Method for predicting sensitivity to immune checkpoint inhibitors, marker, test kit, and screening method for sensitivity enhancers

Abstract

To provide a technology that enables prediction of sensitivity to an immune checkpoint inhibitor.SOLUTION: A method for predicting sensitivity to an immune checkpoint inhibitor, comprises detecting, in a biological sample, an amount of one or more intestinal bacteria selected from the group consisting of Bacteroides stercoris, Bacteroides coprocola, Sutterella wadsworthensis, and Romboutsia timonensis. According to the present invention, sensitivity to an immune checkpoint inhibitor can be predicted by using a biological sample noninvasively obtained, such as feces, without causing a burden on a subject to visit a clinic or a physical burden related to examination.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a method, a marker and a test kit for predicting sensitivity to immune checkpoint inhibitors, and a method for screening sensitivity enhancers. [Background technology]

[0002] Immune responses have two aspects: positive and negative. While positive immune responses are essential for eliminating pathogens and cancer, negative immune responses are also necessary to prevent tissue damage caused by excessive immune responses and to achieve and maintain homeostasis after the goal of the elimination response has been achieved. Negative immune responses require the actions of regulatory cells such as regulatory T cells and myeloid suppressor cells, regulatory cytokines such as IL-10 and TGF-β, metabolic enzymes such as indoleamine 2,3-dioxygenase (IDO), and negative costimulatory molecules. These molecules that negatively regulate immune responses are called immune checkpoint molecules (Non-Patent Document 1).

[0003] In diseases such as cancer, the expression of immune checkpoint molecules can cause exhaustion of host immune cells, making it difficult to eliminate pathogens. Normally, cancer cells are considered non-self, and activated cytotoxic T cells (CTLs) and macrophages attack and eliminate them. However, persistent antigen stimulation induces the expression of costimulatory receptors (negative costimulatory molecules) such as PD-1 and CTLA-4 on the cell membrane of CTLs. Meanwhile, cancer cells express PD-L1 and CD80, which are ligands for costimulatory receptors. When these ligands bind to costimulatory receptors, T cells have reduced cytotoxicity and are unable to attack cancer cells. Furthermore, cancer cells suppress CTL activity by secreting regulatory cytokines (e.g., IL-10 and TGF-β) (Non-Patent Document 2).

[0004] Therefore, in recent years, attention has been focused on disease treatments that activate or maintain positive immune responses by inhibiting the activity of immune checkpoint molecules. Drugs that inhibit the activity of immune checkpoint molecules are called immune checkpoint inhibitors, and they have been approved for use in the treatment of various cancers and are used in clinical settings. [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] Miyuki Azuma, Cutting Edge: Immune Checkpoint Inhibitors from Basic to Clinical Practice, Pharmacia, Vol. 53, No. 1, 2017, pp. 25-29 [Non-patent document 2] MBL Life Sciences, Top > Product Category > Immunology > Product Pickup > Immune Checkpoint Related Antibodies, [Searched April 16, 2024], Internet <URL: https: / / ruo.mbl.co.jp / bio / product / allergy-Immunology / pickup / Immune-checkpoint.html> Summary of the Invention [Problem to be solved by the invention]

[0006] However, because the primary role of immune checkpoint molecules is to maintain self-tolerance and resolve immune responses once they have occurred, their inhibition can result in side effects (immune-related adverse events) such as autoimmune disease-like symptoms and organ inflammation. Furthermore, they are expensive. In addition to these challenges, a major issue is that immune checkpoint inhibitors generally have a response rate of approximately 30%. In other words, approximately 70% of patients do not achieve efficacy despite the high drug price and side effects. Furthermore, because an observation period of at least six months after the start of treatment is generally required to determine whether immune checkpoint inhibitors are effective, patients who do not respond may actually see their condition worsen.

[0007] The present invention has been made to solve these problems, and aims to provide a technique that can predict sensitivity to immune checkpoint inhibitors, and also to provide a technique that can search for and select substances that enhance the efficacy of immune checkpoint inhibitors (sensitivity enhancers). [Means for solving the problem]

[0008] As a result of intensive research, the present inventors have found a correlation between immune checkpoint inhibitor efficacy in individuals with high intestinal bacteria Bacteroides stercoris, low in Bacteroides coprocola, high in Sutterella wadsworthensis, or low in Romboutsia timonensis, and between immune checkpoint inhibitor efficacy in individuals with low intestinal bacteria Bacteroides stercoris, high in Bacteroides coprocola, low in Sutterella wadsworthensis, or high in Romboutsia timonensis. Based on this finding, the present inventors have completed the following inventions.

[0009] (1) A method for predicting susceptibility to an immune checkpoint inhibitor according to the present invention includes detecting the amount of one or more enterobacteria selected from the group consisting of Bacteroides stercoris, Bacteroides coprolae, Saterella wadsworthensis, and Rhombousia timonensis in a biological sample. This method may be performed excluding medical practice.

[0010] (2) In the present invention, the immune checkpoint inhibitor may be an anti-PD-L1 antibody.

[0011] (3) In the present invention, the immune checkpoint inhibitor may be used for cancer treatment. That is, in the present invention, the subject may be a cancer patient.

[0012] (4) The immune checkpoint inhibitor sensitivity prediction marker according to the present invention comprises one or more enterobacteria selected from the group consisting of Bacteroides stercoris, Bacteroides coprolae, Saterella wadsworthensis, and Rhombousia timonensis.

[0013] (5) The test kit for predicting susceptibility to an immune checkpoint inhibitor according to the present invention comprises a PCR primer set for detecting the amount of one or more enterobacteria selected from the group consisting of Bacteroides stercoris, Bacteroides coprolae, Saterella wadsworthensis, and Rhombousia timonensis in a biological sample.

[0014] (6) In the test kit according to the present invention, the PCR primer set may be a PCR primer set capable of amplifying all or part of the heparinase gene derived from Bacteroides stercolis.

[0015] (7) The method of the present invention for screening an agent for enhancing sensitivity to an immune checkpoint inhibitor comprises detecting the amount of one or more enterobacteria selected from the group consisting of Bacteroides stercoris, Bacteroides coprolae, Saterella wadsworthensis, and Rhombousia timonensis in a sample. [Effects of the Invention]

[0016] According to the present invention, it is possible to predict whether or not an immune checkpoint inhibitor will be effective (sensitivity to an immune checkpoint inhibitor).

[0017] According to the present invention, it is possible to predict sensitivity to immune checkpoint inhibitors using non-invasively obtained biological samples such as feces, without imposing the burden of visiting a hospital or the physical burden of testing on the subject.

[0018] The amount of specific intestinal bacteria can be measured by PCR, and since the present invention does not require comprehensive analysis of the intestinal flora, it is possible to predict sensitivity to immune checkpoint inhibitors quickly and inexpensively.

[0019] According to the present invention, it is possible to predict sensitivity to immune checkpoint inhibitors, which enables selective administration to highly sensitive individuals, thereby contributing to improving the response rate. This also contributes to reducing the burden on patients and medical finances, reducing side effects associated with disease treatment, and improving the quality of life of patients.

[0020] According to the present invention, it is possible to screen for substances that enhance the sensitivity of immune checkpoint inhibitors. By using the extracted sensitivity enhancer in combination with an immune checkpoint inhibitor or by using the sensitivity enhancer in advance, it is expected that the efficacy of the immune checkpoint inhibitor or the therapeutic effect of the target disease can be improved. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a bar graph showing the average abundance ratio (stercolis level) of Bacteroides stercoli in feces from the reactive and non-reactive groups. In the figure, the plots show the measured values ​​for each sample. [Figure 2] (a) is a bar graph showing the average stercoli levels in the feces of the healthy and patient groups. (b) is a bar graph showing the average stercoli levels in the feces of the healthy and responder groups. (c) is a bar graph showing the average stercoli levels in the feces of the healthy and non-responder groups. In the figure, the plots show the measured values ​​for each sample. [Figure 3] This is a graph showing plots and regression lines for each sample from a group of 22 hepatocellular carcinoma patients, with the results of quantitative PCR on the vertical axis and the results of NGS on the horizontal axis (explanatory variables). DETAILED DESCRIPTION OF THE INVENTION

[0022] The present invention will be described in detail below.

[0023] As mentioned above, immune checkpoint inhibitors are drugs that suppress the action of immune checkpoint molecules. Immune checkpoint molecules, as mentioned above, refer to a group of molecules that negatively regulate immune responses, and specific examples include PD-L1, PD-L2, CTLA-4, PD-1, LAG-3, TIM-3, BTLA, TIGIT, VISTA / PD-1H, CD96, NIKG2A, KIR, CD4, CD8, CD19, CD28, CD80 / 86, B7, Galectin-9, HVEM, MHC-II, TCR, B7-H3, and B7-H4.

[0024] Examples of immune checkpoint inhibitors include antibodies (monoclonal antibodies, polyclonal antibodies) against the above-mentioned immune checkpoint molecules. More specific examples of immune checkpoint inhibitors include anti-CTLA-4 antibodies (ipilimumab, tremelimumab, etc.), anti-PD-1 antibodies (nivolumab, pembrolizumab, etc.), anti-PD-L1 antibodies (atezolizumab, durvalmab, avelumab, etc.), anti-LAG-3 antibodies, anti-Tim-3 antibodies, and anti-TIGIT antibodies.

[0025] It has been found that cancer cells evade immunity by utilizing host immune checkpoint molecules, and immune checkpoint inhibitors have conventionally been used in cancer treatment. The immune checkpoint inhibitor of the present invention may be used for cancer treatment. In other words, in the present invention, the subject from whom a biological sample is collected, i.e., the subject whose sensitivity to an immune checkpoint inhibitor is predicted, may be a subject for cancer treatment (cancer patient).

[0026] In the present invention, "predicting sensitivity to an immune checkpoint inhibitor" means predicting whether or not the drug will be effective. In the present invention, "low sensitivity" means that the drug will be ineffective or less effective, and "high sensitivity" means that the drug will be effective or more effective.

[0027] As shown in the Examples below, a correlation is observed between a high level of Bacteroides stercoli or Satellella wadsworthensis or a low level of Bacteroides coprolica or Rhombosia timonensis in the intestines of a subject and a low sensitivity to immune checkpoint inhibitors (the drug is ineffective), and a low level of Bacteroides stercoli or Satellella wadsworthensis or a high level of Bacteroides coprolica or Rhombosia timonensis correlates with a high sensitivity (the drug is effective). Therefore, the abundance of these four types of intestinal bacteria can be used as an indicator of immune checkpoint inhibitor sensitivity (sensitivity prediction marker). In other words, detecting the amount of at least one of these four types of intestinal bacteria can predict the level of sensitivity to immune checkpoint inhibitors.

[0028] Furthermore, based on the above correlation, substances that increase the amount of Bacteroides stercoli and / or Satellella wadsworthensis or decrease the amount of Bacteroides coprolica and / or Rhombosia timonensis can be said to decrease sensitivity to immune checkpoint inhibitors. Conversely, substances that decrease the amount of Bacteroides stercoli and / or Satellella wadsworthensis or increase the amount of Bacteroides coprolica and / or Rhombosia timonensis can be said to increase sensitivity to immune checkpoint inhibitors. Therefore, substances that increase sensitivity to immune checkpoint inhibitors (sensitivity enhancers) can be screened using the amount of one or more enterobacteria selected from the above four species as an indicator.

[0029] In this screening method, for example, a test substance may be added to a cultured human intestinal model or administered to a subject, and the amount of one or more enterobacteria selected from the four types listed above may be detected after a certain period of time. If a substance that reduces Bacteroides stercoli, increases Bacteroides coprolae, decreases Saterella wadsworthensis, or increases Rhombosia timonensis is extracted using this test system, it can be said to be an immune checkpoint inhibitor sensitivity enhancer. More specifically, this screening method may comprise, for example, the steps of measuring the amount of a specific enterobacteria in a sample before administration of the test substance, measuring the amount of a specific enterobacteria gene in a sample after administration of the test substance, and selecting a test substance useful as an immune checkpoint inhibitor sensitivity enhancer based on the results of measuring the amount of bacteria in the pre-administration sample and the post-administration sample.

[0030] The amount of a specific enterobacteria can be detected by a known standard method, such as a method in which the total genomic DNA of an enterobacteria extracted from a sample (e.g., a fecal sample or a cultured human intestinal model) is used as a template, bacterial 16S rDNA is amplified by polymerase chain reaction (PCR), the amplified product is decoded by next-generation sequencing (NGS), the bacterial species are identified based on a 16S database, and the abundance ratio is determined, as shown in the Examples below.

[0031] Another example is a method in which PCR is performed using primers specific to specific enterobacteria on the total genomic DNA of enterobacteria extracted from a sample (e.g., a fecal sample or a cultured human intestinal model). PCR reaction conditions can be appropriately set depending on the type and preparation method of the sample, the sequence and length of the primers, the type and properties of the enzyme used in the reaction, etc. This method allows for more rapid and inexpensive detection of the amount of specific enterobacteria. The primers specific to specific enterobacteria used in this method can be designed based on a region of the genome or gene DNA sequence possessed by the bacterial species that is conserved in the bacterial species but not in other species (specific bacterial species conserved region). Because the specific bacterial species conserved region is a region that is specifically conserved in that bacterial species, the copy number of the PCR product generated by the primers can be said to correlate with the amount (bacterial count) of the specific enterobacteria. In other words, the copy number can be used as the bacterial amount (or an indicator of the bacterial amount).

[0032] For example, in the case of Bacteroides stercoris, specific primers can be designed based on a region of the DNA sequence of the heparinase gene (SEQ ID NO: 5) contained in the bacterial species that is conserved in the bacterial species but not in other species of the genus Bacteroides. More specifically, an example of such primers is the PCR primer set of SEQ ID NOs: 3 and 4.

[0033] For example, in the case of Bacteroides coprocytes, specific primers can be designed based on a region of the DNA sequence (SEQ ID NO: 8) of the 5α-reductase gene possessed by the bacterial species that is conserved within the bacterial species but not conserved in other species of the genus Bacteroides. More specifically, an example of such primers is the PCR primer set of SEQ ID NO: 9 and SEQ ID NO: 10 below. <Primers for amplifying the conserved region of the 5α-reductase gene in Bacteroides coprocytes> Forward primer (5ar_coprocola_F); 5'-TTGTGAGGGCAGGATATGGTATGTTC-3' (SEQ ID NO: 9) Reverse primer (5ar_coprocola_R); 5'-AGCAAAAACGTCAATATCACTAGACAGCC-3' (SEQ ID NO: 10)

[0034] Specifically, the present invention provides a test kit for predicting susceptibility to immune checkpoint inhibitors and a screening kit for susceptibility enhancers, each kit comprising a PCR primer set for detecting the amount of one or more enterobacteria selected from the group consisting of Bacteroides stercoris, Bacteroides coprolae, Saterella wadsworthensis, and Rhombousia timonensis. The kit may further comprise enzymes necessary for PCR reactions, such as dNTPs and DNA polymerase, a specimen collection device, a labeling substance, a reaction buffer, a washing buffer, a positive control, a negative control, and instructions for determining the progression or severity of disease, as well as instructions for operation.

[0035] If there are many Bacteroides stercolis or Satellella wadsworthensis or few Bacteroides coporocola or Rhombosia timonensis in the intestines of a subject or in an intestinal model, it is predicted that the sensitivity to immune checkpoint inhibitors is low (the drug is ineffective), and if there are few Bacteroides stercolis or Satellella wadsworthensis or many Bacteroides coporocola or Rhombosia timonensis, it is predicted that the sensitivity is high. However, because the amount of genes purified from biological samples such as feces (purification efficiency) is not constant, it is preferable to calculate the proportion of the total number of intestinal bacteria and make a judgment based on that proportion.

[0036] Based on the results of detecting the amount of specific enterobacteria, the reference value for determining the level of sensitivity to immune checkpoint inhibitors can be set appropriately, and may vary depending on various factors such as the method for measuring the amount of bacteria, the method for calculating the reference value, the sex and age of the subject group, clinical findings, residential area, and test data accumulated up to that point. For example, if the amount of bacteria is detected by PCR using the specific bacterial species conservation region as an indicator, and the value calculated by dividing the "DNA copy number of the specific bacterial species conservation region" by the "DNA copy number of the 16S rRNA gene" is calculated and this is defined as the "specific enterobacteria level," the specific enterobacteria level will be 1.0 x 10 -2 For example, if the number of infected individuals is less than 100 (in the case of Bacteroides stercoris), it is determined that the infected individual is highly susceptible to immune checkpoint inhibitors (highly likely to be effective against the drug).

[0037] In the present invention, the sample may be any sample that reflects the intestinal bacterial flora, such as feces, intestinal contents, lavage fluids and body fluids (saliva, mucus, lymph, etc.) collected during endoscopic examinations, mucous membranes of the gastrointestinal lumen, tissues or cells collected or excised by surgery, blood, skin, and cultured human intestinal models.

[0038] The present invention will be described below based on examples, but the technical scope of the present invention is not limited to the features shown in these examples. [Example]

[0039] <Example 1> Comprehensive bacterial flora analysis (1) Subjects Twenty-two patients diagnosed with unresectable hepatocellular carcinoma by imaging diagnosis were enrolled as subjects. At the time of specimen collection, all patients had received a combined medication treatment of an immune checkpoint inhibitor (anti-PD-L1 antibody, atezolizumab "Tecentriq (registered trademark)") and an angiogenesis inhibitor (anti-VEGF-A antibody, bevacizumab "Avastin (registered trademark)") for a predetermined period. The medication was administered every three weeks according to a previous report (Teiji Kuzuya, et al., Early Changes in Alpha-Fetoprotein Are a Useful Predictor of Efficacy of Atezolizumab plus Bevacizumab Treatment in Patients with Advanced Hepatocellular Carcinoma, Oncology (2022) 100 (1): 12?21.). Every six weeks, the responsiveness to this treatment was evaluated in the following four stages according to the revised version 1.1 of the RECIST (Response Evaluation Criteria in Solid Tumors) guidelines for the determination of the treatment effect of solid tumors. Those who met the criteria for CR or PR were classified into the response group, and those who met the criteria for SD or PD were classified into the non-response group. As a result, the 22 hepatocellular carcinoma patients were divided into an 11-person response group and an 11-person non-response group. <Four-stage evaluation based on RECIST 1.1> CR (Complete Response): Complete response. All signs of cancer disappear. It is not necessarily a cure. PR (Partial Response): Partial response. The state where the tumor has disappeared by more than 30% of the whole. SD (Stable Disease): Stable. The size of the tumor has not changed at all compared to before treatment. PD (Progressive Disease): The progression state has worsened. There is an increase of more than 10% in the tumor diameter.

[0040] The attributes of the subjects are shown in Table 1.

Table 1

[0041] (2) DNA sample Feces were collected from subjects (22 hepatocellular carcinoma patients) using the fecal collection kit "FS-0017" (Techno Suruga Lab Co., Ltd.). DNA was extracted from the fecal samples using the QIAamp QIAamp DNA Stool Mini Kit (QIAGEN) according to the attached instructions, and this was used as total fecal DNA. Total fecal DNA is thought to reflect the DNA of the intestinal bacteria that make up the host's intestinal flora.

[0042] (3) Comprehensive analysis of the intestinal microbiota Using total fecal DNA as a template, PCR was performed using the universal primers SEQ ID NOs: 1 and 2 below to amplify the V3-V4 region of bacterial 16S rDNA (Takahashi S, et al., (2014) Development of a Prokaryotic Universal Primer for Simultaneous Analysis of Bacteria and Archaea Using Next-Generation Sequencing. PLoS ONE 9(8): e105592. Published: August 21, 2014). Forward primer (Pro341F): CCTACGGGNBGCASCAG (SEQ ID NO: 1) Reverse primer (Pro805R): GACTACNVGGGTATCTAATCC (SEQ ID NO: 2)

[0043] The PCR-amplified products were then sequenced by next-generation sequencing (NGS). NGS was performed using the Illumina MiSeq platform (Illumina) and MiSeq Reagent Kit ver. 3 (Illumina) using a paired-end method (2x300bp). The sequences were analyzed using the EzBioCloud 16S database and the 16S Microbiome Pipeline (EzBioCloud 16S-based MTP app, https: / / www.EZbiocloud.net) to identify the taxonomy at the genus or species level and determine their abundance. The abundance was calculated as the percentage of the total number of reads for each bacterial species (genus). The average abundance ratio was calculated for each responder and non-responder group, and p values ​​were calculated for comparisons between groups using a one-sided parametric test. The results are shown in Table 2. [Table 2]

[0044] As shown in Table 2, Bacteroides stercoli and Satellella wadsworthensis were significantly higher in the non-responders and significantly lower in the responders. On the other hand, Bacteroides coprolae and Rhombosia timonensis were significantly lower in the non-responders and significantly higher in the responders. In other words, those with high Bacteroides stercoli, high Satellella wadsworthensis, low Bacteroides coprolae, or low Rhombosia timonensis in their intestinal flora did not respond well to medication. Conversely, those with low Bacteroides stercoli, low Satellella wadsworthensis, high Bacteroides coprolae, or high Rhombosia timonensis in their intestinal flora responded well to medication. These results revealed that Bacteroides stercolis, Bacteroides coprocola, Satellella wadsworthensis, and Rhombousia timonensis can be used as indicators to predict sensitivity to immune checkpoint inhibitors (whether or not the drug will be effective in the subject).

[0045] Example 2: Examination of B. stercoris quantity by quantitative PCR (1) Design of specific primers Using the multiple alignment tool MAFFT, we performed multiple alignment of DNA sequences between the three heparinase genes of Bacteroides stercolis and heparinase gene homologs of other Bacteroides species, and identified regions that are highly conserved in the former but not between the former and latter (Stercolis conserved regions).Based on the sequences of the Stercolis conserved regions, we designed the following primers that can specifically amplify the heparinase genes of Bacteroides stercolis. <Primers for amplifying the stercoris conserved region of the heparinase gene> Forward primer (heparinas_Synbio_F2); 5'-GGTGCTACGACCAGATGAAAGAATCC-3' (SEQ ID NO: 3) Reverse primer (heparinas_Synbio_R2); 5'- AGTATCATCCATTCGCTGGAGTGC -3' (SEQ ID NO: 4)

[0046] The forward primer (SEQ ID NO: 3) corresponds to positions 488 to 513 in the heparinase gene of Bacteroides stercoris ATCC 43183 (Genbank: CP102262.1, SEQ ID NO: 5). The reverse primer (SEQ ID NO: 4) corresponds to positions 603 to 626 in SEQ ID NO: 3. Because the Bacteroides stercoris conserved region is a region that is conserved species-specifically, it can be said that the copy number of the PCR product using this primer set correlates with the bacterial count of Bacteroides stercoris.

[0047] Additionally, the following universal primers were prepared that can amplify the V3-V4 region of the 16S ribosomal RNA gene of all bacteria. The copy number of the PCR product produced by this primer set correlates with the total bacterial count. <For amplifying the 16S ribosomal RNA (V3-V4 region) gene of all bacteria> Forward primer (F_Bact 1369): 5'-CGGTGAATACGTTCCCGG-3' (SEQ ID NO: 6) Reverse primer (R_Prok 1492): 5'-TACGGCTACCTTGTTACGACTT-3' (SEQ ID NO: 7)

[0048] (2) Quantitative PCR Total fecal DNA was prepared from 22 patients with hepatocellular carcinoma (11 responders and 11 non-responders) in Example 1(2). Feces were also collected from 85 healthy individuals (ages 19-61, mean age 38.3, 43 men and 42 women), and total fecal DNA was extracted from them by the method described in Example 1(2).

[0049] Using these total fecal DNAs as templates, quantitative PCR was performed to determine the DNA copy number of the conserved region of S. stercoris using the quantitative PCR reagent "PowerTrack SYBR Green Master Mix" (Thermo Fisher Scientific) and the primers of SEQ ID NOs: 3 and 4. The PCR reaction was held at 95°C for 2 minutes, followed by 40 cycles of 95°C for 10 seconds, 50°C for 15 seconds, and 72°C for 20 seconds, followed by a final extension reaction at 72°C for 1 minute.

[0050] Similarly, quantitative PCR was performed to determine the DNA copy number of the 16S ribosomal RNA gene using the primers of SEQ ID NOs: 6 and 7. The PCR reaction was held at 95°C for 2 minutes, followed by 40 cycles of 95°C for 10 seconds, 60°C for 15 seconds, and 72°C for 15 seconds, followed by a final extension reaction at 72°C for 1 minute.

[0051] Since the DNA copy number of the 16S rRNA gene reflects the total bacterial count, and the DNA copy number of the Stercoris conserved region reflects the number of Bacteroides stercoli, the "DNA copy number of the Stercoris conserved region" per 1 μL of fecal total DNA solution was divided by the "DNA copy number of the 16S rRNA gene." This was used as the "Bacteroides stercoli proportion (Stercolis level)," and the average value was calculated for each group. Statistical analysis was performed using the medical statistical analysis software GraphPad Prism (GraphPad Software) using the Mann-Whitney test, with P<0.05 considered significant.

[0052] (3) Evaluation of the correlation between stercoli level and drug response The stercoli levels in the responder and non-responder groups are shown in Figure 1. As shown in Figure 1, the stercoli levels were significantly higher in the non-responder group compared to the responder group. In other words, hepatocellular carcinoma patients with a high proportion of Bacteroides stercoli as intestinal bacteria did not respond to drug treatment. Conversely, patients with a low proportion of Bacteroides stercoli as intestinal bacteria responded to drug treatment. These results demonstrate that Bacteroides stercoli can be used as an indicator to predict sensitivity to immune checkpoint inhibitors.

[0053] (4) Evaluation of the correlation between stercoli level and hepatocellular carcinoma susceptibility Next, Figure 2 shows the stercoli levels in the healthy subjects, HCC patient groups (responders and non-responders combined), responders, and non-responders. As shown in Figures 2(a)-(c), there were no significant differences in stercoli levels between the healthy subjects and patient groups, between the healthy subjects and responders, or between the healthy subjects and non-responders (ns). Furthermore, several healthy subjects had higher stercoli levels than patients, responders, or non-responders. This indicates that there was no correlation between the abundance of Bacteroides stercoli in the intestine and the presence or absence of HCC. In other words, the abundance of Bacteroides stercoli is not affected by the efficacy of immune checkpoint inhibitors (i.e., the reduction in bacterial counts is not due to the efficacy of the drug and the improvement of cancer).

[0054] <Example 3> Confirmation of correlation between comprehensive bacterial flora analysis results and quantitative PCR results To confirm the correlation between the results of comprehensive NGS analysis and the results of quantitative PCR using the primer set of SEQ ID NOs: 3 and 4 regarding the abundance of Bacteroides stercoli in the intestine, a simple linear regression analysis was performed. Specifically, for samples from 22 hepatocellular carcinoma patients, the quantitative PCR results (stercoli level) were plotted on the vertical axis (objective variable) and the NGS results (proportion of Bacteroides stercoli reads to total reads) on the horizontal axis (explanatory variable), and a regression equation was determined. The results are shown in Figure 3.

[0055] As shown in Figure 3, the P value was P<0.0001 and the coefficient of determination was R 2 = 0.9956, which shows a very high correlation between the NGS read ratio and the stercoli level of quantitative PCR. These results demonstrate that there is a high correlation between the results of comprehensive analysis by NGS and the results of quantitative PCR using the primer set of SEQ ID NOs: 4 and 5 regarding the presence ratio of Bacteroides stercoli in the intestine.

Claims

1. A method for predicting sensitivity to an immune checkpoint inhibitor, comprising detecting the amount of one or more enterobacteria selected from the group consisting of Bacteroides stercoris, Bacteroides coprocola, Sutterella wadsworthensis, and Romboutsia timonensis in a biological sample.

2. The method of claim 1, wherein the immune checkpoint inhibitor is an anti-PD-L1 antibody.

3. The method of claim 1, wherein the immune checkpoint inhibitor is used for cancer treatment.

4. A marker for predicting sensitivity to an immune checkpoint inhibitor, comprising one or more enterobacteria selected from the group consisting of Bacteroides stercoris, Bacteroides coprocola, Sutterella wadsworthensis, and Romboutsia timonensis.

5. A test kit for predicting susceptibility to an immune checkpoint inhibitor, comprising a PCR primer set for detecting the amount of one or more enterobacteria selected from the group consisting of Bacteroides stercoris, Bacteroides coprocola, Sutterella wadsworthensis, and Romboutsia timonensis in a biological sample.

6. The test kit according to claim 5 , wherein the PCR primer set is capable of amplifying all or part of the heparinase gene derived from Bacteroides stercolis.

7. A method for screening for an agent that enhances sensitivity to an immune checkpoint inhibitor, comprising detecting the amount of one or more enterobacteria selected from the group consisting of Bacteroides stercoris, Bacteroides coprocola, Sutterella wadsworthensis, and Romboutsia timonensis in a sample.

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