Among them, Ftria (Proportion of fucosylation in triantennary glycans) is the weighted sum of the 12 peaks according to the following formula: Ftria=SUM[0.5*GP37+GP38+GP40+GP41+0.67*GP42+0.33*GP43+GP44+0.5*GP46+GP47+GP49+GP51+GP52], TG (Proportion of terminal-galactosylated N-glycans) is the weighted sum of the 12 peaks according to the following formula: TG = SUM[SUM(GP5:GP9)+GP11+GP12+GP13+GP15+2*(GP10+GP14+GP16)]。

[0017] Quantify the above N - glycan peaks and glycan subclasses respectively. The glycan subclasses Ftria, TG and the glycan peaks GP6, GP27 are key indicators that deserve key attention. The relative contents of Ftria and TG can be used to diagnose PCNSL: The relative content of Ftria in PCNSL patients is (5.373 ± 1.931)%, and in non - patients is (7.584 ± 2.032)%, and the optimal diagnostic threshold is 5.51%; The relative content of TG in PCNSL patients is (25.499 ± 5.624)%, and in non - patients is (19.608 ± 5.490)%, and the optimal diagnostic threshold is 23.47%.

[0018] GP6 and GP27 combined with age can be used to evaluate the expected survival period of PCNSL patients: Add the scores corresponding to each variable of age, GP6, and GP27, and the final total score corresponds to Figure 4 the 24 - month and 60 - month survival probabilities on the bottom scale.

[0019] Since the glycan subclasses Ftria, TG and the glycan peaks GP6, GP27 are related to the disease status and expected survival period of PCNSL, they can be used to develop or prepare diagnostic and prognostic assessment kits, diagnostic software, and diagnostic systems for PCNSL, and may also be used to evaluate the therapeutic effects of drugs or medical devices.

[0020] In addition, the present invention also provides a kit for assisting in the pretreatment and detection of the above cerebrospinal fluid. This kit includes reagents A, B, C, D, E, F, M, N, and the components of each reagent are: Reagent A: 50 mmol / L ammonium bicarbonate solution; Reagent B: 10% (W / V) RapiGest SF solution; Reagent C: 80 mmol / L TCEP solution; Reagent D: 5 μg / μL PNGase F; Reagent E: ethanol; Reagent F: 70% aqueous acetonitrile solution.

[0021] Among the above reagents, the molecular formula of ammonium bicarbonate is NH4HCO3, and the molecular weight is 79.055; RapiGest SF is an anionic surfactant provided by Waters, with the product number 186002122; TCEP is tris(2 - carboxyethyl)phosphine hydrochloride, with the molecular formula C9H 15 O6P·HCl, the molecular weight is 286.64, and the Cas number is 51805 - 45 - 9.

[0022] PNGase F is an amidase that can cleave between the innermost N-acetylglucosamine (GlcNAc) and asparagine residues of high-mannose, hybrid, and complex oligosaccharides, and it is the most effective enzymatic method for removing almost all N-linked oligosaccharides from glycoproteins.

[0023] The beneficial effect of the present invention is that a method and an auxiliary kit capable of accurately characterizing and systematically classifying the N-glycome of cerebrospinal fluid of PCNSL patients are established, which is convenient for further scientific research on the relationship between cerebrospinal fluid and the diagnosis and treatment of PCNSL, the pathology of PCNSL, and related pharmacology. This method can also be used to develop kits, instruments, and software for the diagnosis and prognostic evaluation of PCNSL. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 Structural diagrams of the 1st to 27th sugar groups.

[0025] Figure 2 Structural diagrams of the 28th - 52nd sugar groups.

[0026] Figure 3 Structures and remarks of the 53rd and 54th sugar groups.

[0027] Figure 4 Nomogram model for predicting the 24-month and 60-month overall survival (OS) of PCNSL patients.

[0028] Figure 5 Calibration curve for predicting the overall survival (OS) of patients.

[0029] Figure 6 Kaplan-Meier analysis of overall survival (OS) using the published prognostic index (IELSG) (A) and the glycan risk prediction model of this study (B).

[0030] Figure 7 Clinical sensitivity and specificity of Ftria and TG for the diagnosis of PCNSL. DETAILED DESCRIPTION OF THE INVENTION

[0031] Example 1. A kit for diagnosing PCNSL by detecting the N-glycome of cerebrospinal fluid

[0032] A kit for diagnosing PCNSL by detecting the N-glycome of cerebrospinal fluid, comprising reagents A, B, C, D, E, F, M, and N. The components of each reagent are: Reagent A: 50 mmol / L ammonium bicarbonate solution; Reagent B: 10% (W / V) RapiGest SF solution; Reagent C: 80 mmol / L TCEP solution; Reagent D: 5 μg / μL PNGase F; Reagent E: ethanol; Reagent F: 70% aqueous acetonitrile solution.

[0033] Among the above reagents, the molecular formula of ammonium bicarbonate is NH4HCO3, and the molecular weight is 79.055; RapiGest SF is an anionic surfactant provided by Waters, part number 186002122; TCEP is tris(2-carboxyethyl)phosphine hydrochloride, molecular formula C9H 15 O6P·HCl, molecular weight 286.64, Cas number 51805-45-9.

[0034] PNGase F is an amidase that can cleave between the innermost N-acetylglucosamine (GlcNAc) and asparagine residues of high-mannose, hybrid, and complex oligosaccharides, and is the most effective enzymatic method for removing almost all N-linked oligosaccharides from glycoproteins.

[0035] Example 2, Method for detecting and analyzing the N-glycome in the cerebrospinal fluid of PCNSL and method for using the kit

[0036] The detection and result analysis are carried out successively according to the following steps:

[0037] 2.1 Preparation of cerebrospinal fluid and release and labeling of N-glycans

[0038] Collect 1 mL of cerebrospinal fluid (CSF) sample obtained by lumbar puncture in a centrifuge tube and immediately place it on ice. The collected CSF is then centrifuged at a rate of 2,000 × g for 5 minutes at 4°C to remove cells. The obtained supernatant is approximately 900 µL, and then the sample is transferred to a new tube and stored in a -80°C ultra-low temperature freezer for further experiments.

[0039] (1) Release of N-glycans Exchange 500 µL of CSF with Reagent A solution in an ultrafiltration centrifugal tube (0.5 mL / 3 kD), concentrate to 100 µL, and then transfer to a new EP tube. Add 5 µL of Reagent B and 5 µL of Reagent C, and heat at 95°C for 15 minutes and cool at room temperature.

[0040] The sample was incubated with 5 µL of Reagent D at 37 °C for 24 hours for deglycosylation. The deglycosylated sample was precipitated with 2 volumes of ice-cold Reagent E for 30 minutes and then centrifuged at 14,000 × g for 30 minutes. The supernatant was obtained and transferred to a new sample tube, and evaporated to dryness.

[0041] (2)N-glycan labeling Using the GlycoProfile™ 2-AB Labeling Kit (provided by Sigma-Aldrich, catalog number PP0520), and operating according to the kit instructions, the released N-glycans were labeled with 2-aminobenzamide (2-AB) at 65 °C for 4 hours. Excess labeling reagent was removed using an HILIC SPE column (provided by Agela Corporation). The effluent containing the labeled N-glycans was then transferred to a new sample tube and evaporated to dryness. The labeled N-glycans were redissolved with Reagent F. After centrifugation at 14,000× g at 4 °C for 10 minutes, the sample was transferred to a high-recovery glass vial (Waters, Milford, MA, USA) for LC-MS / MS analysis.

[0042] 2.2 LC-MS / MS instrument detection

[0043] For liquid chromatography analysis, a 2.1 x 150 mm BEH Glycan (HILIC) column (Waters, Milford, MA, USA) was used, combined with an Acquity UPLC system equipped with a Waters temperature control module and a Waters Acquity fluorescence detector. The column temperature was set at 60 °C, and two buffer solutions were used as the mobile phase. Mobile phase A was 30 mM ammonium formate, pH 4.5, and mobile phase B was pure acetonitrile. A 70-minute linear gradient was carried out at a flow rate of 0.5 mL / min. The concentration of buffer A at the start of the gradient was 22%, gradually increasing to 40% within 50 minutes, then rising to 70%, and finally returning to 22% to end. The elution of N-glycans was measured by fluorescence detection, with an excitation wavelength of 330 nm and a detection wavelength of 420 nm. An external standard was used to compare the carbohydrate results between different experiments for consistency.

[0044] In mass spectrometry (MS) and tandem mass spectrometry (MS / MS) analysis, saccharides labeled as 2-AB were detected on a Waters Xevo G2-S system (Waters, Milford, MA, USA) in ESI+ mode with a low collision energy set at 6 V and an elevated collision energy (ramped from 18 V to 35 V) to acquire precursor ions (MS) and their corresponding fragment data (MS / MS). The scan time was set at 0.5 s (total duty cycle of 1 s), and the desolvation gas and source temperature were maintained at 450 °C and 120 °C. The capillary and cone voltages were set at 3000 V and 40 V, respectively, and the transfer collision energy was set at 6 V. The flow rates of the desolvation and cone gases were 800 L / h and 100 L / h, respectively. The m / z scan range was 650 - 2500. Other mass spectrometry parameters were the same as those for the above mass analysis. All raw data were processed by Waters MassLynx MaxEnt 3 software to obtain deconvoluted mass data.

[0045] 2.3 Feature Analysis

[0046] N-glycan peaks (GPs) were classified according to the relative intensities of glycan peaks (GPs), expressed as a percentage (%) of the total glycan peak area. These sugar peaks were classified based on the similarity of their structures or compositions. Characteristic peaks were identified by examining the prominent saccharide components within the peaks.

[0047] Using the above method, 65 N-glycans (54 sugar groups) with unique structures or isomers were identified. The following table provides an overview of the N-glycan peaks, including their nomenclature, theoretical mass, observed mass, and general description, as described in the following table and the structure is shown in Figures 1 to 3 .

[0048] Table 1 Structural composition, nomenclature, molecular weight, theoretical error, and characteristic description of 65 N-glycans (54 sugar groups) determined by high performance liquid chromatography-hydrophobic interaction chromatography.

[0049] Glycan Peak (GP) <![CDATA[N-GlycanComposition 1 (Major)]]> <![CDATA[Oxford Nomenclature 3 > Theoretical Mass (m / z) Observed Mass (m / z) General description 1 Hex(3)dHex(0)HexNAc(5)NeuAc(0) A2BG0 1640.6419 1640.6691 Biantennary glycan with bisecting GlcNAc 2 Hex(3)dHex(1)HexNAc(4)NeuAc(0) FA2G0 1583.6205 1583.6326 Biantennary glycan with core fucose 3 Hex(5)dHex(0)HexNAc(2)NeuAc(0) M5 1355.5095 1355.5073 High mannose (M5) glycan 4 Hex(3)dHex(1)HexNAc(5)NeuAc(0) FA2BG0 1786.6998 1786.7115 Biantennary glycan with bisecting GlcNAc and core fucose 5 Hex(4)dHex(0)HexNAc(5)NeuAc(0) A2BG1 1802.6947 1802.6952 Monogalactosylated biantennary glycan with bisecting GlcNAc 6 Hex(4)dHex(1)HexNAc(4)NeuAc(0) FA2[3]G1 1745.6733 1745.6708 Monogalactosylated biantennary glycan with 1-3 linkages with core fucose 7 Hex(4)dHex(1)HexNAc(4)NeuAc(0) FA2[6]G1 1745.6733 1745.6906 Monogalactosylated biantennary glycan with 1-6 linkages with core fucose 8 Hex(4)dHex(1)HexNAc(5)NeuAc(0) FA2[3]BG1 1948.7527 1948.7352 Monogalactosylated biantennary glycan with 1-6 linkages with bisecting GlcNAc and core fucose 9 Hex(4)dHex(1)HexNAc(5)NeuAc(0) FA2[6]BG1 1948.7527 1948.7375 Monogalactosylated biantennary glycan with 1-3 linkages with bisecting GlcNAc and core fucose 10 Hex(5)dHex(0)HexNAc(4)NeuAc(0) A2G2 1761.6682 1761.6702 Digalactosylated biantennary glycan 11 Hex(4)dHex(0)HexNAc(4)NeuAc(1)※ FA2F1NG1 1932.7577 1932.7618 MonoN-acetylgalacotosaminylated biantennary glycan with 1-6 linkages with core fucose and outer arm fucose 12 Hex(4)dHex(2)HexNAc(4)NeuAc(0) FA2F1G1 1891.7312 1891.7213 Monogalactosylated biantennary glycan with 1-6 linkages with core fucose and outer arm fucose 13 Hex(4)dHex(2)HexNAc(4)NeuAc(0) FA2F1G1 1891.7312 1891.7244 Monogalactosylated biantennary glycan with 1-3 linkages with core fucose and outer arm fucose 14 Hex(5)dHex(1)HexNAc(4)NeuAc(0) FA2G2 1907.7261 1907.7179 Digalactosylated biantennary glycan with core fucose 15 Hex(4)dHex(2)HexNAc(5)NeuAc(1) FA2BF1G1 2094.8106 2094.8052 Monogalactosylated biantennary glycan with bisecting GlcNAc, core fucose and outer arm fucose 16 Hex(5)dHex(1)HexNAc(5)NeuAc(0) FA2BG2 2110.8055 2110.7983 Digalactosylated biantennary glycan with bisecting GlcNAc and core fucose 17 Hex(4)dHex(1)HexNAc(5)NeuAc(1) FA2BG1S1 2239.8481 2239.8416 Monogalactosylated and monosialylated biantennary glycan with bisecting GlcNAc and core fucose 18 Hex(5)dHex(0)HexNAc(4)NeuAc(2) A2G2S1 2052.7636 2052.7642 Digalactosylated and monosialylated biantennary (Major) 18 Hex(4)dHex(0)HexNAc(5)NeuAc(1) A2BG1S1 2093.7902 2093.7893 Monogalactosylated and monosialylated biantennary glycan with bisecting GlcNAc 19 Hex(4)dHex(1)HexNAc(4)NeuAc(1) FA2G1S1 2036.7687 2036.7726 Monogalactosylated and monosialylated biantennary glycan with core fucose (Major) 19 Hex(4)dHex(1)HexNAc(5)NeuAc(1) FA2BG1S1 2239.8481 2239.8459 Vonogalactosylated and monosialylated biantennary glycan with bisecting GlcNAc and core fucose 20 Hex(7)dHex(0)HexNAc(2)NeuAc(0) M7 1679.6267 1679.6151 High mannose (M7) glycan 21 Hex(5)dHex(0)HexNAc(4)NeuAc(1) A2G2S1 2052.7636 2052.7610 Digalactosylated and monosialylated biantennary glycan 22 Hex(5)dHex(1)HexNAc(5)NeuAc(1) FA2BG2S1 2401.9009 2401.9050 Digalactosylated and monosialylated biantennary glycan with bisecting GlcNAc and core fucose 23 Hex(5)dHex(0)HexNAc(5)NeuAc(1) A2BG2S1 2255.8430 2255.8423 Digalactosylated and monosialylated biantennary glycan with bisecting GlcNAc 24 Hex(5)dHex(1)HexNAc(4)NeuAc(1) FA2G2S1 2198.8215 2198.8232 Digalactosylated and monosialylated biantennary glycan with core fucose (Major) 24 Hex(5)dHex(1)HexNAc(5)NeuAc(2) FA2BG2S1 2401.9009 2401.8911 Digalactosylated and monosialylated biantennary glycan with bisecting GlcNAc and core fucose 25 Hex(8)dHex(0)HexNAc(2)NeuAc(0) M8 1841.6917 1841.6679 High mannose (M8) glycan 26 Hex(5)dHex(1)HexNAc(5)NeuAc(1) FA2BG2S1 2401.9009 2401.8992 Digalactosylated and monosialylated biantennary glycan with bisecting GlcNAc and core fucose 27 Hex(5)dHex(1)HexNAc(4)NeuAc(2) FA2G2S2 2489.9169 2489.9211 Digalactosylated and disialylated biantennary glycan with core fucose 28 Hex(5)dHex(0)HexNAc(4)NeuAc(2) A2G2S2 2343.8590 2343.8157 Digalactosylated and disialylated biantennary glycan 29 Hex(5)dHex(1)HexNAc(4)NeuAc(2) FA2G2S2 2489.9169 2489.8557 Digalactosylated and disialylated biantennary glycan with core fucose 30 Hex(5)dHex(0)HexNAc(4)NeuAc(2) A2G2S2 2343.8590 2343.8149 Digalactosylated and disialylated biantennary glycan 31 Hex(5)dHex(1)HexNAc(5)NeuAc(2) FA2BG2S2 2692.9963 2693.0044 Digalactosylated and disialylated biantennary glycan with bisecting GlcNAc and core fucose (Major) 31 Hex(6)dHex(0)HexNAc(5)NeuAc(1) A3G3S1 2417.8958 2417.8770 Trigalactosylated and monosialylated triantennary glycan 32 Hex(6)dHex(0)HexNAc(5)NeuAc(2) A3G3S2 2708.9912 2709.0052 Trigalactosylated and disialylated triantennary glycan 33 Hex(5)dHex(1)HexNAc(4)NeuAc(2) A2F1G2S2 2489.9169 2489.8896 Digalactosylated and disialylated biantennary glycan with outer arm fucose 34 Hex(5)dHex(1)HexNAc(4)NeuAc(2) FA2G2S2 2489.9169 2489.9233 Digalactosylated and disialylated biantennary glycan with core fucose 35 Hex(5)dHex(1)HexNAc(5)NeuAc(2) FA2BG2S2 2692.9963 2692.9821 Ddigalactosylated and disialylated biantennary glycan with bisecting GlcNAc and core fucose 36 Hex(6)dHex(0)HexNAc(5)NeuAc(2) A3G3S2 2708.9912 2708.9683 Trigalactosylated and disialylated triantennary glycan 37 Hex(6)dHex(1)HexNAc(5)NeuAc(2) A3F1G3S2 2855.0491 2855.0576 Trigalactosylated and disialylated triantennary glycan with outer arm fucose 37 Hex(6)dHex(0)HexNAc(5)NeuAc(2) A3G3S2 2708.9912 2708.9683 Trigalactosylated and disialylated triantennary glycan 38 Hex(6)dHex(1)HexNAc(5)NeuAc(2) FA3G3S2 2855.0576 2855.0464 Trigalactosylated and disialylated triantennary glycan with core fucose 39 Hex(6)dHex(0)HexNAc(5)NeuAc(2) A3G3S2 2708.9912 2708.9678 Trigalactosylated and disialylated triantennary glycan 40 Hex(6)dHex(1)HexNAc(5)NeuAc(2) A3F1G3S2 2855.0491 2855.0515 Trigalactosylated and disialylated triantennary glycan with outer arm fucose 41 Hex(6)dHex(1)HexNAc(5)NeuAc(3) FA3G3S3 3146.1446 3146.1404 Trigalactosylated and trisialylated triantennary glycan with core fucose 42 Hex(6)dHex(1)HexNAc(5)NeuAc(2) FA3G3S2 2855.0491 2855.0566 Trigalactosylated and disialylated triantennary glycan with core fucose 42 Hex(6)dHex(0)HexNAc(5)NeuAc(3) A3G3S3 3000.0866 3000.0679 Trigalactosylated and trisialylated triantennary glycan 42 Hex(6)dHex(1)HexNAc(5)NeuAc(3) FA3G3S3 3146.1446 3146.1682 Trigalactosylated and trisialylated triantennary glycan with core fucose 43 Hex(7)dHex(1)HexNAc(6)NeuAc(1) FA4G4S1 2929.0859 2929.0889 Tetragalactosylated and monosialylated triantennary glycan with core fucose 43 Hex(6)dHex(0)HexNAc(5)NeuAc(3) A3G3S3 3000.0866 3000.0842 Trigalactosylated and trisialylated triantennary glycan 43 Hex(6)dHex(1)HexNAc(5)NeuAc(2) FA3G3S2 2855.0491 2855.0486 Trigalactosylated and disialylated triantennary glycan with core fucose 44 Hex(6)dHex(1)HexNAc(5)NeuAc(3) FA3G3S3 3146.1446 3146.1479 Trigalactosylated and trisialylated triantennary glycan with core fucose 45 Hex(6)dHex(0)HexNAc(5)NeuAc(3) A3G3S3 3000.0866 3000.1042 Trigalactosylated and trisialylated triantennary glycan 46 Hex(7)dHex(0)HexNAc(6)NeuAc(2) A4G4S2 3074.1234 3074.1685 Tetragalactosylated and disialylated triantennary glycan 46 Hex(6)dHex(1)HexNAc(5)NeuAc(3) A3F1G3S3 3146.1446 3146.1733 Trigalactosylated and trisialylated triantennary glycan with outer arm fucose 47 Hex(6)dHex(1)HexNAc(5)NeuAc(3) FA3G3S3 3146.1446 3146.1306 Trigalactosylated and trisialylated triantennary glycan with core fucose 48 Hex(6)dHex(0)HexNAc(5)NeuAc(3) A3G3S3 3000.0866 3000.0886 Trigalactosylated and trisialylated triantennary glycan 49 Hex(6)dHex(1)HexNAc(5)NeuAc(3) A3F1G3S3 3146.1446 3146.1460 Trigalactosylated and trisialylated triantennary glycan with outer arm fucose 50 Hex(7)dHex(0)HexNAc(6)NeuAc(3) FA4G4S3 3365.2188 3365.1853 Tetragalactosylated and trisialylated triantennary glycan 51 Hex(6)dHex(1)HexNAc(5)NeuAc(3) FA3G3S3 3146.1446 3146.1055 Trigalactosylated and trisialylated triantennary glycan with core fucose 52 Hex(6)dHex(2)HexNAc(5)NeuAc(3) FA3F1G3S3 3292.2025 3292.2502 Trigalactosylated and trisialylated triantennary glycan with core fucose and outer arm fucose 53 Hex(7)dHex(0)HexNAc(6)NeuAc(3) A4G4S3 3365.1853 3365.2166 Tetragalactosylated and trisialylated triantennary glycan 53 Hex(7)dHex(1)HexNAc(6)NeuAc(3) FA4G4S3 3511.2767 3511.2839 Tetragalactosylated and trisialylated triantennary glycan with core fucose 54 Hex(7)dHex(0)HexNAc(6)NeuAc(4) A4G4S4 3656.3143 3656.3223 Tetragalactosylated and tetrasialylated triantennary glycan

[0050] 1 : Hex = hexose, dHex = deoxyhexose, HexNAc = N-acetylhexosamine, NeuAc = N-acetylneuraminic acid.

[0051] A total of 19 saccharide subclasses were classified according to the similar structural or compositional characteristics of the sugar peak members. The classification characteristics and calculation formulas of the saccharide subclasses are shown in the following table.

[0052] Table 2 Classification characteristics and calculation formulas of sugar subclasses.

[0053]

[0054] 2.4 Result judgment

[0055] 2.4.1 Identifying PCNSL patients

[0056] The sugar subclasses Ftria and TG serve as the main markers for identifying PCNSL patients.

[0057] The following table shows the results of quantifying cerebrospinal fluid N-glycans from 90 PCNSL patients according to the above method and comparing them between two groups of PCNSL patients and non-PCNSL patients. 28 glycopeaks (GPs) and 15 sugar subclasses were observed to have significant differences (see the following table in detail), and all adjusted p-values were < 0.05.

[0058] Table 3 Comparison of differences in relative contents of N-glycopeaks and sugar subclasses between PCNSL and non-PCNSL patients.

[0059] Glycan Peaks / Glyco - subclasses PCNSL (n = 60) mean(±SD) % Non-PCNSL (n = 30) mean(±SD) % Statistics p <![CDATA[P adj > GP1 0.789±0.384 0.554±0.243 <![CDATA[2.974 ａ > 0.003 0.006 GP2 1.944±0.903 1.636±0.460 <![CDATA[1.25 ａ > 0.213 0.284 GP3 2.680±0.816 2.222±0.836 <![CDATA[2.462 ｂ > 0.016 0.027 GP4 7.698±2.771 5.511±2.624 <![CDATA[3.552 ｂ > <0.001 <0.002 GP5 0.682±0.530 0.429±0.123 <![CDATA[4.288 ａ > <0.001 <0.002 GP6 1.999±0.594 1.571±0.457 <![CDATA[3.218 ａ > 0.001 0.002 GP7 1.075±0.357 0.824±0.210 <![CDATA[3.573 ａ > <0.001 <0.002 GP8 3.777±0.876 2.931±0.727 <![CDATA[4.254 ａ > <0.001 <0.002 GP9 1.329±0.433 0.938±0.319 <![CDATA[4.331 ｂ > <0.001 <0.002 GP10 0.354±0.211 0.381±0.157 <![CDATA[-1.476 ａ > 0.141 0.214 GP11 0.384±0.195 0.359±0.183 <![CDATA[0.579 ｂ > 0.564 0.605 GP12 0.684±0.222 0.529±0.181 <![CDATA[3.261 ｂ > 0.002 0.004 GP13 0.659±0.264 0.584±0.253 <![CDATA[1.275 ｂ > 0.206 0.284 GP14 2.595±0.696 1.842±0.694 <![CDATA[4.417 ａ > <0.001 <0.002 GP15 2.756±1.081 2.394±1.174 <![CDATA[1.439 ｂ > 0.154 0.229 GP16 3.129±1.056 2.302±0.979 <![CDATA[3.549 ｂ > <0.001 <0.002 GP17 0.677±0.203 0.793±0.319 <![CDATA[-1.25 ａ > 0.213 0.284 GP18 0.688±0.221 0.679±0.149 <![CDATA[0.013 ａ > 0.993 0.993 GP19 0.734±0.275 0.733±0.309 <![CDATA[0.021 ａ > 0.986 0.993 GP20 0.382±0.164 0.469±0.246 <![CDATA[-1.22 ａ > 0.224 0.287 GP21 7.189±1.323 6.399±1.277 <![CDATA[2.672 ｂ > 0.009 0.016 GP22 1.377±0.492 1.088±0.389 <![CDATA[2.772 ｂ > 0.007 0.013 GP23 0.303±0.149 0.485±0.196 <![CDATA[-4.16 ａ > <0.001 <0.002 GP24 4.772±0.761 3.873±0.740 <![CDATA[5.27 ｂ > <0.001 <0.002 GP25 0.661±0.302 0.824±0.530 <![CDATA[-0.929 ａ > 0.355 0.418 GP26 3.943±0.993 3.433±1.085 <![CDATA[2.197 ｂ > 0.031 0.051 GP27 1.273±0.552 1.790±0.750 <![CDATA[-3.21 ａ > 0.001 0.002 GP28 2.676±0.960 2.869±0.654 <![CDATA[-1.109 a > 0.271 0.330 GP29 2.277±0.828 1.965±0.678 <![CDATA[1.763 ａ > 0.079 0.125 GP30 19.227±6.272 23.655±6.685 <![CDATA[-3.054 ｂ > 0.003 0.006 GP31 1.015±0.287 1.225±0.264 <![CDATA[-3.319 ｂ > 0.001 0.002 GP32 0.312±0.236 0.307±0.181 <![CDATA[-0.608 ａ > 0.546 0.595 GP33 0.805±0.289 0.904±0.311 <![CDATA[-1.571 ａ > 0.117 0.182 GP34 2.460±0.752 2.692±0.803 <![CDATA[-1.31 ａ > 0.192 0.275 GP35 1.299±0.359 1.279±0.343 <![CDATA[0.24 ａ > 0.814 0.837 GP36 0.912±0.329 1.010±0.326 <![CDATA[-1.324 ｂ > 0.189 0.275 GP37 0.233±0.068 0.376±0.092 <![CDATA[-5.991 ａ > <0.001 <0.002 GP38 0.251±0.123 0.230±0.105 <![CDATA[0.89 ａ > 0.375 0.435 GP39 1.362±0.334 1.355±0.225 <![CDATA[-0.544 ａ > 0.59 0.624 GP40 0.608±0.207 0.792±0.210 <![CDATA[-3.959 ａ > <0.001 0.002 GP41 0.159±0.065 0.185±0.107 <![CDATA[-0.766 ａ > 0.445 0.499 GP42 1.164±0.322 1.243±0.359 <![CDATA[-1.168 ａ > 0.244 0.302 GP43 0.664±0.202 0.814±0.195 <![CDATA[-3.335 ｂ > 0.001 0.002 GP44 0.227±0.091 0.254±0.102 <![CDATA[-1.036 ａ > 0.302 0.361 GP45 3.495±1.421 3.733±1.663 <![CDATA[-0.522 ａ > 0.605 0.631 GP46 0.404±0.180 0.620±0.236 <![CDATA[-4.472 ａ > <0.001 <0.002 GP47 0.590±0.168 0.623±0.176 <![CDATA[-0.85 ｂ > 0.398 0.454 GP48 1.088±0.575 1.565±0.472 <![CDATA[-4.108 ａ > <0.001 <0.002 GP49 1.700±1.549 3.128±1.641 <![CDATA[-4.511 ａ > <0.001 <0.002 GP50 0.338±0.160 0.519±0.227 <![CDATA[-3.651 ａ > <0.001 <0.002 GP51 0.423±0.138 0.503±0.121 <![CDATA[-2.664 ｂ > 0.009 0.016 GP52 0.097±0.103 0.266±0.170 <![CDATA[-5.653 ａ > <0.001 <0.002 GP53 0.784±0.254 1.251±0.397 <![CDATA[-5.127 ａ > <0.001 <0.002 GP54 0.901±0.513 1.062±0.605 <![CDATA[-1.237 ａ > 0.218 0.284 M 3.723±1.110 3.517±1.401 <![CDATA[-0.753 ａ > 0.453 0.499 TG 25.499±5.624 19.608±5.490 <![CDATA[-4.669 ａ > <0.001 <0.002 BiS 29.453±7.402 23.842±7.645 <![CDATA[-3.316 ａ > 0.001 0.002 BiA 50.605±5.851 52.189±6.246 <![CDATA[1.17 ａ > 0.245 0.302 TriA 13.774±3.167 17.041±3.443 <![CDATA[3.886 b > <0.001 <0.002 TetrA 2.444±0.874 3.412±1.233 <![CDATA[3.766 b > <0.001 <0.002 HA 16.218±3.861 20.453±4.436 <![CDATA[4.611 b > <0.001 <0.002 S0 33.575±8.309 26.301±8.192 <![CDATA[-3.89 ａ > <0.001 <0.002 S1 20.411±2.284 18.363±2.324 <![CDATA[-3.924 ａ > <0.001 <0.002 S2 35.342±6.930 41.344±6.848 <![CDATA[3.845 ａ > <0.001 <0.002 S3 9.763±3.027 12.923±3.344 <![CDATA[3.984 b > <0.001 <0.002 S4 0.901±0.513 1.062±0.605 <![CDATA[1.237 b > 0.218 0.284 TS 123.991±21.238 144.067±21.690 <![CDATA[4.151 ａ > <0.001 <0.002 cF 50.710±8.724 43.745±9.163 <![CDATA[-3.471 b > <0.001 <0.002 Ftria 5.373±1.931 7.584±2.032 <![CDATA[5.033 b > <0.001 <0.002 cFtria 2.745±0.565 3.166±0.708 <![CDATA[3.021 ａ > 0.003 0.006 cFa 22.682±2.513 22.324±3.209 <![CDATA[-0.381 b > 0.706 0.123 cFn 28.028±7.084 21.422±6.651 <![CDATA[-4.207 ａ > <0.001 <0.002 oaF 8.010±1.919 9.457±2.141 <![CDATA[3.214 b > 0.001 0.002

[0060] a: Mann-Whitney U test, b: t test The sensitivity and specificity of the above 15 sugar subclasses in differentiating PCNSL and non-PCNSL patients were evaluated using the ROC curve (Table 4). The AUC (area under the curve) of Ftria was 0.827 ( Figure 7 A), with a sensitivity of 90.0% and a specificity of 70.0%. The AUC of another sugar subclass (TG) was 0.791 ( Figure 7 B), with a sensitivity of 71.7% and a specificity of 83.3%. These results indicate that Ftria and TG have the value of serving as markers for identifying PCNSL patients because their accuracy is better than that of other sugar subclasses.

[0061] Table 4 Area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and optimal diagnostic threshold of sugar subclasses with statistically significant differences for diagnosing PCNSL.

[0062]

[0063] 2.4.2 Prognosis assessment of PCNSL patients

[0064] Based on the patient's age combined with the test results of GP6 and GP27, refer to Figure 4 the indicators to judge the probability of the patient's survival at 24 months and 60 months.Figure 4 The usage method of the model is to add the scores corresponding to each variable of age, GP6, and GP27, and the final total score corresponds to the 24-month and 60-month survival probabilities on the bottom scale.

[0065] All PCNSL patients who had their initial consultations and diagnoses as of December 31, 2021 and participated in this study were followed up. Among the entire patient population, 12 patients were lost to follow-up for various reasons, and 16 patients died. For the prognostic study, only patients treated in our hospital were included. Before the start of treatment, cerebrospinal fluid samples of these patients were collected. To evaluate whether N-glycan abundance, age, cerebrospinal fluid protein concentration, serum lactate dehydrogenase (LDH), and methotrexate (MTX) dose could be used as predictors of the prognostic outcome of PCNSL patients, the overall survival (OS) analysis was performed on patients with available survival data using the Cox proportional hazards model.

[0066] In the univariate Cox analysis, there was a significant correlation between GP2, GP6, GP27, age and prognosis (p < 0.05), as shown in the following table.

[0067] Table 5 Univariate and multivariate survival analysis of PCNSL patients stratified by sugar peaks, sugar subclasses, and laboratory parameters.

[0068]

[0069]

[0070]

[0071] The estimation of survival time was performed using the Kaplan-Meier method, and the comparison of survival curves was performed using the Log-rank test. Among many factors, GP27 (a biantennary glycan with digalactosylation and disialylation, with fucose as the core, FA2G2S2) showed a hazard ratio less than 1, indicating a positive correlation between higher GP27 levels and better prognosis. On the contrary, the hazard ratios of the other two glycans and age were greater than 1, suggesting that increased levels of these factors were associated with adverse outcomes. These glycans include GP2 (a biantennary glycan with fucose as the core, FA2G0) and GP6 (a monogalactosylated biantennary glycan with a 1-3 linkage and fucose as the core, FA2[3]G1).

[0072] In the multivariate Cox analysis, the results showed that age and GP27 were independent prognostic factors significantly associated with the survival of PCNSL patients. However, GP2 and GP6 did not show a significant correlation with PCNSL survival as independent prognostic factors.

[0073] A final Cox proportional hazards model for PCNSL was constructed based on age, GP6, and GP27 (see the table below) and a nomogram ( Figure 4 ). The p-values of the Wald, Log-rank, and likelihood ratio tests were all less than or equal to 0.001. To further evaluate the predictive ability of the model, the concordance index (C-index) was calculated, and the result was 0.804 (95% CI: 0.68, 0.927).

[0074] Table 6 Results of the Cox proportional hazards regression model for predicting the survival probability of PCNSL patients.

[0075]

[0076] Figure 4 It is a nomogram model for predicting the overall survival (OS) of PCNSL patients at 24 months and 60 months. The usage method of this model is to add up the scores corresponding to each variable, and the final total score corresponds to the 24-month and 60-month survival probabilities on the bottom scale.

[0077] We also evaluated the previously published prognostic indicators (IELSG) in a cohort of patients (36 patients) with complete evaluation data. The results showed that with the increase in age and the elevation of GP6, it was associated with an increased risk of death, while the decrease in GP27 was associated with a decreased risk of death. The calibration curve showed a high degree of consistency between the predicted survival probability and the actually observed survival probability within the intervals of 24 months and 60 months ( Figure 5 , with the predicted OS of the nomogram model on the abscissa and the actual OS on the ordinate). Generally speaking, the nomogram for PCNSL has quite good discrimination and calibration ability. At the same time, we evaluated the previously published prognostic indicators (IELSG) in a cohort of patients (36 patients) with complete evaluation data. However, as Figure 6 shown, no significant association was shown between the IELSG indicator and the overall survival (OS), suggesting potential limitations of the existing prognostic markers in our population. The carbohydrate risk prediction model in this study has better predictive accuracy compared to the IELSG prognostic indicator ( Figure 6 ). This indicates that an updated prognostic index may be needed.

[0078] The baseline characteristics of the patients participating in this study were:

[0079] Table 7 Baseline characteristics of the subjects.

[0080]

[0081] a: Chi-Square test, b: Mann-Whitney U test

[0082] There were 60 patients in the PCNSL group, including 35 males and 25 females. Pathological diagnosis showed that 52 cases were diffuse large B-cell tumors, 7 cases were B-cell lymphomas, and 1 case was undifferentiated subtype lymphoma. The median age at diagnosis was 56 years. The non-PCNSL group included 15 patients with gliomas and 15 patients with brain metastases, including 2 cases of breast cancer, 1 case of small cell lung cancer, and 12 cases of lung adenocarcinoma. There were 19 males and 11 females in these cases, and the median age at diagnosis was 59 years. In addition, the median cerebrospinal fluid protein concentrations at diagnosis in the two groups were 0.55 g / L and 0.56 g / L, respectively. Since routine tests were not performed in some patient groups, the test results of IL-10 and LDH were not included. No statistically significant differences were observed between the groups in terms of age, gender, and cerebrospinal fluid protein concentration..

Claims

1. A method for detecting the cerebrospinal fluid N-glycome of PCNSL patients, comprising the following steps: Extract the cerebrospinal fluid of PCNSL patients, remove cells, denature and reduce proteins, cleave N-glycans with PNGase F, label N-glycans with 2-aminobenzamide, perform HILIC liquid chromatography and mass spectrometry detection, and analyze the detection results.

2. The method according to claim 1, wherein The analysis method of the detection results is to classify the sugar peaks according to the relative intensity of the sugar peaks, expressed as a percentage (%) of the total sugar peak area, into 54 sugar groups (named GP1 - GP54, and the descriptions of each sugar peak are shown in Table 1) and 19 subclasses (named M, TG, BiS, BiA, TriA, TetrA, HA, S0, S1, S2, S3, S4, TS, cF, Ftria, cFtria, cFa, cFn, oaF, and the descriptions and calculation methods of each subclass are shown in Table 2).

3. The method according to claim 2, characterized in that, The analysis method of the detection results is to extract the relative contents of GP6, GP27, Ftria or TG in the detection results and perform analysis.

4. The method according to claim 3, characterized in that, The analysis method of the detection results is to compare the relative content of Ftria with 5.51% or (7.584 ± 2.032)%, and compare the relative content of TG with 23.47% or (25.499 ± 5.624)%.

5. The method according to claim 3, characterized in that, The analysis method of the detection results is to compare the relative contents of GP6 and GP27 with Figure 4 of the specification drawings.

6. The method according to claim 1, characterized in that The denaturation uses the surfactant RapiGest SF, and the reduction uses TCEP.

7. The method according to claim 1, characterized in that The liquid chromatography analysis method is as follows: Use a 2.1 x 150mm BEH Glycan (HILIC) column in combination with an Acquity UPLC system equipped with a Waters temperature control module and a Waters Acquity fluorescence detector. The column temperature is set at 60 °C. The mobile phase uses two buffer solutions. Mobile phase A is 30 mM ammonium formate with a pH of 4.5, and mobile phase B is pure acetonitrile. Perform a 70-minute linear gradient with a flow rate of 0.5 mL / min. The concentration of buffer solution A at the start of the gradient is 22%, which gradually increases to 40% within 50 minutes, then rises to 70%, and finally returns to 22% to end. The elution of N-glycans is measured by fluorescence detection, with an excitation wavelength of 330 nm and a detection wavelength of 420 nm.

8. The method according to claim 1, characterized in that, The mass spectrometry analysis method is as follows: The 2-AB-labeled carbohydrates are detected by an Xevo G2-S system in ESI+ mode. The low collision energy is set at 6 V, and the elevated collision energy (ramped from 18 V to 35 V) is used to obtain precursor ions (MS) and their corresponding fragment data (MS / MS). The scan time is set at 0.5 seconds (total duty cycle is 1 second). The desolvation gas and source temperature are maintained at 450°C and 120°C respectively. The capillary and cone voltages are set at 3000 V and 40 V respectively. The transfer collision energy is set at 6 V. The flow rates of the desolvation and cone gases are 800 L / h and 100 L / h respectively, and the m / z scan range is 650 - 2500.

9. The method according to claim 1, characterized in that, The mass spectrometry data described above are processed by Waters MassLynx MaxEnt software to obtain deconvoluted mass data.

10. Use of the detection results of sugar subclasses Ftria, TG and sugar peaks GP6, GP27 obtained by the method according to claim 1 in the preparation of a diagnostic or prognostic evaluation kit, instrument and software for PCNSL.

11. A sample pretreatment kit for detecting the N-glycome in the cerebrospinal fluid of PCNSL patients, comprising reagents A, B, C, D, E, and F, and the components of each reagent are: Reagent A: 50 mmol / L ammonium bicarbonate solution; Reagent B: 10% (W / V) RapiGest SF solution; Reagent C: 80 mmol / L TCEP solution; Reagent D: 5 μg / μL PNGase F; Reagent E: ethanol; Reagent F: 70% aqueous acetonitrile solution.

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