CN112725457B - Intestinal flora marker for judging intestinal cancer and detection method thereof - Google Patents
Intestinal flora marker for judging intestinal cancer and detection method thereof Download PDFInfo
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Abstract
The invention discloses an intestinal flora marker for judging intestinal cancer and a detection method thereof, and the method comprises the steps of extracting DNA of excrement, constructing a 16SrRNA gene library of intestinal flora, and performing high-throughput sequencing on the library; splicing data obtained after library sequencing, filtering to remove primer and chimera sequences, carrying out OTU clustering and species annotation to obtain species diversity and species abundance in intestinal flora; and 4 genera are selected from the 10 top-abundance species selected at the genus level, and the differentiation effect of the combined diagnosis of the specific flora on cancer patients and healthy people is detected by respectively making an ROC curve by using binary logistic regression. According to the method, the intestinal flora marker for judging the intestinal cancer and the detection method thereof assist in diagnosing the intestinal cancer from the perspective of the intestinal flora and provide reference for monitoring the curative effect of the intestinal cancer; other diagnosis bases can be combined, and the diagnosis effect is further guaranteed.
Description
Technical Field
The invention relates to the technical field of microorganisms and genetic engineering, in particular to an intestinal flora marker for judging intestinal cancer and a detection method thereof.
Background
At present, the total incidence rate of malignant tumors of colorectal cancer in China is 8.8%, and the mortality rate is 6.8%. In recent years, the incidence rate of colorectal cancer in China is increasing at a rate of 4%, and the death rate of malignant tumors in China is leaping to the fifth place. At the present stage, the treatment method of colorectal cancer mainly depends on operations, and radiotherapy and chemotherapy are not ideal. Moreover, most tumors are found to be in an advanced stage, and relapse easily occurs after operation and the adjuvant therapy effect is not ideal. In addition, the 5-year survival rate of colorectal cancer patients after distant metastasis is only about 12%, but the 5-year survival rate of early colorectal cancer can reach 90%. Therefore, the discovery and search of colorectal cancer tumor markers are imminent. The existing research shows that intestinal microorganisms can influence the occurrence of intestinal cancer in various ways and play an important role in the occurrence and development processes of the intestinal cancer.
In the human gut, there are a large number of microorganisms, which in addition to the traditional intestinal flora include archaea, viruses and protozoa, of which more than 98% are bacteria, collectively known as the gut flora. The normal intestinal flora has 500-1500 different subclasses, most of which are anaerobes, and from the genetic level, the human self genes carry 2.5 ten thousand genes, while the total number of genes biologically coded by the human intestinal flora is about 150 times of the total number of the human self genes, and the genes are regarded as human 'second genome'.
Therefore, the establishment of the relationship between the intestinal microorganisms and the intestines is researched, the accuracy of intestinal cancer diagnosis can be expected to be improved based on an intestinal cancer diagnosis model of the intestinal microorganisms, early discovery, early diagnosis and early treatment can be carried out, and the effect of intestinal cancer treatment can be improved by adjusting intestinal flora.
Disclosure of Invention
The invention aims to: the intestinal cancer detection method is provided from the perspective of intestinal flora, and provides reference for auxiliary diagnosis and curative effect monitoring of intestinal cancer.
The technical scheme adopted by the invention is as follows:
intestinal cancer intestinal flora markers include at least one of Streptococcus, Muospira, Bacteroides and Proteus.
In a further improvement scheme of the invention, the intestinal flora marker is applied to preparation of an individual disease risk detection kit.
In a further improvement scheme of the invention, the detection kit comprises an intestinal flora DNA extraction reagent, a specific primer for intestinal 16SrRNA gene variable region amplification, a library construction reagent and a sequencing reagent.
In a further improvement of the invention, the application method comprises sequencing of the 16SrRNA gene of the intestinal flora, analysis of sequencing data and preparation of an ROC curve by using a specific flora.
In a further improved scheme of the invention, the sequencing method of the intestinal flora 16SrRNA gene comprises the steps of extracting excrement DNA, constructing an intestinal flora 16SrRNA gene library and carrying out high-throughput sequencing on the library.
According to a further improved scheme of the invention, the analysis method of the sequencing data comprises the steps of splicing the data obtained after sequencing the library, filtering to remove primer and chimera sequences, and carrying out OTU clustering and species annotation to obtain species diversity and species abundance in intestinal flora.
The further improvement scheme of the invention is that 4 genera are selected from the species with the abundance ranking of top 10 at the genus level, and the joint diagnosis of the ROC curve detection specific flora is respectively made by applying binary logistic regression to distinguish the cancer patients from the healthy people.
In a further improvement of the invention, the intestinal flora marker is applied to preparation of an intestinal prognosis detection kit.
The detection method of the intestinal flora marker for judging intestinal cancer comprises the following steps:
1) sequencing the 16SrRNA gene of the intestinal flora;
the method comprises the following steps:
1.1) extracting excrement DNA;
1.2) constructing an intestinal flora 16SrRNA gene library;
1.3) high throughput sequencing of the library;
2) analyzing sequencing data;
the method comprises the following steps:
2.1) splicing the data obtained after library sequencing;
2.2) filtering to remove primer and chimera sequences;
2.3) OTU clustering and species annotation;
2.4) obtaining species diversity and species abundance in intestinal flora;
3) preparing an ROC curve by using the detection flora;
the method comprises the following steps:
3.1) selecting 4 strains from the species with the abundance ranking of the top 10 at the genus level as detection floras, and respectively making ROC curves by using binary logistic regression;
3.2) carrying out combined diagnosis according to the ROC curve of the selected detection flora.
According to a further improvement scheme of the invention, in the step 1.1), a centrifugal column method is adopted to extract the DNA of the excrement sample; the method comprises the following steps:
1.1.1) column equilibration: adding 500ul of equilibrium buffer EQ into the adsorption column MPL placed in the collection pipe, centrifuging for 30-80 sec within the rotation speed range of 10000-15000 rpm, pouring off waste liquid in the collection pipe, and placing the adsorption column MPL back into the collection pipe again;
1.1.2) weighing 180-220 mg of a fecal sample into a first centrifuge tube, and placing the first centrifuge tube on ice;
1.1.3) adding 1.2ml of buffer solution GSL into a first centrifuge tube in which the excrement sample is stored, and intermittently oscillating for at least 10min until the sample is uniformly mixed;
1.1.4) incubating the first centrifuge tube at a temperature of 70 ℃ for 10 min;
1.1.5) centrifuging the first centrifuge tube for 10min in a rotating speed range of 10000-15000 rpm, and carrying out vortex vibration for 15sec every 2-3 min; after centrifugation, 700ul of supernatant was transferred to a second centrifuge tube;
1.1.6) adding 700ul of HTR reagent into a second centrifuge tube, and reversely mixing for 15-30 times until uniformly mixing;
1.1.7) centrifuging the second centrifugal tube for 5min at the rotating speed range of 10000-15000 rpm at room temperature, and transferring 500ul of supernate to a third centrifugal tube;
1.1.8) adding 20ul of protease K and 500ul of Buffer GB into the supernatant in a third centrifuge tube, and reversing and uniformly mixing for 5-15 times until uniformly mixing;
1.1.9) incubating the third centrifuge tube at a temperature of 70 ℃ for 10 min;
1.1.10) adding 500ul of absolute ethyl alcohol into a third centrifuge tube, and reversing and uniformly mixing for 5-15 times until uniformly mixing;
1.1.11) adding half of the solution obtained in the previous step into an adsorption column MPL placed in a collecting pipe, centrifuging for 1min within the rotating speed range of 10000-15000 rpm, pouring the waste liquid in the collecting pipe, and placing the adsorption column MPL in the collecting pipe; transferring the remaining mixture to an adsorption column MPL and centrifuging again;
1.1.12) adding 500ul of buffer GD into the adsorption column MPL, centrifuging for 1min within the rotation speed range of 10000 rpm-15000 rpm, pouring the waste liquid in the collecting pipe, and then putting the adsorption column MPL into the collecting pipe;
1.1.13) adding 600ul of rinsing liquid SPW into the adsorption column MPL, centrifuging for 1min within the rotation speed range of 10000 rpm-15000 rpm, pouring the waste liquid in the collecting pipe, and then putting the adsorption column MPL into the collecting pipe;
1.1.14) repeating step 1.1.13) until the residual rinsing liquid in the adsorption column MPL is removed;
1.1.15) placing the adsorption column MPl in a fourth centrifuge tube, dripping 50ul of elution buffer TB into the middle part of the adsorption membrane, placing for 2-5 min at room temperature, then centrifuging for 2min within the rotation speed range of 10000-15000 rpm, and finally collecting the solution.
In a further development of the invention, step 1.2) comprises the following steps:
1.2.1) designing a primer;
specific primers are designed aiming at the V4 region of the 16Sr RNA gene, and the specific sequences are as follows:
an upstream primer F:
5’-GTGCCAGCMGCCGCGGTAA-3’，
a downstream primer R:
5’-GGACTACHVGGGTWTCTAAT-3’；
1.2.2) PCR amplification:
1.2.2.1) PCR reaction 50 ul: 25 mul of High-Fidelity enzyme is Phusion High-Fidelity PCR Master Mix with HF Buffer; F/R primers before and after 3. mu.l each; 10 μ l DNA template 6 μ l ddH 2O;
1.2.2.2) carrying out PCR amplification by the prepared PCR system according to the following reaction conditions: pre-denaturation 98 ℃ for 30s, followed by 25 cycles: denaturation at 98 ℃ for 15s, annealing at 58 ℃ for 15s, elongation at 72 ℃ for 15s, and final elongation at 72 ℃ for 1 min;
1.2.2.3) after the reaction is finished, taking a 2 mu LPCR product to perform agarose gel electrophoresis, wherein the PCR product is about 500 bp; electrophoresis conditions are as follows: 1% Agarose, D2000 ladder, 120V, 20 min;
1.2.3) PCR product purification:
1.2.3.1) taking out AMPure XP magnetic beads from a refrigerator at 4 ℃ in advance, balancing for 30min at room temperature, and shaking and mixing uniformly before use; preparing 80% ethanol in a fresh state;
1.2.3.2) taking a new 1.5mL EP tube, adding 18.4 muL magnetic beads after marking, then adding the PCR product of the previous step, blowing and beating for 10 times, uniformly mixing to ensure that no bubbles are generated, and standing for 5min at room temperature;
1.2.3.3) centrifuging, and then placing the centrifugal tube on a magnetic frame for 10min until the liquid is clear;
1.2.3.4) carefully remove the supernatant, taking care not to attract beads as much as possible;
1.2.3.5) keeping an EP tube on a magnetic frame, slowly adding 200 mu l 80% ethanol into the EP tube for adherence, standing for 30sec after sucking and beating, and removing a supernatant;
1.2.3.6) washing is repeated once, and any residual ethanol is removed as far as possible when the supernatant is removed;
1.2.3.7) keeping the EP tube on a magnetic frame, standing at room temperature for 4min, and drying the magnetic beads;
1.2.3.8), adding 32 mu L of Resuspension Buffer, blowing and uniformly mixing magnetic beads by using a gun, and then standing for 2min at room temperature;
1.2.3.9) instantly centrifuging, and putting the centrifugal tube on a magnetic frame until the liquid is clear;
1.2.3.10) transfer 30 μ L of supernatant into a new labeled 1.5ml centrifuge tube.
In a further improvement scheme of the invention, the step 1.3) adopts Illlumina HiSeq4000 pair-end 2 × 150 bp platform sequencing, which comprises the following steps:
1.3.1) quantification using PicoGreendsDNA, Assay Kit;
1.3.2) library was tested for band distribution using an Agilent 2200High Sensitivity Dl OOOkit.
In a further improvement of the invention, the 2.1) comprises the following steps:
splitting each sample data from the off-line data according to the Barcode sequence, cutting off the Barcode, and splicing the reads of each sample by using FLASH to obtain a spliced sequence which is the original Tags data.
According to a further improvement scheme of the invention, in the step 2.2), the Tags data obtained by splicing in the step 2.1) is filtered to obtain high-quality vignetting Tags data; referring to the Tags quality control flow of QII ME, the filtering process comprises the following steps:
2.2.1) Tags interception:
truncating the tag data from the continuous low-mass value base number to the first low-mass base site with the set length;
2.2.2) Tags Length filtration:
the Tags data set obtained by intercepting the Tags is further filtered to filter out continuous high-quality bases with the length smaller than that of the Tags
Tags 75% in length;
2.2.3) removing primers and chimeras from the Tags obtained by the treatment;
2.2.4) use Mothur filtration process to get high quality reads, followed by further removal of chimeric sequences.
In a further development of the invention, the step 2.3) comprises the following steps:
2.3.1) clustering samples subjected to data processing by utilizing Mothur software, defaulting to cluster sequences into OTUs with 97% consistency, selecting representative sequences of the OTUs, and screening the sequences with the highest occurrence frequency in the OTUs as the representative sequences of the OTUs according to the algorithm principle;
2.3.2) species annotation of OTUs representative sequences, species annotation analysis with Mothur method and SILVA's SSUrRNA database, taxonomic information was obtained and at each taxonomic level: and (4) counting community composition of each sample according to kingdom, phylum, class, order, family, genus and species.
In a further development of the invention, step 2.4) comprises the following steps:
and (3) selecting the species with the maximum half degree ranking of top 10 on each classification level of each sample or group according to the species annotation result, generating a relative intermediate column accumulation chart of the species, and checking the species with high relative abundance and the proportion thereof of each sample on different classification levels.
In a further development of the invention, step 3.1) comprises the following steps:
3.1.1) sequentially arranging the OTUs in each sample according to the abundance values along the abscissa, taking the respective abundance values as the ordinate, and mutually connecting the OTUs by using a broken line to draw a curve graph;
3.1.2) according to step 3.1.1), selecting the species with the top abundance ranking 10 at the gate level for each sample or group and drawing a relative abundance histogram;
3.1.3) selecting the species with the top abundance ranking 10 at the genus level according to the step 3.1.2) to draw a relative abundance pie chart;
3.1.4) selecting 4 genera from the species with the abundance ranking of top 10 according to the step 3.1.3) at the genus level, and respectively making ROC curves by using binary logistic regression.
In a further development of the invention, the step 3.2) comprises the following steps:
classification using a combined bacteroidetes and prevotella model in bacteroidetes, or streptococcus and pileus in firmicutes, according to the graphs obtained in step 3.1) is used for auxiliary diagnosis or for joint diagnosis in combination with other data.
Intestinal cancer intestinal flora markers include one or more of Streptococcus, Muospira, Bacteroides and Proteus. The intestinal flora marker is applied to the preparation of an individual disease risk detection kit. The detection kit comprises an intestinal flora DNA extraction reagent, a specific primer for intestinal 16SrRNA gene variable region amplification, a library construction reagent and a sequencing reagent.
The invention has the beneficial effects that:
the intestinal flora marker for judging intestinal cancer and the detection method thereof assist in diagnosing intestinal cancer from the perspective of intestinal flora and also provide reference for monitoring the curative effect of intestinal cancer; and other diagnostic bases can be combined, so that the diagnostic effect is further ensured.
Description of the drawings:
FIG. 1 is a graph of abundance levels (Rank abundance curve).
Abundance grade curves of normal group (N), tumor group (T) and each stage (I, II, III, IV).
FIG. 2 is a plot of the intersample species abundance at the gate level.
FIG. 3 is a genus-level inter-sample speciation abundance map.
FIG. 4 is a genus-level inter-sample speciation abundance table.
FIG. 5 is a chart of generic ROC.
FIG. 6 is a genus level ROC table.
The specific implementation mode is as follows:
first, establishing library and sequencing of intestinal flora 16SrRNA gene
1 sample origin
Total DNA was extracted from fresh stools of 124 intestinal cancer patients and 131 healthy people.
2 extraction of DNA from stool samples
Extracting DNA of the excrement sample by adopting a centrifugal column method:
(1) column balancing: adding 500ul of equilibrium buffer EQ (Buff erEQ) into an adsorption column MPL (the adsorption column is placed into a collecting pipe), centrifuging at 12,000rpm for 1min, pouring out waste liquid in the collecting pipe, and placing the adsorption column back into the collecting pipe again;
(2) weighing 180-220 mg of a fecal sample into a 2ml centrifuge tube, and placing the tube on ice;
(3) adding 1.2ml of buffer solution GSL into the sample, and intermittently oscillating for 1l min until the sample is uniformly mixed;
(4) incubating at 70 deg.C for 10 min;
(5) vortex for 15sec, centrifuge at 12,000rpm for 10 min. Transferring 700ul of the supernatant to a new 2ml centrifuge tube;
(6) adding 700ul of HTR reagent, and reversing and uniformly mixing for 15-30 times;
(7) centrifuging at room temperature at 12,000rpm for 5min, and transferring 500ul of supernatant into a 2.0 ml centrifuge tube;
(8) adding 20ul of protease K and 500ul of Buffer GB into the supernatant, and reversing and mixing uniformly for 10 times;
(9) incubating at 70 deg.C for 10 min;
(100 add 500ul absolute ethyl alcohol, reverse mixing 10 times;
(11) adding half of the solution obtained in the previous step into an adsorption column MPL (the adsorption column is placed into a collection pipe), centrifuging at 12,000rpm for 1min, pouring off the waste liquid in the collection pipe, and placing the adsorption column MPL into the collection pipe; transferring the remaining mixture to a column and centrifuging;
(12) adding 500ul of GD (buffer solution) into the adsorption column MPL, centrifuging at 12,000rpm for 1min, pouring off waste liquid in the collection pipe, and putting the adsorption column MPL into the collection pipe;
(13) adding 600ul of rinsing liquid SPW into the adsorption column MPL, centrifuging at 12,000rpm for 1min, pouring off waste liquid in the collection pipe, and placing the adsorption column MPL into the collection pipe;
(14) repeating the operation step (13);
(15) placing the adsorption column MPl into a collecting tube, and centrifuging at 12,000rpm for 2min to remove residual rinsing liquid in the adsorption column;
(16) placing the adsorption column MPl in a clean centrifuge tube, adding 50ul of elution buffer TB dropwise to the middle part of the adsorption membrane, standing at room temperature for 2-5 min, centrifuging at 12,000rpm for 2min, and collecting the solution in the centrifuge tube.
3 library construction
3.1 primer design
Specific primers are designed aiming at the V4 region of the 16Sr RNA gene, and the specific sequences are as follows:
an upstream primer F:
5’- GTGCCAGCMGCCGCGGTAA -3’；
a downstream primer R:
5’-GGACTACHVGGGTWTCTAAT-3’。
3.2 PCR amplification
A) PCR reaction system 50 ul: mu.l of the High Fidelity enzyme used was Phusion High-Fidelity PCR Master Mix with HF Buffer. Each 3. mu.l (10 uM) of the F/R primers was used. 10 μ l DNA template 6 μ l ddH 2O;
B) the prepared PCR system carries out PCR amplification according to the following reaction conditions: pre-denaturation 98 ℃ for 30s, followed by 25 cycles: denaturation at 98 deg.C, 15s annealing at 58 deg.C for 15s, extension at 72 deg.C for 15s, and final extension at 72 deg.C for 1 min;
C) after the reaction is finished, 2 mu LPCR products are taken for agarose gel electrophoresis, and the PCR products are about 500 bp. Electrophoresis conditions: 1% Agarose, D2000 ladder, 120V, 20 min.
3.3 PCR product purification
A) Taking out AMPure XP magnetic beads from a refrigerator at 4 ℃ in advance, balancing for 30min at room temperature, and shaking and mixing uniformly before use. Preparing 80% ethanol in fresh;
B) taking a new 1.5mL EP tube, adding 18.4 muL magnetic beads after marking, then adding the PCR product of the previous step, blowing and beating for 10 times (Rl = 0.8: 1) and uniformly mixing, taking care that bubbles are not generated, and standing for 5min at room temperature;
C) after centrifugation, placing the centrifugal tube on a magnetic frame for 10min until the liquid is clear;
D) carefully remove the supernatant, take care not to attract beads as much as possible;
E) keeping the EP tube on a magnetic frame, slowly adding 200 mul 80% ethanol to the EP tube in an adherence manner, standing for 30sec after sucking and beating, and removing supernatant;
F) washing is repeated once, and any residual ethanol is removed as far as possible when supernatant is removed;
G) keeping the EP tube on a magnetic frame, standing for 4min at room temperature, and drying the magnetic beads;
H) adding 32 mu L of Resuspension Buffer, blowing and uniformly mixing the magnetic beads by using a gun, and then standing for 2min at room temperature;
I) after instantaneous centrifugation, putting the centrifugal tube on a magnetic frame until the liquid is clear;
J) transfer 30 μ L of supernatant to a new labeled 1.5ml centrifuge tube.
3.6 library quality testing
A) Quantification was performed using PicoGreendsDNA, Assay Kit (Invitrogen, Carlsbad, Calif., USA).
B) The library was examined for band distribution using Ag i l ent 2200High Sensitivity Dl OOOk i t.
3.7 sequencing results
The sequence was determined using the Illlumina HiSeq4000 pair-end 2X 150 bp platform.
Second, analysis of sequencing data
1 sequencing data splicing
Splitting each sample data from the off-line data according to the Barcode sequence, splicing reads of each sample by using FLASH after the Barcode is cut off, and obtaining a splicing sequence which is original Tags data (RawTags); and (4) strictly filtering the spliced RawTags to obtain Tags data (CleanTags) with high-quality halos. Referring to the Tags quality control flow of QII ME, the following operations are carried out:
A) and (5) intercepting Tags: truncating RawTags from the first low-quality base site with the number of bases reaching a set length (the default length value is 3) of continuous low-quality values (the default quality threshold value is ≦ 19);
B) tags length filtration: and (3) further filtering the Tags data set obtained by intercepting the Tags, wherein the length of the continuous high-quality base is less than 75% of the length of the Tags. Primers and chimeras were removed from the Tags obtained by the above treatment.
2 sequencing data processing
And (4) obtaining high-quality reads by using Mothur filtering treatment, and then further removing the chimera sequence to complete the treatment of the sequencing data.
3 OTU clustering and species annotation
Clustering samples subjected to data processing by using Mothur software, defaulting to cluster sequences into OTUs (operational taxonomicunits) by 97% of consistency (identity), selecting representative sequences of the OTUs at the same time, and screening the sequences with the highest frequency of occurrence in the OTUs as the representative sequences of the OTUs according to the algorithm principle. Species annotation was performed on OTUs representative sequences, species annotation analysis was performed using the mortur method with the SSUrRNA database of SILVA (setting threshold 0.8-1), and taxonomic information was obtained and separately at each classification level: kingdom, phylum, class, order, f a mil, genus, species, and statistics of community composition of each sample.
And according to the species annotation result, selecting the species with the maximum half degree ranking of top 10 on each classification level of each sample or group, and generating a relative intermediate cylindrical cumulative graph of the species so as to visually check the species with high relative abundance and the proportion thereof of each sample on different classification levels.
4 results of analysis
The OTUs in each sample were sequentially arranged along the abscissa according to their abundance values, and the respective abundance values were used as the ordinate to connect the OTUs to each other with a fold line. As shown in figure 1, the abundance of the flora in the feces of cancer patients decreased compared to the normal group, and decreased to different extents between the different stages.
Note: abundance grade curves of the flora in the normal group (N), the tumor group (T) and each stage (I, II, III and IV).
From the species annotation results, a relative abundance histogram was drawn for each sample or group of species with the top abundance ranking of 10 at the gate level. As shown in fig. 2: eurycota (Euryarchaeota), actinomycetea (actinobacillia), Bacteroidetes (Bacteroidetes), Firmicutes (Firmicutes), clostridia (Fusobacteria), Proteobacteria (Proteobacteria), syntrophic bactera (syntestes), candidate phylum (TM 7), Tenericutes (Tenericutes), Verrucomicrobia (verrucocombia) are the top 10 phylum.
And according to the species annotation result, selecting the species with the abundance ranking of top 10 at the genus level to draw a relative abundance pie chart. As shown in fig. 3 and 4: eurycota (Euryarchaeota), actinomycetea (actinobacilla), Bacteroidetes (Bacteroidetes), Firmicutes (Firmicutes), Fusobacteria (Fusobacteria), Proteobacteria (Proteobacteria), syntrophic bacteria (syntestes), candidate (TM 7), Tenericutes (Tenericutes), Verrucomicrobia (verrucocorbia) are the top 10-ranked phyla.
According to species annotation results, 4 genera are selected from the species with the abundance ranking of top 10 at the genus level, and an ROC curve is respectively made by applying binary logistic regression. As shown in fig. 5 and 6, in bacteroidetes, the classification resolution of the combined bacteroidetes and prevotella model was better than that of a single factor, and AUC values for distinguishing intestinal cancer patients from healthy people were 0.8891, 0.85, and 0.7391, respectively. In addition, in firmicutes, the classification resolution of the streptococcus and pileus combined model was better than that of a single factor, and AUC values for distinguishing intestinal cancer patients from healthy persons were 0.8499, 0.7349 and 0.8202, respectively. The results show that the combination of specific flora has a better distinguishing effect on cancer patients and healthy people.
Based on the method, an individual disease risk detection kit can be constructed and used for evaluating the intestinal cancer disease risk. The kit consists of an intestinal flora DNA extraction reagent, a specific primer for amplifying the variable region of the 16Sr RNA gene of the intestinal flora, a library construction reagent and a sequencing reagent. And a detection kit for intestinal cancer prognosis monitoring can be constructed.
In summary, species diversity, relative abundance and pathogenic bacteria related to intestinal cancer can be used as the index for auxiliary diagnosis of intestinal cancer; secondly, the colon cancer can be further diagnosed by combining a diagnosis model, or the risk of the colon cancer is evaluated, or the colon cancer is used for monitoring the prognosis of the colon cancer; thirdly, intestinal cancer patients can adjust intestinal flora balance by supplementing missing beneficial bacteria, and assist in the treatment of intestinal cancer. In addition, the intestinal cancer intestinal flora marker can also be applied to screening medicines for treating or preventing colorectal cancer.
It should be noted that, although the above description has been made in this context, the scope of the present invention is not limited thereby. Therefore, based on the innovative concepts of the present invention, the technical solutions of the present invention can be directly or indirectly applied to other related technical fields by making changes and modifications to the contents described herein, or by using equivalent structures or equivalent processes performed by the present specification and attached drawings, which are included in the patent protection of the present invention.
Claims (1)
1. The application of the intestinal flora marker in preparing an individual intestinal cancer risk detection kit is characterized in that: the gut flora marker includes a combination of streptococcus and pileus.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107904286A (en) * | 2017-12-27 | 2018-04-13 | 苏州普瑞森基因科技有限公司 | A kind of colorectal cancer microbial markers and its application |
| CN109943636A (en) * | 2019-04-11 | 2019-06-28 | 上海宝藤生物医药科技股份有限公司 | Colorectal cancer microbial marker and application thereof |
| CN110408699A (en) * | 2019-07-11 | 2019-11-05 | 福建卫生职业技术学院 | Intestinal cancer intestinal flora marker and its application |
| CN110637097A (en) * | 2017-03-17 | 2019-12-31 | 第二基因组股份有限公司 | Identification of combined biomarkers for colorectal cancer using sequence-based excreta microflora survey data |
| CN111334590A (en) * | 2020-02-20 | 2020-06-26 | 南京派森诺基因科技有限公司 | Kit for identifying colorectal cancer and application thereof |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2019018694A1 (en) * | 2017-07-19 | 2019-01-24 | Dana-Farber Cancer Institute, Inc. | Cancer diagnostic and treatment |
-
2021
- 2021-03-08 CN CN202110253184.2A patent/CN112725457B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110637097A (en) * | 2017-03-17 | 2019-12-31 | 第二基因组股份有限公司 | Identification of combined biomarkers for colorectal cancer using sequence-based excreta microflora survey data |
| CN107904286A (en) * | 2017-12-27 | 2018-04-13 | 苏州普瑞森基因科技有限公司 | A kind of colorectal cancer microbial markers and its application |
| CN109943636A (en) * | 2019-04-11 | 2019-06-28 | 上海宝藤生物医药科技股份有限公司 | Colorectal cancer microbial marker and application thereof |
| CN110408699A (en) * | 2019-07-11 | 2019-11-05 | 福建卫生职业技术学院 | Intestinal cancer intestinal flora marker and its application |
| CN111334590A (en) * | 2020-02-20 | 2020-06-26 | 南京派森诺基因科技有限公司 | Kit for identifying colorectal cancer and application thereof |
Non-Patent Citations (3)
| Title |
|---|
| Microbial Dysbiosis in Colorectal Cancer (CRC) Patients;Iradj Sobhani等;《PLoS ONE》;20110127;e16393 * |
| Structural segregation of gut microbiota between colorectal cancer patients and healthy volunteers;Tingting Wang等;《The ISME Journal》;20121031;第320-329页 * |
| 肠癌大鼠与正常大鼠粪便菌群的结构性差异;高仁元等;《世界华人消化杂志》;20140208;第661-667页 * |
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