CN109142730B

CN109142730B - A kind of lung cancer marker anti-PSIP1 autoantibody and its application

Info

Publication number: CN109142730B
Application number: CN201810611747.9A
Authority: CN
Inventors: 代丽萍; 刘红春; 王鹏; 王婷婷; 裴露; 蒋迪
Original assignee: First Affiliated Hospital of Zhengzhou University
Current assignee: First Affiliated Hospital of Zhengzhou University
Priority date: 2018-06-14
Filing date: 2018-06-14
Publication date: 2021-04-23
Anticipated expiration: 2038-06-14
Also published as: CN109142730A

Abstract

The invention belongs to the technical field of biomedical detection, and in particular relates to a lung cancer marker anti-PSIP1 autoantibody and an application thereof. The invention discloses a lung cancer marker, which is an anti-PSIP1 autoantibody. The present invention also provides the application of the above-mentioned lung cancer marker in the preparation of a detection kit for lung cancer. The invention provides a serum biomarker for clinical lung cancer detection with simple operation, low cost, high accuracy and non-invasiveness. The research of the present invention finds that the detection of serum anti-PSIP1 autoantibodies by ELISA method can more accurately distinguish lung cancer patients from normal people, as well as benign lung disease patients, and can be used for the detection of metastatic lung cancer. In this context, this convenient, fast and effective marker for detecting lung cancer patients and a kit for preparing the marker for lung cancer detection are provided, which can be used for clinical early diagnosis of lung cancer.

Description

Lung cancer marker anti-PSIP 1 autoantibody and application thereof

Technical Field

The invention belongs to the technical field of biomedical detection, and particularly relates to a lung cancer marker anti-PSIP 1 autoantibody and application thereof.

Background

Lung cancer is the first malignancy in china, and worldwide in morbidity and mortality. The clinical manifestations of lung cancer are complex and diverse, early lung cancer is occult and diverse, the clinical characteristics and physical signs are not obvious, and the lung cancer only shows nonspecific symptoms such as cough, expectoration, chest pain, fever, physical strength reduction and the like, so that most of lung cancer patients are found to be in late stage. Clinical data show that nearly 60% of patients have advanced lung cancer at the time of treatment. The 5-year survival rate of the late stage lung cancer is only about 16%, while the five-year survival rate of the early stage lung cancer (stage I) can reach as high as 70%. It can be seen that early detection and early diagnosis of lung cancer are key links for reducing incidence and mortality of lung cancer.

At present, a plurality of detection means for lung cancer are clinically used, and mainly comprise noninvasive examination (CT, X-ray chest radiography and the like) and some invasive examination (fiberbronchoscope, cast-off cytology examination, CT positioning puncture biopsy and the like). The X-ray chest radiography has the advantages of convenience, rapidness, no wound and the like, has important significance for lung cancer diagnosis, but lacks compliance and universality and can only be used as an index for auxiliary diagnosis. Cytology and histopathology methods are the gold standards for the definitive diagnosis of lung cancer, but the difficulty in obtaining materials is large, and the methods cannot be used for large-scale population screening. In recent years, serum biological markers have attracted attention due to the advantages of small invasiveness, simple operation, wide screening range, high detection efficiency and the like. Currently, clinical serum biological markers include sugar chain antigens (CA 125 and CA 199), cytokeratin 19 fragment antigen (CYFRA 21-1), carcinoembryonic antigen (CEA) and the like, but a tumor marker with high sensitivity and specificity is not found.

Tumor development can be attributed to structural or functional abnormalities of a series of tumor-associated genes, and tumor antigens (TAAs) are qualitatively or quantitatively abnormal proteins or polypeptides expressed by these abnormal genes, and the antibodies generated are called anti-TAA autoantibodies. Since tumor antigens are mainly distributed in tumor cells, membrane surfaces or serum, the body's specific or non-specific humoral immune response and cellular immune response are activated to varying degrees. anti-TAAs autoantibodies are absent or have low titers in the serum of normal human and non-tumor patients, the level of autoantibodies in the serum of patients often rises earlier than the appearance of tumor symptoms and it is able to persist in the serum, while other markers, including TAA itself, are rapidly degraded after its release by tumor cells or are cleared by the body shortly after it enters the blood circulation. Therefore, detection of autoantibodies against TAAs can be used as serum markers for early diagnosis of tumors.

PSIP1, a PC4 and SFRS1 interacting protein, also known as DFS70, P75/LEDGF. The DFS70 autoantigen was originally discovered in studies in patients with interstitial cystitis and chronic fatigue syndrome in the 90's of the 20 th century, while the P75/LEDGF autoantigen was first derived from lens epithelial cells in cataract patients. In recent years, it has been widely used as a multifunctional emergency response protein in connection with cancer, autoimmunity, eye diseases, AIDS and the like. There are many studies that have shown that the expression of P75/LEDGF is up-regulated in prostate cancer and other cancers, and that the overexpression of this protein in cancer cells is related to tumor invasiveness, migration, clonogenicity, angiogenesis, tumor growth, etc.

The Oncomine database (http:// www.oncomine.org) is a gene chip-based database and integrated data mining platform that provides tumor transcriptome data. The Oncomine can analyze the differential expression of a certain target gene in tumor tissues and normal tissues, and can obtain important clinical information of the gene, the tumor size, metastasis, survival time and the like. The invention deeply excavates the gene PSIP1 by combining with an Oncomine database, and carries out serological verification on whether the anti-PSIP 1 autoantibody can be used as a specific index for diagnosing lung cancer in large sample quantity.

In conclusion, in order to finally reduce the mortality rate of lung cancer and improve the survival rate, the screening and identification of more sensitive and specific serological autoantibody markers and the development of a kit for detecting the lung cancer autoantibody, which is simple to operate, low in cost and wide in application range, are urgently needed in the field.

Disclosure of Invention

The invention aims to overcome the problem that the existing tumor marker of the lung cancer is not ideal, and aims to provide a new application of an anti-PSIP 1 autoantibody in improving the sensitivity, specificity and accuracy of the diagnosis of the metastatic lung cancer. A diagnostic marker with high specificity and strong sensitivity is used for preparing a kit for diagnosing lung cancer, which has good stability and convenient detection. The invention specifically provides a lung cancer serum diagnostic marker, And particularly relates to an autoantibody of anti-PSIP 1 (PC 4 And SFRS 1-interacting Protein 1) capable of distinguishing lung cancer from normal people.

In order to achieve the purpose, the invention adopts the following technical scheme:

in a first aspect, the invention provides a lung cancer marker which is an anti-PSIP 1 autoantibody.

In a second aspect, the invention provides the use of an anti-PSIP 1 autoantibody according to the first aspect in the manufacture of a reagent or kit for serological detection of lung cancer.

Preferably, the kit is an enzyme-linked immunosorbent assay (ELISA) based detection system.

Preferably, the reagent or kit contains a PSIP1 recombinant purified protein for detecting anti-PSIP 1 autoantibodies.

Preferably, the kit further comprises ELISA coating buffer (20X), secondary HRP-Rec-A antibody, blocking Buffer (BSA), ELISA universal antibody diluent, ELISA-ABTS color reagent, PBST (Tween 20-phosphate buffer), and stop buffer.

Compared with the prior art, the invention has the beneficial effects that:

the invention provides a serum biomarker which is simple to operate, low in cost, high in accuracy and non-invasive and is applied to clinical lung cancer detection. The research of the invention finds that the ELISA method is used for detecting the serum anti-PSIP 1 autoantibody, so that the lung cancer patients can be accurately distinguished from normal people and the lung disease chronic disease patients, and the method can be used for detecting the metastatic lung cancer. Under the background, the marker for conveniently, quickly and effectively detecting the lung cancer patient and the kit for preparing the marker for detecting the lung cancer can be used for clinical early diagnosis of the lung cancer.

Drawings

FIG. 1 is a distribution of anti-PSIP 1 autoantibodies in the test group in the lung cancer group and the normal control group and ROC curve analysis (wherein, FIG. 1A is a distribution of autoantibodies, and FIG. 1B is ROC curve analysis);

FIG. 2 is a graph demonstrating the distribution of anti-PSIP 1 autoantibodies levels in the lung cancer group, normal control group and benign lung disease group in the group;

FIG. 3 shows the lung cancer detection efficacy of anti-PSIP 1 autoantibodies in the ROC curve analysis and verification group (LC: lung cancer group; B: benign lung disease group; N: normal control group);

FIG. 4 shows the detection efficacy of anti-PSIP 1 autoantibodies in the group confirmed by ROC curve analysis in the presence or absence of metastasis of lung cancer (N: normal control group).

Detailed Description

The invention utilizes three independent queue studies of the Oncomine database to analyze the expression of PSIP1 mRNA, and uses an ELISA method to detect the level of anti-PSIP 1 autoantibodies in the serum of a lung cancer patient.

1) Three independent cohort studies (including 375 non-small cell lung cancers and 134 normal tissues) using the Oncomine database were mined to analyze the expression of mRNA from PSIP1 in lung cancer and normal tissues, and found to be low in all of the lung cancer groups studied.

2) To test whether anti-PSIP 1 autoantibodies can be used as a diagnostic marker for lung cancer, 184 sera of lung cancer patients and 184 sera of normal human were tested for anti-PSIP 1 autoantibody by ELISA testing method, comprising the steps of: diluting the purchased PSIP1 recombinant purified Protein to 0.5ug/ml by using an antigen coating buffer solution, coating a 96-well plate, diluting a serum sample by using a universal antibody diluent at a ratio of 1:100, reacting with an antigen, reacting with a horse radish peroxidase-labeled recombinant Protein A (HRP-rec-Protein A) antibody, finally adding an ABTS substrate solution for developing color, and reading an OD value under an enzyme labeling instrument (absorbance of 405 nm) to react with the level of the anti-PSIP 1 autoantibody in the serum. The results showed that the anti-PSIP 1 autoantibodies were expressed in the serum of lung cancer patients at a level higher than that of normal human serum, which was statistically significant (P <0.001, as shown in FIG. 1). To further verify whether anti-PSIP 1 autoantibodies could be used as an indicator for screening for lung cancer, ELISA tests were performed on 446 cases of lung cancer, 446 cases of normal control and 119 cases of benign lung disease, and the results showed that anti-PSIP 1 autoantibodies were expressed in the serum of lung cancer patients at levels greater than those in the normal control group and the benign lung disease group, respectively (P <0.001, as shown in fig. 2).

3) In order to test the ability of the anti-PSIP 1 autoantibody to identify lung cancer patients, ROC curve analysis was performed on the lung cancer group and the normal control group, the lung cancer group and the benign lung disease group, and the lung cancer group and the non-lung cancer group (normal control group + benign lung disease group), and the results showed that the area under the curve of the lung cancer group and the normal control group was 0.673(95% CI:0.641-0.704), the area under the curve of the lung cancer group and the benign lung disease group was 0.700 (95% CI:0.660-0.737), and the area under the curve of the lung cancer group and the non-lung cancer group (benign lung disease group + normal control group) was 0.678 (95% CI: 0.649-0.707) (as shown in FIG. 3). anti-PSIP 1 autoantibodies can distinguish lung cancer from non-lung cancer patients very well.

4) In order to further understand the application value of the anti-PSIP 1 autoantibody in the diagnosis of metastatic lung cancer, the anti-PSIP 1 autoantibody is subjected to positive rate analysis in the serum of 217 patients with metastatic lung cancer and 64 patients without metastatic lung cancer, and the result shows that the positive rate of the anti-PSIP 1 autoantibody in the patients with metastatic lung cancer is 30.0 percent, the positive rate in the patients without metastatic lung cancer is 17.2 percent, and the positive rate in the patients with metastatic lung cancer is obviously higher than that in the patients without metastatic lung cancer (P < 0.05). ROC analysis was performed on 446 cases of normal control groups, and the results showed that the AUC values of the metastatic lung cancer and the normal control group were 0.666 (95% CI: 0.629-0.702), and the AUC values of the non-metastatic lung cancer and the normal control group were 0.567 (95% CI: 0.522-0.610) (as shown in FIG. 4), which indicates that the diagnostic value for metastatic lung cancer was higher than that for non-metastatic lung cancer. The result shows that the anti-PSIP 1 autoantibody provided by the invention can be used as a diagnostic marker for predicting metastatic lung cancer.

The invention is further illustrated by the following specific examples.

Example 1

1. Serum specimen collection

1379 cases of the invention are included into research objects, and the research objects are divided into a test group and a verification group, wherein the test group is used for screening indexes with higher diagnostic value for the lung cancer, and the verification group carries out large-batch serological verification on the indexes. The 184 lung cancer patient sera enrolled in the test group were from lung cancer patients at the first subsidiary hospital of the university of 2016-2017 Zhengzhou. The 446 lung cancer patient sera enrolled in the validation group were from lung cancer patients admitted to the first subsidiary hospital of zheng zhou university from 2013 to 2014. All cases were confirmed histopathologically without any surgery or chemotherapy. The 184 normal controls and 446 normal controls of the test group were all from health examiners at the first subsidiary hospital of zheng zhou university, matched with cases by age and gender, and did not suffer from tumor-related diseases and respiratory diseases. 119 cases of benign lung disease sera were obtained from the first subsidiary hospital of the university of 2016 + 2017 Zheng, including patients with chronic obstructive emphysema and chronic pneumonia. All subjects excluded diseases affecting protein expression, such as autoimmune diseases and acute and chronic infections.

Collecting blood of 5ml of all research objects, standing for 30min, centrifuging at 3000rpm for 5min, taking supernatant into Eppendorf tubes, reserving the supernatant, numbering the supernatant respectively, bringing the supernatant into a specimen bank, subpackaging for a short time, storing the product in a refrigerator at 20 ℃ below zero, and freezing and storing the product in the refrigerator at 80 ℃ below zero after long-time storage, so as to avoid repeated freezing and thawing.

2. mRNA expression analysis of PSIP1 by Oncomine database

The expression level of PSIP1 mRNA was analyzed using the Oncomine database. In the present invention, 3 different data sets Hou Lung Dataset (45 Lung cancer tissues and 65 normal tissues), Okayama Lung Dataset (226 Lung cancer tissues and 20 normal tissues), Landi Lung Dataset (58 Lung cancer tissues and 49 normal tissues) were selected. Differential expression of PSIP1 in non-small cell lung cancer versus normal tissue was compared. Search conditions 1, Gene: PSIP 1; 2. analysis Type: cancer vs. normal Analysis; 3. cancer Type: non-small Cell Lung Cancer; 4. sample Type: clinical specificen; 5. data Type: mRNA. The critical value setting condition is corrected P-value (0.05/base factor) that Hou Lung Dataset is less than or equal to 2.55E-6; okayama Lung is less than or equal to 2.55E-6; landi Lung is less than or equal to 3.96E-6. The study results showed that PSIP1 showed low expression in all three studies, with results of P =8.64E-7, FC = -1.588; p =4.06E-15, FC = -1.662; p =1.15E-11, FC = -1.763.

3. ELISA method for detecting serum expression level of anti-PSIP 1 autoantibody

3.1 reagents required

General antibody diluent, coating buffer (20 x), blocking buffer and ABTS-color development kit were purchased from Shanghai Biotechnology engineering Co., Ltd.

General antibody dilutions: the components are BSA (bovine serum albumin) and PBS buffer.

Coating buffer (20 ×): the composition is carbonate buffer solution, and is diluted with deionized water at a ratio of 1:20 when in use.

10 × ELISA PBST wash (1L): weighing NaCl 81.8g and Na₂HPO₄•12H₂O 28.8g，NaH₂PO₄•2H₂O3.1 g, Tween 205 ml, and thiomersalate sodium 0.1g, and deionized water to 1L.

1 × ELISA PBST wash (1L): 100ml of 10 × ELISA PBST wash was taken and deionized water was added to 1L.

3.2 anti-PSIP 1 autoantibody detection method

(1) Coating antigen protein: PSIP1 recombinant purified protein purchased from Biotech, diluted to a final concentration of 0.5ug/ml with antigen protein coating buffer, coated in 96-well plates, loaded 50

l/hole, sealing the preservative film to prevent volatilization, and placing in a refrigerator at 4 ℃ for coating overnight.

(2) And (3) sealing: discarding the coating solution in the wells, adding 100 per well in a 96-well enzyme label plate

l blocking buffer solution containing 2% BSA, placing in a constant temperature water bath at 37 deg.C, blocking for 2h, throwing off the blocking buffer solution sufficiently, placing the ELISA plate in an automatic plate washing machine, and performing the set procedure (200)

l wash buffer/well, 20 s/time, repeat 3 times) wash, pat dry.

(3) Primary antiserum incubation: the test serum was diluted 1:100 using PBST serum dilution containing 1% BSAAdding 50 parts of the sealed 96-hole enzyme label plate

And l, adding the diluted serum to be detected and the diluted yin-yang control serum into blank control holes, putting the blank control holes into a water bath kettle at 37 ℃ for incubation for 1h, fully throwing the liquid in the holes, putting the holes into a plate washing machine for washing, and drying the holes after the washing is finished.

(4) And (3) secondary antibody incubation: using horse radish peroxidase labeled recombinant Protein A (HRP-rec-Protein A) as a secondary antibody, diluting and fully mixing the secondary antibody by using 1% BSA according to a ratio of 1:3000, adding the secondary antibody into a 96-well enzyme label plate respectively, wherein each well is 50 percent

l, placing the mixture in a water bath kettle at 37 ℃ for incubation for 1h, then discarding liquid in holes, washing the plate for 3 times by PBST washing liquor, and patting the plate dry.

(5) Color development: 50 are added into each reaction hole

l, mixing the reaction solution, placing the mixture in a water bath kettle at 37 ℃ in a dark place for color development for 30min until a green product appears.

(6) And (3) terminating the reaction: 25ul of stop solution per well, and then measuring the absorbance value OD of the stop solution by using an enzyme-linked immunosorbent assay_405nmThe OD of each well was measured after zeroing the blank control wells.

4. Statistical analysis method

The Mann-Whitney U test was used in the present invention to analyze the differences in the level of autoantibody content between the two test groups. The differences in the levels of autoantibody content in the three groups of validation groups were compared using a non-parametric test (Kruskal-Wallis). When the specificity is higher than 90%, the sensitivity is highest as a cutoff value, and the value higher than the cutoff value is judged as positive, and the value lower than the cutoff value is judged as negative. Two independent sample chi-square tests were used to compare the autoantibody positivity rate for the presence or absence of metastasis. ROC curve analysis was performed using medcalc12.0 software to judge the ability of the antibody to discriminate lung cancer based on the area under the curve (AUC). All statistical analyses were performed using SPSS20.0 software, with P <0.05 as the statistical criteria.

5. Application of clinical detection of anti-PSIP 1 autoantibody in lung cancer detection

(1) Diagnostic value of anti-PSIP 1 autoantibodies in lung cancer

The invention uses ELISA detection method to detect the level of anti-PSIP 1 autoantibody in 184 cases of lung cancer patients and 184 cases of normal human serum in the test group, and the result shows that the level of anti-PSIP 1 autoantibody in the lung cancer group is obviously higher than that in the normal control group (P <0.001, as shown in figure 1A). By comparing the positive rates of the autoantibodies, the positive rate (32.0%) of the lung cancer group is obviously higher than that of the normal control group (9.8%), and the difference between the two groups has statistical significance (P is less than 0.001). The AUC and 95% confidence interval for normal lung cancer with anti-PSIP 1 autoantibodies was 0.668(0.617-0.716) (as shown in FIG. 1B), with sensitivity and specificity of 32.0% and 90.2%, respectively.

(2) Ability of anti-PSIP 1 autoantibody to discriminate lung cancer group from non-lung cancer group (normal control group + benign lung disease group)

The level of anti-PSIP 1 autoantibodies in the verification group was statistically significant (P < 0.001) between the lung cancer group and the normal control group (see fig. 2). The area under the curve of the lung cancer group and the normal control group was 0.673(95% CI:0.641-0.704), the area under the curve of the lung cancer group and the benign lung disease group was 0.700 (95% CI:0.660-0.737), and the area under the curve of the lung cancer group and the non-lung cancer group (normal control group + benign lung disease group) was 0.678 (95% CI: 0.649-0.707) (as shown in FIG. 3). The invention suggests that the anti-PSIP 1 autoantibody can well distinguish the lung cancer group from the non-lung cancer group (normal control group + benign lung disease group).

(3) Diagnostic value of anti-PSIP 1 autoantibody for metastatic lung cancer

The positive rate of all clinical data (age, sex, stage, pathological type, metastasis condition, tumor family history, smoking and drinking) of the anti-PSIP 1 autoantibody is analyzed, and the result shows that the positive rate (30.0%) of the anti-PSIP 1 autoantibody in the metastatic lung cancer is obviously higher than the positive rate (17.2%) in the non-metastatic lung cancer, and the difference between the two groups has statistical significance (P < 0.05). Other results showed that there was no statistical significance for the differences in autoantibody positive rates in different clinical profiles. ROC results of anti-PSIP 1 autoantibodies with and without metastasis showed that the area under the curve AUC and 95% confidence interval for metastatic lung cancer versus normal was 0.666 (95% CI: 0.629-0.702), and the area under the curve AUC and confidence interval for non-metastatic lung cancer versus normal was 0.567 (95% CI: 0.522-0.610) (as shown in FIG. 4). The AUC between the two groups was compared by Medcalc software and the results showed that the difference between the two groups was statistically significant (P < 0.05).

The result of the invention indicates that the anti-PSIP 1 autoantibody can be used as a biomarker for predicting the lung cancer progression, and the application of the autoantibody in preparing a reagent or a kit for serological detection of lung cancer.

The above description is only a preferred embodiment of the present invention, and the scope of the present invention is not limited thereto, and any simple modifications or equivalent substitutions of the technical solutions that can be obviously obtained by those skilled in the art within the technical scope of the present invention are within the scope of the present invention.

Claims

1. A lung cancer marker, characterized in that the lung cancer marker is an anti-PSIP1 autoantibody.

2. The application of the lung cancer marker anti-PSIP1 autoantibody as claimed in claim 1 in the preparation of a reagent or kit for serological detection of lung cancer.