Ta cell detection reagent, cancer ta cell proliferation detection reagent, ta cell detection method, proliferative cancer ta cell detection method, ta cell purification method, proliferative cancer ta cell purification method, cell population, and non-human animals

Abstract

To provide a detection reagent that enables detection of TA cells.SOLUTION: TA cell detection reagents disclosed herein include a CD168 detection reagent.SELECTED DRAWING: Figure 7

Description

[Technical Field]

[0001] The present disclosure relates to reagents for detecting TA cells, reagents for detecting the proliferation of cancer TA cells, methods for detecting TA cells, methods for detecting proliferative cancer TA cells, methods for purifying TA cells, methods for purifying proliferative cancer TA cells, cell populations, and non-human animals. [Background technology]

[0002] In intestinal epithelial tissue, transit amplifying (TA) cells arise from intestinal epithelial stem cells present in crypts. These TA cells then proliferate and differentiate into endocrine cells, germ cells, absorptive epithelial cells, and other cells that make up the intestinal epithelium, forming epithelial cells of the villi (Non-Patent Document 1). [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Beumer, J. et.al., “Cell fate specification and differentiation in the adult mammalian intestine.”, Nat Rev Mol Cell Biol 22, 39-53 (2021). Summary of the Invention [Problem to be solved by the invention]

[0004] Although Lgr5 and other markers are known to be epithelial stem cell markers in intestinal epithelial tissue, no TA cell-specific markers have yet been identified. Therefore, a first object of the present disclosure is to provide a detection reagent capable of detecting TA cells.

[0005] Furthermore, cancer stem cells observed in colon cancer and other cancers produce proliferative cells and differentiate into cancer cells, and therefore hyperproliferative cells derived from cancer stem cells exhibit properties similar to normal TA cells (cancer TA cells). Therefore, it is expected that the TA cell marker can be used as a cancer TA cell marker. Therefore, a second object of the present disclosure is to provide a detection reagent for detecting the proliferation of cancer TA cells. [Means for solving the problem]

[0006] In order to achieve the first object, the detection reagent for TA cells (Transient Amplifying cells) of the present disclosure (hereinafter also referred to as "first detection reagent") includes a detection reagent for CD168 (Cluster of differentiation 168).

[0007] In order to achieve the first objective, the detection reagent for detecting the proliferation of cancer TA cells of the present disclosure (hereinafter also referred to as the "second detection reagent") includes the detection reagent for TA cells of the present disclosure.

[0008] The TA cell detection method of the present disclosure (hereinafter also referred to as the "first detection method") comprises the step of detecting CD168-positive TA cells by detecting CD168 in a sample containing intestinal cells.

[0009] The method for detecting proliferation in cancer TA cells of the present disclosure (hereinafter also referred to as the "second detection method") comprises the step of detecting cancer TA cells exhibiting proliferation by detecting CD168 in a cancer-derived sample.

[0010] The TA cell purification method of the present disclosure (hereinafter also referred to as the "first purification method") comprises the step of separating CD168-positive TA cells from a sample containing intestinal cells.

[0011] The method for purifying proliferative cancer TA cells of the present disclosure (hereinafter also referred to as the "second purification method") comprises the step of separating CD168-positive proliferative cancer TA cells from a cancer-derived sample.

[0012] The cell population of the present disclosure (hereinafter also referred to as the "first cell population") is a cell population containing CD168-positive TA cells, The cell population has a ratio of CD168-positive TA cells to the cells in the cell population of 10% or more.

[0013] The cell population of the present disclosure (hereinafter also referred to as the "second cell population") is a cell population containing CD168-positive proliferative cancer TA cells, The cell population has a ratio of CD168-positive cancer TA cells to the cells in the cell population of 10% or more. [Effects of the Invention]

[0014] According to the present disclosure, a detection reagent for TA cells can be provided, and further, according to the present disclosure, a detection reagent capable of detecting the proliferation of cancer TA cells can be provided. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 1 shows the results of scRNA-seq data analyzed from mouse intestinal epithelial organoids in Example 1. [Figure 2] FIG. 2 shows the distribution of CD168 expression in mouse intestinal tissues in Example 2. [Figure 3] FIG. 3 shows the results of immunostaining mouse intestinal epithelial organoids in Example 3. [Figure 4] FIG. 4 shows the expression distribution of CD168 in single-cell RNA analysis of mouse intestinal epithelial organoids in Example 3. [Figure 5] FIG. 5 shows the distribution of CD168 expression in each cell in the mouse normal intestinal epithelial organoid in Example 4. [Figure 6] FIG. 6 shows the expression distribution of CD168 in normal mouse intestinal epithelial organoids in Example 4. [Figure 7]Figure 7 shows the knock-in mouse construct in Example 4, electrophoresis photographs showing the introduction of mTurq2 into the genomic DNA of the knock-in mouse, and electrophoresis photographs showing the expression of mTurq2 in intestinal tissue lysates of the knock-in mouse. [Figure 8] FIG. 8 shows the distribution of CD168 expression in normal human intestinal tissues. [Figure 9] FIG. 9 shows the distribution of each marker in epithelial (Epi) cells extracted from the human colon cancer atlas (c295). [Figure 10] Figure 10 shows a heatmap of Jaccard coefficients calculated based on single-cell RNA-seq data of normal epithelial cell populations to quantify the degree of co-expression of CD168 with known stem cell and TA cell marker genes. [Figure 11] FIG. 11 shows gene expression of TA cell markers and CD168 in cells positive for each of the markers LGR5+, OLFM4+, and CD168+. [Figure 12] FIG. 12 shows a Spearman rank correlation heat map. [Figure 13] FIG. 13 shows the distribution of major biological processes (GO:BP) associated with CD168-positive cells in gene ontology (GO) analysis. [Figure 14] Figure 14 shows a heat map of genes with expression patterns similar to CD168 extracted from normal colon and four cancer subtypes (MMRdDiff, MMRdPoor, MMRpDiff, MMRpPoor), and calculated the Jaccard Index based on the percentage of cells expressing genes in common with CD168. [Figure 15] Figure 15 shows the relationship between genes based on the similarity of their expression patterns, visualized by compressing the dimension of the Jaccard Index profile obtained based on the similarity between CD168 and each gene using principal component analysis (PCA). [Figure 16]FIG. 16 shows the results of immunohistochemical staining of cells from normal human intestinal tissue. DETAILED DESCRIPTION OF THE INVENTION

[0016] <Definition> As used herein, CD168 (Cluster of differentiation 168) refers to a protein also known as hyaluronan-mediated motility receptor (HMMR) or receptor for hyaluronan-mediated motility (RHAMM). CD168 was initially thought to regulate cell motility through binding to hyaluronan, but recent studies suggest that CD168 is a cytoplasmic protein rather than a protein displayed on the cell surface or extracellularly. Information on CD168 derived from various animals can be found, for example, in existing databases. A specific example of human CD168 is the protein consisting of the following amino acid sequence (SEQ ID NO: 1), registered in UniProt under accession number O75330. Examples of human CD168 are registered at NCBI under accession numbers NP_001136028 (isoform a), NP_036616 (isoform b), NP_036617 (isoform c), and NP_001136029 (isoform d). Examples of mouse CD168 include a protein consisting of the following amino acid sequence (SEQ ID NO: 2), registered at UniProt under accession number Q00547.

[0017] Human CD168 (SEQ ID NO: 1) MSFPKAPKRFNDPSGCAPSPGAYDVKTLEVLKGPVSFQKSQRFKQQKESKQNLNVDKDTTLPASARKVKSSESKESQKNDKDLKILEKEIRVLLQERGAQDRRIQDLETELEKMEARLNAALREKTSLSANNATLEKQLIELTRTNELLKSKFSENGNQKNLRILSLELMKLRNKRETKM RGMMAKQEGMEMKLQVTQRSLEESQGKIAQLEGKLVSIEKEKIDEKSETEKLLEYIEEISCASDQVEKYKLDIAQLEENLKEKNDEILSLKQSLEENIVILSKQVEDLNVKCQLLEKEKEDHVNRNREHNENLNAEMQNLKQKFILEQQEREKLQQKELQIDSLLQQEKELSSSLHQKLCS FQEEMVKEKNLFEEELKQTLDELDKLQQKEEQAERLVKQLEEEAKSRAEELKLLEEKLKGKEAELEKSSAAHTQATLLLQEKYDSMVQSLEDVTAQFESYKALTASEIEDLKLENSSLQEKAAKAGKNAEDVQHQILATESSNQEYVRMLLDLQTKSALKETEIKEITVSFLQKITDLQNQ LKQQEEDFRKQLEDEEGRKAEKENTTAELTEEINKWRLLYEELYNKTKPFQLQLDAFEVEKQALLNEHGAAQEQLNKIRDSYAKLLGHQNLKQKIKHVVKLKDENSQLKSEVSKLRCQLAKKKQSETKLQEELNKVLGIKHFDPSKAFHHESKENFALKTPLKEGNTNCYRAPMECQESWK

[0018] Mouse CD168 (SEQ ID NO: 2) MSFPKAPKRFNDPSGCAPSPGAYDVKTSEATKGPVSFQKSQRFKNQRESQQNLNIDKDTTLLASAKKAKKSVSKKDSQKNDKDVKRLEKEIRALLQERGTQDKRIQDMESELEKTEAKLNAAVREKTSLSASNASLEKRLTELTRANELLKAKFSEDGHQKNMRALSLELMKLRNKRETKMRSMMVKQEGMELKLQA TQKDLTESKGKIVQLEGKLVSIEKEKIDEKCETEKLLEYIQEISCASDQVEKCKVDIAQLEEDLKEKDREILSLKQSLEENITFSKQIEDLTVKCQLLE TERDNLVSKDRERAETLSAEMQILTERLALERQEYEKLQQKELQSQSLLQQEKELSARLQQQLCSFQEEMTSEKNVFKEELKLALAELDAVQQKEEQSER LVKQLEEETKSTAEQLTRLDNLLREKEVELEKHIAAHAQAILIAQEKYNDTAQSLRDVTAQLESVQEKYNDTAQSLRDVTAQLESEQEKYNDTAQSLRDVTAQLESEQEKYNDTAQSLRDVTAQLESVQEKYNDTAQSLRDVTAQLESYKSSTLKEIEDLKLENLTLQEKVAMAEKSVEDVQQQILTAESTNQEYARM VQDLQNRSTLKEEIKEITSSFLEKITDLKNQLRQQDEDFRKQLEEKGKRTAEKENVMTELTMEINKWRLLYEELYEKTKPFQQQLDAFEAEKQALLNE HGATQEQLNKIRDSYAQLLGHQNLKQKIKHVVKLKDENSQLKSEVSKLRSQLVKRKQNELRLQGELDKALGIRHFDPSKAFCHASKENFTPLKEGNPNCC

[0019] As used herein, "stem cells" refer to cells that have the ability to self-replicate and differentiate into differentiated cells. The "stem cells" are present, for example, in each tissue and contribute to maintaining homeostasis in the body.

[0020] As used herein, "intestinal epithelial stem cells" refer to stem cells present in the intestinal epithelium. The intestinal epithelial stem cells can be identified, for example, by markers. The TA cells are, for example, Lgr5-, Ascl2-, and Olfm4-positive cells.

[0021] As used herein, "TA cells" (Transient Amplifying cells) refer to cells that are one stage differentiated from stem cells, have a faster cell cycle than stem cells, and actively undergo cell division. TA cells can be classified based on the expression of multiple genes characteristic of cells with high proliferation activity, such as Mcm5, Mcm6, Mki67, Pcna, Cdk4, Top2a, and Birc5.

[0022] As used herein, "cancer TA cells" refer to cells that are one stage differentiated from cancer stem cells in cancer tissues, and, like TA cells in normal tissues, have a faster cell cycle and actively undergo cell division compared to stem cells. The cancer TA cells can be identified, for example, by markers. The cancer cells can be classified using, for example, the expression of multiple proliferation-related genes, such as MCM5, MCM6, MKI67, PCNA, CDK4, TOP2A, and BIRC5, as indicators.

[0023] As used herein, "positive" (+) means that a higher signal is detected by an analytical method such as flow cytometry, which utilizes an antigen-antibody reaction, compared to a negative control reaction using negative control cells that do not express the antigen or an antibody that does not react with the antigen. In the case of cells derived from a non-human animal containing a reporter gene at the CD168 locus described below, the "positive" may also mean that a higher signal is detected compared to a negative control reaction using negative control cells that do not express the reporter gene. As used herein, "negative" (-) means that a signal equivalent to or lower than a negative control reaction using negative control cells that do not express the antigen or an antibody that does not react with the antigen. In the case of cells derived from a non-human animal containing a reporter gene at the CD168 locus described below, the "negative" may also mean that a signal equivalent to or lower than a negative control reaction using negative control cells that do not express the reporter gene.

[0024] As used herein, a "binding molecule" refers to a molecule capable of binding to a predetermined molecule. Examples of the binding molecule include nucleic acid molecules, proteins, sugar chains, and the like capable of binding to the predetermined molecule. Specific examples of the binding molecule include aptamers, antibodies, receptors, ligands, and the like capable of binding to the predetermined molecule.

[0025] As used herein, the term "antibody" refers to a protein comprising one or more polypeptides substantially or partially encoded by immunoglobulin genes or fragments of immunoglobulin genes. Examples of the antibody include polyclonal antibodies and monoclonal antibodies. Examples of the antibody isotype include IgG (e.g., IgG1, IgG2, IgG3, IgG4, etc.), IgM, IgA (e.g., IgA1, IgA2, etc.), IgE, IgD, IgY, etc. Examples of the origin of the antibody include antibodies derived from animals such as mammals such as mouse, rat, hamster, rabbit, goat, cow, horse, camel, and alpaca; birds such as chicken and ostrich; and cartilaginous fish such as shark. The antibody may be, for example, a camelid-derived heavy chain antibody (VHH antibody), a cartilaginous fish-derived immunoglobulin new antigen receptor (IgNAR), an antibody fragment (e.g., Fab, Fab', F(ab')2, single domain antibody (nanobody), etc.), a recombinant antibody (e.g., scFv, disulfide-linked Fv (dsFv), diabody, minibody, etc.). The antibody may also be an antibody-like molecule (e.g., affibody, anticalin, DARPins, monobody, etc.) produced by molecular biological techniques such as phage display and / or by protein engineering techniques using existing protein motifs.

[0026] As used herein, "nucleic acid" or "nucleic acid molecule" refers to a polymer of deoxyribonucleotides (DNA), ribonucleotides (RNA), and / or modified nucleotides. Examples of the nucleic acid include genomic DNA, cDNA, and mRNA. The nucleic acid may be, for example, single-stranded or double-stranded.

[0027] As used herein, "peptide" refers to a polymer composed of several unmodified (naturally occurring), modified, and / or artificial amino acids.

[0028] As used herein, "protein" or "polypeptide" refers to a polymer composed of unmodified (naturally occurring), modified, and / or artificial amino acids. The protein or polypeptide is a peptide having a length of 10 amino acids or more.

[0029] As used herein, the term "label" refers to a label used to distinguish a molecule or substance of interest from other molecules or substances. Examples of the label include fluorescent labels such as fluorescent dyes or fluorescent substances (e.g., fluorescein, fluorescein isothiocyanate, rhodamine), fluorescent protein labels such as green fluorescent protein (GFP), chemiluminescent labels such as luciferin and aequorin, enzyme labels such as horseradish peroxidase, alkaline phosphatase, β-galactosidase (β-gal), glucose oxidase, and luciferase, and the like. 3 H, 14 C. 15 N, 35 S, 90 Y, 99 Tc, 111 In, 125 I, 131 Radioisotopes (RI) such as I; etc.

[0030] As used herein, "proliferative" refers to cells continuously growing or the state in which cells are continuously growing.

[0031] As used herein, the term "specimen" (sample) may refer to a substance containing TA cells or cancer TA cells, a substance that may contain TA cells or cancer TA cells, or a substance whose presence or absence is unknown. Examples of the specimen include biological samples such as biological specimens or specimens. Examples of the biological specimen include samples containing body fluids; cells such as 3D cultured cells (e.g., organoids), cultured cell lines, and circulating cancer cells; tissues and organs (e.g., intestinal tissue); and specific examples include samples derived from epithelial tissues (e.g., cancer tissue, colon epithelium, and small intestinal epithelium). The specimen may be liquid or solid. When the specimen is solid, the present disclosure preferably prepares a liquid specimen by mixing the solid specimen with a liquid. When the specimen is derived from tissue, the tissue may be treated with a protease (e.g., collagenase, dispase, etc.) to separate cells from the tissue. Examples of the liquid include water; physiological saline; and buffer solutions such as Hank's buffer solution, Good's buffer solution (HEPES buffer solution, Tricine buffer solution, etc.), Tris buffer solution, phosphate buffer solution, and glycine buffer solution.

[0032] As used herein, "isolated" or "purified" means identified and separated and / or recovered from components in their natural state. The "isolation" or "purification" can be achieved, for example, by obtaining at least one purification step.

[0033] As used herein, the term "kit" generally refers to a unit in which the components to be provided (e.g., reagents, buffer solutions, other components such as additives, instructions, etc.) are provided separately in two or more compartments. The kit can be suitably used to provide a composition that is not provided in a mixed state, but is preferably mixed immediately before use, for reasons of stability, etc. The kit preferably includes, for example, instructions or instructions on how to use the components to be provided (e.g., reagents, culture media, other components such as additives, etc.), or instructions or instructions describing the processing of the components. As used herein, when the kit is used as a detection kit, the kit may include instructions, etc., describing how to use the detection reagents and other components, etc.

[0034] As used herein, "instructions" or "manuals" refer to written instructions to a technician or other user on how to use the present disclosure. The instructions may, for example, describe instructions on how to use the detection method, detection reagent, or detection kit of the present disclosure. The instructions may be a so-called package insert and are usually provided in paper form, but are not limited thereto and may also be provided in the form of, for example, electronic media (e.g., a homepage provided on the Internet, e-mail).

[0035] As used herein, the term "cell population" refers to a collection of cells that includes a desired cell and is composed of one or more cells. In the cell population, the proportion of the desired cells among all cells (also referred to as "purity") can be quantified, for example, as the proportion of cells expressing one or more markers expressed by the desired cells. The purity is, for example, the proportion among live cells. The purity can be measured by methods such as flow cytometry, immunohistochemistry, and in situ hybridization. The purity of the desired cells in the cell population is, for example, 5% or more, 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 55% or more, 60% or more, 65% or more, 70% or more, 75% or more, 80% or more, 85% or more, 90% or more, 91% or more, 92% or more, 93% or more, 94% or more, 95% or more, 96% or more, 97% or more, 98% or more, or 99% or more. The cell population can also be referred to as, for example, a cell preparation.

[0036] As used herein, the term "reporter gene" refers to an exogenous gene for visualizing a desired gene in a cell. The reporter gene can also be referred to as, for example, a marker gene.

[0037] The sequence information of the protein described in this specification or the nucleic acid encoding the same (e.g., DNA or RNA) is available from the Protein Data Bank, UniProt, GenBank, etc. Also, the nucleic acid sequence of RNA is also available from the corresponding DNA base sequence by using sequence conversion software or the like as appropriate.

[0038] Hereinafter, the present disclosure will be described with examples, but the present disclosure is not limited to the following examples or the like and can be arbitrarily changed and implemented. Also, each description in the present disclosure can be mutually applied unless otherwise specified. In this specification, when the expression "~" is used, it is used in the sense of including the numerical or physical values before and after it. Also, in this specification, the expression "A and / or B" includes "only A", "only B", and "both A and B".

[0039] <Detection reagent for TA cells> In one aspect, the present disclosure provides a detection reagent capable of detecting TA cells. The detection reagent for TA cells of the present disclosure includes a detection reagent for CD168. According to the first detection reagent of the present disclosure, TA cells can be detected.

[0040] As a result of intensive research, the inventors have found CD168 as a marker that can distinguish epithelial stem cells from TA cells, which are proliferative cells differentiated from the epithelial stem cells, in the large intestine epithelial tissue, and have thus established the present disclosure. According to the present disclosure, TA cells can be detected. Also, conventionally, there has been no marker that can be used for the isolation of TA cells. According to the present disclosure, for example, by using CD168 as an isolation marker, TA cells, particularly TA cells derived from epithelial stem cells, can be preferably isolated.

[0041] In the present disclosure, the detection reagent may be, for example, a binding molecule capable of binding to CD168. The binding molecule may be, for example, a known binding molecule capable of binding to CD168, or a newly prepared binding molecule prepared by SELEX, phage display, or the like. Specific examples of the binding molecule include antibodies against CD168, nucleic acid molecules such as aptamers, and the like.

[0042] The detection reagent for the TA cells may comprise, for example, a second binding molecule against the CD168 or a complex of the CD168 and the first binding molecule.

[0043] The first binding molecule and / or the second binding molecule may have a label. In this case, CD168 can be detected via the first binding molecule and / or the second binding molecule by detecting the label, thereby indirectly detecting TA cells. When the CD168 detection reagent contains the first binding molecule and the second binding molecule, it is preferable that one of the first binding molecule and the second binding molecule is supported on the carrier, and the other has a label. It is more preferable that the first binding molecule is supported on the carrier, and the second binding molecule has a label. The method for introducing a label into the first binding molecule and / or the second binding molecule can be carried out by appropriately adopting a conventionally known method or a method similar thereto, depending on the type of the first binding molecule and the second binding molecule. The label may be directly or indirectly bound.

[0044] When the first binding molecule and / or the second binding molecule has a label, the first detection reagent of the present disclosure may have a substrate capable of reacting with the label. In this case, the label is, for example, the enzyme label described above, and the substrate is a substance capable of reacting with the enzyme label. The substrate may be solid or liquid. When the substrate is liquid, it can also be called a substrate liquid.

[0045] The first binding molecule and / or the second binding molecule contained in the first detection reagent of the present disclosure may be in the form of a solution (liquid or gel) dissolved or dispersed in a buffer solution or the like, or may be in the form of a solid such as powder or granules, for example, obtained by freeze-drying a liquid dissolved in a buffer solution or the like.

[0046] In the first detection reagent of the present disclosure, each reagent or component may be in a solid form such as powder or granules, or in a liquid form such as a slurry (suspension), jelly, or solution.

[0047] The first detection reagent of the present disclosure may further include, for example, a container for storing the components of the detection reagent. In this case, the first detection reagent of the present disclosure may be provided in a form in which each component is contained in a different container (e.g., a tube, a plate, etc.). When the first detection reagent of the present disclosure includes multiple components, the first detection reagent of the present disclosure can also be referred to as, for example, a detection kit.

[0048] The first detection reagent of the present disclosure may include, for example, instructions or instructions.

[0049] The first detection reagent of the present disclosure can be suitably used for detecting TA cells. The TA cells are, for example, TA cells derived from intestinal epithelial tissue such as the large intestine or small intestine. The TA cells may be, for example, cells induced from TA cell precursor cells such as pluripotent cells or intestinal epithelial stem cells.

[0050] <Detection reagent for proliferating cancer TA cells> In another aspect, the present disclosure provides a detection reagent expected to be capable of detecting proliferative cancer TA cells. The detection reagent for detecting proliferative cancer TA cells of the present disclosure includes the detection reagent of the present disclosure, i.e., a detection reagent for CD168. The second detection reagent of the present disclosure is expected to be capable of detecting proliferative cancer TA cells.

[0051] The cancer cells include, for example, cancer TA cells of colorectal cancer, small intestine cancer, gastric cancer, esophageal cancer, breast cancer, pancreatic cancer, ovarian cancer, lung cancer, melanoma, and brain tumor, and preferably cancer TA cells of colorectal cancer or small intestine cancer.

[0052] <Method for detecting TA cells> In another aspect, the present disclosure provides a detection method capable of detecting TA cells. The method for detecting TA cells of the present disclosure includes a step (first detection step) of detecting CD168-positive TA cells by detecting CD168 in a sample containing intestinal cells. According to the first detection method of the present disclosure, TA cells can be detected.

[0053] In the first detection step, CD168 is detected in the sample containing intestinal cells. Therefore, the first detection method of the present disclosure may include, for example, a step of preparing a sample containing intestinal cells prior to the first detection step. The sample containing intestinal cells may be prepared, for example, by subjecting an intestine such as the large intestine or small intestine or the epithelial tissue of the intestine to protease treatment with collagenase, dispase, or the like. Further, the sample containing intestinal cells may be prepared, for example, by inducing from precursor cells of TA cells such as pluripotent cells or intestinal epithelial stem cells.

[0054] In the first detection step, CD168-positive TA cells are detected by detecting CD168 in a sample containing intestinal cells. The detection of CD168 can be carried out, for example, using the first detection reagent described above. Further, when the sample containing intestinal cells is derived from an animal containing a reporter gene at the CD168 locus described below, in the first detection step, the detection of CD168 can be carried out, for example, by detecting the expression of the reporter gene.

[0055] When CD168 is detected using a first detection reagent, the first detection step can qualitatively detect the presence or absence of CD168 in the sample, i.e., CD168-positive TA cells, by detecting the presence or absence of CD168 detected with the CD168 detection reagent.Furthermore, the detection step can quantitatively detect the amount of CD168-positive TA cells in the sample by detecting the amount of CD168 detected with the CD168 detection reagent, i.e., the amount of CD168-positive TA cells.

[0056] In the first detection step, CD168 can be detected using a molecule that binds to CD168. In this case, CD168 may be detected by an immunological technique. Examples of the immunological technique include direct competitive ELISA, indirect competitive ELISA, sandwich ELISA, direct competitive immunoassay, indirect competitive immunoassay, sandwich immunoassay, immunochromatography, spin immunoassay, and latex agglutination. When the CD168 detection reagent contains a label, examples of the immunological technique include fluorescent immunoassay (FIA), enzyme immunoassay (EIA), chemiluminescent immunoassay, chemiluminescent enzyme immunoassay, and radioimmunoassay (RIA), depending on the type of label.

[0057] As a specific example, the first detection step includes, for example, a step of contacting the sample with the first detection reagent of the present disclosure to form a complex between CD168 and the detection reagent (first complex formation step), and a step of detecting the complex between CD168 and the reagent in the sample (complex detection step).

[0058] In the complex formation step, the contact can be carried out, for example, by mixing the subject sample with the first binding molecule for CD168. The contact is preferably carried out in a liquid system containing water, physiological saline, the buffer solution, or the like.

[0059] In the complex formation step, the contact conditions (e.g., temperature, time, pH) between the sample and the first binding molecule are not particularly limited as long as they allow the formation of the complex. Specific examples of the contact temperature include 4 to 42°C, or 4 to 25°C. The contact time is, for example, 1 minute to 12 hours, or 1 to 12 hours. The pH during complex formation is, for example, 4 to 9.5, preferably 5 to 9 or 5.5 to 8.5, and more preferably 7 to 8.

[0060] The complex detection step is, for example, a step of detecting a complex between CD168 and the first binding molecule in the sample, i.e., a step of detecting the binding between CD168 and the first binding molecule. In the complex detection step, by detecting the presence or absence of binding between the two, for example, the presence or absence of CD168 in the sample, i.e., the presence or absence of CD168-positive TA cells, can be analyzed (qualitatively determined), and by detecting the degree of binding between the two (amount of binding), for example, the amount of CD168 in the sample, i.e., the amount of CD168-positive TA cells, can be analyzed (quantitatively determined).

[0061] The method for detecting the binding between CD168 and the first binding molecule is not particularly limited, and for example, a conventionally known method for detecting binding between substances can be used, specifically, SPR, fluorescence polarization, etc. Furthermore, when the first binding molecule has a label, the binding between CD168 and the first binding molecule may be detected in the complex detection step by directly or indirectly detecting the label in the complex. The method for detecting the label can be determined appropriately depending on, for example, the type of label. Furthermore, when a second binding molecule for the complex of CD168 and the first detection molecule is used, the complex detection step may indirectly detect CD168 by detecting the second binding molecule or the label of the second binding molecule.

[0062] When the detection of CD168 is the detection of a reporter gene at the CD168 locus, the first detection step can indirectly detect the presence or absence of CD168 in the sample, i.e., CD168-positive TA cells, for example, qualitatively by detecting the presence or absence of the reporter gene. Also, the detection step can indirectly detect the amount of CD168-positive TA cells in the sample, for example, quantitatively by detecting the amount of the reporter gene.

[0063] In the first detection step, CD168 can be indirectly detected, for example, by detecting a protein expressed by the reporter gene, and the method can be appropriately set depending on the type of reporter gene. Specifically, if the reporter gene is a gene encoding a fluorescent protein, CD168 can be indirectly detected in the first detection step by detecting the fluorescence of the fluorescent protein expressed by the reporter gene. If the reporter gene is a gene encoding a membrane protein, CD168 can be indirectly detected in the first detection step by detecting the membrane protein expressed by the reporter gene using a binding molecule for the membrane protein. If the reporter gene is a tag, CD168 can be indirectly detected in the first detection step by detecting the tag expressed by the reporter gene using a binding partner or binding molecule for the tag. The binding partner is a molecule that specifically binds to the tag.

[0064] In this way, the first detection method of the present disclosure can detect CD168 in a sample containing intestinal cells, thereby detecting CD168-positive TA cells.

[0065] <Method for detecting proliferating cancer TA cells> In another aspect, the present disclosure provides a detection method capable of detecting proliferative cancer TA cells. The detection method of proliferative cancer TA cells of the present disclosure includes a step (second detection step) of detecting cancer-derived TA cells exhibiting proliferation by detecting CD168 for a cancer-derived sample. According to the second detection method of the present disclosure, proliferative cancer TA cells can be detected.

[0066] In the second detection step, CD168 is detected for the cancer-derived sample. Therefore, the second detection method of the present disclosure may include, for example, a step of preparing the cancer-derived sample prior to the second detection step. The cancer-derived sample may be prepared, for example, by subjecting a sample derived from a cancer patient to protease treatment such as collagenase and dispase. Examples of the cancer-derived sample include samples derived from cancers of the intestine such as the large intestine and the small intestine.

[0067] The second detection step can be carried out in the same manner as the first detection step of the first detection method of the present disclosure, except that the cancer-derived sample is used instead of the sample containing intestinal cells. In the second detection step, proliferative cancer TA cells expected to be CD168 positive can be detected instead of the CD168 positive TA cells in the first detection step.

[0068] <Purification method of TA cells> In another aspect, the present disclosure provides a purification method capable of purifying TA cells. The purification method of TA cells of the present disclosure includes a step (first separation step) of separating CD168 positive TA cells for a sample containing intestinal cells. According to the first purification method of the present disclosure, TA cells can be purified.

[0069] In the first purification step, CD168 positive TA cells are separated from the sample containing intestinal cells. Therefore, the first purification method of the present disclosure may include a step of preparing a sample containing intestinal cells prior to the first purification step. The method for preparing the sample containing intestinal cells can, for example, make use of the description of the preparation method in the first detection method of the present disclosure.

[0070] The first separation step, for example, separates CD168-positive TA cells from a sample containing intestinal cells. The separation of CD168-positive TA cells includes, for example, a step of reacting the sample with the first detection reagent of the present disclosure to form a complex between CD168 and the detection reagent (second complex formation step), and a step of separating the complex between CD168 and the reagent in the sample to separate the CD168-positive TA cells (complex separation step).

[0071] The second complex formation step can be carried out, for example, in the same manner as the first complex formation step in the first detection method of the present disclosure. In the complex separation step, separation of the complex can be carried out, for example, by solid-liquid separation. In this case, the first detection reagent may be, for example, a carrier carrying the first binding molecule, or may have a label. The carrier may be, for example, particles such as magnetic particles or beads; membranes such as nitrocellulose membranes; substrates such as glass, plastic, or metal; or plates such as multi-well plates; and is preferably a particle because of its excellent operability. The first binding molecule may be provided in a form impregnated in a medium such as filter paper.

[0072] When the first binding molecule is supported on a carrier, the separation of the first complex can be carried out, for example, by separating a solid fraction containing the carrier from a liquid fraction.When the first binding molecule is supported on magnetic particles, the separation of the first complex can be carried out by generating a magnetic field using a magnet or the like to separate a solid fraction containing the magnetic particles from a liquid fraction.

[0073] When the first binding molecule has a label, the separation of the first complex can be carried out, for example, by detecting the label of the first binding molecule in the complex and separating the complex having the label.When the label is a fluorescent label, the separation of the first complex can be carried out by separating the fluorescently labeled positive fraction, i.e., the CD168 positive fraction, by flow cytometry or the like.

[0074] When the sample containing the intestinal cells is a sample derived from a non-human animal containing a reporter gene at the CD168 locus described below, the first purification step can be purified, for example, by detecting the reporter gene and separating the reporter gene-positive cells. The detection of the reporter gene can, for example, draw on the description of the detection of CD168 in the first detection method of the present disclosure.

[0075] In this way, the first purification method of the present disclosure can purify TA cells from the sample containing the intestinal cells. The purification can also be referred to as, for example, isolation, separation, or enrichment.

[0076] <Purification method of proliferative cancer TA cells> In another aspect, the present disclosure provides a purification method capable of purifying proliferative cancer TA cells. The purification method of proliferative cancer TA cells of the present disclosure includes a step (second separation step) of separating CD168-positive proliferative cancer TA cells from a cancer-derived sample. According to the second purification method of the present disclosure, it is expected that proliferative cancer TA cells can be purified.

[0077] The second separation step can be carried out in the same manner as the first separation step of the first purification method of the present disclosure, for example, except that the cancer-derived sample is used instead of the sample containing the intestinal cells in the first purification method of the present disclosure. In the second separation step, proliferative cancer TA cells expected to be CD168-positive can be separated instead of the CD168-positive TA cells in the first separation step.

[0078] <Cell population containing TA cells> In another aspect, the present disclosure provides a cell population containing TA cells. The cell population of the present disclosure is a cell population containing CD168-positive TA cells, and the proportion of CD168-positive TA cells in the cells in the cell population is 10% or more. According to the first cell population of the present disclosure, a cell population with an enriched content ratio of TA cells can be provided. Also, according to the first cell population of the present disclosure, for example, TA cells can be suitably analyzed.

[0079] The ratio of CD168-positive TA cells to the cells in the cell population is preferably 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 60% or more, 70% or more, 80% or more, 85% or more, 90% or more, 95% or more, 96% or more, 97% or more, 98% or more, or 99% or more. The ratio of CD168-positive TA cells in the cell population is, for example, 100% or less. The percentage of CD168-positive TA cells in the cell population is, for example, 10 to 100%, 20 to 100%, 30 to 100%, 40 to 100%, 50 to 100%, 60 to 100%, 70 to 100%, 80 to 100%, 85 to 100%, 90 to 100%, 95 to 100%, 96 to 100%, 97 to 100%, 98 to 100%, or 99 to 100%.

[0080] The proportion of CD168-positive TA cells in the first cell population can be measured, for example, by flow cytometry using a first binding molecule containing a fluorescent label. When the cell population is derived from a non-human animal containing a reporter gene at the CD168 locus described below, the proportion of CD168-positive TA cells in the first cell population can be evaluated, for example, by measuring the expression rate of the reporter gene.

[0081] <Cell population containing proliferative cancer TA cells> In another aspect, the present disclosure provides a cell population containing proliferative cancer TA cells. The cell population of the present disclosure is a cell population containing CD168-positive proliferative cancer TA cells, and the ratio of CD168-positive proliferative cancer TA cells to the total cells in the cell population is 10% or more. The second cell population of the present disclosure can provide a cell population enriched in the proportion of proliferative cancer TA cells. Furthermore, the second cell population of the present disclosure can be used to suitably analyze, for example, proliferative cancer TA cells.

[0082] The proportion of CD168-positive proliferative cancer TA cells among the cells in the cell population is preferably 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 60% or more, 70% or more, 80% or more, 85% or more, 90% or more, 95% or more, 96% or more, 97% or more, 98% or more, or 99% or more. The proportion of CD168-positive proliferative cancer TA cells in the cell population is, for example, 100% or less. The proportion of CD168-positive proliferative cancer TA cells in the cell population is, for example, 10-100%, 20-100%, 30-100%, 40-100%, 50-100%, 60-100%, 70-100%, 80-100%, 85-100%, 90-100%, 95-100%, 96-100%, 97-100%, 98-100%, or 99-100%.

[0083] The proportion of CD168-positive proliferative cancer TA cells in the second cell population can be measured, for example, by flow cytometry or the like using a first binding molecule containing a fluorescent label. When the cell population is derived from a non-human animal containing a reporter gene at the CD168 locus described below, the proportion of CD168-positive proliferative cancer TA cells in the second cell population can be evaluated, for example, by measuring the expression proportion of the reporter gene.

[0084] The second cell population is, for example, a cell population derived from intestinal tissue.

[0085] <Reporter non-human animal for TA cells> In another aspect, the present disclosure provides a non-human animal for use in detecting TA cells. The non-human animal for use in detecting TA cells of the present disclosure contains a reporter gene at the CD168 locus, and the reporter gene is operably linked to the promoter of the CD168 locus. According to the non-human animal of the present disclosure, TA cells can be suitably analyzed.

[0086] The reporter gene may be arranged so that its expression is controlled by the promoter that controls the expression of the CD168 gene.

[0087] Examples of the reporter gene include genes encoding fluorescent proteins such as GFP, EGFP, mCherrry, and mTurq2; membrane proteins such as NGFR; and tags such as Halo tag and SNAP tag.

[0088] Introduction of a reporter gene into the CD168 gene locus can be carried out with reference to the following literature. Sakuma T. et al., “MMEJ-assisted gene knock-in using TALENs and CRISPR-Cas9 with the PITCh systems.”, Nat Protoc 11, 118-133 (2016) Abe T. et.al., “Pronuclear Microinjection during S-Phase Increases the Efficiency of CRISPR-Cas9-Assisted Knockin of Large DNA Donors in Mouse Zygotes.”, Cell Rep. 2020 May 19;31(7):107653 [Example]

[0089] The present disclosure will be described in detail below using examples, but the present invention is not limited to the embodiments described in the examples. Unless otherwise specified, commercially available reagents and kits were used according to the attached protocols. In the following description, "mol / l" may also be abbreviated as "M."

[0090] [Example 1] Using single-cell RNA-seq expression analysis of mouse intestinal epithelial organoids, we searched for markers specific to TA cells and identified CD168.

[0091] (1) Isolation of intestinal crypts and organoid culture R26-H2B-EGFP (RIKEN, CDB0238K) mice and Lgr5-EGFP-IRES-creERT2 / R26-H2b-mCherry mice were used. Lgr5-EGFP-IRES-creERT2 / R26-H2B-mCherry mice were generated by crossbreeding Lgr5-EGFP-IRES-creERT2 mice (Jackson Laboratory, Strain #008875) with R26-H2B-mCherry mice (RIKEN, CDB0239K). Small intestines were collected from R26-H2B-EGFP and Lgr5-EGFP-IRES-creERT2 / R26-H2b-mCherry mice. The small intestines were opened longitudinally and cut into small pieces. The excised small intestine was washed multiple times with ice-cold phosphate-buffered saline (PBS, Fujifilm Wako Pure Chemical Industries, Ltd., 048-29805). The small intestine fragments were cultured in PBS containing 2.5 mM EDTA at 4°C for 30 minutes. The small intestine was pipetted to release the crypts into the supernatant. The supernatant was passed through a 70 μm cell strainer (Falcon, 352350) and centrifuged at 1,000 rpm for 5 minutes. The crypts isolated from the supernatant were embedded in growth factor-reduced Matrigel (BD Biosciences, #356231) and cultured at 37°C and 5% CO2 using IntestiCult Organoid Growth Medium (Stem cell technologies, #06005). To prevent anoikis, the medium was supplemented with 10 μM of ROCK inhibitor Y-27632 (Nacalai Tesque, #18190-96) for 2 days after initial purification. The medium was changed every 2–3 days. Organoids were passaged weekly at a split ratio of 1:3–1:6 by mechanical dissociation with pipetting.

[0092] (2) Sample preparation and single-cell RNA sequencing Normal mouse intestinal organoids generated from R26-H2B-EGFP mice were digested with 1 / 3 diluted TrypLE Select solution (Thermo Fisher Scientific, #1217701) at 37°C for 20 minutes. The digested sample was passed through a 20µm cell strainer (Sysmex, BW890320) to generate a single-cell suspension. Dead cells were removed from the suspension using a dead cell removal kit (Milteny Biotec, #130-090-101) to obtain a single-cell suspension containing highly viable cells. This cell suspension was converted into barcoded scRNA-seq libraries using the Chromium Next GEM Single Cell 3' Reagent Kit v3.1 (10x Genomics, #1000269) and Chromium Next GEM Chip G (10x Genomics, #1000127), aiming for an estimated 8,000 cells per library. The libraries were evaluated using a Bioanalyzer 2100 (Agilent Technologies) equipped with a high-sensitivity chip and sequenced on a NovaSeq™ 6000 sequencing platform (Illumina). From the sequencing, paired-end reads of 150 bp were generated.

[0093] (3) Preprocessing of scRNA-seq data The raw sequencing data were demultiplexed using Cell Ranger mkfastq (10x Genomics). Single-cell gene counts were calculated from the fastq files using Cell Ranger count (10x Genomics) according to the accompanying protocol. The output file was loaded as a Seurat object into statistical software (R (version 4.1.3)). High-quality cells were selected using filtering criteria: ≤700 or >8,000 expressed genes, ≤1,500 unique molecular identifiers (UMIs), and ≥22% of UMIs mapped to mitochondrial genes. Cells that met any of these criteria were excluded. Additionally, cells with low complexity scores (<0.80 log10 GenesPerUMI) were excluded. Based on these criteria, 8,367 cells were used for further analysis.

[0094] (4) scRNA-seq data analysis To normalize gene count data, we used a regularized negative binomial regression normalization technique known as SCTransform in Seurat (v4.0.2). The top 2,000 highly variable genes were identified using the vst method in the Find Variable Features function (Seurat). These genes were then used for dimensionality reduction (principal component analysis). The optimal number of principal components (PCs) was determined using ElbowPlot. The first 41 PCs were selected for clustering analysis (Louvain algorithm). Cell clusters were visualized using the uniform manifold approximation and projection (UMAP) algorithm. We used a likelihood-ratio test (log-fold change threshold of 0.25, minimum percentage of cells in which a gene was detected of 25%).

[0095] Differentially expressed genes (DEGs) in each cluster were identified using the FindAll Markers function (Seurat). Cell types were annotated by detecting standard cell-type-specific markers, and six major cell types were identified: stem cells, TA cells, absorptive epithelial cells, Paneth cells & goblet cells, enteroendocrine cells, and tuft cells. The results are shown in Figure 1.

[0096] Figure 1 shows the results of scRNA-seq data analysis of mouse intestinal epithelial organoids. Figure 1 shows the classification of clusters 0–15 using known marker genes as indicators. Based on the expression patterns of cell-specific markers, clusters 2, 4, and 7 were estimated to be absorptive epithelial cells; clusters 5 and 6 were estimated to be stem cells; clusters 0, 1, 9, 10, 11, and 13 were estimated to be TA cells; cluster 8 was estimated to be goblet cells and Pannett cells; clusters 3 and 14 were estimated to be unknown; cluster 12 was estimated to be enteroendocrine cells; and cluster 15 was estimated to be tuft cells. Of these, clusters 0, 1, 9, 10, 11, and 13 were estimated to be TA cells.

[0097] [Example 2] We extracted candidate genes specifically expressed in TA cells from the scRNA-seq data, and then screened mouse intestinal tissue for genes specifically expressed in the TA cell region in the upper crypt region using immunostaining. We confirmed that TA cells can be identified by CD168.

[0098] Genes expressed in TA cell clusters were extracted from the scRNA-seq data, and genes known to be universally expressed in proliferating cells were excluded. To screen for genes most highly expressed in the TA cell region, we examined the expression of CD168, Nusap1, Ube2c, Cenpe, SMC2, Top2a, Kif11, Tpx2, PRC1, PLK1, Survivin / Birc5, and other genes in mouse intestinal tissue.

[0099] Mouse intestinal tissue sections were deparaffinized using Tissue-clear (Sakura Finetech Japan, 1474). The sections were treated with ethanol (100% to 70% concentration) and rehydrated. The sections were then autoclaved at 105°C for 20 minutes in 10 mM citrate buffer (pH 6.0) for antigen retrieval. To prevent endogenous peroxidase activity, they were then treated with 0.3% H2O2. The sections were then treated with 10% normal goat serum in PBS at room temperature for 30 minutes. The sections were then incubated with primary antibodies overnight at 4°C. After treatment, the sections were incubated with secondary antibodies (biotin-goat anti-rabbit IgG, Jackson ImmunoResearch, #111-065-144) for 30 minutes at room temperature. The staining signals were visualized using DAB (Vector Laboratories, PK-6100). Hematoxylin was used for counterstaining.

[0100] In the screening of the above TA marker candidates, staining using anti-CD168 antibody (Abcam, ab124729) as the primary antibody yielded the most specific staining image in the TA cell region. The results are shown in Figure 2.

[0101] Figure 2 shows the distribution of CD168 expression in mouse intestinal tissue. As shown by the white box, CD168 was found in the crypts of the intestinal tissue, adjacent to epithelial stem cells and Bannett cells at the bottom, and on the villus side. This indicates that CD168 is expressed in TA cells in the intestinal tract, and that TA cells can be detected by detecting CD168.

[0102] [Example 3] Expression of CD168 was confirmed in mouse intestinal epithelial organoids, and it was confirmed that CD168 is expressed in the TA cell region.

[0103] (1) Expression of CD168 in mouse intestinal epithelial organoids Organoids derived from Lgr5-EGFP-IRES-creERT2 / R26-H2B-mCherry mice were fixed with 4% paraformaldehyde in PBS (Fujifilm Wako Pure Chemical Industries, Ltd., 163-20145) for 15 minutes at room temperature (approximately 25°C). After fixation, the organoids were washed three times with PBS. Then, the organoids were permeabilized with 0.3% Triton X-100 in PBS for 3 minutes at room temperature. After treatment, the organoids were treated with blocking buffer (1% BSA and 0.1% Triton X-100 in PBS) for 1 hour at room temperature. The organoids were then treated with rabbit anti-CD168 antibody (Abcam, ab124729) and chicken anti-GFP antibody (Abcam, ab13970) overnight at 4°C. The treated organoids were treated with Alexa Fluor 488-labeled goat anti-chicken IgY (Jackson ImmunoResearch, #103-545-155) and Alexa Fluor 647-labeled goat anti-rabbit IgG (Jackson ImmunoResearch, #111-605-144) at room temperature for 2 hours. Fluorescent images of the treated organoids were acquired using a confocal laser scanning microscope (ZEISS Microscopy, LSM880). Bright-field images were acquired using an inverted microscope (Olympus, IX-71). The results are shown in Figure 3.

[0104] Figure 3 shows the results of immunostaining mouse intestinal epithelial organoids. Lgr5 and H2B were confirmed in the crypt-like domains of mouse intestinal epithelial organoids, allowing the identification of the distribution of stem cells and nuclei. Meanwhile, CD168 was confirmed to be expressed in areas other than nuclei and stem cells in the crypt-like domains, particularly adjacent to Lgr5-positive cells and on the villus epithelial cell side, and was confirmed to be expressed in the area where TA cells are present. Therefore, it was confirmed that CD168 can also be used as a marker for TA cells in mouse intestinal epithelial organoids.

[0105] (2) Expression of CD168 in mouse intestinal epithelial organoids by single-cell RNA-seq analysis The CD168 expression distribution is superimposed on the scRNA-seq data analyzed from the mouse intestinal epithelial organoids in Example 1. These results are shown in Figure 4.

[0106] Figure 4 shows the distribution of CD168 expression in single-cell RNA analysis of mouse intestinal epithelial organoids. As shown in Figure 4, CD168 gene expression was confirmed in the area representing TA cells. In other words, it was found that CD168 is specifically expressed in the TA cell population.

[0107] [Example 4] Clustering analysis was performed on normal mouse intestinal organoids using a method different from that used in Example 1, and it was confirmed that CD168 expression is specific to TA cells.

[0108] Clustering analysis was performed using a different method from that used in Example 1 using the single-cell RNA sequencing data from the normal mouse intestinal organoids obtained in Example 1. To normalize the gene count data, a regularized negative binomial regression normalization technique known as SCTransform in Seurat (v5) was used. The vst method of the Find Variable Features function (Seurat) was used to identify the top 2,000 highly variable genes. Scaling was performed to remove unnecessary variation due to cell quality (proportion of mitochondrial reads). Principal component analysis (PCA) was performed on the expression of selected genes. Cells constituting normal mouse intestinal epithelial organoids could be divided into eight clusters. Based on the expression patterns of standard cell-type-specific markers, the clusters were estimated to be: Cluster 0, absorptive epithelial cells; Cluster 1, stem cells; Clusters 2-4, TA cells; Cluster 5, goblet cells and Pannett cells; Cluster 6, unknown; and Cluster 7, enteroendocrine cells. The results are shown in Figure 5. CD168 expression was then examined for each cell type. The results are shown in Figure 6.

[0109] Figure 5 shows the distribution of CD168 expression in each cell type in normal mouse intestinal epithelial organoids. Figure 6 shows the distribution of CD168 expression in normal mouse intestinal epithelial organoids. In Figure 5, the horizontal axis, from left to right, indicates 0: absorptive epithelial cells, 1: stem cells, 2-4: TA cells, 5: goblet cells and Pannett cells, 6: unknown, and 7: enteroendocrine cells, and the vertical axis indicates each gene. As shown in Figure 5, high CD168 expression levels were confirmed in the TA cell region. In Figure 6, the horizontal axis, from left to right, indicates 0: absorptive epithelial cells, 1: stem cells, 2-4: TA cells, 5: goblet cells and Pannett cells, 6: unknown, and 7: enteroendocrine cells, and the vertical axis indicates CD168 expression levels. As shown in Figure 6, CD168 expression was confirmed in clusters 3 and 4, i.e., clusters classified as TA cells. These results demonstrate that CD168 can be used as a TA cell-specific marker in normal mouse intestinal organoids, even when the clustering analysis method is changed.

[0110] [Example 5] In mouse intestinal tissue, we expressed a fluorescent protein (mTurquoise2: mTurq2) in a manner dependent on the CD168 promoter activity, and confirmed that cells expressing CD168 could be fluorescently labeled and detected.

[0111] CD168-mTurq2 knock-in mice were generated by inserting a fluorescent protein (mTurq2) into the ATG translation initiation codon of CD168. Expression of the fluorescent protein (mTurq2) in the intestinal tissue of the knock-in mice was confirmed by immunoblotting. Specifically, as shown in Figure 7(A), the knock-in mice were generated by introducing donor nucleic acids using the CRISPR / Cas9 system (see Sakuma T. et al., "MMEJ-assisted gene knock-in using TALENs and CRISPR-Cas9 with the PITCh systems," Nat Protoc 11, 118-133 (2016); Abe T. et al., "Pronuclear Microinjection during S-Phase Increases the Efficiency of CRISPR-Cas9-Assisted Knockin of Large DNA Donors in Mouse Zygotes," Cell Rep. 2020 May 19;31(7):107653). Figure 7(A) shows the knock-in mouse construct. In Figure 7(A), the upper panel shows the genome near Exon 1 of the CD168 gene. From the 5' end, the intron region, the non-coding region of Exon 1 (thin line), and the coding region of Exon 1 (thick line) are shown. In Figure 7(A), the middle panel shows the targeting construct. In Figure 7(A), the lower panel shows the state of the CD168 locus after introduction of the targeting construct. In the figure, "ad" indicates the position of the primers used for genotyping. Primer a is the Hmmr-mTurq2-Nter forward primer (SEQ ID NO: 3), primer b is the Hmmr-mTurq2-Nter reverse primer (SEQ ID NO: 4), primer c is the Hmmr-mTurq2-Cter forward primer (SEQ ID NO: 5), and primer d is the Hmmr-mTurq2-Cter reverse primer (SEQ ID NO: 6).The PCR product (amplified fragment) length for each primer set was 290 bases for both primers a / b and primers c / d. The arrows (CRISPR / Cas9) in the figure indicate the target position of the guide RNA. As shown in the middle of Figure 7(A), the donor nucleic acid had the same nucleotide sequences as the 40 bases on either side of the CD168 translation initiation codon ATG site (SEQ ID NO: 7 and SEQ ID NO: 8, respectively) as the 5' and 3' arms, respectively, with mTurq2 positioned between the two arms. The target sequence of the 20-base guide RNA was the nucleotide sequence shown in SEQ ID NO: 9, below. By introducing these CRISPR / Cas9 systems and donor nucleic acids into mouse embryos, two independent lines of CD168-mTurq2 knock-in mice were obtained. The introduction of mTurq2 into the knock-in mice was confirmed by PCR genotyping using primers a / d and genomic DNA extracted from the tails of each knock-in mouse. The results are shown in Figure 7(B). In addition, mTurq2 expression was confirmed by immunoblotting using a GFP antibody (BioVision, #3999) that recognizes mTurq2 after SDS-PAGE gel electrophoresis of intestinal tissue lysates from the knock-in mice. The results are shown in Figure 7(C).

[0112] [Table 1]

[0113] [Table 2]

[0114] Figure 7(B) is an electrophoretic photograph showing the introduction of mTurq2 into the genomic DNA of knockin mice, and Figure 7(C) is an electrophoretic photograph showing the expression of mTurq2 in intestinal tissue lysates of knockin mice. In Figure 7(B), the photographs show, from left to right, a wild-type mouse and a knockin mouse. In Figure 7(B), the upper row shows the results of nucleic acid amplification using primers a / b, and the lower row shows the results of nucleic acid amplification using primers c / d. As shown in Figure 7(B), mTurq2 was introduced into the genomic DNA of the knockin mice. As shown in Figure 7(C), mTurq2 was expressed in the intestinal tissue of the knockin mice.

[0115] [Example 6] We confirmed that TA cells can be detected in normal human intestinal tissue by immunohistochemical staining of CD168.

[0116] Immunohistochemical staining was performed to examine the localization and expression of CD168 in normal human intestinal tissue. For immunostaining, we used a primary antibody against CD168 (Abcam, ab124729), secondary antibodies (Nichirei, Histofine Simple Stain MAX-PO® and Histofine Simple Stain MAX-PO®), and ImmPRESS-Alkaline Phosphatase Polymer Reagents (Vector, MP-5402: anti-mouse, MP-5401: anti-rabbit). Histofine DAB (Nichirei) was used for brown staining, and counterstaining was performed with hematoxylin. The results are shown in Figure 8.

[0117] Figure 8 shows the distribution of CD168 expression in normal human intestinal tissue. CD168 staining was observed throughout the cells present in the TA region of human intestinal tissue, as shown by the area enclosed in the white line. However, CD168-positive cells were not detected in the stem cell niche. This indicates that CD168 is expressed in TA cells in the human intestine, and therefore, TA cells can be detected by detecting CD168.

[0118] [Example 7] Using the Human Colon Cancer Atlas, we compared the expression pattern of CD168 with that of known stem cell markers and confirmed that CD168-positive cells in the human intestinal epithelium represent a population of TA-like cells derived from stem cells.

[0119] To further evaluate whether CD168-expressing cells belong to TA-like cells similar to those observed in normal mouse intestines, we utilized the scatter plot tool in the Human Colon Cancer Atlas (c295) web resource (https: / / singlecell.broadinstitute.org / single_cell / study / SCP1162 / human-colon-cancer-atlas-c295#study-summary). Using this tool, we compared the CD168 expression pattern with known stem cell markers (e.g., LGR5 and OLFM4). The results are shown in Figure 9. Furthermore, to quantify the degree of co-expression with known stem cell and TA cell marker genes, we calculated the Jaccard coefficient based on single-cell RNA sequencing data of normal epithelial cell populations. The results are shown in Figure 10. Furthermore, LGR5 + , OLFM4 + , CD168 + To compare the gene expression of representative TA cell markers and CD168 in each marker-positive cell, the average expression value in each cell group was calculated. The results are shown in Figure 11.

[0120] Figure 9 shows the distribution of each marker in epithelial (Epi) cells extracted from the human colon cancer atlas (c295). In Figure 9, the top panel shows clustered t-SNE plots, with the left panel showing the expression patterns of CD168 and ASPM. The bottom panel shows the expression patterns of Lgr5 and OLFM4, markers associated with stem cell-like cell populations. The clustered t-SNE plots show epithelial cells grouped into distinct cell clusters based on their transcriptional profiles, with normal epithelial cells on the left and cancer epithelial cells on the right. As shown in Figure 9, in both normal and cancer tissues, CD168-expressing cells were spatially distinct from LGR5 and OLFM4. This suggests that, like normal mouse intestine, CD168-positive cells in human intestinal epithelium represent a stem cell-derived TA-like cell population.

[0121] Figure 10 shows a heatmap of the Jaccard index calculated based on single-cell RNA sequencing data from a normal epithelial cell population to quantify the degree of co-expression of CD168 with known stem cell and TA cell marker genes. The Jaccard index is defined as the intersection size of the expressing cell population (expression level > 0) for each gene divided by the union size. The gene expression matrix was filtered to remove cells with fewer than 200 expressed genes and genes with fewer than three expressed genes to eliminate the influence of low-quality cells and rare genes. Cells with expression levels of ≥ 1 for CD168 and each target gene were then extracted, and the Jaccard index was calculated based on these cell populations. The marker genes analyzed were LGR5, PROM1, ASCL2, SOX9, and OLFM4, which are representative intestinal stem cell genes, and PCNA, MKI67, BIRC5, TOP2A, and CENPF, which are TA cell markers. OLFM4 and PCNA have recently been treated as intermediate markers. The resulting Jaccard coefficients were visualized as heatmaps. All calculations were performed using Python with the pandas and seaborn libraries. Analysis based on the Jaccard coefficient revealed clear patterns of overlap between CD168 and each cell type marker gene. The stem cell markers LGR5 (0.048), PROM1 (0.054), and ASCL2 (0.069) had low Jaccard coefficients with CD168, indicating limited overlap in expressing cells. In contrast, the TA cell markers MKI67 (0.329), BIRC5 (0.335), TOP2A (0.338), and CENPF (0.339) showed high co-expression with CD168. OLFM4 (0.107), often considered a stem cell marker, showed a moderate Jaccard coefficient, similar to that of PCNA (0.101), an early TA marker. OLFM4 has been widely used as an intestinal stem cell marker, but in recent years its expression has also been confirmed in some TA cells, and it is thought to also have the aspect of being a marker indicating an intermediate stage between stem cells and proliferative progenitor cells.The Jaccard index of OLFM4 in our analysis was comparable to that of the TA marker PCNA, consistent with previous reports. These results support the notion that CD168 is co-expressed with TA cell markers rather than stem cell markers. In particular, the high Jaccard index with cell proliferation-related genes such as MKI67, TOP2A, and CENPF is consistent with the hypothesis that CD168 is associated with actively dividing cell populations. This result suggests that CD168 is involved in cell cycle progression and mitotic spindle dynamics. The clear separation of low-overlapping stem cell markers from high-overlapping TA markers in the Jaccard index heatmap supports the usefulness of CD168 and our method for analyzing gene expression patterns in heterogeneous cell populations.

[0122] Figure 11 shows the LGR5 + , OLFM4 + and CD168 + 11 is a graph showing gene expression of TA cell markers and CD168 in cells positive for each marker. In FIG. 11, the horizontal axis (X axis) represents the expression of LGR5 + OLFM4 + CD168 + The vertical axis (Y axis) shows the average expression value of each gene. The gene expression matrix used was filtered to include only normal epithelial cells, and LGR5 was selected based on the expression of the marker gene. + , OLFM4 + CD168 + Cell groups were extracted. The average expression value of each gene in the three marker-positive groups was calculated and visualized as a line graph. Representative TA marker groups (e.g., MKI67, TOP2A, CDC20) were all LGR5. + and OLFM4 + On the other hand, CD168 + In LGR5 cells, the expression of the TA markers showed a tendency to increase significantly. + and OLFM4 + The lowest expression in cells was CD168 +The expression pattern of CD168 was characterized by a significant increase in the expression of TA cells, with the highest increase in expression in TA cells. This dramatic change in expression strongly suggests that CD168 is hardly expressed in stem cells and is specifically expressed in a subset of TA cells that are proliferatively activated. Other common TA markers are LGR5 + While CD168 was also expressed to some extent on TA cells, it is thought to be a marker that sensitively detects the transition from stem cells to TA. These expression characteristics make CD168 an indicator of TA cells with high cell type specificity, different from conventional proliferation markers.

[0123] [Example 8] Spearman rank correlation analysis of CD168-coexpressed genes indicated that CD168-positive cells may retain TA-like transcriptional signatures regardless of cancer type or progression, suggesting that CD168 may function as a marker of TA-like cell state within cancer.

[0124] (1) Acquisition and preprocessing of scRNA-seq data We used scRNA-seq data from the c295 Human Colon Cancer Atlas (https: / / singlecell.broadinstitute.org / single_cell / study / SCP1162 / human-colon-cancer-atlas-c295) for this analysis. This scRNA-seq data set includes squamous and non-squamous cells from normal and cancerous human colon tissues, providing a reference for gene expression profiles in different cellular contexts. The raw count matrix was processed using Seurat (v4.0) in R. The scRNA-seq data were loaded and converted into Seurat objects, and a minimum threshold of one cell was applied to retain genes detected in at least one cell. Gene expression was normalized using the LogNormalize method with a scale factor of 10,000.

[0125] (2) Extraction of epithelial cells To focus on epithelial cells, only EPCAM-positive cells (EPCAM>0.000001) were retained for subsequent analysis.

[0126] (3) Dataset definition Epithelial cells were classified into five groups based on the origin of the c295 dataset and mismatch repair (MMR) status. These classifications were used to compare gene expression patterns and identify transcriptional signatures associated with CD168 expression in normal and cancer epithelial populations: c295:NormalEpi: Normal epithelial cells derived from non-cancerous colon tissue. c295:MMRdDiffEpi: Differentiated epithelial cells derived from mismatch repair deficient (MMRd) colon cancer tissue. c295:MMRdPoorEpi: Poorly differentiated epithelial cells derived from mismatch repair deficient (MMRd) colon cancer tissue. c295:MMRpDiffEpi: Differentiated epithelial cells derived from mismatch repair-competent (MMRp) colon cancer tissue. c295:MMRpPoorEpi: Poorly differentiated epithelial cells derived from mismatch repair-competent (MMRp) colon cancer tissue.

[0127] (4) Spearman rank correlation analysis of CD168 co-expressed genes and comparison of profiles between groups To evaluate the molecular characteristics of CD168-positive cells in more detail, we performed analyses on WT mouse organoids and human epithelial cells in the c295 dataset (NormalEpi, MMRdDiffEpi, MMRdPoorEpi, MMRpDiffEpi, and MMRpPoorEpi). This analysis aimed to assess potential differences in the transcriptional landscape of CD168-positive cells in colorectal cancer, related to animal species, cell environment, mismatch repair status, and cancer progression. First, we obtained CD168 expression values ​​using the FetchData function in Seurat. Spearman rank correlation coefficients with all genes in each dataset were calculated using the cor function in R (method = "spearman"). p-values ​​were calculated using the cor.test function, and genes meeting a significance level of p<0.05 were extracted as CD168-coexpressed genes (no multiple testing correction was applied). Next, we used the top 100 genes most strongly correlated with CD168 to recalculate the correlation matrix between these genes in each sample type (WT mouse organoid, NormalEpi, MMRdDiffEpi, MMRdPoorEpi, MMRpDiffEpi, MMRpPoorEpi) using Python to compare the differences in transcriptional structure according to repair status and differentiation stage. Finally, to visually evaluate the similarities and differences in co-expression patterns in each sample, we visualized the resulting correlation matrix as a heatmap using Python (seaborn, matplotlib). The results are shown in Figure 12.

[0128] Figure 12 shows a Spearman rank correlation heatmap. The horizontal and vertical axes represent, from left to right, WT mouse organoids, c295:NormalEpi samples, c295:MMRdDiffEpi samples, c295:MMRdPoorEpi samples, c295:MMRpDiffEpi samples, and c295:MMRpPoorEpi samples, respectively. The c295:NormalEpi sample represents epithelial cells isolated from normal colorectal tissue and serves as a non-malignant state. These cells were identified using EPCAM as an epithelial marker to ensure that the dataset reliably captures epithelial cells. The c295:MMRdDiffEpi sample is composed of epithelial cells derived from mismatch repair-deficient (MMRd) colorectal cancer, characterized by a high frequency of microsatellite instability (MSI-H) and a unique mutation profile. The c295:MMRdPoorEpi sample is composed of poorly differentiated epithelial cells derived from MMRd colon cancer tissue, reflecting a more advanced stage of the cancer. The c295:MMRpDiffEpi sample is composed of epithelial cells from mismatch repair-competent (MMRp) colon cancer, which are microsatellite stable (MSS) and typically associated with chromosomal instability (CIN). The c295:MMRpPoorEpi sample is composed of poorly differentiated epithelial cells derived from MMRp colon cancer, reflecting a more aggressive stage. As shown in Figure 12, the correlation between WT mouse organoids and NormalEpi was moderate at 0.42, indicating some commonality, although not perfect agreement. This suggests that there may be conserved transcriptional features between mouse and human CD168 co-expressed genes. However, differences in the environment and structure between the organoid culture system and actual normal tissue may also affect the transcriptional profile, in addition to differences between mouse and human species. Next, high correlations were observed between NormalEpi and MMRdDiffEpi (0.80) and between MMRdDiffEpi and MMRdPoorEpi (0.82), indicating that poorly differentiated and differentiated cells derived from MMRd have high transcriptional similarity to each other, suggesting that a TA-like transcriptional state may be relatively maintained in MMRd cancers as they progress.On the other hand, the correlation between MMRpDiffEpi and MMRpPoorEpi (0.64) was slightly lower, suggesting that transcriptional changes associated with differentiation state are more pronounced in MMRp cancers. Furthermore, the correlation with NormalEpi was higher for the MMRd group (0.80 and 0.72) than for the MMRp group (0.75 and 0.60), confirming that MMRp-derived cells exhibit greater transcriptional divergence from normal epithelial cells. Furthermore, the correlation between MMRdPoorEpi and MMRpPoorEpi (0.80) was relatively high, suggesting that common transcriptional features may be maintained across differences in mismatch repair state at low differentiation levels. However, MMRdPoorEpi correlated more strongly with MMRdDiffEpi (0.82), suggesting that mismatch repair deficiency, rather than differentiation state, may have a stronger influence on determining the transcriptional profile. These results suggest a structural difference between MMRd cancers, where a TA-like gene expression state is likely to be maintained even as the cancer progresses, and MMRp cancers, where more diverse differentiation and transcriptional changes occur as the cancer progresses. Notably, CD168-positive cells consistently maintained a TA-like gene expression profile regardless of the mismatch repair status (MMRd / MMRp) or the degree of cancer differentiation (Diff / Poor). These data suggest that CD168 may function as a molecular marker defining a TA-like cellular state across cancer stages and subtypes. In other words, CD168-positive cells may represent a stably emerging proliferative cell population within cancers, maintaining their fundamental properties regardless of cancer type or state.

[0129] [Example 9] Gene ontology (GO) analysis revealed that CD168-positive cells expressed genes related to cell division, the mitotic cell cycle, spindle formation, and kinetochore function.

[0130] (1) Identifying common genes in the dataset The top 100 correlated genes were analyzed using Spearman's rank correlation analysis of CD168 co-expressed genes in Example 8(4). After the analysis, 49 genes were identified that were commonly co-expressed with CD168 in all WT mouse organoids, c295:NormalEpi, c295:MMRdDiffEpi, c295:MMRdPoorEpi, c295:MMRpDiffEpi, and c295:MMRpPoorEpi. The 49 genes were selected from the top 100 genes in the Spearman's rank correlation coefficient of CD168 expression in the dataset, and only consistently co-expressed genes were included. The 49 genes are shown in Table 3 below.

[0131] [Table 3]

[0132] Table 3 shows 49 genes that are commonly expressed with CD168 in WT mouse organoids, c295:NormalEpi, c295:MMRdDiffEpi, c295:MMRdPoorEpi, c295:MMRpDiffEpi, and c295:MMRpPoorEpi. As shown in Table 3, by selecting genes present in all six datasets, it became possible to identify a conserved molecular signature of CD168-positive cells.

[0133] (2) Gene Ontology (GO) analysis To further investigate the biological significance of the 49 genes, a Gene Ontology (GO) analysis was performed using the database g:Profiler (https: / / biit.cs.ut.ee / gprofiler / gost). The GO analysis focused on significantly enriched biological processes (GO:BP). The analysis results were ranked based on the adjusted p-value after correction for multiple testing, and items with an adjusted p<0.05 were considered significant. The results were presented in a bubble plot. The results are shown in Figure 13.

[0134] Figure 13 shows the distribution of major biological processes (GO:BP) associated with CD168+ cells in gene ontology (GO) analysis. In Figure 13, the horizontal axis (x-axis) shows the number of genes associated with each GO term, and the vertical axis (y-axis) lists the biological process terms. The size of each bubble corresponds to the number of genes included in that GO term, and the color intensity is based on the -log10 of the p-value (adjusted p-value) after multiple testing correction, with higher significance indicated by darker colors. To improve visibility, only the top 20 significant GO terms ranked based on the adjusted p-value are displayed. As shown in Figure 13, CD168+ cells were significantly enriched for GO terms related to cell cycle progression and mitosis. Specifically, pathways related to cell division, mitotic cell cycle, spindle assembly, and chromosome segregation were significantly involved.

[0135] [Example 10] Many of the genes co-expressed with CD168 are commonly expressed in both normal and cancerous tissues, indicating that CD168 constitutes a fundamental network important for maintaining cell division ability, rather than a cancer-specific network.

[0136] In the five human-derived datasets excluding WT mouse organoids from the above dataset, the top 100 genes co-expressed with CD168 were classified into genes commonly or specifically expressed in normal, MMRp, and MMRd specimens, and their characteristics were compared. The results are shown in Table 4. It was shown that some of the genes co-expressed with CD168 were uniquely expressed in cancer, and in both MMR-deficient (MMRd) and MMR-normal (MMRp) cancers.

[0137] [Table 4]

[0138] Table 4 classifies the top 100 genes co-expressed with CD168 in each dataset, and classifies the genes that are commonly or specifically expressed in Normal, MMRp, and MMRd samples. "Genes Common to All Human Samples" indicates the genes that were included in the Top 100 lists common to all five datasets: Normal, MMRp (Poor and Differentiated), and MMRd (Poor and Differentiated). "Genes Specific to Cancer" indicates cancer-specific genes that are included in both MMRp and MMRd but not in Normal. "Genes Lost in Cancer" indicates genes that were lost in cancer, that were included in the Top 100 in Normal but not in either MMRp or MMRd. "MMRd-Specific Genes" and "MMRp-Specific Genes" indicate characteristic genes that were only present in the Top 100 lists for MMRd or MMRp, respectively. The values ​​shown for each gene represent the average Spearman rank correlation coefficient (ρ) across five human datasets, representing the strength of co-expression with CD168. Genes commonly detected across all human samples included many factors involved in cell cycle progression and chromosome segregation, such as AURKA, CDC20, BIRC5, and MKI67. These findings suggest that CD168 consistently functions as part of the fundamental cell division network, even during oncogenesis. Meanwhile, genes specifically co-expressed with MMRp and MMRd included many genes involved in chromosome replication and repair and mitotic phase control. These findings suggest that the CD168 network may be enhanced or reorganized depending on the cancer state. In particular, genes thought to be associated with CIN (e.g., TRIP13 and MYBL2) were found in MMRp, suggesting an adaptive role for CD168 in chromosomal instability. Furthermore, genes present only in normal tissues but lost in cancer are factors involved in nucleotide repair and cell cycle control, which may function as a regulatory brake on the CD168 network.These results suggest that while CD168+ cells maintain their fundamental proliferative identity, their regulatory networks change in response to genomic instability, potentially affecting cancer heterogeneity and adaptive capacity.

[0139] Coordinated expression of cell cycle-related genes in CD168-positive cells and their alterations in cancer Based on expression data from normal human colonic tissues, CD168+ cells co-expressed several key regulators involved in cell cycle and mitotic progression, suggesting that these cells represent a proliferation-committed cell population with high mitotic potential and fidelity. In particular, high expression of SGO1 indicates activation of regulatory mechanisms maintaining sister chromatid cohesion and fidelity of chromosome segregation. Furthermore, co-expression of the mitotic kinases PLK1 and AURKA suggests that active transition from late cell cycle to mitosis is promoted in CD168+ cells. Increased expression of DLGAP5 was also observed, which contributes to spindle stability and strengthens kinetochore-microtubule attachment, possibly supporting rapid and accurate cell division. Furthermore, extensive co-expression of regulators involved in various stages of the cell cycle, including CENPF, BIRC5, CDC20, CCNB1, and TOP2A, confirmed that the entire cell cycle program is highly activated in CD168+ cells. These results indicate that CD168 is not merely a proliferation marker but also a core marker of TA cells, involving mitotic activity and precise regulation. Furthermore, comparison of the expression profile in cancer cells revealed that many of these CD168-coexpressed genes were conserved in cancer cells, suggesting that cancer may partially reactivate the normal TA program. On the other hand, some genes (e.g., CDCA2 and TRIP13) that are barely expressed in normal tissues were newly coexpressed in cancer, indicating the ongoing reorganization of the transcriptional network associated with carcinogenesis. This suggests that while CD168-positive cells function as proliferation-specialized TA cells in normal tissues, they may also function as "cancer TA cells" in cancer, providing a platform for the acquisition and selective expansion of novel cell division regulatory mechanisms. Thus, CD168-positive cells constitute a representative subset of TA cells specialized in cell cycle control and mitosis in normal colonic epithelium, and are equipped with precise regulation of chromosome segregation in addition to mitotic activity. Furthermore, because a similar set of genes is reactivated in cancer cells, CD168 may also be an effective marker for identifying TA-like cell populations responsible for abnormal proliferation in cancer.In particular, while CD168-positive cells in normal tissues correspond to a restricted, proliferative intermediate stage in the differentiation lineage, in cancer, this program may be expanded and fixed. In other words, CD168 may also function as an axis for capturing the continuous transition from normal to cancer. These findings suggest that CD168 may be a useful indicator for visualizing and targeting the state of TA cells and abnormal cell division activity in cancer, and may provide fundamental information for future diagnostic and therapeutic applications.

[0140] [Example 11] Among the genes co-expressed with CD168, ASPM (Abnormal Spindle-like, Microcephaly-associated or Assembly Factor For Spindle Microtubules) in particular showed the highest Jaccard Index across all conditions (normal and cancer subtypes).

[0141] The Jaccard Index was calculated based on the proportion of cells in which CD168 and each gene were co-expressed, and the similarity of expression between normal colon and four colon cancer subtypes (MMRdDiff, MMRdPoor, MMRpDiff, MMRpPoor) was evaluated. The results are shown in Figure 14. Furthermore, the expression similarity between CD168 and the genes was visualized using PCA based on the Jaccard Index values ​​in normal colon and each cancer subtype. The results are shown in Figure 15.

[0142] Figure 14 shows a heat map of genes with expression patterns similar to CD168 extracted from normal colon and four cancer subtypes (MMRdDiff, MMRdPoor, MMRpDiff, and MMRpPoor). The Jaccard Index, based on the percentage of cells co-expressing CD168, was calculated. The genes analyzed were selected from those whose expression patterns overlapped with those of CD168-positive cells in normal colon. Specifically, the top 28 genes with the highest Jaccard Index were extracted, and their co-expression patterns were analyzed. This group of genes includes many cell cycle control and mitosis-related factors, such as ASPM, CCNA2, CCNB1, CDC20, CENPF, TOP2A, MKI67, BIRC5, PLK1, TPX2, GTSE1, and CENPA. These genes likely function as components of the proliferation program characteristic of CD168-positive cells. The analysis revealed that ASPM showed the highest Jaccard Index with CD168 under all conditions and co-expressed more strongly with CD168 than any other gene. Meanwhile, other cell cycle-related genes, such as TOP2A, CCNA2, CCNB1, CDC20, CENPF, BIRC5, and MKI67, also showed high Jaccard Indexes with CD168, but were found to represent a broader range of cell cycle activity in CD168-positive cells. Furthermore, some genes, such as NEK2, CEP55, and DEPDC1, showed no similarity with CD168 in normal tissues but exhibited elevated Jaccard Indexes in specific cancer subtypes, suggesting reorganization of cancer-specific transcriptional networks in CD168-positive cells. Conversely, genes such as UBE2C, AURKB, and SGO1 showed similarity with CD168 in normal tissues but lost co-expression in cancer, potentially reflecting a disruption or reorganization of cell cycle control.

[0143] Figure 15 shows the Jaccard Index profile obtained based on the similarity between CD168 and each gene, which was then subjected to dimensionality reduction using principal component analysis (PCA) to visualize the relationships between genes based on the similarity of their expression patterns. The Jaccard Index was calculated based on the overlapping expression rate between CD168 and each gene at the cellular level in normal colon tissue and each cancer subtype (MMRdDiff, MMRdPoor, MMRpDiff, MMRpPoor). As a result, ASPM was isolated in the upper right corner, clearly separated from all other gene groups (cluster 1). This indicates that ASPM shares extremely high expression similarity with CD168 and forms the core of a transcriptional network specific to CD168-positive cells. This cluster, consisting of CD168 and ASPM, is thought to be the core of a transcriptional program deeply involved in cell cycle progression. In addition, a second cluster (cluster 2), consisting of TOP2A, CCNA2, CCNB1, CENPF, MKI67, CDC20, and BIRC5, is also densely concentrated on the right side, suggesting that these genes are also strongly involved in cell cycle activity in CD168-positive cells. On the other hand, genes such as NEK2, CEP55, DEPDC1, PTTG1, and AURKB are located at distant positions in the PCA space, suggesting that they may play different roles in the cancer-specific CD168 co-expression network or may be transcriptionally regulated differently from clusters 1 and 2. In particular, genes such as UBE2S and SGO1, which are co-expressed with CD168 in normal tissues but lose this association in cancer, are depicted in spatially isolated positions, possibly reflecting the reorganization of the cell proliferation control network in cancer.

[0144] These results suggest that ASPM is the gene with the strongest and most consistent co-expression pattern in CD168-positive cells and has the highest overlap with CD168 under all conditions, both normal and cancerous. These results suggest that ASPM may play a central role in defining the molecular characteristics of CD168-positive cells. ASPM (Abnormal Spindle-like, Microcephaly-associated, or Assembly Factor For Spindle Microtubules) is known to be involved in the regulation of symmetric cell division and has been identified as one of the causative genes for autosomal recessive microcephaly (MCPH) in humans. Loss of ASPM function has been reported to cause increased asymmetric cell division in neural stem cells and an associated insufficient supply of proliferating lineage cells, resulting in impaired maintenance of the stem cell pool and cell number, leading to reduced brain size. These findings suggest that ASPM is not a factor essential for stem cell self-renewal itself, but rather for the stable formation and maintenance of the proliferating cell pool through symmetric cell division. Meanwhile, CD168 is also involved in the control of the division axis and spindle assembly, and may be involved in regulating the division pattern of developing stem cells. Given these functional commonalities, the robust coexpression of ASPM in CD168+ cells suggests that cancer cells may reconstitute part of the division control network seen during development, rather than simply activating cell cycle genes. Our results support the possibility that CD168+ cells retain elements of the division control machinery similar to normal TA cells and maintain their characteristics in the cancer environment. The coordinated expression of CD168 and ASPM may serve as a molecular marker for capturing the TA-like cellular state in cancer, and may be important for future functional analysis and the identification of therapeutic targets.

[0145] [Example 12] In normal human intestinal tissue, 83% (n=12) of CD168-positive dividing cells underwent symmetric division, indicating that CD168-positive cancer TA cells maintain a division pattern that promotes proliferation rather than differentiation.

[0146] Normal human intestinal tissue sections were used to analyze the orientation of the mitotic spindle in CD168-positive cells. Nuclei and CD168-positive structures were visualized by immunohistochemical staining. The orientation of cell division was quantified by measuring the angle of the two daughter cells relative to a plane parallel to the basal surface. Divisions whose axes were within ±20° of this plane were classified as parallel divisions. The results are shown in Figure 16.

[0147] Figure 16 shows the results of immunohistochemical staining of cells in normal human intestinal tissue. In Figure 16, arrows indicate the direction of division and their position relative to the basal surface. In Figure 16, nuclei are shown as dark ovals with intense staining, and CD168 expression is shown as columnar staining throughout the cytoplasm. The boxed area in the leftmost image in Figure 16 highlights a dividing cell. The rightmost image in Figure 16 shows a magnified view of the boxed area in the leftmost image. Scale bars are 20 μm (left image) and 5 μm (right image). In Figure 16, analysis of CD168-positive dividing cells in normal human intestinal tissue revealed that the majority (83%) divided parallel to the basal surface, i.e., exhibited symmetric division (Figure 16). Division parallel to the basal plane (transverse division) is interpreted as symmetric division, since both daughter cells remain in the same cell layer and are exposed to a similar niche environment, which tends to maintain similar cell types. In contrast, vertical division is known as asymmetric division, because one daughter cell may migrate upwards, resulting in a change in environment and induction of differentiation. This symmetric division results in both daughter cells remaining as CD168-positive cells with identical properties, reflecting specialized behavior for increasing cell numbers while maintaining an undifferentiated state. In this study, we confirmed that CD168-positive cells not only express high levels of proliferation-related genes (e.g., ASPM, CDC20, and CCNA2), but also structurally and functionally demonstrate symmetric division, continuously producing similar proliferative cells. In particular, ASPM is known to be involved in the regulation of symmetric division, and its strong coexpression with CD168 suggests that the two may function cooperatively in the selection of the division mode. These results suggest that CD168+ cells are a specialized cell population that maintains their identity as TA cells and expands their numbers, rather than differentiating into stem cells. In other words, they possess a program that prioritizes proliferation through division over differentiation, and are responsible for expanding the proliferating cell pool within the tissue.This division pattern may explain the high division maintenance capacity of cancerous TA cells, and cells that co-express CD168 and ASPM may be a marker for cell populations that support proliferation within cancer.

[0148] ·Proliferative transcriptional program and division strategy characteristic of CD168+ cells This study revealed that CD168+ cells consistently and strongly co-expressed several genes involved in cell cycle and mitosis, including ASPM, CCNA2, CDC20, TOP2A, and PLK1. Among these, ASPM, which is involved in symmetric division, showed the highest expression similarity with CD168 in normal colon and all cancer subtypes, suggesting that it is a central component of the transcriptional network of CD168+ cells. Furthermore, analysis of cell division axes in tissue sections revealed that CD168+ cells frequently underwent symmetric division, suggesting that these cells maintain division symmetry and employ a strategy to continuously generate proliferative cells with similar properties without differentiation. Thus, CD168 is a highly specific and potent marker for identifying cancerous TA cells, and its expression status is extremely useful for understanding the proliferative status within tumors. In particular, the strong co-expression relationship between CD168 and ASPM reflects the division pattern and control of the division program characteristic of cancerous TA cells. Focusing on the CD168-ASPM axis can be applied to distinguish cellular states that indicate cancer progression and therapeutic responsiveness, predict prognosis, and even identify new therapeutic targets based on the division mechanism and develop personalized medicine. Therefore, the present invention provides a useful tool that will contribute to innovation in cancer diagnosis, classification, and treatment strategies.

[0149] Although the present disclosure has been described above with reference to embodiments and examples, the present disclosure is not limited to the above embodiments and examples. Various modifications that can be understood by a person skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure.

[0150] <Additional Notes> Some or all of the above embodiments and examples can be described as follows in the following supplementary notes, but are not limited thereto. <Detection reagent for TA cells> (Supplementary Note 1) A detection reagent for TA cells, comprising a detection reagent for CD168 (Cluster of differentiation 168). (Supplementary Note 2) The detection reagent according to Supplementary Note 1, comprising a binding molecule for CD168. (Supplementary Note 3) The detection reagent according to Supplementary Note 1 or 2, wherein the binding molecule comprises an antibody or a nucleic acid molecule. (Supplementary Note 4) The detection reagent according to any one of Supplementary Notes 1 to 3, which is an intestinal TA cell. <Detection reagent for proliferative cancer TA cells> (Supplementary Note 5) A detection reagent for detecting proliferative cancer TA cells, comprising the detection reagent according to any one of Supplementary Notes 1 to 4. <Method for detecting TA cells> (Supplementary Note 6) A method for detecting TA cells, comprising the step of detecting CD168-positive TA cells by detecting CD168 in a sample containing intestinal cells. (Supplementary Note 7) For the sample, the steps of contacting with the detection reagent according to any one of Supplementary Notes 1 to 4 to form a complex of the CD168 and the detection reagent; The detection method according to Supplementary Note 6, further comprising the step of detecting the complex of CD168 and the reagent in the sample. <Method for detecting proliferative cancer TA cells> (Supplementary Note 8) A method for detecting the proliferative property in cancer TA cells, comprising the step of detecting cancer TA cells showing proliferative property by detecting CD168 in a cancer-derived sample. (Supplementary Note 9) For the sample, the steps of contacting with the detection reagent according to Supplementary Note 5 to form a complex; The detection method according to Supplementary Note 8, further comprising the step of detecting the complex of CD168 and the reagent in the sample. <Method for purifying TA cells> (Appendix 10) A method for purifying TA cells, comprising the step of separating CD168-positive TA cells from a sample containing intestinal cells. (Appendix 11) For the sample, reacting with the detection reagent described in any of Appendices 1 to 3 to form a complex of the CD168 and the detection reagent; The purification method according to Appendix 10, comprising the step of separating the CD168-positive TA cells by separating the complex of CD168 and the reagent in the sample. <Method for purifying proliferative cancer TA cells> (Appendix 12) A method for purifying proliferative cancer TA cells, comprising the step of separating CD168-positive proliferative cancer TA cells from a cancer-derived sample. (Appendix 13) For the sample, reacting with the reagent described in Appendix 5 to form a complex of the CD168 and the detection reagent; The purification method according to Appendix 12, comprising the step of separating the CD168-positive proliferative cancer TA cells by separating the complex of CD168 and the reagent in the sample. <Cell population containing TA cells> (Appendix 14) A cell population containing CD168-positive TA cells, where the proportion of CD168-positive TA cells in the cells of the cell population is 10% or more. <Cell population containing proliferative cancer TA cells> (Appendix 15) A cell population containing CD168-positive proliferative cancer TA cells, where the proportion of CD168-positive proliferative cancer TA cells in the cells of the cell population is 10% or more.

Industrial Applicability

[0151] As described above, according to the present disclosure, TA cells can be detected using a single marker, making the present disclosure extremely useful in the field of life science.

Claims

1. A reagent for detecting TA cells (Transient Amplifying cells), which comprises a reagent for detecting CD168 (Cluster of differentiation 168).

2. The detection reagent of claim 1 , comprising a binding molecule for CD168.

3. The detection reagent of claim 1 or 2, wherein the binding molecule comprises an antibody or a nucleic acid molecule.

4. The detection reagent according to claim 1 or 2, which is an intestinal TA cell.

5. A detection reagent for detecting proliferating cancer TA cells, comprising the detection reagent according to claim 1 or 2.

6. A method for detecting TA cells, comprising the step of detecting CD168-positive TA cells by detecting CD168 in a sample containing intestinal cells.

7. contacting the sample with the detection reagent of claim 1 or 2 to form a complex between the CD168 and the detection reagent; The detection method according to claim 6, further comprising the step of detecting a complex between CD168 and the reagent in the sample.

8. A method for detecting proliferation in cancer TA cells, comprising the step of detecting proliferative cancer TA cells by detecting CD168 in a cancer-derived sample.

9. contacting the sample with the detection reagent of claim 5 to form a complex; The detection method according to claim 8, further comprising the step of detecting a complex between CD168 and the reagent in the sample.

10. A method for purifying TA cells, comprising a step of separating CD168-positive TA cells from a sample containing intestinal cells.

11. A step of reacting the sample with the detection reagent according to claim 1 or 2 to form a complex between the CD168 and the detection reagent; The purification method according to claim 10, further comprising a step of separating the CD168-positive TA cells by separating a complex between CD168 and the reagent in the sample.

12. A method for purifying proliferative cancer TA cells, comprising a step of separating CD168-positive proliferative cancer TA cells from a cancer-derived sample.

13. Reacting the sample with the reagent of claim 5 to form a complex between the CD168 and the detection reagent; The purification method according to claim 12, further comprising a step of separating the CD168-positive proliferating cancer TA cells by separating the complex between CD168 and the reagent in the sample.

14. a cell population containing CD168-positive TA cells, The cell population has a ratio of CD168-positive TA cells to the cells in the cell population of 10% or more.

15. a cell population containing CD168-positive proliferative cancer TA cells, The cell population has a ratio of CD168-positive proliferating cancer TA cells to the cells in the cell population of 10% or more.

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