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Gene methylation panel and kit for diagnosing and predicting curative effect and prognosis of colorectal cancer

A colorectal cancer and methylation technology, applied in the field of gene epigenetics, can solve the problems of colorectal cancer detection methods such as convenience in operation, accuracy of results and cost of detection

Pending Publication Date: 2020-02-04
SUN YAT SEN UNIV CANCER CENT
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a gene methylation panel and kit for diagnosing and predicting the curative effect and prognosis of colorectal cancer, so as to solve the problems of the existing colorectal cancer detection methods in terms of ease of operation, accuracy of results, Difficult to take into account issues such as testing costs

Method used

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  • Gene methylation panel and kit for diagnosing and predicting curative effect and prognosis of colorectal cancer
  • Gene methylation panel and kit for diagnosing and predicting curative effect and prognosis of colorectal cancer
  • Gene methylation panel and kit for diagnosing and predicting curative effect and prognosis of colorectal cancer

Examples

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Embodiment 1

[0073] This example discloses a gene methylation panel for diagnosing and predicting the curative effect and prognosis of colorectal cancer. The gene methylation panel is composed of the first group of methylated genes, these methylated genes are MYO1G, BMPR1A , CD6, RBP5, Chr 13:10, LGAP5, ATXN1 and Chr 8:20. This gene methylation panel detects the gene methylation level changes of MYO1G, BMPR1A, CD6, RBP5, Chr 13:10, LGAP5, ATXN1 and Chr 8:20 in the plasma of colorectal cancer patients, and is used to diagnose the occurrence of colorectal cancer .

[0074] This embodiment also discloses the detection method of the above-mentioned gene methylation panel for diagnosing colorectal cancer, comprising the following steps:

[0075] In the first step, ctDNA is extracted from plasma;

[0076]In the second step, the extracted ctDNA is subjected to sulfite conversion, so that unmethylated cytosine in the ctDNA is deaminated and converted into uracil, while the methylated cytosine re...

Embodiment 2

[0092] The difference between this example and Example 1 is that the methylated genes in the gene methylation panel of this example are MYO1G, BMPR1A, CD6, Chr 13:10, LGAP5, ATXN1 and Chr 8:20.

[0093] A diagnostic prediction model was constructed using a gene methylation panel (including 7 methylated genes: MYO1G, BMPR1A, CD6, Chr 13:10, LGAP5, ATXN1, and Chr 8:20) by logistic regression method. Using this model to diagnose colorectal cancer, the sensitivity in the training set is 87.69%, the specificity is 89.91%, and the overall correct rate is 88.94%. This model can very well distinguish colorectal cancer from normal controls in the training data set (AUC=0.956) and validation data set (AUC=0.955) (such as figure 2 , Table 3). It was confirmed that this gene methylation panel can be used to distinguish colorectal cancer patients from normal people.

[0094] Table 3: Sensitivity and specificity results of the gene methylation panel in the training set of Example 2

[0...

Embodiment 3

[0098] The difference between this example and Example 1 is that the methylated genes in the gene methylation panel of this example are MYO1G, BMPR1A, CD6, LGAP5, ATXN1 and Chr 8:20.

[0099] A diagnostic prediction model was constructed using a gene methylation panel (including 6 methylated genes: MYO1G, BMPR1A, CD6, LGAP5, ATXN1, and Chr 8:20) by logistic regression method. Using this model to diagnose colorectal cancer, the sensitivity in the training set is 85.61%, the specificity is 92.14%, and the overall correct rate is 89.27%. This model can very well distinguish colorectal cancer from normal controls in the training data set (AUC=0.954) and validation data set (AUC=0.954) (such as image 3 , Table 4). It was confirmed that this gene methylation panel can be used to distinguish colorectal cancer patients from normal people.

[0100] Table 4: Sensitivity and specificity results of the example three gene methylation panels in the training set

[0101]

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Abstract

The invention discloses a gene methylation panel and kit for diagnosing and predicting the curative effect and prognosis of colorectal cancer. The gene methylation panel comprises a first group of methylation genes and / or a second group of methylation genes, the first group of the methylation genes are selected from one or more of MYO1G, ADAMTS4, BMPR1A, CD6, RBP5, Chr 13:10, LGAP5, ATXN1 and Chr8:20, and the second group of the methylation genes are selected from one or more of MYO1G, GCET2, CALML4, KLF3, and ATXN1. The gene methylation panel and the kit containing the gene methylation panelcan be used for rapid and low-cost early diagnosis, early evaluation and early prevention of the colorectal cancer.

Description

technical field [0001] The invention relates to the technical field of gene epigenetics, in particular to a gene methylation panel and a kit for diagnosing and predicting the curative effect and prognosis of colorectal cancer, and using the gene methylation panel to diagnose intestinal cancer and predict curative effect and recurrence, and methods for predicting bowel cancer prognosis and risk of death. Background technique [0002] As a common malignant tumor, colorectal cancer ranks third among all malignant tumors in my country. The symptoms of colorectal cancer are not obvious at the early stage of the disease, and it is difficult to detect and treat them in time. Therefore, it will be of great significance for the effective treatment of colorectal cancer to detect symptoms and treat symptoms at the early stage of colorectal cancer through technological innovation. [0003] Currently, the detection methods for colorectal cancer mainly include colonoscopy, fecal occult b...

Claims

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Application Information

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IPC IPC(8): C12Q1/6886G16H50/70G16H50/20
CPCC12Q1/6886G16H50/20G16H50/70C12Q2600/154C12Q2600/118
Inventor 徐瑞华骆卉妍赵齐韦玮
Owner SUN YAT SEN UNIV CANCER CENT
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