Identification and use of glycopeptides as biomarkers for diagnosis and treatment monitoring

A technology of biomarkers and biological samples, applied in biological testing, disease diagnosis, bioinformatics, etc., can solve problems such as the inability to trace back to the initial protein site of glycan

Pending Publication Date: 2020-05-12
VENN BIOSCIENCES CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Although protein glycosylation provides useful information about cancer and other diseases, a limitation of this method is that it cannot be traced back to the original protein site of the glycan
Simultaneously obtaining mixed fragments of glycans and their glycopeptides is also challenging because of their different enzymatic efficiencies

Method used

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  • Identification and use of glycopeptides as biomarkers for diagnosis and treatment monitoring
  • Identification and use of glycopeptides as biomarkers for diagnosis and treatment monitoring
  • Identification and use of glycopeptides as biomarkers for diagnosis and treatment monitoring

Examples

Experimental program
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Effect test

example 1

[0097] General approach to biomarker discovery

[0098] In a targeted approach, the target glycoprotein is first identified in a biological sample, and then the peptide fragments are identified and quantified using LC / MS to analyze the site of modification, the nature of the modification, the nature of the modification, and the relative abundance of each modification. The method uses a triple quadrupole (QQQ) mass spectrometer to quantify glycosylated peptide fragments and then analyze their relationship to the subject classification.

[0099] In a non-targeted approach, the glycosylation patterns of all peptide fragments (known and unknown) are analyzed for information on changes in glycosylation patterns in various subjects. Specifically, the up- or down-regulation of glycoproteins is monitored for the classification of subjects. For example, glycoprotein fragments are monitored separately for subjects with a disease or condition versus subjects without the disease or condi...

example 2

[0101] Quantitative analysis of IgG glycopeptides as potential biomarkers for breast cancer

[0102] Plasma samples of breast cancer patients at different stages and a control group corresponding to the age of said patients were analyzed for IgG1, IgG0 and IgG2 glycopeptides, and their ratio changes were compared. Specifically, 20 samples at the stage of carcinoma in situ, 50 samples at the EC1 stage, 138 samples at the EC2 stage, 25 samples at the EC3 stage, 9 samples at the EC4 stage and 73 A control sample matched to their age was used for MRM quantification. Quantitative results such as figure 2 As shown, in the various stages of breast cancer studied in this experiment, the levels of certain IgG1 glycopeptides were increased and the levels of certain IgG1 glycopeptides were decreased compared with the control group. For example, in the various stages of breast cancer studied in this experiment, the IgG1 glycopeptide Al-A11 was monitored; compared with the control group...

example 3

[0104] Quantitative analysis of IgG glycopeptides as potential biomarkers for PSC and PBC

[0105] Analysis of IgG1 and IgG2 glycopeptides in plasma samples from patients with primary sclerosing cholangitis (PSC), patients with primary biliary cirrhosis (PBC), and plasma samples from healthy donors and comparing their glycopeptide ratios The change. Specifically, 100 PBC plasma samples, 76 PSC plasma samples, and 49 healthy donor plasma samples were subjected to MRM quantitative analysis on a QQQ mass spectrometer. from image 3 It can be seen from the quantitative results that some IgG1 glycopeptides were elevated and some IgG1 glycopeptides were decreased in the plasma samples of PBC and PSC patients compared with healthy donors. For example, glycopeptide A was elevated and glycopeptides H, I, and J were decreased in PBC and PSC patients compared with healthy donors. Therefore, glycopeptides A, H, I and J are potential biomarkers for PBC and PSC.

[0106] Similar analyze...

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PUM

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Abstract

Provided herein are methods for identifying new biomarkers for various diseases using proteomics, peptidomics, metabolics, proteoglycomics, glvcomics, mass spectrometry and machine learning. The present disclosure also provides glycopeptides as biomarkers for various diseases such as cancer and autoimmune diseases.

Description

technical field [0001] This patent relates to the field of multi-omics in general, especially glycomics and glycoproteomics, advanced instrument big data, machine learning and artificial intelligence to identify biomarkers for disease diagnosis and treatment monitoring. Background technique [0002] Protein glycosylation and other post-translational modifications play important structural and functional roles in various aspects of human growth and development. Defective protein glycosylation contributes to a variety of diseases. Identifying altered glycosylation at an early stage of disease offers disease-affected subjects the opportunity for earlier detection, intervention, and a greater chance of survival. Currently, there are methods to identify biomarkers of early cancer and to distinguish certain types of cancer from other diseases. These methods include proteomics, peptidomics, metabolomics, glycoproteomics, and glycomics using mass spectrometry (MS). [0003] Altho...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): C12Q1/37G01N33/53G01N33/574G01N33/68
CPCG01N33/57415G01N2400/00G01N33/6842G01N33/6848G01N33/564G01N2800/08G16B20/00G16B40/10G16B40/20G01N33/6857G16B40/00G01N2560/00
Inventor L.M.A.·丹南-里欧A.M.E.S.·卡拉斯科C.R.·贝尔托西C.B.·拉韦利亚
Owner VENN BIOSCIENCES CORP
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