A biomarker combination for detecting gastric cancer autoantibodies and its application

A technology for biomarkers and autoantibodies, applied in biological testing, biomaterial analysis, measurement devices, etc., can solve the problems of low specificity, sensitivity and accuracy of autoantibodies in gastric cancer detection

Active Publication Date: 2022-07-26
RAYBIOTECH INC GUANGZHOU
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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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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  • A biomarker combination for detecting gastric cancer autoantibodies and its application
  • A biomarker combination for detecting gastric cancer autoantibodies and its application
  • A biomarker combination for detecting gastric cancer autoantibodies and its application

Examples

Experimental program
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Embodiment 1

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

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

[0046] By means of genetic engineering, a variety of proteins are produced and identified using eukaryotic expression platforms. Specifically, the target gene is amplified by RT-PCR and cloned 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, a variety of proteins were obtained by affinity chromatography and high performance liquid chromatography purification from the lysate or inclusion bodies. These proteins are human proteins and serve as the biomarkers to be screened by the following protein chips, figure 1 Thi...

Embodiment 2

[0058] The examples of this application provide log 2 Accuracy and sensitivity analysis of (IgG / IgA) ratio modeling to predict autoantibodies in gastric cancer. The specific analysis steps are as follows:

[0059] Since the response of IgG and IgA to different targets on the gastric cancer detection chip was simultaneously detected in this example, 18 targets were obtained by further analysis. The log of these 18 targets 2 (IgG / IgA) was significantly different 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, and the three supervised SVM, GBM and RDA were used. The mathematical model performs different permutation and combination calculations on these 18 targets. The screening results of modeling analysis in 222 cases of gastric cancer and 198 control samples are shown in Table 3. The biomarkers for the diagnosis of gastric cancer screened in the examples of ...

Embodiment 3

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

[0064] 1. The test samples were selected from the asymptomatic control group of healthy people (denoted as the control group, 67 cases) and gastric cancer patients (denoted as the gastric cancer group, 74 cases). IgG.

[0065] 2. The 141 serum samples in step 1 were respectively subjected to immunoreaction with the protein chip for gastric cancer diagnosis in Example 1, and then washed to remove non-specifically bound antibodies. The anti-human IgG antibody and the anti-human IgA antibody were incubated with the above chip respectively, and the serum IgA and IgG of 141 samples were detected to be respectively the 18 biomarkers (hereinafter refe...

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Abstract

The present 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. The present application can detect autoantibodies in the serum of gastric cancer patients. The application provides a biomarker combination for detecting autoantibodies in gastric cancer, including macrophage inflammatory protein-3α, macrophage inflammatory protein-1β, monocyte chemokine-1 and matrix metalloproteinase-9. The present application provides a biomarker combination for detecting gastric cancer autoantibodies, which can effectively solve the technical defects of low specificity, sensitivity and accuracy of existing markers for detecting gastric cancer autoantibodies.

Description

technical field [0001] The present application belongs to the technical field of molecular biology, and in particular relates to a combination of biomarkers for detecting autoantibodies in gastric cancer and applications thereof. Background technique [0002] Gastric cancer is one of the most common malignant tumors in the world and one of the malignant tumors with the highest mortality rate. Most patients with gastric cancer have missed the best time for diagnosis and treatment when they are diagnosed, leading to disease progression, tumor metastasis, and even end-stage disease. 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. was 31.9%, and the fourth period was 6.5%. It can be seen that the diagnosis of early gas...

Claims

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Application Information

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Patent Type & Authority Patents(China)
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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