KR101795595B1 - Method for Haematological Diagnosing Non Small Cell Lung Cancer - Google Patents

Abstract

The present invention relates to a method of providing necessary information for the diagnosis of non-small-cell lung cancer, and peptide for the diagnosis of non-small-cell lung cancer. The present invention is a method for haematological diagnosis of non-small-cell lung cancer, and by diagnosing lung cancer through quantifying BCHE in blood, problems of radiation-induced side effects of lung cancer diagnosis using conventional CT can be prevented.

Description

[0001] The present invention relates to a method for diagnosing non-small cell lung cancer,

The present invention relates to a method for hematologic diagnosis of non-small cell lung cancer.

Lung cancer is one of the leading causes of cancer-related death worldwide due to its high metastatic potential and mortality. It is associated with small cell lung cancer (SCLC) and non-small cell lung cancer small cell lung cancer (NSCLC). Approximately 80% of all lung cancer patients are non-small cell lung cancer and consist of two subtypes of adenocarcinoma (ADC) and squamous cell carcinoma (SQC), with over 900,000 patients annually by ADC and SQC Death has occurred [1]. Diagnosis of non-small cell lung cancer through markers is important in improving the prognosis and survival rate of patients.

Serological biomarkers can be analyzed relatively easily and economically, but the discovery of biomarkers using plasma and serum samples is challenging due to the high complexity and wide dynamic range of plasma proteins. Although much effort has been made to discover biomarkers using plasma samples from patients with non-small cell lung cancer [2], unfortunately the clinical use of these markers may be limited.

Over the past decade, high-throughput omics-based technologies have been widely used, and many researchers have studied the differentiation and differentiation of proteins and mechanisms in tumor genomes. The resulting genome, transcriptome, and proteome data are stored in a public database [3]. Technological advances in fields such as the human genome and proteome-bound proteomics, bioinformatics and biostatistics are expected to further develop the healthcare sector, particularly using biomarkers for diagnosis and prognosis. Many lung cancer studies have developed markers of potentially non-small cell lung cancer using a variety of biological samples including cell lines, tissues and serum / plasma [2,4-9]. The candidate markers were evaluated for their diagnostic potential as non-invasive biomarkers using antibody-based assays such as ELISA in human serum / plasma. However, ELISA kits are costly, time consuming, and have the disadvantage of being able to measure only one protein at a time. In addition, the efficacy of high quality commercial ELISA kits has the disadvantage of being dependent on the quality of the antibody.

Recent advances in MS-based quantitation, particularly selected reaction monitoring (SRM) or multiple reaction monitoring (MRM), enable accurate measurement of antibody-free target proteins [11-13]. The high selectivity and specificity obtained using two mass-filtering quadrupoles facilitates the selection of target metastases from complex samples such as plasma / serum and enables reproducible assays.

Numerous papers and patent documents are referenced and cited throughout this specification. The disclosures of the cited papers and patent documents are incorporated herein by reference in their entirety to better understand the state of the art to which the present invention pertains and the content of the present invention.

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The present inventors have sought to develop a method for diagnosing hematological lung cancer for early diagnosis of lung cancer. As a result, the inventors have completed the present invention by diagnosing small cell lung cancer by detecting the expression amount of BCHE in blood based on proteotypic and quantotypic peptides by applying a protein-based diagnostic technique.

Accordingly, an object of the present invention is to provide a method for providing information necessary for diagnosis of non-small cell lung cancer.

Another object of the present invention is to provide a peptide for diagnosing non-small cell lung cancer.

It is another object of the present invention to provide a method for quantifying BCHE in a biological sample.

Another object of the present invention is to provide a diagnostic kit for non-small cell lung cancer.

Other objects and advantages of the present invention will become more apparent from the following detailed description of the invention, claims and drawings.

According to one aspect of the present invention, the present invention provides a method for providing information necessary for diagnosis of non-small cell lung cancer comprising the steps of:

(a) measuring the expression level of BCHE in a biological sample separated from the object, wherein the expression level of the BCHE is measured through quantification of a peptide comprising the amino acid sequence of SEQ ID No. 2; And

(b) analyzing the expression level of the BCHE, wherein the expression level of the BCHE is down-regulated compared to the control, the non-small cell lung cancer is judged.

The present inventors have sought to develop a method for diagnosing hematological lung cancer for early diagnosis of lung cancer. As a result, the expression of BCHE in the blood based on proteotypic and quantotypic peptides was detected by using the protein - based diagnostic technology and diagnosed as small cell lung cancer.

As used herein, the term " diagnosis " refers to determining susceptibility to a subject's disease for a particular disease or disorder, determining whether a particular disease or disorder is presently present, Determining the prognosis of the acquired subject (e.g., identifying a transitional cancerous condition, determining the stage or progress of a cancer, or determining the response of a cancer to treatment), or determining therametrics (e.g., And monitoring the status of the object to provide information).

A method for providing information necessary for diagnosis of non-small cell lung cancer of the present invention will be described step by step.

Step (a): Measurement of the expression level of BCHE

First, the expression level of BCHE is measured in a biological sample separated from an object. The expression level of the BCHE is measured by quantifying a peptide containing the amino acid sequence of the second sequence.

The term " biological sample " as used herein refers to all substances of an organism including nucleic acids, and biological samples usable in the diagnostic method of the present invention include viruses, bacteria, tissues, cells, hair, oral tissues, But are not limited to, lymphatic fluids, bone marrow fluids, saliva, milk, urine, feces, ocular fluids, semen, brain extracts, spinal fluid, articular fluid, mammary fluid, ascites, amniotic fluid or cell tissue fluids. As a biological sample, blood contains whole blood, plasma, or serum.

Specifically, the biological sample is blood, serum or plasma.

As can be seen in the following examples, blood, serum or plasma can be collected from an object to diagnose non-small cell lung cancer.

More specifically, the biological sample is serum or plasma.

The step (a ') of decomposing the biological sample separated from the object prior to the step (a) may be preceded.

Specifically, the degradation is the degradation of the protein in the biological sample. The degradation of the protein may be chemical cleavage or enzymatic digestion. More specifically, degradation of the protein is enzymatic degradation. Wherein the enzymatic degradation is carried out by using at least one enzyme selected from the group consisting of trypsin, pepsin, alcalase, bromelain, papain and neutrase, But the present invention is not limited thereto.

The step (a ') may degrade the protein in the biological sample to a peptide level.

Next, the expression level of BCHE in the biological sample is measured. The expression level of the BCHE is measured by quantitation of the peptide consisting of the amino acid sequence of the second sequence of the Sequence Listing.

Specifically, quantification of the peptide is carried out by multiple reaction mornitoring.

In the present specification, the term " multiple reaction assay method " is a technique capable of quantifying 100-300 protein markers at a time by a single test of a trace amount (e.g., 1 ㎍) sample. Briefly, a specific protein is chemically pretreated to make a peptide, and the mass (Q1, precursor ion m / z) is measured by electron scanning. The peptide is pulverized into peptide fragments, / z), and the quantitative value of a specific protein in the sample is obtained through the mass value of Q1 / Q3 inherent to each protein. This is a way to quantify proteins without antibodies to proteins. For example, a stable isotope labeled peptide standard may be injected prior to mass spectrometry and used for absolute quantitative analysis. For the more efficient quantitative analysis using multiple reaction assays, the selection of unique peptides that are detected only in the candidate protein using databases and programs such as targeted identification for quantitative analysis (MRM), and the generation of MRM transitions for the peptides (Anderson L, et al., Mol. Cell Proteomics. 2006, 5: 573-588).

The present invention has identified a peptide consisting of the amino acid sequence of Sequence Listing 2, which can quantify the expression level of BCHE in a biological sample.

As used herein, the term " peptide " refers to a linear molecule formed by peptide bonds and amino acid residues joined together.

Specifically, the peptide has a transition of 604.313269 / 931.471869 or 599.309134 / 921.4636.

In the present specification, the term " transition " refers to the mass (Q1) of a peptide prepared by chemically pretreating a specific protein and the value of the mass (Q3) of peptide fragments that have been fused with the peptide. The transition is denoted by " Q1 / Q3 ". These transitions are protein-specific values and can be used to quantitatively analyze specific protein concentrations by measuring the mass intensity of a sample by inputting a transition into a mass spectrometer.

The peptides of the present invention can be labeled with isotopes and used as internal standard parameters in biological samples.

The labeling can be performed by adding an amino acid having a stable isotope in the course of peptide synthesis, or by labeling a functional group having a stable isotope at a specific amino acid after synthesis. In the present invention, since the radioactive isotope is used to distinguish the wild type peptide from the wild type peptide by binding to the wild type peptide by binding to the standard peptide, the radioactive isotope does not need to be included in the standard peptide and is included in a form bound to the OH end of the standard peptide It is possible.

The labeling of the isotope may include one or more stable light isotopes or heavy isotopes selected from ¹⁸ O, ¹⁷ O, ³⁴ S, ¹⁵ N, ¹³ C, ² H, do.

As used herein, the term " comprising " used to define the amino acid sequence of a peptide means that it may consist of or consist of additional amino acid sequences as described, and the term " consisting of " Or "consists of ". In addition, the amino acid may include a variation of the amino acid. The amino acid variation is based on the relative similarity of amino acid side chain substituents, such as hydrophobicity, hydrophilicity, charge, size, and the like. By analysis of the size, shape and type of amino acid side chain substituents, arginine, lysine and histidine are both positively charged residues; Alanine, glycine and serine have similar sizes; Phenylalanine, tryptophan and tyrosine have similar shapes. Thus, based on these considerations, arginine, lysine and histidine; Alanine, glycine and serine; And phenylalanine, tryptophan and tyrosine are biologically functional equivalents.

Considering the mutation having the above-mentioned biological equivalent activity, the peptide of the present invention is interpreted to include a sequence showing substantial identity with the sequence described in the sequence listing. The above-mentioned substantial identity is determined by aligning the sequence of the present invention with any other sequence as much as possible, and analyzing the aligned sequence using an algorithm commonly used in the art. Homology, more preferably 80% homology, even more preferably 90% homology, most preferably 98% homology. Alignment methods for sequence comparison are well known in the art. Various methods and algorithms for alignment are described by Smith and Waterman, Adv . Appl . Math. 2: 482 (1981) ; Needleman and Wunsch, J. Mol . Bio. 48: 443 (1970); Pearson and Lipman, Methods in Mol . Biol . 24: 307-31 (1988); Higgins and Sharp, Gene 73: 237-44 (1988); Higgins and Sharp, CABIOS 5: 151-3 (1989); Corpet et al., Nuc. Acids Res. 16: 10881-90 (1988); Huang et al., Comp. Appl . BioSci . 8: 155-65 (1992) and Pearson et al., Meth . Mol . Biol . 24: 307-31 (1994). The NCBI Basic Local Alignment Search Tool (BLAST) (Altschul et al., J. Mol . Biol . 215: 403-10 (1990)) is accessible from National Center for Biological Information (NBCI) It can be used in conjunction with sequence analysis programs such as blastx, tblastn and tblastx.

Step (b): determination of non-small cell lung cancer

Next, the expression level of the BCHE is analyzed. When the expression level of the BCHE is down-regulated as compared with the control, it is judged to be non-small cell lung cancer.

Specifically, when the expression level of BCHE is 3.91 占 1.17 占 퐂 / ml, it is judged to be non-small cell lung cancer.

The method for providing the information necessary for diagnosis of non-small cell lung cancer of the present invention is that a marker according to BCHE et al. Is one or two or more combinations, for example, two, three, four, five, six, For example, peptides consisting of the amino acid sequence of each of Sequence Listing 8, Sequence 4, Sequence 3, and Sequence 10 corresponding to GPx3, CP, C7 and PRG4 are simultaneously quantified . A combination of markers satisfying the desired sensitivity and specificity can be selected through a method such as analysis using a biological sample of a subject including a normal person and a patient such as the method described in this embodiment and / or a logistic regression analysis. By using disease-specific panels, the accuracy (specificity and sensitivity) of diagnosis of non-small cell lung cancer can be increased.

According to another aspect of the invention, the present invention provides a method of quantifying BCHE in a biological sample, comprising quantifying the level of a peptide consisting of the amino acid sequence of the second sequence of the sequence listing in a biological sample.

Since the method of quantifying BCHE of the present invention uses the same method as the method of providing information necessary for diagnosis of non-small cell lung cancer, the content common to the two is omitted in order to avoid the excessive complexity of the present specification do.

According to another aspect of the present invention, the present invention provides a method for providing information necessary for the diagnosis of non-small cell lung cancer comprising the steps of:

(a) measuring the expression level of BCHE in a biological sample separated from an object; And

(b) analyzing the expression level of the BCHE, wherein the expression level of the BCHE is down-regulated compared to the control, the non-small cell lung cancer is judged.

The measurement of the expression level of BCHE in the step (a) can be carried out through various immunoassay methods known in the art. For example, the expression levels of BCHE include, but are not limited to, ELISA (enzyme-linked immunosorbent assay, e.g., direct ELISA, indirect ELISA and sandwich ELISA), radioimmunoassay, radioimmunoprecipitation, immunoprecipitation.

When the method of the present invention is carried out by an ELISA method, a specific embodiment of the present invention comprises the steps of (i) coating an unknown biological sample to be analyzed on the surface of a solid substrate; (Ii) reacting said sample with an antibody to BCHE as a primary antibody; (Iii) reacting the result of step (ii) with an enzyme-conjugated secondary antibody; And (iv) measuring the activity of the enzyme.

Suitable as said solid substrate are hydrocarbon polymers (e.g., polystyrene and polypropylene), glass, metal or gel, and most preferably microtiter plates.

The enzyme bound to the secondary antibody may include an enzyme catalyzing a chromogenic reaction, a fluorescence reaction, a luminescent reaction, or an infrared reaction, but is not limited thereto. For example, an alkaline phosphatase,? -Galactosidase, Radish peroxidase, luciferase, and cytochrome P ₄₅₀ . In the case where alkaline phosphatase is used as an enzyme binding to the secondary antibody, it is preferable that the substrate is selected from the group consisting of bromochloroindole phosphate (BCIP), nitroblue tetrazolium (NBT), naphthol-AS -Bl-phosphate and ECF (enhanced chemifluorescence) are used. When horseradish peroxidase is used, chloronaphthol, aminoethylcarbazole, diaminobenzidine, D-luciferin, lucigenin (10-acetyl-3,7-dihydroxyphenoxazine), HYR (p-phenylenediamine-HCl and pyrocatechol), TMB (tetramethylbenzidine), ABTS (2,2'- Azine-di [3-ethylbenzthiazoline sulfonate]), o - phenylenediamine (OPD) and naphthol / pie Ronin, glucose oxidase and t-NBT (nitroblue tetrazolium) and m-PMS a substrate such as phenzaine methosulfate may be used All.

When the method of the present invention is carried out in a sandwich ELISA system, a specific embodiment of the present invention comprises the steps of (i) coating the surface of a solid substrate with an antibody against the BCHE of the present invention as a capturing antibody; (Ii) reacting the capture antibody with the sample; (Iii) reacting the result of step (ii) with a detecting antibody which is labeled with a signal generating label and specifically reacts with a BCHE protein; And (iv) measuring a signal originating from said label.

The detection antibody has a label that generates a detectable signal. The label may be a chemical (e.g., biotin), an enzyme (alkaline phosphatase,? -Galactosidase, horseradish peroxidase and cytochrome P ₄₅₀ ), a radioactive material (such as C ¹⁴ , I ¹²⁵ , P ³² and S ³⁵ ), fluorescent materials (e.g., fluorescein), luminescent materials, chemiluminescent materials and fluorescence resonance energy transfer (FRET). Ed Harlow and David Lane, Using Antibodies: A Laboratory Manual , Cold Spring Harbor Laboratory Press, 1999.

The measurement of the activity or the signal of the final enzyme in the ELISA method and the sandwich ELISA method can be carried out according to various methods known in the art. This signal detection enables a qualitative or quantitative analysis of the BCHE of the present invention. If biotin is used as a label, it can be easily detected by streptavidin. When luciferase is used, luciferin can easily detect a signal.

By analyzing the intensity of the final signal by the above-described immunoassay, it is possible to determine non-small cell lung cancer. That is, if the signal for BCHE of the present invention in the biological sample is down-regulated from the control, it is determined to be non-small cell lung cancer.

Specifically, the determination in step (b) above is determined to be non-small cell lung cancer when the expression level of BCHE is 4.04 占 .12 占 퐂 / ml.

According to another aspect of the present invention, there is provided a diagnostic kit for non-small cell lung cancer comprising an antibody or an aptamer that specifically binds to a BCHE protein for detecting BCHE in a biological sample separated from an object.

Since the diagnostic kit for non-small cell lung cancer of the present invention uses the same immunoassay method as the method for providing the information necessary for diagnosis of non-small cell lung cancer, the common content between them avoids the excessive complexity of the present specification , The description thereof is omitted.

The features and advantages of the present invention are summarized as follows:

(a) The present invention provides a method for providing information necessary for diagnosis of non-small cell lung cancer and a peptide for diagnosing non-small cell lung cancer.

(b) The present invention is a hematological diagnostic method for non-small cell lung cancer. By diagnosing lung cancer by quantifying BCHE in blood, it is possible to solve the problem of radiation-induced side effects of lung cancer diagnosis using conventional CT.

Figure 1 is a schematic diagram of the experimental procedure used in this study.
Figures 2a-2d are analyzes of a GEO 10 transcriptome data set. Figure 2a shows a hierarchical cluster analysis of 3232 DEGs (differentially expressed genes) between tumor and non-tumor tissue (p-value <0.001; fold change +/- 15%; red: up-regulated; Figure 2b shows the number of identified proteins in the cell secretory (FDR < = 1%). The secretion pathway was predicted using SignalP, SecretomeP and TMHMM. Figure 2c classifies DEGs based on the molecular function proposed in DAVID Figure 2d shows the location of the quasi-cell of DEG (black: upregulated in non-small cell lung cancer; white: downregulated in non-small cell lung cancer ).
FIGS. 3A to 3D are the results of analysis of conditioned media harvested from non-small cell lung cancer cell lines. FIG. FIG. 3A shows the result of Western blot analysis of the protein (10 μg) in conditioned medium (CM) and cell extract (CE) using an anti-α-tubulin antibody. Figure 3b is the number of identified proteins in the cell secretory (FDR a 1%). SignalP, SecretomeP and TMHMM were used to predict the secretion pathway. The human-FBS database was used to distinguish the bovine contaminants. Figure 3c is a Venn diagram of DEG and protein in tissue identified from cell secretory. Figure 3d is an estimated secretory pathway of identified secretory proteins in all cell lines.
4A to 4D are the results of proteome analysis of plasma by mass spectrometry. Figure 4a shows SDS-PAGE (protein 10 [mu] g) of pooled plasma taken from 10 healthy controls and 10 lung cancer patients divided into 25 fractions. Figure 4b is a schematic diagram of the high-pH RPLC fraction (10 [mu] g protein) description. The eluate was combined into a column (1-12 columns, 12 fractions). The corresponding peptides were monitored by measuring the UV absorbance of the eluate at 215 nm. Figure 4c is a Venn diagram of proteins identified with GeLC-MS / MS and high-pH RPLC fractions. 4D is a Venn diagram of the number of molecules analyzed in DEG, secretory and plasma proteomes.
Figures 5A through 5E show a systematic evaluation of serum MRM analysis. Figure 5a is the total ion chromatogram (TIC) of endogenous (red) peptide and each SIS peptide (blue). Figure 5b is a circular heat map of the relative expression of the two groups of six proteins. The 46 clinical samples were 23 control and 23 non-small cell lung cancer (adenocarcinoma 16, squamous cell carcinoma 17). Following the indexing, a sequence of LC-MRM run was performed. FIG. 5c is the BCHE serum concentration of the control and non-small cell lung cancer group, and FIG. 5d is the serum concentration of GPx3 of the control and non-small cell lung cancer group. Figure 5E is the ROC curve of BCHE, GPx3 and the combination of the two proteins.
Figures 6a to 6c are quantitative results using ELISA of two proteins in an independent set of control (n = 50) and non-small cell lung cancer (n = 50) samples. Serum levels of BCHE (A) and GPx3 (B) in control and non-small cell lung cancer groups. Figure 6C is the ROC curve of BCHE, GPx3 and the combination of the two proteins.

Hereinafter, the present invention will be described in more detail with reference to Examples. It is to be understood by those skilled in the art that these embodiments are only for describing the present invention in more detail and that the scope of the present invention is not limited by these embodiments in accordance with the gist of the present invention .

Throughout this specification, "%" used to denote the concentration of a particular substance is intended to include solids / solids (wt / wt), solid / liquid (wt / Liquid / liquid is (volume / volume)%

Example

1. Materials and Methods

1.1. Mining of gene expression omnivus Microarray data

Human arrays can be obtained from GEO (Gene Expression Omnibus) of the National Center for Biotechnology Information (NCBI) and are widely used as open repositories for gene expression data. 10 data sets (GEO accession numbers GSE1643 [14], GSE12667 [15], GSE10245 [16]) using the same platform (GPL 570; Affymetrix Human Genome U133 Plus 2.0 Array) were used to compare mRNA expression of lung cancer and normal tissues. , GSE18842 [17], GSE10445 [18], GSE19188 [19], GSE10799 [20], GSE19804 [21], GSE12345 [22], and GSE21369 [23]. In many experiments, global proportions are assumed to be different depending on position and / or intensity level, so global normalization is applied, assuming a mathematically constant coefficient of proportionality for all genes in the array [24]. In this approach, the median distribution of expression through the microarray (the level of expression for all genes in the microarray) was set equal. Next, false discovery rates (FDRs) were calculated (q <0.001) to perform a heteroscedastic t-test to determine statistical significance (p <0.001) ].

1.2. Manufacture of secretome

RPMI1640 (Gibco, Rockville, MD, USA) supplemented with 10% FBS (Gibco) and 1% penicillin / streptomycin (Gibco) was used to humidify the lung cancer cell lines A549, Calu-1, H1299, H23, H460 and H520 And cultured in a 95% air, 5% CO ₂ incubator at 37 ° C. Cells were grown to about 70% confluence and carefully washed three times with serum free medium (SFM) at room temperature. Next, the cells were cultured in SFM at 37 ° C for 12 hours to minimize the release of cytoplasmic proteins to the periphery due to apoptosis. After the incubation, the conditioned medium was carefully collected and 2 mM PMSF and 1 mM EDTA were treated with the protease inhibitor. Suspension cells and cell debris were removed by centrifugation (400 × g, 10 min, 4 ° C.) and sterile filtration (pore size: 0.22 μm, Millipore, MA, USA). The medium was concentrated and ultrafiltered using an Amicon Ultra-15 centrifugal filter device (Millipore) and replaced with a buffer consisting of 8 M urea, 75 mM NaCl and 50 mM Tris (pH 8.2).

1.3. Plasma and Serum

All blood samples were prepared by collecting blood in EDTA tubes and preparing plasma as in the HUPO plasma proteome project [26]. Plasma samples for pre-test were collected at Yonsei Severance Hospital (Seoul, Korea) and obtained permission from IRB to use the samples for research purposes. Plasma samples taken from 10 lung cancer patients and 10 healthy controls were used. (Α1-acid glycoprotein, fibrinogen, α1-antitrypsin, haptoglobin, α2-macroglubulin, IgA, albumin, IgG, and albumin) in plasma using PierceTM Top12 Abundant Protein Depletion Spin Columns (Pierce, Rockford, IL, USA) apolipoprotein AI, IgM, apolipoprotein A-II and transferrin).

Serum samples used in the MRM study consisted of 23 patients with non - small cell lung cancer (adenocarcinoma 16, squamous cell carcinoma 7 before initiation of treatment at Chonnam National University Hwasun Hospital) and 23 healthy control subjects. For ELISA-based assays, independent non-small cell lung cancer patients (n = 50, all new patients) and controls (n = 50, 41 were new normal controls and 9 others were MRM controls) were selected. Clinical information was obtained through chart review, and all diagnoses were histologically confirmed by surgical biopsy. This study was approved by IRB (HCRI 12045-3) of Chonnam National University Hwasun Hospital. Serum samples were immediately placed on ice, transferred to the laboratory, centrifuged and dispensed, and frozen at 80 ° C until use.

1.4. Protein degradation by trypsin

For in-solution digestion, all samples (~ 100 μg) of cell line, plasma and serum-derived secretory form were incubated with 5 mM DTT (Sigma, St. Louis, MO, USA) And alkylated with 14 mM iodoacetamide (Sigma, St. Louis, MO, USA) at 30 ° C for 1 hour. Samples were diluted 5 times to reduce the urea concentration to 1.6 M and CaCl ₂ (Sigma) was added to a final concentration of 1 mM. Protein mixtures were digested with sequencing grade modified trypsin (Promega, Madison, WI, USA) at 37 ° C for 16 hours (enzyme: protein = 1:50). Peptides degraded by trypsin were desalted with C18 spin column (Thermo Scientific, Waltham, Mass., USA) and further fractionated.

For in-gel digestion, the pooled plasma was reduced with 20 mM DTT at 56 ° C for 1 hour and alkylated with 50 mM iodoacetamide (in 25 mM ammonium bicarbonate) for 1 hour under dark conditions. After treatment, the reagent was removed and the gel piece washed with 50 mM ammonium bicarbonate and dehydrated with acetonitrile. The dried gel pieces were then rehydrated in a trypsin solution (25 mM ammonium bicarbonate) for 16 hours. The trypsin peptide in the gel was extracted with 50% acetonitrile (in 5% formic acid) and 70% acetonitrile (in 5% formic acid). All the degradation products were desalted with a C18 spin column, vacuum dried and stored at 80 ° C until use.

1.5. After decomposition in solution,

The tryptic cleavage from the secretory tract was further separated into 12 fractions using an OFFGEL 3100 fractionator (Agilent Technology, Santa Clara, Calif., USA) based on the peptide isoelectric point. All fractions were desalted with C18 spin columns (Thermo Scientific), vacuum dried and stored at 80 ° C until use. Trypsin digests of depleted plasma samples were fractionated by high pH, reversed phase (RP) micro LC using AKTA Exploer (GE Healthcare Life Science, USA). Fractionation was performed using an XBridge C-18 column (diameter 4.6 mm, length 250 mm, pore size 130 Å, particle size 5 mm, Waters Corporation, Milford, Mass., USA) at a flow rate of 0.5 mL / min. The mobile phase A was 10 mM ammonium formate (pH 10) and the mobile phase B was 10 mM ammonium formate (in 90% acetonitrile, pH 10). The plasma lysate was dissolved in 125 [mu] l of mobile phase A and then injected manually into a 100 [mu] l sample loop. After a gradient of 5-10% Phase A for 5 minutes, 10-30% Phase B for 45 minutes, 30-45% Phase B for 10 minutes and 45-90% Phase B for 15 minutes, the columns were washed for 30 minutes each Lt; RTI ID = 0.0 &gt; 100% &lt; / RTI &gt; In the fractionation procedure, the eluent was collected every minute on a 96-well plate in the Frac-950 fraction collector of AKTA Explorer [12]. A total of 96 fractions, 8 column (A-E) × 12 columns (1 to 12) peptide eluants were combined in a column and connected in one fraction. In addition, surrogate peptides were found during high-pH RPLC by monitoring the UV absorbance of the eluent at 215 mm. The fractions selected for the next step of LC-SRM / MS were dried and stored at 20 ° C until use.

1.6. Liquid chromatography and double mass spectrometry (LC-MS / MS)

The peptide sample was reconstituted in 0.4% acetic acid and the fraction (~ 1 ug) was injected onto a reversed phase Magic C18 _aq column (15 cm × 75 μm, 200 Å, 5 U). The column was pre-equilibrated with 95% Buffer A (0.1% formic acid in water) and 5% Buffer B (0.1% formic acid in acetonitrile) on an Agilent 1200 HPLC system. The peptides obtained from Sikritom were eluted over an analytical column with a linear gradient of 5-40% Buffer B for 90 minutes at a flow rate of 0.4 l / min. The HPLC system was connected to an LTQ-XL mass spectrometer (Thermo Scientific, San Jose, Calif.). The ESI voltage was set to 1.9 kV, the capillary voltage was set to 30 V, and the temperature of the heated capillary was set to 250 캜. The MS survey was scanned at 300-2,000 m / z and then subjected to three data-dependent MS / MS scans according to the following three options: separation width, 1.5 m / z; Standardized impact energy, 25%; Dynamic exclusion duration, 180 seconds. All experiments were performed in duplicate and all data were obtained using Xcalibur software v2.0.7.

Analyzes from plasma were analyzed using the LTQ-XL-Orbitrap mass spectrometer (Thermo Scientific). The spraying voltage was set to 1.9 kV and the temperature of the heated capillary was set to 250 캜. Measurement The full scan MS spectrum (300-2000 m / z) was obtained from Orbitrap with one microscope and 100,000 resolution, allowing preview mode for precursor screening and charge-state measurements. The MS / MS peptides of the strongest ion 10 in the preview survey scans were simultaneously collected in the ion-trap to obtain a full scan of Orbitrap and the following options were used: separation width 10 ppm; Standardized impact energy. 35%; Dynamic exclusion duration, 30 seconds. Precursors with unmatched dislocation states were excluded from the data-dependent acquisition process. Precursors with a single charge were also excluded. Data was obtained using Xcalibur software v2.0.7.

1.7. Analysis of mass data

MS / MS spectra obtained from the cell secretor were searched using the SEQUEST (TurboSequest version 27, revision 12) for the UniProtKB database (released March 2012) containing human experimental and validated FBS UniProtKB database [27] . Two trypsin-missed cleavages were allowed, and peptide mass tolerances of MS / MS and MS were set to ± 0.5 and ± 2 Da, respectively. Another option used in SEQUEST is a fixed strain (+57.02 Da) of carbaminomethylation in cysteine and a variable strain (+15.99 Da) of oxidation in methionine. Peptide placement and validation were performed using the Trans-Proteomic Pipeline (TPP, version 4.0). SEQUEST search output was used as an input for TPP analysis. MS / MS spectra from plasma samples were analyzed using SEQUEST in Proteome Discoverer 1.4 (Thermo Fisher Scientific, version 1.4.0.288). The search parameters were the same as those mentioned above. For the verification of peptide sequence matching (PSM), the q value was calculated as a measure of the statistical reliability for each PSM using a percolator. The output was filtered with q <0.01.

1.8. Bioinformatics for Data Mining

ProteinCenter (Proxeon Bioinformatics) was used to analyze the identified secreted proteins. Several proteins were submitted in one FASTA format file for each program. SignalP (version 4.0) was used to predict the presence of signal peptides in identified proteins [28]. We used the SecretomeP program (version 2.0) to predict the probability of non-standard protein secretion. In addition, the TMHMM program (version 2.0) was used to predict transmembrane helix of visceral membrane proteins. All secreted proteins were further analyzed using the Plasma Proteome Database (PPD). Ingenuity Pathway Analysis (IPA, Ingenuity system) was used to determine intracellular localization and biological function of proteins.

1.9. The stable isotope standard (SIS) synthetic peptide

The MRM assay panel consisted of 11 light peptides instead of 8 plasma proteins corresponding to 11 internal SIS peptides from the pre-screening LC-MRM / MS data. The selected peptides were quantified as double or triple charged precursor ions to ensure stable and reproducible detection. A synthetic SIS peptide containing [ ¹³ C ₆ , ¹⁵ N ₂ ] lysine and [ ¹³ C ₆ , ¹⁵ N ₄ ] arginine at the carboxy terminus was obtained from 21st Century Biochemical (Marlboro, Mass., USA). Amino acid analysis (AAA) for each peptide was performed by the supplier. These peptides were redissolved in 20% acetonitrile containing 0.1% formic acid on a scale similar to that expected for target proteins in plasma. Eleven SIS peptides were pooled and added to plasma prior to trypsin degradation.

1.10. Multiple reaction monitoring mass spectrometry (MRM-MS)

LC-MRM-MS analysis was performed by two-column switching on nanoLC-MRM-MS. The LC system consists of the Eksigent nanoLC-Ultra 2D Plus and the NanoFlex system. Mobile phase A and mobile phase B are water (solvent A) and acetonitrile (solvent B), each containing 0.1% formic acid. Plasma sample lysates were reconstituted with 22.5 [mu] l of 2% acetonitrile and 0.1% formic acid. Each sample was picked up in a 1 μl sample loop and flow rate was adjusted to 300 nL using a Nano cHiPLC ReproSil-Pur C18-column (id 75 μm, length 15 cm, pore size 120 A, particle size 3 μm, Eksigent Technologies, Dublin, CA) / Min. The column was maintained at 40 &lt; 0 &gt; C. Because the two-column switching method was used, the sample was loaded into the regenerated column (i.e., the column where the flow was not directed to the mass spectrometer) as follows: mobile phase B (5-90-5-90-5% ), Followed by re-equilibration at 5% B for 40 minutes. A sample was injected into the loading column at 30 minutes. The sample was separated by the following eluting method: a gradient of 5% to 10% B over 4 minutes, a gradient of 10% to 25% over 30 minutes, 3 minutes (for example, Keep a gradient of 25% -60% B, 60% B for 3 minutes, a gradient of 60% -5% B for 1 minute, and 5% B for 9 minutes. The LC system was connected to a 5500 Qtrap mass spectrometer (ABSciex) by a nanoelectrospray ion source (SCIEX, Foster City, Calif.). MS detection was performed in a positive MRM mode with the following parameters: ion spray voltage 2200 V, curtain gas 10 psi, atomizer gas 30 psi, resolution at 0.7 Da (unit resolution) for Q1 / Q3, Mass range m / z &gt; 300-1250. The collisional energy (CE) and declustering potential (DP) were optimized by direct injection using a Turbospray (Sciex, Foster City, CA). Quantification was performed using an unscheduled MRM mode with a residence time of 20 ms and a cycle time of 2.4 s [30]. The original data was stored in the PeptideAtlas database (accession number PASS00767).

1.11. Analysis of MRM-MS data

Analyst software (version 1.5.2, ABSciex) was used to generate MRM-MS data and to optimize MRM parameter data (*. Wiff). Skyline (version 2.6.0) [31] was used to analyze the MRM results of extracted ion chromatograms (XICs). Standard peptides labeled with stable isotopes (C-terminal lysine or arginine 12C / 14N replaced with 13C / 15N) were synthesized and then added to the peptide in a predetermined amount to measure the MRM. When each peptide was fragmented by CID in a mass spectrometer, four or more transitions consisting of a combination of parent and daughter ions were measured. One transient with low interference and highest sensitivity was selected and quantified using the ion chromatograms (XICs) extracted from the transitions of the peptides and standard peptides of the sample. Marker candidate proteins were statistically analyzed using Excel 2010 (version 14.0, Microsoft Office) and R software (version 3.1.0).

1.12. ELISA-based verification of proteins in blood samples

Serum levels of GPx3 and BCHE were determined using a commercial ELISA kit (AdipoGen, Inc., Korea, R & D Systems, Inc., USA, USA). Each microtiter plate was coated with human GPx3 specific polyclonal antibody or human BCHE specific monoclonal antibody. For GPx3, serum samples from each patient were diluted 1: 250 and 100 μl were added to the wells and incubated at 37 ° C for 1 hour. After washing the plate three times, 100 [mu] l of primary detection antibody was added. After incubation at 37 ° C for 1 hour, the plate was washed three more times and 100 μl of secondary detection antibody was added. Followed by further incubation at 37 DEG C for 1 hour. After washing the plate 5 times, 100 [mu] l of substrate solution was added. Plates were then read at a wavelength of 450 nm within 20 minutes using a VERSAmax microplate reader (Molecular Devices, Sunnyvale, Calif.). For BCHE, each serum sample was diluted 1: 2000 and 50 [mu] l was added to the wells. Plates were incubated at room temperature for 2 hours on a horizontal orbital microplate shaker set at 500 rpm. After washing the plate three times, 200 [mu] l of detection antibody was added and incubated at room temperature for 2 hours in a shaker. After 3 washes, 200 [mu] l of substrate solution was added to each well. Then, the cells were incubated at room temperature for 30 minutes under dark conditions. Absorbance at 450 nm was read on an Infinite M200 Pro microplate reader (TECAN, Mannedorf, Switzerland). All experimental procedures were performed in duplicate and the measurements were averaged.

1.13. Statistical analysis

Analysis of ELISA data was performed using SOFTMax Pro version 5 software (Molecular Devices, Sunnyvale, Calif.). All MRM-MS and ELISA values were expressed as mean SD. The Mann-Whitney test was used to compare the age, BCHE and GPx3 levels of the two groups (control and non-small cell lung cancer). A chi-square test was used to evaluate differences in sex, smoking history, hypertension (HTN) and diabetes (DM) among the serum sample groups. AUC was assessed by receiver operating characteristic curve (ROC) analysis. p value <0.05 was considered statistically significant. All statistical analyzes were performed with SPSS Statistics 21 (IBM, Armonk, United States).

2. Results

2.1. Quantitative analysis of GEO data

A schematic diagram of the experimental procedure used in this study is shown in FIG. The starting point is gene expression data analysis. 10 GEO data sets (GSE1643 [14], GSE12667 [15], GSE10245 [16], GSE18842 [17], GSE10445 [18], GSE19188 [19], GSE10799 [20], GSE19804 [21], GSE12345 [ And GSE21369 [23]) and used to identify non-invasive lung cancer-specific genes (Table 1).

Access number title platform Journal Year of publication Number of samples GSE1643 Non-diseased lung tissue GPL570a Am J Respir Cell Mol  Biol 2006 40 GSE10245 Non-small lung cancer subtypes: adenocarcinoma and squamous cell carcinoma GPL570 Lung Cancer 2009 58 GSE10445 Merlion lung cancer study GPL570 Cancer Res 2009 72 GSE10799 Gene expression profile of lung tumors GPL570 Clin  Cancer Res 2009 19 GSE12345  Global gene expression profiling of human pleural mesotheliomas GPL570 PLoS One 2009 13 GSE12667 Discovery of somatic mutations in lung adenocarcinomas GPL570 Nature 2008 75 GSE18842  Gene expression analysis of human lung cancer and control samples GPL570 Int  J Cancer 2011 91 GSE19188 Expression data for early stage NSCLC GPL570 PLoS One 2010 156 GSE19804  Genome-wide screening of transcriptional modulation in nonsmoking female lung cancer in Taiwan GPL570 Cancer Epidemiol Biomarkers Prev 2010 120 GSE21369 Gene expression profiles of interstitial lung disease (ILD) patients GPL570 BMC Med  Genomics 2011 29

This analysis included 20,297 genes in 271 normal lung tissues and 547 lung cancer tissues. A global standardization method was applied to all data sets to collect a total of 3232 DEG based on the bi-dispersive T-test p-value <0.001, the FDR q-value <0.001 and the change in expression magnification> ± 15% In lung cancer tissues, 2507 genes were up-regulated (maximal multiple changes; 2.287), and 725 genes were down-regulated (maximal multiple changes; 0.524). A hierarchical cluster analysis of DEG is shown in the heat map of FIG. 2A. Up-regulated genes in cancer tissues are involved in transcription factor activity, membrane permeability transporter activity, and enzyme inhibitor activity, and down-regulated genes are involved in protein binding, signal transducer activity, and substrate-specific transporter activity 2B). DEG was predominantly localized in the extracellular domain (Fig. 2C), indicating that the DEG protein is more likely to be secreted from the cell.

2.2. Identification of secretory cells of lung cancer cells by LC-MS / MS

The secretion of six lung cancer cell lines (A549, Calu-1, H1299, H23, H460, and H520) was profiled by LC-MS / MS (Fig. 1). The main goal of this analysis is to identify proteins that can be secreted in the cancer cells of non-small cell lung cancer. The? -Tubulin was measured as a negative control of the secretory cells of the cells in Western blot analysis. The cytoskeletal proteins were clearly detected in cell extracts but not in conditioned media (Fig. 3A). This means that the secretory protein is rarely contaminated with the intracellular proteins released from the ruptured cells. A total of 2,992 non-redundant human proteins were identified in six cell lines and 942, 1498, 1114, 1390, 1328 and 1128 proteins were identified in A549, Calu-1, H1299, H23, H460 and H520, .

2.3. Integration of DEG and cell secretory data

The DEG identified in open gene expression data was integrated with the protein obtained by profiling the cancer cell secrete (Fig. 1). As a result of binding 3,232 DEGs to 2,992 secreted proteins, 281 proteins were superimposed between the two lists (215 upregulated DEG and 66 downregulated DEG; Fig. 3C). These 281 genes / proteins showed a quantitative change in cancer tissue compared to the levels of cancer cells in normal tissues and hypothesised that they would be suitable lung biomarkers in plasma / serum because they are also present in the cell cytochrome. Thus, these 281 proteins were considered potential marker candidates for lung cancer.

The 281 protein was analyzed using a bioinformatics program designed to predict the protein secretion pathway, and 70% of the proteins (198 of 281 proteins) expected to be secreted via various secretion pathways (FIG. 3D) were analyzed. Briefly, based on the SignalP program, 46% of the protein was secreted through the classic secretory pathway based on the presence of the signal peptide (D cut-off value for SignalP-noTM network> 0.45 or SignalP-TM networks> 0.5 signal Peptides = cut-off for 'yes') [28]. The SecretomeP 2.0 program predicted that 21% of the protein would be released via a non-classical secretory pathway (SignalP signal peptide = 'No, SecretomeP score> 0.5) [29]. An additional 3% of the proteins were determined as complete membrane proteins via TMHMM [30]. Of these, 203 proteins (72.2%) were reported as plasma proteins in PPD, of which 6.8% (19 proteins) were also evident in the MRM-MS spectrum.

2.4. Detection of Candidate Proteins in Plasma by LC-MS / MS Analysis

Next, the detectability of 281 protein in human plasma or serum was evaluated (Fig. 1). 12 proteins rich in proteins were removed from samples prepared by mixing 10 plasma lung cancer patients and 10 healthy human plasma samples, and the resultant protein samples were analyzed by GeLC (25 gel piece in Fig. 4A) and partially after the in-solution trypsin digestion, LC-MS / MS analysis was carried out after fractionation through two independent methods of fractionation (12 fractions in Figure 5B). All LC-MS / MS implementations were performed using predefined inclusion lists. The inclusion list included m / z values of proteotypic peptides for 215 candidate proteins that were up-regulated in tumor tissue and detected at the secretion site. A total of 524 non-overlapping proteins were identified from the plasma proteome profile (Figure 4C). Seventeen proteins were finally selected based on an integrated analysis comprehensively synthesizing gene expression data, cancer cell division and plasma proteome of lung cancer patients among 281 candidate proteins (FIG. 4D).

2.5. Optimization of LC-MRM-MS for detection of candidate proteins

Proteotypic peptides and MRM transitions for 17 selected proteins were selected based on the results of plasma proteome profiling. Six to 20 amino acid sequences and unique double-charged trypsin peptides from the Uniprot database (published after 2014.02) were the primary choice. Peptides containing proline, a proline following the trypsin site, a basic amino acid at the P1 'site and known single amino acid polymorphisms (SAPs) or post-translational modifications at the P2 (xxxxPK / R) or P3 (xxxxPxK / R) 13]. Finally, 78 peptides of 17 proteins were selected as targets for LC-MRM-MS.

The tandem mass spectra of 78 selected peptides were used to generate MRM transitions by searching in the Global Proteome Machine (GPM) and National Institute of Standards and Technology (NIST) databases. To maintain high reproducibility, the possibility of accessing the peptide through MRM in whole plasma / serum without prior immunodepletion was assessed because the affinity-based depletion process in the MRM assay was excluded. Our team developed intermittent optimization of device parameters such as declustering potential (DP), collisional energy (CE) and collision cell exit potential (CXP) 373 transitions of 78 peptides were monitored using LC-MRM run [32]. Finally, eleven peptides of eight proteins (Table 2) were clearly detected and considered as detectable and quantifiable marker candidates that could be included in the next verification step by LC-MRM-MS. Therefore, we synthesized heavy isotope label standards for eleven target peptides.

- protein Peptide sequence Target ion Q1 / Q3 Sequence List One BCHE NIAAFGGNPK 2y8.heavy 498.771265 / 769.408263 First sequence 2y8.light 494.764166 / 761.394064 YLTLNTESTR 2y7.heavy 604.313269 / 931.471869 Second sequence 2y7.light 599.309134 / 921.4636 2 C7 VLFYVDSEK 2y7.heavy 554.294239 / 895.428724 Third sequence 2y7.light 550.287139 / 887.414525 3 CP ALYLQYTDETFR 2y8.heavy 765.37914 / 1069.482434 Fourth sequence 2y8.light 760.375006 / 1059.474165 EYTDASFTNR 2y5.heavy 607.271601 / 634.318269 Fifth sequence 2y5.light 602.267467 / 624.310 4 CRISP3 YEDLYSNC * K 2y7.heavy 600.26007 / 907.406943 6th sequence 2y7.light 596.252971 / 899.392744 5 GGH YYIAASYVK 2y6.heavy 543.291499 / 646.365001 Seventh sequence 2y6.light 539.2844 / 638.350802 6 GPX3 FLVGPDGIPIMR 2y4.heavy 662.8697 / 526.304533 Eighth sequence 2y4.light 657.865565 / 516.296264 LFWEPMK 2y5.heavy 479.750956 / 698.342157 Ninth sequence 2y5.light 475.743856 / 690.327958 7 PRG4 DQYYNIDVPSR 2y3.heavy 690.326908 / 369.212013 Tenth sequence 2y3.light 685.322773 / 359.203744 8 SPP2 VNSQSLSPYLFR 2y6.heavy 710.876568 / 792.42782 Eleventh sequence 2y6.light 705.872433 / 782.419551

C ^* is Carbamidomethyl-cysteine.

2.6. Standard and demographic characteristics of serum samples

Forty-six patients were enrolled in this study for biomarker measurements by MRM-MS. Twenty - three subjects who were enrolled in the control group visited our hospital for regular physical examination. No patient had previously had a malignant tumor in the control group. The mean age of the control group was 56.5 ± 14.9 years. 14 subjects were male (56%) and 6 had a history of smoking (26%). 5 had hypertension (HTN, 22%) and 1 had diabetes (DM, 4%). Twenty - three patients with adenocarcinoma (70%) and seven patients with squamous cell carcinoma (30%) were enrolled in the non - metastatic lung cancer group (NSCLC). The mean age of non-small cell lung cancer was 60.3 ± 9.8 years; Ten men (43%) were male and six were smoking history (26%). Eight patients had hypertension (35%) and four patients had diabetes (21%) (Table 3).

For ELISA measurements of biomarkers, an independent set of samples from the control (n = 50) and non-small cell lung cancer (NSCLC, n = 50) samples was selected. The mean age of the control group was 56.9 ± 10.2 years. 26 (52%) were men and 13 (26%) were smoking history. 12 were HTN (24%), and 7 were DM (14%). Adenocarcinoma was found in 40 patients (80%) and squamous cell carcinoma in 10 patients (20%). The mean age of non-small cell lung cancer was 59.2 ± 8.4 years; 17 (34%) were male and 14 (28%) were smoking history. 19 had hypertension (38%) and 8 had diabetes (16%).

- MRM-MS ELISA Control group NSCLC p-value Control group NSCLC p-value Number 23 23 - 50 50 - age 56.5 ± 14.9 60.3 ± 9.8 0.66 56.9 ± 10.2 59.2 + - 8.4 0.23 gender
(M / F) 14/9 10/13 0.24 26/24 17/33 0.07 smoking
(Y / N) 6/17 6/17 1.00 13/37 14/36 0.82 HTN
(Y / N) 5/18 8/15 0.33 12/38 19/31 0.13 DM
(Y / N) 1/22 4/19 0.35 7/43 8/42 0.78

2.7. Identification of Marker Candidates for Non-Small Cell Lung Cancer by MRM-MS Analysis

We monitored 11 peptides corresponding to the 8 target proteins in the sample without immunological depletion or fractionation through MRM-MS analysis. All samples were randomly sequenced. In addition, 12 randomly selected samples (5 healthy controls, 4 adenocarcinoma patients, 3 squamous cell carcinoma patients) were repeated 3 times to evaluate the reproducibility and accuracy of the analysis procedure.

XIC corresponding to the SIS peptide and XIC of the endogenous peptide were compared to obtain the final quantitative value (Fig. 5A). Of the 11 peptides monitored by MRM, only one peptide, CRISP3.YEDLYSNCK, was not found in several triplicates. Therefore, the deviation (CV) for this peptide could not be calculated. For the other peptides SPP.VNSQSLSPYLFR and GGH.YYIAASYVK, the signal-to-noise ratio was lower than 3 in over 50% of the normal and NSCLC serum samples, and the two-fold repeatable CV exceeded 30%. The CV of the remaining 8 peptides was less than 20% and the median was 4.4%. The three proteins, BCHE, CP, and GPx3, used two peptides simultaneously monitored and peptides that displayed a higher MRM signal for final protein-level quantification. The other two proteins (C7 and PRG4) showed only one representative peptide. The relative standard deviation (RSDs,%) of the retention times of the five quantotypic peptides was less than 6%. The levels of the five target proteins are shown in FIG. 5B as a circular heat map according to the sample evaluation sequence.

The levels of the five biomarker candidates were compared between the two groups (control and non-small cell lung cancer) using the Mann-Whitney test (Table 4). Only two proteins (BCHE and GPx3) with significant differences between the control and non-small cell lung cancer groups were selected. The mean BCHE values of the control and non - small cell lung cancer groups were 4.87 ± 1.27 ㎍ / ㎖ and 3.91 ± 1.17 ㎍ / ㎖, respectively (p <0.05). The GPx3 levels of the control and non-small cell lung cancer groups were 11.20 ± 2.26 ㎍ / ㎖ and 9.79 ± 1.98 ㎍ / ㎖, respectively (Figs. 5C and 5D and Table 4). As a result of ROC analysis, the AUC of BCHE was 0.713 (95% confidence interval (CI): 0.563-0.862, p <0.05) and the AUC of GPx3 was 0.673 (95% CI: 0.517-0.828, p <0.05). Combining these two values increased the AUC to 0.773 (95% CI: 0.631-0.915, p <0.01) (Fig. 5E).

(占 퐂 / ml) MRM-MS ELISA Control group NSCLC p-value Control group NSCLC p-value BCHE 4.87 ± 1.27 3.91 ± 1.17 &Lt; 0.05 4.50 + - 0.93 4.04 ± 1.12 &Lt; 0.05 C7 40.72 ± 12.79 32.61 ± 14.00 0.11 - - - CP 2006.94 ± 538.75 1934.31 + - 631.82 0.49 - - - GPx3 11.20 ± 2.27 9.79 ± 1.98 &Lt; 0.05 13.79 ± 5.25 9.01 + - 4.27 <0.01 PRG4 5.83 + 1.84 6.81 + - 3.07 0.30 - - -

3.8. ELISA-based quantitative assays for GPx3 and BCHE

Two biomarkers selected by MRM (BCHE and GPx3) were validated with ELISA with independent control and patient (NSCLC) samples. The levels of BCHE and GPx3 in the control and non-small cell lung cancer groups were compared by the Mann-Whitney test (Table 4). The BCHE level of the control group was significantly different from the non-small cell lung cancer group (p <0.05). The mean BCHE values of the control and non-small cell lung cancer groups were 4.50 ± 0.93 ㎍ / ㎖ and 4.04 ± 1.10 ㎍ / ㎖, respectively (Fig. 6A and Table 4). The GPx3 level of the control group was significantly different from the non-small cell lung cancer group (p <0.01). The mean GPx3 values of the control and non-small cell lung cancer groups were 13.79 ± 5.25 ㎍ / ㎖ and 9.01 ± 4.27 ㎍ / ㎖, respectively (Fig. 6B and Table 4). ROC curves for GPx3 and BCHE were generated in the validation group. The AUC for BCHE was 0.630 (95% CI: 0.520 +/- 0.740, p <0.05); The AUC for GPx3 was 0.759 (95% CI: 0.665 +/- 0.852, p < 0.01). In the combined model of GPx3 and BCHE, the AUC was 0.788 (95% CI: 0.700 + 0.876, p < 0.01) (Fig. 6C).

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the same is by way of illustration and example only and is not to be construed as limiting the scope of the present invention. It is therefore intended that the scope of the invention be defined by the claims appended hereto and their equivalents.

<110> INDUSTRY FOUNDATION OF CHONNAM NATIONAL UNIVERSITY <120> Method for Haematological Diagnosis Non Small Cell Lung Cancer <130> PN170064 <160> 11 <170> KoPatentin 3.0 <210> 1 <211> 10 <212> PRT <213> Homo sapiens <400> 1 Asn Ile Ala Ala Phe Gly Gly Asn Pro Lys   1 5 10 <210> 2 <211> 10 <212> PRT <213> Homo sapiens <400> 2 Tyr Leu Thr Leu Asn Thr Glu Ser Thr Arg   1 5 10 <210> 3 <211> 9 <212> PRT <213> Homo sapiens <400> 3 Val Leu Phe Tyr Val Asp Ser Glu Lys   1 5 <210> 4 <211> 12 <212> PRT <213> Homo sapiens <400> 4 Ala Leu Tyr Leu Gln Tyr Thr Asp Glu Thr Phe Arg   1 5 10 <210> 5 <211> 10 <212> PRT <213> Homo sapiens <400> 5 Glu Tyr Thr Asp Ala Ser Phe Thr Asn Arg   1 5 10 <210> 6 <211> 9 <212> PRT <213> Homo sapiens <220> <221> MISC_FEATURE <222> (8) <223> xaa denotes carbaminomethyl-cysteine <400> 6 Tyr Glu Asp Leu Tyr Ser Asn Xaa Lys   1 5 <210> 7 <211> 9 <212> PRT <213> Homo sapiens <400> 7 Tyr Tyr Ile Ala Ala Ser Tyr Val Lys   1 5 <210> 8 <211> 12 <212> PRT <213> Homo sapiens <400> 8 Phe Leu Val Gly Pro Asp Gly Ile Pro Ile Met Arg   1 5 10 <210> 9 <211> 7 <212> PRT <213> Homo sapiens <400> 9 Leu Phe Trp Glu Pro Met Lys   1 5 <210> 10 <211> 11 <212> PRT <213> Homo sapiens <400> 10 Asp Gln Tyr Tyr Asn Ile Asp Val Pro Ser Arg   1 5 10 <210> 11 <211> 12 <212> PRT <213> Homo sapiens <400> 11 Val Asn Ser Gln Ser Leu Ser Pro Tyr Leu Phe Arg   1 5 10

Claims (11)

A method for providing information necessary for the diagnosis of non-small cell lung cancer comprising the steps of:
(a) measuring the expression level of BCHE (butyrylcholinesterase) in a biological sample separated from an object, wherein the expression level of the BCHE is measured by quantifying a peptide comprising the amino acid sequence of the second sequence of the sequence listing ; And
(b) analyzing the expression level of the BCHE, wherein the expression level of the BCHE is down-regulated compared to the control, the non-small cell lung cancer is judged.
2. The method of claim 1, wherein the biological sample of step (a) is a blood, serum, or plasma sample.
The method according to claim 1, comprising a step (a ') of digesting the biological sample separated from the object prior to said step (a).
The method according to claim 1, wherein the quantification of the peptide of step (a) is performed by multiple reaction mornitoring, selected reaction monitoring, or multiple selected reaction monitoring &Lt; / RTI &gt;
3. The method of claim 1, wherein the peptide of step (a) has a transition of 604.313 / 931.472 or 599.309 / 921.464.
The method according to claim 1, wherein the step (b) is determined to be non-small cell lung cancer when the expression level of BCHE is 3.91 占 1.17 占 퐂 / ml.
delete A method for providing information necessary for the diagnosis of non-small cell lung cancer comprising the steps of:
(a) measuring the expression level of BCHE (butyrylcholinesterase) in a biological sample separated from an object; And
(b) analyzing the expression level of the BCHE, wherein the expression level of the BCHE is down-regulated compared to the control, the non-small cell lung cancer is judged.
9. The method according to claim 8, wherein step (a) is carried out by an immunoassay method
9. The method according to claim 8, wherein the determination in step (b) is determined to be non-small cell lung cancer when the expression level of BCHE is 4.04 占 .1 占 퐂 / ml.
A diagnostic kit for non-small cell lung cancer comprising an antibody or an aptamer that specifically binds to a BCHE protein to detect BCHE (butyrylcholinesterase) in a biological sample separated from the object.

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