Method for providing information about colorectal cancer

Abstract

The present specification provides a method for providing information about colorectal cancer, and a kit and a drug screening method that are based thereon, the information provision method comprising the steps of: measuring the level of mRNA of an IgA maturation (IGAM) marker gene for a biological sample isolated from an individual, or the level of protein encoded by the mRNA; and determining the prognosis of colorectal cancer of the individual on the basis of the measured level of mRNA for the marker gene or the measured level of protein encoded by the mRNA.

Description

How to provide information about colon cancer

[0001] The present invention relates to a method for providing information on colon cancer based on an IgA maturation (IGAM) marker gene, a kit based thereon, and a drug screening method.

[0002] Colon cancer, or colorectal cancer, is a malignant tumor that develops in the cecum, colon, and rectum, originating in the mucosa, the innermost surface of the colon. A definitive diagnosis of colon cancer requires the detection of cancer cells through a biopsy performed through a colonoscopy. Most colon cancers are asymptomatic in their early stages, making diagnosis quite challenging. Currently, there are no non-invasive methods for predicting colon cancer. Because existing diagnostic methods often reveal colon cancer at an advanced stage, it is crucial to predict the development and causative factors of colon cancer and provide preventative measures for high-risk groups to reduce medical costs and prevent deaths caused by colon cancer.

[0003] Furthermore, colon cancer contains a complex mixture of malignant cells, non-transformed cells, and microorganisms. Among these microorganisms, pathogenic bacteria can further aggravate the disease. Furthermore, the presence of pathogenic bacteria can be used to determine the presence of colon cancer.

[0004] The microbiota refers to the microbial community, including bacteria, archaea, eukaryotes, and viruses, existing in a given environment. The microbiome refers to the sum total of these substances, including their genomes and metabolites. The gut microbiota and microbiome play a crucial role in human physiology and are known to significantly influence human health and disease through their interactions with human cells.

[0005] Among these commensal microorganisms, Fusobacterium (or Fusobacteria) is one of the most prevalent bacterial species in colorectal cancer tissues and may contribute to the development of colorectal cancer. More specifically, Fusobacterium is associated with human colorectal cancer, with Fusobacterium being infected in 40-60% of colorectal cancer patient tumor tissues, particularly in the right colon. Furthermore, Fusobacterium is selectively present in tumor cells at a concentration more than 10-fold higher than that of surrounding cells, which can increase the number of tumor-promoting myeloid cells, activate the β-WNT signaling pathway through the binding of FadA adhesin to E-cadherin of the host bacteria, and alter the antitumor suppressive immune response by promoting the T cell immunoreceptor with immunoglobulin and ITIM domain (TIGIT) on T cells and natural killer cells through the bacterial Fap2 protein. Additionally, Fusobacteria are known to be associated with BRAF gene mutations and microsatellite instability (MSI), which are commonly found in colorectal cancer.

[0006] Therefore, Fusobacteria have the characteristics of promoting colon cancer growth and inducing acquired resistance to chemotherapy, thereby contributing to a poor prognosis for colon cancer. Furthermore, this suggests that Fusobacteria may promote tumorigenesis through various mechanisms, including immune system evasion, induction of an inflammatory microenvironment, and activation of oncogenic pathways. However, the precise mechanisms by which Fusobacteria influence colon cancer outcomes within the tumor microenvironment remain unclear, necessitating the development of fundamental approaches to address this issue.

[0007] The background technology of the invention has been prepared to facilitate a better understanding of the present invention. It should not be construed as an admission that the matters described in the background technology of the invention constitute prior art.

[0008] Meanwhile, the inventors of the present invention noted differentiated changes in the tumor microenvironment in subjects infected with Puzobacterium , and discovered that the IgA-mediated immune mechanism was impaired by Puzobacterium infection. More specifically, the inventors of the present invention discovered that the mechanism and related pathways that can induce the conversion of B cells to IgA plasma cells and produce mature IgA plasma cells were damaged and reduced by Puzobacterium infection.

[0009] Furthermore, the inventors of the present invention were able to recognize that due to a decrease in mature IgA plasma cells capable of secreting sIgA caused by infection with Fuzobacterium, the secretion of sIgA is reduced or blocked, and accordingly, the immune mechanism capable of blocking bacterial invasion into the intestinal mucosa is impaired, which may cause chronic inflammation and have a negative impact on the individual.

[0010] Finally, the inventors of the present invention further discovered that this IgA maturation can be activated by a specific set of genes, and that the prognosis for colon cancer in an individual can be predicted based on this.

[0011] As a result, the inventors of the present invention have identified MEF2B, UTS2B, MT1E, TIMP1, SPINK2, JCHAIN, AL133467.1, TNFRSF4, TNFRSF18, ERLEC1, ENFRSF17, TXNDC5, MZB1, XBP1, SEL1L, UBE2J1, ITM2C, FCRL5, SPCS1, PRDX4, RPN1, DERL3, PHPT1, FKBP11, SLAMF7, LGALS1, PPIB, RABAC1, LMAN1, SSR3, CD63, AC012236.1, SSR4, PSAP, CD38, IGHA2, ZBTB38, MYDGF, SELPLG, PRDM1, NCLN, IGLC7, IGKC, ERN1, GSTP1, We developed a new information-providing method through a total of 55 IgA maturation (IGAM) marker genes, including PECAM1, ZBP1, IGLC3, IGHM, IGLC2, IGLC1, S100A6, IGHA1, PRR5, and RAB13.

[0012] In addition, the inventors of the present invention recognized that when the IgA maturation (IGAM) marker gene described above is used in conjunction with the presence or absence of Pujobacterium infection, it is possible to stratify individuals including colon cancer, and based on this, it is possible to provide information on personalized treatment strategies and prognosis for each individual.

[0013] Accordingly, the problem to be solved by the present invention is to provide a method for providing information on colon cancer, which can predict the prognosis of an individual based on the mRNA and coding protein of the IgA maturation (IGAM) marker gene. While infection with Fusobacterium may be measured concurrently, this may not be essential.

[0014] Furthermore, another problem to be solved by the present invention is to provide a kit for providing information on colon cancer, which includes a preparation for measuring the expression level of mRNA of an IgA maturation (IGAM) marker gene or a protein encoded by the mRNA for a biological sample isolated from an individual.

[0015] Furthermore, another problem to be solved by the present invention is to provide a method for screening drugs for colon cancer, including the steps of treating a sample isolated from an individual with a candidate substance, measuring the level of mRNA of an IgA maturation (IGAM) marker gene or a protein encoded by the mRNA in the sample treated with the candidate substance, and selecting a candidate substance that increases the level of mRNA of the marker gene or a protein encoded by the mRNA.

[0016] The tasks of the present invention are not limited to the tasks mentioned above, and other tasks not mentioned will be clearly understood by those skilled in the art from the description below.

[0017] In order to solve the above-described problem, the present invention provides a method for providing information on colon cancer, including the step of measuring the level of mRNA of an IgA maturation (IGAM) marker gene or a protein encoded by the mRNA for a biological sample isolated from an individual, and the step of determining the prognosis for colon cancer of the individual based on the level of mRNA for the measured marker gene or a protein encoded by the mRNA.

[0018] According to a feature of the present invention, the biological sample may be, but is not limited to, tumor tissue isolated from the right colon.

[0019] According to another feature of the present invention, the IgA maturation marker genes are MEF2B, UTS2B, MT1E, TIMP1, SPINK2, JCHAIN, AL133467.1, TNFRSF4, TNFRSF18, ERLEC1, ENFRSF17, TXNDC5, MZB1, XBP1, SEL1L, UBE2J1, ITM2C, FCRL5, SPCS1, PRDX4, RPN1, DERL3, PHPT1, FKBP11, SLAMF7, LGALS1, PPIB, RABAC1, LMAN1, SSR3, CD63, AC012236.1, SSR4, PSAP, CD38, IGHA2, ZBTB38, MYDGF, SELPLG, PRDM1, NCLN, IGLC7, IGKC, ERN1, GSTP1, PECAM1, It may include, but is not limited to, at least one of ZBP1, IGLC3, IGHM, IGLC2, IGLC1, S100A6, IGHA1, PRR5, and RAB13.

[0020] According to another feature of the present invention, the step of determining the prognosis includes the step of determining that the prognosis for the colon cancer of the subject is negative if the level of mRNA for the marker gene or the protein encoded by the mRNA is below a predetermined level.

[0021] According to another feature of the present invention, the predetermined level may be, but is not limited to, the median of the distribution of scores based on the total expression rank per individual of the IgA maturation marker gene measured by the Singscore R package.

[0022] According to another feature of the present invention, the method further comprises the step of determining whether a biological sample is infected with Fusobacterium nucleatum.

[0023] According to another feature of the present invention, the step of determining the prognosis includes a step of determining that the survival probability of the individual is lower than that of an individual that is negative for Pujobacterium (Fn(-)), when the infection with Pujobacterium is positive (Fn(+)) and the level of mRNA of the marker gene or the protein encoded by the mRNA is below a predetermined level.

[0024] According to another feature of the present invention, the step of determining the prognosis includes a step of determining that, if the infection with the determined Fuzobacterium is positive (Fn(+)) and the level of the mRNA of the measured marker gene or the protein encoded by the mRNA is below a predetermined level, the survival probability of the individual is lower than that of an individual that is Fuzobacterium negative (Fn(-)) and the level of the mRNA of the marker gene or the protein encoded by the mRNA is above a predetermined level.

[0025] According to another feature of the present invention, the step of determining the prognosis includes a step of determining that the survival probability of an individual is lower than that of an individual that is Fn(-) negative for Pujobacterium and has a level of mRNA of the marker gene or a protein encoded by the mRNA below a predetermined level when the infection with Pujobacterium is positive (Fn(+)) and the level of mRNA of the marker gene or a protein encoded by the mRNA is below a predetermined level.

[0026] According to another feature of the present invention, the step of determining the prognosis includes a step of determining that the survival rate of the individual is similar to that of a Fuzobacterium negative individual, when the infection with Fuzobacterium is positive (Fn(+)) and the level of mRNA of the marker gene or the protein encoded by the mRNA is equal to or higher than a predetermined level.

[0027] In order to solve other problems as described above, the present invention provides a kit for providing information on colon cancer, comprising a preparation for measuring the expression level of mRNA of an IgA maturation (IGAM) marker gene or a protein encoded by the mRNA for a biological sample isolated from an individual.

[0028] According to the features of the present invention, the IgA maturation marker genes are MEF2B, UTS2B, MT1E, TIMP1, SPINK2, JCHAIN, AL133467.1, TNFRSF4, TNFRSF18, ERLEC1, ENFRSF17, TXNDC5, MZB1, XBP1, SEL1L, UBE2J1, ITM2C, FCRL5, SPCS1, PRDX4, RPN1, DERL3, PHPT1, FKBP11, SLAMF7, LGALS1, PPIB, RABAC1, LMAN1, SSR3, CD63, AC012236.1, SSR4, PSAP, CD38, IGHA2, ZBTB38, MYDGF, SELPLG, PRDM1, NCLN, IGLC7, IGKC, ERN1, GSTP1, PECAM1, May include, but is not limited to, one of ZBP1, IGLC3, IGHM, IGLC2, IGLC1, S100A6, IGHA1, PRR5, and RAB13.

[0029] According to another feature of the present invention, the kit further comprises a preparation capable of detecting infection with Pujobacterium.

[0030] According to another feature of the present invention, the biological sample may be, but is not limited to, tumor tissue isolated from the right colon.

[0031] According to another feature of the present invention, the expression level of mRNA can be measured through at least one method selected from among FISH (Fluorescence In Situ Hybridization), NanoString nCounter analysis, polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), real-time PCR, RNase-6 protection assay (RPA), microarray, and northern blotting, but is not limited thereto.

[0032] According to another feature of the present invention, the protein expression level is measured by at least one method selected from among western blotting, radioimmunoassay (RIA), radioimmunodiffusion, enzyme-linked immunosorbent assay (ELISA), immunoprecipitation, flow cytometry, immunofluorescence, ouchterlony, complement fixation assay, and protein chip methods, but is not limited thereto.

[0033] In order to solve another problem as described above, the present invention provides a method for screening a drug for colon cancer, comprising the steps of treating a sample isolated from an individual with a candidate substance, measuring the level of mRNA of an IgA maturation (IGAM) marker gene or a protein encoded by the mRNA in the sample treated with the candidate substance, and selecting a candidate substance that increases the level of mRNA of the marker gene or a protein encoded by the mRNA.

[0034] Hereinafter, the present invention will be described in more detail through examples. However, these examples are provided merely to illustrate the present invention, and therefore, the scope of the present invention should not be construed as being limited by these examples.

[0035] The present invention can predict the prognosis of colon cancer patients. More specifically, the present invention relates to a method for treating MEF2B, UTS2B, MT1E, TIMP1, SPINK2, JCHAIN, AL133467.1, TNFRSF4, TNFRSF18, ERLEC1, ENFRSF17, TXNDC5, MZB1, XBP1, SEL1L, UBE2J1, ITM2C, FCRL5, SPCS1, PRDX4, RPN1, DERL3, PHPT1, FKBP11, SLAMF7, LGALS1, PPIB, RABAC1, LMAN1, SSR3, CD63, AC012236.1, SSR4, PSAP, CD38, IGHA2, ZBTB38, MYDGF, SELPLG, PRDM1, NCLN, IGLC7, IGKC, ERN1, GSTP1, PECAM1, ZBP1, IGLC3, Based on IgA maturation (IGAM) marker genes, including IGHM, IGLC2, IGLC1, S100A6, IGHA1, PRR5, and RAB13, the prognosis for survival in colon cancer patients can be predicted.

[0036] In addition, the present invention can systematically suggest a prognosis and treatment direction suitable for colon cancer individuals by classifying them by considering whether or not they are infected with Pujobacterium together with the aforementioned markers.

[0037] The effects according to the present invention are not limited to those exemplified above, and more diverse effects are included in this specification.

[0038] Figure 1 is a flowchart of a method for providing information on colon cancer according to one embodiment of the present invention.

[0039] Figure 2a is a schematic diagram of the research process to confirm the relationship between the immune mechanism of colon cancer and the prognosis according to Pujobacterium infection.

[0040] Figure 2b shows the results of immune composition changes following Pujobacterium infection in colon cancer.

[0041] Figure 2c is a graph of progression-free survival (PFS) according to Pujobacterium infection in patients with right-sided colon cancer.

[0042] Figures 3a to 3c show the results of cell analysis on the developmental mechanism of IgA-secreting plasma cells following infection with Puzobacterium.

[0043] Figures 4a to 4e show the results of cell analysis on the T cell-independent pathway mechanism of IgA-secreting plasma cells following infection with Puzobacterium.

[0044] Figures 5a to 5d show the results of an analysis of a gene network involved in IgA plasma cell maturation following Puzobacterium infection.

[0045] Figure 6 shows the results of survival analysis in TCGA-COAD (The Cancer Genome Atlas Colon Adenocarcinoma) according to the IGAM gene expression activity score.

[0046] Figures 7a and 7b show the results of analysis of the bacterial burden within tumors following Puzobacterium infection.

[0047] The advantages and features of the present invention, and the methods for achieving them, will become clearer with reference to the embodiments described in detail below together with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but may be implemented in various different forms. These embodiments are provided solely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention, and the present invention is defined solely by the scope of the claims.

[0048] In this document, the expressions "has," "may have," "includes," or "may include" indicate the presence of a feature (e.g., a number, function, operation, or component such as a part), but do not exclude the presence of additional features.

[0049] In this document, the expressions "A or B," "at least one of A and / or B," or "one or more of A or / and B" can include all possible combinations of the listed items. For example, "A or B," "at least one of A and B," or "at least one of A or B" can all refer to cases where (1) at least one A is included, (2) at least one B is included, or (3) at least one A and at least one B are included.

[0050] The terms "first," "second," "first," or "second," as used herein, may describe various components, regardless of order and / or importance, and are only used to distinguish one component from another, without limiting the components. For example, a first user device and a second user device may represent different user devices, regardless of order or importance. For example, without departing from the scope of the rights set forth in this document, a first component may be referred to as a second component, and similarly, a second component may also be referred to as a first component.

[0051] The term "diagnosis of colon cancer" as used herein refers to determining whether a patient is likely to develop colon cancer, has a relatively high risk of developing colon cancer, or has already developed colon cancer. The method of the present invention can be used to delay or prevent the onset of colon cancer in any specific patient at high risk of developing colon cancer through special and appropriate management. Furthermore, the method of the present invention can be clinically applied to diagnose colon cancer early and determine the most appropriate treatment method, thereby determining treatment.

[0052] The term "primer" as used herein refers to a single-stranded oligonucleotide, which may also include ribonucleotides and preferably may be a deoxyribonucleotide. The primer hybridizes or anneals to a portion of a template to form a double-stranded structure. In the present invention, the primer may hybridize or anneal to an NGS sequencing adapter sequence. Annealing refers to the juxtaposition of an oligonucleotide or nucleic acid to a template nucleic acid, and juxtaposition allows a polymerase to polymerize nucleotides to form a nucleic acid molecule complementary to the template nucleic acid or a portion thereof. Hybridization refers to the formation of a duplex structure by the pairing of complementary base sequences between two single-stranded nucleic acids. A primer can act as an initiation point of synthesis under conditions that induce synthesis of a primer extension product complementary to the template.

[0053] The term "amplification" as used herein refers to a reaction that amplifies a target nucleic acid sequence, and may include, but is not limited to, reverse transcription polymerase chain reaction (RT-PCR), multiplex PCR, real-time PCR, assembly PCR, fusion PCR, ligase chain reaction (LCR), and droplet-digital PCR (ddPCR).

[0054] The term "target gene sequence" as used herein refers to a nucleotide sequence present in a target gene or nucleic acid, specifically, a nucleotide sequence of a portion of a target region within a target gene or nucleic acid, wherein the "target region" is a site within the target gene or nucleic acid that can be modified by a guide nucleic acid-editor protein.

[0055] The term "nucleic acid" as used herein may refer to at least one nucleotide consisting of a sugar linked to an organic base (either a substituted pyrimidine such as cytosine, thymidine, and uracil, or a substituted purine such as adenine and guanine). More specifically, nucleic acids may include ribonucleic acid (RNA), deoxyribonucleic acid (DNA), methylphosphonate nucleic acids, S-oligosaccharides, cDNA, miRNA, and aptamers, and may include both naturally occurring and artificially synthesized ones. However, it may be preferably RNA and DNA, but is not limited thereto.

[0056] The term "about" as used herein refers to the typical error range for each value, which is readily known to those skilled in the art. References herein to "about" a value or parameter include embodiments relating to that value or parameter itself.

[0057] The term "patient or subject" as used herein is used interchangeably and refers to any single animal, more preferably a mammal (including non-human animals such as cats, dogs, horses, rabbits, zoo animals, cows, pigs, sheep, and non-human primates) in need of treatment. In certain embodiments, the patient herein is a human. The patient may be a "cancer patient," i.e., a person suffering from one or more symptoms of cancer, at risk of suffering from cancer, or suffering from cancer.

[0058] As used herein, the terms "level of expression" and "expression level" are used interchangeably and generally refer to the amount of a biomarker in a biological sample. "Expression" generally refers to the process by which information (e.g., genetically encoded and / or epigenetic information) is converted into a structure that exists and functions in said cell.

[0059] Thus, as used herein, "expression" refers to the transcription of a polynucleotide, translation of a polypeptide, or further a polynucleotide and / or polypeptide modification (e.g., post-translational modification of a polypeptide). Fragments of a transcribed polynucleotide, a translated polypeptide, or a polynucleotide and / or polypeptide modification (e.g., post-translational modification of a polypeptide) should also be considered expressed, whether they are derived from transcripts generated by alternative splicing (alternative splicing) or from degraded transcripts, or from post-translational processing of a polypeptide, e.g., by proteolysis.

[0060] Meanwhile, an "expressed gene" includes a polynucleotide transcribed as mRNA and then translated into a polypeptide, as well as a RNA transcribed but not translated into a polypeptide (e.g., mobile and ribosomal RNAs). The expression level for more than one gene of interest can be determined by aggregation methods known to those skilled in the art and disclosed herein, including, for example, by calculating the median or average of the expression levels of all genes of interest. Prior to aggregation, the expression level of each gene of interest can be normalized using statistical methods known to those skilled in the art and disclosed herein, including, for example, normalizing to the expression levels of one or more housekeeping genes, normalizing to the total library size, or normalizing to the median or average expression level value across all genes measured. In some cases, prior to aggregation across multiple genes of interest, the normalized expression levels of each gene of interest may be normalized using statistical methods known to those skilled in the art and also disclosed herein, including, for example, by calculating a Z-score of the normalized expression levels of each gene of interest.

[0061] The terms used in this document are used only to describe specific embodiments and may not be intended to limit the scope of other embodiments. The singular expression may include the plural expression unless the context clearly indicates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by those of ordinary skill in the art described in this document. Terms defined in general dictionaries among the terms used in this document may be interpreted as having the same or similar meaning in the context of the relevant technology, and shall not be interpreted in an idealized or overly formal sense unless explicitly defined in this document. In some cases, even if a term is defined in this document, it cannot be interpreted to exclude the embodiments of this document.

[0062] The individual features of the various embodiments of the present invention can be partially or wholly combined or combined with each other, and as can be fully understood by those skilled in the art, various technical connections and operations are possible, and each embodiment can be implemented independently of each other or can be implemented together in a related relationship.

[0063]

[0064] Method for providing information on colon cancer according to one embodiment of the present invention

[0065]

[0066] Hereinafter, with reference to FIG. 1, a method for providing information on colon cancer according to one embodiment of the present invention will be described in detail.

[0067] Figure 1 is a flowchart of a method for providing information on colon cancer according to one embodiment of the present invention.

[0068] Referring to FIG. 1, a method for providing information on colon cancer according to one embodiment of the present invention may include a step (S110) of measuring the level of mRNA of an IgA maturation (IGAM) marker gene or a protein encoded by the mRNA for a biological sample isolated from an individual, and a step (S120) of determining a prognosis for colon cancer of the individual based on the measured level of mRNA for the marker gene or the protein encoded by the mRNA.

[0069] First, the biological sample in the measuring step (S110) may be tumor tissue isolated from the right colon, but is not limited thereto, and may include all tumor tissues in the region corresponding to the colon in a colon cancer subject.

[0070] IgA maturation marker genes at the measuring step (S110) are MEF2B, UTS2B, MT1E, TIMP1, SPINK2, JCHAIN, AL133467.1, TNFRSF4, TNFRSF18, ERLEC1, ENFRSF17, TXNDC5, MZB1, XBP1, SEL1L, UBE2J1, ITM2C, FCRL5, SPCS1, PRDX4, RPN1, DERL3, PHPT1, FKBP11, SLAMF7, LGALS1, PPIB, RABAC1, LMAN1, SSR3, CD63, AC012236.1, SSR4, PSAP, CD38, IGHA2, ZBTB38, MYDGF, SELPLG, PRDM1, NCLN, IGLC7, IGKC, ERN1, GSTP1, It may include at least one of PECAM1, ZBP1, IGLC3, IGHM, IGLC2, IGLC1, S100A6, IGHA1, PRR5, and RAB13.

[0071] The step of determining the prognosis (S120) may include a step of determining that the prognosis for the individual's colon cancer is negative if the level of mRNA for the marker gene or the protein encoded by the mRNA is below a predetermined level. In this case, the predetermined level is established based on the expression score of the IgA maturation (IGAM) marker gene set of the discovery cohort in the method for providing information on colon cancer according to one embodiment of the present invention, and the activity for the IgA maturation marker gene can be classified based on this.

[0072] Furthermore, in the method for providing information on colon cancer according to one embodiment of the present invention, the discovery cohort is classified into groups based on the activity level of the IgA maturation marker gene (IGAM gene set), and thus, in the method for providing information on colon cancer according to one embodiment of the present invention, the predetermined level may be the median of the score distribution based on the total expression rank per individual of the IgA maturation marker gene measured by the Singscore R package.

[0073] Meanwhile, according to a method for providing information on colon cancer according to one embodiment of the present invention, the prognosis of colon cancer for an individual can be determined (predicted) based on not only the mRNA or protein level of the IgA maturation marker gene, but also the presence or absence of infection with Fusobacterium nucleatum.

[0074] Accordingly, a method for providing information on colon cancer according to one embodiment of the present invention may further include a step of determining whether a biological sample is infected with Fusobacterium nucleatum.

[0075] Furthermore, the method for providing information on colon cancer according to one embodiment of the present invention may further include a step of determining whether or not there is an infection as described above, and thus may include a step of determining the prognosis of the subject based on the step.

[0076] In relation to this, the step of determining the prognosis (S120) may include a step of determining that, if the infection with Pujobacterium is positive (Fn(+)) and the level of mRNA of the marker gene or the protein encoded by the mRNA is below a predetermined level, the survival probability of the individual is lower than that of an individual that is Pujobacterium negative (Fn(-)).

[0077] More specifically, the step of determining the prognosis (S120) may include a step of determining that, if the infection with Fusobacterium is positive (Fn(+)) and the level of mRNA of the marker gene or the protein encoded by the mRNA is below a predetermined level, the survival probability of the individual for colon cancer is lower than that of an individual who is Fusobacterium negative (Fn(-)) and the level of mRNA of the marker gene or the protein encoded by the mRNA is above a predetermined level.

[0078] Furthermore, the step of determining the prognosis (S120) may include a step of determining that, if the infection with Fuzobacterium is positive (Fn(+)) and the mRNA of the marker gene or the level of the protein encoded by the mRNA is below a predetermined level, the survival probability of the individual for colon cancer is lower than that of an individual who is Fuzobacterium negative (Fn(-)) and the level of the mRNA of the marker gene or the level of the protein encoded by the mRNA is below a predetermined level.

[0079] Additionally, the step of determining the prognosis (S120) may include a step of determining that the survival rate of the individual is similar to that of a Fuzobacterium negative individual when the infection with Fuzobacterium is positive (Fn(+)) and the level of mRNA of the marker gene or the protein encoded by the mRNA is above a predetermined level.

[0080] Ultimately, the method for providing information on colon cancer according to one embodiment of the present invention can predict the prognosis of colon cancer through the expression level of the IgA maturation marker gene. Furthermore, the method for providing information on colon cancer according to one embodiment of the present invention can classify and stratify individuals with colon cancer based on the presence or absence of Fusobacterium infection in addition to the aforementioned IgA maturation marker gene, and determine the prognosis for the survival rate of the individual based on the classification.

[0081] Meanwhile, the present invention may further include a kit for providing information on colon cancer based on a method for providing information on colon cancer according to one embodiment of the present invention.

[0082] Accordingly, a kit for providing information on colon cancer according to one embodiment of the present invention may include a preparation for measuring the expression level of mRNA of an IgA maturation (IGAM) marker gene or a protein encoded by the mRNA for a biological sample isolated from an individual.

[0083] At this time, the expression level of mRNA can be measured through at least one method selected from among FISH (Fluorescence In Situ Hybridization), NanoString nCounter analysis, polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), real-time polymerase chain reaction (Real-time PCR), RNase-6 protection assay (RPA), microarray, and northern blotting, but is not limited thereto, and can include all various methods capable of measuring mRNA.

[0084] Furthermore, the expression level of the protein may be measured by at least one method selected from among western blotting, radioimmunoassay (RIA), radioimmunodiffusion, enzyme-linked immunosorbent assay (ELISA), immunoprecipitation, flow cytometry, immunofluorescence, ouchterlony, complement fixation assay, and protein chip, but is not limited thereto, and may include any variety of methods capable of measuring the protein.

[0085] Furthermore, a kit for providing information on colon cancer according to one embodiment of the present invention may further include a preparation capable of detecting infection with Pujobacterium.

[0086] Meanwhile, the present invention may further include a drug screening method based on the method for providing information on colon cancer according to one embodiment of the present invention.

[0087] More specifically, in the method for providing information on colon cancer according to one embodiment of the present invention, high activity of the IgA maturation (IGAM) marker gene can result in enhanced immunity in individuals infected with Pujobacterium, thereby providing a prognosis similar to that of individuals negative for Pujobacterium.

[0088] Accordingly, based on the enhancement of the activity of the IgA maturation (IGAM) marker gene, a substance (drug) capable of enhancing the immune mechanism of an individual infected with Pujobacterium can be derived. Accordingly, the present invention can provide a drug screening method for colorectal cancer, including the steps of treating a sample isolated from an individual based on a method for providing information on colorectal cancer according to an embodiment of the present invention with a candidate substance, the step of measuring the level of mRNA of the IgA maturation (IGAM) marker gene or a protein encoded by the mRNA in the sample treated with the candidate substance, and the step of selecting a candidate substance that increases the level of mRNA of the marker gene or a protein encoded by the mRNA.

[0089]

[0090] Identification of the prognosis and immune mechanisms of colorectal cancer according to IgA maturation marker gene expression and Fusobacterium infection

[0091]

[0092] First, with reference to Figures 2a to 2c, the distribution of immune cells in colon cancer due to Pujobacterium infection and its relationship to prognosis will be described.

[0093] Figure 2a is a schematic diagram of the process of confirming the relationship between the immune mechanism of colon cancer and the prognosis according to Pujobacterium infection.

[0094] More specifically, to confirm the difference in cell distribution according to Pujobacterium infection, 12 colorectal tumor tissues (CRC tumor samples) from each of Pujobacterium-positive individuals (Fn(+)) and Pujobacterium-negative individuals (Fn(-)) were surgically resected and collected, and single cells were isolated, and single cell RNA sequencing (scRNA-seq) was performed. More specifically, single cell isolation was performed according to the manufacturer's instructions for the Human Tumor Dissociation Kit (Cat# 130-095-929, Miltenyi Biotec, USA), and fresh tumor tissues immediately after surgery were 1 mm thick. 3 Less than (<1 mm) 3), and collected in a gentleMACS C tube (Cat# 130-093-237, Miltenyi Biotec, USA) with RPMI 1640 medium containing Enzyme H, Enzyme R, and Enzyme A. Then, to separate cells from tumor tissue, the tube containing tumor tissue was placed in a cell collection device, gentleMACS Dissociator (Cat# 130-093-235, Miltenyi Biotec, USA), and GentleMACS programs h_tumor_01 and h_tumor_02 were executed, and each was incubated with rotation at 37°C for 30 minutes. Next, to obtain single-cell suspensions, the tubes containing cells isolated from tumor tissues were filtered through a 70 μm MACS SmartStrainer (Cat# 130-098-462, Miltenyi Biotec, USA), and the filtrate was centrifuged at 300 × g for 10 min at 4°C. The cell pellet obtained through centrifugation was then resuspended in 4 mL of RPMI 1640 medium (Cat# 11875093, Thermo Fisher Scientific, USA), and dead cells were removed using Ficoll-Paque PLUS (Cat# 17-1440-03, GE Healthcare, USA). Then, after washing and resuspension using PBS solution containing 0.1% bovine serum albumin (BSA, Cat# 15561020, Invitrogen, USA), the resuspended single cell suspension was lysed in LIVE / DEAD TMCell viability was assessed using the Viability / Cytotoxicity Kit (Cat# L3224, Invitrogen, USA). To increase cell viability within the single-cell suspension, the suspension was further purified using the Dead Cell Removal Kit (Cat# 130-090-101, Miltenyi Biotec, USA) and used as the final single-cell suspension for scRNA-seq analysis. The single-cell suspension was then processed using the Chromium system (10x Genomics, USA), and single-cell transcriptome profiles were generated using the 10x Chromium Single Cell 5' Gene Expression Dual Index library. In a cohort (24 samples), 5′ scRNA-seq libraries were prepared using the Chromium Next GEM Single Cell 5′ Library and Gel Bead Kit v1.1 (PN-1000165). The 5′ scRNA-seq libraries were sequenced on an Illumina NovaSeq 6000, and the sequenced reads were aligned to the human reference genome (GRCh38) using Cell Ranger software (v6.0.0). The Seurat R package (v4.0.0) was utilized for data processing. Cells with fewer than 200 features were initially removed. Cell quality control was then performed for each sample, and the mitochondrial read ratio, total read count, and feature count thresholds were evaluated. Doublets, in which two or more cells were captured together in a single droplet, were then identified and excluded using the DoubletFinder (v2.0.3) R package.Furthermore, the count matrix was log-normalized using the NormalizeData() function, and 3,000 variant features were identified using the FindVariableFeatures() function with the selection method set to 'vst'. At this time, T-cell receptor and immunoglobulin variable genes, which are known to have large patient-to-patient variant differences, were classified as 'bad genes' and removed from the identification list. The cell cycle score was calculated using the CellCycleScoring() function, which quantifies the degree of alignment with the transcriptional program of cells in the G1 or S / G2 / M phases, and this score was regressed against the mitochondrial ratio while scaling the data using the ScaleData() function. Next, principal component analysis (PCA) was performed using the RunPCA() function using the previously determined variant features as input. Next, after the top 50 principal components (PCs) were input, the RunHarmony() function of the Harmony (v1.0) R package was used to remove patient-specific signals and correct for batch effects between samples. Next, the k-nearest neighbors (kNN) graph was constructed by applying the FindNeighbors() function to the corrected 50 PCs, and the RunUMAP() function was applied to the same 50 coordinates to perform nonlinear dimensionality reduction. Cell clustering was then performed using the FindClusters() function at a resolution of 0.5, clusters annotated as epithelial cells, endothelial cells, goblet cells, fibroblasts, and myofibroblasts, clusters with high mitochondrial or cell cycle scores, and clusters without marker gene expression were removed. Cell subtype analysis was then performed on a cell-by-cell basis.

[0095] Accordingly, referring to Fig. 2a (b), which is a UMAP visualization of immune cells, a total of 22 immune cell types were identified from a total of 24 colon cancer subjects through the aforementioned process.

[0096] Next, Figure 2b shows the results of immune composition changes following Puzobacterium infection in colon cancer. The proportional changes between single-cell groups following Puzobacterium infection were evaluated based on Pearson residuals (r), which represent the deviation between the expected and observed cell counts, and are presented in a mosaic plot. Furthermore, increases compared to the expected count are expressed as positive numbers, while decreases are expressed as negative numbers.

[0097] Referring to Figure 2b, the composition of immune cells within the tumor appears to differ depending on the Puzobacterium infection.

[0098] More specifically, in the Fusobacterium -positive group (Fn (+)), most immune cells, including memory B, Naive T, M2 macrophage, helper T, cytotoxic T, Treg, Mast, CD16+ NK, M1 macrophage, DC, Migratory DC, ILC3, monocyte, T fh, and CD16-NK, were found to be decreased (r<-4), whereas Naive B, gd T (germinal center T cell), IgG plasma, NKT, pDC, and GC B cells were found to be increased (r<4). At this time, the increased Naive B, gd T, IgG plasma, NKT, pDC, and GC B cells are cells involved in immunoglobulin (Ig)-mediated immunity, which may mean that infection with Fusobacterium can change the intratumoral immune microenvironment of colorectal cancer. In particular, since cells related to immunoglobulin (Ig)-mediated immunity are altered by Pujobacterium infection, it may be suggested that immune mechanisms based on these cells may be a major therapeutic strategy in colorectal cancer including Pujobacterium infection.

[0099] In relation to this, Figure 2c is a graph of progression-free survival (PFS) according to Pujobacterium infection in colon cancer.

[0100] Referring to Fig. 2c (a), previous studies have reported that the presence of a tumor in the right colon and infection with Pujo bacterium can worsen the prognosis of colorectal cancer. Therefore, to confirm the prognostic impact of Pujo bacterium infection, bulk RNA sequencing data for tumors in the right colon in The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD) cohort were analyzed, and individuals with Pujo bacterium infection were identified using GATK's PathSeq. At this time, a total of 116 individuals were identified as Pujo bacterium-positive (Fn(+)) and a total of 63 individuals were identified as Pujo bacterium-negative (Fn(-)), and PFS was tracked based on this.

[0101] Accordingly, referring to (b) of Fig. 2c, the survival rate of the Fuzobacterium positive individual group (Fn(+)) is shown to have a lower disease-free survival rate of 0.25 to 0.50 after 2,000 days than the Fuzobacterium negative individual group (Fn(-)) which is 0.75 or higher.

[0102] That is, similar to previous studies, this may mean that infection with Pujobacterium may worsen the prognosis of colorectal cancer, and it may suggest that intratumoral immune changes caused by infection with Pujobacterium may have a significant impact on the prognosis of colorectal cancer.

[0103] Hereinafter, with reference to Figures 3a to 3c, the developmental mechanism of IgA-secreting plasma cells following Puzo bacterium infection will be described. Figures 3a to 3c show the results of cell analysis on the developmental mechanism of IgA-secreting plasma cells following Puzo bacterium infection.

[0104] As previously described in Figure 2b, the Fusobacterium positive group (Fn (+)) showed an increase in Naive B, germinal center T (gd T) cells, IgG plasma, NKT, pDC, and GC B cells, which are cells involved in immunoglobulin (Ig)-mediated immunity. In this regard, these B cells are usually found in Peyer's patches in the gastrointestinal tract (GALT), and can be activated to differentiate into IgA plasma cells within Peyer's patches. IgA plasma cells play an important role in mucosal immunity against intestinal commensal bacteria (microorganisms). More specifically, IgA plasma cells can polyreactively induce colonization and invasion of pathogens and neutralize bacteria by producing sIgA and binding to intestinal bacteria. That is, B cells and plasma cells may be very important in bacterial immunity in the gut mucosal, and B cells can differentiate into IgA plasma cells through interaction with immune cells such as T cells and macrophages within the GALT.

[0105] In relation to this, Figure 3a is a UMAP visualization graph for B cells and plasma cells in colon cancer.

[0106] Referring to (a) of Fig. 3a, single-cell trajectory analysis was performed between B cells and plasma cells for individuals with colon cancer through dimension reduction, clearly separating the B cells and plasma cells. At this time, they were clustered into a total of 11 subgroups using the Louvain algorithm.

[0107] Next, in order to confirm mature plasma cells, the expression of PRDM1 (encoding Blimp-1) was confirmed, and with reference to Fig. 3a (b), it can be suggested that there is a differential expression difference of PRDM1 by subgroup, and that each subgroup has a different identity.

[0108] In particular, the expression level of PRDM1 increases from the Cluster 7 region to the Cluster 9 region, and decreases from the Cluster 7 region to the Cluster 2 or 3 region. In other words, the direction of differentiation from B cells to IgA plasma cells can be confirmed through the expression of PRDM1, which is an indicator of mature IgA plasma cells.

[0109] Figure 3b shows the results of comparing the differentiation trajectory from B cells to IgA plasma cells and PRDM1 expression following infection with Fuzobacterium.

[0110] Referring to (a) of Fig. 3b, a trajectory from naive B cells to IgA plasma cells was constructed based on the clusters and the expression levels of PRDM1 in the graph of (a) of Fig. 3a described above, and it is shown that B cells have transcriptional changes during differentiation through a specific trajectory.

[0111] More specifically, referring to (b) of Fig. 3B, naive B cells appear to have a differentiation direction from cluster 7 to clusters 5, 9, 2, and 3. Furthermore, PRDM1 expression in the Fusobacterium-positive group (Fn(+)) appears to be significantly lower than that in the negative group (Fn(-)) at all differentiation stages (p<0.001). This suggests that Fusobacterium infection may delay the development of IgA plasma cells.

[0112] Figure 3c shows the RNA velocity and transition probability results of B cells and IgA plasma cells following infection with Fusobacterium bacterium. The statistical significance of the probability distribution was determined based on the Kolmogorov-Smirnov test.

[0113] Referring to (a) of Fig. 3c, it appears that there is a difference in RNA velocity between B cells and IgA plasma cells depending on whether or not they are infected with Puzobacterium, and that each has a different transfer pattern.

[0114] Furthermore, referring to Fig. 3c (b), the transition probability from cluster 5 to 3, the transition probability from cluster 5 to 9, and the transition probability from cluster 9 to 2 in the Fuzobacterium positive group (Fn(+)) are all lower than those in the negative group (Fn(-)) (p<0.001). This suggests that Fuzobacterium infection may decrease the likelihood of progression toward the normal differentiation pathway of IgA plasma cells, thereby leading to the differentiation of abnormal IgA plasma cells. Furthermore, the low transition probability results may support the results of increased Naive B and GC B cells in the Fuzobacterium positive group (Fn(+)) of Fig. 2b described above.

[0115] Finally, according to the results of Figures 3a to 3c described above, it may be suggested that Pujobacterium infection may impair the maturation of B cells into IgA plasma cells, which may negatively affect the sIgA-mediated immune defense function.

[0116] Differentiation of B cells into IgA plasma cells within the GALT can be stimulated through interactions with immune cells such as T cells and macrophages, and thus, stimulatory signals for differentiation of B cells into IgA plasma cells may include T cell-dependent and -independent signaling pathways.

[0117] Hereinafter, the mechanism of decreased maturation of IgA plasma cells in B cells due to Pujobacterium infection will be explained as a T cell-independent signaling pathway.

[0118] Figures 4a to 4e show the results of cell analysis on the T cell independent pathways of IgA-secreting plasma cells following infection with Puzobacterium.

[0119] Figure 4a is a schematic diagram of ligand-receptor interactions for the IgA-independent pathway of plasma cells and T cells.

[0120] B cells contain receptors for TACI, BCMA, and BAFFR, and antigen-presenting cells (APCs), such as myeloid cells, can contain ligands such as APRIL and BAFF, and the interaction of each receptor and ligand can contribute to the immune mechanism. More specifically, the interaction between BAFF and BAFFR can contribute to the maturation of B cells, the activation of BCMA by APRIL or BAFF can contribute to the survival of IgA plasma cells, and the interaction of APRIL or BAFF ligands and TACI can contribute to the IgA response to commensal bacteria.

[0121] That is, the immune mechanism based on the T cell-independent pathway of IgA plasma cells may be based on the TACI, BCMA and BAFFR receptors of B cells and the APRIL and BAFF ligands of APCs.

[0122] Accordingly, Figure 4b is a UMAP visualization graph of immune cells and their subpopulations associated with the T cell-independent pathway in colon cancer.

[0123] Referring to (a) of Fig. 4b, myeloid cells, which are immune cells associated with the T cell-independent pathway in colon cancer, were shown to include subsets of migrating DC, cDC, M1 macrophage, M2 macrophage, and monocyte, and were clustered into a total of 14 subgroups through the Louvain algorithm.

[0124] Referring to Fig. 4b (b), tumor-associated macrophages (TAMs), which are tumor-associated macrophages associated with the T cell-independent pathway in colon cancer, are shown to include subpopulations of Migratory DC, DC, prolif-TAMs, Reg-TAMs, Intermediate Mono, Angio-TAMs, LA-TAMs, NFKB-high DC, and Classical Monocyte. These subpopulations appear to be macrophages present in the antigen processing and presentation pathway.

[0125] Figure 4c shows the RNA velocity and turnover probability results of myeloid cells associated with the T-cell-independent pathway in colon cancer. The statistical significance of the probability distribution was determined based on the Kolmogorov-Smirnov test.

[0126] Referring to (a) of Fig. 4c, depending on whether or not the myeloid cells are infected with Pujobacterium, there is a difference in RNA velocity for each subgroup of myeloid cells, and each has a different kinetic pattern.

[0127] Meanwhile, a polarization phenomenon was observed in which surrounding clusters were oriented toward the TAM cluster.

[0128] However, referring to (b) of Fig. 4c, the Fusobacterium positive group (Fn(+)) appears to have a lower probability of transitioning from adjacent cell clusters (Angio-TAM, Prolif-TAM) to cell subtypes (LA-TAM, Reg-TAM) involved in antigen processing and presentation than the negative group (Fn(-)) (p<0.001).

[0129] That is, this could mean that Pujobacterium infection may reduce the probability of transitioning to an antigen processing and presenting cell state.

[0130] Figure 4d is a plot result for cell-cell interactions (CCI) between bone marrow cells, B cells, and IgA plasma cells.

[0131] Referring to Figure 4d, in the case of the Fusobacterium positive group (Fn(+)), there appears to be no interaction with the TACI receptor on IgA plasma cells and B cells based on the APRIL and BAFF ligands on M2 macrophages.

[0132] Additionally, for the Fusobacterium positive group (Fn(+)), no interaction with the TACI receptor on IgA plasma cells and B cells based on the APRIL ligand on DCs was observed.

[0133] That is, the interaction between APRIL and BAFF ligand-TACI receptor may be inhibited by Pujobacterium infection, thereby reducing sIgA induction function.

[0134] Furthermore, for the Fusobacterium positive group (Fn(+)), there appears to be no interaction with the BCMA receptor on IgA plasma cells based on the APRIL and BAFF ligands on M2 macrophages.

[0135] That is, the interaction between APRIL and BAFF ligand-BCMA receptor may be inhibited by Pujobacterium infection, and thus, the survival function of IgA plasma cells (PC survival) may be reduced.

[0136] Furthermore, in the case of the Fusobacterium positive group (Fn(+)), there appears to be no interaction with the BAFFR receptor on IgA plasma cells based on the BAFF ligand on M2 macrophages.

[0137] That is, the interaction between BAFF ligand and BAFFR receptor may be inhibited by Pujobacterium infection, and thus, B cell maturation function may be impaired.

[0138] Figure 4e is a circular plot result for the number of ligand-receptor interactions between myeloid cells, B cells, and IgA plasma cells.

[0139] Referring to Figure 4e, the Fuzobacterium positive group (Fn(+)) appears to have a lower number of interactions than the Fuzobacterium negative group (Fn(-)) in terms of all ligand-receptor interactions.

[0140] Ultimately, the results of Figures 4a to 4e suggest that Puzobacterium infection may impair T cell-independent immune signaling pathways in colon cancer.

[0141] The results of Figures 4a to 4e above suggest that infection with Fusobacterium tumefaciens can delay the development of B cells into IgA plasma cells by reducing (blocking) T cell-independent immune signals in colon cancer. Furthermore, the reduction (blocking) of T cell-independent immune signals can secondarily lead to the dysregulation of downstream molecular programs, i.e., downstream signals essential for sIgA (secretory IgA) production.

[0142] Hereinafter, by analyzing single cell transcriptome data during the development process from naive B cells to IgA plasma cells, we confirmed sub-signal abnormalities, and with reference to Figures 5a to 5d, we will explain the abnormalities in genes involved in IgA maturation following infection with Fusobacterium.

[0143] Figures 5a to 5d show the results of an analysis of the gene network involved in IgA plasma cell maturation following Puzo bacteria infection. For trajectory-based analysis, B cells and plasma cells were separated and analyzed using the Slingshot R package (v2.2.0). A lineage trajectory from naive B cells to IgA-secreting plasma cells was constructed by reflecting the pathways involved in IgA maturation. After constructing the lineage, genes related to the IgA maturation lineage that were differentially expressed depending on Puzo bacteria infection (differences between groups) were identified using the tradeSeq R package (v1.8.0). Next, a negative binomial generalized model was additionally applied using the tradeSeq fitGAM() function, and after integrating the count matrix, pseudotime, and cell weight information, the conditionTest() function was used to identify genes with different expression dynamics depending on Puzo bacteria infection. Furthermore, the clusterExpressionPatterns() function (nPoints=20) was used for gene clustering, and labeling was performed using the primaryCluster() function of the clusterExperiment R package (v2.14.0). Finally, gene clusters containing marker genes of IgA-secreting plasma cells, such as PRDM1, were selected.

[0144] Figure 5a depicts the results of pseudotime analysis of the developmental pathway from naive B cells to mature IgA plasma cells in colorectal cancer. Differentially expressed genes along this developmental pathway were identified using tradeSeq 30.

[0145] In relation to this, referring to (a) of Fig. 5a, the development of naive B cells into IgA plasma cells appears to be based on the pathways of clusters 1, 8, 7, 5, 9 and 2.

[0146] Furthermore, referring to (b) of Fig. 5a, the results of differential expression gene analysis according to pseudotime between the positive and negative groups infected with Puzobacterium identified a total of 55 genes involved in the maturation of IgA plasma cells. These 55 identified genes may be referred to as IGAM modules (IgA maturation modules) or IgA maturation marker genes, as they are involved in the maturation of IgA plasma cells.

[0147] Figure 5b shows the results of GO analysis (GO term enrichment analysis) for IGAM module genes.

[0148] Referring to Fig. 5b, the 55 gene clusters identified in the aforementioned Fig. 5a, i.e., the IGAM module genes, appear to be involved in biological processes such as protein N-linked glycosylation via asparagine, peptidyl-asparagine modification, negative regulation of retrograde protein transport (ER to cytosol), negative regulation of protein exit from endoplasmic reticulum, regulation of retrograde protein transport (ER to cytosol), and protein N-linked glycosylation, which may mean that they have a high possibility of participating in the corresponding processes in that order.

[0149] Accordingly, the IGAM module (IgA maturation module), a set of IgA maturation marker genes, appears to be primarily involved in the protein N-linked glycosylation pathway.

[0150] At this time, protein N-linked glycosylation (hereinafter referred to as glycosylation) can contribute to the maintenance and enhancement of sIgA-mediated mucosal immunity. More specifically, glycosylation facilitates the transcytosis of dimeric IgA through mucosal epithelial cells, allowing IgA to be secreted into the lumen. Furthermore, the glycosylated structures on IgA can directly interact with commensal and pathogenic bacteria.

[0151] Figure 5c shows the coexpression results of IGAM module genes following Pujobacterium infection.

[0152] Referring to Fig. 5c, the IGAM module gene expression of the Fuzobacterium positive group (Fn(+)) has a lower PCC (Pearson correlation coefficient) value than that of the Fuzobacterium negative group (Fn(-)), which may mean that coregulation within the IGAM module may be reduced by infection with Fuzobacterium.

[0153] Figure 5d is a dot plot result for IGAM module genes with reduced expression correlation following Pujobacterium infection.

[0154] At this time, each gene was sorted according to the difference in PCC average between the Fusobacterium negative group (Fn(-)) and the Fusobacterium positive group (Fn(+)), as shown in (a) and (b) of 5d, and its priority was determined based on the decrease in expression correlation, and then adjusted using -log10(p) of the Wilcoxon rank sum test.

[0155] Furthermore, referring to (b) of 5d, MEF2B, UTS2B, MT1E, TIMP1, SPINK2, JCHAIN, AL133467.1, TNFRSF4, TNFRSF18, ERLEC1, ENFRSF17, TXNDC5, MZB1, XBP1, SEL1L, UBE2J1, ITM2C, FCRL5, SPCS1, PRDX4, RPN1, DERL3, PHPT1, FKBP11, SLAMF7, LGALS1, PPIB, RABAC1, LMAN1, SSR3, CD63, AC012236.1, SSR4, PSAP, CD38, IGHA2, ZBTB38, MYDGF, SELPLG, PRDM1, NCLN, IGLC7, IGKC, ERN1, GSTP1, PECAM1, The expression correlations of ZBP1, IGLC3, IGHM, IGLC2, IGLC1, S100A6, IGHA1, PRR5, and RAB13 were shown to be decreased. In particular, referring to (c) of Fig. 5d, the Fuzobacterium positive group (Fn(+)) showed a significant decrease in the expression correlations of MEF2B, UTS2B, MT1E, TIMP1, SPINK2, JCHAIN, AL133467.1, TNFRSF4, TNFRSF18, ERLEC1, ENFRSF17, TXNDC5, MZB1, XBP1, SEL1L, and UBE2J1 (p<0.05).

[0156] That is, depending on the presence or absence of Pujobacterium infection, there may be differences in the expression of IGAM module genes, and MEF2B appears to have the greatest difference in expression, and the expression correlation decreases in the order of the genes listed above.

[0157] Therefore, it may mean that 16 genes, including MEF2B, UTS2B, MT1E, TIMP1, SPINK2, JCHAIN, AL133467.1, TNFRSF4, TNFRSF18, ERLEC1, ENFRSF17, TXNDC5, MZB1, XBP1, SEL1L, and UBE2J1, among the genes involved in sIgA maturation and function, were significantly dysregulated by infection with Pujot bacterium.

[0158] Ultimately, based on the results of 5a to 5d, Fusobacterium infection may lead to aberrant regulation of IGAM module genes in colon cancer, thereby reducing or blocking glycosylation associated with IgA, thereby reducing IgA secretion in the mucosa, and impairing gut bacterial defense function.

[0159] Figure 6 shows the results of survival analysis according to IGAM gene expression activity score in TCGA-COAD (The Cancer Genome Atlas Colon Adenocarcinoma). At this time, the singscore R package (v1.10.0) was utilized for robust rank-based expression scoring of the IGAM gene set in the TCGA data. TCGA samples with an IGAM expression score higher than the median were classified into the IGAM high activity group (IGAM-high), and samples with a score lower than the median were classified into the IGAM low activity group (IGAM-low) and used for analysis. Raw sequencing data for TCGA-COAD were accessed through the GDC (Genomic Data Commons) data portal, and the coefficient matrix and metadata were collected from the TCGA-COAD dataset using the TCGAbiolinks R package (v2.25.2). Clinical data were collected from only the TCGA data obtained from the right colon in the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR, v68). Data samples without clinical data were filtered out, and finally 179 TCGA sample data were used. Furthermore, for survival analysis according to Fusobacterium infection and IGAM gene expression, PFI (progress-free interval) data from TCGA-CDR were used as clinical data, and survival curves were estimated using the Kaplan-Meier method using the survfit() function of the survival (v3.2-7) R package, and were graphed using the ggsurvplot() function of the survminer (v0.4.9) R package.

[0160] Referring to Figure 6 (a), regardless of the presence or absence of Pujobacterium infection, the group with high IGAM module activity (IGAM-high) appears to have a longer survival time with a higher survival rate than the group with low activity (IGAM-low). This suggests that IGAM module genes may be independent prognostic indicators for determining the prognosis of colon cancer.

[0161] Accordingly, in a method for providing information on colon cancer according to one embodiment of the present invention, an IGAM module gene set can be used as an IgA maturation marker gene for predicting the prognosis of colon cancer. Furthermore, referring to Fig. 6 (b), the prognosis is shown to be stratified according to the presence or absence of Pujobacterium infection and the activity level of the IGAM module. More specifically, the group that is Pujobacterium negative and has high IGAM module activity (Fn(-) IGAM-high) has the highest survival rate, and the group that is Pujobacterium positive and has low IGAM module activity (Fn(+) IGAM-low) has the lowest survival rate and survival period.

[0162] Furthermore, in a comparison between the Fusobacterium negative (Fn(-)) groups, the group with higher IGAM module activity was shown to have a higher survival rate, and this was also shown to have the same result in the Fusobacterium positive (Fn(+)) group.

[0163] That is, it can be suggested that the presence or absence of Pujobacterium infection and the IGAM module gene can each be independent prognostic indicators that determine the prognosis of colorectal cancer, and the prognosis of colorectal cancer individuals can be predicted by stratifying them according to the presence or absence of Pujobacterium infection and the expression level of the IGAM module gene (IgA maturation marker gene). More specifically, in the method for providing information on colorectal cancer according to one embodiment of the present invention, individuals can be stratified according to the presence or absence of Pujobacterium infection and the expression level of the IGAM module gene, and the prognosis of the survival probability of colorectal cancer for each group can be predicted.

[0164] For example, for tissues isolated from an individual, if the presence of bacterial infection and the level of the IgA maturation marker gene, which is an IGAM module gene, are measured, and if the individual's infection with Pujot bacterium is positive (Fn(+)) and the level of the mRNA of the marker gene or the protein encoded by the mRNA is below a predetermined level, the individual's survival probability for colon cancer can be determined to be lower than that of an individual negative for Pujot bacterium. At this time, the predetermined level may mean, but is not limited to, the median value separating the group with high IGAM module activity (IGAM-high) and the group with low IGAM module activity (IGAM-low) in FIG. 6, and since the median value may relatively vary depending on the cohort, it may mean the median value of the score distribution based on the total expression rank per individual of the IgA maturation marker gene measured with the Singscore R package.

[0165] Ultimately, infection with Fusobacterium (Fn(+)) and expression of low IgA maturation marker genes (IGAM-low) may negatively impact the survival rate of individuals with colorectal cancer.

[0166] Meanwhile, the group with high Puzobacterium positive and IGAM module activity (Fn(+) IGAM-high) was found to have a similar survival rate of 0.50 to 0.75 with no statistical difference from the group with low Puzobacterium negative and IGAM module activity (Fn(-) IGAM-low) (p=0.6116).

[0167] Accordingly, expression of high IgA maturation marker gene (IGAM-low) may result in a positive prognosis for survival in individuals infected with Fusobacterium (Fn(+)), and based on this, the prognosis for the survival of the individual can be predicted.

[0168] Furthermore, activation of the IgA maturation marker gene (IGAM module) can improve the survival rate of individuals infected with Fuzobacterium tumefaciens, suggesting a personalized treatment strategy for each individual. Ultimately, IGAM activation in colon cancer patients infected with Fuzobacterium (Fn(+)) may be an important therapeutic strategy for improving survival and improving prognosis, and drug screening can be performed based on this mechanism.

[0169] For example, by treating a sample isolated from an individual with candidate substances that can enhance activity against the IgA maturation marker gene (IGAM module) and then measuring the level of its mRNA or the protein encoded by the mRNA, a drug (substance) that can have a positive effect on the prognosis of colon cancer can be selected.

[0170] Hereinafter, with reference to Figures 7a and 7b, we describe the intratumoral bacterial burden following Puzobacterium infection. Figures 8a and 8b show the results of an analysis of the intratumoral bacterial burden following Puzobacterium infection. In this case, tumor bulk RNA sequencing data was analyzed using the number of reads aligned to human gut prokaryotic genomes in the TCGA-COAD cohort. More specifically, the number of reads was analyzed using GATK PathSeq, and the bacterial burden within tumor tissue was quantified and presented on a log scale.

[0171] Figure 7a shows the results of bacterial distribution according to Pujobacterium infection in colon cancer.

[0172] Referring to (a) of Fig. 7a, the number of intratumoral bacterial leads in the Fusobacterium positive group (Fn(+)) was found to be significantly higher than that in the Fusobacterium negative group (Fn(-)) (p=1.3e-11).

[0173] That is, it may mean that the number of bacteria infiltrating into the tumor may increase due to Pujobacterium infection.

[0174] Furthermore, referring to (a) of Fig. 7a, the volcano plot results for the increased bacterial species in the Fusobacterium positive group (Fn(+)) are shown, and various bacterial species including pathogenic bacteria and commensal bacteria were shown to be significantly increased in the tumors for the Fusobacterium positive group (Fn(+)) (p<0.001). Furthermore, referring to (b) of Fig. 7a, the increased bacteria were shown to include F. animalis, K. ascrobata, C. acnes, L. adecarboxylata, K. michiganensis, C. granulosum, E. marmotae, C. freundii, M. funiformis, P. aeruginosa, C. afermentans, C. striatum, S. gordonii, C. farmeri, N. subflava, and F. magna.

[0175] That is, by infection with Pujobacterium, bacteria such as F. animalis, K. ascrobata, C. acnes, L. adecarboxylata, K. michiganensis, C. granulosum, E. marmotae, C. freundii, M. funiformis, P. aeruginosa, C. afermentans, C. striatum, S. gordonii, C. farmeri, N. subflava, and F. magna may increase or infiltrate into the tumor.

[0176] Figure 7b shows the results for the IgA binding probability of intratumoral bacteria in the Fusobacterium positive group (Fn(+)).

[0177] Referring to Figure 7b, in the Fusobacterium positive group (Fn(+)), the intratumoral infiltrating bacterial species were found to have a higher probability of binding to IgA (p=0.00029).

[0178] Ultimately, IgA-mediated mucosal immunity is impaired by Pujobacterium infection, allowing IgA-regulated bacterial species to invade tumors. Thus, the IgA-mediated mucosal immunity-suppressing mechanism by Pujobacterium infection may exacerbate (increase) intratumoral bacterial burden, and the increased intratumoral bacterial burden may induce chronic inflammation, which may negatively impact the prognosis of colorectal cancer.

[0179] Based on the above results, infection with Fuzobacterium can alter the composition of immune cells within colorectal cancer tumors, i.e., the tumor microenvironment, and primarily causes dysregulation of pathways related to the production and maturation of IgA-secreting plasma cells. This suggests that related subtypes, including B cells, may be key prognostic determinants in Fuzobacterium infection in colorectal cancer. Furthermore, Fuzobacterium infection can impair IgA maturation and sIgA secretion, thereby leading to loss of IgA-based immune function in the intestinal mucosa and inducing bacterial infiltration. Furthermore, chronic inflammation can be induced in the intestinal mucosa infected with bacteria, further negatively impacting the prognosis of the individual.

[0180] Meanwhile, these IgA-related immune functions are regulated by MEF2B, UTS2B, MT1E, TIMP1, SPINK2, JCHAIN, AL133467.1, TNFRSF4, TNFRSF18, ERLEC1, ENFRSF17, TXNDC5, MZB1, XBP1, SEL1L, UBE2J1, ITM2C, FCRL5, SPCS1, PRDX4, RPN1, DERL3, PHPT1, FKBP11, SLAMF7, LGALS1, PPIB, RABAC1, LMAN1, SSR3, CD63, AC012236.1, SSR4, PSAP, CD38, IGHA2, ZBTB38, MYDGF, SELPLG, PRDM1, NCLN, IGLC7, IGKC, ERN1, GSTP1, PECAM1, ZBP1, It can be caused by low expression (low activity) of IgA maturation (IGAM) marker genes, including IGLC3, IGHM, IGLC2, IGLC1, S100A6, IGHA1, PRR5, and RAB13. Furthermore, the activity of IgA maturation (IGAM) marker genes can improve the immune function reduced by infection with Fuzobacterium, which can have a positive effect on the prognosis of the individual. Accordingly, IgA maturation (IGAM) marker genes can be used as an independent prognostic predictor.

[0181] Furthermore, the IgA maturation (IGAM) marker gene can be used to classify individuals in more detail, such as whether they are infected with Pujobacterium, and thus to more specifically predict the prognosis of the individual.

[0182] Furthermore, as described above, the activity of the IgA maturation (IGAM) marker gene can improve immune function impaired by Pujobacterium infection, thereby improving the prognosis of the individual to a level similar to that of Pujobacterium negative individuals, and thus, personalized therapy targeting the IgA maturation (IGAM) marker gene may be possible.

[0183] Furthermore, based on this mechanism, drug screening can be performed on Fusobacterium-positive colon cancer subjects.

[0184]

[0185] Although the embodiments of the present invention have been described in more detail with reference to the attached drawings, the present invention is not necessarily limited to these embodiments, and various modifications may be implemented without departing from the technical spirit of the present invention. Therefore, the embodiments disclosed in the present invention are not intended to limit the technical spirit of the present invention, but to explain it, and the scope of the technical spirit of the present invention is not limited by these embodiments. Therefore, it should be understood that the embodiments described above are exemplary in all aspects and not restrictive. The protection scope of the present invention should be interpreted by the claims below, and all technical ideas within a scope equivalent thereto should be interpreted as being included in the scope of the rights of the present invention.

[0186]

[0187] [National Research and Development Project Supporting This Invention]

[0188] [Project ID] 1465038573

[0189] [Assignment Number] HI22C0353000023

[0190] [Ministry Name] Ministry of Health and Welfare

[0191] [Name of Project Management (Specialist) Agency] Korea Health Industry Development Institute

[0192] [Research Project Name] Health and Medical Technology Research and Development Project

[0193] [Research Project Name] Discovery of Diagnostic Circulating Tumor Biomarkers and Clinical Validation of Their Validity Through Proteomic Analysis of Primary Colon Cancer Tissues and Blood-Derived Extracellular Vesicles

[0194] [Name of the project performing organization] Yonsei University Industry-Academic Cooperation Foundation

[0195] [Research Period] January 1, 2023 - December 31, 2023

[0196]

[0197] [National Research and Development Project Supporting This Invention]

[0198] [Project ID] 1711188500

[0199] [Assignment Number] 2022R1A2C4001879

[0200] [Ministry Name] Ministry of Science and ICT

[0201] [Name of Project Management (Specialist) Institution] National Research Foundation of Korea

[0202] [Research Project Name] Mid-career Researcher Support Project

[0203] [Research Project Title] Elucidating the Packaging Principles of Tumor-Derived Exosomal DNA and Its Effects on Tumor Growth and Metastasis

[0204] [Name of the project performing organization] Yonsei University

[0205] [Research Period] March 1, 2023 - February 29, 2024

[0206]

[0207] [National Research and Development Project Supporting This Invention]

[0208] [Project ID] 1711197577

[0209] [Assignment Number] 00247969

[0210] [Ministry Name] Ministry of Science and ICT

[0211] [Name of Project Management (Specialist) Institution] National Research Foundation of Korea

[0212] [Research Project Name] Basic Research Project in Science and Engineering

[0213] [Research Project Title] Identifying the Colon Cancer-Causing Factor of Pujo Bacteria by Building a Gut Microbiome Disease Model Based on Single-Cell RNA Sequencing

[0214] [Name of the project performing organization] Yonsei University

[0215] Research Period: June 1, 2023 - February 29, 2024

[0216]

[0217] [National Research and Development Project Supporting This Invention]

[0218] [Project ID] 1345362988

[0219] [Assignment Number] 2022R1I1A1A01072740

[0220] [Ministry Name] Ministry of Education

[0221] [Name of Project Management (Specialist) Institution] National Research Foundation of Korea

[0222] [Research Project Name] Establishment of a Research Base for Science and Engineering

[0223] [Research Project Name] Isolation of Bacteriophages Targeting the Intratumoral Microbiome and Development of Precision Antitumor Therapy Using Bacteriophage Peptide Sequences

[0224] [Name of the project performing organization] Yonsei University

[0225] [Research Period] March 1, 2023 - February 29, 2024

[0226]

[0227] [National Research and Development Project Supporting This Invention]

[0228] [Project ID] 1711184591

[0229] [Assignment Number] 2022R1A2C1092062

[0230] [Ministry Name] Ministry of Science and ICT

[0231] [Name of Project Management (Specialist) Institution] National Research Foundation of Korea

[0232] [Research Project Name] Mid-career Researcher Support Project

[0233] [Research Project Title] Metagenomic Analysis-Based Study of Human Symbiotic Virome-Immune Interactions

[0234] [Name of the project performing organization] Yonsei University

[0235] [Research Period] March 1, 2023 - February 29, 2024

[0236]

[0237] [National Research and Development Project Supporting This Invention]

[0238] [Project ID] 1711187729

[0239] [Assignment Number] 2022M3A9F3016364

[0240] [Ministry Name] Ministry of Science and ICT

[0241] [Name of Project Management (Specialist) Institution] National Research Foundation of Korea

[0242] [Research Project Name] Source Technology Development Project

[0243] [Research Project Name] Development of an Oral Microbiome Functional Evaluation Platform and Disease Control Source Technology

[0244] [Name of the project performing organization] Yonsei University

[0245] [Research Period] January 1, 2023 - December 31, 2023

[0246]

[0247] [National Research and Development Project Supporting This Invention]

[0248] [Project ID] 1415186750

[0249] [Assignment Number] 20022947

[0250] Ministry of Trade, Industry and Energy

[0251] [Name of Project Management (Specialist) Agency] Korea Industrial Technology Evaluation and Planning Institute

[0252] [Research Project Name] Industrial Technology Innovation Project

[0253] [Research Project Name] Development of Human Microbiome Therapy to Enhance the Efficacy of Immunotherapy in Cancer Patients

[0254] [Name of the project performing organization] Yonsei University Industry-Academic Cooperation Foundation

[0255] Research Period: April 1, 2023 - December 31, 2023

[0256]

[0257] [National Research and Development Project Supporting This Invention]

[0258] [Project ID] 1711186373

[0259] [Assignment Number] 2018R1A5A2025079

[0260] [Ministry Name] Ministry of Science and ICT

[0261] [Name of Project Management (Specialist) Institution] National Research Foundation of Korea

[0262] [Research Project Name] Leading Research Center Support Project

[0263] [Research Project Name] Center for Systems Medicine for Chronic and Intractable Diseases

[0264] [Name of the project performing organization] Yonsei University

[0265] [Research Period] March 1, 2023 - February 29, 2024

Claims

1. A step of measuring the level of mRNA of an IgA maturation (IGAM) marker gene or a protein encoded by the mRNA for a biological sample isolated from an individual; and A method for providing information on colon cancer, comprising a step of determining a prognosis for colon cancer of the subject based on the level of mRNA for the measured marker gene or a protein encoded by the mRNA.

2. In paragraph 1, The above biological sample, A method for providing information on colorectal cancer, which is tumor tissue isolated from the right colon.

3. In paragraph 1, The above IgA maturation marker gene is, MEF2B, UTS2B, MT1E, TIMP1, SPINK2, JCHAIN, AL133467.1, TNFRSF4, TNFRSF18, ERLEC1, ENFRSF17, TXNDC5, MZB1, FKBP11, SLAMF7, LGALS1, PPIB, RABAC1, LMAN1, SSR3, CD63, AC012236.1, SSR4, PSAP, CD38, IGHA2, ZBTB38, MYDGF, SELPLG, PRDM1, NCLN, IGLC7, IGKC, ERN1, GSTP1, PECAM1, ZBP1, IGLC3, IGHM, A method for providing information on colon cancer, comprising at least one of IGLC2, IGLC1, S100A6, IGHA1, PRR5 and RAB13.

4. In paragraph 1, The steps for determining the above prognosis are: If the level of mRNA for the marker gene or the protein encoded by the mRNA is below a predetermined level, A method for providing information on colon cancer, comprising a step of determining that the prognosis for colon cancer of the above object is negative.

5. In paragraph 4, The above predetermined level is, A method for providing information on colorectal cancer, wherein the score is greater than or equal to the median of the distribution of scores based on the total expression rank of IgA maturation marker genes per individual measured using the Singscore R package.

6. In paragraph 1, A method for providing information on colon cancer, further comprising the step of determining whether the biological sample is infected with Fusobacterium nucleatum.

7. In paragraph 6, The steps for determining the above prognosis are: The above infection with Pujobacterium is positive (Fn(+)), If the level of mRNA of the above marker gene or the protein encoded by the above mRNA is below a predetermined level, A method for providing information on colon cancer, comprising a step of determining that the survival probability for the above-mentioned individual is lower than that of an individual that is Fn(-) negative for Fusobacterium.

8. In paragraph 7, The steps for determining the above prognosis are: The above-determined infection with the Pujobacterium is positive (Fn(+)), If the measured mRNA of the marker gene or the protein level encoded by the mRNA is below a predetermined level, The survival probability for the above object is A method for providing information on colon cancer, comprising the step of determining that the subject is Fn(-) negative and has a lower mRNA level of the marker gene or a protein encoded by the mRNA than a subject having a predetermined level or higher.

9. In paragraph 7, The steps for determining the above prognosis are: The above infection with Pujobacterium is positive (Fn(+)), If the level of mRNA of the above marker gene or the protein encoded by the above mRNA is below a predetermined level, The survival probability for the above object is Fn(-), A method for providing information on colon cancer, comprising a step of determining that the mRNA of the marker gene or the protein encoded by the mRNA is lower than that of an individual below a predetermined level.

10. In paragraph 6, The steps for determining the above prognosis are: The above infection with Pujobacterium is positive (Fn(+)), If the level of mRNA of the above marker gene or the protein encoded by the above mRNA is above a predetermined level, A method for providing information on colon cancer, comprising the step of determining that the survival rate for the above object is similar to that of a Pujobacterium negative object.

11. As a kit to provide information on colon cancer, A kit for providing information on colon cancer, comprising a preparation for measuring the expression level of mRNA of an IgA maturation (IGAM) marker gene or a protein encoded by said mRNA in a biological sample isolated from an individual.

12. In paragraph 11, The above IgA maturation marker gene is, MEF2B, UTS2B, MT1E, TIMP1, SPINK2, JCHAIN, AL133467.1, TNFRSF4, TNFRSF18, ERLEC1, ENFRSF17, TXNDC5, MZB1, FKBP11, SLAMF7, LGALS1, PPIB, RABAC1, LMAN1, SSR3, CD63, AC012236.1, SSR4, PSAP, CD38, IGHA2, ZBTB38, MYDGF, SELPLG, PRDM1, NCLN, IGLC7, IGKC, ERN1, GSTP1, PECAM1, ZBP1, IGLC3, IGHM, A kit for providing information on colon cancer, comprising at least one of IGLC2, IGLC1, S100A6, IGHA1, PRR5, and RAB13.

13. In paragraph 11, The above kit includes: A kit for providing information on colon cancer, further comprising a preparation capable of detecting infection with Pujobacterium.

14. In paragraph 11, The above biological sample, A kit providing information on colon cancer, isolated from the right colon.

15. In paragraph 11, The expression level of the above mRNA is A kit for providing information on colorectal cancer, measured by at least one method selected from among FISH (Fluorescence In Situ Hybridization), NanoString nCounter analysis, polymerase chain reaction (PCR), reverse transcription polymerase chain reaction (RT-PCR), real-time polymerase chain reaction (Real-time PCR), RNase-6 protection assay (RPA), microarray, and northern blotting.

16. In paragraph 11, The above protein expression level is, A kit for providing information on colorectal cancer, the information being measured by at least one method selected from among western blotting, radioimmunoassay (RIA), radioimmunodiffusion, enzyme-linked immunosorbent assay (ELISA), immunoprecipitation, flow cytometry, immunofluorescence, ouchterlony, complement fixation assay, and protein chip.

17. Step of processing a candidate substance into a sample separated from an object; A step of measuring the level of mRNA of an IgA maturation (IGAM) marker gene or a protein encoded by the mRNA for a sample treated with the above candidate substance; and A drug screening method for colon cancer, comprising a step of selecting a candidate substance that increases the level of mRNA of the marker gene or a protein encoded by the mRNA.

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