Use of a combination of plasma proteins in screening for pancreatic cancer

Abstract

The application belongs to the technical field of proteomics and clinical disease screening, and relates to application of a combination of plasma proteins in screening of pancreatic cancer. The application is based on mass spectrometry quantitative proteomics technology, screens and determines a marker combination composed of four plasma proteins of GCLC, ALAD, HAGH and SORD, and comprehensively analyzes relative abundance of the marker combination through a binary Logistic regression model to distinguish pancreatic cancer patients from healthy people. Experimental results show that the protein combination has high sensitivity, specificity and area under curve (AUC) in a screening set and an independent verification set, and has good stability and repeatability. The method has the advantages of non-invasiveness, feasible operation and applicability to population screening by taking plasma as a detection sample, and can provide a new technical means for early screening of pancreatic cancer.

Description

Technical Field

[0001] This invention belongs to the field of clinical proteomics detection technology, specifically involving a biomarker combination composed of four proteins: GCLC, ALAD, HAGH, and SORD, and the application of the biomarker combination in pancreatic cancer screening. Background Technology

[0002] Pancreatic cancer is one of the most malignant solid tumors, with a 5-year survival rate of only 13%. Approximately 80% of cases are diagnosed at a locally advanced or metastatic stage, thus losing the opportunity for radical surgery. Population-wide disease screening can help in the early diagnosis and treatment of pancreatic cancer.

[0003] Current pancreatic cancer screening methods mainly include imaging examinations and plasma biomarkers. Imaging examinations have limited sensitivity and are costly, making them unsuitable for large-scale population screening. Plasma biomarkers, such as CA19-9, suffer from low sensitivity and false negatives. Therefore, at the molecular level, the search for novel plasma biomarkers is of great significance for pancreatic cancer screening. Summary of the Invention

[0004] The purpose of this invention is to provide a method for screening patients with pancreatic cancer.

[0005] The inventors of this invention used mass spectrometry-based proteomics technology to screen plasma samples from pancreatic cancer patients for a combination of protein biomarkers that can be used to screen for pancreatic cancer. The combination of protein biomarkers includes four proteins: GCLC, ALAD, HAGH, and SORD. This led to the technical solution of this invention.

[0006] In a first aspect, the present invention provides a mass spectrometry-based system for screening pancreatic cancer patients, the system comprising a device for detecting GCLC, ALAD, HAGH and SORD proteins; and a data processing device.

[0007] Furthermore, the devices for detecting GCLC, ALAD, HAGH, and SORD proteins include, but are not limited to, signal reading devices such as mass spectrometers, spectrophotometers, and chemiluminescence analyzers, or antibody-based immunohistochemistry and ELISA quantitative devices; the devices can quantify the abundance of the target proteins. Furthermore, the protein detection device includes a mass spectrometer; preferably, the mass spectrometer is configured to include, but is not limited to, the following modes: data independent acquisition (DIA), data-dependent acquisition (DDA), and mass spectrometry-targeted quantification, wherein the above modes can quantify the abundance of the target protein; Furthermore, the data processing device operates a diagnostic criterion for screening pancreatic cancer patients. This criterion calculates the relative levels of GCLC, ALAD, HAGH, and SORD proteins in plasma based on binary logistic regression analysis, resulting in the following formula: P = 1 / (1+e^(-1 / 2)) -(-75.635+2.189×GCLC+0.378×ALAD+0.317×HAGH+0.681×SORD) When P>0.29, the patient is judged to be a pancreatic cancer patient; otherwise, the patient is judged to be a healthy person. Preferably, the relative content is defined as the abundance of GCLC, ALAD, HAGH and SORD proteins in the sample measured by mass spectrometry or immunohistochemistry quantitative techniques in quantitative proteomics analysis.

[0008] A second aspect of the present invention provides a biomarker combination, characterized in that the biomarker combination comprises GCLC, ALAD, HAGH and SORD proteins, and the biomarker combination is used for screening pancreatic cancer patients.

[0009] Thirdly, the present invention provides the use of a substance specifically detecting the combination of biomarkers described in the second aspect in the preparation of an agent for screening patients with pancreatic cancer; characterized in that the substance specifically detected is suitable for mass spectrometry, and the use includes the following steps: S1. Obtain the plasma sample to be tested; S2. Based on mass spectrometry, DIA proteomics method is used to perform qualitative and quantitative detection of proteins in the test sample; S3. Quantitative abundance values ​​of proteins were normalized using quantile and transformed using log2. Missing values ​​were filled with the minimum value. The relative abundances of GCLC, ALAD, HAGH, and SORD proteins were then calculated using the following formula: P = 1 / (1+e^(-1 / 2)) -(-75.635+2.189×GCLC+0.378×ALAD+0.317×HAGH+0.681×SORD) ).

[0010] Fourthly, the present invention provides the use of an apparatus for detecting GCLC, ALAD, HAGH, and SORD proteins in the preparation of a system for screening patients with pancreatic cancer.

[0011] Furthermore, the device for detecting GCLC, ALAD, HAGH, and SORD proteins is capable of qualitatively and quantitatively detecting these proteins in plasma samples from pancreatic cancer patients. Examples include signal reading devices such as mass spectrometers, spectrophotometers, and chemiluminescence analyzers, or antibody quantification devices such as immunohistochemistry and ELISA.

[0012] The beneficial effects of this invention include: 1) Significantly improves the overall accuracy of pancreatic cancer screening: This invention, by jointly detecting the abundance of four proteins—GCLC, ALAD, HAGH, and SORD—in plasma and performing comprehensive discrimination based on a binary logistic regression model, significantly improves the sensitivity and specificity of pancreatic cancer screening compared to single plasma biomarkers. The AUC reached 0.93 in the screening set and remained at 0.96 in the independent validation set, demonstrating high discriminative ability.

[0013] 2) It has good stability and reproducibility, and meets the review requirements of "screening + verification": This invention constructs a verification sample set independently of the screening set, and directly uses the discriminant model parameters established in the screening stage without refitting, and still obtains high sensitivity (100%) and specificity (79.2%), proving that the association between the protein combination and pancreatic cancer has stability and reproducibility, which meets the requirements of full disclosure and verifiability in the field of disease biomarkers.

[0014] 3) Applicable to non-invasive and scalable population screening applications: This invention uses plasma samples as the detection object and can complete the detection by combining mass spectrometry or immunological quantitative technology, avoiding invasive operations. The detection process is highly standardized and suitable for large-scale screening in physical examinations or high-risk groups. It has good clinical application prospects and promotion value.

[0015] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0016] Figure 1 ROC curves were used to screen combined biomarkers of GCLC, ALAD, HAGH, and SORD to distinguish between healthy individuals and pancreatic cancer patients; Figure 2 To independently validate the ROC curves of combined biomarkers of GCLC, ALAD, HAGH, and SORD in distinguishing healthy individuals from pancreatic cancer patients. Detailed Implementation

[0017] The following detailed embodiments further illustrate the concept and technical effects of the present invention to fully understand its purpose, features, and effects. Unless otherwise specified, all methods described are conventional methods. Unless otherwise specified, all materials are available from publicly available commercial sources. The illustrative embodiments and descriptions of the present invention are used to explain the invention and do not constitute an undue limitation thereof. It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0018] Example 1: DIA (Digital Imaging and Absorption) non-standard quantitative technique for detecting plasma proteomics in pancreatic cancer patients and healthy individuals.

[0019] I. Experimental Materials

[0020] Plasma samples from 10 pancreatic cancer patients and 10 healthy individuals were all obtained from Yantai Yuhuangding Hospital.

[0021] II. Experimental Methods

[0022] 1. High-abundance protein removal and peptide digestion: Take a self-made centrifuge column and add Human High-Select™ Top14 high-abundance protein removal resin, High Select HSA / immunoglobulin removal resin, and n-dodecyl-β-D-maltose (DDM) solution sequentially. Centrifuge at 1000 g for 1 min to remove air bubbles. Add plasma sample, incubate vertically at room temperature for 10 min, then centrifuge at 10000 g for 5 min to collect the flow-through. Add 1 mM DDM solution to elute, incubate vertically at room temperature for 5 min, then centrifuge at 10000 g for 5 min. Combine the flow-through and eluent to obtain the protein solution after high-abundance protein removal.

[0023] Take approximately 20 μg of the above protein solution into an EP tube, add 1 μL of 10 mM DTT, and incubate at 60°C for 30 min. After cooling to room temperature, add 1 μL of 20 mM IAA and incubate at room temperature in the dark for 30 min; add 1 μL of 10 mM DTT and incubate at room temperature in the dark for 15 min to terminate the reaction. Add 4 μL of mixed SP3 magnetic beads to the reaction system, and add anhydrous ethanol to a final concentration of 50% (v / v), incubate at 24°C and 1000 rpm for 5 min; place on a magnetic rack and let stand for 1 min, discard the supernatant, and wash the magnetic beads three times with 180 μL of 80% ethanol. Add trypsin solution (enzyme to protein ratio 1:25, prepared with 100 mM ammonium bicarbonate) to the magnetic bead-protein complex. First add 50% of the enzyme amount, incubate at 37°C for 2 h, then add the remaining 50% of the enzyme amount, and continue incubation for 16 h. Place the mixture on a magnetic rack and collect the supernatant, which is the peptide solution.

[0024] 2. Mass Spectrometry Data Acquisition: Samples were analyzed by DIA mode mass spectrometry using an EASY-nLC 1200 nanoliter liquid chromatography system coupled with an Orbitrap Exploris 480 mass spectrometer (Thermo Fisher Scientific). The LC-MS parameters were as follows: mobile phase A was a 0.1% formic acid aqueous solution, mobile phase B was an 80% acetonitrile and 0.1% formic acid aqueous solution, liquid phase gradient was 90 min, and the flow rate was constant at 350 nL / min; mass spectrometry was in DIA scan mode, MS1 full scan resolution was 120,000, and the scan range was 400–1200 m / z; the DIA fragmentation scan was set with 32 consecutive isolation windows of 10 m / z, covering the range of 440–760 m / z; fragment ions were analyzed at 30,000 resolution on the Orbitrap detector using HCD fragmentation with a normalized collision energy of 27%; the ion source spray voltage was 2.3 kV.

[0025] 3. Mass Spectrometry Data Analysis: DIA-NN (v1.9.2) software was used to analyze mass spectrometry data and perform protein identification and quantification. An experimentally specific spectral library was constructed based on the UniProt human reference proteome database. Search parameters were set as follows: Trypsin / P restriction enzyme digestion, a maximum of 2 missed cleavage sites, variable modifications of methionine oxidation and N-terminal acetylation, fixed modification of cysteine ​​carbamylation, peptide length of 7-30 amino acids, precursor charge of 2+–4+, and deep learning spectral prediction enabled. Subsequently, DIA data was searched, cross-sample matching and peptide modification variant identification were enabled, retention time-dependent correction and QuantUMS quantification strategy were employed, and protein identification and quantification results were output. The FDR threshold for both precursor and protein levels was set to 1%.

[0026] The obtained protein quantification results were normalized by quantile and transformed by log2. After filling missing values ​​with minimum values, the relative quantification values ​​of GCLC, ALAD, HAGH and SORD proteins were extracted.

[0027] The relative abundances of GCLC, ALAD, HAGH, and SORD proteins in the plasma of healthy individuals and pancreatic cancer patients are as follows: The mean ± standard deviation (MSD) of the relative abundance of GCLC protein in healthy individuals' plasma was 20.84 ± 0.56, while that in pancreatic cancer patients' plasma was 21.76 ± 0.69. The mean ± standard deviation (MSD) of the relative abundance of ALAD protein in healthy individuals' plasma was 23.02 ± 0.62, while that in pancreatic cancer patients' plasma was 23.89 ± 1.03. The mean ± standard deviation (MSD) of the relative abundance of HAGH protein in healthy individuals' plasma was 20.2 ± 0.71, while that in pancreatic cancer patients' plasma was 21.26 ± 0.74. The mean ± standard deviation of the relative abundance of SORD protein in the plasma of healthy individuals was 17.24 ± 3.1, while that in pancreatic cancer patients was 20.37 ± 0.86. Statistical analysis of the relative abundance of proteins in each group (Mann-Whitney U test) revealed that the relative abundance of GCLC, ALAD, HAGH, and SORD proteins in plasma was significantly upregulated in the pancreatic cancer patient group compared to the healthy group (P < 0.0001). Using the healthy group as the control group and the pancreatic cancer patient group as the disease group, ROC curve analysis of the combined biomarkers of GCLC, ALAD, HAGH, and SORD proteins in plasma was performed. The area under the curve (AUC) for pancreatic cancer patients was 0.93, with a sensitivity of 100% and a specificity of 80%. Figure 1 ).

[0028] Example 2: Independent validation of the screening performance of a combination of plasma GCLC, ALAD, HAGH, and SORD proteins for pancreatic cancer.

[0029] 1. Source of validation set samples

[0030] To further verify the stability and reproducibility of the plasma protein combinations obtained in Example 1 in pancreatic cancer screening, an independent validation sample set was constructed separately.

[0031] A total of 44 plasma samples were collected for verification, all from Yantai Yuhuangding Hospital. These samples differed from the batch used in Example 1 and included the following: Plasma samples from 20 pancreatic cancer patients were collected. Plasma samples were collected from 24 healthy controls.

[0032] 2. Experimental Methods

[0033] The processing procedure, mass spectrometry detection conditions, and data analysis methods for the validated plasma samples are completely consistent with those in Example 1, and briefly include: The steps for removing high-abundance proteins from plasma, protein reductive alkylation, and trypsin hydrolysis are the same as in Example 1; The EASY-nLC 1200 liquid chromatography system was coupled with an Orbitrap Exploris 480 mass spectrometer, and data acquisition was performed using DIA mode. Protein identification and quantification were performed using DIA-NN software. The protein quantification data were quantile normalized and log2 transformed, and missing values ​​were filled using the minimum value. Relative quantification values ​​of GCLC, ALAD, HAGH, and SORD proteins were extracted.

[0034] 3. Verify protein abundance levels

[0035] In the validation set, the relative abundance of GCLC, ALAD, HAGH, and SORD proteins in the plasma of healthy individuals and pancreatic cancer patients are as follows (mean ± standard deviation):

[0036] Mann-Whitney U test analysis showed that the relative abundance of the above four proteins in the plasma of pancreatic cancer patients was significantly higher than that in the healthy control group (P < 0.0001).

[0037] 4. Validation set screening model and ROC analysis

[0038] In the validation set, the binary logistic regression model established in Example 1 was directly used for screening and judgment, without refitting the model parameters. The judgment formula is as follows: P = 1 / (1+e) -(-75.635+2.189×GCLC+0.378×ALAD+0.317×HAGH+0.681×SORD) ) When P > 0.29, the patient is diagnosed with pancreatic cancer; otherwise, the patient is diagnosed as healthy.

[0039] Using pancreatic cancer patients as positive samples and healthy individuals as negative samples, ROC curve analysis was performed on the prediction results. The results showed: The area under the ROC curve (AUC) is 0.96. At the above-mentioned threshold: sensitivity is 100%, specificity is 79.2% (e.g., Figure 2 (As shown).

[0040] 5. Results Analysis

[0041] The validation results showed that the screening model based on the abundance of plasma GCLC, ALAD, HAGH and SORD proteins maintained high screening efficacy in the independent validation sample set, indicating that the protein combination has a stable and reproducible association with pancreatic cancer.

[0042] Example 3: Consistency analysis of screening performance of plasma protein combinations in different sample sets

[0043] 1. Comparison of results between the filter set and the validation set

[0044] The screening performance of Example 1 (screening set) and Example 2 (validation set) was compared and analyzed, and the results are as follows:

[0045] It can be seen that the screening performance remains unchanged compared to the filter set.

[0046] The above results indicate that the combination of abundance of GCLC, ALAD, HAGH, and SORD proteins in plasma can be used to screen for pancreatic cancer.

[0047] The above embodiments provide a detailed description of the present invention and are not intended to limit the invention. Any modifications or alterations to the present invention that do not depart from its principles should be included within the scope of protection of the present invention.

Claims

1. A combination of markers, characterized in that, The biomarker combination includes GCLC, ALAD, HAGH, and SORD proteins, and is used to screen patients with pancreatic cancer.

2. The marker combination according to claim 1, characterized in that, The biomarker combination is used to prepare a substance for detecting the expression levels of GCLC, ALAD, HAGH, and SORD proteins in plasma samples to distinguish between pancreatic cancer patients and healthy individuals.

3. A system for screening pancreatic cancer, characterized in that, The system includes a device for detecting the expression levels of GCLC, ALAD, HAGH, and SORD proteins, as well as a data processing device; the device for detecting protein expression levels is configured to quantify the abundance of the proteins.

4. The system according to claim 3, characterized in that, The apparatus for detecting GCLC, ALAD, HAGH, and SORD proteins is selected from mass spectrometry, spectrophotometer, chemiluminescence analyzer, immunohistochemistry apparatus, or ELISA quantitative apparatus.

5. The system according to claim 4, characterized in that, The device for detecting protein expression levels is a mass spectrometer, which is configured to use a data-independent acquisition (DIA) mode, a data-dependent acquisition (DDA) mode, or a targeted quantification mode to quantify the abundance of the target protein.

6. The system according to claim 3, characterized in that, The data processing device operates a diagnostic criterion for screening pancreatic cancer patients. This criterion is based on binary logistic regression analysis to calculate the relative levels of GCLC, ALAD, HAGH, and SORD proteins in plasma. The formula is as follows: P= 1 / (1+e -(-75.635+2.189×GCLC+0.378×ALAD+0.317×HAGH+0.681×SORD) ), When P > 0.29, the patient is diagnosed with pancreatic cancer; otherwise, the patient is considered healthy.

7. The system according to claim 6, characterized in that, The relative abundance refers to the abundance values ​​of GCLC, ALAD, HAGH, and SORD proteins in the sample, measured using quantitative proteomics analysis based on mass spectrometry or immunohistochemistry, after quantile normalization and log2 transformation.

8. Use of a substance that specifically detects the combination of biomarkers of claim 1 in the preparation of an agent for screening patients with pancreatic cancer, characterized in that, The substance is suitable for mass spectrometry detection, including acquiring the plasma sample to be tested, performing quantitative protein detection based on the DIA proteomics method, and calculating the relative content of GCLC, ALAD, HAGH and SORD proteins.

9. The use according to claim 8, characterized in that, The calculation uses a judgment formula: P= 1 / (1+e -(-75.635+2.189×GCLC+0.378×ALAD+0.317×HAGH+0.681×SORD) ), When P > 0.29, the patient is diagnosed with pancreatic cancer.

10. Use of an apparatus for detecting GCLC, ALAD, HAGH, and SORD proteins in the preparation of a system for screening patients with pancreatic cancer, characterized in that, The device can qualitatively and quantitatively detect the protein in plasma samples, and uses a judgment formula in conjunction with a data processing device: P = 1 / (1+e) -(-75.635+2.189×GCLC+0.378×ALAD+0.317×HAGH+0.681×SORD) Screening will be conducted. A p-value > 0.29 indicates a pancreatic cancer patient.

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