Microbial markers for predicting risk of colorectal cancer and application thereof

A colorectal cancer and marker technology, applied in the field of microorganisms, can solve the problems of unfavorable widespread promotion and application, difficulty in data acquisition, increased cost, and high detection cost, and achieve increased patient compliance, good application prospects and practical significance, and sensitivity. high effect

Inactive Publication Date: 2021-04-06
天津奇云诺德生物医学有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, it should be noted that although the multiple input data used in this invention patent include multiple dimensions, the difficulty and cost of data acquisition are also multiplied. For example, the hemoglobin content requires a special fecal occult blood detection method or kit for detection. Gene mutations also re

Method used

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  • Microbial markers for predicting risk of colorectal cancer and application thereof
  • Microbial markers for predicting risk of colorectal cancer and application thereof
  • Microbial markers for predicting risk of colorectal cancer and application thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0054] Embodiment 1, the extraction of DNA sample

[0055] (1) Collect fresh stool samples from the subjects, freeze them immediately, and put them on ice before the experiment;

[0056] (2) Weigh 200 mg of fixed feces into 2 mL centrifuge tubes, add 800 μL of fecal DNA extraction buffer, shake and mix well for 5 min, and centrifuge at 1800 g for 1 min;

[0057] (3) Take 50 μL of the suspension into a 1.5 mL centrifuge tube, add 800 μL of lysate, vortex and mix, lyse at 70°C for 5 min, centrifuge for 5 min, and transfer the supernatant to a clean 1.5 mL centrifuge tube;

[0058] (4) Add 20 μL of well-mixed magnetic beads, vortex for 20 seconds, let stand at room temperature for 4 minutes, place on a magnetic rack, let stand for 20 seconds, and absorb the supernatant;

[0059] (5) Add 500 μL of washing solution Ⅰ, vortex for 20 seconds, mix the magnetic beads, place them on a magnetic rack, let them stand for 20 seconds, and discard the supernatant;

[0060] (6) Add 750 μL of...

Embodiment 2

[0063] Example 2, Quantitative Detection of Microbial Markers

[0064] The quantitative detection of microbial markers adopts the Taqman qPCR method, and the probes and primers used are shown in Table 1:

[0065] Table 1. Probes and primers for microbial markers and internal controls

[0066]

[0067]

[0068] The specific steps of this embodiment are described below taking the TaqMan Master Mix kit product of Suzhou Xinhai Biotechnology Co., Ltd. as an example:

[0069] (1) Prepare the PCR reaction solution according to the qPCR reaction system shown in Table 2;

[0070] Table 2. qPCR reaction system

[0071]

[0072] (2) After the PCR reaction solution is prepared, mix it upside down and centrifuge it, dispense it into a 96-well PCR reaction plate, centrifuge it at 2000g for 2 minutes, seal it and place it in a PCR machine for reaction;

[0073] (3) Use the two-step PCR reaction method to carry out qPCR reaction, and set the program as shown in Table 3;

[0074]...

Embodiment 3

[0077] Example 3, the training of colorectal cancer risk assessment calculation model

[0078] The establishment of the colorectal cancer risk assessment calculation model uses the random forest algorithm to train the abundance information of the above three microbial markers and their grouping information in the collected samples of 513 healthy individuals and 435 colorectal cancer patients and internal data Test, and finally select the optimal model from multiple training models as the follow-up colorectal cancer risk calculation model, the specific steps are as follows:

[0079] Step 1) Collect 513 fresh stool samples from healthy individuals and 435 fresh stool samples from colorectal cancer patients;

[0080] Step 2) extracting and purifying DNA fragments from the stool sample of the individual described in step 1);

[0081] Step 3) Use the TaqMan probe method for qPCR real-time quantification, and detect step 2) the gene content of the target gene fragment of the microbia...

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Abstract

The invention provides microbial markers for predicting the risk of colorectal cancer and application of the microbial marker. The microbial markers comprise the following three types: fusobacterium nucleatum, parvimonas micra and solobacter moorei. The abundance of the above three bacteria in a colorectal cancer patient is remarkably increased; corresponding microbial marker expression abundance values are obtained through an experimental method and input into a machine learning model established by the invention; and a risk value is given after the model conducts comprehensive calculation, so colorectal cancer is diagnosed in an assisted manner. The microbial markers provided by the invention are high in sensitivity and good in specificity, have the potential of serving as colorectal cancer markers, and provide a means for non-invasive auxiliary diagnosis of colorectal cancer.

Description

technical field [0001] The invention relates to the field of microorganisms, in particular to a microbial marker for predicting the risk of colorectal cancer and its application. Background technique [0002] Colorectal cancer (Colorectal cancer) is the third most frequently occurring cancer in my country after lung cancer and gastric cancer. According to the statistics of the 2018 "Expert Consensus on Early Diagnosis and Screening Strategies for Colorectal Tumors in China", colorectal cancer has become one of the most common cancers in my country. It is one of the malignant tumors with the fastest growing incidence rate, with 429,200 new cases and 281,000 deaths every year. The situation of prevention and control is severe. The incidence of colorectal cancer is related to factors such as age and environment. About 90% of patients are over 40 years old. However, in recent years, with the improvement of people's living standards and changes in eating habits, the proportion of ...

Claims

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Application Information

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IPC IPC(8): C12Q1/689C12Q1/6851C12Q1/06G16H50/30G16H50/20G16B40/00G16B30/00G16B20/00G06K9/62C12R1/01
CPCC12Q1/689C12Q1/6851C12Q1/06G16H50/30G16H50/20G16B40/00G16B30/00G16B20/00G01N2800/7028G01N2333/195G06F18/24323C12Q2531/113C12Q2561/101
Inventor 罗奇斌申玉林任毅廖胜光
Owner 天津奇云诺德生物医学有限公司
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