CN110554196A - Pancreatic cancer prognosis marker and application thereof - Google Patents

Abstract

The invention relates to pancreatic cancer prognostic markers and application thereof. The pancreatic cancer prognostic markers of the present invention include any one or any plurality of proteins selected from FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB. The invention also relates to kits for detecting the expression level of any one or any plurality of these proteins.

Description

Pancreatic cancer prognosis marker and application thereof

Technical Field

The invention relates to pancreatic cancer prognosis, in particular to a pancreatic cancer prognosis marker and application thereof.

background

Pancreatic cancer is the twelfth most frequently occurring cancer and the seventh most frequently occurring cancer in the world at present, the prognosis of pancreatic cancer is very poor, and the number of the occurring people and the number of the dead people are close to 1:1 each year. The 2012-year statistics of the world health organization show that the pancreatic cancer is the twelfth cancer with the twelfth incidence and the seventh cancer with the seventh mortality in the world at present, 33 ten thousand pancreatic cancer patients are newly added in the world every year, 33 ten thousand patients die due to the pancreatic cancer every year, and the ratio of the incidence number to the death number of the pancreatic cancer is close to 1: 1. Pancreatic cancer includes endocrine pancreatic cancer and exocrine pancreatic cancer, and most of pancreatic cancer patients belong to exocrine pancreatic cancer, wherein pancreatic ductal adenocarcinoma patients account for about 90% of pancreatic cancer patients. Pancreatic cancer progresses very fast, the prognosis of patients is very poor, the average survival time of pancreatic cancer patients is only 6-9 months, the annual survival rate is 28%, and the five-year survival rate is 7%; the patients with 20 percent of pancreatic cancer can be resected by operation, but most of the patients can have cancer recurrence and metastasis, the median survival time of the patients is 12-19 months, the five-year survival rate is 20 percent, and the pancreatic cancer is called 'king of cancer'.

Although the five-year survival rate of the American pancreatic cancer patients between 1975 and 2017 is increased from 3.0% to 8.5%, the 5-year survival rate of the pancreatic cancer patients is still less than 10% at present, which is not optimistic. Early diagnosis is difficult, prognosis is poor, occurrence and development are rapid, most of patients diagnosed with pancreatic cancer reach late stage, surgical resection is the only effective means for completely curing pancreatic cancer at present, but the recurrence rate of pancreatic cancer of patients who are surgically resected is very high. Early discovery and early treatment are very critical for curing pancreatic cancer, and the tracking of patients after surgical resection is very important for timely intervention after surgery to improve the survival rate of patients.

Disclosure of Invention

The invention provides application of any one or more of proteins selected from FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB as a detection object in preparing a detection reagent or a detection kit for predicting disease development or disease malignancy of a pancreatic cancer patient.

In one or more embodiments, the protein comprises:

(1) Any one or more of proteins selected from FMO1, ADH6, PLIN4 and GSTZ 1; and optionally

(2) one or more selected from LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB.

In one or more embodiments, the protein comprises:

(1) FMO1, ADH6, PLIN4, and GSTZ 1; and optionally

(2) One or more selected from LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB.

The invention also provides application of a detection reagent of any one or more proteins selected from FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB in preparing a detection kit for predicting disease development or disease malignancy of a pancreatic cancer patient.

In one or more embodiments, the protein comprises:

(1) Any one or more of proteins selected from FMO1, ADH6, PLIN4 and GSTZ 1; and optionally

(2) One or more selected from LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB.

In one or more embodiments, the protein comprises:

(1) FMO1, ADH6, PLIN4, and GSTZ 1; and optionally

(2) One or more selected from LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB.

In one or more embodiments, the detection reagent is an antibody or antigen-binding fragment thereof.

The present invention also provides a kit containing a detection reagent for a protein selected from any one or any plurality of FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB.

In one or more embodiments, the kit contains:

(1) a detection reagent for any one or more proteins selected from FMO1, ADH6, PLIN4 and GSTZ1, preferably FMO1, ADH6, PLIN4 and GSTZ 1; and optionally

(2) A detection reagent for any one or more proteins selected from LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB.

In one or more embodiments, the kit contains: an agent that specifically binds to the protein, including an antibody or antigen-binding fragment thereof; and optionally reagents for preparing a biopsy sample, optionally reagents for tissue homogenization, optionally reagents for preparing a peptide sample, and optionally reagents for desalting the peptide.

Drawings

FIG. 1: ROC curves for 14 different proteins with associated prognosis and 4 proteins selected.

FIG. 2: on-line survival analysis of the selected prognostic-related 14 differentially expressed proteins was performed with surfexpress.

FIG. 3: on-line survival analysis of 4 differential proteins with selected prognoses was performed with surfexpress.

Detailed Description

It is understood that within the scope of the present invention, the above-mentioned technical features of the present invention and the technical features specifically described below (e.g., examples) may be combined with each other to constitute a preferred embodiment.

Differentially expressed proteins in cancer and paracancerous tissues of 32 pancreatic cancer patients were studied using a TMT marker-based quantitative proteomics strategy; meanwhile, patients were classified into a survival group and a death group according to their survival conditions for 9-15 months, and proteins differentially expressed in cancer tissues of the survival and death patients were studied. Finally, 540 differentially expressed proteins were found in cancer and paracancerous tissues, with 540 proteins being significantly enriched in the ECM-receptor interaction pathway. In cancer tissues in the survival and death groups, we found that PLIN4, ADH6, FMO1 and GSTZ1 could be used as biomarkers for pancreatic cancer prognosis.

Accordingly, provided herein is a method of predicting the progression or malignancy of a pancreatic cancer patient, the method comprising the step of detecting the expression level of one or any plurality (e.g., at least 2, at least 3, at least 4, at least 5) of biomarkers (proteins) selected from the group consisting of: FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2, and HBB.

In certain embodiments, the method of predicting disease progression or disease malignancy in a pancreatic cancer patient comprises detecting the expression level of any one or more, preferably all 4, of FMO1, ADH6, PLIN4, and GSTZ1 in pancreatic cancer tissue of a pancreatic cancer patient. In certain embodiments, in addition to detecting the expression level of any one or any more, preferably all 4, of FMO1, ADH6, PLIN4, and GSTZ1 in pancreatic cancer tissue of a pancreatic cancer patient, the method further comprises detecting the expression level of one or any more of the proteins selected from the group consisting of: LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2, and HBB.

The invention also includes the use of one or any of a plurality (e.g., at least 2, at least 3, at least 4, at least 5) of proteins selected from the group consisting of: FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2, and HBB. For example, in certain embodiments, the invention includes proteins of any one or any plurality of FMO1, ADH6, PLIN4, GSTZ1, lip, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2, and HBB for predicting the progression or malignancy of a pancreatic cancer patient. In certain embodiments, the invention includes any one or a combination of any one or any more, preferably all 4, of LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2, and HBB for predicting the progression of, or malignancy of, a pancreatic cancer patient. For example, the invention relates to a combination of FMO1, ADH6, PLIN4 and GSTZ1 for predicting the progression or malignancy of a disease in a pancreatic cancer patient.

In certain embodiments, the use is in the preparation of a detection reagent or a detection kit. For example, the present invention includes the use of any one or any plurality of proteins selected from FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2, and HBB as a subject for detection in the preparation of a detection reagent or a detection kit for diagnosing pancreatic cancer. In certain embodiments, the present invention relates to the use of any one or any plurality of FMO1, ADH6, PLIN4, and GSTZ1 as a test object in the preparation of a test reagent or a test kit for the diagnosis of pancreatic cancer. The invention relates to application of FMO1, ADH6, PLIN4 and GSTZ1 as detection objects in preparation of a detection reagent or a detection kit for pancreatic cancer diagnosis. In certain embodiments, the present invention relates to the use of any one or any plurality of proteins selected from FMO1, ADH6, PLIN4 and GSTZ1, and any one or any plurality of proteins selected from LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB as a test subject in the preparation of a test reagent or test kit for the diagnosis of pancreatic cancer. In certain embodiments, the present invention relates to the use of FMO1, ADH6, PLIN4 and GSTZ1 and any one or any more of proteins selected from the group consisting of lip, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB as a test subject in the preparation of a test reagent or a test kit for the diagnosis of pancreatic cancer.

The invention also provides application of a detection reagent of any one or more proteins selected from FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB in preparing a detection kit for predicting disease development or disease malignancy of a pancreatic cancer patient. In certain embodiments, the detection reagent is a detection reagent of any one or more of FMO1, ADH6, PLIN4, and GSTZ 1. In certain embodiments, the detection reagent is a detection reagent for FMO1, ADH6, PLIN4, and GSTZ 1. In certain embodiments, the detection reagent is a detection reagent selected from any one or any more of FMO1, ADH6, PLIN4, and GSTZ1 and a detection reagent selected from any one or any more of lip, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2, and HBB. In certain embodiments, the detection reagent is FMO1, ADH6, PLIN4, and GSTZ1 and a detection reagent for any one or any more proteins selected from the group consisting of lip, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2, and HBB.

The present invention also provides a detection kit containing a detection reagent for a protein selected from any one or any plurality of FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB. In certain embodiments, the kit contains a detection reagent for any one or more of FMO1, ADH6, PLIN4, and GSTZ1, or a detection reagent for FMO1, ADH6, PLIN4, and GSTZ 1. In certain embodiments, the kit comprises: a detection reagent for any one or more of FMO1, ADH6, PLIN4 and GSTZ1, and a detection reagent for any one or more of proteins selected from LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB. In certain embodiments, the kit contains detection reagents for FMO1, ADH6, PLIN4, and GSTZ1, and detection reagents for any one or more proteins selected from the group consisting of lip, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2, and HBB.

Herein, FMO1, ADH6, PLIN4, GSTZ1, as well as LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2, and HBB have art-recognized meanings. For example, FMO1 is flavin-containing monooxygenase 1; ADH6 is alcohol dehydrogenase 6; PLIN 4is perilipin 4; GSTZ1 is maleylacetoacetate isomerase. The amino acid sequences and gene sequences of all of these proteins (particularly human amino acid sequences and gene sequences) can be obtained from various databases such as GenBank or GenBankTo obtain the compound. For example, the GC ID of FMO1 is GC01P 171217; the GC ID of ADH6 is GC04M 099202; the GC ID of PLIN4 was GC19M 004503; the GC ID of GSTZ1 is GC14P 077320. The amino acid sequences of other proteins may also be derived fromto obtain the compound.

It is understood that, in different individuals, there may be mutations in FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2, and HBB, but the use of such mutant protein detection and results is within the scope of the present invention as long as the mutated protein remains recognized in the art as such.

In methods or applications for predicting the progression or malignancy of a pancreatic cancer patient, the expression level of a protein in the pancreatic cancer tissue of the subject can be compared to the average (statistically significant) expression level of the protein in the pancreatic cancer patient, or to the average (statistically significant) expression level of the same protein in the pre-operative pancreatic cancer tissue of a pancreatic cancer patient with a longer post-operative survival time. In certain embodiments, the comparison is made to the average expression level of protein in pancreatic cancer tissue in patients of the same pathological stage. For example, the expression levels of proteins of a plurality of pancreatic cancer patients belonging to the same pathological stage, which satisfy statistical requirements, can be obtained, and the average expression levels thereof can be obtained as a basis for comparison. In particular, in the case of individuals whose pancreatic cancer belongs to a pathological stage, when the progression of the disease or the degree of malignancy of the disease is to be predicted, the detected expression level of the corresponding protein can be compared with the average expression level of the same protein in the patient in the pathological stage. In contrast, up-regulated expression levels of ADH6 and HNRNPH1 (e.g., protein expression levels in the pancreatic cancer tissue of the subject that are 1.5-fold or more greater than the average expression level), and down-regulated expression levels of FMO1, ADH6, PLIN4, GSTZ1, lip, COBLL1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2, and HBB (e.g., average expression levels that are 1.5-fold or more greater than the protein expression levels in the pancreatic cancer tissue of the subject) indicate poor prognosis (e.g., rapid disease progression, high malignancy, short patient survival time, etc.) in pancreatic cancer patients. Thus, in certain embodiments described herein, the methods or uses comprise detecting FMO1, ADH6, PLIN4, and GSTZ1, indicating a poor prognosis for the patient if the expression level of ADH6 is 1.5 times or more the mean expression level and the expression level of FMO1, PLIN4, and GSTZ1 is 2/3 or less the mean expression level. Optionally, one or more of any of the proteins of LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB may also be detected, and if the expression level of HNRNPH1 is 1.5 times or more the average expression level, or the expression level of any one or more of the remaining proteins is 2/3 or less the average expression level, in combination with the results of the detection of FMO1, ADH6, PLIN4 and GSTZ1, a conclusion that the prognosis of the patient is poor may also be drawn.

Methods for the quantification of proteins are well known in the art. For example, the protein can be quantified by the conventional Kjeldahl method, the biuret method, the Folin-phenol reagent method, the BCA method, the colloidal gold method, Western blot, ELISA, and liquid chromatography-tandem mass spectrometry. In certain embodiments, Multiple Reaction Monitoring (MRM) techniques may be used in conjunction with synthetic peptide fragment-based absolute quantitation techniques (AQUA), which allow direct absolute content detection of a protein or proteins in a plurality of samples. For example, to detect the amount of a polypeptide in a sample, the polypeptide can be synthesized and labeled with a heavy isotope (e.g., 13C); then adding a certain amount of the heavy isotope labeled polypeptide into a sample to be detected, detecting the intensity of the polypeptide (or the fragment thereof) in the sample by using a multiple reaction monitoring technology, and determining the content of the polypeptide in the sample by comparing the intensity of the unlabeled polypeptide (namely the polypeptide in the sample) or the fragment thereof with the intensity of the heavy isotope labeled polypeptide.

Herein, the detection reagent contained in the kit may be a reagent used in the detection process, such as a reagent required for preparation of a corresponding biopsy sample and a reagent required for tissue homogenization, etc., or may be a direct detection reagent, such as an antibody or an antigen-binding fragment thereof specifically binding to the protein. Tissue homogenization reagents include, but are not limited to, SDT lysis buffer (4% SDS, 0.1M Tris-HCl pH7.6,0.1M DTT). The reagents used in the detection process may be, for example, those used for preparing a suitable protein solution to be detected, including, for example, reagents used for preparing a peptide fragment sample, such as enzymatic reagents required for FASP enzymatic hydrolysis of proteins in cell lysates, and reagents required for desalting the peptide fragments. In performing liquid chromatography-tandem mass spectrometry, the reagents also include the corresponding mobile phases, such as 0.1% FA in water and 0.1% FA in ACN.

In certain embodiments, immunohistochemical methods may be used to quantitatively detect the expression of the proteins described herein. Immunohistochemistry is a method that is conventional in the art, and generally uses specific binding of an antigen to an antibody to color a color-developing agent that labels the antibody by a chemical reaction, thereby determining the presence and/or amount of a protein of interest. The method or use may be carried out using antibodies specific for each of the proteins described herein that can serve as biomarkers. Such specific antibodies may be known commercially available antibodies. Alternatively, their respective specific antibodies can be prepared per se according to known techniques (e.g., hybridoma technology). The antibody can be a monoclonal antibody or a polyclonal antibody; monoclonal antibodies are preferred. Antigen-binding fragments of antibodies may also be used. Thus, in certain embodiments, the reagents described in various embodiments of the kits herein can be antibodies that specifically bind to the respective proteins, and optionally other reagents required to carry out the immunohistochemical methods

In certain embodiments, the proteins described herein are quantitatively determined using a Multiplex Reaction Monitoring (MRM) technique in combination with an absolute quantitative technique based on synthetic peptide fragments (AQUA). Thus, the kit neutralizes the protein to be tested or its corresponding peptide fragment. For each protein described herein as a biomarker, the marker peptide will vary depending on the enzymatic method and can be readily determined by one of skill in the art using routine techniques.

The present invention will be illustrated below by way of specific examples. It is to be understood that these examples are illustrative only and are not intended to limit the present invention. The various methods and materials mentioned in the examples are, unless otherwise indicated, conventional in the art.

Experimental procedure

Experimental sample collection

A pancreatic cancer patient from the second military medical university affiliated long sea hospital was invited to attend the program. From No. 1/6 in 2016 to No. 5/4 in 2016, 75 pancreatic cancer patients are grouped, and 32 pancreatic ductal adenocarcinoma patients are established as the official experimental analysis samples according to the completeness of experimental data and pathological information and prognostic information. Within the 9-15 month follow-up period after surgery, by 5 months of 2017, 22 of 32 pancreatic cancer patients survived and 10 died. We collected cancer tissue surgically removed from the patient and adjacent paracancerous tissue and immediately stored it in liquid nitrogen, which was used for proteomic analysis. In proteomics analysis, a statistical analysis method of paired t-test is used, and a clustering method of HCA and PCA is adopted to perform clustering analysis on proteins, and simultaneously, a signal path enriched by differential proteins is displayed. Clinical data for the patients are shown in table 1 below.

TABLE 1

peptide fragment sample preparation

tissue homogenates were prepared using SDT lysis buffer (4% SDS, 0.1M Tris-HCl pH7.6,0.1M DTT) and JX-FSTPRP full-automatic sample cryomill (Shanghai Jingxin technology). Protein concentration was determined using tryptophan fluorescence emission with an excitation wavelength of 295nm and light absorption at 350nm [ Suman S.Thakur, T.G., BhastatateChanterjee, PeterBandilla, Florian frohlich, Juergen Cox and Matthias Mann, Deep and Highllysensive Proteomegaproduct by LC-MS/MS Without precipitation, Mol CellProteomics,2011.16(7): p.1-9 ]. Modified filtration-assisted sample preparation (FASP, FASP method reference [ Wisniwski, J.R. et al, Universal sample preparation method for proteomics, Nat Methods,2009.6(5): p.359-62 ] (compatible with TMT10 marker, TMT10 marker method reference kit instructions) was used for enzymatic treatment of protein samples, peptide fragment StageTip desalting (method reference [ Rappsil, J., M.Man and Y.Ishihama, Protocol for micro-purification, pre-differentiation and storage of peptides for proteomics using StageTips, Natprotoc,2007.2(8): p.1896-906, TMT10 marker quantitative proteomics Methods were used to determine differences between two patient groups for reducing protein expression differences between the same patient groups, for comparison of experimental deviations between the same TMT10, for the convenience of subsequent experimental treatment of different groups, and for comparison of the differences between the TMT 387 and TMT 387 for the same experimental treatment of protein groups, TMT 387, and for comparison of the same experimental deviation of protein groups, TMT 387, and for comparison of experimental deviations of the same experimental techniques.

Peptide high-pH RP fractionation

Fractionation of the TMT 10-labeled peptide fragments was carried out using the High pH RP system, method reference [ Kong, R.P., et al, Development of online High-/low-pH reversed-phase two-dimensional liquid chromatography for shotgun proteins: reversed-phase-strand displacement-reversed-phase amplification, J chromatography A, 2011.1218(23): p.3681-8 ]. The column was Waters xbridge BEH300C18RP, and the fractionation column was Dionex U3000. Mobile phase is solution a, 2M aqueous ammonia with pH 10.0 (100 ×, FA adjusted pH 10.0): ACN: H2O ═ 1: 2: 97, a stabilizer; solution B, 2M aqueous ammonia (pH 10.0 by FA) (100 ×, pH 10.0 by FA): ACN: H2O ═ 1: 97: 2. gradient set as (% B): time, 5: 2min, (5-25): 40min, (25-40): 20min, (40-95): 4min, 95: 4min, (95-5): 4min, 5: and 6 min. The flow rate was 0.7mL/min, the column oven temperature was 45 ℃ and the detection wavelength was 214nm, 40 fractions were collected every 2min and combined into 20 lyophilisates (combination strategy 1&21, 2&22 … 20&40) for mass spectrometric detection.

Liquid chromatography-tandem mass spectrometry

The peptides were separated by EASY-nLC 1000 chromatography (Thermo Fisher Scientific) with mobile phase A at 0.1% FA in H₂O solution and B solution are 0.1 percent FA solution in ACN. The C18 reversed phase chromatographic column is a self-made packing with the diameter of 75 mu m, the diameter of 150mm and the diameter of 3 mu m C18. Chromatographic gradient (% B): time, (2-8): 2min, (8-15): 50min, (15-19): 28min, (19-27): 20min, (27-40): 8min, (40-90): 2min, (99-90): 10min, separation time 2h, flow rate 250 nL/min. The mass spectrometer is Q-exact HF (Thermo Fisher Scientific), and data acquisition is performedin "high-high" mode, the first-order full scan is the Orbitrap detector (300- & ltSUB & gt 1800m/z), the resolution is 120,000- & ltSUB & gt m/z 200, the AGC target is set to 3E6, and maximum IT is 50 ms; the secondary scan was data dependent acquisition mode (DDA, top 20), HCD fragmentation with a resolution of 60,000@ m/z 200, AGC target set to 2E5, maximum IT of 80ms, isolation window of 1.2m/z, 30.0% NCE, Orbitrap detector (200 + 2000 m/z). The dynamic exclusion settings are: repetition times, 1; repetition time, 30 s; exclusion time, 120 s. All data were collected by Xcalibur software.

Database search and quantitative analysis of mass spectrometry data

All Raw files were data-searched by MaxQuant 1.5.2.8 software [ Cox, J. et al, aprical guide to the MaxQuant computerized platform for SILAC-based quantitative programs, Nat protocol, 2009.4(5): p.698-705 ], which is the SwissP-rot human database (2016 year 03 month download). The fixed modification sets cysteine Carbammidomethyl; the variable modification was set to oxidizedmethionine, N-acetylation. The trypsin/P is selected by enzyme, at most 2 enzyme cutting deletion sites are allowed, the Type is reporter ion MS2TMT10, the reporter mass tolerance is 0.04ppm, the mass tolerance of the peptide first search and the mass tolerance of the main search are respectively set to be 20ppm and 4.5ppm, and the FDR of the peptide and the protein are both set to be 0.01.

Statistical and bioinformatics analysis

The quantitative results of the proteins were corrected linearly (longitudinal median correction), Mix between different groups was the same sample, Mix transverse correction between groups, data analysis and statistical tests were done using software R or Excel, and pathway enrichment was done using DAVID software.

(1) Hierarchical Clustering Analysis (HCA): this was done using the pheatmap package in software R, and the distance was calculated from the protein expression level between samples, and the samples at closer distances were pooled together.

(2) Principal Component Analysis (PCA): the method is completed by utilizing a prcomp function in the software R, a large number of related variables are converted into a group of few unrelated variables, the dimensionality of the variables is reduced, and meanwhile, original data information is kept as much as possible.

(3) and (3) path enrichment: the GO biological process and the enrichment of the KEGG metabolic pathway are completed through a DAVID website, the count number is set to be 2, and the enrichment analysis is carried out by taking a human whole protein database as a background. While performing multiple tests will reduce false positives for both the enriched GO-BP (biological Process, BP) and KEGG pathways, it will also reduce the number of enriched pathways. Therefore, in order to ensure the integrity of the enrichment information, except for the different protein enrichment biological processes of cancer tissues and tissues beside cancer and the p value corrected by Benjamini, the original p value is used in other enrichment processes and the threshold value is set to be 0.05.

(4) Validation of candidate protein prognostic effect patient samples in two online biomarker validation tool (SurvExpress, http:// bioinformatica. mty. itesm. mx:8080/Biomatec/Survivax. jsp) data sets were used and divided into two groups according to median gene expression (SurvExpress). The overall survival of the two groups of patients was compared by the Kaplan-Meier survival curve. Hazard ratios and logrank P values are calculated [ Gyorffy, B. et al, Onlinescurval analysis software to assess the physiological value of biomarkers using a transcriptional data in non-small-cell lung cancer, PLoS One, 2013.8(12): p.e82241 ].

Results

Experimental procedure and data overview

The cancer tissues and the paracarcinoma tissues of 75 pancreatic cancer patients are counted in 17 groups of TMT10 experiments, the peptide fragment labeling efficiency is over 99 percent, the total amount of the 17 groups of TMT10 experiments is 101808 credible peptide fragments (FDR <0.01) and 6867 credible proteins (FDR <0.01), and 3115 overlapped proteins are arranged in the cancer tissues and the paracarcinoma tissues of all the patients. 32 patients with complete pathological information, complete prognostic information and pathological diagnosis of ductal pancreatic adenocarcinoma were used as experimental samples for subsequent analysis, and 3252 proteins overlapping in the cancer tissues and the paracarcinoma tissues of the 32 patients were used for subsequent data analysis.

Differential protein analysis of cancer tissue and paracarcinoma tissue

To find biomarkers associated with pancreatic cancer, we compared proteome expression in cancer and paracancerous tissues and performed a paired t-test (select FDR correction) on 3252 proteins that overlapped in cancer and paracancerous tissues. In order to ensure that the pancreatic cancer is enriched to be sufficiently rich in biological processes and metabolic pathways, p values are controlled to be less than 0.05 and FC (fold change) is controlled to be more than or equal to 1.2 after FDR correction, 540 differential proteins are screened out in total, wherein 410 proteins are up-regulated in cancer tissues, 130 proteins are down-regulated in cancer tissues, and the significant increase of the up-regulated proteins in the cancer tissues indicates that the pancreatic cancer obtains certain functions significantly. The results show that the 540 HCAs and PCA differentially expressed proteins clearly divided cancer and paracancerous tissues into two clusters.

The KEGG pathways significantly enriched with 410 proteins upregulated in cancer tissues include focal adhesion, actin aggregation regulation (regulation of actin cytoskeleton), antigen presentation and presentation, and the KEGG metabolic pathways significantly enriched with 130 differential proteins downregulated in cancer tissues include metabolic pathways (metabolic pathways), autoimmune thymus disease (autoimmune thymus disease), and allograft rejection (allograft rejection).

In the obtained pancreatic cancer tissue proteome data, 540 proteins differentially expressed in cancer tissues and paracarcinoma tissues are significantly enriched in the ECM-Receptor interaction pathway, wherein proteins such as fibronectin (fibronectin), THBS (THBS), Laminin (lamin) and the like are significantly up-regulated in cancer tissues. Studies have shown that Fibronectin (FN) protein is a protein rich in pancreatic cancer stroma and less in normal tissue, FN protein plays an important role in pancreatic cancer metastasis, chemotherapy drug resistance and angiogenesis, and a target drug designed for FN can effectively reduce pancreatic cancer growth and metastasis while increasing the delivery efficiency of chemotherapy drugs [ Jones, S. et al, Core signalings pathway in human clinical cancer recovered by general genetic analysis. science,2008.321(5897): p.1801-6 ].

Cancer tissue differential protein analysis in patients with survival and death

In a follow-up period of 9-15 months after the operation, 22 of 32 pancreatic cancer patients live and 10 patients die by 5 months in 2017, the patients are divided into a survival group and a death group according to the survival condition of the patients, a non-pairing t-test is carried out on a proteome in a cancer tissue of a pancreatic cancer patient, and differential proteins are screened according to the standard that the p value is less than 0.05 and the FC is more than or equal to 1.2. 95 differential proteins were screened from 3252 proteins in pancreatic cancer patient tissues in the survival and death groups. The results show that 95 different proteins of HCA and PCA can be well separated between the pancreatic cancer patients in the survival group and the death group. Of the 95 differential proteins, 34 were up-regulated in pancreatic cancer patients in the death group, 61 were down-regulated in cancer tissues in pancreatic cancer patients in the death group, and no significant KEGG pathway enrichment was found for these differential proteins.

according to the screening criteria of p-value <0.05 and FC ≧ 1.5, 14 more significantly different proteins were screened in total in cancer tissues of both living and dead pancreatic cancer patients (see Table 2). The results of HCA and PCA for these 14 different proteins also show that the separation of patients with live and dead pancreatic cancer is good.

Table 2: 14 differential proteins with p-value <0.05 and FC ≥ 1.5 in cancer tissues of patients with living and dead pancreatic cancer

As shown in fig. 1, the ROC curve AUC of 14 proteins with more significant differences in cancer tissues of pancreatic cancer patients in the survival group and the death group and 4 proteins (FMO1, ADH6, PLIN4, and GSTZ1) selected as prognostic markers were both 1, pancreatic cancer patients could be strictly divided according to survival status in the 9-15 month follow-up period, and the specificity and sensitivity were 1, indicating that the 14 different proteins with more significant differences and the last 4 different proteins could be used as biomarkers for prognosis of pancreatic cancer patients. FMO1 is a riboflavin-containing monooxygenase that mediates N-oxidation of the amino acid Trimethylamine (TMA), but no studies on riboflavin and cancer correlations are currently available. A Jelski-led study measuring ADH activity in plasma of 165 pancreatic cancer patients and 166 healthy persons showed that ADH activity was higher in pancreatic cancer patients than in plasma of normal control patients, indicating that ADH could be a biomarker for predicting pancreatic cancer, and had 70% sensitivity and 76% specificity [ Jelski, W. et al, Alcohol Dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) as candidates for tumor markers in tissues with clinical marker, JGastrontion Liver Dis,2011.20(3): p.255-9 ]; ADH6 also has significant relevance as a subtype of ADH and pancreatic cancer prognosis. PLIN 4is a lipid droplet-associated protein that is associated with a poor and up-regulated prognosis of PLIN4 in uterine and colorectal cancers, while PLIN 4is down-regulated in patients with death in pancreatic cancer data, suggesting a correlation between PLIN4 down-regulation and poor prognosis, suggesting a difference in the role of PLIN4 in pancreatic and uterine cancers as well as colorectal cancers. The GSTZ1 protein is a member of the glutathione transferase superfamily, encodes proteins involved in detoxification, including various carcinogens, mutagens, and therapeutic drugs, glutathione is also involved in regulating cell proliferation, and high expression of glutathione in tissues may be a cancer biomarker [ Bermano, G., et al; immunological expression of glutathione peroxidase-4gene in epithelial tissue, cancer Biomarkers,2010.7(1): p.39-46; hamios, D.L., Glutathione-Its Role in modulation of Immune function. eos-Rivista Di Immunologia Edimmumofacologia 1992.12(1) p.11-15; oh, I.J., et al, Serum glutaminone Peroxidase3as a Biomarker of Positive Relay in Patients with Lung cancer, journal of clinical Oncology,2015.10(9) p.S496-S496; wang, x.m. et al, glutaminone S-transferase alpha 4is a potential biological marker for Enterococcus failure-induced inflammation and cancer Research,2013.73(8), down-regulated in patients with dying pancreatic cancer, may indicate that proteins exerting detoxification in dying patients down-regulated in vivo may influence the patients 'tolerance to toxicity to reduce, leading to the patients' physical health being impaired, and specific mechanisms are to be studied later. In conclusion, the 4 selected proteins for predicting the postoperative survival length of pancreatic cancer have certain correlation with pancreatic cancer, and are newly discovered markers for predicting the prognosis of pancreatic cancer patients.

To further assess the correlation between the 14 different proteins and the overall survival of cancer patients, we used online survival analysis software surfexpress. In the survivorship analysis, a microarray dataset based on one of the TCGAs containing 176 pancreatic cancer patients was selected and studied for survival curves of the patients. The 14 differential proteins we found were significantly associated with a high risk of prognosis in pancreatic cancer patients as shown in the TCGA dataset (risk ratio 2.14, p-value 0.0005481, fig. 2); the marker combination consisting of 4 selected proteins, namely FMO1, ADH6, PLIN4 and GSTZ1, is also significantly related to the high risk of pancreatic cancer patients (the risk ratio is 1.58, the p value is 0.03173, and figure 3), and the effectiveness of the combination of FMO1, ADH6, PLIN4 and GSTZ1 as a pancreatic cancer prognosis marker is verified.

In a follow-up period of 9-15 months, the death of the patient indicates higher malignancy of the cancer of the patient, and a biomarker combination consisting of FMO1, ADH6, PLIN4 and GSTZ1 can be used as a prognosis marker of the malignancy of the pancreatic cancer, so that the death state of the patient can be predicted, and meanwhile, the postoperative patient can be intervened in time according to the expression level of the markers, so that the life cycle and the quality of life of the patient are prolonged.

Discussion of the related Art

Quantitative proteomics is widely used for the discovery of biomarkers for various cancers. The classical approach to proteomic biomarkers is to compare the differential expression of proteins between cancerous and distant normal tissues (or tissues adjacent to cancer). In our study, to identify proteins associated with pancreatic cancer, we compared the differential proteins between the cancer tissue and the paracancerous tissue of the same pancreatic cancer patient, and this pairing avoided the effect of individual differences on differential protein screening.

Pancreatic cancer progresses rapidly, and symptoms are not obvious, so that most of cancers are advanced at the time of diagnosis, and the prognosis and survival rate of patients are extremely low. At present, research on early biomarkers and prognosis tracking are the most effective means for curing pancreatic cancer and timely intervening after operation to improve the survival time and the quality of life of patients. In this study, we investigated the proteomic differences of cancer tissues in patients in the survival and death groups during the 9-15 month follow-up period after surgery in order to investigate biomarkers indicative of prognosis and guiding post-operative treatment. We found that 95 differentially expressed proteins in two groups, including 14 differential proteins such as PLIN4, ADH6, FMO1 and GSTZ1, can be used as biomarkers for indicating prognosis, and in order to verify the validity of prognosis significance of 14 differential proteins and the combination of selected FMO1, ADH6, PLIN4 and GSTZ1 proteins, the AUC of ROC of 14 differential proteins and 4 differential proteins is 1, so that patients in survival and death groups can be completely distinguished, and the survival analysis data set of microarray containing 176 samples in TCGA verifies our findings, which indicates that the combination of PLIN4, ADH6, FMO1 and GSTZ1 proteins can be used as biomarkers for pancreatic cancer, indicating prognosis and timely intervening in postoperative survival.

Claims (10)

1. The application of any one or more of proteins selected from FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB as a detection object in preparing a detection reagent or a detection kit for predicting the disease development or the disease malignancy of a pancreatic cancer patient.

2. The use of claim 1, wherein the protein comprises:

(1) Any one or more of proteins selected from FMO1, ADH6, PLIN4 and GSTZ 1; and optionally

(2) One or more selected from LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB.

3. the use of claim 2, wherein the protein comprises:

(1) FMO1, ADH6, PLIN4, and GSTZ 1; and optionally

(2) One or more selected from LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB.

4. Use of a detection reagent for any one or more of proteins selected from FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBLL1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB in the preparation of a detection kit for predicting the development or malignancy of a pancreatic cancer patient.

5. The use of claim 4, wherein the protein comprises:

(1) Any one or more of proteins selected from FMO1, ADH6, PLIN4 and GSTZ 1; and optionally

(2) One or more selected from LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB.

6. The use of claim 5, wherein the protein comprises:

(1) FMO1, ADH6, PLIN4, and GSTZ 1; and optionally

(2) One or more selected from LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB.

7. The use of any one of claims 4 to 6, wherein the detection reagent is an antibody or antigen-binding fragment thereof.

8. A kit comprising a reagent for detecting a protein selected from any one or more of FMO1, ADH6, PLIN4, GSTZ1, LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB.

9. The kit of claim 9, wherein the kit comprises:

(1) A detection reagent for any one or more proteins selected from FMO1, ADH6, PLIN4 and GSTZ1, preferably FMO1, ADH6, PLIN4 and GSTZ 1; and optionally

(2) A detection reagent for any one or more proteins selected from LIPE, COBALL 1, HNRNPH1, TPM3, ZNF587B, PLIN1, GCG, PNLIPRP2 and HBB.

10. The kit of claim 8 or 9, wherein the kit comprises: an agent that specifically binds to the protein, including an antibody or antigen-binding fragment thereof; and optionally reagents for preparing a biopsy sample, optionally reagents for tissue homogenization, optionally reagents for preparing a peptide sample, and optionally reagents for desalting the peptide.