KR20240108836A - Biomarker for lung cancer diagnosis and method for diagnosing lung cancer using the same - Google Patents

Abstract

LBP, SERPINA 10, SERPINA3, SERPINA1, LRG1, LGALS3BP, C9, C4B, C4A, CFB, CP, C6, CFH, C4BPA, CPB2, C8G, C1R, C1RL, C3, C1S, C1QA, CFI, SAA4, APCS, A1BG A composition and diagnostic method for diagnosing lung cancer using the expression levels of genes selected from the group consisting of ITIH3, PPBP, ORM1, and ORM2 are provided.

Description

Biomarker for lung cancer diagnosis and lung cancer diagnosis method using the same {Biomarker for lung cancer diagnosis and method for diagnosing lung cancer using the same}

The present invention relates to protein markers for lung cancer diagnosis and a lung cancer diagnosis method using the same.

The 5-year survival rate of lung cancer is the second lowest after liver cancer, and it is a cancer with an extremely poor prognosis. This is because lung cancer is often discovered late and the effectiveness of traditional chemotherapy is limited. However, if lung cancer is detected early, the prognosis can be positive. For example, in stage IA patients, where a tumor (mass) less than 3 cm in diameter exists within the lobar bronchus, the 5-year survival rate after surgery is around 70%.

Meanwhile, blood-based protein biomarkers for lung cancer were difficult to detect due to the presence of major proteins (high-abundant proteins, such as albumin, IgG, transferin, etc.) in the sample. However, with the development of mass spectrometry technology, plasma proteins can be analyzed. The scope has been expanded.

Previously known blood-based biomarkers of lung cancer include VEGF-C, LDHB (Lactate Dehydrogenase B), Carcinoembryonic antigen (CEA), retinol binding protein, 1-antitrypsin, and squamous cell carcinoma antigen. cell carcinoma antigen (SCCA), etc., and has a sensitivity of 78-81%. However, because early diagnosis of lung cancer is still difficult using only known markers, there is a need to discover new blood-based protein biomarkers.

Republic of Korea Public Gazette No. 10-1479548 (2014.12.30)

According to one embodiment, a biomarker for early diagnosis of lung cancer and a lung cancer diagnosis method using the same are provided.

One modality is to detect LBP, SERPINA 10, SERPINA3, SERPINA1, LRG1, LGALS3BP, C9, C4B, C4A, CFB, CP, C6, CFH, C4BPA, CPB2, C8G, C1R, C1RL, C3, C1S, C1QA, CFI from biological samples. , SAA4, APCS, A1BG, ITIH3, PPBP, ORM1, and ORM2. It provides a composition for diagnosing lung cancer, including an agent for measuring the expression level of mRNA or protein of one or more biomarker genes selected from the group consisting of.

According to one embodiment, the biomarker gene has a sensitivity of 0.8 or more and may include, for example, SERPINA3, C4A, CFH, C1RL, C3, C1S, CFI, ITIH3, and ORM1.

The biological sample may be selected from the group consisting of blood, plasma, and serum.

The lung cancer may be non-small cell lung cancer (NSCLC).

The lung cancer diagnosis may be for Koreans.

Another aspect includes preparing a biological sample obtained from an individual to be diagnosed; A step of measuring the expression level of mRNA or protein of a biomarker gene from the sample, wherein the biomarker gene is LBP, SERPINA 10, SERPINA3, SERPINA1, LRG1, LGALS3BP, C9, C4B, C4A, CFB, CP, C6. , CFH, C4BPA, CPB2, C8G, C1R, C1RL, C3, C1S, C1QA, CFI, SAA4, APCS, A1BG, ITIH3, PPBP, ORM1, and ORM2, which provides information necessary for diagnosing lung cancer. Provides a method.

Information and sequences about the genes and proteins expressed therefrom are available from Uniprot (https://www.uniprot.org/), Genecards (https://www.genecards.org/), and Blast (https://blast. They can be easily searched on search sites such as ncbi.nlm.nih.gov/Blast.cgi), and for example, their protein sequences may be SEQ ID NOs: 1 to 29.

The sample may be selected from the group consisting of blood, plasma, and serum.

The sample may be prepared from 1 to 10 μl, 2 to 6 μl, or 4 μl of the individual's plasma.

The method may further include determining that the cancer is lung cancer if the expression level of the biomarker is higher than that of normal people.

The expression level may be determined based on label-free relative quantitative values.

According to one embodiment, the label-free relative quantitative value can be obtained by peptideting the protein of the plasma sample, performing LC-MS/MS, and quantitative analysis using Proteome Discover software.

The Proteome Discover software can use the Uniprot human database, and the database search parameters can be set to fixedly modified cysteine +57Da, variable modified methionine +16Da, trypsin digestion 2, and trypsin-uncleaved 2.

The expression level may be determined by applying the label-free relative quantitative value to the Mixed Effects Model.

The applied mixed effects model uses the fixed effect as sample status (lung cancer or normal), the random effect as technical replicates, and the covariates as batches (batch 1 and batch 2). ), and the response variable may be a protein-free quantitative value.

Information about samples, lung cancer, patient groups, etc. can be understood by referring to the above-mentioned information.

Another aspect includes treating a lung cancer patient sample with a lung cancer treatment candidate; And measuring the expression level of biomarkers in the sample before and after processing the candidate material, wherein the biomarkers are LBP, SERPINA 10, SERPINA3, SERPINA1, LRG1, LGALS3BP, C9, C4B, C4A, CFB, CP. , C6, CFH, C4BPA, CPB2, C8G, C1R, C1RL, C3, C1S, C1QA, CFI, SAA4, APCS, A1BG, ITIH3, PPBP, ORM1, and ORM2, providing a screening method for a treatment for lung cancer that is at least one selected from the group consisting of do.

Information about samples, lung cancer, patient groups, etc. can be understood by referring to the above-mentioned information.

The marker according to one embodiment shows a difference in expression level in plasma samples of normal people and lung cancer patients, so it can be used for early diagnosis of lung cancer.

Figure 1 shows the protein abundance and degree of crossover in the samples. The experiment was repeated three times with plasma samples from 10 normal people (controls) and 10 lung cancer patients.
Figure 2 shows the results of correlation analysis on 191 proteins with no missing values in the LC-MS/MS results. We confirmed the difference between technical replicate and biological replicate for 191 proteins. Overall, the expression correlation between technical replicates was found to be high.
Figure 3 shows heatmap results for 83 proteins according to one example. 83 DEPs (differentially expressed proteins) were sorted according to fold change. (BH adjusted p-value < 0.05) The modeling method used the SVM method to analyze lung cancer plasma samples compared to normal plasma through 3 repeated experiments, and leave-one-out cross validation (LOOCV) was used to prevent overfitting problems. used. The results were compared and analyzed using AUC, sensitivity, specificity, and balanced accuracy.
Figure 4 shows the 29 proteins that were finally selected through secondary selection among the 83 proteins that were initially selected by applying the mixed effect model to the label-free relative quantification values. The selection conditions in the mixed effects model are as follows. Response: protein expression; Fixed effect: case or control; Random effect: technical replicates; No interaction effect
Figures 5 to 8 show ROC curves of selected proteins.

Hereinafter, one or more embodiments will be described in more detail through examples. However, these examples are intended to illustrate one or more embodiments and the scope of the present invention is not limited to these examples.

Example 1: Sample and reagent preparation

1-1. Plasma sample preparation

The plasma samples were from Samsung Medical Center/Health Checkup Center. The normal sample (n=10) consisted of 9 people in their 40s and 60s and 1 person in their 20s. The lung cancer samples (n=10) were 9 in their 40s to 70s and 1 in their 30s, and the stage of the lesion was 5 in stage 1, 3 in stage 2, and 2 in stage 3. (See Table 1)

NO Type Sex Age Stage NO Type Sex Age Stage One Normal Health M 56 N One Lung Cancer M 71 IB 2 M 52 2 M 39 IIA 3 M 29 3 M 70 IB 4 M 53 4 M 68 IIB 5 M 55 5 M 70 IIIA 6 M 41 6 M 73 IB 7 M 41 7 M 60 IIA 8 M 63 8 F 50 IIIA 9 M 62 9 F 67 IA 10 M 67 10 M 46 IB

All lung cancer patients are non-small cell lung cancer patients. Stages were classified according to the TNM classification, and were distinguished according to primary tumor (T), lymph node metastasis (N), and distant metastasis (M). (See Table 2) For example, if the tumor exists only in the bronchial mucosa and is less than 3cm in diameter (T1) and there is no lymph node or distant metastasis, it is IA. If the tumor exceeds 3cm in diameter or invades the pleura, it is T2 and is classified as IB. T3 means that the tumor has invaded the parietal pleura, diaphragm, and heart.

Stage TNM Subset 0 Carcinoma in situ IA T1N0M0 IB T2N0M0 IIA T1N1M0 IIB T2N1M0T3N0M0 IIIA T3N1M0T1N2M0
T2N2M0
T3N2M0 IIIB T4N0M0T4N1M0
T4N2M0
T1N3M0
T3N3M0
T4N3M0 IV Any T Any N M1

1-2. Reagents and Materials

The reagents and materials used to discover protein diagnostic markers from the plasma of lung cancer patients are as follows.

(1) Pierce™ Rapid Gold BCA Protein Assay Kit (Thermo Fisher Scientific, USA, #A53225)

(2) EasyPep 96 MS Sample Prep Kit (Thermo Fisher Scientific, USA, #A45733)

(3) Trypsin/Lys-C Protease Mix (Thermo Fisher Scientific, USA, #A40009)

(4) 0.1% Formic Acid (v/v) in Water, LC-MS Grade (Thermo Fisher Scientific, USA, #85170)

(5) 0.1% Formic Acid (v/v) in Acetonitrile, LC-MS Grade (Thermo Fisher Scientific, USA, #85174)

(6) Pierce™ FlexMix™ Calibration Solution (Thermo Fisher Scientific, USA, #A39239)

(7) Acclaim™ PepMap™ 100 C18 LC Column, 5 ㎛, 100 ㎛ x 20 mm (Thermo Fisher Scientific, USA, #164564)

(8) EASY-Spray™ C18 Reversed Phase HPLC Column, 2 ㎛, 50 ㎛ x 150 mm (Thermo Fisher Scientific, USA, #ES801A)

All reagents were used at sequencing grade or HPLC grade or higher.

Example 2: Plasma protein acquisition

EasyPep 96 MS Sample Prep Kit was used for sample pretreatment. 4 μl each of 10 plasma samples from normal people and 10 plasma samples from lung cancer patients were taken and diluted 100 times with the lysis buffer included in the kit to make a total of 400 μl of plasma dilution. The amount of protein in diluted plasma was quantified using the BCA method, and each sample was prepared at a concentration of 30 μg/100 μl. To each sample, 50 ㎕ of reducing solution was added and mixed, 50 ㎕ of alkylation solution was added and mixed, light was blocked, and the reaction was shaken at 95°C at 700 rpm for 10 minutes to break the disulfide bond of the peptide and alkylate it. . 1 ㎍ of Trypsin/Lys-C Protease Mix, an enzyme for sequencing, was added to each sample and reacted at 37°C at 700 rpm for 16 hours to cleave the protein. Afterwards, the reaction was stopped by mixing 50 ㎕ of stopping solution. The peptides in the cleaved sample were purified using the C18 column for peptide purification included in the kit. The purified peptide solution was dried with Speedvac and then dissolved in 200 μl of water containing 0.1% (v/v) formic acid for LC-MS analysis.

Example 3: Plasma protein analysis

Each peptide sample was subjected to LC-MS/MS analysis using a mass spectrometry system consisting of an EASY-nLC™ 1200 and an Orbitrap Eclipse™ Tribrid™ mass spectrometer (Thermo Scientific). All samples were injected at 10 μl of 200 μl each and analyzed three times. To separate the peptides, reversed-phase liquid chromatography was performed with an EASY-nLC™ 1200 system (Thermo Scientific). Peptides were separated using a C18 trap column with a diameter of 100 μm, a length of 2 cm, a particle size of 5 μm, and a pore size of 100°C, and a C18 analytical column with a diameter of 50 μm, a length of 15 cm, a particle size of 2 μm, and a pore size of 100°C. . The mobile phase was water containing 0.1% (v/v) formic acid and acetonitrile solution containing 0.1% (v/v) formic acid, and the flow rate was 300 nL/min for 120 minutes with a concentration gradient of 5%-45%. It was eluted at a rate of and injected into an Orbitrap Eclipse™ Tribrid™ mass spectrometer (Thermo Scientific). The injected peptide sample was ionized by electrospray ionization (ESI) in positive ion mode and fragmented by higher energy collisional dissociation (HCD). The overall mass scan range was 400 to 1,600 m/z.

Example 4: Identification and label-free quantification of plasma proteins

Proteome Discoverer 2.4 (Thermo Scientific) software was used to analyze the LC-MS/MS results. All spectral data were searched with the Sequest engine using the Uniprot human database. Peptides and proteins were identified through database search, and label-free quantification analysis was performed between normal and patient groups (Figures 1 and 2). The database search parameters were fixed modification cysteine (+57 Da: carbamidomethylation), dynamic modification methionine (+16 Da: oxidation), and full trypsin digestion (full trypsin digestion) and trypsin uncleavage ( missed cleavage) was set to 2. The hypothesis test for label-free relative quantitative analysis was conducted using the ANOVA test.

Example 5: Selection of lung cancer-related protein markers according to mixed effects model

A mixed effect model was applied based on label-free relative quantitative values. The fixed effect used sample status (cancer or normal), the random effect used technical replicates, and the covariates used batches (batch 1 and batch 2). was applied, and the protein quantitative value was used as the response variable. Using the p-value of the mixed effects model, the effect of multiple testing was corrected using the Benjamini-Hochberge correction, and 83 proteins were selected based on q-value < 0.05 (Figures 3 and 4).

Example 6: Final screening of protein markers for early diagnosis of lung cancer

Among 83 proteins, protein markers for early diagnosis of lung cancer were selected according to the following criteria.

(1) Excluding (cut-off) cases where the protein expression level in the plasma of lung cancer patients is less than 120 compared to that of normal people (controls)

(2) The functions of the selected proteins were reviewed in Protein atlas and GeneCards, and proteins inappropriate as markers were excluded. (excluding immunoglobulin, for example)

(3) Classification by cancer type at Cbioportal Mutation (especially amplification) in lung cancer

(4) Review (there are relatively few lung cancer cases, so the actual number of cases is small compared to the ratio on the graph)

(5) Review of correlation in lung cancer based on published papers (Reference indicated in the text)

(6) Proteins commonly found in serum samples of other solid tumors were excluded as much as possible because they were judged to have little disease specificity. However, even if it had already been reported as a lung cancer marker, it was not excluded.

(7) Informatics was analyzed based on indicators related to reliability (AUC, SN, SP, AC, BA).

(8) The selected proteins were mainly selected for expression locations in the plasma membrane, cytosol, and secreted proteins.

As a result of screening, among the plasma proteins of patients with early lung cancer, LBP, SERPINA10, SERPINA3, SERPINA1, LRG1, LGALS3BP, C9, C4B, C4A, CFB, CP, C6, CFH, C4BPA, CPB2, C8G, C1R, C1RL, C3, C1S, C1QA, CFI, SAA4, APCS, A1BG, ITIH3, PPBP, ORM1 and ORM2 were found to be significantly increased.

The AUC values and ROC curves of the 29 proteins are shown in Table 2 and Figures 4 to 7. ROC, AUC, Sensitivity, and Specificity used in the table represent the values in the test set using the leave-one-out cross validation method.

marker AUC Sensitivity Specificity One LBP 0.72814 0.7 0.63333 2 SERPINA10 0.72653 0.73333 0.83333 3 SERPINA3 0.72653 0.8 0.76667 4 SERPINA1 0.64126 0.6 0.73333 5 LRG1 0.62085 0.63333 0.6 6 LGALS3BP 0.55368 0.26667 0.83333 7 C9 0.59273 0.6 0.56667 8 C4B 0.55941 0.36667 0.76667 9 C4A 0.62887 0.9 0.63333 10 CFB 0.85181 0.7 0.8 11 CP 0.86997 0.66667 0.9 12 C6 0.703 0.63333 0.76667 13 CFH 0.62353 0.86667 0.6 14 C4BPA 0.61491 0.23333 One 15 CPB2 0.74586 0.73333 0.83333 16 C8G 0.79256 0.53333 0.93333 17 C1R 0.73109 0.76667 0.7 18 C1RL 0.67805 0.8 0.7 19 C3 0.8318 0.9 0.73333 20 C1S 0.51384 0.86667 0.46667 21 C1QA 0.78311 0.7 0.63333 22 CFI 0.59796 0.83333 0.56667 23 SAA4 0.61533 0.66667 0.8 24 APCS 0.59668 0.33333 0.83333 25 A1BG 0.75382 One 0.83333 26 ITIH3 0.60679 0.93333 0.4 27 PPBP 0.67191 0.7 0.7 28 ORM1 0.75414 0.8 0.8 29 ORM2 0.77949 0.46667 0.93333

Sequence list electronic file attached

Claims (6)

LBP, SERPINA 10, SERPINA3, SERPINA1, LRG1, LGALS3BP, C9, C4B, C4A, CFB, CP, C6, CFH, C4BPA, CPB2, C8G, C1R, C1RL, C3, C1S, C1QA, CFI, SAA4, Comprising an agent for measuring the expression level of mRNA or protein of one or more genes selected from the group consisting of APCS, A1BG, ITIH3, PPBP, ORM1, and ORM2,
Composition for diagnosing lung cancer. According to paragraph 1,
The biological sample is selected from the group consisting of blood, plasma, and serum,
Composition for diagnosing lung cancer. Preparing a biological sample obtained from an individual to be diagnosed;
It includes measuring the expression level of mRNA or protein of the biomarker from the sample,
The biomarkers are LBP, SERPINA 10, SERPINA3, SERPINA1, LRG1, LGALS3BP, C9, C4B, C4A, CFB, CP, C6, CFH, C4BPA, CPB2, C8G, C1R, C1RL, C3, C1S, C1QA, CFI, SAA4 , one or more selected from the group consisting of APCS, A1BG, ITIH3, PPBP, ORM1, and ORM2,
How to provide the information needed to diagnose lung cancer. According to paragraph 3,
The sample is selected from the group consisting of blood, plasma, and serum,
How to provide the information needed to diagnose lung cancer. According to paragraph 3,
Further comprising determining that it is lung cancer if the expression level of the biomarker is higher than that of normal people,
How to provide the information needed to diagnose lung cancer. Processing a lung cancer treatment candidate material in a lung cancer patient sample; and
Comprising the step of measuring the expression level of the biomarker in the sample before and after processing the candidate substance,
The biomarkers are LBP, SERPINA 10, SERPINA3, SERPINA1, LRG1, LGALS3BP, C9, C4B, C4A, CFB, CP, C6, CFH, C4BPA, CPB2, C8G, C1R, C1RL, C3, C1S, C1QA, CFI, SAA4 , one or more selected from the group consisting of APCS, A1BG, ITIH3, PPBP, ORM1, and ORM2,
Lung cancer treatment screening method.