Use of IgG Fc N-glycopeptide as a marker to determine or assist in the selection of lung cancer treatment options

Abstract

The present invention relates to the use of IgG Fc N-glycopeptide as a marker for determining or assisting the selection of a lung cancer treatment regimen. Specifically, the present invention relates to the use of a reagent for detecting IgG Fc N-glycopeptide in preparing a kit for predicting the therapeutic effects of different clinical treatments for lung cancer and / or guiding the selection of clinical treatments for lung cancer, wherein the peptide sequence of the N-glycopeptide is Glu Glu Gln Tyr Asn 180 Ser Thr Tyr Arg (IgG1 subtype) or Glu Glu Gln Phe Asn 176 Ser Thr Phe Arg (IgG2 subtype), glycoforms of the N-glycopeptide have any of the following glycosylation modification patterns: GlcNAc2-Man3-GlcNAc2-Fuc; Gal-GlcNAc2-Man3-GlcNAc2; Gal-GlcNAc2-Man3-GlcNAc2-Fuc; Gal2-GlcNAc2-Man3-GlcNAc2; Gal2-GlcNAc2-Man3-GlcNAc2-Fuc; Gal2-GlcNAc3-Man3-GlcNAc2; Sia-Gal-GlcNAc2-Man3-GlcNAc2-Fuc and Sia-Gal2-GlcNAc2-Man3-GlcNAc2-Fuc.

Description

Technical Field

[0001] The present invention relates to individualized markers and methods for predicting clinical treatment effects of lung cancer and / or guiding the selection of clinical treatment methods for lung cancer. Specifically, the present invention relates to providing a preferred treatment method for lung cancer patients, such as radiotherapy, surgical treatment, chemotherapy or targeted therapy, based on the ratio of the relative intensities of disease-specific IgG Fc N-glycopeptides in the serum or plasma of lung cancer patients, to guide the clinical treatment of lung cancer. Background Art

[0002] Worldwide, the incidence and mortality of lung cancer are both the highest among malignant tumors, and the 5-year survival rate of patients is about 20%. According to clinical and histopathological data, lung cancer can be divided into non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), of which NSCLC accounts for about 85% and SCLC accounts for about 15%. Non-small cell lung cancer is further divided into three types: squamous cell carcinoma, adenocarcinoma, and large cell carcinoma.

[0003] The choice of lung cancer treatment is mainly based on the pathological type and stage of the tumor. Common treatment methods include surgery, radiotherapy, chemotherapy, targeted therapy, etc. Patients with early non-small cell lung cancer are mostly treated with surgery, while patients with small cell carcinoma and mid-to-late stage non-small cell lung cancer are mostly treated with chemotherapy and radiotherapy. For patients with gene mutations, targeted therapy can be considered. The etiology and molecular mechanism of lung cancer are very complex. Recurrence, metastasis and drug resistance make it difficult for most lung cancer patients to achieve long-term survival after treatment. Therefore, individualized prediction of the treatment effect of lung cancer treatment plans and timely guidance on the rational selection of lung cancer treatment plans have important clinical significance and social value for prolonging patient survival, improving patient quality of life, and reducing treatment toxicity and side effects.

[0004] At present, the clinical evaluation of the treatment effect of lung cancer patients is mainly based on imaging examinations and blood tumor marker detection. Imaging examinations evaluate the effect of tumor treatment by measuring the size of the tumor, but the examination results are generally lagging, and tumor shrinkage is not necessarily positively correlated with the prognosis of tumor treatment. Tumor markers refer to active substances such as antigens, enzymes, hormones, etc. produced by tumor cells and released into body fluids or tissues. Monitoring their concentration changes can assist in evaluating the effect of tumor treatment, but the specificity of single indicator detection is low, and multiple tumor markers are often used in clinical practice. With the application of molecular diagnostic technology in the field of tumors, liquid biopsy has become an emerging blood test method. It monitors circulating tumor DNA (ctDNA), circulating tumor cells (CTC), circulating non-coding RNA (ncRNA), exosomes and other substances to evaluate the effect of tumor treatment in real time. These indicators are positively correlated with tumor size and cannot be warned or predicted in advance. In order to predict the treatment effect of different treatment plans for lung cancer patients in an individualized manner, it is necessary to invent a set of simple, economical and minimally invasive markers and their detection and application methods.

[0005] Glycosylation is one of the important post-translational modifications of proteins. Changes in glycosylation can significantly affect the structure and function of glycoproteins, and its changes are related to a variety of physiological and pathological states, including the occurrence and development of tumors. Immunoglobulin G (IgG) is the most important antibody component in the immune system. Its Fc N-glycosylation is involved in regulating the pro-inflammatory or anti-inflammatory activity of IgG and is closely related to the physiological and pathological states of various cancers. Summary of the invention

[0006] The present inventors utilized a previously reported method (see Wang Y, Song G, Wang Y, et al. Elevated Serum Levels of Circulating Immunoinflammation-Related Protein Complexes Are Associated with Cancer [J]. Journal of Proteome Research, 2014, 13(2): 710), using non-denaturing polyacrylamide gel electrophoresis to separate immune inflammation-related protein complexes (IIRPCs) in serum or plasma, using denaturing polyacrylamide gel electrophoresis to separate IgG heavy chains in immune inflammation-related complexes, using IgG heavy chains obtained by trypsin digestion, using carbon nitride enrichment to obtain IgG Fc N-glycopeptides in the IgG heavy chain trypsin digestion products, and using mass spectrometry to detect and identify the relative intensity of IgG Fc N-glycopeptides enriched in serum or plasma. On this basis, the inventors unexpectedly found that the disease-specific IgG Fc N-glycopeptide relative intensity ratio in the serum or plasma of lung cancer patients is closely related to the efficacy of radiotherapy, surgical treatment, chemotherapy (including but not limited to pemetrexed (plus platinum) chemotherapy, gemcitabine (plus platinum) chemotherapy) and targeted therapy (including but not limited to icotinib targeted therapy, gefitinib targeted therapy, anlotinib targeted therapy).

[0007] In a specific embodiment of the present invention, the inventors used electrophoresis to separate disease-specific IgG heavy chains (heavy chain constant region amino acid sequences see SEQ ID NO: 3 and 4) in serum, followed by trypsin enzymatic hydrolysis and glycopeptide enrichment, and mass spectrometry to detect Fc N-glycopeptides. Then, the relative intensities of glycopeptides with one or two identical monosaccharide residues at the same glycosylation modification site in the Fc segment of the same IgG subtype were ratioed to obtain a glycopeptide relative intensity ratio. In the study of the correlation between the obtained glycopeptide relative intensity ratio and different lung cancer therapies, we unexpectedly discovered a marker that can be used to predict the efficacy of a clinical treatment for lung cancer or to guide the selection of a clinical treatment for lung cancer.

[0008] Thus, in one aspect, the present invention provides a use of a reagent for detecting IgG Fc N-glycopeptide in the preparation of a kit for predicting the therapeutic effects of different clinical treatments for lung cancer and / or guiding the selection of clinical treatments for lung cancer, wherein the peptide sequence of the IgG Fc N-glycopeptide is an IgG1 subtype polypeptide sequence as shown in SEQ ID NO: 1 or an IgG2 subtype polypeptide sequence as shown in SEQ ID NO: 2, and the glycoform of the IgG Fc N-glycopeptide is selected from any one of the following tables:

[0009]

[0010]

[0011] Note: GlcNAc2-Man3-GlcNAc2 represents the common basic structure of IgG Fc N-sugar, GlcNAc represents N-acetylglucosamine residue, Man represents mannose residue, Fuc (F) represents fucose residue, Gal (G) represents galactose residue, Sia (S) represents sialic acid residue, and the number represents the number of monosaccharide residues. (See, Epp A, Sullivan KC, Herr AB, et al. Immunoglobulin Glycosylation Effects in Allergy and Immunity [J]. Current Allergy & Asthma Reports, 2016, 16 (11): 79).

[0012] In a specific embodiment of the present invention, the glycoform of the IgG Fc N-glycopeptide is Asn in the sequence shown in SEQ ID NO: 1 or 2. 180 (IgG1 subtype) or Asn 176 (IgG2 subtype) site, preferably, the reagent is used to detect IgG Fc N-glycopeptide in the serum or plasma of lung cancer patients before receiving anti-cancer treatment.

[0013] In a specific embodiment of the present invention, IgG Fc N-glycopeptide is detected in serum or plasma samples by the following steps:

[0014] a) Separating immune inflammatory related protein complexes (IIRPCs) in serum or plasma by non-denaturing polyacrylamide gel electrophoresis;

[0015] b) separating the IgG heavy chains in the immune inflammation-related complex obtained in step a) by denaturing polyacrylamide gel electrophoresis;

[0016] c) subjecting the IgG heavy chain obtained in step b) to trypsin digestion;

[0017] d) enriching the glycopeptides in the IgG heavy chain tryptic digest obtained in step c) using carbon nitride; and

[0018] e) identifying the IgG Fc N-glycopeptide enriched in step d) by mass spectrometry and obtaining its relative intensity.

[0019] Further preferably, in a specific embodiment of the present invention, IgG1 G1F, IgG1 G2F, IgG2 G0F, IgG2 G1, IgG2 G1F, IgG2 G2, IgG2 G2F, IgG2 G2N, IgG2G1FS and IgG2 G2FS glycopeptides are detected in samples of patients with lung cancer, and their relative intensities are obtained;

[0020] Further preferably, the relative intensity ratios of the following IgG Fc N-glycopeptides are significantly correlated with the therapeutic effects of different lung cancer treatments:

[0021] IgG1 G2F to G1F, IgG2 G2F to G0F, IgG2 G2 to G1, IgG2 G2F to G1F, IgG2 G2F to G2, IgG2 G2N to G2 and / or IgG2 G2FS to G1FS.

[0022] In a further aspect, the lung cancer of the present invention is non-small cell lung cancer or small cell lung cancer; preferably, the non-small cell lung cancer is lung adenocarcinoma or squamous cell carcinoma.

[0023] In a further embodiment, the clinical treatment method is selected from one or more of surgical treatment, radiotherapy, chemotherapy and targeted therapy. Preferably, the chemotherapy is selected from one or more of pemetrexed and gemcitabine treatment; the targeted therapy is selected from one or more of icotinib, gefitinib and anlotinib.

[0024] In a further embodiment of the present invention, the therapeutic effects of different clinical treatments for lung cancer are predicted and / or the selection of clinical treatments for lung cancer is guided by calculating the ratio of the relative intensities of glycopeptides that differ by one or two identical monosaccharide residues at the same glycosylation modification site in the Fc peptide segment of the same IgG subtype.

[0025] In a specific embodiment of the present invention, the therapeutic effects of different clinical treatments for lung cancer are predicted and / or the selection of clinical treatments for lung cancer is guided based on one or more of the following glycopeptide relative intensity ratios:

[0026] G2F to G1F of IgG1; G2F to G0F of IgG2; G2 to G1 of IgG2; G2F to G1F of IgG2; G2F to G2 of IgG2; G2N to G2 of IgG2; and G2FS to G1FS of IgG2;

[0027] Preferably, whether to select radiotherapy is determined based on the ratio of G2F to G1F of IgG1; whether to select surgical treatment is determined based on the ratio of G2F to G0F of IgG2, G2F to G1F of IgG2, and G2FS to G1FS of IgG2; chemotherapeutic drugs are selected based on the ratio of G2 to G1 of IgG2, and G2F to G2 of IgG2; and / or targeted therapy drugs are selected based on the ratio of G2N to G2 of IgG2 and G2FS to G1FS of IgG2.

[0028] In another aspect, the present invention provides the use of a ratio of relative intensities of IgG Fc N-glycopeptides in serum or plasma of a subject as a marker in the preparation of a kit for selecting a treatment for a subject, wherein the ratio of relative intensities of IgG Fc N-glycopeptides is selected from one or more of the following:

[0029] G2F to G1F of IgG1; G2F to G0F of IgG2; G2 to G1 of IgG2; G2F to G1F of IgG2; G2F to G2 of IgG2; G2N to G2 of IgG2; and G2FS to G1FS of IgG2;

[0030] Preferably, the subject is a lung cancer patient;

[0031] Preferably, the treatment method is selected from one or more of surgical treatment, radiotherapy, chemotherapy and targeted therapy. Preferably, the chemotherapy is selected from one or more of pemetrexed and gemcitabine treatment; the targeted therapy is selected from one or more of icotinib, gefitinib and anlotinib.

[0032] In another aspect, the present invention provides an in vitro method for predicting the therapeutic effects of different clinical treatments for lung cancer and / or guiding the selection of clinical treatments for lung cancer, the method comprising the following steps:

[0033] a) Separating immune inflammatory related protein complexes (IIRPCs) in serum or plasma by non-denaturing polyacrylamide gel electrophoresis;

[0034] b) separating the IgG heavy chains in the immune inflammation-related complex obtained in step a) by denaturing polyacrylamide gel electrophoresis;

[0035] c) subjecting the IgG heavy chain obtained in step b) to trypsin digestion;

[0036] d) enriching the glycopeptides in the IgG heavy chain trypsin hydrolysate obtained in step c) using carbon nitride;

[0037] e) identifying the enriched IgG glycopeptides obtained in step d) by mass spectrometry and obtaining their relative intensities;

[0038] f) calculating the ratio of the relative intensities of glycopeptides with the same glycosylation modification site at the same glycosylation modification site in the Fc peptide of the same IgG subtype from the relative intensities obtained in e); preferably, calculating the ratio of G2F to G1F of IgG1; G2F to G0F of IgG2; G2 to G1 of IgG2; G2F to G1F of IgG2; G2F to G2 of IgG2; G2N to G2 of IgG2; and G2FS to G1FS of IgG2;

[0039] g) comparing the ratio obtained in f) with the standard value to select a clinical treatment method for the subject;

[0040] Preferably, those skilled in the art can determine the standard value according to the method described in the present invention, for example, but not limited to, the values ​​described in the following Table 16.

[0041] In another aspect, the present invention relates to a computer-readable storage device that may store computer-executable instructions that, if executed by a machine (eg, a computer, a processor), cause the machine to perform the method of the present invention.

[0042] Common forms of computer-readable storage devices may include, but are not limited to, floppy disks, disks, hard disks, tapes, other magnetic media, application specific integrated circuits (ASICs), compact disks (CDs), other optical media, random access memory (RAM), read-only memory (ROM), memory chips or memory cards, solid-state devices (SSDs), memory sticks, data storage devices, and other media from which a computer, processor, cloud in SAS mode, or other electronic device may read.

[0043] In another aspect, the present invention provides a computer-readable storage device for selecting a clinical treatment for lung cancer for a subject, comprising:

[0044] a) a data input device for inputting the relative intensity values ​​of each IgG glycopeptide in the serum or plasma of the subject obtained by the mass spectrometer;

[0045] b) a data processing device for calculating the ratio of the relative intensities of glycopeptides with the same glycosylation modification site in the Fc peptide segment of the same IgG subtype that differ by one or two identical monosaccharide residues from the relative intensity values ​​obtained in a); and

[0046] c) an output device for comparing the value obtained in b) with a standard value, so as to select a clinical treatment method for the subject.

[0047] According to the computer-readable storage device of the present invention, the clinical treatment method is selected from one or more of surgical treatment, radiotherapy, chemotherapy and targeted therapy. Preferably, the chemotherapy is selected from one or more of pemetrexed and gemcitabine treatment; the targeted therapy is selected from one or more of icotinib, gefitinib and anlotinib.

[0048] According to the device of the present invention, the data processing device in step b) is used to calculate the following glycopeptide relative intensity ratios:

[0049] G2F to G1F of IgG1; G2F to G0F of IgG2; G2 to G1 of IgG2; G2F to G1F of IgG2; G2F to G2 of IgG2; G2N to G2 of IgG2; and G2FS to G1FS of IgG2.

[0050] In a further aspect, the present invention provides a device for selecting a clinical treatment for lung cancer for a subject, comprising:

[0051] i) Non-denaturing polyacrylamide gel electrophoresis apparatus, used to separate immune-inflammatory related protein complexes in serum or plasma;

[0052] ii) Denaturing polyacrylamide gel electrophoresis apparatus for separation of IgG heavy chains from immune-inflammatory related complexes;

[0053] iii) a trypsin treatment device, used for trypsinizing IgG heavy chains;

[0054] iv) a carbon nitride enrichment device for enriching IgG Fc N-glycopeptides from IgG heavy chain trypsin digests;

[0055] v) a mass spectrometer to identify the enriched IgG Fc N-glycopeptides and obtain their relative intensities; and

[0056] vi) A computer readable storage device according to the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 : Representative property spectrum of disease-specific IgG Fc N-glycopeptide in the serum of a lung cancer patient at the time of treatment (the dotted line represents the peptide sequence of SEQ ID NO: 1 (Glu Glu Gln Tyr Asn 180 Ser Thr Tyr Arg) as the IgG1 glycopeptide; the dot-dashed line represents the peptide sequence of SEQ ID NO: 2 (Glu Glu Gln Phe Asn 176IgG2 glycopeptide (Ser Thr PheArg); ■ (N), N-acetylglucosamine; ● (M), mannose; ○ (G), galactose; ◆ (S), sialic acid; ▲ (F), fucose). DETAILED DESCRIPTION

[0058] The following examples are provided to facilitate a better understanding of the present invention, but are not intended to limit the present invention. The research subjects included serum samples of 48 patients with lung cancer (including small cell lung cancer and non-small cell lung cancer, such as lung adenocarcinoma and squamous cell carcinoma) who were followed up and received surgery (15 cases), radiotherapy (10 cases), chemotherapy (pemetrexed (7 cases) or gemcitabine (6 cases)) or targeted therapy (icotinib (13 cases), gefitinib (4 cases) or anlotinib (4 cases)).

[0059] In a specific embodiment of the present invention, the separation, enzymatic hydrolysis, enrichment, detection, identification of disease-specific IgG Fc N-glycopeptides in serum provided by the present invention and its application in predicting the efficacy of clinical treatments for lung cancer or guiding the selection of clinical treatments for lung cancer are achieved by the following steps:

[0060] 1) Separation of immune-inflammatory related protein complexes (IIRPCs) in serum by non-denaturing polyacrylamide gel electrophoresis;

[0061] 2) separating the disease-specific IgG heavy chains in the immune inflammation-related complexes in step 1) by denaturing polyacrylamide gel electrophoresis;

[0062] 3) digesting the disease-specific IgG heavy chain separated in step 2) with trypsin;

[0063] 4) enriching the disease-specific IgG heavy chain enzymatic hydrolysate obtained in step 3) using carbon nitride;

[0064] 5) performing mass spectrometry identification on the glycopeptides enriched in step 4);

[0065] 6) When analyzing the relative intensity of disease-specific IgG Fc N-glycopeptides, IgG1 G1F, IgG1 G2F, IgG2 G0F, IgG2 G1, IgG2 G1F, IgG2 G2, IgG2 G2F, IgG2 G2N, IgG2 G1FS and IgG2 G2FS glycopeptides can be detected in each sample of the present invention, and their relative intensities can be obtained;

[0066] 7) using the relative intensities of the glycopeptides obtained in step 6), calculate the relative intensity ratios of IgG1 G2F / G1F, IgG2 G2F / G0F, IgG2G2 / G1, IgG2 G2F / G1F, IgG2 G2F / G2, IgG2 G2N / G2, and IgG2 G2FS / G1FS;

[0067] 8) Correlating the relative intensity ratio of the glycopeptides obtained in step 7) with the different treatments for lung cancer patients selected in the example to obtain the corresponding reference ranges of the different clinical treatments shown in Table 16, which can be used to predict the efficacy of clinical treatments for lung cancer and guide the selection of clinical treatments for lung cancer.

[0068] In the present invention, IIRPCs are disease-specific proteins, which are highly expressed in cancer patients and almost not expressed in normal people, see Wang Y, Song G, Wang Y, et al., Elevated Serum Levels of Circulating Immunoinflammation-Related Protein Complexes Are Associated with Cancer [J]. Journal of Proteome Research, 2014, 13 (2): 710. Identification of IgG glycosylation modification in IIRPCs in lung cancer patients can obtain disease-specific IgG glycosylation modification. Compared with the analysis of total IgG glycosylation modification in serum, the present invention has strong specificity and high sensitivity, and can more accurately reflect the patient's pathological state and immune system function.

[0069] In addition, the serum volume used in the present invention is small (10 μL), and the operation method is simple, easy and cheap. Carbon nitride is a chemical synthetic material that is easy to prepare, and is more stable than natural glycopeptide enrichment materials such as poplar fluff, and the enrichment method has good reproducibility. The detection method of the present invention can realize the simultaneous detection of glycopeptides with glycopeptide structures of IgG1 G1F, IgG1 G2F, IgG2 G0F, IgG2 G1, IgG2 G1F, IgG2 G2, IgG2 G2F, IgG2 G2N, IgG2 G1FS and IgG2 G2FS in a sample in the same mass spectrum, according to the multiple indicators of the relative intensity ratio of IgG1 G2F / G1F, IgG2 G2F / G0F, IgG2 G2 / G1, IgG2 G2F / G1F, IgG2 G2F / G2, IgG2G2N / G2, IgG2 G2FS / G1FS, to achieve individualized prediction of the clinical treatment efficacy of lung cancer, and guide the selection of clinical treatment of lung cancer.

[0070] The methods in the following embodiments, unless otherwise specified, are all performed according to conventional methods.

[0071] Example 1 Isolation, Detection and Identification of Disease-Specific IgG Fc N-Glycopeptides in Serum

[0072] 1. Isolation method of disease-specific IgG Fc N-glycopeptide in serum

[0073] 10 μL of serum was collected from each of the 48 lung cancer patients before treatment, and IIRPCs were separated by non-denaturing polyacrylamide gel electrophoresis with a concentration gradient of 4% to 10%. The band corresponding to IIRPCs (molecular weight of 200 to 700 kDa) was cut out, and 300 μL of a balanced solution containing 0.03 g / mL dithiothreitol (formula: 25 mL of 1.5 M tris(hydroxymethyl)aminomethane, 40 mL of glycerol, 8 g of sodium dodecyl sulfate, and dilute to 400 mL with deionized purified water) was added, reacted at 37°C for 1 hour, the supernatant was discarded, and after washing three times with water, 300 μL of a balanced solution containing 0.12 g / mL iodoacetamide was added, and the mixture was reacted at room temperature in the dark for 45 minutes. After washing three times with water, the protein complex was separated for a second time by 12% sodium dodecyl sulfate denaturing polyacrylamide gel electrophoresis to obtain disease-specific IgG heavy chain (~55 kDa), stained with Coomassie brilliant blue overnight, and then the background color was removed with water.

[0074] Cut off the gel dots of IgG heavy chain and crush them into pieces of about 0.2mm. 3 , add 50% acetonitrile / 25mM ammonium bicarbonate for decolorization. After about 1 hour, the decolorization is complete, discard the supernatant, add 100% acetonitrile to dehydrate and harden the gel block, discard the supernatant, and let the gel block stand until it is dry. Add about 15μL of trypsin solution (12.5ng / μL, prepared with 25mM ammonium bicarbonate), place at 4℃ for about 1 hour to fully hydrate the gel block, add 25mM ammonium bicarbonate to cover the gel surface, place at 37℃ for about 16 hours, and aspirate the enzymatic solution to dryness.

[0075] Disperse 2 mg of carbon nitride (g-C3N4) powder in 1 mL of 80% acetonitrile solution and vortex for 30 seconds to prepare a dispersion. Take 60 μL of the dispersion and add it to the enzymatically dried sample, vortex for 30 seconds, shake and adsorb for 1 hour under light-proof conditions, centrifuge at 15,000 × g for 5 minutes, and discard the supernatant. Add 80% acetonitrile to the precipitate, vortex for 2 minutes, centrifuge at 15,000 × g for 5 minutes, discard the supernatant, repeat three times, and wash away nonspecifically enriched peptides. Add 0.025% ammonia solution to the g-C3N4 precipitate adsorbed with glycopeptides, shake for 1 hour, centrifuge at 15,000 × g, aspirate the supernatant, obtain an enriched glycopeptide aqueous solution, and vacuum freeze-dry for later use.

[0076] 2. Detection and identification of IgG Fc N-glycopeptide

[0077] 1) Redissolve the evaporated sample with 2 μL of deionized pure water, take 0.3 μL of the re-dissolved solution and spot it on the MTPAnchorChipTM target. After evaporation, cover the sample trace with 0.3 μL of 20 mg / mL 2,5-dihydroxybenzoic acid solution, and perform mass spectrometry analysis after evaporation.

[0078] Detection instrument: Fourier transform ion cyclotron resonance mass spectrometer equipped with matrix-assisted laser desorption ionization source, ApexControl 3.0.0 data acquisition software and Data Analysis 4.0 (Bruker Daltonics) data processing software.

[0079] Mass spectrometry conditions: Nd:YAG laser, laser wavelength 355 nm, positive ion mode.

[0080] Since the types of disease-specific IgG Fc N-glycopeptides in the serum of patients are the same, the present invention only lists the mass spectrometry results of disease-specific IgG Fc N-glycopeptides in the serum of one patient (see Figure 1 ).exist Figure 1 The 10 glycopeptide types involved in the present invention are identified in (see Table 1 below). These glycopeptides are all N-glycopeptides, and the sugar chain is connected to the Asn of the polypeptide chain. In the case of IgG1, the N-glycosylation modification site is located at Asn180, and in the case of IgG2, the N-glycosylation modification site is located at Asn176, wherein 180 and 176 both refer to the position of the glycosylation modification site at Asn in the amino acid sequence of the IgG heavy chain constant region.

[0081] 2) Acquisition of mass spectrometry data: The data information (mass-to-charge ratio and relative intensity) in the mass spectrum was acquired using software, with signal-to-noise ratio ≥ 3, relative intensity > 0.1%, absolute intensity > 100,000, and reliable isotope peaks as selection criteria. The results were imported into Microsoft Excel for analysis.

[0082] 3) Identification of glycopeptides: (1) High-resolution mass spectrometry obtains accurate molecular mass information (observed value). Using the information provided by the database, the corresponding possible glycopeptides are inferred and their theoretical molecular weight is calculated. If the error between the observed value and the theoretical value obtained by mass spectrometry is within 20 ppm, they are considered to be the same substance; (2) Literature has reported the structural information of total IgG N-glycopeptides in serum and identified 10 glycoforms: G0, G0F, G0N, G1F, G0FN, G2F, G1FN, G1FS, G2FN, and G2FS. See Gardinassi LG, Dotz V, Hipgrave Ederveen A, et al., Clinical Severity of Visceral Leishmaniasis Is Associated with Changes in Immunoglobulin G Fc N-Glycosylation[J]. mBio, 2014, 5(6). In this example, according to the established method, 10 glycoforms, including G0F, G1, G1F, G2, G0FN, G2F, G1FN, G2N, G1FS, and G2FS, were identified in disease-specific IgG, as shown in Table 1. Among them, 10 glycopeptides corresponding to 8 glycoforms are related to the selection of lung cancer treatment options.

[0083] Table 1 Glycopeptide information

[0084]

[0085] ■(N), N-acetylglucosamine; ●(M), mannose; ○(G), galactose; ◆(S), sialic acid; ▲(F), fucose

[0086] There is a conserved N-glycosylation modification site on the Fc CH2 domain of the IgG molecule. The sugar chain connected to this site is mainly a complex N-sugar chain. The complex N-sugar chain connected to Fc generally has a common seven-sugar basic structure GlcNAc2-Man3-GlcNAc2 (see Epp A, Sullivan KC, Herr AB, et al., Immunoglobulin Glycosylation Effects in Allergy and Immunity [J]. Current Allergy & Asthma Reports, 2016, 16 (11): 79). On the basis of this common seven-sugar basic structure, Fuc, Gal, Sia and bisecting GlcNAc can be further connected. For example, the IgG2 G0F in the present invention refers to a seven-sugar basic structure (GlcNAc2-Man3-GlcNAc2) connected to the Asn176 site of the IgG2 heavy chain constant region, and then connected to a fucose residue. Its structure is as follows As shown; IgG2G1F refers to a seven sugar basic structure (GlcNAc2-Man3-GlcNAc2) connected to the Asn176 site of the IgG2 peptide, and then connected to a galactose residue and a fucose residue, and its structure is as shown The remaining glycoforms are represented in a similar manner.

[0087] That is, the glycoforms of the present invention have a glycosylation modification pattern as shown in the following table:

[0088]

[0089] Example 2 Correlation between the relative intensity ratios of disease-specific IgG Fc N-glycopeptides IgG2 G2F / G0F, IgG2 G2F / G1F, and IgG2 G2FS / G1FS and the efficacy of surgical treatment in patients with lung cancer

[0090] 1. Surgical treatment is an important method for clinically curing lung cancer by removing cancer lesions. The inventors found through the following research that the relative intensity ratios of disease-specific IgG Fc N-glycopeptides IgG2 G2F / G0F, IgG2 G2F / G1F, and IgG2G2FS / G1FS can be used to predict the efficacy of surgical treatment of lung cancer patients or guide the application of surgical treatment to treat patients. The basic information of the fifteen lung cancer patients used is shown in Table 2.

[0091] Table 2 Basic information of patients with lung cancer treated surgically

[0092]

[0093] 2. Fifteen serum samples of lung cancer patients who underwent surgical treatment before treatment were used for separation and detection of disease-specific IgG Fc N-glycopeptide according to the method in Example 1, and 10 μL of serum was taken from each sample.

[0094] 3. Obtain the mass spectrometry data of each sample according to the method in Example 1, import it into an Excel table, establish a database and calculate the relative intensity ratios between the various glycopeptides listed in Table 1. The relative intensity ratios of the three glycopeptides related to the efficacy of surgical treatment and the time interval Δt between each surgical treatment and disease progression of fifteen lung cancer patients are shown in Table 3. Studies have shown that the length of time Δt for patients with lung cancer surgical treatment is not related to pathological type and clinical stage. According to whether Δt is greater than 80 weeks, the fifteen subjects were divided into two groups with good prognosis and poor prognosis. Among them, patients 1 to 7 had a good prognosis, and patients 8 to 15 had a poor prognosis. The receiver operating characteristic curve (ROC) analysis of various glycopeptide ratios was performed and the area under the curve (AUC) was calculated. Only the AUC of the three glycopeptide ratios of IgG2 G2F / G0F (AUC=0.946), IgG2 G2F / G1F (AUC=1), and IgG2 G2FS / G1FS (AUC=1) was greater than 0.9, proving that these three glycopeptide ratios are effective indicators for distinguishing the efficacy of surgical treatment. By calculating the Youden index, the glycopeptide ratio with the maximum sum of specificity and sensitivity was obtained, and the optimal screening positive cut-off values ​​(cut-off values) corresponding to the three glycopeptide ratios were obtained, among which the cut-off value of IgG2 G2F / G0F was 0.3364 (sensitivity was 0.875, specificity was 1), the cut-off value of IgG2 G2F / G1F was 0.4362 (sensitivity was 1, specificity was 1), and the cut-off value of IgG2 G2FS / G1FS was 1.1636 (sensitivity was 1, specificity was 1). Therefore, as shown in Table 16, the reference range of the glycopeptide relative intensity ratio for lung cancer patients suitable for surgical treatment was set to IgG2 G2F / G0F<0.3364, IgG2 G2F / G1F<0.4362 and IgG2 G2FS / G1FS<1.1636.

[0095] The results showed that the relative intensity ratios of the three glycopeptides in patients 1 to 7 all met their respective reference ranges, and the time interval between their treatment and disease progression was longer than that of patients 8 to 15, all greater than 80 weeks. The surgical treatment had a good effect and was suitable for surgical treatment. Patients 8 to 15 all had a certain glycopeptide relative intensity ratio that did not meet their respective reference ranges, and the time interval between their treatment and disease progression was shorter than that of patients 1 to 7, all less than 80 weeks. They had a poor prognosis and were not suitable for surgical treatment. This result shows that the relative intensity ratios of disease-specific IgG Fc N-glycopeptides IgG2 G2F / G0F, IgG2 G2F / G1F, and IgG2 G2FS / G1FS are a group of individualized markers that can predict the efficacy of surgical treatment. This group of markers can be used to formulate a reasonable surgical treatment plan for lung cancer patients in advance.

[0096] Table 3 Glycopeptide relative intensity ratios and the time interval between treatment and disease progression in patients with lung cancer treated with surgery

[0097]

[0098] Example 3 Correlation between the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG1 G2F / G1F and the efficacy of radiotherapy in lung cancer patients

[0099] 1. For patients who are not suitable for surgery, radiotherapy is the most effective and safest treatment method. Its purpose is to give an accurate radiation dose to a determined tumor volume, killing the tumor while causing minimal damage to the normal tissue around the lesion. The inventors found through the following research that the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG1 G2F / G1F can be used to predict the efficacy of radiotherapy for lung cancer patients or guide the use of radiotherapy to treat patients. The basic information of the ten lung cancer patients used is shown in Table 4.

[0100] 2. Serum samples of ten lung cancer patients who received radiotherapy before treatment were used for separation and detection of disease-specific IgG Fc N-glycopeptide according to the method in Example 1, and 10 μL of serum was taken from each sample.

[0101] 3. Obtain the mass spectrometry data of each sample according to the method in Example 1, import it into an Excel table, establish a database and calculate the relative intensity ratios between the various glycopeptides listed in Table 1. The relative intensity ratios of glycopeptides related to the efficacy of radiotherapy and the time interval Δt between each radiotherapy and disease progression of ten lung cancer patients are shown in Table 5. Similarly, the length of Δt of patients with lung cancer radiotherapy is not related to pathological type and clinical stage. According to whether Δt is greater than 44 weeks, the ten subjects are divided into two groups with good prognosis and poor prognosis. Among them, patients 1 to 5 have a good prognosis, and patients 6 to 10 have a poor prognosis. The receiver operating characteristic curve (ROC) analysis of various glycopeptide ratios was performed and the area under the curve (AUC) was calculated. Only IgG1 G2F / G1F (AUC=1) had an AUC greater than 0.9, proving that the glycopeptide ratio is an effective indicator for distinguishing the efficacy of radiotherapy. By calculating the Youden index, the glycopeptide ratio with the maximum sum of specificity and sensitivity was obtained, and the cutoff value of IgG1 G2F / G1F was 0.4495 (sensitivity is 1, specificity is 1). Therefore, as shown in Table 16, the reference range of the glycopeptide relative intensity ratio for lung cancer patients suitable for radiotherapy was set to IgG1 G2F / G1F<0.4495.

[0102] The results showed that the IgG1 G2F / G1F ratio of patients 1 to 5 met the reference range, and the time interval between their treatment and disease progression was longer than that of patients 6 to 10, both greater than 44 weeks. The radiotherapy effect was good, and radiotherapy was suitable. The IgG1 G2F / G1F ratio of patients 6 to 10 did not meet the reference range, and the time interval between their treatment and disease progression was shorter than that of patients 1 to 5, both less than 44 weeks. The prognosis was poor, and radiotherapy was not suitable. This result shows that the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG1 G2F / G1F is an individualized marker that can predict the efficacy of radiotherapy. This marker can be used to formulate a reasonable radiotherapy plan for lung cancer patients in advance.

[0103] Table 4 Basic information of patients with lung cancer treated with radiotherapy

[0104]

[0105] Table 5 Relative intensity ratio of glycopeptides and time interval between treatment and disease progression in patients with lung cancer treated with radiotherapy

[0106]

[0107]

[0108] Example 4 Correlation between the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG2 G2 / G1 and the efficacy of pemetrexed chemotherapy

[0109] 1. Pemetrexed is an anti-folate chemotherapy drug containing a pyrrolopyrimidine group in its structure. It inhibits cell replication by destroying the normal metabolic process of intracellular folate dependence, thereby inhibiting tumor growth. The inventors found through the following research that the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG2 G2 / G1 can be used to predict the efficacy of pemetrexed (plus platinum) chemotherapy for patients with lung adenocarcinoma or guide the use of this chemotherapy to treat patients. The basic information of the seven lung cancer patients used is shown in Table 6.

[0110] 2. The serum samples of seven lung cancer patients who received pemetrexed chemotherapy before treatment were separated and detected for disease-specific IgG Fc N-glycopeptide according to the method in Example 1, and 10 μL of serum was taken from each sample.

[0111] Table 6 Basic information of lung cancer patients treated with pemetrexed chemotherapy

[0112]

[0113] 3. Obtain the mass spectrometry data of each sample according to the method in Example 1, import it into an Excel table, establish a database and calculate the relative intensity ratios between the various glycopeptides listed in Table 1. The relative intensity ratios of glycopeptides related to the efficacy of pemetrexed chemotherapy in seven patients with lung cancer and the time interval Δt between each chemotherapy and disease progression are shown in Table 7. The results of the study showed that the length of Δt of patients with lung cancer treated with pemetrexed was not related to the clinical stage. According to whether Δt was greater than 100 weeks, the seven subjects were divided into two groups with good prognosis and poor prognosis. Among them, patients 1 to 2 had a good prognosis, and patients 3 to 7 had a poor prognosis. The receiver operating characteristic curve (ROC) analysis was performed on various glycopeptide ratios and the area under the curve (AUC) was calculated. Only the AUC of IgG2 G2 / G1 (AUC=1) was greater than 0.9, proving that the glycopeptide ratio is an effective indicator for distinguishing the efficacy of pemetrexed chemotherapy. By calculating the Youden index, the glycopeptide ratio with the maximum sum of specificity and sensitivity was obtained, and the cutoff value of IgG2 G2 / G1 was 0.4476 (sensitivity is 1, specificity is 1). Therefore, as shown in Table 16, the reference range of the glycopeptide relative intensity ratio for lung cancer patients suitable for pemetrexed chemotherapy was set to IgG2 G2 / G1>0.4476.

[0114] The results showed that the relative intensity ratio of glycopeptides in patients 1 to 2 met the reference range, and the time interval between their treatment and disease progression was longer than that of patients 3 to 7, both greater than 100 weeks, with good chemotherapy efficacy, and pemetrexed chemotherapy was suitable. In contrast, the relative intensity ratio of glycopeptides in patients 3 to 7 did not meet the reference range, and the time interval between their treatment and disease progression was less than 100 weeks, with a poor prognosis, and pemetrexed chemotherapy was not suitable. This result shows that the relative intensity ratio of disease-specific IgG FcN-glycopeptide IgG2 G2 / G1 is an individualized marker that can predict the efficacy of pemetrexed chemotherapy, and this marker can be used to formulate a reasonable chemotherapy plan for lung cancer patients in advance.

[0115] Table 7 Relative intensity ratio of glycopeptides and time interval between treatment and disease progression in patients with lung adenocarcinoma treated with pemetrexed chemotherapy

[0116]

[0117] Example 5 Correlation between the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG2 G2F / G2 and the efficacy of gemcitabine chemotherapy

[0118] 1. Gemcitabine is a pyrimidine chemotherapeutic drug. After entering the human body, it is activated by deoxycytidine kinase and metabolized by cytosine nucleoside deaminase. It mainly acts on tumor cells in the DNA synthesis phase (i.e., S phase), which can cause DNA breakage and tumor cell death. The inventors found through the following research that the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG2 G2F / G2 can be used to predict the efficacy of gemcitabine (plus platinum) chemotherapy for patients with non-small cell lung cancer or to guide the use of this chemotherapy method to treat patients. The basic information of the six lung cancer patients used is shown in Table 8.

[0119] Table 8 Basic information of patients with lung cancer treated with gemcitabine chemotherapy

[0120]

[0121]

[0122] 2. The serum samples of six lung cancer patients who received gemcitabine chemotherapy before treatment were subjected to separation and detection of disease-specific IgG Fc N-glycopeptide according to the method in Example 1, and 10 μL of serum was taken from each sample.

[0123] 3. Obtain the mass spectrometry data of each sample according to the method in Example 1, import it into an Excel table, establish a database and calculate the relative intensity ratios between the various glycopeptides listed in Table 1. The relative intensity ratios of glycopeptides related to the efficacy of gemcitabine chemotherapy in six lung cancer patients and the time interval Δt between chemotherapy and disease progression are shown in Table 9. The results of the study showed that the duration of Δt in patients with lung cancer treated with gemcitabine was not related to the clinical stage. According to whether Δt was greater than 100 weeks, the six subjects were divided into two groups with good prognosis and poor prognosis. Among them, patients 1 to 3 had a good prognosis, and patients 4 to 6 had a poor prognosis. The receiver operating characteristic curve (ROC) analysis was performed on various glycopeptide ratios and the area under the curve (AUC) was calculated. Only IgG2 G2F / G2 (AUC=1) had an AUC greater than 0.9, proving that the glycopeptide ratio is an effective indicator for distinguishing the efficacy of gemcitabine chemotherapy. By calculating the Youden index, the glycopeptide ratio with the maximum sum of specificity and sensitivity was obtained, and the cutoff value of IgG2G2F / G2 was 3.0838 (sensitivity is 1, specificity is 1). Therefore, as shown in Table 16, the reference range of the glycopeptide relative intensity ratio for lung cancer patients suitable for gemcitabine chemotherapy was set to IgG2 G2F / G2>3.0838.

[0124] The results showed that the IgG2 G2F / G2 ratio of patients 1 to 3 met the reference range, and the time interval between treatment and disease progression was longer than that of patients 4 to 6, both greater than 100 weeks, with good chemotherapy efficacy, and gemcitabine chemotherapy was suitable. In contrast, the glycopeptide relative intensity ratio of patients 4 to 6 did not meet the reference range, and the time interval between treatment and disease progression was less than 100 weeks, with a poor prognosis, and gemcitabine chemotherapy was not suitable. This result shows that the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG2 G2F / G2 is an individualized marker that can predict the efficacy of gemcitabine chemotherapy, and this marker can be used to formulate a reasonable chemotherapy plan for lung cancer patients in advance.

[0125] Table 9 Relative intensity ratio of glycopeptides and time interval between treatment and disease progression in patients with non-small cell lung cancer treated with gemcitabine chemotherapy

[0126]

[0127]

[0128] Example 6 Correlation between the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG2 G2N / G2 and the efficacy of icotinib targeted therapy

[0129] 1. Icotinib is a targeted anticancer drug targeting epidermal growth factor receptor kinase, which can effectively inhibit tumor proliferation and is suitable for patients with advanced non-small cell lung cancer. The inventors found through the following research that the relative intensity ratio of disease-specific IgG FcN-glycopeptide IgG2 G2N / G2 can be used to predict the efficacy of icotinib targeted therapy for patients with lung adenocarcinoma or to guide the application of this targeted therapy to treat patients. The basic information of the thirteen lung cancer patients used is shown in Table 10.

[0130] 2. The serum samples of thirteen lung cancer patients who received icotinib targeted therapy before treatment were subjected to separation and detection of disease-specific IgG Fc N-glycopeptide according to the method in Example 1, and 10 μL of serum was taken from each sample.

[0131] Table 10 Basic information of patients with lung cancer treated with icotinib

[0132]

[0133] 3. Obtain the mass spectrometry data of each sample according to the method in Example 1, import it into an Excel table, and establish the database. The relative intensity ratios of various glycopeptides listed in Table 1 are shown in Table 11. The relative intensity ratios of glycopeptides related to the therapeutic efficacy of icotinib in thirteen lung cancer patients and the time interval Δt between each targeted therapy and disease progression are shown in Table 11. According to whether Δt is greater than or equal to 52 weeks, the 13 subjects were divided into two groups with good prognosis and poor prognosis. Among them, patients 1 to 7 had a good prognosis, and patients 8 to 13 had a poor prognosis. The receiver operating characteristic curve (ROC) analysis was performed on various glycopeptide ratios and the area under the curve (AUC) was calculated. Only IgG2 G2N / G2 (AUC=1) had an AUC greater than 0.9, proving that the glycopeptide ratio is an effective indicator for distinguishing the efficacy of icotinib targeted therapy. By calculating the Youden index, the glycopeptide ratio with the largest sum of specificity and sensitivity was obtained, and the cutoff value of IgG2 G2N / G2 was 0.3197 (sensitivity is 1, specificity is 1). Therefore, as shown in Table 16, the reference range of glycopeptide relative intensity ratio for lung adenocarcinoma patients suitable for icotinib targeted therapy was set as IgG2 G2N / G2<0.3197.

[0134] The results showed that the IgG2 G2N / G2 ratio of patients 1 to 7 met the reference range, and the time interval between treatment and disease progression was longer than that of patients 8 to 13, both greater than or equal to 52 weeks. The targeted therapy had a good effect, and it was suitable for icotinib targeted therapy. In contrast, the glycopeptide relative intensity ratio of patients 8 to 13 did not meet the reference range, and the time interval between treatment and disease progression was less than 52 weeks. The prognosis was poor, and it was not suitable for icotinib targeted therapy. This result shows that the disease-specific IgGFc N-glycopeptide IgG2 G2N / G2 relative intensity ratio is an individualized marker that can predict the efficacy of icotinib targeted therapy. This marker can be used to formulate a reasonable targeted treatment plan for lung cancer patients in advance.

[0135] Table 11 Relative intensity ratio of glycopeptides and time interval between treatment and disease progression in patients with lung adenocarcinoma treated with icotinib

[0136]

[0137] Example 7 Correlation between the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG2 G2FS / G1FS and the efficacy of gefitinib targeted therapy

[0138] 1. Gefitinib is a selective epidermal growth factor receptor tyrosine kinase inhibitor that inhibits tumor growth and metastasis and promotes apoptosis of tumor cells. The inventors found through the following research that the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG2 G2FS / G1FS can be used to predict the efficacy of gefitinib targeted therapy for patients with lung adenocarcinoma or to guide the application of this targeted therapy to treat patients. The basic information of the four lung cancer patients used is shown in Table 12.

[0139] 2. The serum samples of four lung cancer patients who received gefitinib targeted therapy before treatment were subjected to separation and detection of disease-specific IgG Fc N-glycopeptide according to the method in Example 1, and 10 μL of serum was taken from each sample.

[0140] Table 12 Basic information of patients with lung cancer treated with gefitinib targeted therapy

[0141]

[0142] 3. Obtain the mass spectrometry data of each sample according to the method in Example 1, import it into an Excel table, and the relative intensity ratios of the various glycopeptides listed in Table 1, the relative intensity ratios of glycopeptides related to the therapeutic efficacy of gefitinib in four lung cancer patients, and the time interval Δt between each targeted therapy and disease progression are shown in Table 13. According to whether Δt is greater than or equal to 52 weeks, the four subjects are divided into two groups with good prognosis and poor prognosis, among which patients 1 to 2 have a good prognosis, and patients 3 to 4 have a poor prognosis. The receiver operating characteristic curve (ROC) analysis of various glycopeptide ratios was performed and the area under the curve (AUC) was calculated. Only the AUC of IgG2 G2FS / G1FS (AUC=1) was greater than 0.9, proving that the glycopeptide ratio is an effective indicator for distinguishing the efficacy of gefitinib targeted therapy. By calculating the Youden index, the glycopeptide ratio with the largest sum of specificity and sensitivity was obtained, and the cutoff value of IgG2G2FS / G1FS was 1.1403 (sensitivity is 1, specificity is 1). Therefore, as shown in Table 16, the reference range of the glycopeptide relative intensity ratio for lung adenocarcinoma patients suitable for gefitinib targeted therapy was set to IgG2 G2FS / G1FS<1.1403.

[0143] The results showed that the IgG2 G2FS / G1FS ratio of patients 1 to 2 met the reference range, and the time interval between their treatment and disease progression was longer than that of patients 3 to 4, both greater than 52 weeks. The targeted therapy had a good effect, and gefitinib targeted therapy was suitable. In contrast, the glycopeptide relative intensity ratio of patients 3 to 4 did not meet the reference range, and the time interval between their treatment and disease progression was less than 52 weeks. The prognosis was poor, and gefitinib targeted therapy was not suitable. This result shows that the disease-specific IgG FcN-glycopeptide IgG2 G2FS / G1FS relative intensity ratio is an individualized marker that can predict the efficacy of gefitinib targeted therapy. This marker can be used to formulate a reasonable targeted treatment plan for lung cancer patients in advance.

[0144] Table 13 Relative intensity ratio of glycopeptides and time interval between treatment and disease progression in patients with lung adenocarcinoma treated with gefitinib

[0145]

[0146]

[0147] Example 8 Correlation between the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG2 G2FS / G1FS and the efficacy of anlotinib targeted therapy

[0148] 1. Anlotinib is a small molecule multi-target tyrosine kinase inhibitor with anti-tumor angiogenesis and tumor growth inhibition effects. The inventors found through the following research that the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG2 G2FS / G1FS can be used to predict the efficacy of anlotinib targeted therapy for non-small cell carcinoma patients or guide the application of this targeted therapy to treat patients. The basic information of the four lung cancer patients used is shown in Table 14.

[0149] Table 14 Basic information of patients with lung cancer treated with anlotinib

[0150]

[0151] 2. The serum samples of four lung cancer patients who received anlotinib targeted therapy before treatment were separated and detected for disease-specific IgG Fc N-glycopeptide according to the method in Example 1, and 10 μL of serum was taken from each sample.

[0152] 3. Obtain the mass spectrometry data of each sample according to the method in Example 1, import it into an Excel table, establish a database and calculate the relative intensity ratios between the various glycopeptides listed in Table 1. The relative intensity ratios of glycopeptides related to the therapeutic efficacy of anlotinib in four lung cancer patients and the time interval Δt between each targeted therapy and disease progression are shown in Table 15. According to whether Δt is greater than or equal to 52 weeks, the four subjects were divided into two groups with good prognosis and poor prognosis, among which patient No. 1 had a good prognosis and patients No. 2 to No. 4 had a poor prognosis. The receiver operating characteristic curve (ROC) analysis was performed on various glycopeptide ratios and the area under the curve (AUC) was calculated. Only the AUC of IgG2 G2FS / G1FS (AUC=1) was greater than 0.9, proving that the glycopeptide ratio is an effective indicator for distinguishing the efficacy of anlotinib targeted therapy. By calculating the Youden index, the glycopeptide ratio with the largest sum of specificity and sensitivity was obtained, and the cutoff value of IgG2 G2FS / G1FS was 1.1244 (sensitivity is 1, specificity is 1). Therefore, as shown in Table 16, the reference range of the glycopeptide relative intensity ratio for lung cancer patients suitable for anlotinib targeted therapy was set to IgG2 G2FS / G1FS>1.1244.

[0153] The results showed that the IgG2 G2FS / G1FS ratio of patient 1 met the reference range, and the time interval between treatment and disease progression was longer than that of patients 2 to 4, greater than 52 weeks, with good efficacy of targeted therapy, and anlotinib targeted therapy was suitable. In contrast, the glycopeptide relative intensity ratio of patients 2 to 4 did not meet the reference range, and the time interval between treatment and disease progression was less than 52 weeks, with a poor prognosis, and anlotinib targeted therapy was not suitable. This result shows that the relative intensity ratio of disease-specific IgG Fc N-glycopeptide IgG2 G2FS / G1FS is an individualized marker that can predict the efficacy of anlotinib targeted therapy, and this marker can be used to formulate a reasonable targeted treatment plan for lung cancer patients in advance.

[0154] Table 15 Relative intensity ratio of glycopeptides and time interval between treatment and disease progression in patients with non-small cell lung cancer treated with anlotinib

[0155]

[0156] In summary, the present invention provides a method for predicting the therapeutic effect of clinical treatments for lung cancer by using the relative intensity ratio of disease-specific IgG Fc N-glycopeptide in serum as a predictive index and setting a reference range for it according to different treatment plans. This index has individualized characteristics and can guide the selection of clinical treatments for lung cancer. It eliminates the shortcomings of the prior art, that is, a group of non-invasive, individualized markers are discovered, and it guides the selection of clinical lung cancer treatment plans more sensitively than traditional methods.

[0157] Table 16 Reference range of glycopeptide relative intensity ratio to guide the selection of lung cancer treatment methods

[0158]

[0159] Although the content of the present invention is described in conjunction with the present embodiment, it cannot be considered as limiting the scope of the present invention, and the scope of the present invention is defined by the attached claims. Therefore, those skilled in the art may make various changes or modifications to the present invention within the scope defined by the attached claims, and these changes or modifications are also within the protection scope of the present invention. Sequence Listing <110> Institute of Basic Medicine, Chinese Academy of Medical Sciences <120> Use of IgG Fc N-glycopeptide as a marker to determine or assist in the selection of lung cancer treatment options <130> 310029CG <160> 4 <170> SIPOSequenceListing 1.0 <210> 1 <211> 9 <212> PRT <213> Homo sapiens <400> 1 Glu Glu Gln Tyr Asn Ser Thr Tyr Arg 1 5 <210> 2 <211> 9 <212> PRT <213> Homo sapiens <400> 2 Glu Glu Gln Phe Asn Ser Thr Phe Arg 1 5 <210> 3 <211> 330 <212> PRT <213> Homo sapiens <400> 3 Ala Ser Thr Lys Gly Pro Ser Val Phe Pro Leu Ala Pro Ser Ser Lys 1 5 10 15 Ser Thr Ser Gly Gly Thr Ala Ala Leu Gly Cys Leu Val Lys Asp Tyr 20 25 30 Phe Pro Glu Pro Val Thr Val Ser Trp Asn Ser Gly Ala Leu Thr Ser 35 40 45 Gly Val His Thr Phe Pro Ala Val Leu Gln Ser Ser Gly Leu Tyr Ser 50 55 60 Leu Ser Ser Val Val Thr Val Pro Ser Ser Ser Leu Gly Thr Gln Thr 65 70 75 80 Tyr Ile Cys Asn Val Asn His Lys Pro Ser Asn Thr Lys Val Asp Lys 85 90 95 Lys Val Glu Pro Lys Ser Cys Asp Lys Thr His Thr Cys Pro Pro Cys 100 105 110 Pro Ala Pro Glu Leu Leu Gly Gly Pro Ser Val Phe Leu Phe Pro Pro 115 120 125 Lys Pro Lys Asp Thr Leu Met Ile Ser Arg Thr Pro Glu Val Thr Cys 130 135 140 Val Val Val Asp Val Ser His Glu Asp Pro Glu Val Lys Phe Asn Trp 145 150 155 160 Tyr Val Asp Gly Val Glu Val His Asn Ala Lys Thr Lys Pro Arg Glu 165 170 175 Glu Gln Tyr Asn Ser Thr Tyr Arg Val Val Ser Val Leu Thr Val Leu 180 185 190 His Gln Asp Trp Leu Asn Gly Lys Glu Tyr Lys Cys Lys Val Ser Asn 195 200 205 Lys Ala Leu Pro Ala Pro Ile Glu Lys Thr Ile Ser Lys Ala Lys Gly 210 215 220 Gln Pro Arg Glu Pro Gln Val Tyr Thr Leu Pro Pro Ser Arg Asp Glu 225 230 235 240 Leu Thr Lys Asn Gln Val Ser Leu Thr Cys Leu Val Lys Gly Phe Tyr 245 250 255 Pro Ser Asp Ile Ala Val Glu Trp Glu Ser Asn Gly Gln Pro Glu Asn 260 265 270 Asn Tyr Lys Thr Thr Pro Pro Val Leu Asp Ser Asp Gly Ser Phe Phe 275 280 285 Leu Tyr Ser Lys Leu Thr Val Asp Lys Ser Arg Trp Gln Gln Gly Asn 290 295 300 Val Phe Ser Cys Ser Val Met His Glu Ala Leu His Asn His Tyr Thr 305 310 315 320 Gln Lys Ser Leu Ser Leu Ser Pro Gly Lys 325 330 <210> 4 <211> 326 <212> PRT <213> Homo sapiens <400> 4 Ala Ser Thr Lys Gly Pro Ser Val Phe Pro Leu Ala Pro Cys Ser Arg 1 5 10 15 Ser Thr Ser Glu Ser Thr Ala Ala Leu Gly Cys Leu Val Lys Asp Tyr 20 25 30 Phe Pro Glu Pro Val Thr Val Ser Trp Asn Ser Gly Ala Leu Thr Ser 35 40 45 Gly Val His Thr Phe Pro Ala Val Leu Gln Ser Ser Gly Leu Tyr Ser 50 55 60 Leu Ser Ser Val Val Thr Val Pro Ser Ser Asn Phe Gly Thr Gln Thr 65 70 75 80 Tyr Thr Cys Asn Val Asp His Lys Pro Ser Asn Thr Lys Val Asp Lys 85 90 95 Thr Val Glu Arg Lys Cys Cys Val Glu Cys Pro Pro Cys Pro Ala Pro 100 105 110 Pro Val Ala Gly Pro Ser Val Phe Leu Phe Pro Pro Lys Pro Lys Asp 115 120 125 Thr Leu Met Ile Ser Arg Thr Pro Glu Val Thr Cys Val Val Val Asp 130 135 140 Val Ser His Glu Asp Pro Glu Val Gln Phe Asn Trp Tyr Val Asp Gly 145 150 155 160 Val Glu Val His Asn Ala Lys Thr Lys Pro Arg Glu Glu Gln Phe Asn 165 170 175 Ser Thr Phe Arg Val Val Ser Val Leu Thr Val Val His Gln Asp Trp 180 185 190 Leu Asn Gly Lys Glu Tyr Lys Cys Lys Val Ser Asn Lys Gly Leu Pro 195 200 205 Ala Pro Ile Glu Lys Thr Ile Ser Lys Thr Lys Gly Gln Pro Arg Glu 210 215 220 Pro Gln Val Tyr Thr Leu Pro Pro Ser Arg Glu Glu Met Thr Lys Asn 225 230 235 240 Gln Val Ser Leu Thr Cys Leu Val Lys Gly Phe Tyr Pro Ser Asp Ile 245 250 255 Ser Val Glu Trp Glu Ser Asn Gly Gln Pro Glu Asn Asn Tyr Lys Thr 260 265 270 Thr Pro Pro Met Leu Asp Ser Asp Gly Ser Phe Phe Leu Tyr Ser Lys 275 280 285 Leu Thr Val Asp Lys Ser Arg Trp Gln Gln Gly Asn Val Phe Ser Cys 290 295 300 Ser Val Met His Glu Ala Leu His Asn His Tyr Thr Gln Lys Ser Leu 305 310 315 320 Ser Leu Ser Pro Gly Lys 325

Claims

1. Use of a reagent for detecting IgG Fc N-glycopeptide in the preparation of a kit for predicting the therapeutic effects of different clinical treatments for lung cancer and / or guiding the selection of clinical treatments for lung cancer, wherein the peptide sequence of the IgG Fc N-glycopeptide is an IgG1 subtype polypeptide sequence as shown in SEQ ID NO: 1 or an IgG2 subtype polypeptide sequence as shown in SEQ ID NO: 2, and the glycoform of the IgG Fc N-glycopeptide is selected from any one of the following tables: in, Predict the therapeutic effects of different clinical treatments for lung cancer and / or guide the selection of clinical treatments for lung cancer based on one or more of the following glycopeptide relative intensity ratios: G2F to G1F of IgG1; G2F to G0F of IgG2; G2 to G1 of IgG2; G2F to G1F of IgG2; G2F to G2 of IgG2; G2N to G2 of IgG2; and G2FS to G1FS of IgG2; wherein, Whether to select radiotherapy is determined based on the ratio of G2F to G1F of IgG1; whether to select surgical treatment is determined based on the ratios of G2F to G0F of IgG2, G2F to G1F of IgG2, and G2FS to G1FS of IgG2; chemotherapeutic drugs are selected based on the ratios of G2 to G1 of IgG2, and G2F to G2 of IgG2; and targeted therapy drugs are selected based on the ratios of G2N to G2 of IgG2 and G2FS to G1FS of IgG2.

2. The use according to claim 1, wherein the glycoform of the IgG Fc N-glycopeptide is Asn in the IgG1 subtype in the sequence shown in SEQ ID NO: 1 or 2. 180 or Asn of IgG2 subtype 176 Glycosylation modification at the site.

3. The use according to claim 1, wherein the reagent is used to detect IgG Fc N-glycopeptide in the serum or plasma of lung cancer patients before receiving anti-cancer treatment.

4. The use according to any one of claims 1 to 3, wherein the IgG Fc N-glycopeptide in the serum or plasma sample is detected by the following steps: a) separating immune inflammation-related protein complexes in serum or plasma by non-denaturing polyacrylamide gel electrophoresis; b) separating the IgG heavy chains in the immune inflammation-related complex obtained in step a) by denaturing polyacrylamide gel electrophoresis; c) subjecting the IgG heavy chain obtained in step b) to trypsin digestion; d) enriching the IgG Fc N-glycopeptide in the IgG heavy chain tryptic digest obtained in step c) using carbon nitride; and e) identifying the IgG Fc N-glycopeptide enriched in step d) by mass spectrometry and obtaining its relative intensity.

5. The use according to any one of claims 1 to 3, wherein the lung cancer is non-small cell lung cancer or small cell lung cancer. The use according to claim 5, wherein the non-small cell lung cancer is lung adenocarcinoma or squamous cell carcinoma.

7. The use according to any one of claims 1 to 3, wherein the clinical treatment method is selected from one or more of surgical treatment, radiotherapy, chemotherapy and targeted therapy.

8. The use according to claim 7, wherein the chemotherapy is selected from one or more of pemetrexed and gemcitabine; and the targeted therapy is selected from one or more of icotinib, gefitinib and anlotinib.

9. Use of the ratio of relative intensities of IgG Fc N-glycopeptides in serum or plasma of a subject as a marker in the preparation of a kit for selecting a treatment for a subject, wherein the subject is a lung cancer patient; the ratio of relative intensities of IgG Fc N-glycopeptides is selected from one or more of the following: G2F to G1F of IgG1; G2F to G0F of IgG2; G2 to G1 of IgG2; G2F to G1F of IgG2; G2F to G2 of IgG2; G2N to G2 of IgG2; and G2FS to G1FS of IgG2; in, Whether to select radiotherapy is determined based on the ratio of G2F to G1F of IgG1; whether to select surgical treatment is determined based on the ratios of G2F to G0F of IgG2, G2F to G1F of IgG2, and G2FS to G1FS of IgG2; chemotherapeutic drugs are selected based on the ratios of G2 to G1 of IgG2, and G2F to G2 of IgG2; and targeted therapy drugs are selected based on the ratios of G2N to G2 of IgG2 and G2FS to G1FS of IgG2.

10. The use according to claim 9, wherein the treatment modality is selected from one or more of surgical treatment, radiotherapy, chemotherapy and targeted therapy.

11. The use according to claim 10, wherein the chemotherapy is selected from one or more of pemetrexed and gemcitabine; and the targeted therapy is selected from one or more of icotinib, gefitinib and anlotinib.

12. A computer-readable storage device for selecting a clinical treatment for lung cancer for a subject, comprising: a) a data input device for inputting the relative intensity values ​​of each IgG glycopeptide in the serum or plasma of the subject obtained by the mass spectrometer; b) a data processing device for calculating the ratio of the relative intensities of glycopeptides with the same glycosylation modification site in the Fc peptide segment of the same IgG subtype that differ by one or two identical monosaccharide residues from the relative intensity values ​​obtained in a); and c) an output device for comparing the value obtained in b) with a standard value, so as to select a clinical treatment method for the subject; The clinical treatment method is selected from one or more of surgical treatment, radiotherapy, chemotherapy and targeted therapy; The data processing device in step b) is used to calculate the following glycopeptide relative intensity ratios: G2F to G1F of IgG1; G2F to G0F of IgG2; G2 to G1 of IgG2; G2F to G1F of IgG2; G2F to G2 of IgG2; G2N to G2 of IgG2; and G2FS to G1FS of IgG2; Among them, whether to select radiotherapy is determined based on the ratio of G2F to G1F of IgG1; whether to select surgical treatment is determined based on the ratio of G2F to G0F of IgG2, G2F to G1F of IgG2, and G2FS to G1FS of IgG2; chemotherapeutic drugs are selected based on the ratio of G2 to G1 of IgG2 and G2F to G2 of IgG2; and targeted therapy drugs are selected based on the ratio of G2N to G2 of IgG2 and G2FS to G1FS of IgG2.

13. The computer-readable storage device of claim 12, wherein the chemotherapy is selected from one or more of pemetrexed and gemcitabine treatment; and the targeted therapy is selected from one or more of icotinib, gefitinib and anlotinib.

14. A device for selecting a clinical treatment for lung cancer for a subject, comprising: i) Non-denaturing polyacrylamide gel electrophoresis apparatus, used to separate immune-inflammatory related protein complexes in serum or plasma; ii) Denaturing polyacrylamide gel electrophoresis apparatus for separation of IgG heavy chains from immune-inflammatory related complexes; iii) a trypsin treatment device, used for trypsinizing IgG heavy chains; iv) a carbon nitride enrichment device for enriching IgG Fc N-glycopeptides from IgG heavy chain trypsin digests; v) a mass spectrometer to identify the enriched IgG Fc N-glycopeptides and obtain their relative intensities; and vi) A computer readable storage device as claimed in claim 12 or 13.

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