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Biomarker composition for detecting gastric cancer autoantibody and application of biomarker composition

A technology of biomarkers and autoantibodies, which is applied in biological testing, biomaterial analysis, measuring devices, etc., can solve the problems of low specificity, sensitivity and accuracy in the detection of gastric cancer autoantibodies, and achieve improved sensitivity and accuracy, The effect of a good diagnosis

Active Publication Date: 2021-04-09
RAYBIOTECH INC GUANGZHOU
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In view of this, this application provides a combination of biomarkers for detecting gastric cancer autoantibodies and its application, which can effectively solve the technical defects of the existing markers in detecting gastric cancer autoantibodies with low specificity, sensitivity and accuracy

Method used

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  • Biomarker composition for detecting gastric cancer autoantibody and application of biomarker composition
  • Biomarker composition for detecting gastric cancer autoantibody and application of biomarker composition
  • Biomarker composition for detecting gastric cancer autoantibody and application of biomarker composition

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Embodiment 1

[0044] The embodiment of the present application provides a screening test for the combination of biomarkers for the diagnosis of gastric cancer autoantibodies, and the specific steps are as follows:

[0045] 1. Construction of a protein chip for detection of gastric cancer autoantibodies

[0046] Using genetic engineering means, using eukaryotic expression platform to produce and identify a variety of proteins. Specifically, RT-PCR is used to amplify the target gene and clone it into a bacterial expression vector. After the correctness of the gene cloning vector is verified by DNA sequencing, the recombinant material is transformed into competent expression bacteria. After gene induction and expression, various proteins were purified by affinity chromatography and high performance liquid chromatography from the lysate or inclusion body, and these proteins were human proteins, which were used as biomarkers to be screened by the following protein chip, figure 1 It is the SDS-P...

Embodiment 2

[0058] The embodiment of this application provides log 2 (IgG / IgA) ratio modeling to predict the accuracy and sensitivity of gastric cancer autoantibodies, the specific analysis steps are as follows:

[0059] Since this embodiment simultaneously detected the responses of IgG and IgA to different targets on the gastric cancer detection chip, further analysis obtained 18 targets, and the log of these 18 targets 2 (IgG / IgA) has a significant difference between the gastric cancer group and the control group. In order to screen specific biomarkers related to gastric cancer, the "crate" package in the R language was used to use the three supervised SVM, GBM and RDA The mathematical model performs different permutation and combination calculations on these 18 targets, and the screening results of modeling analysis in 222 cases of gastric cancer and 198 cases of control samples are shown in Table 3. Combination: MIP-3α, MIP-1β, MCP-1 and MMP-9 have the lowest AUC for diagnosing gastr...

Embodiment 3

[0063] The examples of this application provide biomarker combinations for detecting gastric cancer autoantibodies: macrophage inflammatory protein-3α (MIP-3α), macrophage inflammatory protein-1β (MIP-1β), monocyte chemoattractant-1 (MCP-1) and matrix metalloproteinase-9 (MMP-9) confirmation test, the specific steps are as follows:

[0064] 1. The test samples were selected from the asymptomatic control group of healthy people (recorded as the control group, 67 cases), gastric cancer patients (recorded as the gastric cancer group, 74 cases), the serum of the above samples was extracted, and the IgA and IgA levels of the serum of the above 141 samples were obtained. IgG.

[0065] 2. The 141 serum samples in step 1 were immunoreacted with the protein chip for gastric cancer diagnosis of Example 1, and then washed to remove non-specifically bound antibodies. The anti-human IgG antibody and anti-human IgA antibody were respectively incubated with the above-mentioned chips, and th...

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Abstract

The invention belongs to the technical field of molecular biology, and relates to a biomarker composition for detecting a gastric cancer autoantibody and application of the biomarker composition. The biomarker composition can be used for detecting the autoantibody in serum of a patient with gastric cancer. The biomarker combination for detecting the gastric cancer autoantibody comprises macrophage inflammatory protein -3alpha, macrophage inflammatory protein -1beta, a monocyte chemotactic factor -1 and matrix metalloproteinase -9. With the biomarker composition for detecting the gastric cancer autoantibody, the technical defects of low specificity, sensitivity and accuracy of an existing marker for detecting the gastric cancer autoantibody can be eliminated.

Description

technical field [0001] The application belongs to the technical field of molecular biology, and in particular relates to a biomarker combination for detecting gastric cancer autoantibodies and its application. Background technique [0002] Gastric cancer is one of the most common malignant tumors in the world, and it is also one of the malignant tumors with the highest mortality rate. Most gastric cancer patients have missed the best opportunity for diagnosis and treatment when they are diagnosed, leading to disease progression, tumor metastasis, and even entering the terminal stage. From the perspective of TMN staging of gastric cancer, the 5-year survival rate of gastric cancer is 97.6% in the early stage of the first stage, 94.9% in the late stage of the first stage, 70.49% in the second stage, 56.7% in the early stage of the third stage, and 56.7% in the late stage of the third stage. It was 31.9%, and the fourth period was 6.5%. Visible early gastric cancer diagnosis ...

Claims

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Application Information

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IPC IPC(8): G01N33/574G01N33/564G01N33/543G01N33/58
CPCG01N33/57446G01N33/57488G01N33/564G01N33/543G01N33/582G01N2333/523G01N2333/96419
Inventor 黄若磐罗树红符聪聪琼·克拉布特里
Owner RAYBIOTECH INC GUANGZHOU
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