WO2018124735A1 - Method for diagnosing colon tumor via bacterial metagenomic analysis - Google Patents

Abstract

The present invention relates to a method for predicting the incidence of a colon tumor, such as a colon polyp and colon cancer, and a causative factor thereof through metagenomic analysis of a bacterium-derived vesicle present in a human body-derived substance. More particularly, the present invention relates to a method for diagnosing a causative factor of a colon tumor and the risk of the incidence thereof by sequencing a metagenome present in a bacterium-derived vesicle present in excrement or urine. There are trillions of bacteria in an intestine, and the bacteria secrete vesicles out of the cells thereof for the purpose of information exchange. The bacteria are not absorbed into epithelial cells in a colon, but the vesicles secreted therefrom pass through the mucous membrane, are absorbed into the colonic epithelial cells, are distributed throughout the body via blood, and then are excreted through a liver and a kidney. The bacteria-derived vesicles may increase or decrease the occurrence of inflammation and cancer, and the present invention can be useful as a method for diagnosing the risk of the incidence of a colon tumor or a causative factor thereof by sequencing a genetic metagenome of a bacterium-derived vesicle present in a human body-derived substance. Further, an early diagnosis can still be made even after the incidence of a colon polyp or the onset of colon cancer, and the incidence of colon cancer can be lowered, and the treatment effect can be enhanced.

Description

Colon Tumor Diagnosis Method Using Bacterial Metagenome Analysis

The present invention relates to a method for diagnosing colon tumors by analyzing bacterial metagenome, and more specifically, by performing bacterial metagenomic analysis using a sample derived from a subject, by analyzing the increase or decrease in the content of specific bacterial-derived extracellular vesicles. And a method for diagnosing colorectal tumors such as colorectal cancer.

Colon cancer (colon cancer) or colorectal cancer is a malignant tumor of the cecum, colon and rectum that occurs on the mucous membrane of the innermost surface of the large intestine. According to the announcement in 2006, the second most common cancer after stomach cancer in Korea, the frequency of eating habits has been increasing rapidly as westernized aspects of the diet recently, and the mortality rate of colorectal cancer in recent 10 years is about 80%. The rate of increase is increasing. The age of onset occurs most frequently in the sixties, and by site, it occurs slightly more in the rectum than in the colon. Colorectal cancer can occur at any age, but over 90% of people with colorectal cancer are older than 40 years of age, and their incidence doubles every 10 years.

All colon cancers are known to originate from colon polyp or colon adenoma. Polyps are initially an abnormal growth of the epithelium in the lining of the large intestine, protruding and appearing in 15-20% of adults. It is a common disease. In addition to colorectal polyps, family members of colorectal cancer are at increased risk for colon cancer, even if they have had ulcerative colitis for a long time. In addition, colorectal cancer is a representative cancer known to be associated with food, and is known to cause low intake of fiber, high intake of animal fat, or excessive intake of refined sugar (sugar) due to westernization of diet. .

Early colorectal cancer does not show any particular symptoms, but even without symptoms, invisible bowel bleeding may cause anemia due to blood loss, and sometimes anorexia and weight loss may occur. If the cancer is advanced, changes in bowel habits such as stomach ache, diarrhea or constipation may occur, rectal bleeding from the anus may occur, and the blood may appear bright red or black. If colon cancer has progressed, the lumps that were not usually touched on the stomach may be touched. The most important symptoms to look for are changes in bowel habits, bloody stools, pain and anemia, especially when these changes occur in adults over 40 years of age.

To confirm colon cancer, cancer cells can be detected by biopsy through colonoscopy. Most colon cancers are asymptomatic and therefore difficult to diagnose. Currently, there is no way to predict colon cancer in a non-invasive way. As conventional diagnostic methods are often found when solid cancers such as colorectal cancer are advanced, it is necessary to predict colon cancer and causative factors in advance in order to prevent medical costs and death due to colorectal cancer. Providing a method of prevention is an effective way.

On the other hand, the symbiosis of the human body reaches 100 trillion times 10 times more than human cells, the number of genes of the microorganism is known to be more than 100 times the number of human genes. Microbiota (microbiota or microbiome) refers to a microbial community including bacteria, archaea and eukarya that exist in a given settlement.Intestinal microbiota is an important role in human physiology. It is known to have a great effect on human health and disease through interaction with human cells. The symbiotic bacteria secrete nanometer-sized vesicles to exchange information about genes and proteins in other cells. The mucous membrane forms a physical protective film that particles larger than 200 nanometers (nm) in size can't pass through, so that the symbiotic bacteria cannot pass through the mucosa, but bacterial-derived vesicles are usually less than 100 nanometers in size. It freely speaks to the mucous membrane and is absorbed by our body.

Metagenomics, also called environmental genomics, can be said to be an analysis of metagenomic data obtained from samples taken from the environment (Korean Patent Publication No. 2011-0073049). Recently, it has become possible to list the bacterial composition of the human microflora by a method based on 16s ribosomal RNA (16s rRNA) sequencing. Next generation sequencing of 16s rDNA sequencing gene of 16s ribosomal RNA is performed. , NGS) platform to analyze. However, in the development of colorectal tumors, bacteria and bacteria-derived vesicles are separated from human-derived stool such as stool, and meta-genomic analysis of colon-derived vesicles is identified to identify the causative factors of colon tumors such as colon polyps and colon cancer. No method of diagnosing this has been reported.

In order to diagnose colon tumors such as colorectal polyps and colorectal cancer, the present inventors extracted a gene from bacterial vesicles using urine and stool, which are samples derived from a subject, and performed a metagenome analysis on the colon polyps and colon. Bacterial-derived extracellular vesicles that can act as causative factors of colorectal tumors, such as cancer, have been identified, and thus the present invention has been completed.

Accordingly, an object of the present invention is to provide an information providing method for diagnosing colon tumors through metagenomic analysis of genes present in bacterial extracellular vesicles.

However, the technical problem to be achieved by the present invention is not limited to the above-mentioned problem, another task that is not mentioned will be clearly understood by those skilled in the art from the following description.

In order to achieve the object of the present invention as described above, the present invention provides a method for providing information for diagnosing colon tumor, comprising the following steps:

(a) extracting DNA from extracellular vesicles isolated from a subject sample;

(b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

(c) comparing the increase and decrease of the bacterial-derived extracellular vesicles in the normal-derived colorectal cancer-derived sample by sequencing the PCR product; or

Comparing the increase and decrease of the bacterial-derived extracellular vesicles in the colon-derived patient and the colon cancer-derived sample by sequencing the PCR product; or

Comparing the increase and decrease of the content of bacterial-derived extracellular vesicles in the sample derived from normal people and colon polyps through the sequencing of the PCR product.

In addition, the present invention provides a method for diagnosing colon tumor, comprising the following steps:

(a) extracting DNA from extracellular vesicles isolated from a subject sample;

(b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

(c) comparing the increase and decrease of the bacterial-derived extracellular vesicles in the normal-derived colorectal cancer-derived sample by sequencing the PCR product; or

Comparing the increase and decrease of the bacterial-derived extracellular vesicles in the colon-derived patient and the colon cancer-derived sample by sequencing the PCR product; or

Comparing the increase and decrease of the content of bacterial-derived extracellular vesicles in the sample derived from normal people and colon polyps through the sequencing of the PCR product.

In addition, the present invention provides a method for predicting the risk of developing colon tumor, comprising the following steps:

(a) extracting DNA from extracellular vesicles isolated from a subject sample;

(b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

(c) comparing the increase and decrease of the bacterial-derived extracellular vesicles in the normal-derived colorectal cancer-derived sample by sequencing the PCR product; or

Comparing the increase and decrease of the bacterial-derived extracellular vesicles in the colon-derived patient and the colon cancer-derived sample by sequencing the PCR product; or

Comparing the increase and decrease of the content of bacterial-derived extracellular vesicles in the sample derived from normal people and colon polyps through the sequencing of the PCR product.

In one embodiment of the present invention, colorectal cancer may be diagnosed by comparing the increase and decrease of the bacterial-derived extracellular vesicles in a sample derived from normal and colon cancer patients by sequencing the PCR product in step (c). have.

In one embodiment of the present invention, in the step (c) Deferribacteres, Tenericutes, Actinobacteria, Acidobacteria, Armatimonadetes, Planctomycetes, Fusobacteria, Proteobacteria, and Euryarchaeota extracellular vesicles derived from (phylum) bacteria ,

One or more species of cells derived from the group consisting of Deferribacteres, Mollicutes, 4C0d-2, Bacilli, Alphaproteobacteria, Saprospirae, Fimbriimonadia, Acidobacteria-6, Solibacteres, Coriobacteriia, Oscillatoriophycideae, Fusobacteriia, Gammaproteobacteria, Clostridia, and Methanobacteria Out parcel,

RF32, YS2, Deferribacterales, Turicibacterales, RF39, Oceanospirillales, Rhizobiales, Lactobacillales, Rhodobacterales, Saprospirales, Sphingomonadales, Fimbriimonadales, iii1-15, Solibacterales, Coriobacteriales, Chroococcales, Fusobacteriales, Bd One or more order bacterial derived extracellular vesicles selected from the group consisting of:

Peptococcaceae, Deferribacteraceae, Turicibacteraceae, Halomonadaceae, Clostridiaceae, Prevotellaceae, Peptostreptococcaceae, Rhodobacteraceae, Nocardioidaceae, Sphingomonadaceae, Bartonellaceae, Cellulomonadaceae, Lactobacillaceae, Rhizobiaceae, Fimbriimonadaceae, Dermacoccaceae, Leptotrichiaceae, Coriobacteriaceae, Xenococcaceae, Aeromonadaceae, Geodermatophilaceae, Bdellovibrionaceae, Moraxellaceae, Pseudomonadaceae, Streptococcaceae, One or more family or small family cells from the group consisting of Veillonellaceae, Bacteroidaceae, Aerococcaceae, Comamonadaceae, Paraprevotellaceae, Christensenellaceae, Ruminococcaceae, Corynebacteriaceae, Gordoniaceae, Mycobacteriaceae, Desulfovibrionaceae, Alcaligenaceae, Barnesiellaceae, Methanobacteriaceae, and Rikenellaceae

rc4-4, Proteus, Catenibacterium, Mucispirillum, Eubacterium, Turicibacter, Alloiococcus, Halomonas, Prevotella, Dialister, Anaerostipes, SMB53, Faecalibacterium, Blautia, Capnocytophaga, Sphingomonas, Lactobacillus, Fimbriicus, Achromobacus, Achromobacsium, Achromobacsium Bdellovibrio, Alkanindiges, Roseateles, Shuttleworthia, Rhizobium, Morganella, Acinetobacter, Pseudomonas, Enterococcus, Lactococcus, Coprococcus, Bacteroides, Dorea, Streptococcus, Lachnospira, Ruminococcus, Corynebacteria, Comamocobacterium, Comamocobacterium, Lacosebacteria, Mycobacterium terpenia The increase or decrease in the content of one or more genus bacterial-derived extracellular vesicles selected from the group consisting of Sutterella, Virgibacillus, Eggerthella, Citrobacter, Roseomonas, Serratia, Methanobrevibacter, and Bilophila can be compared.

In one embodiment of the present invention, in the step (c), the colorectal cancer through the step of comparing the increase and decrease of the content of bacterial-derived extracellular vesicles in the colon-derived patient and colorectal cancer-derived sample by sequencing the PCR product Diagnosis can be made.

In one embodiment of the present invention, in step (c) Spirochaetes phylum bacteria-derived extracellular vesicles,

One or more class bacterial-derived extracellular vesicles selected from the group consisting of Spirochaetes, and Acidobacteria-6,

One or more order bacterial extracellular vesicles selected from the group consisting of Spirochaetales, and Myxococcales,

Extracellular vesicles derived from one or more family bacteria selected from the group consisting of Spirochaetaceae, and S24-7, or

The increase or decrease in the content of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of Treponema, Dialister, Oscillospira, and Eubacterium can be compared.

In one embodiment of the present invention, in step (c), the colon polyps are diagnosed by comparing the increase or decrease of the bacterial-derived extracellular vesicles in the sample from the normal and colon polyps patient by sequencing the PCR product. Can be.

In one embodiment of the present invention, in step (c), at least one phylum bacteria-derived extracellular vesicles selected from the group consisting of Actinobacteria, Proteobacteria, and Euryarchaeota,

One or more class bacterial-derived extracellular vesicles selected from the group consisting of Betaproteobacteria, Solibacteres, Gammaproteobacteria, Clostridia, Methanobacteria, and 4C0d-2,

One or more order bacterial-derived extracellular vesicles selected from the group consisting of Burkholderiales, Sphingomonadales, Solibacterales, Stramenopiles, Pseudomonadales, Clostridiales, Oceanospirillales, Desulfovibrionales, and Methanobacteriales,

Group consisting of Rhizobiaceae, Sphingomonadaceae, Exiguobacteraceae, Moraxellaceae, Pseudomonadaceae, Streptococcaceae, Peptostreptococcaceae, Comamonadaceae, Veillonellaceae, Bacteroidaceae, Paraprevotellaceae, Ruminococcaceae, Corynebacteriaceae, Christensenellaceae, Odoribacteraceae, Deofolioaceae, Deofolioaceae Extracellular vesicles derived from abnormal families, or

Sphingomonas, Alkanindiges, Roseateles, Rhizobium, Morganella, Proteus, Exiguobacterium, Acinetobacter, Pseudomonas, SMB53, Lactococcus, Coprococcus, Streptococcus, Bacteroides, Ruminococcus, Corynebacterium, Odoribacter, Clonastriia Triacerocitra, Clonastriia Viracerosia, Clonastriia psi The increase or decrease in the content of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of Dialister, Phascolarctobacterium, Sutterella, Halomonas, Roseomonas, and Methanobrevibacter can be compared.

In one embodiment of the present invention, the subject sample may be feces or urine.

Extracellular vesicles secreted by the bacteria present in the environment can be absorbed into the body and directly affect inflammation and cancer development, and colon polyps and colorectal cancer are difficult to diagnose effectively because they are difficult to diagnose early. Predicting the risk of colon tumors such as colorectal polyps and colorectal cancer through metagenomic analysis of bacterial or bacterial-derived extracellular vesicles using a human-derived sample according to the present invention, early diagnosis and prediction of risk groups of colon tumors and appropriate management By delaying the onset time or preventing the onset, and after the onset can be diagnosed early can reduce the incidence of colon tumors and increase the treatment effect. In addition, metagenome analysis predicts causative factors in patients diagnosed with colorectal polyps or colorectal cancer, thereby avoiding exposure to causative factors and improving colon polyps and colorectal cancer, or preventing recurrence.

Figure 1 is for evaluating the distribution of bacteria-derived extracellular vesicles in the body, Figure 1a after the administration of oral intestinal bacteria (Bacteria) and bacteria-derived vesicles (EV) in the mouth hourly (0, 5min, 3h, 6h, and 12h) is a photograph taken of their distribution, Figure 1b is a 12 hours after oral administration of intestinal bacteria (Bacteria) and bacteria-derived extracellular vesicles (EV) to the urine and various organs (heart, Lung, liver, kidney, spleen, adipose tissue, and muscles), and the photographs of the distribution of the bacterial and extracellular vesicles.

Figure 2 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the phylum level by separating bacterial-derived vesicles from colon cancer patients and normal feces.

FIG. 3 shows the distribution of bacterial-derived vesicles (EVs) with significant diagnostic performance at a class level by separating bacterial-derived vesicles from colon cancer patients and normal stool.

4 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the order level by separating the bacteria-derived vesicles from colon cancer patients and normal stool.

5 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level by separating bacteria-derived vesicles from colon cancer patients and normal stool.

6 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level by separating bacterial-derived vesicles from colon cancer patients and normal stool.

7 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the phylum level by separating the bacteria-derived vesicles from colon cancer patients and normal urine, and performing a metagenome analysis.

FIG. 8 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at a class level by separating bacterial-derived vesicles from colorectal cancer patients and normal urine.

9 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the order level by separating the bacteria-derived vesicles in colon cancer patients and normal urine, and performing a metagenome analysis.

FIG. 10 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level after separation of bacteria-derived vesicles from colon cancer patients and normal urine.

11 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level after separating the bacteria-derived vesicles in colon cancer patients and normal urine.

7 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the phylum level by separating the bacteria-derived vesicles in the urine of colon cancer patients and colon polyps patients .

8 is a result showing the distribution of bacteria-derived vesicles (EVs) of significant diagnostic performance at the class level by separating the bacteria-derived vesicles in the urine of colorectal cancer patients and colon polyps patients, performing a metagenome analysis .

9 is a result showing the distribution of bacteria-derived vesicles (EVs) of significant diagnostic performance at the order (neck) by separating the bacteria-derived vesicles in the urine of colorectal cancer patients and colon polyps patients, performing a metagenome analysis .

10 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level by separating the bacteria-derived vesicles in the urine of colorectal cancer patients and colon polyps patients, and performing a metagenome analysis. .

11 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level after separating the bacteria-derived vesicles in the urine of patients with colorectal cancer and colon polyps. .

12 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the phylum level by separating the bacteria-derived vesicles in the stool of colon cancer patients and colon polyps patients .

13 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the class level by separating the bacteria-derived vesicles in the stool of colon cancer patients and colon polyps patients, and performing a metagenomic analysis .

14 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the order (neck) after separating the bacteria-derived vesicles in the stool of colon cancer patients and colon polyps patients .

15 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level by separating the bacteria-derived vesicles from the stool of colorectal cancer patients and colon polyps patients, performing a metagenome analysis .

16 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level after separation of bacteria-derived vesicles in the bowel cancer patients and colon polyps patients stool. .

17 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the order level by separating the bacteria-derived vesicles in the urine of colorectal cancer patients and colon polyps patients after performing a metagenome analysis .

18 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level after separation of bacteria-derived vesicles in urine of colorectal cancer patients and colon polyps. .

19 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the phylum level by separating bacterial-derived vesicles from colon polyps and normal feces.

20 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the class level by separating bacterial-derived vesicles from colon polyps and normal stool.

21 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the order level by separating bacterial-derived vesicles from colon polyps and normal feces, and performing a metagenome analysis.

22 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level by separating bacteria-derived vesicles from colon polyps and normal stool.

23 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level after separating the bacteria-derived vesicles from colon polyps and normal feces.

Figure 24 shows the distribution of bacterial-derived vesicles (EVs) with significant diagnostic performance at the phylum level by separating bacterial-derived vesicles from colon polyps and normal urine.

FIG. 25 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at a class level after separation of bacterial-derived vesicles from colon polyps and normal urine.

FIG. 26 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the neck level after separation of bacteria-derived vesicles from colon polyps and normal urine.

FIG. 27 shows the distribution of bacterial-derived vesicles (EVs) with significant diagnostic performance at the family level after separation of bacterial-derived vesicles from colon polyps and normal urine.

FIG. 28 shows the distribution of bacterial-derived vesicles (EVs) with significant diagnostic performance at genus level after isolation of bacterial-derived vesicles from colon polyps and normal urine.

The present invention relates to a method for diagnosing colorectal tumors such as colon polyps and colorectal cancer through bacterial metagenome analysis, and the present inventors extract genes from extracellular vesicles derived from bacteria using a sample derived from a subject, Bacterial-derived extracellular vesicles that could act as causative factors of colorectal tumors such as colon polyps and colorectal cancer were identified.

Thus, the present invention comprises the steps of (a) extracting DNA from the extracellular vesicles isolated from the subject sample;

(b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

(c) comparing the increase and decrease of the bacterial-derived extracellular vesicles in the normal-derived colorectal cancer-derived sample by sequencing the PCR product; or

Comparing the increase and decrease of the bacterial-derived extracellular vesicles in the colon-derived patient and the colon cancer-derived sample by sequencing the PCR product; or

It provides an information providing method for diagnosing colon tumors comprising comparing the increase and decrease of the content of bacterial-derived extracellular vesicles in a sample derived from normal people and colon polyps through sequencing of the PCR product.

As used herein, the term "diagnosed colorectal cancer" means to determine whether or not colon cancer is likely to develop, whether or not colon cancer is relatively high, or whether colorectal cancer has already occurred in a patient. . The method of the present invention can be used to prevent or delay the onset of the disease through special and appropriate management as a patient at high risk of developing colorectal cancer for any particular patient. In addition, the methods of the present invention can be used clinically to determine treatment by early diagnosis of colon cancer and selecting the most appropriate treatment regimen.

As used herein, the term "diagnosing colon polyps" means determining whether a colon polyp is likely to develop, whether the colon polyp is relatively high, or whether a polyp has already occurred. . The method of the present invention can be used to prevent or delay the onset of the disease through special and appropriate management as a patient at high risk of developing colon polyps for any particular patient. In addition, the methods of the present invention can be used clinically to determine treatment by early diagnosis of colon polyps and selecting the most appropriate treatment regimen.

The term "metagenome" used in the present invention, also referred to as "metagenome", refers to the total of the genome including all viruses, bacteria, fungi, etc. in an isolated area such as soil, animal intestine, It is mainly used as a concept of genome explaining the identification of many microorganisms at once using sequencer to analyze microorganisms which are not cultured. In particular, metagenome does not refer to one species of genome or genome, but refers to a kind of mixed dielectric as the genome of all species of one environmental unit. This is a term from the point of view of defining a species in the course of the evolution of biology in terms of functional species as well as various species that interact with each other to create a complete species. Technically, rapid sequencing is used to analyze all DNA and RNA, regardless of species, to identify all species in one environment, and to identify interactions and metabolism. In the present invention, metagenome analysis was preferably performed using bacterial-derived extracellular vesicles isolated from serum.

In the embodiment of the present invention, meta-genomic analysis was performed on genes present in the extracellular vesicles in feces and urine of normal people, colon polyps, and colon cancer patients. Analyzes at the order, family, and genus levels, respectively, identified bacterial vesicles that could actually cause colon cancer and colon polyps development.

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived vesicles metagenome present in the stool at the gate level, Deferribacteres, Tenericutes, Actinobacteria, Acidobacteria, Armatimonadetes, Planctomycetes, and Fusobacteria door-derived vesicles derived from colon cancer patients There was a significant difference between and normal (see Example 4).

More specifically, in one embodiment of the present invention, the bacterium-derived vesicle metagenome present in the feces at the river level, Deferribacteres, Mollicutes, 4C0d-2, Bacilli, Alphaproteobacteria, Saprospirae, Fimbriimonadia, Acidobacteria-6, Solibacteres, Vesicles derived from Coriobacteriia, Oscillatoriophycideae, and Fusobacteriia bacterium showed significant differences between colon cancer patients and normal individuals (see Example 4).

More specifically, in one embodiment of the present invention, the result of analyzing the bacterial-derived vesicle metagenome present in the stool at the neck level, RF32, YS2, Deferribacterales, Turicibacterales, RF39, Oceanospirillales, Rhizobiales, Lactobacillales, Rhodobacterales, Saprospirales, Sphingomonadales, Fimbriimonadales, iii1-15, Solibacterales, Coriobacteriales, Chroococcales, Fusobacteriales, and Bdellovibrionales neck bacterial-derived vesicles showed significant differences between colon cancer patients and normal individuals (see Example 4).

More specifically, in one embodiment of the present invention, the bacterium-derived vesicles metagenome present in the feces at an excessive level, Peptococcaceae, Deferribacteraceae, Turicibacteraceae, Halomonadaceae, Clostridiaceae, Prevotellaceae, Peptostreptococcaceae, Rhodobacteraceae, Nocardioidaceae, Sphellomoaceae, Barton Cellulomonadaceae, Lactobacillaceae, Rhizobiaceae, Fimbriimonadaceae, Dermacoccaceae, Leptotrichiaceae, Coriobacteriaceae, Xenococcaceae, Aeromonadaceae, Geodermatophilaceae, and Bdellovibrionaceae were significantly different between colon cancer patients and normal colon cancer patients (see Example 4).

More specifically, in one embodiment of the present invention, bacteria-derived vesicle metagenome present in the feces at the genus level, rc4-4, Proteus, Catenibacterium, Mucispirillum, Eubacterium, Turicibacter, Alloiococcus, Halomonas, Prevotella, Dialister, Anaerostipes, SMB53, Faecalibacterium, Blautia, Capnocytophaga, Sphingomonas, Lactobacillus, Fimbriimonas, Dermacoccus, Achromobacter, Novosphingobium, Sneathia, Agrobacterium, Blastomonas, Bdellovibrio, Alkanindiges, Roseateles, and the subcutaneous intestines of the genus There was a difference (see Example 4).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived vesicles metagenome present in the urine at the gate level, there was a significant difference between the proteobacteria and the Euryarchaeota door bacteria-derived vesicles between colon cancer patients and normal people ( See Example 5).

More specifically, in one embodiment of the present invention, as a result of analysis of the vesicle metagenome derived from bacteria present in the urine, there was a significant difference between Gammaproteobacteria, Clostridia, and Methanobacteria river bacterial vesicles between colon cancer patients and normal people. (See Example 5).

More specifically, in an embodiment of the present invention, the bacterium-derived vesicles metagenome present in the urine was analyzed at the neck level. There was a significant difference between cancer patients and normal subjects (see Example 5).

More specifically, in one embodiment of the present invention, the bacteria-derived vesicles metagenome present in the urine at an excessive level, Moraxellaceae, Pseudomonadaceae, Streptococcaceae, Turicibacteraceae, Veillonellaceae, Bacteroidaceae, Aerococcaceae, Comamonadaceae, Clostridiaceae, Paraprevotellaceae, Christensenellaceae, Ruminococcaceae, Corynebacteriaceae, Gordoniaceae, Mycobacteriaceae, Desulfovibrionaceae, Halomonadaceae, Alcaligenaceae, Barnesiellaceae, Methanobacteriaceae, and Rikenellaceae and bacterial-derived vesicles showed significant differences between colon cancer patients and normal individuals (see Example 5).

More specifically, in one embodiment of the present invention, the bacteria-derived vesicle metagenome present in the urine at the genus level, Rhizobium, Proteus, Morganella, Acinetobacter, Pseudomonas, SMB53, Enterococcus, Lactococcus, Turicibacter, Coprococcus, Bacteroides, Dorea, Streptococcus, Lachnospira, Ruminococcus, Corynebacterium, Comamonas, Gordonia, Paraprevotella, Mycobacterium, Roseburia, Dialister, Slackia, Escherichia, Phascolarctobacterium, Sutterella, Virgibacillus, Eggerthella, Halomonasoc, Citrobacteriococcus, Miobacteriumobacero Derived vesicles were significantly different between colorectal cancer patients and normal subjects (see Example 5).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived vesicle metagenome present in the stool at the gate level, there was a significant difference between the colon cancer patients and colon polyps patients in the spirochaetes-door bacteria-derived vesicles (implementation See example 6.)

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived vesicle metagenome present in the stool at the river level, the vesicles derived from Spirochaetes, and Acidobacteria-6 strong bacteria were significant between colon cancer patients and colon polyps patients. There was a difference (see Example 6).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacterial-derived vesicles metagenome present in the stool at the neck level, there was a significant difference between the colon cancer patients and colonic polyps in the spirochaetales neck bacteria-derived vesicles. See example 6.)

More specifically, in an embodiment of the present invention, as a result of analyzing the bacteria-derived vesicles metagenome present in the feces at an excessive level, Spirochaetaceae, and S24-7 and bacteria-derived vesicles were significant between colon cancer patients and colon polyps patients. There was a difference (see Example 6).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived vesicle metagenome in the feces at the genus level, Treponema, Dialister, and Oscillospira bacteria-derived vesicles significant between colon cancer patients and colon polyps patients There was a difference (see Example 6).

More specifically, in one embodiment of the present invention, as a result of neck analysis of bacterial vesicles metagenome present in urine, there was a significant difference between Mycococcales neck bacteria-derived vesicles between colon cancer patients and colon polyps patients (execution See Example 7).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived vesicle metagenome present in the urine at the genus level, Eubacterium neck bacteria-derived vesicles had a significant difference between colon cancer patients and colon polyps patients (execution See Example 7).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived vesicle metagenome present in the stool at the gate level, there was a significant difference between the colon-derived and normal people with Actinobacteria vesicle-derived vesicles (Example 8 Reference).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived vesicle metagenome present in the feces at the river level, there was a significant difference between the beta-proteobacteria, and Solibacteres-derived bacteria-derived vesicles between colon polyps and normal people ( See Example 8).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacterial-derived vesicle metagenome present in the stool at the neck level, Burkholderiales, Sphingomonadales, and Solibacterales neck bacteria-derived vesicles were significantly different between colonic patients and normal people (See Example 8).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived vesicle metagenome present in the feces at the excessive level, there was a significant difference between Rhizobiaceae, and Sphingomonadaceae and bacteria-derived vesicles between colon polyps and normal people ( See Example 8).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived vesicles metagenome present in the feces at the genus level, Sphingomonas, Alkanindiges, and Roseateles bacteria-derived vesicles significant differences between the colon polyps and normal people (See Example 8).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived vesicles metagenome in the urine at the gate level, there was a significant difference between the proteobacteria and Euryarchaeota door bacteria-derived vesicles between the colon polyp and the normal ( See Example 9).

More specifically, in one embodiment of the present invention, the bacterium-derived vesicle metagenome present in the urine, as a result of the analysis, Gammaproteobacteria, Clostridia, Methanobacteria, and 4C0d-2 strong bacteria-derived vesicles between the colon polyps and normal people There was a significant difference (see Example 9).

More specifically, in an embodiment of the present invention, the bacterial-derived vesicle metagenome present in the urine, as a result of neck analysis, Stramenopiles, Pseudomonadales, Clostridiales, Oceanospirillales, Desulfovibrionales, and Methanobacteriales vesicles derived from the neck bacteria and normal colon colon patients There was a significant difference between them (see Example 9).

More specifically, in one embodiment of the present invention, the bacterium-derived vesicle metagenome present in the urine at an exaggerated level, Exiguobacteraceae, Moraxellaceae, Pseudomonadaceae, Rhizobiaceae, Streptococcaceae, Peptostreptococcaceae, Comamonadaceae, Veillonellaceae, Bacteroidaceae, Paraprevotellaceae, Ruminococcaceae Corynebacteriaceae, Christensenellaceae, Odoribacteraceae, Desulfovibrionaceae, Halomonadaceae, Alcaligenaceae, Barnesiellaceae, Methanobacteriaceae, and Rikenellaceae showed significant differences between colonic and normal patients (see Example 9).

More specifically, in one embodiment of the present invention, the bacteria-derived vesicle metagenome present in the urine at the genus level, Rhizobium, Morganella, Proteus, Exiguobacterium, Acinetobacter, Pseudomonas, SMB53, Lactococcus, Coprococcus, Streptococcus, Bacteroides, Differences between the normal vesicles of the genus of the genus of the genus of the genus of the strains of the genus (See Example 9).

The present invention, through the results of the above embodiment, by performing a metagenomic analysis on the bacterial-derived extracellular vesicles isolated from feces and urine bacteria significantly changed in colorectal cancer patients compared to normal and colon polyps patients Derived vesicles were identified, and metagenome analysis confirmed that colon cancer can be diagnosed by analyzing the increase or decrease in the content of bacterial derived vesicles at each level.

In addition, the present invention is a bacterial-derived vesicle with a significantly changed content in colorectal patients compared to the normal by performing a metagenome analysis on the bacterial-derived extracellular vesicles isolated from feces and urine through the results as described above The metagenomic analysis confirmed that colon polyps could be diagnosed by analyzing the increase and decrease of the content of bacterial-derived vesicles at each level.

Hereinafter, preferred examples are provided to aid in understanding the present invention. However, the following examples are merely provided to more easily understand the present invention, and the contents of the present invention are not limited by the following examples.

EXAMPLE

Example 1 Analysis of Uptake, Distribution, and Excretion of Intestinal Bacteria and Bacterial-Derived Vesicles

In order to evaluate whether the intestinal bacteria and bacteria-derived vesicles are absorbed systemically through the gastrointestinal tract, experiments were performed as follows. Fluorescently labeled enterobacteriaceae and enteric bacteria-derived vesicles were administered to the gastrointestinal tract at doses of 50 μg, respectively, and the fluorescence was measured after 0, 5, 3, 6 and 12 hours. As a result of observing the entire image of the mouse, as shown in FIG. 1A, the bacteria (Bacteria) were not absorbed systemically, but in the case of bacteria-derived vesicles (EV), they were absorbed systemically 5 minutes after administration and administered. After 3 hours, the bladder was strongly observed, indicating that the vesicles were excreted by the urinary system. In addition, the vesicles were found to exist in the body until 12 hours of administration.

After the systemic absorption of enterobacteriaceae and enteric bacteria-derived vesicles systemically, in order to assess the invasion of various organs, the fluorescently labeled 50 μg of bacteria and bacteria-derived vesicles were administered in the same manner as above 12 hours. Blood, Heart, Lung, Liver, Kidney, Spleen, Adipose tissue, and Muscle were extracted from mice. As shown in FIG. 1B, the intestinal bacteria (Bacteria) were not absorbed in each organ, whereas the intestinal bacteria-derived extracellular vesicles (EVs) were urine, heart, lung as shown in FIG. And distribution in liver, kidney, spleen, adipose tissue, and muscle.

Example 2. Vesicle Separation and DNA Extraction from Feces and Urine

To separate the vesicles from the feces and urine and extract the DNA, first stool and urine were put in a 10 ml tube and centrifuged (3,500 xg, 10min, 4 ° C) to settle the suspended solids to recover only the supernatant, followed by a new 10 ml. Transferred to the tube. After removing the bacteria and foreign substances from the recovered supernatant using a 0.22 ㎛ filter, transfer to centripreigugal filters (50 kD) and centrifuged at 1500 xg, 4 ℃ for 15 minutes to discard the material smaller than 50 kD and 10 ml Concentrated until. Once again, remove the bacteria and foreign substances using a 0.22 ㎛ filter, discard the supernatant using ultra-fast centrifugation for 3 hours at 150,000 xg, 4 ℃ with a Type 90ti rotor and dissolve the agglomerated pellet in physiological saline (PBS) Vesicles were obtained.

According to the method, 100 μl of the vesicles isolated from feces and urine were boiled at 100 ° C. to let the DNA inside the lipids out and then cooled on ice for 5 minutes. Next, in order to remove the remaining suspended matter, centrifugation at 10,000 x g, 4 ℃ for 30 minutes, and collected only the supernatant and quantified the DNA amount using Nanodrop. Thereafter, PCR was performed with the 16s rDNA primer shown in Table 1 to confirm whether the bacteria-derived DNA exists in the extracted DNA, and it was confirmed that the bacteria-derived gene exists in the extracted gene.

primer order SEQ ID NO: 16S rDNA 16S_V3_F 5'-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3 ' One 16S_V4_R 5'-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC-3 2

Example 3 Metagenomic Analysis Using DNA Extracted from Fecal and Urine Vesicles

After the gene was extracted by the method of Example 2, PCR was performed using the 16S rDNA primer shown in Table 1 to amplify the gene and perform sequencing (Illumina MiSeq sequencer). Output the result as a Standard Flowgram Format (SFF) file, convert the SFF file into a sequence file (.fasta) and a nucleotide quality score file using GS FLX software (v2.9), check the credit rating of the lead, and window (20 bps) The part with the average base call accuracy of less than 99% (Phred score <20) was removed. After removing the low quality part, only the lead length was 300 bps or more (Sickle version 1.33), and the Operational Taxonomy Unit (OTU) performed UCLUST and USEARCH for clustering according to sequence similarity. Specifically, the clustering is based on 94% genus, 90% family, 85% order, 80% class, and 75% sequence similarity. OTU's door, river, neck, family and genus level classifications were performed, and bacteria with greater than 97% sequence similarity were analyzed using BLASTN and GreenGenes' 16S DNA sequence database (108,453 sequences) (QIIME).

Example  4. Isolation from Stool in Normal and Colorectal Cancer Patients Germ-derived  parcel Metagenome  Analysis-based Colorectal Cancer Diagnosis Model

By the method of Example 3, vesicles were isolated from stool of 29 colon cancer patients and 358 normal patients, and then metagenome sequencing was performed. In the development of the diagnostic model, the strains whose p-value between the two groups is 0.05 or less and more than two times different between the two groups are selected in the t-test. under curve), sensitivity, and specificity.

Analysis of stool-derived vesicles at the phylum level revealed colon diagnosis of colon cancer when one or more biomarkers were developed in Deferribacteres, Tenericutes, Actinobacteria, Acidobacteria, Armatimonadetes, Planctomycetes, and Fusobacteria door bacteria. Performance was significant (see Table 2 and FIG. 2).

Control Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity p__Deferribacteres 0.0004 0.0018 0.0001 0.0003 0.0006 0.16 0.74 1.00 0.03 p__Tenericutes 0.0098 0.0256 0.0027 0.0064 0.0001 0.27 0.74 1.00 0.03 p__Actinobacteria 0.0353 0.0403 0.0817 0.0588 0.0003 2.32 0.80 0.99 0.14 p__Acidobacteria 0.0005 0.0024 0.0019 0.0021 0.0024 3.61 0.75 1.00 0.03 p__Armatimonadetes 0.0002 0.0007 0.0009 0.0013 0.0075 5.11 0.77 1.00 0.07 p__Planctomycetes 0.0001 0.0006 0.0011 0.0015 0.0027 7.36 0.82 0.99 0.24 p__Fusobacteria 0.0016 0.0040 0.0124 0.0202 0.0088 7.60 0.82 0.99 0.17

Analysis of fecal bacteria-derived vesicles at the class level revealed that one or more biopsies of Deferribacteres, Mollicutes, 4C0d-2, Bacilli, Alphaproteobacteria, Saprospirae, Fimbriimonadia, Acidobacteria-6, Solibacteres, Coriobacteriia, Oscillatoriophycideae, and Fusobacteriia river bacteria When the diagnostic model was developed as a marker, the diagnostic performance for colorectal cancer was significant (see Table 3 and FIG. 3).

Control Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity c__Deferribacteres 0.0004 0.0018 0.0001 0.0003 0.0006 0.16 0.74 1.00 0.03 c__Mollicutes 0.0095 0.0254 0.0026 0.0064 0.0002 0.28 0.74 1.00 0.03 c__4C0d-2 0.0007 0.0028 0.0002 0.0004 0.0084 0.34 0.73 1.00 0.03 c__Bacilli 0.0820 0.0955 0.1661 0.1537 0.0078 2.03 0.75 1.00 0.03 c__Alphaproteobacteria 0.0192 0.0306 0.0491 0.0520 0.0054 2.56 0.80 1.00 0.14 c __ [Saprospirae] 0.0003 0.0010 0.0008 0.0012 0.0040 2.94 0.74 1.00 0.03 c __ [Fimbriimonadia] 0.0002 0.0007 0.0009 0.0013 0.0075 5.14 0.77 1.00 0.07 c__Acidobacteria-6 0.0001 0.0007 0.0007 0.0010 0.0037 5.85 0.78 0.99 0.03 c__Solibacteres 0.0001 0.0006 0.0006 0.0009 0.0090 5.86 0.75 0.99 0.07 c__Coriobacteriia 0.0040 0.0081 0.0251 0.0363 0.0046 6.33 0.80 0.99 0.17 c__Oscillatoriophycideae 0.0001 0.0005 0.0006 0.0009 0.0050 6.72 0.80 0.99 0.10 c__Fusobacteriia 0.0016 0.0040 0.0124 0.0202 0.0088 7.60 0.82 0.99 0.17

Bacterial-derived vesicles in feces at the order level were analyzed by RF32, YS2, Deferribacterales, Turicibacterales, RF39, Oceanospirillales, Rhizobiales, Lactobacillales, Rhodobacterales, Saprospirales, Sphingomonadales, Fimbriimonadales, iii1-15, Solibactles, Corio When developing a diagnostic model with one or more biomarkers in Fusobacteriales, and Bdellovibrionales neck bacteria, the diagnostic performance for colorectal cancer was significant (see Table 4 and Figure 4).

Control Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity o__RF32 0.0005 0.0026 0.0000 0.0001 0.0005 0.03 0.75 1.00 0.03 o__YS2 0.0006 0.0027 0.0001 0.0002 0.0003 0.09 0.74 1.00 0.03 o__Deferribacterales 0.0004 0.0018 0.0001 0.0003 0.0006 0.16 0.74 1.00 0.03 o__Turicibacterales 0.0148 0.0493 0.0024 0.0053 0.0000 0.16 0.75 1.00 0.03 o__RF39 0.0090 0.0248 0.0017 0.0046 0.0000 0.18 0.75 1.00 0.03 o__Oceanospirillales 0.0009 0.0033 0.0002 0.0003 0.0001 0.22 0.75 1.00 0.03 o__Rhizobiales 0.0085 0.0202 0.0189 0.0215 0.0082 2.23 0.75 1.00 0.03 o__Lactobacillales 0.0519 0.0809 0.1402 0.1495 0.0044 2.70 0.76 1.00 0.10 o__Rhodobacterales 0.0019 0.0057 0.0054 0.0059 0.0020 2.81 0.76 1.00 0.03 o __ [Saprospirales] 0.0003 0.0010 0.0008 0.0012 0.0040 2.94 0.74 1.00 0.03 o__Sphingomonadales 0.0050 0.0097 0.0192 0.0207 0.0012 3.87 0.85 0.99 0.21 o __ [Fimbriimonadales] 0.0002 0.0007 0.0009 0.0013 0.0075 5.14 0.77 1.00 0.07 o__iii1-15 0.0001 0.0007 0.0006 0.0010 0.0090 5.67 0.78 0.99 0.03 o__Solibacterales 0.0001 0.0006 0.0006 0.0009 0.0089 5.89 0.75 0.99 0.07 o__Coriobacteriales 0.0040 0.0081 0.0251 0.0363 0.0046 6.33 0.80 0.99 0.17 o__Chroococcales 0.0001 0.0005 0.0006 0.0009 0.0050 6.63 0.80 0.99 0.14 o__Fusobacteriales 0.0016 0.0040 0.0124 0.0202 0.0088 7.60 0.82 0.99 0.17 o__Bdellovibrionales 0.0001 0.0004 0.0006 0.0009 0.0063 9.79 0.76 0.99 0.10

Analysis of bacteria-derived vesicles in feces at the family level revealed that Peptococcaceae, Deferribacteraceae, Turicibacteraceae, Halomonadaceae, Clostridiaceae, Prevotellaceae, Peptostreptococcaceae, Rhodobacteraceae, Nocardioidaceae, Sphingomonadaceae, Bartonellaceae, Cellulomonadaceae, Rriiobaaceae When diagnostic models were developed with one or more biomarkers in Coriobacteriaceae, Xenococcaceae, Aeromonadaceae, Geodermatophilaceae, and Bdellovibrionaceae and bacteria, the diagnostic performance for colorectal cancer was significant (see Table 5 and Figure 5).

Control Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity f__Peptococcaceae 0.0020 0.0048 0.0001 0.0003 0.0000 0.07 0.80 1.00 0.03 f__Deferribacteraceae 0.0004 0.0018 0.0001 0.0003 0.0006 0.16 0.74 1.00 0.03 f__Turicibacteraceae 0.0148 0.0493 0.0024 0.0053 0.0000 0.16 0.75 1.00 0.03 f__Halomonadaceae 0.0008 0.0027 0.0002 0.0003 0.0002 0.25 0.74 1.00 0.03 f__Clostridiaceae 0.0477 0.0792 0.0129 0.0176 0.0000 0.27 0.79 1.00 0.03 f__Prevotellaceae 0.1518 0.1717 0.0454 0.0656 0.0000 0.30 0.79 1.00 0.03 f__Peptostreptococcaceae 0.0275 0.0623 0.0088 0.0134 0.0000 0.32 0.76 1.00 0.03 f__Rhodobacteraceae 0.0019 0.0057 0.0054 0.0059 0.0020 2.82 0.76 1.00 0.03 f__Nocardioidaceae 0.0004 0.0016 0.0013 0.0019 0.0037 3.58 0.75 1.00 0.03 f__Sphingomonadaceae 0.0047 0.0091 0.0187 0.0202 0.0010 4.00 0.86 0.99 0.21 f__Bartonellaceae 0.0002 0.0014 0.0009 0.0012 0.0088 4.27 0.75 1.00 0.03 f__Cellulomonadaceae 0.0001 0.0009 0.0006 0.0009 0.0084 4.48 0.74 1.00 0.03 f__Lactobacillaceae 0.0162 0.0224 0.0733 0.0967 0.0042 4.52 0.83 0.99 0.21 f__Rhizobiaceae 0.0022 0.0040 0.0102 0.0125 0.0023 4.62 0.83 1.00 0.28 f __ [Fimbriimonadaceae] 0.0002 0.0007 0.0009 0.0013 0.0075 5.14 0.77 1.00 0.07 f__Dermacoccaceae 0.0003 0.0010 0.0018 0.0025 0.0047 5.58 0.81 0.99 0.14 f__Leptotrichiaceae 0.0007 0.0027 0.0042 0.0055 0.0021 5.93 0.82 0.99 0.07 f__Coriobacteriaceae 0.0040 0.0081 0.0251 0.0363 0.0046 6.33 0.80 0.99 0.17 f__Xenococcaceae 0.0001 0.0005 0.0006 0.0009 0.0049 6.72 0.81 0.99 0.14 f__Aeromonadaceae 0.0001 0.0006 0.0009 0.0013 0.0035 7.11 0.82 0.99 0.10 f__Geodermatophilaceae 0.0002 0.0008 0.0013 0.0018 0.0023 7.46 0.83 0.99 0.17 f__Bdellovibrionaceae 0.0000 0.0002 0.0006 0.0009 0.0038 23.48 0.80 1.00 0.24

Bacterial-derived vesicles in feces at genus level were analyzed by rc4-4, Proteus, Catenibacterium, Mucispirillum, Eubacterium, Turicibacter, Alloiococcus, Halomonas, Prevotella, Dialister, Anaerostipes, SMB53, Faecalibacterium, Blautia, Capnocytopomonas, When diagnostic models were developed with one or more biomarkers of bacteria of the genus Lactobacillus, Fimbriimonas, Dermacoccus, Achromobacter, Novosphingobium, Sneathia, Agrobacterium, Blastomonas, Bdellovibrio, Alkanindiges, Roseateles, and Shuttleworthia, diagnostic performance for colorectal cancer was significant. (See Table 6 and FIG. 6).

Control Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity g__rc4-4 0.0010 0.0035 0.0000 0.0000 0.0000 0.01 0.80 1.00 0.03 g__Proteus 0.0121 0.0272 0.0005 0.0011 0.0000 0.04 0.80 1.00 0.03 g__Catenibacterium 0.0014 0.0047 0.0002 0.0004 0.0000 0.11 0.75 1.00 0.03 g__Mucispirillum 0.0004 0.0018 0.0001 0.0003 0.0006 0.16 0.74 1.00 0.03 g __ [Eubacterium] 0.0008 0.0020 0.0001 0.0003 0.0000 0.16 0.74 1.00 0.03 g__Turicibacter 0.0148 0.0493 0.0024 0.0053 0.0000 0.16 0.75 1.00 0.03 g__Alloiococcus 0.0004 0.0025 0.0001 0.0002 0.0086 0.16 0.73 1.00 0.03 g__Halomonas 0.0006 0.0024 0.0002 0.0003 0.0027 0.29 0.73 1.00 0.03 g__Prevotella 0.1518 0.1717 0.0454 0.0656 0.0000 0.30 0.79 1.00 0.03 g__Dialister 0.0063 0.0186 0.0020 0.0027 0.0001 0.32 0.75 1.00 0.03 g__Anaerostipes 0.0006 0.0014 0.0002 0.0005 0.0020 0.36 0.74 1.00 0.03 g__SMB53 0.0011 0.0018 0.0004 0.0007 0.0002 0.39 0.76 1.00 0.00 g__Faecalibacterium 0.0681 0.0882 0.0285 0.0584 0.0020 0.42 0.77 1.00 0.03 g__Blautia 0.0037 0.0100 0.0017 0.0017 0.0009 0.45 0.74 1.00 0.03 g__Capnocytophaga 0.0003 0.0008 0.0007 0.0009 0.0052 2.59 0.75 1.00 0.03 g__Sphingomonas 0.0032 0.0059 0.0128 0.0138 0.0011 3.95 0.85 0.99 0.28 g__Lactobacillus 0.0160 0.0223 0.0731 0.0966 0.0041 4.58 0.83 0.99 0.21 g__Fimbriimonas 0.0002 0.0007 0.0009 0.0013 0.0079 5.10 0.77 1.00 0.07 g__Dermacoccus 0.0003 0.0010 0.0018 0.0025 0.0047 5.58 0.81 0.99 0.14 g__Achromobacter 0.0001 0.0003 0.0005 0.0008 0.0065 6.93 0.83 0.99 0.17 g__Novosphingobium 0.0002 0.0009 0.0014 0.0021 0.0046 7.84 0.82 0.99 0.10 g__Sneathia 0.0002 0.0019 0.0038 0.0050 0.0009 17.60 0.85 1.00 0.28 g__Agrobacterium 0.0002 0.0006 0.0036 0.0047 0.0005 20.68 0.87 1.00 0.41 g__Blastomonas 0.0000 0.0002 0.0006 0.0008 0.0012 22.87 0.84 0.99 0.31 g__Bdellovibrio 0.0000 0.0002 0.0006 0.0009 0.0038 23.63 0.80 1.00 0.24 g__Alkanindiges 0.0000 0.0002 0.0008 0.0014 0.0037 26.94 0.85 1.00 0.28 g__Roseateles 0.0000 0.0002 0.0011 0.0020 0.0086 51.47 0.83 0.99 0.31 g__Shuttleworthia 0.0000 0.0003 0.0020 0.0034 0.0043 51.55 0.84 1.00 0.34

Example  5. Isolation from Urine of Normal and Colorectal Cancer Patients Germ-derived  parcel Metagenome  Analysis-based Colorectal Cancer Diagnosis Model

By the method of Example 3, the vesicles were isolated from the urine of 38 patients with colorectal cancer and 38 normal people and then subjected to metagenome sequencing. In the development of the diagnostic model, the strains whose p-value between the two groups is 0.05 or less and more than two times different between the two groups are selected in the t-test. under curve), sensitivity, and specificity.

Analysis of vesicle-derived vesicles in the urine at the phylum level revealed significant diagnostic performance for colorectal cancer when developing a diagnostic model with one or more biomarkers in Proteobacteria and Euryarchaeota cultivars (Table 7 and See FIG. 7).

Control Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity p__Proteobacteria 0.5379 0.1871 0.2394 0.0820 0.0000 0.45 0.94 0.84 0.87 p__Euryarchaeota 0.0000 0.0001 0.0021 0.0021 0.0000 70.49 0.90 0.97 0.71

Analysis of the vesicle-derived vesicles in urine at the class level showed a significant diagnostic performance for colorectal cancer when developing a diagnostic model with one or more biomarkers in Gammaproteobacteria, Clostridia, and Methanobacteria river bacteria. 8 and FIG. 8).

Control Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity c__Gammaproteobacteria 0.4431 0.2104 0.1776 0.0577 0.0000 0.40 0.90 0.76 0.87 c__Clostridia 0.1286 0.0723 0.2752 0.0844 0.0000 2.14 0.93 0.87 0.82 c__Methanobacteria 0.0000 0.0001 0.0020 0.0021 0.0000 67.36 0.90 0.97 0.68

Analysis of the urine-derived vesicles at the order level revealed colorectal cancer when developing diagnostic models with one or more biomarkers from Desulfobacterales, Stramenopiles, Pseudomonadales, Clostridiales, Turicibacterales, Desulfovibrionales, Oceanospirillales, and Methanobacteriales neck bacteria. Diagnostic performance was significant (see Table 9 and FIG. 9).

Control Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity o__Desulfobacterales 0.0012 0.0027 0.0000 0.0000 0.0078 0.00 0.77 0.53 0.76 o__Stramenopiles 0.0055 0.0083 0.0001 0.0004 0.0003 0.02 0.82 0.58 0.87 o__Pseudomonadales 0.3124 0.1910 0.0622 0.0401 0.0000 0.20 0.93 0.87 0.92 o__Clostridiales 0.1284 0.0725 0.2751 0.0843 0.0000 2.14 0.93 0.87 0.82 o__Turicibacterales 0.0017 0.0026 0.0038 0.0040 0.0075 2.27 0.72 0.71 0.61 o__Desulfovibrionales 0.0001 0.0005 0.0009 0.0010 0.0001 6.78 0.79 0.89 0.58 o__Oceanospirillales 0.0005 0.0012 0.0038 0.0073 0.0098 7.70 0.84 0.87 0.58 o__Methanobacteriales 0.0000 0.0001 0.0020 0.0021 0.0000 67.36 0.90 0.97 0.68

Analysis of bacteria-derived vesicles in the urine at the family level showed Moraxellaceae, Pseudomonadaceae, Streptococcaceae, Turicibacteraceae, Veillonellaceae, Bacteroidaceae, Aerococcaceae, Comamonadaceae, Clostridiaceae, Paraprevotellaceae, Christensenellaceae, Ruminococcaceae, Corynebacteriaceae, Gordonviaceae, Myoraceae, Myraceae, When diagnostic models were developed with one or more biomarkers in Alcaligenaceae, Barnesiellaceae, Methanobacteriaceae, and Rikenellaceae, the diagnostic performance for colorectal cancer was significant (see Table 10 and Figure 10).

Control Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity f__Moraxellaceae 0.1810 0.1401 0.0313 0.0220 0.0000 0.17 0.93 0.87 0.87 f__Pseudomonadaceae 0.1314 0.0973 0.0306 0.0204 0.0000 0.23 0.90 0.82 0.89 f__Streptococcaceae 0.0180 0.0126 0.0383 0.0167 0.0000 2.13 0.89 0.79 0.87 f__Turicibacteraceae 0.0017 0.0026 0.0038 0.0040 0.0075 2.27 0.72 0.71 0.61 f__Veillonellaceae 0.0070 0.0083 0.0168 0.0074 0.0000 2.41 0.85 0.71 0.74 f__Bacteroidaceae 0.0212 0.0207 0.0517 0.0381 0.0001 2.44 0.84 0.82 0.74 f__Aerococcaceae 0.0021 0.0033 0.0052 0.0059 0.0057 2.51 0.74 0.74 0.61 f__Comamonadaceae 0.0027 0.0036 0.0071 0.0062 0.0003 2.63 0.76 0.76 0.63 f__Clostridiaceae 0.0100 0.0114 0.0299 0.0205 0.0000 2.99 0.86 0.79 0.71 f __ [Paraprevotellaceae] 0.0012 0.0036 0.0038 0.0033 0.0017 3.11 0.82 0.82 0.63 f__Christensenellaceae 0.0004 0.0013 0.0014 0.0014 0.0040 3.16 0.74 0.87 0.68 f__Ruminococcaceae 0.0379 0.0431 0.1280 0.0390 0.0000 3.38 0.95 0.92 0.87 f__Corynebacteriaceae 0.0090 0.0097 0.0366 0.0197 0.0000 4.07 0.96 0.89 0.87 f__Gordoniaceae 0.0001 0.0005 0.0004 0.0006 0.0081 5.03 0.78 0.76 0.68 f__Mycobacteriaceae 0.0002 0.0008 0.0009 0.0015 0.0090 5.82 0.76 0.92 0.58 f__Desulfovibrionaceae 0.0001 0.0005 0.0009 0.0010 0.0001 6.78 0.79 0.89 0.58 f__Halomonadaceae 0.0002 0.0008 0.0018 0.0022 0.0001 9.40 0.88 0.92 0.66 f__Alcaligenaceae 0.0001 0.0004 0.0018 0.0017 0.0000 15.77 0.90 0.95 0.79 f __ [Barnesiellaceae] 0.0001 0.0004 0.0016 0.0018 0.0000 24.08 0.84 0.95 0.66 f__Methanobacteriaceae 0.0000 0.0001 0.0020 0.0021 0.0000 67.36 0.90 0.97 0.68 f__Rikenellaceae 0.0000 0.0002 0.0059 0.0040 0.0000 153.18 0.98 0.97 0.92

Analysis of bacterial vesicles in the urine at genus level showed Rhizobium, Proteus, Morganella, Acinetobacter, Pseudomonas, SMB53, Enterococcus, Lactococcus, Turicibacter, Coprococcus, Bacteroides, Dorea, Streptococcus, Lachnospira, Coramobacter, One or more biotypes of the genus were diagnosed as one or more biotypes in the genus of the genus of bacteria: Gordonia, Paraprevotella, Mycobacterium, Roseburia, Dialister, Slackia, Escherichia, Phascolarctobacterium, Sutterella, Virgibacillus, Eggerthella, Halomonas, Citrobacter, Roseomonas, Alloiococcus, Serratia, Methanobrevibacter, and Bilophila , Diagnostic performance for colorectal cancer was significant (see Table 11 and FIG. 11).

Control Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity g__Rhizobium 0.0056 0.0056 0.0000 0.0000 0.0000 0.00 1.00 1.00 1.00 g__Proteus 0.0132 0.0192 0.0006 0.0010 0.0003 0.04 0.87 0.76 0.95 g__Morganella 0.0211 0.0295 0.0013 0.0060 0.0002 0.06 0.84 0.61 0.84 g__Acinetobacter 0.1683 0.1396 0.0172 0.0138 0.0000 0.10 0.94 0.84 0.95 g__Pseudomonas 0.1288 0.0965 0.0286 0.0201 0.0000 0.22 0.90 0.82 0.89 g__SMB53 0.0034 0.0046 0.0008 0.0012 0.0017 0.23 0.73 0.58 0.66 g__Enterococcus 0.0086 0.0108 0.0023 0.0024 0.0010 0.26 0.74 0.50 0.82 g__Lactococcus 0.0035 0.0039 0.0015 0.0019 0.0074 0.44 0.67 0.50 0.66 g__Turicibacter 0.0017 0.0026 0.0038 0.0040 0.0075 2.27 0.72 0.71 0.61 g__Coprococcus 0.0036 0.0043 0.0083 0.0052 0.0000 2.31 0.81 0.74 0.76 g__Bacteroides 0.0212 0.0207 0.0517 0.0381 0.0001 2.44 0.84 0.82 0.74 g__Dorea 0.0010 0.0015 0.0025 0.0024 0.0011 2.55 0.80 0.79 0.66 g__Streptococcus 0.0143 0.0122 0.0366 0.0166 0.0000 2.56 0.90 0.79 0.87 g__Lachnospira 0.0005 0.0012 0.0017 0.0020 0.0020 3.54 0.76 0.82 0.66 g __ [Ruminococcus] 0.0010 0.0015 0.0040 0.0031 0.0000 3.83 0.85 0.79 0.58 g__Corynebacterium 0.0090 0.0097 0.0366 0.0197 0.0000 4.07 0.96 0.89 0.87 g__Comamonas 0.0003 0.0010 0.0013 0.0018 0.0050 4.32 0.77 0.87 0.61 g__Ruminococcus 0.0030 0.0043 0.0148 0.0073 0.0000 4.94 0.94 0.87 0.82 g__Gordonia 0.0001 0.0005 0.0004 0.0006 0.0081 5.03 0.78 0.76 0.68 g__Paraprevotella 0.0002 0.0007 0.0010 0.0014 0.0015 5.70 0.80 0.89 0.66 g__Mycobacterium 0.0002 0.0008 0.0009 0.0015 0.0090 5.82 0.76 0.92 0.58 g__Roseburia 0.0004 0.0017 0.0032 0.0028 0.0000 8.45 0.93 0.92 0.79 g__Dialister 0.0005 0.0012 0.0065 0.0046 0.0000 13.84 0.94 0.92 0.87 g__Slackia 0.0000 0.0003 0.0007 0.0014 0.0062 15.14 0.77 0.92 0.58 g__Escherichia 0.0001 0.0001 0.0009 0.0008 0.0000 15.98 0.95 0.95 0.84 g__Phascolarctobacterium 0.0001 0.0007 0.0026 0.0030 0.0000 20.76 0.93 0.97 0.84 g__Sutterella 0.0001 0.0003 0.0013 0.0015 0.0000 20.99 0.86 0.95 0.74 g__Virgibacillus 0.0000 0.0001 0.0008 0.0010 0.0000 21.74 0.83 0.89 0.61 g__Eggerthella 0.0000 0.0001 0.0005 0.0010 0.0044 24.82 0.76 0.76 0.55 g__Halomonas 0.0001 0.0003 0.0017 0.0022 0.0000 26.50 0.91 0.95 0.76 g__Citrobacter 0.0003 0.0005 0.0089 0.0056 0.0000 30.07 0.99 0.97 0.92 g__Roseomonas 0.0000 0.0002 0.0012 0.0016 0.0001 35.67 0.85 0.97 0.58 g__Alloiococcus 0.0000 0.0001 0.0022 0.0050 0.0097 174.52 0.88 0.95 0.74 g__Serratia 0.0000 0.0000 0.0006 0.0010 0.0007 195.10 0.81 0.92 0.55 g__Methanobrevibacter 0.0000 0.0000 0.0020 0.0021 0.0000 555.27 0.92 1.00 0.74 g__Bilophila 0.0000 0.0000 0.0005 0.0008 0.0003 873.83 0.79 0.92 0.53

Example  6. With colon polyps  Isolated from Stool in Patients with Colorectal Cancer Germ-derived  parcel Metagenome  Analysis-based Colorectal Cancer Diagnosis Model

By the method of Example 3, vesicles were isolated from the stool of 29 colon cancer patients and 27 colon polyp patients, and then metagenome sequencing was performed. In the development of the diagnostic model, the strains whose p-value between the two groups is 0.05 or less and more than two times different between the two groups are selected in the t-test. under curve), sensitivity, and specificity.

As a result of analyzing the stool-derived vesicles at the phylum level, when the diagnostic model was developed as a biomarker of Spirochaetes cultivars, the diagnostic performance for colon cancer was significant (see Table 12 and FIG. 12).

Colon polyp Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity p__Spirochaetes 0.0005 0.0009 0.0001 0.0001 0.0216 0.12 0.87 0.74 0.79

As a result of analyzing the stool-derived vesicles at the class level, the diagnostic performance for colon cancer was significant when the diagnostic model was developed for biomarkers of spirochaetes and Acidobacteria-6. See FIG. 13).

Colon polyp Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity c__Spirochaetes 0.0005 0.0009 0.0001 0.0001 0.0202 0.11 0.87 0.78 0.83 c__Acidobacteria-6 0.0003 0.0004 0.0007 0.0010 0.0237 2.92 0.85 0.81 0.69

As a result of analyzing the stool-derived vesicles at the order level, when the diagnostic model was developed as a biomarker of Spirochaetales neck bacteria, the diagnostic performance for colon cancer was significant (see Table 14 and FIG. 14).

Colon polyp Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity o__Spirochaetales 0.0005 0.0009 0.0001 0.0001 0.0202 0.11 0.87 0.78 0.83

Analysis of bacterial vesicles in the feces at the family level showed that diagnostic performance for colon cancer was significant when Spirochaetaceae and S24-7 and bacteria were developed as biomarkers (Table 15 and See FIG. 15).

Colon polyp Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity f__Spirochaetaceae 0.0005 0.0009 0.0001 0.0001 0.0202 0.11 0.87 0.78 0.83 f__S24-7 0.0021 0.0053 0.0103 0.0206 0.0492 4.93 0.84 0.81 0.69

Analysis of bacterial vesicle-derived stool at the genus level showed that diagnostic performance for colon cancer was significant when a diagnostic model was developed for the biomarkers of bacteria of Treponema, Dialister, and Oscillospira (Table 16 and See FIG. 16).

Colon polyp Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity g__Treponema 0.0005 0.0009 0.0001 0.0001 0.0202 0.11 0.8685 0.7778 0.8276 g__Dialister 0.0103 0.0152 0.0020 0.0027 0.0106 0.20 0.8672 0.7778 0.8276 g__Oscillospira 0.0023 0.0019 0.0074 0.0109 0.0212 3.18 0.8378 0.7778 0.7241

Example  7. With colon polyps  Isolated from Urine Colon Cancer Patients Germ-derived  parcel Metagenome  Analysis-based Colorectal Cancer Diagnosis Model

By the method of Example 3, the vesicles were isolated from the urine of 26 patients with colorectal cancer and 38 patients with colorectal polyps, and then metagenome sequencing was performed. In the development of the diagnostic model, the strains whose p-value between the two groups is 0.05 or less and more than two times different between the two groups are selected in the t-test. under curve), sensitivity, and specificity.

As a result of analyzing the vesicle-derived vesicles in the urine at the order level, when the diagnostic model was developed with the tree Myxococcales, the diagnostic performance for colon cancer was significant (see Table 17 and FIG. 17).

Colon polyp Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity o__Myxococcales 0.0000 0.0001 0.0005 0.0013 0.0442 14.52 0.78 0.69 0.82

As a result of analyzing the bacterial vesicles in the urine at the genus level, when diagnostic models were developed with Eubacterium spp., The diagnostic performance for colon cancer was significant (see Table 18 and Fig. 18).

Colon polyp Colorectal cancer t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity g __ [Eubacterium] 0.0009 0.0011 0.0024 0.0028 0.0040 2.72 0.79 0.62 0.79

Example  8. Normal people Colon polyp  Separated from feces Germ-derived  parcel Metagenome  Analytics based Colon polyp  Diagnostic Model

By the method of Example 3, vesicles were isolated from stool of 27 colon cancer patients and 358 normal patients, and then metagenome sequencing was performed. In the development of the diagnostic model, the strains whose p-value between the two groups is 0.05 or less and more than two times different between the two groups are selected in the t-test. under curve), sensitivity, and specificity.

As a result of analyzing fecal bacteria-derived vesicles at the phylum level, when the diagnostic model was developed with Actinobacteria cultivars, the diagnostic performance of colon polyps was significant (see Table 19 and FIG. 19).

Control Colon polyp t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity p__Actinobacteria 0.0353 0.0403 0.0826 0.0680 0.0016 2.34 0.84 0.99 0.11

Analysis of fecal bacteria-derived vesicles at the class level showed significant diagnostic performance for colorectal polyps when developing a diagnostic model with at least one biomarker in Betaproteobacteria and Solibacteres river bacteria (Table 20 and 20).

Control Colon polyp t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity c__Betaproteobacteria 0.0151 0.0370 0.0391 0.0369 0.0013 2.58 0.82 1.00 0.00 c__Solibacteres 0.0001 0.0006 0.0005 0.0007 0.0093 4.95 0.83 1.00 0.00

Analysis of bacterial vesicles from stool at the order level showed significant diagnostic performance for colon polyps when developing a diagnostic model with one or more biomarkers in Burkholderiales, Sphingomonadales, and Solibacterales throat bacteria. 21 and FIG. 21).

Control Colon polyp t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity o__Burkholderiales 0.0121 0.0358 0.0367 0.0365 0.0007 3.02 0.82 1.00 0.00 o__Sphingomonadales 0.0050 0.0097 0.0215 0.0216 0.0006 4.33 0.87 0.99 0.19 o__Solibacterales 0.0001 0.0006 0.0005 0.0007 0.0091 4.98 0.83 1.00 0.00

Analysis of fecal-derived vesicles at the family level showed significant diagnostic performance for colon polyps when developing a diagnostic model with one or more biomarkers in Rhizobiaceae, Sphingomonadaceae and bacteria (Table 22 and See FIG. 22).

Control Colon polyp t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity f__Rhizobiaceae 0.0022 0.0040 0.0080 0.0105 0.0091 3.64 0.83 0.99 0.19 f__Sphingomonadaceae 0.0047 0.0091 0.0208 0.0210 0.0006 4.46 0.87 0.99 0.22

Analysis of bacterial vesicle-derived stool at the genus level revealed significant diagnostic performance for colon polyps when developing a diagnostic model with one or more biomarkers in bacteria of Sphingomonas, Alkanindiges, and Roseateles. 23 and FIG. 23).

Control Colon polyp t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity g__Sphingomonas 0.0032 0.0059 0.0155 0.0164 0.0008 4.77 0.87 0.99 0.30 g__Alkanindiges 0.0000 0.0002 0.0008 0.0015 0.0097 26.73 0.84 1.00 0.26 g__Roseateles 0.0000 0.0002 0.0006 0.0011 0.0078 30.88 0.85 0.99 0.22

Example  9. The normal person Colon polyp  Isolated from urine Germ-derived  parcel Metagenome  Analytics based Colon polyp  Diagnostic Model

By the method of Example 3, the vesicles were isolated from the urine of 38 patients with colorectal cancer and 38 normal people and then subjected to metagenome sequencing. In the development of the diagnostic model, the strains whose p-value between the two groups is 0.05 or less and more than two times different between the two groups are selected in the t-test. under curve), sensitivity, and specificity.

Analysis of vesicle-derived vesicles in the urine at the phylum level revealed significant diagnostic performance for colon polyps when developing a diagnostic model with one or more biomarkers in Proteobacteria and Euryarchaeota cultivars (Table 24 and See FIG. 24).

Control Colon polyp t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity p__Proteobacteria 0.5379 0.1871 0.2416 0.0691 0.0000 0.45 0.92 0.82 0.88 p__Euryarchaeota 0.0000 0.0001 0.0024 0.0027 0.0001 82.21 0.90 1.00 0.73

The analysis of vesicle-derived vesicles in urine at the class level revealed that diagnostic performance of colonic polyps was significant when Gammaproteobacteria, Clostridia, Methanobacteria, and 4C0d-2 river bacteria were developed with one or more biomarkers. (See Table 25 and FIG. 25).

Control Colon polyp t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity c__Gammaproteobacteria 0.4431 0.2104 0.1807 0.0511 0.0000 0.41 0.86 0.76 0.88 c__Clostridia 0.1286 0.0723 0.2804 0.0637 0.0000 2.18 0.94 0.87 0.77 c__Methanobacteria 0.0000 0.0001 0.0024 0.0027 0.0002 79.88 0.90 1.00 0.73 c__4C0d-2 0.0000 0.0000 0.0006 0.0011 0.0099 1952.62 0.81 0.92 0.38

Analysis of the urine-derived vesicles at the order level showed diagnostic performance for colon polyps when one or more biomarkers were developed for stramenopiles, Pseudomonadales, Clostridiales, Oceanospirillales, Desulfovibrionales, and Methanobacteriales neck bacteria. This was significant (see Table 26 and Figure 26).

Control Colon polyp t-test Taxon Mean SD Mean SD p-value Ratio Auc sensitivity specificity o__Stramenopiles 0.0055 0.0083 0.0000 0.0000 0.0014 0.00 0.89 0.74 1.00 o__Pseudomonadales 0.3124 0.1910 0.0622 0.0414 0.0000 0.20 0.91 0.84 0.85 o__Clostridiales 0.1284 0.0725 0.2804 0.0637 0.0000 2.18 0.94 0.87 0.77 o__Oceanospirillales 0.0005 0.0012 0.0018 0.0015 0.0003 3.65 0.86 0.89 0.62 o__Desulfovibrionales 0.0001 0.0005 0.0010 0.0015 0.0064 7.61 0.83 0.92 0.54 o__Methanobacteriales 0.0000 0.0001 0.0024 0.0027 0.0002 79.88 0.90 1.00 0.73

Analysis of bacteria-derived vesicles in the urine at the family level revealed Exiguobacteraceae, Moraxellaceae, Pseudomonadaceae, Rhizobiaceae, Streptococcaceae, Peptostreptococcaceae, Comamonadaceae, Veillonellaceae, Bacteroidaceae, Paraprevotellaceae, Ruminococcaceae, Corynebacteriaceae, Halbacaceae necaceae When diagnostic models were developed with one or more biomarkers in Barnesiellaceae, Methanobacteriaceae, and Rikenellaceae family and bacteria, the diagnostic performance for colon polyps was significant (see Table 27 and Figure 27).

Control Colon polyp t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity f __ [Exiguobacteraceae] 0.0013 0.0026 0.0001 0.0003 0.0076 0.06 0.74 0.63 0.77 f__Moraxellaceae 0.1810 0.1401 0.0306 0.0235 0.0000 0.17 0.88 0.79 0.81 f__Pseudomonadaceae 0.1314 0.0973 0.0315 0.0201 0.0000 0.24 0.89 0.82 0.85 f__Rhizobiaceae 0.0068 0.0062 0.0025 0.0032 0.0007 0.37 0.83 0.79 0.62 f__Streptococcaceae 0.0180 0.0126 0.0373 0.0099 0.0000 2.08 0.90 0.87 0.85 f__Peptostreptococcaceae 0.0009 0.0017 0.0023 0.0017 0.0029 2.42 0.84 0.95 0.65 f__Comamonadaceae 0.0027 0.0036 0.0067 0.0067 0.0090 2.48 0.77 0.79 0.46 f__Veillonellaceae 0.0070 0.0083 0.0186 0.0056 0.0000 2.67 0.86 0.79 0.77 f__Bacteroidaceae 0.0212 0.0207 0.0571 0.0217 0.0000 2.69 0.92 0.89 0.73 f __ [Paraprevotellaceae] 0.0012 0.0036 0.0037 0.0021 0.0008 3.07 0.85 0.82 0.65 f__Ruminococcaceae 0.0379 0.0431 0.1325 0.0396 0.0000 3.50 0.93 0.87 0.85 f__Corynebacteriaceae 0.0090 0.0097 0.0367 0.0159 0.0000 4.09 0.97 0.95 0.85 f__Christensenellaceae 0.0004 0.0013 0.0018 0.0021 0.0042 4.23 0.84 0.92 0.62 f __ [Odoribacteraceae] 0.0005 0.0022 0.0023 0.0022 0.0026 4.30 0.83 0.89 0.54 f__Desulfovibrionaceae 0.0001 0.0005 0.0010 0.0015 0.0064 7.61 0.83 0.92 0.54 f__Halomonadaceae 0.0002 0.0008 0.0016 0.0015 0.0001 8.48 0.91 0.97 0.73 f__Alcaligenaceae 0.0001 0.0004 0.0014 0.0017 0.0006 12.38 0.82 0.92 0.50 f __ [Barnesiellaceae] 0.0001 0.0004 0.0022 0.0031 0.0015 33.09 0.93 0.97 0.77 f__Methanobacteriaceae 0.0000 0.0001 0.0024 0.0027 0.0002 79.88 0.90 1.00 0.73 f__Rikenellaceae 0.0000 0.0002 0.0054 0.0033 0.0000 139.26 0.97 0.97 0.92

Analysis of bacteria-derived vesicles in the urine at genus level showed Rhizobium, Morganella, Proteus, Exiguobacterium, Acinetobacter, Pseudomonas, SMB53, Lactococcus, Coprococcus, Streptococcus, Bacteroides, Ruminococcus, Corynebacterium, Odoribacvoella, Cloribactera When developing a diagnostic model with one or more biomarkers in bacteria of Roseburia, Citrobacter, Klebsiella, Virgibacillus, Slackia, Dialister, Phascolarctobacterium, Sutterella, Halomonas, Roseomonas, and Methanobrevibacter, diagnostic performance for colon polyps was significant. 28 and FIG. 28).

Control Colon polyp t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity g__Rhizobium 0.0056 0.0056 0.0000 0.0000 0.0000 0.00 0.99 0.95 1.00 g__Morganella 0.0211 0.0295 0.0003 0.0006 0.0001 0.01 0.82 0.63 0.85 g__Proteus 0.0132 0.0192 0.0003 0.0005 0.0002 0.02 0.91 0.82 0.96 g__Exiguobacterium 0.0013 0.0026 0.0001 0.0003 0.0078 0.06 0.74 0.63 0.77 g__Acinetobacter 0.1683 0.1396 0.0152 0.0123 0.0000 0.09 0.90 0.82 0.81 g__Pseudomonas 0.1288 0.0965 0.0296 0.0195 0.0000 0.23 0.89 0.82 0.81 g__SMB53 0.0034 0.0046 0.0010 0.0010 0.0039 0.30 0.78 0.74 0.69 g__Lactococcus 0.0035 0.0039 0.0014 0.0014 0.0029 0.39 0.75 0.71 0.62 g__Coprococcus 0.0036 0.0043 0.0084 0.0047 0.0001 2.35 0.82 0.87 0.73 g__Streptococcus 0.0143 0.0122 0.0358 0.0102 0.0000 2.50 0.90 0.87 0.81 g__Bacteroides 0.0212 0.0207 0.0571 0.0217 0.0000 2.69 0.92 0.89 0.73 g __ [Ruminococcus] 0.0010 0.0015 0.0041 0.0039 0.0005 3.96 0.81 0.87 0.58 g__Corynebacterium 0.0090 0.0097 0.0367 0.0159 0.0000 4.09 0.97 0.95 0.85 g__Odoribacter 0.0002 0.0009 0.0010 0.0012 0.0050 4.31 0.82 0.92 0.54 g__Clostridium 0.0003 0.0011 0.0014 0.0015 0.0016 4.39 0.84 0.95 0.58 g__Ruminococcus 0.0030 0.0043 0.0145 0.0083 0.0000 4.84 0.91 0.89 0.73 g__Comamonas 0.0003 0.0010 0.0015 0.0020 0.0087 5.17 0.78 0.92 0.50 g__Paraprevotella 0.0002 0.0007 0.0012 0.0014 0.0010 6.62 0.85 0.92 0.62 g__Roseburia 0.0004 0.0017 0.0043 0.0029 0.0000 11.30 0.96 0.95 0.88 g__Citrobacter 0.0003 0.0005 0.0034 0.0020 0.0000 11.61 0.97 0.95 0.92 g__Klebsiella 0.0002 0.0006 0.0026 0.0042 0.0070 13.68 0.89 0.95 0.58 g__Virgibacillus 0.0000 0.0001 0.0006 0.0010 0.0074 15.87 0.75 0.92 0.42 g__Slackia 0.0000 0.0003 0.0008 0.0007 0.0000 16.11 0.88 0.95 0.65 g__Dialister 0.0005 0.0012 0.0082 0.0047 0.0000 17.52 0.95 0.97 0.85 g__Phascolarctobacterium 0.0001 0.0007 0.0023 0.0025 0.0002 18.69 0.88 0.97 0.65 g__Sutterella 0.0001 0.0003 0.0012 0.0017 0.0015 19.16 0.80 0.97 0.46 g__Halomonas 0.0001 0.0003 0.0015 0.0015 0.0001 22.99 0.91 0.95 0.73 g__Roseomonas 0.0000 0.0002 0.0026 0.0043 0.0052 78.36 0.93 0.97 0.77 g__Methanobrevibacter 0.0000 0.0000 0.0024 0.0027 0.0002 661.93 0.91 1.00 0.73

The description of the present invention set forth above is for illustrative purposes, and one of ordinary skill in the art may understand that the present invention may be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. There will be. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive.

The method for diagnosing colon tumors through bacterial metagenomic analysis according to the present invention is performed by performing bacterial metagenomic analysis using a sample derived from a subject to analyze the increase or decrease in the content of specific bacterial-derived extracellular vesicles, such as colon polyps and colon cancer. It can be used to predict and diagnose the risk of developing a tumor. Extracellular vesicles secreted by the bacteria present in the environment can be absorbed into the body and directly affect inflammation and cancer development, and colon polyps and colorectal cancer are difficult to diagnose effectively because they are difficult to diagnose early. Predicting the risk of colon tumors such as colorectal polyps and colorectal cancer through metagenomic analysis of bacterial or bacterial-derived extracellular vesicles using a human-derived sample according to the present invention, early diagnosis and prediction of risk groups of colon tumors and appropriate management By delaying the onset time or preventing the onset, and after the onset can be diagnosed early can reduce the incidence of colon tumors and increase the treatment effect. In addition, the bacterial metagenomic analysis according to the present invention in patients diagnosed with colorectal polyps or colon cancer improves the progression of colon polyps and colorectal cancer or prevents recurrence by predicting the causative factors and avoiding exposure to the causative factors. It is available.

Claims (16)

Information providing method for the diagnosis of colorectal tumor, comprising the following steps: (a) extracting DNA from extracellular vesicles isolated from a subject sample; (b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And (c) comparing the increase and decrease of the bacterial-derived extracellular vesicles in the normal-derived colorectal cancer-derived sample by sequencing the PCR product; or Comparing the increase and decrease of the bacterial-derived extracellular vesicles in the colon-derived patient and the colon cancer-derived sample by sequencing the PCR product; or Comparing the increase and decrease of the content of bacterial-derived extracellular vesicles in the sample derived from normal people and colon polyps through the sequencing of the PCR product. The method of claim 1, In the step (c), the colorectal cancer is diagnosed by comparing the increase and decrease of the bacterial-derived extracellular vesicles in the sample derived from normal people and colon cancer patients by sequencing the PCR product, information providing method . The method of claim 2, (C) at least one phylum bacteria-derived extracellular vesicle selected from the group consisting of Deferribacteres, Tenericutes, Actinobacteria, Acidobacteria, Armatimonadetes, Planctomycetes, Fusobacteria, Proteobacteria, and Euryarchaeota, One or more species of cells derived from the group consisting of Deferribacteres, Mollicutes, 4C0d-2, Bacilli, Alphaproteobacteria, Saprospirae, Fimbriimonadia, Acidobacteria-6, Solibacteres, Coriobacteriia, Oscillatoriophycideae, Fusobacteriia, Gammaproteobacteria, Clostridia, and Methanobacteria Out parcel, RF32, YS2, Deferribacterales, Turicibacterales, RF39, Oceanospirillales, Rhizobiales, Lactobacillales, Rhodobacterales, Saprospirales, Sphingomonadales, Fimbriimonadales, iii1-15, Solibacterales, Coriobacteriales, Chroococcales, Fusobacteriales, Bd One or more order bacterial derived extracellular vesicles selected from the group consisting of: Peptococcaceae, Deferribacteraceae, Turicibacteraceae, Halomonadaceae, Clostridiaceae, Prevotellaceae, Peptostreptococcaceae, Rhodobacteraceae, Nocardioidaceae, Sphingomonadaceae, Bartonellaceae, Cellulomonadaceae, Lactobacillaceae, Rhizobiaceae, Fimbriimonadaceae, Dermacoccaceae, Leptotrichiaceae, Coriobacteriaceae, Xenococcaceae, Aeromonadaceae, Geodermatophilaceae, Bdellovibrionaceae, Moraxellaceae, Pseudomonadaceae, Streptococcaceae, One or more family or small family cells from the group consisting of Veillonellaceae, Bacteroidaceae, Aerococcaceae, Comamonadaceae, Paraprevotellaceae, Christensenellaceae, Ruminococcaceae, Corynebacteriaceae, Gordoniaceae, Mycobacteriaceae, Desulfovibrionaceae, Alcaligenaceae, Barnesiellaceae, Methanobacteriaceae, and Rikenellaceae rc4-4, Proteus, Catenibacterium, Mucispirillum, Eubacterium, Turicibacter, Alloiococcus, Halomonas, Prevotella, Dialister, Anaerostipes, SMB53, Faecalibacterium, Blautia, Capnocytophaga, Sphingomonas, Lactobacillus, Fimbriicus, Achromobacus, Achromobacsium, Achromobacsium Bdellovibrio, Alkanindiges, Roseateles, Shuttleworthia, Rhizobium, Morganella, Acinetobacter, Pseudomonas, Enterococcus, Lactococcus, Coprococcus, Bacteroides, Dorea, Streptococcus, Lachnospira, Ruminococcus, Corynebacteria, Comamocobacterium, Comamocobacterium, Lacosebacteria, Mycobacterium terpenia An information providing method, characterized by comparing the increase or decrease in the content of one or more genus bacterial-derived extracellular vesicles selected from the group consisting of Sutterella, Virgibacillus, Eggerthella, Citrobacter, Roseomonas, Serratia, Methanobrevibacter, and Bilophila. The method of claim 1, In the step (c), the colon product is diagnosed through comparing the increase or decrease in the amount of bacterial-derived extracellular vesicles in the colon-derived patient and colorectal cancer-derived sample by sequencing the PCR product, information How to Provide. The method of claim 4, wherein In the step (c) Spirochaetes phylum bacteria-derived extracellular vesicles, One or more class bacterial-derived extracellular vesicles selected from the group consisting of Spirochaetes, and Acidobacteria-6, One or more order bacterial extracellular vesicles selected from the group consisting of Spirochaetales, and Myxococcales, Extracellular vesicles derived from one or more family bacteria selected from the group consisting of Spirochaetaceae, and S24-7, or An information providing method, characterized by comparing the increase or decrease in the content of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of Treponema, Dialister, Oscillospira, and Eubacterium. The method of claim 1, In the step (c), the colon polyps are diagnosed by comparing the increase and decrease of the bacterial-derived extracellular vesicles in the sample from the normal and colon polyps patient through the sequencing of the PCR product, information providing method . The method of claim 6, (C) at least one phylum bacteria-derived extracellular vesicles selected from the group consisting of Actinobacteria, Proteobacteria, and Euryarchaeota, One or more class bacterial-derived extracellular vesicles selected from the group consisting of Betaproteobacteria, Solibacteres, Gammaproteobacteria, Clostridia, Methanobacteria, and 4C0d-2, One or more order bacterial-derived extracellular vesicles selected from the group consisting of Burkholderiales, Sphingomonadales, Solibacterales, Stramenopiles, Pseudomonadales, Clostridiales, Oceanospirillales, Desulfovibrionales, and Methanobacteriales, Group consisting of Rhizobiaceae, Sphingomonadaceae, Exiguobacteraceae, Moraxellaceae, Pseudomonadaceae, Streptococcaceae, Peptostreptococcaceae, Comamonadaceae, Veillonellaceae, Bacteroidaceae, Paraprevotellaceae, Ruminococcaceae, Corynebacteriaceae, Christensenellaceae, Odoribacteraceae, Deofolioaceae, Deofolioaceae Extracellular vesicles derived from abnormal families, or Sphingomonas, Alkanindiges, Roseateles, Rhizobium, Morganella, Proteus, Exiguobacterium, Acinetobacter, Pseudomonas, SMB53, Lactococcus, Coprococcus, Streptococcus, Bacteroides, Ruminococcus, Corynebacterium, Odoribacter, Clonastriia Triacerocitra, Clonastriia Viracerosia, Clonastriia psi An information providing method, characterized by comparing the increase or decrease in the content of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of Dialister, Phascolarctobacterium, Sutterella, Halomonas, Roseomonas, and Methanobrevibacter. The method of claim 1, The subject sample is characterized in that the feces or urine, information providing method. Colon tumor diagnosis method comprising the following steps: (a) extracting DNA from extracellular vesicles isolated from a subject sample; (b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And (c) comparing the increase and decrease of the bacterial-derived extracellular vesicles in the normal-derived colorectal cancer-derived sample by sequencing the PCR product; or Comparing the increase and decrease of the bacterial-derived extracellular vesicles in the colon-derived patient and the colon cancer-derived sample by sequencing the PCR product; or Comparing the increase and decrease of the content of bacterial-derived extracellular vesicles in the sample derived from normal people and colon polyps through the sequencing of the PCR product. The method of claim 9, In the step (c), colon cancer is diagnosed by comparing the increase and decrease of the bacterial-derived extracellular vesicles in the sample derived from normal people and colon cancer patients by sequencing the PCR product, colon tumor diagnosis Way. The method of claim 10, (C) at least one phylum bacteria-derived extracellular vesicle selected from the group consisting of Deferribacteres, Tenericutes, Actinobacteria, Acidobacteria, Armatimonadetes, Planctomycetes, Fusobacteria, Proteobacteria, and Euryarchaeota, One or more species of cells derived from the group consisting of Deferribacteres, Mollicutes, 4C0d-2, Bacilli, Alphaproteobacteria, Saprospirae, Fimbriimonadia, Acidobacteria-6, Solibacteres, Coriobacteriia, Oscillatoriophycideae, Fusobacteriia, Gammaproteobacteria, Clostridia, and Methanobacteria Out parcel, RF32, YS2, Deferribacterales, Turicibacterales, RF39, Oceanospirillales, Rhizobiales, Lactobacillales, Rhodobacterales, Saprospirales, Sphingomonadales, Fimbriimonadales, iii1-15, Solibacterales, Coriobacteriales, Chroococcales, Fusobacteriales, Bd One or more order bacterial derived extracellular vesicles selected from the group consisting of: Peptococcaceae, Deferribacteraceae, Turicibacteraceae, Halomonadaceae, Clostridiaceae, Prevotellaceae, Peptostreptococcaceae, Rhodobacteraceae, Nocardioidaceae, Sphingomonadaceae, Bartonellaceae, Cellulomonadaceae, Lactobacillaceae, Rhizobiaceae, Fimbriimonadaceae, Dermacoccaceae, Leptotrichiaceae, Coriobacteriaceae, Xenococcaceae, Aeromonadaceae, Geodermatophilaceae, Bdellovibrionaceae, Moraxellaceae, Pseudomonadaceae, Streptococcaceae, One or more family or small family cells from the group consisting of Veillonellaceae, Bacteroidaceae, Aerococcaceae, Comamonadaceae, Paraprevotellaceae, Christensenellaceae, Ruminococcaceae, Corynebacteriaceae, Gordoniaceae, Mycobacteriaceae, Desulfovibrionaceae, Alcaligenaceae, Barnesiellaceae, Methanobacteriaceae, and Rikenellaceae rc4-4, Proteus, Catenibacterium, Mucispirillum, Eubacterium, Turicibacter, Alloiococcus, Halomonas, Prevotella, Dialister, Anaerostipes, SMB53, Faecalibacterium, Blautia, Capnocytophaga, Sphingomonas, Lactobacillus, Fimbriicus, Achromobacus, Achromobacsium, Achromobacsium Bdellovibrio, Alkanindiges, Roseateles, Shuttleworthia, Rhizobium, Morganella, Acinetobacter, Pseudomonas, Enterococcus, Lactococcus, Coprococcus, Bacteroides, Dorea, Streptococcus, Lachnospira, Ruminococcus, Corynebacteria, Comamocobacterium, Comamocobacterium, Lacosebacteria, Mycobacterium terpenia A method for diagnosing colon tumors, characterized by comparing the increase or decrease in the content of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of Sutterella, Virgibacillus, Eggerthella, Citrobacter, Roseomonas, Serratia, Methanobrevibacter, and Bilophila. The method of claim 9, In the step (c), colon cancer is diagnosed by comparing the increase and decrease of the bacterial-derived extracellular vesicles in the sample from the colon polyps and colon cancer patients through the sequencing of the PCR product, colon Tumor diagnostic method. The method of claim 12, In the step (c) Spirochaetes phylum bacteria-derived extracellular vesicles, One or more class bacterial-derived extracellular vesicles selected from the group consisting of Spirochaetes, and Acidobacteria-6, One or more order bacterial extracellular vesicles selected from the group consisting of Spirochaetales, and Myxococcales, Extracellular vesicles derived from one or more family bacteria selected from the group consisting of Spirochaetaceae, and S24-7, or A method for diagnosing colorectal tumors, comprising comparing the increase or decrease of the content of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of Treponema, Dialister, Oscillospira, and Eubacterium. The method of claim 9, In step (c), colon polyps are diagnosed by comparing the increase and decrease of the bacterial-derived extracellular vesicles in the sample derived from normal people and colon polyps through sequencing the PCR product. Way. The method of claim 14, (C) at least one phylum bacteria-derived extracellular vesicles selected from the group consisting of Actinobacteria, Proteobacteria, and Euryarchaeota, One or more class bacterial-derived extracellular vesicles selected from the group consisting of Betaproteobacteria, Solibacteres, Gammaproteobacteria, Clostridia, Methanobacteria, and 4C0d-2, One or more order bacterial-derived extracellular vesicles selected from the group consisting of Burkholderiales, Sphingomonadales, Solibacterales, Stramenopiles, Pseudomonadales, Clostridiales, Oceanospirillales, Desulfovibrionales, and Methanobacteriales, Group consisting of Rhizobiaceae, Sphingomonadaceae, Exiguobacteraceae, Moraxellaceae, Pseudomonadaceae, Streptococcaceae, Peptostreptococcaceae, Comamonadaceae, Veillonellaceae, Bacteroidaceae, Paraprevotellaceae, Ruminococcaceae, Corynebacteriaceae, Christensenellaceae, Odoribacteraceae, Deofolioaceae, Deofolioaceae Extracellular vesicles derived from abnormal families, or Sphingomonas, Alkanindiges, Roseateles, Rhizobium, Morganella, Proteus, Exiguobacterium, Acinetobacter, Pseudomonas, SMB53, Lactococcus, Coprococcus, Streptococcus, Bacteroides, Ruminococcus, Corynebacterium, Odoribacter, Clonastriia Triacerocitra, Clonastriia Viracerosia, Clonastriia psi A method for diagnosing colon tumors, characterized by comparing the increase or decrease in the content of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of Dialister, Phascolarctobacterium, Sutterella, Halomonas, Roseomonas, and Methanobrevibacter. The method of claim 9, The subject sample is characterized in that the feces or urine, colon tumor diagnosis method.

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