WO2020168541A1 - Utilisation d'un métagénome intestinal dans le criblage de l'effet thérapeutique des anticorps bloqueurs pd-1 - Google Patents

Utilisation d'un métagénome intestinal dans le criblage de l'effet thérapeutique des anticorps bloqueurs pd-1 Download PDF

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WO2020168541A1
WO2020168541A1 PCT/CN2019/075825 CN2019075825W WO2020168541A1 WO 2020168541 A1 WO2020168541 A1 WO 2020168541A1 CN 2019075825 W CN2019075825 W CN 2019075825W WO 2020168541 A1 WO2020168541 A1 WO 2020168541A1
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lung cancer
marker
relative abundance
sequencing
small cell
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PCT/CN2019/075825
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Chinese (zh)
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方超
钟焕姿
侯勇
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深圳华大生命科学研究院
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Priority to PCT/CN2019/075825 priority Critical patent/WO2020168541A1/fr
Priority to CN201980076831.8A priority patent/CN113166815B/zh
Publication of WO2020168541A1 publication Critical patent/WO2020168541A1/fr

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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/02—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving viable microorganisms
    • C12Q1/04—Determining presence or kind of microorganism; Use of selective media for testing antibiotics or bacteriocides; Compositions containing a chemical indicator therefor
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6888—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms
    • C12Q1/689—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer

Definitions

  • the invention relates to the field of biological detection, in particular to the use of an intestinal metagenomics in screening the curative effect of PD-1 antibody blockers.
  • PD-1 Programmed apoptosis protein 1 receptor
  • T cells T cells, B cells, macrophages, regulatory T cells, and natural killer cells.
  • PD-1 can be bound by a variety of ligands, the main two types are called PD-1 ligand 1 and PD-1 ligand 2.
  • the PD-1 signaling pathway activated by ligand binding can inhibit T cell proliferation and immune response activities. Therefore, activating the PD-1 signaling pathway has become the main means for tumor cells to escape the antigen-specific T cell immune response.
  • the PD-1 antibody blocker developed for this phenomenon can block this process, thereby enhancing the body's own anti-tumor immunity activity.
  • the present invention aims to solve one of the technical problems in related technologies at least to a certain extent, and provides a method for screening the curative effect of PD-1 antibody blockers using the intestinal metagenomics.
  • the application of the intestinal metagenomics to predict the therapeutic effect of PD-1 antibody blockers on cancer can guide clinical medication, so as to achieve precise treatment of individuals.
  • the present invention screens to determine the flora markers that can effectively assist the therapeutic effect of PD-1 antibody blockers on specific tumor patients; at the same time, the relative content of intestinal flora markers is used to construct a model to effectively predict the patient’s acceptance of the species. The expected response level of the therapy.
  • the present invention provides the use of the intestinal metagenomics in predicting the therapeutic effect of PD-1 antibody blockers on cancer.
  • the metagenome also called the environmental microbial genome or metagenome, is the sum of all genetic genes in a specific environment.
  • the gut metagenome refers to the sum of all genetic genes in the gut environment.
  • the use of the aforementioned intestinal metagenomics in predicting the therapeutic effect of PD-1 antibody blockers on cancer may further include the following technical features:
  • metagenomics is used to analyze the components or functional changes of the intestinal metagenomics to predict the therapeutic effect of PD-1 antibody blockers on cancer.
  • metagenomics refers to the microbial population genome in environmental samples as the research object. Through modern genomics technology, including the screening and sequencing analysis of functional genes, it can analyze the microbial diversity, population structure, evolutionary relationship and function of the environment. A new microbial research method for studying the relationship between activity, mutual cooperation and the environment.
  • the metagenomics is an omics study based on data by identifying microorganisms in environmental samples and quantifying their richness through DNA sequencing.
  • the metagenomics is whole-gene sequencing metagenomics.
  • Whole gene sequencing Metagenomics (whole genome metagenomics) is to sequence all microorganisms in a specific environment as a whole. Using whole-gene sequencing metagenomics can study the functional genes or functional microorganisms in samples and the role of functional genes or functional microorganisms in the environment.
  • the metagenomics is 16S/18S rDNA sequencing, or probe sequencing.
  • 16S rDNA is a gene encoding the small subunit 16S rRNA of prokaryotic ribosomes.
  • the degree of variation in the hypervariable region is closely related to the phylogeny of prokaryotic microorganisms.
  • Using high-throughput sequencing technology to sequence the 16S rDNA hypervariable region can analyze the diversity of the community structure of prokaryotic microorganisms in the environment.
  • 18S rDNA is a gene encoding the small eukaryotic ribosomal subunit 18S rRNA, which also has conserved and hypervariable regions.
  • the 18S rDNA hypervariable region was sequenced through high-throughput sequencing technology to analyze the colony structure diversity of eukaryotic microorganisms in the environment.
  • Probe sequencing is to capture target regions by designing probes, such as capturing all exon regions of microorganisms in the intestinal metagenomics, to analyze and study the relationship between these regions and diseases.
  • the intestinal metagenomic group includes intestinal microorganisms.
  • the intestinal metagenomics includes all the genetic material in the intestine. A large part of these genetic material comes from gut microbes. Through the analysis of intestinal microbes, the changes in the type or content of intestinal microbes can be used to predict the therapeutic effect of PD-1 antibody blockers on cancer and guide clinical medication.
  • the changes in the composition of the intestinal metagenomics include changes in the type or content of intestinal microorganisms.
  • the functional changes of the intestinal metagenomics include changes in metabolic function genes.
  • Metabolic genes refer to genes related to the metabolic function of the intestine. These genes can be expressed as enhancing the metabolic function of the intestine or reducing the metabolic function of the intestine. For example, changes in intestinal metabolic function can be manifested as changes in the microbial environment in the intestines, thereby showing differences in response efficiency to PD-1 antibody blockers.
  • the cancer includes at least one selected from the group consisting of non-small cell lung cancer, colorectal cancer, liver cancer, esophageal cancer, lung cancer, breast cancer, and gastric cancer.
  • these cancers usually appear as malignant tumors, and during treatment with PD-1 antibody blockers, different patients usually show different response rates.
  • a review published in 2016 Zou, W, et al, 2016
  • 22 projects involving kidney cancer, non-small cell lung cancer, and colorectal cancer were treated with PD-1 blockers before 2015.
  • the response rate fluctuated from 12.8% to 43.7%.
  • the PD-1 antibody blocking agent includes at least one selected from the group consisting of pembrolizumab, nivolumab, and Camrelizumab.
  • the present invention provides a marker comprising at least one selected from the group consisting of Streptococcus sanguinis (Streptococcus sanguinis) and/or its analogues, Escherichia coli (E.
  • Clostridium sp.L2-50 Clostridium sp.L2-50 and/or its analogues
  • Citrobacter freundii (Citrobacter freundii) and/or its analogues
  • Pyramidobacter piscolens conetobacter sp.L2-50) piscolens bacteria
  • Streptococcus sanguinis analogue and the Streptococcus sanguinis genome sequence are more than 85% similar
  • the Escherichia coli analogue is compared with the Escherichia coli genome sequence.
  • the Clostridium sp.L2-50 analogue is more than 85% similar to the Clostridium sp.L2-50 genome sequence.
  • the Citrobacter freundii analogue is similar to the Citrobacter freundii Compared with the genome sequence, the alignment similarity is more than 85%, and the Pyramidobacter piscolens analog is more than 85% compared with the Pyramidobacter piscolens genome sequence.
  • each bacterial analogue when the comparison coverage of each bacterial analogue is more than 80% compared with the corresponding bacterial genome sequence, and the comparison similarity is more than 85%, these analogues can be considered It belongs to the same genus as the corresponding bacteria and can be used as a marker.
  • the comparison coverage of these analogs and the corresponding bacteria is more than 80%, and the comparison similarity is more than 95%, it can be considered that these analogs are the same species as the corresponding bacteria. landmark.
  • the comparison coverage in the present invention refers to the ratio of the length of the sequence compared with the reference sequence in the target sequence to the total length of the detection sequence in the process of comparing the target sequence with the reference sequence.
  • the present invention provides a preparation comprising Escherichia coli (E. coli) and/or its analogues, Citrobacter freundii (Citrobacter freundii) and/or At least one of the analogs is prepared.
  • Escherichia coli E. coli
  • Citrobacter freundii Citrobacter freundii
  • At least one of the analogs is prepared.
  • Each marker strain can be separated and cultured, combined with auxiliary materials, or directly lyophilized to form a freeze-dried powder, to obtain a preparation, which can intervene and regulate the intestinal tract of patients with non-small cell lung cancer to improve PD -1 The effect of immunotherapy on patients.
  • the formulation includes at least one selected from the group consisting of tablets, pills, powders, injections, solutions, suspensions, capsules, and granules.
  • the present invention provides a method for predicting the therapeutic effect of a PD-1 antibody blocker on patients with non-small cell lung cancer, including: (1) collecting samples from the patients; (2) The sample is tested to determine the relative abundance information of the marker in the sample, the marker is the marker according to the second aspect of the present invention; (3) the relative abundance of the marker in the sample The abundance information is compared with a reference data set or reference value to predict the therapeutic effect of the PD-1 antibody blocker on the patient.
  • the reference data set includes the relative abundance information of the markers in a plurality of samples of non-small cell lung cancer patients that show an effective response to the PD-1 antibody blocker and a plurality of information on the relative abundance of the markers in the PD-1 antibody blocker.
  • the reference data set in the present invention refers to patients with non-small cell lung cancer who have shown an effective response to PD-1 antibody blockers and non-small cell lung cancer patients who have shown an ineffective response to PD-1 antibody blockers
  • the relative abundance information of each marker obtained by the operation of the patient sample is used as a reference for the relative abundance of each marker.
  • the reference data set refers to the training data set.
  • the training set refers to and the verification set has a well-known meaning in the art.
  • the training set refers to subjects with non-small cell lung cancer who show an effective response to PD-1 antibody blockers and a certain number of samples that show blockade of PD-1 antibodies A data collection of the content of each marker in the test sample of non-small cell lung cancer subjects who did not respond to the drug.
  • the verification set is an independent data set used to test the performance of the training set.
  • the reference value in the present invention refers to the reference value or the normal value of the content of each marker in patients with non-small cell lung cancer that effectively responds to the PD-1 antibody blocker.
  • Those skilled in the art know that when the sample volume of patients with non-small cell lung cancer that responds effectively to PD-1 antibody blockers is large enough, the absolute value of each marker in the sample can be obtained using detection and calculation methods known in the art Range.
  • the detection method is used to detect the level of the marker
  • the measured value of the marker level in the sample can be directly compared with the reference value to evaluate the response effect of the non-small cell lung cancer patient to the PD-1 antibody blocker. For example, statistical methods can be used for analysis and comparison.
  • the above-mentioned method for predicting the therapeutic effect of a PD-1 antibody blocker on patients with non-small cell lung cancer may further include the following technical features:
  • the relative abundance information of the markers in the sample with the reference data set when comparing the relative abundance information of the markers in the sample with the reference data set, it further includes executing a multivariate statistical model to obtain the response probability.
  • the multivariate statistical model is a random forest model.
  • the response probability greater than a predetermined threshold indicates that the PD-1 antibody blocker can effectively treat the patient's non-small cell lung cancer.
  • the predetermined threshold is 0.5.
  • the relative abundance information of the marker in step (2) is obtained by a sequencing method, further comprising: isolating a nucleic acid sample from the sample of the patient; based on the nucleic acid sample, A sequencing library is constructed, and sequencing results are obtained by sequencing; the sequencing results are analyzed to determine the relative abundance information of the markers in the sample.
  • the sequencing results can be compared and analyzed using SOAP2 or MAQ, etc., which can improve the efficiency of comparison, and thus the efficiency of PD-1 antibody blocker response detection.
  • the sample is a stool sample.
  • the sequencing is performed by a second-generation sequencing method or a third-generation sequencing method.
  • the sequencing is performed by at least one selected from the group consisting of Hiseq2000, SOLiD, 454, and single-molecule sequencing devices. of. Utilizing the high-throughput and deep sequencing characteristics of these sequencing devices is beneficial to the analysis of subsequent sequencing data, especially the accuracy and accuracy of statistical tests.
  • the PD-1 antibody blocking agent includes at least one selected from the group consisting of pembrolizumab, nivolumab, and Camrelizumab.
  • the present invention provides a device for predicting the therapeutic effect of a PD-1 antibody blocker on patients with non-small cell lung cancer, including: a sample collection device, the sample collection device being adapted to A sample is collected from a patient; a marker relative abundance determination device, the marker relative abundance determination device is connected to the sample collection device, and the marker relative abundance determination device is adapted to detect the sample to determine Relative abundance information of the marker in the sample, the marker includes the marker according to the second aspect of the present invention; a result determination device, the result determination device is connected to the marker relative abundance determination device, The result determination device is adapted to compare the relative abundance information of the markers in the sample with a reference data set or reference value to predict the therapeutic effect of the PD-1 antibody blocker on the patient; wherein the reference The data set includes information on the relative abundance of the markers in a number of samples from patients with non-small cell lung cancer that showed an effective response to the PD-1 antibody blocker and multiple expressions of the PD-1 antibody blocker Information on
  • the above-mentioned device for predicting the therapeutic effect of PD-1 antibody blocker on patients with non-small cell lung cancer may further include the following technical features:
  • the device when comparing the relative abundance information of the markers in the sample with a reference data set, it further includes executing a multivariate statistical model to obtain the response probability.
  • the multivariate statistical model is a random forest model.
  • the response probability greater than a predetermined threshold indicates that the PD-1 antibody blocker can effectively treat the patient's non-small cell lung cancer; preferably, the predetermined threshold is 0.5.
  • the device for determining relative abundance of markers further includes: a nucleic acid sample separation unit, the nucleic acid sample separation unit is adapted to separate a nucleic acid sample from the sample; a sequencing unit, the sequencing unit and the The nucleic acid sample separation unit is connected, and the sequencing unit constructs a sequencing library based on the nucleic acid sample, and performs sequencing to obtain a sequencing result; a comparison unit, the comparison unit is adapted to analyze the sequencing result to determine the sample The relative abundance information of the markers in.
  • the sample is a stool sample.
  • the sequencing is performed by a second-generation sequencing method or a third-generation sequencing method; preferably, the sequencing is performed by at least one selected from the group consisting of Hiseq2000, SOLiD, 454, and single-molecule sequencing devices .
  • the present invention provides a kit, including reagents for detecting the marker according to the second aspect of the present invention.
  • the kit described above may further include the following technical features:
  • the kit includes at least one set of reference data sets or reference values, which are used as a reference for the relative abundance of each marker.
  • the reference data set or reference value can be attached to some physical carrier such as an optical disk or CD-ROM.
  • the kit further includes a first computer program product, and the first computer program product is used to execute to obtain the reference data set or reference value. That is, the first computer program product is used to execute and obtain the therapeutic effect of the PD-1 antibody blocker on the diagnostic subject.
  • the kit further includes a second computer program product, the second computer program product is used to execute the predicted PD-1 antibody blocker to treat the disease according to any one of the embodiments of the fourth aspect of the present invention Methods of treatment effect for patients with small cell lung cancer.
  • the present invention provides a method for screening PD-1 antibody blockers for non-small cell lung cancer, including: administering candidate PD-1 to subjects suffering from non-small cell lung cancer. 1 After treatment with the antibody blocker, the relative abundance information of the marker in the sample from the subject is determined, and the marker is the marker according to the second aspect of the present invention; The relative abundance information of the marker is compared with the relative abundance information of the marker before the candidate PD-1 antibody blocker is administered to the subject. By administering candidate PD-1 antibody blocker treatment to multiple subjects with non-small cell lung cancer, by detecting changes in the relative abundance information of each marker in the subject, it can be used to indicate candidate PD-1 The effect of antibody blockers on non-small cell lung cancer.
  • the increase in the relative abundance of at least one marker of Escherichia coli and/or its analogs, Citrobacter freundii and/or its analogs indicates that the candidate PD-1 antibody blocker is used Drugs for treating non-small cell lung cancer in the subject, or the method is effective for non-small cell lung cancer in the subject.
  • the relative abundance of at least one marker of Streptococcus sanguinis and/or its analogs, Clostridium sp.L2-50 and/or its analogs, Pyramidobacter piscolens and/or its analogs is reduced.
  • the candidate PD-1 antibody blocker is a drug for treating non-small cell lung cancer in the subject, or the method is effective for non-small cell lung cancer in the subject.
  • the subject is an animal or a human.
  • the present invention provides the use of a marker in the preparation of a kit for predicting the response of patients with non-small cell lung cancer to PD-1 antibody blockers or for screening
  • the PD-1 antibody blocker for non-small cell lung cancer the marker is the marker according to the second aspect of the present invention.
  • the present invention provides a method for establishing a predictive model for predicting the response effect of a PD-1 antibody blocker in patients with non-small cell lung cancer, the method comprising identifying patients with non-small cell lung cancer The step of differentially expressed substances between samples that show an effective response to the PD-1 antibody blocker and those that show an ineffective response to the PD-1 antibody blocker, wherein the differentially expressed substance includes the second selected from the present invention One or more of the markers in the aspect.
  • the beneficial effects achieved by the present invention are: the first successful use of intestinal microbes to screen the efficacy of PD-1 immune blockers in the treatment of non-small cell lung cancer, the intestinal bacteria provided by the present invention or any combination thereof can be more ideally predicted The response rate of patients receiving specific PD-1 blocker immunotherapy.
  • the therapeutic effect of PD-1 antibody blockers on cancer can be predicted, and precise medical treatment of different individuals can be realized.
  • Fig. 1 is a schematic diagram of a device for predicting the therapeutic effect of a PD-1 antibody blocker on patients with non-small cell lung cancer according to an embodiment of the present invention.
  • Fig. 2 is a schematic diagram of a device for determining relative abundance of markers according to an embodiment of the present invention.
  • Fig. 3 is a schematic diagram of a random forest screening, model construction and verification process according to an embodiment of the present invention.
  • a is the error coefficient of variation obtained by random forest screening with different numbers of markers
  • Figure 3 b is the training set, the probability that the combination of 5 markers is effective in the invalid group and the effective group is predicted
  • Figure 3 c is the ROC curve obtained by using the decision model of 5 kinds of marker combinations and random forest
  • Fig. 3 d is the verification set, the probability of the 5 kinds of marker combinations being effective in the invalid group and the effective group is predicted
  • Fig. 3 e In order to use the decision model of 5 kinds of markers and random forest to verify in the verification set, the obtained ROC curve graph.
  • Non-small cell lung cancer is a kind of malignant tumor that is highly malignant and easy to relapse and metastasize, including squamous cell carcinoma, adenocarcinoma, and large cell carcinoma.
  • Lung cancer is the malignant tumor with the highest incidence and mortality in China, and 85% of its patients are non-small cell lung cancer.
  • the application of antibody drugs targeting PD-1/PD-L1 in various solid tumors such as melanoma and non-small cell lung cancer (NSCLC) has achieved remarkable broad-spectrum anti-cancer effects.
  • PD-1 antibody blocker is also called “PD-1 blocker” or "PD-1 blocking inhibitor” refers to a substance that can block the PD-1 signal pathway. These substances are prepared into drugs that can block the PD-1 signaling pathway, thereby preventing tumor cells from escaping the antigen-specific T cell immune response.
  • PD-1 antibody blockers that have been discovered include, but are not limited to: pembrolizumab, nivolumab, and Camrelizumab (which have been launched in China this year, and the last one is a domestically developed blocker).
  • the present invention provides a marker that includes at least one selected from the following Species: Streptococcus sanguinis and/or its analogues, Escherichia coli and/or its analogues, Clostridium sp.L2-50 and/or its analogues, Citrobacter freundii and/or its analogues, Pyramidobacter piscolens and/or its analogues .
  • Streptococcus sanguinis is Streptococcus sanguinis, a gram-positive facultative anaerobe bacterium, commonly found in human oral environment.
  • Escherichia coli is Escherichia coli, commonly found in the intestines of animals and humans, and is a gram-negative facultative anaerobe.
  • Clostridium sp.L2-50 is an unnamed bacterium belonging to the genus Clostridium, which is widely distributed in nature.
  • Citrobacter freundii is Citrobacter freundii, a facultative anaerobic gram-negative bacterium, which is a relatively common bacterium in the intestines of healthy people.
  • Pyramidobacter piscolens is a newly discovered bacteria in human oral cavity in recent years. Most of the bacteria in this genus are anaerobic, non-motile bacilli, and their final secondary metabolites are mainly hydrogen sulfide.
  • biomarker also called “marker”, can also be called “biological marker” or “biological marker”, refers to a measurable indicator of the biological state of an individual.
  • biomarkers can be any substance in the individual, as long as they are related to the specific biological state (e.g., disease) of the subject, for example, nucleic acid markers (also called genetic markers, such as DNA), Protein markers, cytokine markers, chemokine markers, carbohydrate markers, antigen markers, antibody markers, species markers (species/genus markers) and functional markers (KO/OG markers), etc.
  • nucleic acid markers is not limited to existing genes that can be expressed as biologically active proteins, but also includes any nucleic acid fragments, which can be DNA, RNA, modified DNA or RNA, or It is unmodified DNA or RNA, and a collection of them. In this context, nucleic acid markers can sometimes be referred to as characteristic fragments. In the present invention, markers can also be replaced by "intestinal markers", because several biomarkers that are closely related to the response of PD-1 antibody blockers discovered in the present invention are all present in the subject's In the intestines. Biomarkers are measured and evaluated, often used to check normal biological processes, pathogenic processes, or pharmacological responses to therapeutic interventions, and are useful in many scientific fields.
  • the present invention provides a method for predicting the therapeutic effect of a PD-1 antibody blocker on patients with non-small cell lung cancer, including: (1) collecting a sample from the patient; (2) evaluating the The sample is tested to determine the relative abundance information of the markers in the sample; (3) The relative abundance information of the markers in the sample is compared with a reference data set or reference value to predict PD-1 antibody blocking The therapeutic effect of the drug on the patient; wherein the reference data set includes information on the relative abundance of the markers in a plurality of samples from patients with non-small cell lung cancer that show an effective response to the PD-1 antibody blocker And the relative abundance information of the markers in a plurality of samples from patients with non-small cell lung cancer that showed an ineffective response to the PD-1 antibody blocker.
  • high-throughput sequencing can be used to batch analyze stool samples of patients with non-small cell lung cancer that show effective responses to PD-1 antibody blockers and show ineffective responses to PD-1 antibody blockers.
  • Stool samples from patients with non-small cell lung cancer Stool samples from patients with non-small cell lung cancer.
  • samples from patients with non-small cell lung cancer that showed an effective response to PD-1 antibody blockers and samples from patients with non-small cell lung cancer that showed an ineffective response to PD-1 antibody blockers The comparison is performed to determine the specific nucleic acid sequence closely related to the response effect of the PD-1 antibody blocker.
  • the steps are as follows:
  • Sample collection and processing collection of stool samples from non-small cell lung cancer patients who showed an effective response to PD-1 antibody blockers and stool samples from non-small cell lung cancer patients who showed ineffective responses to PD-1 antibody blockers , Use the kit for DNA extraction to obtain nucleic acid samples;
  • DNA library construction and sequencing are performed by high-throughput sequencing to obtain the nucleic acid sequence of gut microbes contained in stool samples;
  • a reference gene set also called a reference gene set, which can be a newly constructed gene set or any database of known sequences, for example, using known non-redundant genes of the human gut microbial community Set
  • stool samples from patients with non-small cell lung cancer who showed an effective response to PD-1 antibody blockers and non-small cell lung cancer patients who showed an ineffective response to PD-1 antibody blockers were determined respectively The relative abundance of each gene in the nucleic acid sample.
  • the corresponding relationship between the sequencing sequence and the genes in the reference gene set can be established, so that for a specific gene in a nucleic acid sample, the number of corresponding sequencing sequences can effectively reflect the gene Relative abundance. Therefore, the relative abundance of genes in the nucleic acid sample can be determined through the comparison results and conventional statistical analysis. Finally, after determining the relative abundance of each gene in the nucleic acid sample, the response to non-small cell lung cancer patients who showed an effective response to PD-1 antibody blockers and non-small cell lung cancer patients who showed an ineffective response to PD-1 antibody blockers was determined. The relative abundance of each gene in the nucleic acid samples of patients with small cell lung cancer is statistically tested.
  • the method for determining species markers and functional markers further includes: comparing patients with non-small cell lung cancer who showed an effective response to PD-1 antibody blockers with those who showed an ineffective response to PD-1 antibody blockers.
  • the sequencing sequence of patients with non-small cell lung cancer was compared with the reference gene set; based on the comparison results, the patients with non-small cell lung cancer that showed an effective response to the PD-1 antibody blocker and the PD-1 antibody blocker were determined respectively.
  • the relative abundance of species and relative abundance of each gene in the nucleic acid samples of patients with non-small cell lung cancer who showed an ineffective response; for patients with non-small cell lung cancer who showed an effective response to PD-1 antibody blockers and for PD The relative abundance of each gene in the nucleic acid samples of non-small cell lung cancer patients who showed an ineffective response to the -1 antibody blocker was tested statistically; and the performance of the PD-1 antibody blocker was determined separately
  • the relative abundance of nucleic acid samples from non-small cell lung cancer patients who responded effectively and non-small cell lung cancer patients who showed an ineffective response to PD-1 antibody blockers has significant differences in species markers and functional markers.
  • the relative abundance of genes from the same species and the relative abundance of genes with the same functional annotation can be used to perform statistical tests, such as summation, average value, median value, etc., to determine the function Relative abundance and relative abundance of species.
  • the term "existence" used in this article should be understood in a broad sense. It can refer to qualitative analysis of whether the sample contains the corresponding target, or it can refer to the quantitative analysis of the target in the sample, and it can further
  • the obtained quantitative analysis result is the result of statistical analysis or any known mathematical operation with the reference (for example, the quantitative analysis result obtained by performing a parallel test on a sample with a known state).
  • the relative abundance of these microorganisms in the intestinal flora can also be determined to determine the response effect of the subject to PD-1 antibody blockers, as well as the monitoring of non-small cell lung cancer patients. treatment effect.
  • biomarker combination refers to a combination of two or more biomarkers.
  • species markers and functional markers those skilled in the art can also determine whether the species and functions exist in the intestinal flora through conventional bacterial species identification methods and biological activity testing methods.
  • bacterial species identification can be performed by 16s rRNA.
  • the device as shown in FIG. 1 includes a sample collection device 100, a marker relative abundance determination device 200, and a response result determination device 300, the marker relative abundance determination device is connected to the sample collection device, The response result determination device is connected to the marker relative abundance determination device.
  • the sample collection device is suitable for collecting samples from patients with non-small cell lung cancer; the marker relative abundance determining device is suitable for detecting the sample to determine the relative abundance information of the markers in the sample; the response result determining device is suitable for transferring the sample Compare the relative abundance information of the markers with reference data sets or reference values to predict the therapeutic effect of PD-1 antibody blockers on patients.
  • the reference data set includes the relative abundance information and the number of the markers in a plurality of samples from patients with non-small cell lung cancer that show an effective response to the PD-1 antibody blocker. Information on the relative abundance of the marker in a sample of non-small cell lung cancer patients that showed an ineffective response to the PD-1 antibody blocker.
  • the device for determining relative abundance of markers includes: a nucleic acid sample separation unit 210, a sequencing unit 220, and a comparison unit 230.
  • the sequencing unit is connected to the nucleic acid sample separation unit, and the comparison unit is connected to the nucleic acid sample separation unit.
  • the sequencing unit is connected; wherein the nucleic acid sample separation unit is adapted to separate the nucleic acid sample from the sample; the sequencing unit constructs a sequencing library based on the nucleic acid sample, and the sequencing obtains the sequencing result; the comparison unit is adapted to perform the sequencing result Analysis to determine the relative abundance information of the markers in the sample.
  • NSCLC non-small-cell lung cancer
  • Type obtained by analyzing the obtained data.
  • Sampling time points include the baseline period before treatment and multiple time points after treatment, and regular efficacy evaluations are performed until the disease worsens (progressive disease, PD).
  • the baseline period refers to the 2 weeks before the first PD-1 blocker treatment in the trial. During this period, the patient needs to stop the previous treatment plan and control the intake of other drugs.
  • the fecal DNA of the patient was extracted using next-generation sequencing for metagenomic sequencing.
  • the species difference analysis of the intestinal flora is carried out to find out the species closely related to the curative effect.
  • Permutational multivariate analysis of variance (PERMANOVA, Permutational multivariate analysis of variance) method is used to globally determine whether there is a significant difference in bacterial group scores between different groups.
  • the permutation multivariate analysis of variance is a non-parametric multivariate statistical test. It is used in the association analysis of this project to test the composition of the intestinal flora of the samples belonging to various phenotype groups, and the information on the composition of the intestinal flora used It is often transformed by bray distance.
  • machine learning methods are used to construct a model of immunotherapy efficacy using multiple factors such as the host and flora related to the efficacy of the treatment, so as to guide the clinical precise medication.
  • This process mainly uses the random forest prediction model (Random Forest model).
  • This model is an ensemble learning method and is often used in application scenarios such as classification and regression.
  • this method will repeatedly randomly generate multi-layer decision trees to form a classification decision set, and evaluate the prediction effect of the set.
  • the random forest model in this project also integrates a cross-validation module to stabilize the training effect.
  • the model obtained by this method can not only be applied to the prediction of related curative effects, but also can prompt the bacteria markers that play a related role in the treatment.
  • the method of using the random forest model and the ROC curve is well known in the art, and those skilled in the art can set and adjust the parameters according to the specific situation. According to the embodiment of the present invention, it can be based on the literature (Drogan D, Dunn WB, Lin W, Buijsse B, Schulze MB, Langenberg C, Brown M, Floegel a., Dietrich S, Rolandsson O, Wedge DC, Goodacre R, Forouhi NG ,Sharp SJ,Spranger J,Wareham NJ,Boeing H:Untargeted Metabolic Profiling Identifies Altered Serum Metabolites of Type 2-Diabetes Melitus in a Prospective, Nested Case Control Study.Clin 487-Study, Milik 497, 61ich-Study.
  • Example 1 The treatment response rate of PD-1 blocking inhibitors in the Chinese lung cancer patient population
  • This example includes a total of 84 patients with stage III non-small-cell lung cancer (NSCLC) who meet the requirements of the test (ie, patients who are ineffective through other treatments and are in stage III non-small cell lung cancer).
  • NSCLC stage III non-small-cell lung cancer
  • the patient Before starting PD-1 blocker immunotherapy, the patient first entered the two-week baseline management period, during which other tumor treatment options were suspended. Subsequently, the patient received PD-1 blocker once every two weeks, and received relevant examinations to determine the progress of the disease. Among them, three PD-1 blockers are randomly administered. Each patient with non-small cell lung cancer is given a specific PD-1 blocker. The three PD-1 blockers are Pembrolizumab (Pembrolizumab). ), Nivolumab and Camrelizumab.
  • Table 1 The overall response rate of Chinese lung cancer patients receiving PD-1 blocker therapy
  • the overall response rate of this therapy is only 15.48%, which is a low level compared to the data in European and American (Caucasian) population trials during the same period (ranging from 12.8% to 43.7%) (Weiping et al. 2016) .
  • the intestines of patients with non-small cell lung cancer are screened for bacteria related to the efficacy of PD-1 blocking inhibitors, and the efficacy prediction model is constructed to verify the effectiveness in independent lung cancer patients. .
  • Example 2 Screening of strains highly related to the efficacy of PD-1 blocking inhibitors in the intestines of Chinese lung cancer patients before treatment
  • Example 1 33 had taken antibiotics during the treatment period or had patients with known cancer driver genes such as ALK, EGFR, etc. positive. Considering that antibiotics will affect the results of the flora, and cancer driven Genes may affect the identification of the correlation of the flora, so the samples of these 33 people were not analyzed. Therefore, 51 human intestinal fecal samples were selected for analysis in this example. Through the analysis of these samples, the intestines of lung cancer patients before treatment are screened for bacteria that are highly correlated with the efficacy of PD-1 blocking inhibitors.
  • sample DNA extraction All stool samples were collected from the patient within a week before the start of treatment, and passed through standard procedures such as DNA extraction, high-depth sequencing, database comparison and quantification, and finally a data set of relative abundance of intestinal flora of each sample (sample DNA extraction, The procedures for sequencing, database comparison and quantification are the same as those in the literature, Fang, C., et al. Assessment of the cPAS-based BGISEQ-500 platform for metadata sequencing. Gigascience 7, 1-8 (2018). It is incorporated by reference This article).
  • the data set is subjected to a statistical test of species differences between groups (Wilcoxon rank-sum test), and finally get 17 kinds of relatively reliable differential strain markers (Table 2).
  • the median of the invalid group and the median of the effective group in Table 2 are used to indicate the relative abundance value of the invalid group of bacteria and the effective group of bacteria, that is, the relative content of each bacteria obtained by the MGS method.
  • the sum of the relative abundance values of each bacteria is 1.
  • the R (effective) shown in the column of the enrichment group means that the content of the bacteria in the effective group is significantly higher than that of the ineffective group
  • NR (invalid) indicates that the content of the bacteria in the ineffective group is significantly higher than that in the effective group.
  • the MGS (metagenomic species, metagenomic species) method is referenced from Nielsen, HBet al. Identification and assembly of genes and genetic elements without using reference genes.
  • Example 3 Screening of strains in the intestines of Chinese lung cancer patients that have potential markers for the efficacy of PD-1 blocking inhibitors before treatment and 1 to 3 months after treatment
  • Example 2 For the 51 patients in Example 2, during the treatment process, some patients gave up the treatment because their condition deteriorated, and some withdrew from the study because of other cancer side effects. These were no way to continue to provide stool samples. In order to obtain a more comprehensive sample, this embodiment screened the following samples to obtain bacterial species that have potential markers for the efficacy of PD-1 blocking inhibitors in the intestine of lung cancer patients 1 to 3 months before treatment.
  • This example includes the intestines of 51 patients before treatment, patients after 1 month of continuous treatment (34 cases in total), patients after 2 months of continuous treatment (18 cases in total), and patients after 3 months of continuous treatment (11 cases in total).
  • the subset of each treatment period in the data set is tested for differences in species statistics (Wilcoxon rank- sum test) to obtain the markers of different bacterial species. Since the degree of patient tracking coordination decreases after treatment, in order to increase the number of samples to ensure the reliability of the test, in this embodiment, the union of the patients after treatment is also taken out for testing, so as to screen for intestinal bacterial species with different efficacy after treatment. In addition, in order to select as many potential markers as possible, the statistical test results of two strategies including 0 value and eliminating 0 value were carried out (Table 3).
  • the samples collected by patients after treatment were combined. And each patient selects a sample (for example, a sample of one month after treatment, a sample of two months of treatment, or a sample of three months of treatment) as a sample representing the status of the patient's flora after treatment. These samples are combined after treatment to perform the above-mentioned tests, which can increase the sample size and make the test results more reliable.
  • Example 4 The process of constructing a curative effect prediction model through screening of potential flora markers
  • Example 2 The samples of 10 patients who responded and the samples of 10 patients who did not respond were randomly selected, and the therapeutic effect prediction model was constructed through the screening of potential flora markers obtained in Example 2 and Example 3.
  • This embodiment contains a data set of relative abundance of the microflora before treatment of 10 responsive patients and 10 non-responsive patients randomly selected from the above 51 samples.
  • This data set uses the significantly different bacteria appearing in Table 2 and Table 3 as the main potential markers as the training set to perform 100,000 cross-validation random forest screening.
  • the lowest error rate was obtained in the decision tree combination of the specific 5 intestinal bacteria combination (Table 4) (as shown in a in Figure 3).
  • This combination was used to construct a random forest-based decision model, and an area under the curve of 0.97 was obtained (the maximum value is 1), indicating that the sensitivity and specificity of the model are quite high (Figure 3 b, and Figure 3) c).
  • Annotation rate the percentage of genes clustered under this MGS number to the annotated species.
  • Table 5 The relative abundance of markers in the training set and the prediction probability of the model
  • Example 5 Effectiveness verification of curative effect prediction model in independent lung cancer patient population
  • This example contains the relative abundance data set of the flora of 14 responding patients and 19 non-responding patients out of the above 84 samples that are independent of the training set of Example 4 before treatment.
  • the obtained model performs treatment feedback prediction and evaluation.
  • the test discriminant result is 0.70 area under the curve (the highest is 1), which illustrates the repeatability and real validity of the model (as shown in Figure 3 d and Figure 3 e).
  • the content of markers in each validation set sample and the predicted response rate given by the model are shown in Table 6. Individuals whose predicted probability is higher than 0.5 will be judged as valid, otherwise invalid.
  • the model's best discriminant threshold is 0.5 and has a better discriminative effect.
  • the specific prediction method is: use "randomForest 4.6-12package" in R version 3.3.2 for random forest model classification and regression.
  • the input includes training set data (that is, the relative abundance of selected MGS species markers in the training sample, see Table 5) and sample efficacy (response or non-response), and a validation set (the MGS species selected in the validation set For the relative abundance of markers, see Table 6).
  • the inventor uses the random forest function of the random forest package in the R software to establish classification and prediction functions to predict the verification set data, and the output is the prediction result (response probability), and the optimal classification threshold is 0.5 (if the response probability is higher than 0.5 , It is predicted to have curative effect).

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Abstract

La présente invention concerne l'utilisation d'un métagénome intestinal dans la prédiction de l'effet thérapeutique des anticorps bloqueurs PD-1 sur le cancer et un marqueur utilisé pour prédire l'effet thérapeutique des anticorps bloqueurs PD-1 sur des patients atteints d'un cancer du poumon non à petites cellules, ainsi qu'une application associée. Le marqueur comprend au moins l'une des bactéries parmi Streptococcus sanguinis, Escherichia coli, Clostridium sp. L2-50, Citrobacter Freundii et Pyrimidobacter Piscolens, et des analogues de celles-ci.
PCT/CN2019/075825 2019-02-22 2019-02-22 Utilisation d'un métagénome intestinal dans le criblage de l'effet thérapeutique des anticorps bloqueurs pd-1 WO2020168541A1 (fr)

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