CN114085916A - Intestinal flora marker for predicting curative effect of immunotherapy and application thereof - Google Patents
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Abstract
The invention discloses an intestinal flora marker for predicting the curative effect of immunotherapy and application thereof. The inventor screens DNA detection targets with expression difference in patients with different clinical curative effects from 55 intestinal bacteria DNA detection targets, and can solve the problems of few available biomarkers and unsatisfactory effect in melanoma immunotherapy patients. The relationship of gut flora characteristics to PD-1/PD-L1 blockade therapy may have commonalities in different classes of tumors; the research result of the project is subjected to data supplement and reanalysis, and has the possibility of being applied to tumors except melanoma, such as sarcoma, renal cancer, lung cancer, gastric cancer or colorectal cancer, and enabling patients to benefit.
Description
Technical Field
The invention relates to the field of immunotherapy, in particular to an intestinal flora marker for predicting the curative effect of immunotherapy and application thereof.
Background
Compared with the traditional treatment scheme, the immunotherapy has the advantages of long in-vivo maintenance time, small side effect and the like. Although immunotherapy has been highly successful in the treatment of tumors, its effectiveness is still low; immunotherapy has been effective at about 30% for melanoma and soft tissue sarcomas, which is not very effective compared to conventional therapies. Screening patients who can benefit from immunotherapy is the key to successful treatment, and currently, indexes which can be used for predicting the curative effect of immunotherapy include tumor PD-L1 expression level, tumor mutation load (TMB) and the like, but are not yet discussed; immunotherapy patients face the problems of few available biomarkers and unsatisfactory predictive efficacy, and how to distinguish which patients would benefit from immunotherapy is a major challenge.
The expression of PD-L1 has a certain prediction effect on the curative effect of immunotherapy, and the expression of PD-L1 is not a perfect index. Although studies have shown that patients with high expression of PD-L1 are more likely to benefit from the use of anti-PD-1/PD-L1 drugs than patients with low expression of PD-L1; however, in several studies, high expression of PD-L1 was associated with shorter survival than low expression of PD-L1[1]。
TMB (tumor statistical garden) indicates the total number of mutations present in the tumor cell genome, but as with PD-L1, TMB is still not a perfect predictor. Patients with high TMB are associated with better overall survival, but some patients have undesirable therapeutic effects despite high TMB; and the cutoff value of TMB is different among different cancers, more studies are still needed before the application of TMB to clinic[2]。
The subject groups such as Routey and Gopalakrishnan adopt metagenome sequencing technology aiming at the research of intestinal flora[3,4]. Metagenomic sequencing can comprehensively analyze intestinal flora, but the technology has the defect that bacteria are difficult to analyze to species. According to the results of sequencing studies by Routy et al, bacteria with significant statistical differences and at the species level were only seen with Akkermansia muciniphila; other differential bacteria are mostly at the phylum, family or genus level; and Firmicutes, Lachnospiraceae and Erysipelotrichaceae are both in the immunotherapeutically effective group and progression free survival<High expression in the 3 month group, which resulted in difficult pairingAnd (4) accurately judging or reading the sequencing result. Establishing a technology capable of detecting intestinal bacteria at species or genus level and serving for clinical application is the key to transforming the existing research results into application.
Real-time fluorescent Quantitative PCR (Quantitative Real-time PCR, Rt-PCR) is a method for detecting the total amount of products after each Polymerase Chain Reaction (PCR) cycle by using fluorescent chemical substances in DNA amplification reaction, and the specific DNA sequence in a sample to be detected is quantitatively analyzed by internal reference or external reference[5]. Rt-PCR has been recognized worldwide due to its good accuracy and repeatability, and is widely used in gene expression research, pathogen detection and other fields, such as quantitative detection of hepatitis B virus DNA and EBV-DNA.
Reference documents:
1.Brody R,Zhang Y,Ballas M et al.PD-L1 expression in advanced NSCLC:Insights into risk stratification and treatment selection from a systematic literature review.Lung Cancer 2017；112:200-215.
2.Choucair K,Morand S,Stanbery L et al.TMB:a promising immune-response biomarker,and potential spearhead in advancing targeted therapy trials.Cancer Gene Therapy 2020；27:841-853.
3.Routy B,Le Chatelier E,Derosa L et al.Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors.Science Cancer immunotherapy 2018；359:91-97.
4.Gopalakrishnan V,Spencer CN,Nezi L et al.Gut microbiome modulates response to anti-PD-1immunotherapy in melanoma patients.Science 2018；359:97-103.
5.Bookout AL,Cummins CL,Mangelsdorf DJ.High-Throughput Real-Time Quantitative Reverse Transcription PCR.Current Protocols in Molecular Biology 2005；15.8:1-21.
disclosure of Invention
The invention aims to overcome at least one defect of the prior art and provides a group of intestinal flora markers for predicting the curative effect of immunotherapy and an application mode thereof.
The technical scheme adopted by the invention is as follows:
in a first aspect of the present invention, there is provided:
an intestinal flora marker panel for predicting the curative effect of immunotherapy, wherein the detection targets in the intestinal flora marker panel are selected from at least 2, preferably at least 5 of the following 31 bacterial DNA targets:
the marker panel of intestinal flora can be used for predicting the curative effect of immunotherapy.
In some examples, the gut flora marker panel relates to gut bacteria DNA detection targets that are at least one of the following combinations:
combination I: cluster IV Ruminococcus spp, Bifidobacterium adolescentis, Peptostreptococcus productus, Bacteroides thetaiotaomicron, Bacteroides vulgatus, Bacteroides distassonis, Bacteroides spp, Enterococcus hirae, Akkermansia mulilina and Corynebacterium are used for 11 intestinal bacterial DNA detection targets in total;
combination C1C 3: bacilli vulgatus, bacilli distorsonius, Alleubacteria, Bifidobacterium catenulatum group, Bifidobacterium bifidum, 5 intestinal bacteria DNA detection targets in total;
combination C2C 4: fusobacterium prausnitzii, bacteriodes spp, Clostridium cluster IV, Bifidobacterium catenulatum group, Clostridium perfringens group, totaling 5 intestinal bacteria DNA detection targets;
combination AL: cluster IV Ruminococcus spp, Fusobacterium spp, 2 intestinal bacteria DNA detection targets in total;
and (3) combination V: bacteria-Prevotella-Porphyromonas, All Eubacterium, Clostridium clusterium XIVa, Butyryl-CoA-transferase gene, Clostridium coccoides-Eubacterium repeat group, totaling 5 intestinal bacterial DNA detection targets.
In some examples, the immunotherapy is a PD-1 pathway blocking therapy alone, a PD-1 pathway blocking therapy in combination with chemotherapy, or a PD-1 pathway blocking therapy in combination with targeted therapy.
In some examples, the immunotherapy is an immunotherapy of melanoma.
In some examples, the scoring formula for predicting the efficacy of immunotherapy is:
formula I: CF-186.811-2 + 500.54-11-397.623-17 + 243.817-22 + 468.598-24-564.659-25 m + 60.101-26 + 1652.688-29-1291.203-46-38.697-47-416.678-55-987.267;
formula C1C 3: CF-54.105-25 m-321.927-26 + 904.879-28-16.335-38-35.708-39-531.83;
formula C2C 4: CF 189.453 targets 21-767.437 targets 29-683.808 targets 34-15.06 targets 38-36.041 targets 42+ 1216.563;
formula AL: CF 195.493 target 2+468.221 target 43-411.411;
formula V: CF 1452.393 targets 13-2926.599 targets 28+3257.596 targets 30-1753.58 targets 36-526.748 targets 41-573.037;
in each formula, the target number refers to the relative expression quantity of a DNA detection target of the corresponding intestinal bacteria, and the relative expression quantity is determined based on an internal reference gene; preferably, the internal reference gene is the bacterial 16S rRNA V4 region.
In some examples, formula I is used to calculate the CF value for a regimen of the single agent pappalbociclib, terepril, nivaleur, or pappalbociclib combined leprima.
In some examples, formula C1C3 is used to calculate the CF value for a regimen of either pappalbociclib or terepril in combination with temozolomide.
In some examples, formula C2C4 is used to calculate the CF value for a regimen of pappalobique or terepril in combination with albumin paclitaxel.
In some examples, formula AL is used to calculate the CF value for a regimen of pappalobique or teripril in combination with antrocinib, lenvatinib or axitinib.
In some examples, formula V is used to calculate the CF value for a regimen of pappalobique or teripril in combination with vemurafenib.
In a second aspect of the present invention, there is provided:
use of a primer sequence set for predicting the efficacy of immunotherapy, said primer sequence being capable of determining the expression level of an intestinal flora marker according to the first aspect of the invention.
In some examples, the expression amount is a relative expression amount, determined based on an internal reference gene.
In some examples, the internal reference gene is the bacterial 16S rRNA V4 region.
In some examples, the immunotherapy is a PD-1 pathway blocking therapy alone, a PD-1 pathway blocking therapy in combination with chemotherapy, or a PD-1 pathway blocking therapy in combination with targeted therapy.
In some examples, the immunotherapy is an immunotherapy of melanoma.
In a third aspect of the present invention, there is provided:
a detection and analysis system for predicting the curative effect of immunotherapy comprises a relative quantification device of different detection targets of the genomic DNA of intestinal bacteria, a data analysis device and a result output device.
The relative quantification device of different detection targets of the genome DNA of the intestinal bacteria is used for determining the relative expression quantity of the intestinal flora marker in the first aspect of the invention;
the data analysis device is used for calculating a joint prediction factor CF based on the relative expression quantity;
the result output device is used for outputting a calculation result and predicting the curative effect of the immunotherapy.
In some examples, the relative expression amount is determined based on an internal reference gene.
In some examples, the internal reference gene is the bacterial 16S rRNA V4 region.
In some examples, the marker panel of gut flora is at least one of the following combinations:
combination I: cluster IV Ruminococcus spp, Bifidobacterium adolescentis, Peptostreptococcus productus, Bacteroides thetaiotaomicron, Bacteroides vulgatus, Bacteroides distassonis, Bacteroides spp, Enterococcus hirae, Akkermansia mulilina and Corynebacterium are used for 11 intestinal bacterial DNA detection targets in total;
combination C1C 3: bacilli vulgatus, bacilli distorsonius, Alleubacteria, Bifidobacterium catenulatum group, Bifidobacterium bifidum, 5 intestinal bacteria DNA detection targets in total;
combination C2C 4: fusobacterium prausnitzii, bacteriodes spp, Clostridium cluster IV, Bifidobacterium catenulatum group, Clostridium perfringens group, totaling 5 intestinal bacteria DNA detection targets;
combination AL: cluster IV Ruminococcus spp, Fusobacterium spp, 2 intestinal bacteria DNA detection targets in total;
and (3) combination V: bacteria-Prevotella-Porphyromonas, All Eubacterium, Clostridium clusterium XIVa, Butyryl-CoA-transferase gene, Clostridium coccoides-Eubacterium repeat group, totaling 5 intestinal bacterial DNA detection targets.
In some examples, the immunotherapy is a PD-1 pathway blocking therapy alone, a PD-1 pathway blocking therapy in combination with chemotherapy, or a PD-1 pathway blocking therapy in combination with targeted therapy.
In some examples, the immunotherapy is an immunotherapy of melanoma.
In some examples, the scoring formula for predicting the efficacy of immunotherapy is:
formula I: CF-186.811-2 + 500.54-11-397.623-17 + 243.817-22 + 468.598-24-564.659-25 m + 60.101-26 + 1652.688-29-1291.203-46-38.697-47-416.678-55-987.267;
formula C1C 3: CF-54.105-25 m-321.927-26 + 904.879-28-16.335-38-35.708-39-531.83;
formula C2C 4: CF 189.453 targets 21-767.437 targets 29-683.808 targets 34-15.06 targets 38-36.041 targets 42+ 1216.563;
formula AL: CF 195.493 target 2+468.221 target 43-411.411;
formula V: CF 1452.393 targets 13-2926.599 targets 28+3257.596 targets 30-1753.58 targets 36-526.748 targets 41-573.037;
in each formula, the target number refers to the relative expression amount of the DNA detection target of the corresponding intestinal bacteria, and the relative expression amount is determined based on an internal reference gene which is the 16S rRNA V4 region of the bacteria.
In some examples, formula I is used to calculate the CF value for a regimen of the single agent pappalbociclib, terepril, nivaleur, or pappalbociclib combined leprima.
In some examples, formula C1C3 is used to calculate the CF value for a regimen of either pappalbociclib or terepril in combination with temozolomide.
In some examples, formula C2C4 is used to calculate the CF value for a regimen of pappalobique or terepril in combination with albumin paclitaxel.
In some examples, formula AL is used to calculate the CF value for a regimen of pappalobique or teripril in combination with antrocinib, lenvatinib or axitinib.
In some examples, formula V is used to calculate the CF value for a regimen of pappalobique or teripril in combination with vemurafenib.
In some examples, if CF is less than 0, the corresponding immunotherapy regimen is predicted to be effective for the patient; if the resulting CF is greater than 0, the patient is predicted to be resistant to the corresponding immunotherapy regimen.
The invention has the beneficial effects that:
1) the invention takes melanoma as a research object, and selects DNA detection targets with expression difference in patients with different clinical curative effects from 55 intestinal bacteria DNA detection targets, so that the problems of few available biomarkers and unsatisfactory effect of melanoma immunotherapy patients can be solved.
2) The single detection index is difficult to effectively predict the curative effect of the immunotherapy. The inventor utilizes the advantages of large individual difference, multiple detection targets and the like of the intestinal flora, and adopts a method of jointly analyzing a plurality of DNA detection targets, so that the defect of detecting a single index can be effectively avoided.
3) The inventor firstly proposes that different combined detection targets are selected according to the types of treatment schemes, and 5 curative effect prediction models of immunotherapy schemes are established.
4) The relationship of gut flora characteristics to PD-1/PD-L1 blockade therapy may have commonalities in different classes of tumors; the research result of the project is subjected to data supplement and reanalysis, and has the possibility of being applied to tumors except melanoma, such as sarcoma, renal cancer, lung cancer, gastric cancer or colorectal cancer, and enabling patients to benefit.
Drawings
FIG. 1 is a plot of the fluorescent quantitative PCR amplification of the internal reference gene (green circle) and Bacteroides thetaiotaomicron (red triangle) from 8 DNA samples;
FIG. 2 is a graph of the distribution of the combined predictor of CF in different clinical efficacy evaluation groups for 46 patients treated with PD-1 pathway blockade alone;
FIG. 3 is a graph of the distribution of the combined predictor of CF in different clinical efficacy evaluation groups for 11 patients treated with PD-1 pathway blockade in combination with temozolomide;
FIG. 4 is a graph of the distribution of the combined predictor of CF in different clinical efficacy evaluation groups for 10 patients treated with PD-1 pathway blockade in combination with albumin paclitaxel;
FIG. 5 shows the distribution of the combined predictor of CF for 8 patients treated with the PD-1 pathway blockade combined TKI targets in different clinical efficacy evaluation groups;
fig. 6 is a graph of the distribution of the combined predictor CF in different clinical efficacy evaluation groups for 11 patients treated with PD-1 pathway blockade in combination with the BRAF target.
Detailed Description
According to the current research results, the single detection index is difficult to effectively predict the curative effect of the immunotherapy, and the high false positive rate or false negative rate exists. As a biomarker, the intestinal flora has the advantages of large individual difference, multiple detection targets and the like. The invention takes a real-time fluorescence quantitative PCR detection method as a basis, and screens 55 detection targets of the intestinal bacterium genome DNA to obtain 5 scoring formulas which can be used for predicting the curative effect of immunotherapy, and the relative expression quantity of each target of the intestinal bacterium genome DNA in the detection formulas is scored, so that the curative effect of the immunotherapy of melanoma patients with different medication schemes can be predicted. The specific detection targets and the serial numbers thereof are as follows:
the particularity of the fecal specimen makes the collection amount or the sample adding amount of the specimen not reach the same standardization degree as that of the blood and urine specimens, so that the absolute quantification of the intestinal bacteria expression level is difficult to realize; therefore, the method for simultaneously analyzing the internal reference genes is selected to relatively quantify the expression of different bacterial species in the intestinal tract, and the problems that the collection of the stool sample and the sample adding are difficult to standardize can be avoided by utilizing the characteristics and the advantages of the internal reference genes. The invention uses the 16S rRNA V4 region of bacteria as a reference gene in real-time fluorescence quantitative PCR to calculate the relative expression quantity of a target spot. FIG. 1 shows the fluorescent quantitative PCR amplification curves of the internal reference gene (green circle) and Bacteroides thetaiotaomicron (red triangle) of 8 DNA samples; when the sample adding quality of the DNA is controlled within a certain range, 8 samples can obtain relatively stable expression levels of the internal reference genes, and the expression amounts of the bacteriodes theoetaomicron are different.
The immunotherapy regimens for melanoma patients vary and mainly comprise three main groups:
1) PD-1/PD-L1 pathway blockade therapy alone, such as the single drug Paboly beads (Pembrolizumab), the single drug Terapril (Tripalimab) or Nivolumab;
2) the PD-1/PD-L1 pathway blockade therapy in combination with chemotherapy, for example in combination with Temozolomide (Temozolomide) or albumin Paclitaxel (Paclitaxel);
3) PD-1/PD-L1 pathway blockade therapy in combination with targeted therapy, such as in combination with TKI target drug Arotinib (Anlotinib), Lenvatinib (Lenvatinib), or BRAF target drug Vemurafenib (Vemurafenib);
86 melanoma patients are taken as research objects in the project, and the medication scheme and the clinical efficacy evaluation are shown in table 1.
TABLE 186 immunotherapy regimens and clinical efficacy evaluation for melanoma patients
And (4) surface note: PR, partial response; CR, complete response; PD, progressive disease; SD, stable disease; ICT ═ Immune Check-point Inhibitor Therapy, Immune checkpoint Inhibitor Therapy.
The specific experimental scheme is as follows:
1) collecting fresh feces collected by a patient, placing the feces in a commercial feces collection kit containing a stabilizer (Shenzhen Huadai manufacturing), and extracting feces bacterial genome DNA (magnetic bead method magen kit automatic extraction).
2) The bacterial genome DNA of excrement of 10 patients with different cancer species is mixed in equal mass to serve as a primer verification template, and the primer amplification efficiency verification is carried out on 55 intestinal tract bacterial genome DNA detection targets by referring to a real-time fluorescent quantitative PCR primer verification method recommended by Bookout AL and other scholars. The 55 detection targets comprise common intestinal bacteria such as Bifidobacterium, Eubacterium, Fusobacterium, Peptostreptococcus, Lactobacillus, Bacteroides, Ruminococcus, Clostridium and the like, and bacteria which are found in the prior art and have low expression level and great significance, such as Enterococcus hirae and Akkermansia muciniphila.
3) And (3) selecting 33 detection targets with amplification efficiency basically meeting the requirement according to the primer verification result in the step (2). Taking the 16S rRNA V4 region of the bacterium as an internal reference gene, carrying out real-time fluorescence quantitative PCR detection on the 33 detection targets, and calculating the relative quantitative result of each DNA target, wherein the specific calculation steps are as follows:
calculating delta Ctsample. The formula is delta Ctsample＝CtGOI-CtrefWherein Ct isGOICt as the result of the fluorescent quantitative PCR run of the targetrefThe results are run on the internal reference gene.
And calculating delta Ct. The formula is that delta Ct is delta Ctsample-ΔCtcalibratorWherein Δ CtcalibratorIs constant and takes a value between-20 and 20.
Calculating the relative expression quantity (fold-change) of the detected target. The formula is fold-change ═ X(-ΔΔCt)Wherein X is a constant and takes a value between 1 and 3.
4) Preliminary analysis of the relative quantitative results of 86 patients revealed that the intestinal flora was characteristic when the patients used different immunotherapeutic regimens; therefore, when using the intestinal flora as a biomarker for predicting the clinical efficacy of immunotherapy, patients using different treatment regimens should jointly detect different bacterial targets.
This project divided patients into 5 groups according to the dosing regimen:
meanwhile, patients are divided into two groups according to clinical curative effect: PR/CR (partial remission or complete remission) and PD/SD (disease progression or disease stabilization); performing t-test analysis on two groups of independent samples with different clinical curative effects on patients with each medication scheme according to the relative quantitative result obtained in the step 3; in each medication scheme, 11 different target points are obtained from 33 screening target points respectively, and the obtained target points and the statistical difference thereof are shown in table 2.
TABLE 2 differential targets for different regimens and their P-values
And (4) surface note: p values in the table are obtained by t-test analysis of two independent groups of samples at different clinical efficacy groups for the corresponding target, and null values indicate that no significant difference is found, and marked are modeling targets.
Analyzing different target points of each medication scheme by using SPSS-Logistic Regression to obtain a scoring formula for predicting the curative effect of immunotherapy:
and (4) surface note: CF ═ Combination factor, joint predictor; the target numbers are relative expression levels of the corresponding bacterial DNA targets.
Patients were scored using the scoring formula and the distribution and statistical differences of the resulting CF across the different clinical efficacy groups are shown in fig. 2, fig. 3, fig. 4, fig. 5 and fig. 6. As shown in the figure, the combined detection scheme is established by the DNA detection target point in the formula and CF is calculated, and the CF obtained by patients with different clinical curative effects of each medication scheme has obvious statistical difference between the two groups; the scoring formula can effectively classify and judge the characteristics of the intestinal flora of patients with different clinical curative effects according to the relative expression quantity of the intestinal bacterium DNA target.
In practical application, Cut-off is taken as a judgment standard, and if the obtained CF is less than 0, the corresponding immunotherapy scheme is predicted to be effective for patients; if the resulting CF is greater than 0, the patient is predicted to be resistant to the corresponding immunotherapy regimen.
The relationship of gut flora characteristics to PD-1/PD-L1 blockade therapy may have commonalities in different classes of tumors; the research result of the project is subjected to data supplement and reanalysis, and has the possibility of being applied to tumors except melanoma, such as sarcoma, renal cancer, lung cancer, gastric cancer or colorectal cancer, and enabling patients to benefit.
The foregoing is a more detailed description of the invention and is not to be taken in a limiting sense. It will be apparent to those skilled in the art that simple deductions or substitutions without departing from the spirit of the invention are within the scope of the invention.
Claims (10)
1. A panel of gut flora markers for predicting the efficacy of immunotherapy, said gut flora markers being selected from at least 2 of the following 31 bacterial DNA targets:
preferably at least 5 of them.
2. The marker panel for intestinal flora according to claim 1, wherein: the intestinal flora marker group relates to intestinal bacteria DNA detection targets of at least one of the following combinations:
combination I: cluster IV Ruminococcus spp, Bifidobacterium adolescentis, Peptostreptococcus productus, Bacteroides thetaiotaomicron, Bacteroides vulgatus, Bacteroides distassonis, Bacteroides spp, Enterococcus hirae, Akkermansia mulilina and Corynebacterium are used for 11 intestinal bacterial DNA detection targets in total;
combination C1C 3: bacilli vulgatus, bacilli distorsonius, Alleubacteria, Bifidobacterium catenulatum group, Bifidobacterium bifidum, 5 intestinal bacteria DNA detection targets in total;
combination C2C 4: fusobacterium prausnitzii, bacteriodes spp, Clostridium cluster IV, Bifidobacterium catenulatum group, Clostridium perfringens group, totaling 5 intestinal bacteria DNA detection targets;
combination AL: cluster IV Ruminococcus spp, Fusobacterium spp, 2 intestinal bacteria DNA detection targets in total;
and (3) combination V: bacteria-Prevotella-Porphyromonas, All Eubacterium, Clostridium clusterium XIVa, Butyryl-CoA-transferase gene, Clostridium coccoides-Eubacterium repeat group, totaling 5 intestinal bacterial DNA detection targets.
3. The intestinal flora marker panel according to claim 1 or 2, wherein: the immunotherapy is single PD-1 pathway blocking therapy, PD-1 pathway blocking therapy combined chemotherapy or PD-1 pathway blocking therapy combined targeted therapy.
4. The marker panel for intestinal flora according to claim 3, wherein: the immunotherapy is an immunotherapy for melanoma.
5. The marker panel for gut flora according to claim 4, wherein: the scoring formula for predicting immunotherapy efficacy is one of the following formulas:
formula I: CF-186.811-2 + 500.54-11-397.623-17 + 243.817-22 + 468.598-24-564.659-25 m + 60.101-26 + 1652.688-29-1291.203-46-38.697-47-416.678-55-987.267;
formula C1C 3: CF-54.105-25 m-321.927-26 + 904.879-28-16.335-38-35.708-39-531.83;
formula C2C 4: CF 189.453 targets 21-767.437 targets 29-683.808 targets 34-15.06 targets 38-36.041 targets 42+ 1216.563;
formula AL: CF 195.493 target 2+468.221 target 43-411.411;
formula V: CF 1452.393 targets 13-2926.599 targets 28+3257.596 targets 30-1753.58 targets 36-526.748 targets 41-573.037;
in each formula, the target number refers to the relative expression quantity of a DNA detection target of the corresponding intestinal bacteria, and the relative expression quantity is determined based on an internal reference gene; preferably, the internal reference gene is the bacterial 16S rRNA V4 region.
6. The application of the primer sequence group in predicting the curative effect of immunotherapy is characterized in that: the primer sequence can determine the expression quantity of the intestinal flora marker in the claim 1, and the expression quantity is determined based on an internal reference gene; preferably, the internal reference gene is the bacterial 16S rnav4 region.
7. A detection and analysis system for predicting the curative effect of immunotherapy comprises a relative quantification device, a data analysis device and a result output device of different detection targets of the genomic DNA of intestinal bacteria, and is characterized in that:
the relative quantification device of different detection targets of the intestinal bacterial genome DNA is used for determining the relative expression quantity of the intestinal flora marker in the claim 1;
the data analysis device is used for calculating a joint prediction factor CF based on the relative expression quantity;
the result output device is used for outputting a calculation result and predicting the curative effect of the immunotherapy.
8. The detection analysis system of claim 7, wherein: the relative expression amount is determined based on an internal reference gene; preferably, the internal reference gene is the bacterial 16S rRNA V4 region.
9. The detection analysis system of claim 8, wherein: the formula for calculating the joint predictor CF is selected from:
formula I: CF-186.811-2 + 500.54-11-397.623-17 + 243.817-22 + 468.598-24-564.659-25 m + 60.101-26 + 1652.688-29-1291.203-46-38.697-47-416.678-55-987.267;
formula C1C 3: CF-54.105-25 m-321.927-26 + 904.879-28-16.335-38-35.708-39-531.83;
formula C2C 4: CF 189.453 targets 21-767.437 targets 29-683.808 targets 34-15.06 targets 38-36.041 targets 42+ 1216.563;
formula AL: CF 195.493 target 2+468.221 target 43-411.411;
formula V: CF 1452.393 targets 13-2926.599 targets 28+3257.596 targets 30-1753.58 targets 36-526.748 targets 41-573.037;
in the above formulas, the target number refers to the relative expression level of the target spot corresponding to the DNA detection of the enteric bacteria.
10. The detection analysis system of claim 9, wherein: predicting that a corresponding immunotherapy regimen will be effective for the patient if the CF is less than 0; if the resulting CF is greater than 0, the patient is predicted to be resistant to the corresponding immunotherapy regimen.
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