Method for determining the differentiation state of stem cells

Abstract

The present invention relates to a method for determining the differentiation state of stem cells based on cell signaling pathway activity. The method can be used to determine the pluripotency, multipotency, or unipotency of stem cells. The method further relates to a method for generating a reference library for use in the method for determining the differentiation state. The present invention further relates to a non-transitory storage medium for carrying out the method, a kit suitable for carrying out the method, and the use of the kit in carrying out the method of the present invention.

Description

Technical Field

[0001] The present invention relates to a method for determining the differentiation state of stem cells. The method further relates to a method for creating a reference library used in a method for characterizing stem cells. Furthermore, the present invention relates to a kit suitable for use in the methods described herein.

Background Art

[0002] Embryonic development is controlled by the cooperative activity of a relatively small number of signaling pathways, and thus the cell division, migration, and differentiation of stem cells with various differentiation potentials are controlled. Signaling pathways are well conserved evolutionarily and control these basic cellular mechanisms.

[0003] Signaling pathways can be broadly classified into nuclear receptor pathways by hormones (e.g., androgen and estrogen receptor pathways), developmental pathways (e.g., Wnt pathway, Hedgehog pathway, TGFβ pathway, Notch pathway), inflammatory NFκB pathway, and a very complex growth factor-regulated signaling pathway network (among the networks, the PI3K-AKT-mTOR pathway is probably the most important, followed by the MAPK pathway and the JAK-STAT pathway). In addition to embryonic development, important physiological processes such as hematopoiesis, generation of immune responses, tissue regeneration, hair growth, and regeneration of the intestinal mucosa are controlled. In both physiological cell processes and embryonic development, the activity of signaling pathways is tightly regulated.

[0004] Stem cell technology has matured over the past few decades, and a major revolutionary discovery and subsequent development has been the reliable generation of induced pluripotent stem cells (iPS). The development of iPS technology has led to robust protocols that enable the generation of pluripotent stem cell lines from any healthy or diseased individual [see Chacon‐Martinez, et al., Development, vol. 145, no. 15, p. dev165399, August 2018]. However, other types of stem cells are also known, such as human embryonic stem cells, and organ stem cells such as hematopoietic stem cells or intestinal crypt stem cells. iPS cells and HES cells are pluripotent, that is, in principle they can form all cell types of the human body, while most organ stem cells are multipotent and can form multiple cell types that make up the organ tissue, and progenitor stem cells within the organ generally can form only one mature cell type.

[0005] The use of iPS cell culture and differentiation into specific cell types is increasing in an attempt to create in vitro disease models to gain knowledge about the pathophysiology of diseases or for drug development purposes. iPS-based disease models are unique because the disease is generated within the genetic environment of the individual who is the donor. In addition to understanding the pathophysiology of diseases and drug development, iPS-based disease models may also be useful in personalized disease models of medical subjects with specific genetic diseases. This may be particularly relevant when it is difficult to obtain pathological materials, for example, in children with brain disorders such as epilepsy or cognitive impairment. In such cases, iPS-derived disease models may play a role in diagnosis by enabling the identification of the cause and in vitro investigation of the drug efficacy for that patient.

[0006] In the case of simple genetic diseases, it is possible to create control "companion" iPS cell lines with corrected mutations, which has been facilitated by the development of CRISP-CAS technology. In the case of complex genetic diseases, this is not possible. Therefore, the advantage of iPS technology is the potential to collect a large number of iPS lines derived from patients with the same disease and reproduce the disease in culture in a standardized manner. Subsequently, such patient-derived disease models can be used as surrogate patients "in a dish", for example, for the purpose of drug development. Therefore, it is necessary to confirm that the various stem cell batches used have the same characteristics, define the differentiation steps into the cell types required to mimic the disease, and develop assays to evaluate the effect of drug administration, for example, on cell culture disease models.

[0007] Stem cells enable the in vitro culture of differentiated cells or tissues to be returned to patients for organ or tissue repair. Although several applications to regenerative medicine have been explored using human embryonic stem cells (HES), generally, iPS cell lines have greater potential for use in regenerative medicine [Chacon-Martinez, et al., Development, vol. 145, no. 15, p. dev165399, August 2018]. To obtain specific differentiated organ cells, it is necessary to reproduce the differentiation steps that occur during normal embryonic development, either completely in vitro or partially in vivo after delivering progenitor cells to the patient.

[0008] Generating cell types for tissue repair using stem cells, particularly iPS cells, holds great clinical potential for treating and potentially curing various diseases. However, many challenges remain, partly due to the incomplete understanding of methods for generating appropriate cells with sufficient purity to achieve true regenerative medicine based on stem cell therapies [Badylak et al., npj Regenerative Medicine, vol. 2, no. 1, p. 2, January 2017]. Therefore, assays are needed to confirm that the various stem cell batches used have the same characteristics, define the differentiation stages into the types of cells required to mimic the disease, and quantify the purity and differentiation state of the cell batches that are returned to the patient after in vitro culture and manipulation.

[0009] The problem with stem cell lines, including iPS cell lines, is that they do not always have the same pluripotency characteristics. This depends in part on the method by which the stem cell line was generated [Strano et al., https: / / doi.org / 10.1016 / j.celrep.2020.107732]. It is difficult to establish and maintain the pluripotent state of human stem cell lines during culture [International Stem Cell Initiative, Nat Commun, vol.9, no.1, p.1925, 15 2018]. Multiple signaling pathways, such as the PI3K pathway, Wnt pathway, Hedgehog pathway, TGFβ pathway, STAT3 pathway, etc., orchestrate the state of stem cell pluripotency [Ying et al., Stem Cell Reports, vol. 8, no. 6, pp.1457‐1464, July 2017; Sokol, Development, vol.138, no.20, pp.4341‐4350, October 2011; Huang et al., Cell Res., vol.19, no.10, pp.1127‐1138, October 2009; Massague, Nat.Rev.Mol.Cell Biol., vol.13, no.10, pp.616‐630, October 2012; Yu et al., Development, vol.143, no.17, pp.3050‐3060, September 2016]. Therefore, there is a high need for an assay that quantifies the degree of pluripotency and the ability to differentiate into various differentiation lineages, and that enables quantitative comparison of the various stem cell batches (e.g., before and after freezing, after passage of stem cell culture) used to avoid selection of stem cell clones with different characteristics.

[0010] The generation of iPS-derived disease models is challenging, and among these, the most important is the reproducibility in generating disease models [van de Stolpe et al., Lab Chip, vol.13, no.18, pp.3449-3470, September 2013]. This requires standardized differentiation steps to reliably obtain the necessary cell or tissue types. Therefore, there is a high need for assays that can quantify the degree of pluripotency and the differentiation capacity into various differentiation lineages, and that enable quantitative comparison of the various (differentiated) stem cell batches used.

[0011] Specific challenges in the use of stem cells for clinical regenerative medicine To obtain regulatory approval for clinical use, cell culture and differentiation need to be highly controlled and reproducible, and strict quality control protocols and standardization are required. The clinical use of stem cell-derived products for regenerative medicine involves numerous quality control requirements. In addition to detailed characterization of the final product, it is expected that a series of differentiation steps, such as obtaining insulin-producing pancreatic cells via the definitive endoderm stage, etc., need to be documented. Analysis of the activity of signaling pathways can enable thorough and quantitative biological evaluation of stem cell-derived products and comparison between different cell batches presumed to have the same differentiation characteristics [see Dimmeler et al., Nat. Med., vol.20, no.8, pp.814-821, August 2014]. Therefore, there is a high need for assays that enable quantitative comparison of the various stem cell batches used and that can quantify the purity of the specific cell type of interest in cell culture.

[0012] Stem cell lines, particularly iPS cell lines, are important for generating disease models and form the backbone of regenerative medicine in both the development of therapeutic methods and clinical use. However, stem cell lines differ with respect to phenotype (RNA and / or protein expression), and importantly, with respect to differentiation capacity. These are the result of underlying different genetic characteristics even when the generation and culture protocols of iPS cell lines are standardized.

[0013] In Sun et al., 2007 (PLoS ONE 3(10): e3406), the role of transcriptional co-expression leading to self-renewal of ESCs and differentiation from pathways to global networks has been investigated under the framework of inter-species comparison. This publication emphasizes the relevance of cell signaling pathways in maintaining pluripotency and differentiation of stem cells, but does not suggest methods for quantifying pluripotency or differentiation of stem cells, nor does it address the standardization of stem cells. This poses a major problem regarding experimental reproducibility in using these cell lines or their differentiated derivatives for any purpose, particularly for the development of therapeutic methods in regenerative medicine or the prescription of cell-based therapies to patients. Therefore, there is a high need for standardized quantitative quality control assays to quantify totipotency, pluripotency, or progenitor cell state, and differentiation potential, as well as the differentiated states obtained during cell batch preparation for research or cell therapy.

[0014] The methods and products described in the appended claims meet the above needs and overcome the above problems. SUMMARY OF THE INVENTION

[0015] To further develop the field of stem cell technology, a method for quantitatively identifying the pluripotency and differentiation state of stem cells is required. Thus, in a first aspect of the present invention, there is provided an in vitro or ex vivo method for determining the differentiation state of stem cells by determining the activity of at least three cell signaling pathways selected from the group consisting of TGFβ, Notch, JAK-STAT3, Hedgehog, and Wnt, or based on the result of the determination. The method includes calculating numerical values of the activity of at least three cell signaling pathways, comparing the numerical values calculated for the activity of at least three cell signaling pathways in the stem cells with the numerical values calculated for the activity of at least three reference cell signaling pathways, and determining the differentiation state of the stem cells based on the compared cell signaling pathway activities, wherein the differentiation state of the stem cells is determined to be totipotency, pluripotency, unipotency, or at least partially differentiated, and the determining step, The comparing step is performed by comparing the activity of at least three cell signaling pathways in the stem cells with the activity of the same three pathways in a reference library, which includes the activity of at least three cell signaling pathways determined in at least two reference samples. The numerical values of the activity of at least three cell signaling pathways are calculated based on the expression levels of three or more target genes of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathways measured in the stem cells, and the calculation is Determining the level of a TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt transcription factor (TF) element in a stem cell, wherein the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt TF element controls the transcription of three or more target genes of a TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway, and the determining is at least partially based on evaluating a mathematical model that correlates the expression levels of three or more target genes of a TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway to the level of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt TF element, and inferring the activity of a TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway in the stem cell based on the determined level of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt TF element in the stem cell, Three or more TGFβ target genes are selected from the group consisting of ANGPTL4, CDC42EP3, CDKNIA, CDKN2B, CTGF, GADD45A, GADD45B, HMGA2, ID1, IL11, SERPINE1, INPP5D, JUNB, MMP2, MMP9, NKX2-5, OVOL1, PDGFB, PTHLH, SGK1, SKIL, SMAD4, SMAD5, SMAD6, SMAD7, SNAI1, SNAI2, TIMP1, and VEGFA; three or more Notch target genes are selected from the group consisting of CD28, CD44, DLGAP5, DTX1, EPHB3, FABP7, GFAP, GIMAP5, HES1, HES4, HES5, HES7, HEY1, HEY2, HEYL, KLF5, MYC, NFKB2, NOX1, NRARP, PBX1, PIN1, PLXND1, PTCRA, SOX9, and TNC; three or more JAK-STAT3 target genes are selected from the group consisting of AKT1, BCL2, BCL2L1, BIRC5, CCND1, CD274, CDKN1A, CRP, FGF2, FOS, FSCN1, FSCN2, FSCN3, HIF1A, HSP90AA1, HSP90AB1, HSP90B1, HSPA1A, HSPA1B, ICAM1, IFNG, IL10, JunB, MCL1, MMP1, MMP3, MMP9, MUC1, MYC, NOS2, POU2F1, PTGS2, SAA1, STAT1, TIMP1, TNFRSF1B, TWIST1, VIM, and ZEB1; three or more Hedgehog target genes are selected from the group consisting of GLI1, PTCH1, PTCH2, IGFBP6, SPP1, CCND2, FST, FOXL1, CFLAR, TSC22D1, RAB34, S100A9, S100A7, MYCN, FOXM1, GLI3, TCEA2, FYN, and CTSL1; and three or more Wnt target genes are selected from the group consisting of KIAA1199, AXIN2, RNF43, TBX3, TDGF1, SOX9, ASCL2, IL8, SP5, ZNRF3, KLF6, CCND1, DEFA6, and FZD7.

[0016] Furthermore, provided are in vitro or ex vivo methods for determining the differentiation state of stem cells by determining the activity of at least three cell signaling pathways selected from the group consisting of TGFβ, Notch, JAK-STAT3, Hedgehog, and Wnt, or based on the results of such determination, the method comprising: comparing the activity of at least three cell signaling pathways in the stem cells with the activity of at least one reference cell signaling pathway; determining the differentiation state of the stem cells based on the compared cell signaling pathway activities, wherein the differentiation state of the stem cells is determined to be totipotency, pluripotency, unipotency, or at least partially differentiated.

[0017] Regarding the activity of signaling pathways, it is important to quantitatively characterize stem cell lines and different batches or passages of the same cell line to accurately define the functional state of totipotency of each cell line or passage of the cell line. Assays are needed that can simultaneously measure the activity of these pathways in cells or tissue samples at various stages of the differentiation process [Yu et al., Development, vol. 143, no. 17, pp. 3050-3060, September 2016]. The same problem also applies to the characterization of multipotent and progenitor stem cells.

[0018] The methods disclosed herein provide such quantitative characterization of stem cells by determining the activity of multiple cell signaling pathways. As shown in the examples provided below, doing so can determine the totipotency of the analyzed stem cells or whether these stem cells are (partially) differentiated. A single assay that can quantitatively determine the totipotency or differentiation state of a stem cell sample has not been described in the art and is a useful tool for advancing the fields of stem cell research and stem cell medicine.

[0019] The expression levels of certain genes, such as OCT4, SOX2, SSEA4, and TRA-1-60, are used to determine the pluripotency of stem cells. When stem cells are totipotent, the qualitative expression levels of these genes provide good information, but the analysis of expression levels does not provide a quantitative answer and does not provide information about the activity of the pluripotency signaling pathway. The latter is necessary, for example, to change the pluripotent state by adding more ligands to induce a more active pluripotency pathway, and to appropriately adjust the culture medium. This is necessary for the standardization of stem cell experiments and for accurately defining the level of pluripotency. However, more importantly, it does not provide further information about stem cell differentiation, such as germ layer or tissue type.

[0020] In Sun et al., 2007 (supra), the role of transcriptional co-expression leading to self-renewal of ESCs and differentiation from pathways to global networks has been investigated under the framework of interspecies comparison. This publication does not disclose or suggest a method for quantitatively determining pluripotency, nor does it disclose or suggest performing such an analysis based on the activity of the signaling pathway.

[0021] By using a calibrated mathematical method to determine the activity of a cell signaling pathway (e.g., based on the expression level of a target gene), comparison between different samples becomes possible. The mathematical model provides a numerical value for each determined pathway activity, and the numerical value can be compared with the values obtained in one or more other samples. This enables the use of the method for various purposes, such as quality control of stem cell samples by comparing the cell signaling pathway activity with a desired value (e.g., the value obtained in a validated reference sample). The method can also be used to determine the differentiation state by comparing the pathway activity, for example, with the pathway activity obtained from pluripotent stem cells or with the pathway activity obtained from different differentiation stages of the same or similar stem cells.

[0022] By analyzing the required pathway activities, it is possible to determine whether these activities match the expected pathway activities for the type of stem cells being analyzed. For example, the signal transduction pathway activities of iPS cell lines are clearly defined and are also shown in the results described below, enabling comparison of the signal transduction pathway activities determined in iPS samples with predicted or reference values. For example, as further shown in the examples described below, hES cells can be cultured under different conditions, for example, with or without using a feeder layer, and a human or mouse cell feeder layer may also be used, or when a feeder layer-conditioned medium is not used for human or mouse cells, or can be cultured in a defined medium containing known components that can be changed as needed. It is known in the art that only hES cells grown on a feeder layer of human cells exhibit true pluripotency characteristics, i.e., these stem cells can form each of the three germ layers. Other culture conditions that are easier to use have been investigated and defined in an attempt to copy this pluripotent state. The examples showed that cells grown under these different conditions can be clearly distinguished. For example, true pluripotent hES cells grown on a T3HDF (human cell) feeder layer exhibit low FOXO and Wnt signal transduction activities, moderate TGFβ signal transduction activity, and high hedgehog, Notch, and STAT3 signal transduction activities. hES cells grown in T3HDF medium exhibit similar characteristics but differ in that they show intermediate FOXO signal transduction activity and appear to have slightly reduced STAT3 signal transduction activity. When hES is grown on a mouse feeder layer or medium, TGFβ signal transduction is reduced and Notch and STAT3 signal transduction activities are moderate.

[0023] These differences in signaling pathway activity may explain the reasons for the decline in the ability to differentiate into each germ layer and cells derived from each germ layer. However, it also shows the ability to characterize stem cells using signaling pathway activity or use pathway activity as a quality control tool. In other words, by analyzing the pathway activity of a stem cell sample, for example, an hES or iPS sample, it is possible to predict the ability (pluripotency) of the stem cell to differentiate into each of the three germ layers, and thus predict the quality of the stem cell sample.

[0024] The methods disclosed herein are preferably performed using cultured stem cells, but may also be performed using stem cells extracted from or present in a sample obtained from a subject such as a human or non-human animal. Thus, in one embodiment, the stem cells used in the methods described herein are human stem cells or non-human animal stem cells. The methods described herein may further include the step of obtaining or providing stem cells. The stem cells obtained or provided may be derived from cultured cells or a subject (e.g., a human or non-human animal). The methods described herein may further include the step of isolating a polynucleotide from the stem cells, preferably the polynucleotide is RNA, more preferably mRNA.

[0025] As used herein, the differentiation state refers to the ability of a stem cell to differentiate into various lineages or cell types into which the stem cell can differentiate in vivo. This may vary depending on the type of stem cell. For example, hES or iPS (both pluripotent stem cells) can, in principle, differentiate into each of the three germ layers and can then generate any cell type. Therefore, the differentiation state of these stem cells is determined as the ability to form each of the three germ layers and is reflected in the pluripotency of these stem cells. On the other hand, organ stem cells can self-renew or differentiate into specific subtypes of specialized cells. Therefore, their differentiation state is reflected by the ability to self-renew and multipotency, i.e., the ability to form specialized cells present within the organ from which the stem cell is derived. Therefore, when a stem cell differentiates from a more pluripotent one, the stem cell gradually loses the ability to differentiate into different lineages or cell types, and thus the differentiation state reflects the differentiation of the stem cell.

[0026] Therefore, the differentiation state of a stem cell can be determined by comparing the required signal transduction pathway activity of the stem cell with the signal transduction pathway activity expected for that particular stem cell, e.g., a value obtained from a reference sample or derived from general knowledge in the art.

[0027] As used herein, determining the activity of a cell signal transduction pathway refers to any method by which the activity level of the signal transduction pathway can be determined and quantified. For example, by determining the expression levels of at least three target genes of each cell signal transduction pathway and correlating the expression levels of these target genes with the activity of the cell signal transduction pathway, the methods described later in this specification can be used. However, other methods that can be used to determine pathway activity are known to those skilled in the art, and such methods are not limited to immunohistochemistry, Western blotting, Northern blotting, localization assays, and phosphorylation-specific antibodies, etc.

[0028] Preferably, the method comprises determining, or being based on the result of determining, the activity of three or more cell signaling pathways, such as, for example, 3, 4, 5, 6, 7, 8, 9, or 10 or more cell signaling pathways. It is recognized that determining as many cell signaling pathway activities as possible provides the most information, but it has been found that at least three cell signaling pathways selected from TGFβ, Notch, JAK-STAT3, Hedgehog, and Wnt are sufficient to distinguish between the pluripotent (or multipotent) state and the partially differentiated state for all analyzed stem cell types. Thus, in a more preferred embodiment, the method comprises determining, or being based on the result of determining, the activity of three or more cell signaling pathways, such as 3, 4, or 5 or more cell signaling pathways selected from the group consisting of TGFβ, Notch, JAK-STAT3, Hedgehog, and Wnt, among 3, 4, 5, 6, 7, 8, 9, or 10 or more cell signaling pathways.

[0029] As used herein, the step of comparing the activity of at least three cell signaling pathways in a stem cell to the activity of at least one reference cell signaling pathway refers to the step of comparing the determined pathway activity to an internal or external reference that includes the activity of at least one pathway. The at least one reference cell signaling pathway may be determined, for example, using the stem cell sample itself, simultaneously with the three or more cell signaling pathways. In such a case, the reference cell signaling pathway may function as an internal control for normalizing the determined three or more pathway activities. In such a case, preferably, the step further comprises evaluating the determined pathway activity based on the expected pathway activity, and evaluating comprises determining, for each pathway activity, whether it is as expected, lower than expected, or higher than expected.

[0030] For example, in hES, Wnt signaling is very low and relatively constant. Therefore, Wnt cell signaling activity can be used as an internal control to normalize active pathways such as Hedgehog, Notch, STAT3, etc. This can be done, for example, by calculating the relative activity or ratio of the HH, Notch, and STAT3 pathways to the Wnt pathway. Alternatively, the activity of three or more cells can be compared to the pathway activity in a reference sample, such as the activity of the same three or more cell signaling pathways.

[0031] Alternatively, more preferably, the reference cell signaling pathway can be determined in a reference sample, preferably a reference sample of a similar or identical stem cell type. In such cases, the reference cell signaling pathway activity can be used to be directly compared to the determined activity of three or more pathways. It will be understood that the two options can also be combined. That is, an internal control can be used to normalize the determined activity of three or more pathways, and then the normalized activity of three or more pathways can be compared to the reference pathway determined in a control sample or stem cell.

[0032] Therefore, in one preferred embodiment, the method - includes comparing the activity of three or more cell signaling pathways in a stem cell to the activity of three or more reference cell signaling pathways.

[0033] Therefore, in a more preferred embodiment, the method - includes comparing the activity of at least three cell signaling pathways in a stem cell to the activity of at least three or more reference cell signaling pathways, wherein the three or more cell signaling pathways and the three or more reference cell signaling pathways are the same pathways.

[0034] For example, by determining HH, Notch, and STAT3 signaling pathway activities in validated reference cultured hES, a reference pathway activity or a range of pathway activities can be obtained. In the stem cell sample to be determined, Notch and STAT3 signaling pathway activities can be determined and directly compared with the determined reference pathway activity.

[0035] It will be appreciated that multiple references can be used in the comparison step. In such cases, the average numerical value of each cell signaling pathway can be determined among multiple reference samples, and the comparison step can be performed using the determined average value. By doing so, there is a further advantage that a standard deviation can be obtained that can be used as a threshold for determining whether the pathway activity is high or low as described herein. Alternatively, different values of each pathway activity determined with multiple references can be used to specify a range of expected values for a particular condition of the reference sample.

[0036] By associating gene expression levels with cell signaling pathway activities using a calibrated mathematical model, a numerical value can be assigned to the pathway activity. Depending on the model, this value can be normalized to a value, for example, from 0 to 100, where 0 indicates no pathway activity and 100 is the theoretical maximum pathway activity. Alternatively, the value can be normalized so that the average value is 0, and thus a decrease in pathway activity is represented by a negative value and an increase in pathway activity is represented by a positive value. It should be understood that the values obtained using such a model depend on the model used and do not represent absolute values. Therefore, in order to enable comparison of the numerical values obtained for pathway activity, the same model needs to be used when calibrating, determining reference values, and using the method of the present invention.

[0037] Thus, the numerical values obtained for the pathway activity in the sample can be compared to the numerical values obtained for that pathway activity in a reference sample. By performing such a comparison, it is possible to describe the pathway activity in the sample (e.g., a stem cell sample) relative to the pathway activity determined in the reference sample (e.g., a stem cell sample). Based on the numerical values, it is possible to describe the pathway activity in the sample relative to the pathway activity in the reference sample, for example, to state whether the pathway activity in the sample is high or low corresponding to the numerical value obtained for the pathway activity. For example, the Wnt cell signaling pathway activity can be determined in a reference stem cell sample, such as a reference hES sample. Since it has been identified by the inventors that the Wnt cell signaling pathway activity in hES is very low, this can be set as a baseline numerical value representing an inactive pathway, i.e., a reference value. By determining the numerical value of the Wnt cell signaling pathway activity in the hES sample being analyzed, the numerical value representing that pathway activity is compared to the reference value, and based on the numerical value, it can be determined whether the pathway activity is above (or below) the reference. To enable more accurate results and statistics, the comparison may be made using multiple reference samples. Alternatively, the baseline pathway activity may be set using a reference sample, which enables further comparison of pathway activities. For example, the mean and standard deviation can be calculated and used to calculate values for totipotent, pluripotent, or unipotent stem cells and to define thresholds for abnormal pathway activity.

[0038] Thus, in a preferred embodiment, if the numerical value obtained for pathway activity differs by at least one standard deviation from the numerical value obtained for pathway activity in the reference sample, the pathway activity is determined to be higher or lower. If the value is within one standard deviation range, the value is said to be equal to or equivalent to the pathway activity of the reference sample, and thus, if it is higher by more than one standard deviation, the activity is said to be "high" or "higher". The threshold may be set higher, for example, twice the standard deviation, or in some cases, three times the standard deviation. Also, different methods, such as statistical methods, may be used to determine the threshold for determining a significant deviation from the reference value. Alternatively, a preset value may be used as a cutoff for considering the activity of the pathway to be abnormal (with reference to the pathway activity of the reference sample). Thus, the relative terms "high" or "higher" and "low" or "lower" as used herein in the context of cell signaling pathway activity preferably refer to a predefined and validated pathway activity in a defined reference sample (or the average of the pathway activities determined in a plurality of defined reference samples).

[0039] It should be understood that, in principle, the reference value for a particular pathway activity in a sample only needs to be determined once. Thus, since a predefined reference pathway activity can be used, the step of determining the reference pathway activity is not part of the method of the present invention.

[0040] When referring to Figure 1A and the examples shown below, for different stem cell samples, the activities of the FOXO, Hedgehog, TGFβ, Wnt, Notch, and STAT3 cell signaling pathways were measured. Cultured human embryonic stem cells can be truly pluripotent when cultured under appropriate conditions. It is known that cells can be grown regardless of the presence or absence of a feeder layer to provide the necessary growth factors to the cells. When growing without using a feeder layer, it is necessary to culture the cells in the medium obtained from feeder layer cells. The feeder layer can be human cells or mouse cells. It is known in the art that using a human cell feeder layer results in truly pluripotent cells, and that cells grown under different conditions still have the ability to differentiate but exhibit different characteristics from cells grown in this way. The data shown in Figure 1A indicates that these differences in culture conditions are manifested at the signaling pathway level. Although some of these signaling pathways are known to be important in maintaining stem cell pluripotency or differentiation, this is the first time that the activities of multiple signaling pathways can be analyzed in a quantitative and calibrated manner suitable for comparing different samples with each other.

[0041] These data provide a reference for a set of signaling pathway activities, and by comparing the pathway activities of a test stem cell sample with these activities, it is possible to determine whether the test sample has the desired signaling pathway activity (e.g., as shown by ES cells grown on a human feeder layer), which is useful for several reasons.

[0042] For example, FIG. 1B shows the signal transduction pathway activities of several iPS samples and hES samples. From this figure, it can be concluded that although equivalent, when comparing iPS samples with ES samples, there are differences in pathway activities with respect to, for example, Notch signal transduction and TGFβ signal transduction. These differences may be due to different cell characteristics (e.g., pluripotency or differentiation) or culture conditions. Furthermore, these results can be compared with the results of FIG. 1A, indicating that the H7 ES sample shows the pathway activity that most closely matches that of hES grown on a human feeder layer, and thus is highly likely to be a pluripotent stem cell sample.

[0043] FIG. 1C shows the pathway activities of mesenchymal stem cells. These stem cells are multipotent and are of mesodermal origin. Since mesenchymal stem cells show higher TGFβ activity and lower Notch activity, the pathway activities can be clearly distinguished from those of pluripotent stem cells.

[0044] For the purposes of the present invention, determining the expression level of a target gene can be obtained based on the extracted RNA. The step of determining the expression level and / or the step of extracting RNA from the sample may be part of the method, i.e., the method may include the step of determining the expression level of the target gene on RNA extracted from a stem cell sample using a method known to those skilled in the art or a method described herein. Alternatively, the expression level may be determined separately, and the step of determining (the expression level of the target gene) is not an active step in the method of the present invention. In such a case, the expression level is provided as an input value, for example, as a relative expression level with respect to the expression levels of one or more control genes.

[0045] As used herein, the "expression level" refers to quantifying the number of mRNA copies transcribed from a gene. Generally, since this number is a relative value rather than an absolute value, it is preferably normalized against the expression of one or more housekeeping genes, for example. Housekeeping genes are genes that are considered to have a constant expression level regardless of cell type and / or the functional state of the cell (i.e., from a diseased or healthy subject), and thus can be used to normalize experimentally determined relative expression levels. Housekeeping genes are generally known to those skilled in the art, and non-limiting examples of housekeeping genes that can be used for normalization include β-actin, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and transcription factor IID TATA-binding protein (TBP).

[0046] Accordingly, the expression "expression level of a target gene" refers to a value representing the amount, for example, the concentration, of the target gene present in a sample. This value can be based on the amount of the transcription product (e.g., mRNA) or the translation product (e.g., protein) of the target gene. Preferably, the expression level is based on the amount of mRNA formed from the target gene. To determine the expression level, techniques such as qPCR, multiple qPCR, multiplexed qPCR, ddPCR, RNAseq, RNA expression arrays, or mass spectrometry may be used. For example, gene expression microarrays such as Affymetrix microarrays, or RNA sequencing such as Illumina sequencers can be used.

[0047] A set of cell signaling pathway target genes whose expression levels are preferably analyzed has been identified, or methods for identifying appropriate target genes are described herein. For example, when used to determine pathway activity by a mathematical model, pathway activity may be determined by analyzing three or more, for example, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 or more target genes from each cell signaling being evaluated.

[0048] In one embodiment, the measurement of the signal transduction pathway is performed using qPCR, multiple qPCR, multiplexed qPCR, ddPCR, RNAseq, RNA expression array, or mass spectrometry. For example, gene expression microarray data such as Affymetrix microarray, or RNA sequencing such as Illumina sequencer can be used.

[0049] As used herein, the term "subject" refers to any organism. In some embodiments, the subject is an animal, preferably a mammal. In certain embodiments, the subject is a human such as a patient. Although the present invention is not necessarily limited to a specific group of subjects, it will be understood that subjects suffering from an infectious disease, subjects suspected of having an infection, or subjects at risk of developing an infectious disease will most benefit from the invention described herein. This method is particularly useful for subjects infected with a virus.

[0050] The terms "pathway", "signal transduction pathway / signaling pathway", and "cellular signal transduction pathway" are used synonymously herein.

[0051] "Activity of the signal transduction pathway" may refer to the activity of a signal transduction pathway-related transcription factor (TF) element (a TF element that controls the transcription of the target gene) in a sample when expressing the target gene, that is, the rate at which the target gene is transcribed. For example, it can be expressed in units such as high activity (i.e., high speed) or low activity (i.e., low speed), or other dimensions such as levels or values related to such activity (e.g., rate) as units. Therefore, for the purposes of the present invention, the term "activity" as used herein is also intended to refer to the activity level obtained as an intermediate result in the "pathway analysis" described herein.

[0052] As used herein, the term "transcription factor element" (TF element) preferably refers to an intermediate or precursor protein or protein complex of an active transcription factor, or an active transcription factor protein or protein complex that controls the expression of a specific target gene. For example, the protein complex may include an intracellular domain of one of a plurality of signal transduction pathway proteins and at least one or more cofactors, thereby controlling the transcription of the target gene. Preferably, this term refers to either a protein or a protein complex transcription factor triggered by cleavage of one of a plurality of signal transduction pathway proteins that gives rise to an intracellular domain.

[0053] As used herein, the term "target gene" means a gene whose transcription is directly or indirectly controlled by each transcription factor element. A "target gene" may be a "direct target gene" and / or (as described herein) an "indirect target gene".

[0054] Pathway analysis enables quantitative measurement of signal transduction pathway activity in blood cells based on inferring the activity of a signal transduction pathway from measurement of the mRNA levels of well-validated direct target genes of transcription factors associated with each signal transduction pathway (see, for example, W Verhaegh, A van de Stolpe, Oncotarget, 2014, 5(14):5196).

[0055] Preferably, determining the activity of one or more of the signal transduction pathways, determining combinations of multiple pathway activities, and their applications are carried out, for example, as described in the following documents, each of which is incorporated herein by reference in its entirety for the purpose of determining the activity of the respective signal transduction pathway. The published international patent applications are WO2013011479 (title "ASSESSMENT OF CELLULAR SIGNALING PATHWAY ACTIVITY USING PROBABILISTIC MODELING OF TARGET GENE EXPRESSION"), WO2014102668 (title "ASSESSMENT OF CELLULAR SIGNALING PATHWAY ACTIVITY USING LINEAR COMBINATION(S) OF TARGET GENE EXPRESSIONS"), WO2015101635 (title "ASSESSMENT OF THE PI3K CELLULAR SIGNALING PATHWAY ACTIVITY USING MATHEMATICAL MODELLING OF TARGET GENE EXPRESSION"), WO2016062891 (title "ASSESSMENT OF TGF‐β CELLULAR SIGNALING PATHWAY ACTIVITY USING MATHEMATICAL MODELLING OF TARGET GENE EXPRESSION"), WO2017029215 (title "ASSESSMENT OF NFKB CELLULAR SIGNALING PATHWAY ACTIVITY USING MATHEMATICAL MODELLING OF TARGET GENE EXPRESSION"), WO2014174003 (title "MEDICAL PROGNOSIS AND PREDICTION OF TREATMENT RESPONSE USING MULTIPLE CELLULAR SIGNALLING PATHWAY ACTIVITIES"), WO2016062892 (title "MEDICAL PROGNOSIS AND PREDICTION OF TREATMENT RESPONSE USINGMULTIPLE CELLULAR SIGNALING PATHWAY ACTIVITIES”), WO2016062893 (title “MEDICAL PROGNOSIS AND PREDICTION OF TREATMENT RESPONSE USING MULTIPLE CELLULAR SIGNALING PATHWAY ACTIVITIES”), WO2018096076 (title “Method to distinguish tumor suppressive FOXO activity from oxidative stress”), as well as patent application WO2018096076 (title “Method to distinguish tumor suppressive FOXO activity from oxidative stress”), WO2019068585 (title “Assessment of Notch cellular signaling pathway activity using mathematical modelling of target gene expression”), WO2019120658 (title “Assessment of MAPK-MAPK-AP1 cellular signaling pathway activity using mathematical modelling of target gene expression”), WO2019068543 (title “Assessment of JAK-JAK-STAT3 cellular signaling pathway activity using mathematical modelling of target gene expression”), WO2019068562 (title “Assessment of JAK-STAT1 / 2 cellular signaling pathway activity using mathematical modelling of target gene expression”), and WO2019068623 (title “Determining functional status of immune cells types andis an “immune response”).

[0056] The model has been biologically validated using several cell types for the ER, AR, PI3K-FOXO, HH, Notch, TGF-β, Wnt, NFkB, JAK-STAT1 / 2, JAK-JAK-STAT3, and MAPK-MAPK-AP1 pathways.

[0057] A plurality of unique sets of cell signaling pathway target genes whose expression levels are preferably analyzed have been identified. When used in a mathematical model, pathway activity may be determined by analyzing three or more, for example, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 or more target genes from each cell signaling being evaluated.

[0058] The concepts common to the pathway analysis methods for determining the activities of the various signaling pathways disclosed herein are preferably applied herein for the purposes of the present invention. The activity of a signaling pathway in a cell, such as a cell present in a blood sample, is determined by receiving the expression levels of one or more, preferably three or more, target genes of the signaling pathway and determining the activity level of a signaling pathway-related transcription factor (TF) element in the sample, wherein the TF element controls the transcription of three or more target genes, and the determining is based on evaluating a calibrated mathematical pathway model that correlates the expression levels of the one or more, preferably three or more, target genes with the activity level of the signaling pathway, and optionally, based on the determined activity level of the signaling pathway-related TF element, inferring the activity of the signaling pathway in the cells present in the blood sample, and can be determined by. As described herein, the activity level may be directly used as an input for examining the immune response of a subject and / or determining whether an infection is viral and / or determining the severity of a viral infection and / or examining the cellular immunity conferred by a vaccine, and the present invention contemplates this as well.

[0059] As used herein, the term "activity level" of a TF element refers to the activity level of the TF element with respect to the transcription of a target gene.

[0060] The calibrated mathematical pathway model may be a probability model, preferably a Bayesian network model, based on conditional probabilities that relate the activity levels of signal transduction pathway-related TF elements and the expression levels of three or more target genes, or the calibrated mathematical pathway model may be obtained based on one or more linear combinations of the expression levels of three or more target genes. For the purposes of the present invention, the calibrated mathematical pathway model is preferably a centroid or linear model, or a Bayesian network model based on conditional probabilities.

[0061] In particular, determining the above expression levels and, optionally, inferring the activity of a signal transduction pathway in a subject can be performed, for example, among other things, by: (i) evaluating, for a set of inputs including the expression levels of three or more target genes of a cellular signal transduction pathway measured in a sample of the subject, a calibrated probabilistic pathway model representing the cellular signal transduction pathway, preferably a part of a Bayesian network; (ii) estimating the activity level in the subject of a signal transduction pathway-related transcription factor (TF) element, wherein the signal transduction pathway-related TF element controls the transcription of three or more target genes of the cellular signal transduction pathway, and the estimating is based on conditional probabilities that relate the activity level of the signal transduction pathway-related TF element and the expression levels of three or more target genes of the cellular signal transduction pathway measured in a sample of the subject; and (iii) inferring the activity of the cellular signal transduction pathway based on the estimated activity level of the signal transduction pathway-related TF element in a sample of the subject. This is described in detail in the published international patent application WO2013 / 011479A2 ("Assessment of cellular signaling pathway activity using probabilistic modeling of target gene expression"), the entire content of which is incorporated herein by reference.

[0062] In an exemplary alternative, determining the expression level and, optionally, inferring the activity of a cell signaling pathway in a subject comprises, inter alia, (i) determining the activity level of a signal transduction pathway-related transcription factor (TF) element in a sample of the subject, wherein the signal transduction pathway-related TF element controls the transcription of three or more target genes of the cell signaling pathway, and the determining is based on evaluating a calibrated mathematical pathway model that correlates the expression levels of three or more target genes of the cell signaling pathway to the expression level of the signal transduction pathway-related TF element, the mathematical pathway model being based on one or more linear combinations of the expression levels of three or more target genes, and, optionally, (ii) inferring the activity of the cell signaling pathway in the subject based on the determined activity level of the signal transduction pathway-related TF element in the sample of the subject. This is described in detail in the published international patent application WO2014 / 102668A2 (“Assessment of cellular signaling pathway activity using linear combination(s) of target gene expressions”), the entirety of which is incorporated herein by reference.

[0063] Further details regarding the estimation of cell signaling pathway activity using mathematical modeling of target gene expression are described in W Verhaegh et al., “Selection of personalized patient therapy through the use of knowledge-based computational models that identify tumor-driving signal transduction pathways”, Cancer Research, Vol. 74, No. 11, 2014, pp. 2936-2945.

[0064] To facilitate the rapid identification of references, the present specification assigns the above references to each signal transduction pathway of interest and shows exemplary corresponding target genes suitable for determining the activity of the signal transduction pathway. In this regard, reference is also made to the sequence listing of the target genes provided with the above references. AR: KLK2, PMEPA1, TMPRSS2, NKX3 1, ABCC4, KLK3, FKBP5, ELL2, UGT2B15, DHCR24, PPAP2A, NDRG1, LRIG1, CREB3L4, LCP1, GUCY1A3, AR, EAF2, APP, NTS, PLAU, CDKN1A, DRG1, FGF8, IGF1, PRKACB, PTPN1, SGK1, and TACC2 (WO2013 / 011479, WO2014 / 102668); KLK2, PMEPA1, TMPRSS2, NKX3 1, ABCC4, KLK3, FKBP5, ELL2, UGT2B15, DHCR24, PPAP2A, NDRG1, LRIG1, CREB3L4, LCP1, GUCY1A3, AR, and EAF2 (WO2014 / 174003); ER: CDH26, SGK3, PGR, GREB1, CA12, XBP1, CELSR2, WISP2, DSCAM, ERBB2, CTSD, TFF1, PDZK1, IGFBP4, ESR1, SOD1, AP1B1, NRIP1, AP1B1, ATP5J, COL18A1, COX7A2L, EBAG9, ESR1, HSPB1, IGFBP4, KRT19, MYC, NDUFV3, PISD, PRDM15, PTMA, RARA, SOD1, and TRIM25 (WO2013 / 011479, WO2014 / 174003); WNT: KIAA1199, AXIN2, RNF43, TBX3, TDGF1, SOX9, ASCL2, IL8, SP5, ZNRF3, KLF6, CCND1, DEFA6, FZD, NKD1, OAT, FAT1, LEF1, GLUL, REG1B, TCF7L2, COL18A1, BMP7, SLC1A2, ADRA2C, PPARG, DKK1, HNF1A, and LECT2 (WO2014 / 174003); HH: GLI1, PTCH1, PTCH2, IGFBP6, SPP1, CCND2, FST, FOXL1, CFLAR, TSC22D1, RAB34, S100A9, S100A7, MYCN, FOXM1, GLI3, TCEA2, FYN, CTSL1, BCL2, FOXA2, FOXF1, H19, HHIP, IL1R2, JAG2, JUP, MIF, MYLK, NKX2.2, NKX2.8, PITRM1, and TOM1 (WO2014 / 174003); NOTCH: CD28, CD44, DLGAP5, DTX1, EPHB3, FABP7, GFAP, GIMAP5, HES1, HES4, HES5, HES7, HEY1, HEY2, HEYL, KLF5, MYC, NFKB2, NOX1, NRARP, PBX1, PIN1, PLXND1, PTCRA, SOX9, and TNC (WO2019 / 068585A1); PI3K: AGRP, BCL2L11, BCL6, BNIP3, BTG1, CAT, CAV1, CCND1, CCND2, CCNG2, CDK 1A, CDK 1B, ESR1, FASLG, FBX032, GADD45A, INSR, MXI1, NOS3, PCK1, POMC, PPARGC1A, PRDX3, RBL2, SOD2, TNFSF10, ATP8A1, C10orf10, CBLB, DDB1, DYRK2, ERBB3, EREG, EXT1, FGFR2, IGF1R, IGFBP1, IGFBP3, LGMN, PPM ID, SEMA3C, SEPP1, SESN1, SLC5A3, SMAD4, TLE4, ATG14, BIRC5, IGFBP1, KLF2, KLF4, MYOD1, PDK4, RAG1, RAG2, SESN1, SIRT1, STK11, and TXNIP (WO2015 / 101635A1); SOD2, BNIP3, MXI1, PCK1, PPARGC1A, and CAT (WO2018 / 096076A1) JAK-STAT1 / 2: BID, GNAZ, IRF1, IRF7, IRF8, IRF9, LGALS1, NCF4, NFAM1, OAS1, PDCD1, RAB36, RBX1, RFPL3, SAMM50, SMARCB1, SSTR3, ST13, STAT1, TRMT1, UFD1L, USP18, and ZNRF3, preferably those selected from the group consisting of IRF1, IRF7, IRF8, IRF9, OAS1, PDCD1, ST13, STAT1, and USP18 (WO2019 / 068562A1); JAK-STAT3: AKT1, BCL2, BCL2L1, BIRC5, CCND1, CD274, CDKN1A, CRP, FGF2, FOS, FSCN1, FSCN2, FSCN3, HIF1A, HSP90AA1, HSP90AB1, HSP90B1, HSPA1A, HSPA1B, ICAM1, IFNG, IL10, JunB, MCL1, MMP1, MMP3, MMP9, MUC1, MYC, NOS2, POU2F1, PTGS2, SAA1, STAT1, TIMP1, TNFRSF1B, TWIST1, VIM, and ZEB1 (WO2019 / 068543A1); MAPK-AP-1: BCL2L11, CCND1, DDIT3, DNMT1, EGFR, ENPP2, EZR, FASLG, FIGF, GLRX, IL2, IVL, LOR, MMP1, MMP3, MMP9, SERPINE1, PLAU, PLAUR, PTGS2, SNCG, TIMP1, TP53, and VIM (WO2019 / 120658A1); NFkB: BCL2L1, BIRC3, CCL2, CCL3, CCL4, CCL5, CCL20, CCL22, CX3CL1, CXCL1, CXCL2, CXCL3, ICAM1, IL1B, IL6, IL8, IRF1, MMP9, NFKB2, NFKBIA, NFKB IE, PTGS2, SELE, STAT5A, TNF, TNFAIP2, TNIP1, TRAF1, and VCAM1 (WO2017 / 029215); TGFβ: ANGPTL4, CDC42EP3, CDKNIA, CDKN2B, CTGF, GADD45A, GADD45B, HMGA2, ID1, IL11, SERPINE1, INPP5D, JUNB, MMP2, MMP9, NKX2-5, OVOL1, PDGFB, PTHLH, SGK1, SKIL, SMAD4, SMAD5, SMAD6, SMAD7, SNAI1, SNAI2, TIMP1, and VEGFA (WO2016 / 062891, WO2016 / 062893).

[0065] In a particularly preferred method, the above-mentioned speculation is including or consisting of measuring the expression levels of three or more target genes of the Wnt pathway, such as 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13 or more, in a sample selected from the group consisting of KIAA1199, AXIN2, RNF43, TBX3, TDGF1, SOX9, ASCL2, IL8, SP5, ZNRF3, KLF6, CCND1, DEFA6, and FZD7, and optionally, the above-mentioned speculation is further based on the expression levels of at least one target gene of the Wnt pathway, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 or more target genes, measured in a sample selected from the group consisting of NKD1, OAT, FAT1, LEF1, GLUL, REG1B, TCF7L2, COL18A1, BMP7, SLC1A2, ADRA2C, PPARG, DKK1, HNF1A, and LECT2. Inferring the activity of the ER cell signaling pathway in a sample based at least on the expression levels of three or more, such as 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, target genes of the ER pathway measured in a sample selected from the group consisting of or comprising CDH26, SGK3, PGR, GREB1, CA12, XBP1, CELSR2, WISP2, DSCAM, ERBB2, CTSD, TFF1, and NRIP1, optionally, the inferring is further based on the expression levels of at least one target gene of the ER pathway, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, or 12 or more target genes, measured in a sample selected from the group consisting of or comprising AP1B1, ATP5J, COL18A1, COX7A2L, EBAG9, ESR1, HSPB1, IGFBP4, KRT19, MYC, NDUFV3, PISD, PRDM15, PTMA, RARA, SOD1, and TRIM25. Inferring the activity of the HH cell signaling pathway in a sample based at least on the expression levels of three or more, such as 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13, target genes of the HH pathway measured in a sample selected from the group consisting of or comprising GLI1, PTCH1, PTCH2, IGFBP6, SPP1, CCND2, FST, FOXL1, CFLAR, TSC22D1, RAB34, S100A9, S100A7, MYCN, FOXM1, GLI3, TCEA2, FYN, and CTSL1, optionally, the inferring is further based on the expression levels of at least one target gene of the HH pathway, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 or more target genes, measured in a sample selected from the group consisting of or comprising BCL2, FOXA2, FOXF1, H19, HHIP, IL1R2, JAG2, JUP, MIF, MYLK, NKX2.2, NKX2.8, PITRM1, and TOM1. Inferring the activity of the AR cell signaling pathway in a sample, based at least on the expression levels of three or more, such as 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13 target genes of the AR pathway measured in a sample selected from the group consisting of or comprising KLK2, PMEPA1, TMPRSS2, NKX3_1, ABCC4, KLK3, FKBP5, ELL2, UGT2B15, DHCR24, PPAP2A, NDRG1, LRIG1, CREB3L4, LCP1, GUCY1A3, AR, and EAF2, and optionally, said inferring is further based on the expression levels of at least one target gene of the AR pathway, such as 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 or more target genes measured in a sample selected from the group consisting of or comprising APP, NTS, PLAU, CDKN1A, DRG1, FGF8, IGF1, PRKACB, PTPN1, SGK1, and TACC2 Inferred activity of the PI3K cell signaling pathway in a sample, at least based on the expression levels of three or more, e.g., 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13 target genes of the PI3K pathway measured in a sample selected from the group consisting of or comprising AGRP, BCL2L11, BCL6, BNIP3, BTG1, CAT, CAV1, CCND1, CCND2, CCNG2, CDK1A, CDK1B, ESR1, FASLG, FBX032, GADD45A, INSR, MX1, NOS3, PCK1, POMC, PPARGC1A, PRDX3, RBL2, SOD2, and TNFSF10, optionally, the inferring comprises ATP8A1, C10orf10, CBLB, DDB1, DYRK2, ERBB3, EREG, EXT1, FGFR2, IGF1R, IGFBP1, IGFBP3, LGMN, PPMBased further on the expression levels of at least one target gene of the PI3K pathway, e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 or more target genes, measured in a sample selected from the group consisting of or comprising ID, SEMA3C, SEPP1, SESN1, SLC5A3, SMAD4, and TLE4. Optionally, the above inference is further based on the expression levels of at least one target gene of the PI3K pathway, e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, or 12 or more target genes, measured in a sample selected from the group consisting of or comprising ATG14, BIRC5, IGFBP1, KLF2, KLF4, MYOD1, PDK4, RAG1, RAG2, SESN1, SIRT1, STK11, and TXNIP. Preferably, inferring the activity of the FOXO / PI3K cell signaling pathway in a sample is based on the expression levels of at least three target genes of the FOXO / PI3K cell signaling pathway, selected from the group consisting of AGRP, BCL2L11, BCL6, BNTP3, BTG1, CAT, CAV1, CCND1, CCND2, CCNG2, CDKN1A, CDKN1B, ESR1, FASLG, FBX032, GADD45A, INSR, MXI1, NOS3, PCK1, POMC, PPARGC1A, PRDX3, RBL2, SOD2, and TNFSF10, measured in an extracted sample of a medical subject. And / or, inferring the oxidative stress state of the FOXO transcription factor element is based on the expression levels of one or more, preferably all, of the target genes of the FOXO transcription factors SOD2, BNIP3, MXI1, and PCK1, measured in an extracted sample of a medical subject. A sample selected from the group consisting of or comprising ANGPTL4, CDC42EP3, CDKNIA, CDKN2B, CTGF, GADD45A, GADD45B, HMGA2, ID1, IL11, SERPINE1, INPP5D, JUNB, MMP2, MMP9, NKX2-5, OVOL1, PDGFB, PTHLH, SGK1, SKIL, SMAD4, SMAD5, SMAD6, SMAD7, SNAI1, SNAI2, TIMP1, and VEGFA, preferably, the group consisting of ANGPTL4, CDC42EP3, CDKNIA, CTGF, GADD45A, GADD45B, HMGA2, ID1, IL11, JUNB, PDGFB, PTHLH, SERPINE1, SGK1, SKIL, SMAD4, SMAD5, SMAD6, SMAD7, SNAI2, VEGFA, more preferably, the group consisting of ANGPTL4, CDC42EP3, CDKNIA, CTGF, GADD45B, ID1, IL11, JUNB, SERPINE1, PDGFB, SKIL, SMAD7, SNAI2, and VEGFA, more preferably, the group consisting of ANGPTL4, CDC42EP3, ID1, IL11, JUNB, SERPINE1, SKIL, and SMAD7, including at least based on the expression levels of three or more, for example 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13 target genes of the TGFβ pathway measured in the sample, inferring the activity of the TGFβ cell signaling pathway in the sample, Including at least based on the expression levels of three or more, for example 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13 target genes of the NFkB pathway measured in a sample selected from the group consisting of or comprising BCL2L1, BIRC3, CCL2, CCL3, CCL4, CCL5, CCL20, CCL22, CX3CL1, CXCL1, CXCL2, CXCL3, ICAM1, IL1B, IL6, IL8, IRF1, MMP9, NFKB2, NFKBIA, NFKB IE, PTGS2, SELE, STAT5A, TNF, TNFAIP2, TNIP1, TRAF1, and VCAM1, inferring the activity of the NFkB cell signaling pathway in the sample, Including or consisting of a group of BID, GNAZ, IRF1, IRF7, IRF8, IRF9, LGALS1, NCF4, NFAM1, OAS1, PDCD1, RAB36, RBX1, RFPL3, SAMM50, SMARCB1, SSTR3, ST13, STAT1, TRMT1, UFDIL, USP18, and ZNRF3, preferably, at least based on the expression levels of three or more, such as 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13 target genes of the JAK-STAT1 / 2 pathway measured in a sample selected from the group consisting of IRF1, IRF7, IRF8, IRF9, OAS1, PDCD1, ST13, STAT1, and USP18, including inferring the activity of the JAK-STAT1 / 2 cell signaling pathway in the sample, Including or consisting of a group of AKT1, BCL2, BCL2L1, BIRC5, CCND1, CD274, CDKN1A, CRP, FGF2, FOS, FSCN1, FSCN2, FSCN3, HIF1A, HSP90AA1, HSP90AB1, HSP90B1, HSPA1A, HSPA1B, ICAM1, IFNG, IL10, JunB, MCL1, MMP1, MMP3, MMP9, MUC1, MYC, NOS2, POU2F1, PTGS2, SAA1, STAT1, TIMP1, TNFRSF1B, TWIST1, VIM, and ZEB1, preferably, either a group consisting of BCL2L1, BIRC5, CCND1, CD274, FOS, HIF1A, HSP90AA1, HSP90AB1, MMP1, and MYC, or a group consisting of BCL2L1, CD274, FOS, HSP90B1, HSPA1B, ICAM1, IFNG, JunB, PTGS2, STAT1, TNFRSF1B, and ZEB1. At least based on the expression levels of three or more, such as 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13 target genes of the JAK-STAT3 pathway measured in a sample selected therefrom, including inferring the activity of the JAK-STAT3 cell signaling pathway in the sample, Including or consisting of a group of BCL2L11, CCND1, DDIT3, DNMT1, EGFR, ENPP2, EZR, FASLG, FIGF, GLRX, IL2, IVL, LOR, MMP1, MMP3, MMP9, SERPINE1, PLAU, PLAUR, PTGS2, SNCG, TIMP1, TP53, and VIM, preferably, at least based on the expression levels of three or more, such as 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13 target genes of the MAPK-AP1 pathway measured in a sample selected from the group consisting of CCND1, EGFR, EZR, GLRX, MMP1, MMP3, PLAU, PLAUR, SERPINE1, SNCG, and TIMP1, including inferring the activity of the MAPK-AP1 cell signaling pathway in the sample, Including or consisting of a group of CD28, CD44, DLGAP5, DTX1, EPHB3, FABP7, GFAP, GIMAP5, HES1, HES4, HES5, HES7, HEY1, HEY2, HEYL, KLF5, MYC, NFKB2, NOX1, NRARP, PBX1, PIN1, PLXND1, PTCRA, SOX9, and TNC, including inferring the activity of the Notch cell signaling pathway in a sample at least based on the expression levels of three or more, such as 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13 target genes of the Notch pathway measured in the sample, wherein preferably, two or more, such as 3, 4, 5, or 6 or more Notch target genes are selected from the group consisting of DTX1, HES1, HES4, HES5, HEY2, MYC, NRARP, and PTCRA, and one or more, such as 2, 3, or 4 or more Notch target genes are selected from the group consisting of CD28, CD44, DLGAP5, EPHB3, FABP7, GFAP, GIMAP5, HES7, HEY1, HEYL, KLF5, NFKB2, NOX1, PBX1, PIN1, PLXND1, SOX9, and TNC, Inferring the activity of the PR cell signaling pathway in a sample, at least based on the expression levels of three or more, e.g., 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or 13 target genes of the PR pathway measured in a sample selected from the group consisting of or comprising AGRP, BCL2L11, BCL6, BNIP3, BTG1, CAT, CAV1, CCND1, CCND2, CCNG2, CDKN1A, CDKN1B, ESR1, FASLG, FBXO32, GADD45A, INSR, MXI1, NOS3, PCK1, POMC, PPARGC1A, PRDX3, RBL2, SOD2, and TNFSF10; preferably, from the group consisting of or comprising BCL2L11, BCL6, BNIP3, BTG1, CAT, CAV1, CCNG2, FBXO32, GADD45A, INSR, MXI1, SOD2, and TNFSF10.

[0066] As used herein, a FOXO transcription factor (TF) element is a protein complex comprising at least one of the FOXO TF family members, namely FOXO1, FOXO3A, FOXO4, and FOXO6, and is defined as controlling the transcription of target genes by being capable of binding to a specific DNA sequence.

[0067] As used herein, a Wnt transcription factor (TF) element is a protein complex comprising at least one of the TCF / LEF TF family members, namely TCF1, TCF3, TCF4, or LEF1 (preferably, the Wnt TF element comprises β-catenin / TCF4), and is defined as controlling the transcription of target genes by being capable of binding to a specific DNA sequence.

[0068] As used herein, a HH transcription factor (TF) element is a protein complex comprising at least one of the GLI TF family members, namely GLI1, GLI2, or GLI3, and is defined as controlling the transcription of target genes by being capable of binding to a specific DNA sequence.

[0069] As used herein, an AR transcription factor (TF) element is defined as a protein complex that includes at least one androgen receptor, or preferably a dimer of androgen receptors.

[0070] As used herein, an ER transcription factor (TF) element is defined as a protein complex that includes at least one estrogen receptor, or preferably a dimer of estrogen receptors, preferably an ERα dimer.

[0071] As used herein, the terms "TGFβ transcription factor element", "TGFβ TF element", or "TF element" when used in relation to the TGFβ pathway are defined as a protein complex that includes at least one, or preferably a dimer (SMAD1, SMAD2, SMAD3, SMAD5, and SMAD8 and SMAD4) or trimer (two of the proteins SMAD1, SMAD2, SMAD3, SMAD5, and SMAD8 and SMAD4) of TGFβ members and that is capable of binding to a specific DNA sequence to control the transcription of target genes. Preferably, this term refers to either a protein or protein complex transcription factor that is triggered by TGFβ binding to its receptor, or an intermediate downstream signaling molecule between TGFβ binding to its receptor and the final transcription factor protein or protein complex. For example, TGFβ binds to an extracellular TGFβ receptor, which initiates an intracellular "SMAD" signaling pathway involving one or more SMAD proteins (R (receptor-regulated)-SMAD (SMAD1, SMAD2, SMAD3, SMAD5, and SMAD8) and SMAD4). Also, this can form a heterocomplex that is involved in the TGFβ transcriptional signaling cascade that controls expression.

[0072] As used herein, an NFkB transcription factor (TF) element is defined as a protein complex that includes at least one NFkB member, or a dimer of NFkB members (NFKB1 or p50 / pl05, NFKB2 or p52 / pl00, RELA or p65, REL and RELB), and controls the transcription of target genes by being able to bind to a specific DNA sequence.

[0073] As used herein, the terms "Notch transcription factor element", "Notch TF element", or "TF element" refer to a protein complex that includes the intracellular domain of a Notch protein (Notch1, Notch2, Notch3, and Notch4 having the corresponding intracellular domains N1ICD, N2ICD, N3ICD, and N4ICD), and a cofactor (e.g., at least the DNA-binding transcription factor CSL (CBF1 / RBP-JK, SU(H), and LAG-1)), and controls the transcription of target genes by being able to bind to a specific DNA sequence and, preferably, to one coactivator protein from the MAML (mastermind-like) family (MAML1, MAML2, and MAML3) necessary for activating transcription. Preferably, this term refers to either a protein or a protein complex transcription factor triggered by the cleavage of one Notch protein out of a plurality of Notch proteins (Notch1, Notch2, Notch3, and Notch4) that result in the Notch intracellular domain (N1ICD, N2ICD, N3ICD, and N4ICD). For example, it is known that DSL ligands (DLL1, DLL3, DLL4, Jagged1, and Jagged2) expressed in adjacent cells bind to the extracellular domain of the Notch protein / receptor and initiate the intracellular Notch signaling pathway, and that the Notch intracellular domain is involved in the Notch signaling cascade that controls expression.

[0074] As used herein, the terms "JAK-STAT1 / 2 transcription factor element", "JAK-STAT1 / 2 TF element", or "TF element" with respect to JAK-STAT1 / 2 are protein complexes that include at least a STAT1-STAT2 heterodimer or a STAT1 homodimer, and are defined as those that can control the transcription of target genes by binding to specific DNA sequences, preferably ISRE (binding motif AGTTTC NTTCNC / T) or GAS (binding motif TTC / A NNG / TAA) response elements, respectively. Preferably, this term refers to either a protein or a protein complex transcription factor formed by different stimuli such as IFN triggered by a stimulatory ligand binding to its receptor to bring about downstream signaling.

[0075] As used herein, the terms "JAK-STAT3 transcription factor element", "JAK-STAT3 TF element", or "TF element" with respect to the JAK-STAT3 pathway are protein complexes that include at least a STAT3 homodimer, and are defined as those that can control the transcription of target genes by binding to a specific DNA sequence, preferably a response element having a binding motif CTGGGAA. Preferably, this term refers to either a protein or a protein complex transcription factor triggered by the binding of a STAT3-inducing ligand such as interleukin-6 (IL-6) or an IL-6 family cytokine to its receptor, or to either an intermediate downstream signaling substance between the binding of the ligand to the receptor and the final transcription factor protein or protein complex.

[0076] As used herein, the terms “AP-1 transcription factor element,” “AP-1 TF element,” or “TF element” when used with respect to the MAPK-AP1 pathway refer to a protein complex that includes at least members of the Jun (e.g., c-Jun, JunB, and JunB) family, and / or members of the Fos (e.g., c-Fos, FosB, Fra-1, and Fra-2) family, and / or members of the ATF family, and / or members of the JDP family, which form, for example, Jun-Jun or Jun-Fos dimers, and that is capable of controlling the transcription of target genes by binding to a specific DNA sequence and preferably a response element having the binding motif 5'-TGA G / C TCA-3', the 12-O-tetradecanoylphorbol-13-acetate (TPA) response element (TRE), or a cyclic AMP response element (CRE) having the binding motif 5'-TGACGTCA-3'. Preferably, the term refers to a protein or protein complex transcription factor that is triggered by, for example, an AP-1-inducing ligand such as a growth factor (e.g., EGF) or cytokine binding to its receptor, or by an intermediate downstream signaling substance, or by the presence of an AP-1 activating mutation.

[0077] As used herein, an “in vitro or ex vivo method” refers to any method performed outside of a human or animal body. Thus, the method may be performed using a sample containing stem cells. Non-limiting examples of samples containing stem cells include cultured cells, cultured cell suspensions, cultured tissues, organoids, or cells or tissues extracted from a human or animal. The term “stem cells” as used herein may also refer to a plurality of stem cells or a sample containing stem cells, and these terms are used synonymously herein.

[0078] As used herein, the step of "determining the differentiation state of a stem cell based on the compared cell signal transduction pathway activity" refers to the step of determining the differentiation state of a stem cell based on the pathway activity. Based on the compared cell signal transduction pathway activity, the differentiation state of the stem cell can be determined by evaluating whether the pathway activity meets or deviates from the expected pathway activity. For example, in the step of comparison, when comparing the activities of three or more pathways to normalize them with an internal reference pathway activity, the pathway activity can be evaluated based on the known or expected pathway activity of the stem cell. For example, embryonic stem cells are known to have high Hedgehog and Notch activities and low FOXO activity, and in such cases, they are considered to be pluripotent. The determined activity of the stem cell can be evaluated based on this knowledge of whether these criteria (i.e., high Hedgehog and Notch activities and low FOXO activity) are met, partially met, or not met at all. Based on this evaluation, the differentiation state of the stem cell can be determined as pluripotency (when the set criteria are met) or partial differentiation (when the criteria are partially met or not met).

[0079] Alternatively, preferably, when in the comparison step, a comparison with the external reference signal transduction pathway activity is made (preferably, the reference signal transduction pathway is the same as three or more signal transduction pathways), based on this comparison, the differentiation state of the stem cells can be directly evaluated. For example, in reference stem cells or samples known to be pluripotent (e.g., it has been verified that they can differentiate in each of the three germ layers), the pathway activities of HH, Notch, and FOXO have been determined. And the obtained values of these pathway activities in the stem cells can be compared with these values. If the values are equal or very close, the stem cells can be regarded as pluripotent. A cut-off value can be used to determine whether a certain value is regarded as equal to the reference value (the value is the numerical value obtained for the pathway activity). Alternatively, when the pathway activity has been determined using a plurality of reference samples, a threshold value, for example, a standard deviation (or a plurality of standard deviations), or can be set based on an alternative statistical evaluation.

[0080] The comparison step may further include additional reference samples. For example, it may be beneficial to include partially differentiated stem cells as a reference in order for the comparison step to include the reference signal transduction pathway activity from pluripotent (or multipotent) stem cells and the reference signal transduction pathway activity from partially differentiated stem cells. This may be even more beneficial when the stem cells may differentiate into different lineages (e.g., the three germ layers), and by including a reference for each of the partially differentiated lineages, it is possible to further distinguish whether the stem cells are partially differentiated or have differentiated in that lineage.

[0081] Therefore, preferably, the method - includes comparing the activities of at least three cell signal transduction pathways in the stem cells with the activities of at least three or more reference cell signal transduction pathways, and more preferably, the method - comparing the activities of at least three cell signaling pathways in the stem cells with the activities of at least three or more reference cell signaling pathways, wherein the three or more cell signaling pathways and the three or more reference cell signaling pathways are the same pathways, and including the step of making the comparison, The differentiation state of the reference sample is known (e.g., totipotency, pluripotency, or partially differentiated).

[0082] More preferably, a plurality of reference samples (e.g., two or more), each having a different known differentiation state, are used.

[0083] As used herein, the term "totipotency" refers to stem cells that can differentiate into each of the three germ layers, such as embryonic stem cells or induced pluripotent stem cells. A cell is said to be able to differentiate into a germ layer if it can differentiate into a cell type or a progenitor cell of a cell type typically associated with that germ layer. Examples of tissues or organs associated with the endoderm are the pharynx, esophagus, stomach, small intestine, colon, liver, pancreas, bladder, epithelial portions of the trachea and bronchi, lungs, thyroid, and parathyroid glands. Examples of tissues or organs associated with the mesoderm are muscle (smooth and striated), bone, cartilage, connective tissue, adipose tissue, the circulatory system, the lymphatic system, the dermis, the urogenital system, the serous membranes, the spleen, and the notochord. Examples of tissues or organs associated with the ectoderm are the epidermis, hair, nails, the lens of the eye, sebaceous glands, the cornea, dental enamel, the epithelium of the mouth and nose, the peripheral nervous system, the adrenal medulla, melanocytes, facial cartilage, dental dentin, the brain, the spinal cord, the posterior pituitary gland, motor neurons, and the retina.

[0084] It is generally known in the art that stem cells that can develop into germ layers do so only when the necessary conditions are met. Generally, a combination of specific growth factors and culture conditions is required.

[0085] As used herein, the term "multipotent" stem cells refers to stem cells such as organ stem cells that can differentiate into different specialized cells. Since multipotent stem cells are generally restricted to a certain germ layer, they can only differentiate into cells of the same germ layer. Non-limiting examples of multipotent stem cells include mesenchymal stem cells, hematopoietic stem cells, umbilical cord blood stem cells, adipose tissue-derived stem cells, cardiac stem cells, vascular stem cells, intestinal crypt stem cells, and neural progenitor cells.

[0086] As used herein, a stem cell is considered to be at least partially differentiated when it has lost the ability to self-renew, i.e., to produce stem cells of the same type, or when it shows a reduced ability to differentiate into all possible cell types or lineages that it is normally capable of differentiating into, i.e., when it becomes restricted to a single cell type or lineage, or a subset of cell types or lineages.

[0087] In one embodiment of the first aspect of the present invention, the reference cell signaling pathway activity is determined in a stem cell, and the comparison step is used to normalize the activity of at least three cell signaling pathways in the stem cell.

[0088] In one embodiment of the first aspect of the present invention, the reference cell signaling pathway activity is determined in one or more reference samples, and the comparison step is used to compare the activity of one or more signaling pathways with a reference having a known differentiation state.

[0089] Preferably, the comparison step is performed by comparing the activity of at least three cell signaling pathways in the stem cell with a reference library, which includes the activity of at least three cell signaling pathways determined in at least two reference samples. In a more preferred embodiment, at least three cell signaling pathways in the reference library are the same as the three or more pathways for which the activity is determined.

[0090] In one embodiment of the first aspect of the present invention, the activities of three or more cell signaling pathways further include the activities of one or more cell signaling pathways selected from the group consisting of PI3K-FOXO, AR, ER, PR, NFkB, AP1-MAPK, JAK-STAT1 / 2, and the PR pathway. Thus, preferably, the method is for the activities of three or more cell signaling pathways, such as 3, 4, 5, 6, 7, 8, 9, or 10 or more cell signaling pathways, such as 3, 4, or 5 cell signaling pathways selected from the group consisting of TGFβ, Notch, JAK-STAT3, Hedgehog, and Wnt, and one or more cell signaling pathways selected from the group consisting of PI3K-FOXO, AR, ER, NFkB, AP1-MAPK, JAK-STAT1 / 2, and the PR pathway, such as 1, 2, 3, 4, 5, 6, 7, or 8 cell signaling pathways, or is based on the obtained results.

[0091] As shown in the examples and figures described below, the TGFβ, Notch, JAK-STAT3, Hedgehog, and Wnt pathways are involved in the process of maintaining the pluripotency and differentiation of stem cells. Therefore, to determine the differentiation state of stem cells, the activities of at least 3, preferably 4, more preferably all 5 of these pathways are required. However, it may be beneficial to additionally determine the activities of one or more of the pathways of PI3K-FOXO, AR, ER, NFkB, AP1-MAPK, JAK-STAT1 / 2, and PR, as additional information may be provided.

[0092] In one embodiment of the first aspect of the present invention, the stem cells are iPS cells, embryonic stem cells, organoid cells, organ- or tissue-derived stem cells, or cancer stem cells. In a particular embodiment, the stem cells are embryonic stem cells or induced pluripotent stem cells. The method can be used, for example, to determine the pluripotency of embryonic stem cells or iPS cells.

[0093] In certain embodiments, the stem cells are cancer stem cells. For example, FIG. 2 shows three different lung cancer cell lines that have been differentiated or not differentiated into cancer stem cells by inducing endothelial-mesenchymal transition by treatment with TGFβ. As can be seen from the figure, FOXO signaling is consistently low across the three cell lines, while TGFβ and Wnt signaling are high in cancer stem cells. This information can be utilized in the methods described herein. Thus, in further embodiments, the state of cancer stem cells is used to determine the stemness of cancer stem cells, and more generally, the method is used to determine the stemness of cancer cells. This can be achieved, for example, by creating two reference samples for a particular cancer type (e.g., lung cancer), one a normal reference sample and the other an induced cancer stem cell reference sample, determining the pathways available for discriminating cancer stem cells, and then comparing cancer cells or cancer stem cells to the reference pathway activity to implement the method of the present invention.

[0094] In certain embodiments, the stem cells are organ stem cells, such as intestinal crypt stem cells. For example, FIG. 3 shows the activities of the MAPK-AP1, ER, FOXO, HH, Wnt, and Notch signaling pathways in various compartments of the intestinal crypt as suggested by EPHB2 expression. Here, high EPHB2 indicates a compartment containing stem cells that self-renew and generate more differentiated daughter cells. The daughter cells slowly move towards the intestinal lumen while differentiating. This figure shows that upon differentiating the stem cells, MAPK-AP1, ER, and FOXO signaling increase, while HH, Wnt, and Notch signaling decrease. Thus, in certain embodiments, the stem cells are organ stem cells, such as intestinal crypt stem cells, and the method is used to determine the differentiation state. As described herein, reference samples representing stem cells and various differentiation states can be used. In further embodiments, the organ stem cells are intestinal stem cells, and the differentiation state is determined based on at least one, two, or three pathways selected from MAPK-AP1, ER, and FOXO and at least one, two, or three pathways selected from HH, Wnt, and Notch.

[0095] In one embodiment of the first aspect of the present invention, the method further includes the step of determining the cell signaling pathway activity of three or more cell signaling pathways. It will be understood that the method can be performed based on an input signal representing the cell signaling pathway activity. Alternatively, a cell signaling pathway may be determined as part of the method. The cell signaling pathway activity may be determined, for example, based on the expression level of the target gene of each cell signaling pathway. The cell signaling pathway activity may be determined using the expression level as described herein.

[0096] In a preferred embodiment of the first aspect of the present invention, the method further includes the step of determining the expression levels of three or more target genes for each cell signaling pathway, and the cell signaling pathway activities of these three or more cell signaling pathways are determined based on the three or more expression levels of the target genes of each cell signaling pathway. In one embodiment, the measurement of the signaling pathway is performed using qPCR, multiple qPCR, multiplexed qPCR, ddPCR, RNAseq, RNA expression array, or mass spectrometry. For example, gene expression microarray data such as Affymetrix microarrays, or RNA sequencing such as Illumina sequencers can be used.

[0097] In a preferred embodiment of the first aspect of the present invention, the stem cells are embryonic stem cells, the differentiation state of the embryonic stem cells is determined to be pluripotent when three or more, preferably four, more preferably five of the following criteria are met, or - High TGFβ signaling, - High Notch signaling, - High STAT3 signaling, - High Hedgehog signaling, - Low Wnt signaling, The differentiation state of embryonic stem cells is determined to be at least partially differentiated when less than three of the above criteria are met, or when at least three of the above criteria are not met.

[0098] Pathway activity can be determined for a reference sample having a known state. For example, a verified pluripotent stem cell sample may be used as a reference sample to determine the activity of the TGFβ, Notch, STAT3, HH, and Wnt signaling pathways. In this way, "high TGFβ signaling activity" may be defined as equal to or equivalent to the pathway activity obtained in the reference sample. Equivalent activity in this context may be activity ± a preset cut-off value. Alternatively, this may be set based on statistical analysis, for example, the mean ± standard deviation when multiple reference samples are analyzed. These can be similarly applied to other pathways. Also, to further define the values and boundaries between pluripotency and non-pluripotency, deviant references (e.g., stem cells verified to be neither pluripotent nor partially differentiated) may be included. For example, if the numerical value of a pathway in a pluripotent reference sample is 20 and the value of the same pathway in a non-pluripotent reference is 6, the cut-off may be determined to be 13 (6+(20-6) / 2 = 13). That is, pathway activity with a value exceeding 13 is considered to belong to the pluripotent state, and less than 13 is considered to belong to the non-pluripotent state.

[0099] In a preferred embodiment of the first aspect of the present invention, the stem cells are induced pluripotent stem cells, The differentiation state of induced pluripotent stem cells is determined to be pluripotent when three or more, preferably four, more preferably five of the following criteria are met, or - High TGFβ signaling, - High Notch signaling, - High STAT3 signaling, - High Hedgehog signaling, - Low Wnt signaling, When less than three of the above criteria are met, the differentiation state of the induced pluripotent stem cells is determined to be at least partially differentiated.

[0100] Pathway activity can be determined for a reference sample having a known state as described above.

[0101] In a preferred embodiment of the first aspect of the present invention, the stem cells are organ stem cells, and the differentiation state of the organ stem cells is determined to be multipotent when three or more of the following criteria are met, or - High Notch signaling, - High Wnt signaling, - Low Hedgehog signaling, - Low MAPK signaling, - Low ER signaling, The differentiation state of the organ stem cells is determined to be partially differentiated when less than three of the above criteria are met, preferably, the organ stem cells are intestinal stem cells.

[0102] Pathway activity can be determined for a reference sample having a known state as described above.

[0103] In a preferred embodiment of the first aspect of the present invention, the activity of the cell signaling pathway used to determine the differentiation state of the stem cells is used to determine the totipotency or multipotency of the stem cells, and the totipotency or multipotency of the stem cells is further - Predict the ability of the stem cells to maintain stemness and / or maintain the stem cell phenotype, and / or - Predict the ability of the stem cells to differentiate into any of the ectodermal, endodermal, and mesodermal lineages, or cells or tissue types thereof, and / or - Predict the ability of the stem cells to maintain a balance between quiescence, proliferation, and regeneration, and is used for one or more of Determining the differentiation state of stem cells further includes determining the lineage of the stem cells, and preferably, the lineage is selected from the group consisting of embryonic stem cells (undifferentiated), anterior primitive streak, mesoderm, embryonic endoderm, anterior foregut, posterior foregut, midgut / hindgut, pluripotent stem cells, multipotent stem cells, organ stem cells, intestinal stem cells, neural progenitor cells, terminally differentiated cells, and / or the method is used to manage the quality of the stem cells by comparing the activities of three or more cell signaling pathways with the activities of three or more desired reference signaling pathways of the stem cells.

[0104] The pathway activity can be determined for a reference sample having a known state as described above.

[0105] In a preferred embodiment of the first aspect of the present invention, the stem cells are embryonic stem cells or induced pluripotent stem cells, and the differentiation state of the embryonic stem cells or induced pluripotent stem cells is determined using the following criteria. - When FOXO signaling is very low, TGFβ signaling is moderate, Wnt signaling is very low, and STAT3 signaling is high, the stem cells are determined to be pluripotent embryonic stem cells, - When FOXO signaling is very low, TGFβ signaling is low, Wnt signaling is low, and STAT3 signaling is high, the stem cells are determined to be primitive streak stem cells, - When FOXO signaling is low, TGFβ signaling is low, Wnt signaling is very low, and STAT3 signaling is low, the stem cells are determined to be embryonic endoderm stem cells, - When FOXO signaling is low, TGFβ signaling is moderate, Wnt signaling is low, and STAT3 signaling is low, the stem cells are determined to be mesoderm stem cells, - When FOXO signaling is low, TGFβ signaling is very low, Wnt signaling is very low, and STAT3 signaling is high, the stem cells are determined to be anterior foregut stem cells, - When FOXO signaling is low, TGFβ signaling is low, Wnt signaling is very low, and STAT3 signaling is high, the stem cells are determined to be posterior foregut stem cells, - When FOXO signaling is very low, TGFβ signaling is very low, Wnt signaling is high, and STAT3 signaling is high, the stem cells are determined to be midgut / hindgut stem cells.

[0106] The pathway activity can be determined for a reference sample having a known state as described above.

[0107] In a second aspect, the present invention relates to a method of creating a reference library for use in a method of characterizing stem cells based on the activity of three or more cell signaling pathways, the method comprising: obtaining two or more reference samples having a known pluripotency or differentiation state; - determining the activity of three or more cell signaling pathways in two or more of the samples, wherein the three or more cell signaling pathways are selected from TGFβ, Notch, JAK-STAT3, Hedgehog, and Wnt, the two or more reference samples are stem cells, the two or more reference samples differ in at least one differentiation or pluripotency parameter, and the comparing step is performed by comparing the activity of at least three cell signaling pathways in the stem cells with the same three pathway activities in the reference library, the reference library comprising the activity of at least three cell signaling pathways determined in two or more reference samples, the numerical values of the activity of at least three cell signaling pathways are calculated based on the expression levels of three or more target genes of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathways measured in the stem cells, and this calculation is Determining the levels of TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt transcription factor (TF) elements in stem cells, wherein the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt TF elements control the transcription of three or more of the target genes of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway, and the determining is at least partially based on evaluating a mathematical model that correlates the expression levels of the three or more target genes of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway with the levels of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt TF elements, and inferring the activity of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway in stem cells based on the determined levels of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt TF elements in the stem cells, Three or more TGFβ target genes are selected from the group consisting of ANGPTL4, CDC42EP3, CDKNIA, CDKN2B, CTGF, GADD45A, GADD45B, HMGA2, ID1, IL11, SERPINE1, INPP5D, JUNB, MMP2, MMP9, NKX2-5, OVOL1, PDGFB, PTHLH, SGK1, SKIL, SMAD4, SMAD5, SMAD6, SMAD7, SNAI1, SNAI2, TIMP1, and VEGFA; Three or more Notch target genes are selected from the group consisting of CD28, CD44, DLGAP5, DTX1, EPHB3, FABP7, GFAP, GIMAP5, HES1, HES4, HES5, HES7, HEY1, HEY2, HEYL, KLF5, MYC, NFKB2, NOX1, NRARP, PBX1, PIN1, PLXND1, PTCRA, SOX9, and TNC; Three or more JAK-STAT3 target genes are selected from the group consisting of AKT1, BCL2, BCL2L1, BIRC5, CCND1, CD274, CDKN1A, CRP, FGF2, FOS, FSCN1, FSCN2, FSCN3, HIF1A, HSP90AA1, HSP90AB1, HSP90B1, HSPA1A, HSPA1B, ICAM1, IFNG, IL10, JunB, MCL1, MMP1, MMP3, MMP9, MUC1, MYC, NOS2, POU2F1, PTGS2, SAA1, STAT1, TIMP1, TNFRSF1B, TWIST1, VIM, and ZEB1, Three or more Hedgehog target genes are selected from the group consisting of GLI1, PTCH1, PTCH2, IGFBP6, SPP1, CCND2, FST, FOXL1, CFLAR, TSC22D1, RAB34, S100A9, S100A7, MYCN, FOXM1, GLI3, TCEA2, FYN, and CTSL1, Three or more Wnt target genes are selected from the group consisting of KIAA1199, AXIN2, RNF43, TBX3, TDGF1, SOX9, ASCL2, IL8, SP5, ZNRF3, KLF6, CCND1, DEFA6, and FZD7.

[0108] Accordingly, the reference library as used herein refers to a set of numerical values representing the pathway activities of three or more cell signaling pathways obtained in one or more stem cells. Preferably, the reference library is created using a plurality of stem cells. Preferably, one or more stem cells used to create the reference library are characterized, i.e., their pluripotency, multipotency, or differentiation state is known.

[0109] Preferably, the three or more cell signaling pathways are selected from the group consisting of TGFβ, Notch, JAK-STAT3, Hedgehog, and Wnt.

[0110] In a further preferred embodiment, the three or more cell signaling pathways further include the activity of one or more cell signaling pathways selected from the group consisting of PI3K-FOXO, AR, ER, PR, NFkB, AP1-MAPK, JAK-STAT1 / 2, and the PR pathway cell signaling pathway activity. Thus, preferably, the method is based on determining the activity of three or more cell signaling pathways, such as the activity of 3, 4, 5, 6, 7, 8, 9, or 10 or more cell signaling pathways, such as 3, 4, or 5 cell signaling pathways selected from the group consisting of TGFβ, Notch, JAK-STAT3, Hedgehog, and Wnt, and one or more cell signaling pathways selected from the group consisting of PI3K-FOXO, AR, ER, PR, NFkB, AP1-MAPK, JAK-STAT1 / 2, and the PR pathway, such as 1, 2, 3, 4, 5, 6, 7, or 8 cell signaling pathways.

[0111] Thus, the comparing step in the method according to the first aspect of the present invention is preferably performed using the reference library described herein or a reference library obtained or obtainable according to the method of the second aspect of the present invention.

[0112] Preferably, stem cells with a known state, such as stem cells that have been verified to be totipotent, pluripotent, unipotent, partially differentiated, etc., are used in the reference library. It may be further advantageous to use a plurality of stem cells having the same (or very similar) state within the reference library, a plurality of stem cells each having a different known state, or a plurality of groups of stem cells where each group is different from each other (with respect to the state of the stem cells) and the cells within the group have the same (or very similar) state.

[0113] In a third aspect, the present invention relates to a non-transitory storage medium for characterizing stem cells, which stores instructions executable by a digital processing device to perform the method of the first aspect of the present invention.

[0114] The non-transitory memory medium may be a computer-readable memory medium, for example, a hard drive or other magnetic storage medium, an optical disk or other optical storage medium, a random access memory (RAM), a read-only memory (ROM), a flash memory, or other electronic storage medium or a network server, etc. The digital processing device may be a handheld device (e.g., a mobile information terminal or a smartphone), a notebook computer, a desktop computer, a tablet computer or device, or a remote network server, etc.

[0115] In a fourth aspect of the present invention, there is provided a computer program for determining the differentiation state of stem cells. When the computer program is executed on a digital processing device, it includes program code means for causing the digital processing device to execute the methods and various embodiments of the first and / or second aspects of the present invention. The computer program may be stored and / or distributed on a suitable medium such as an optical storage medium or a solid-state medium supplied together with or as part of other hardware, or may be distributed in other forms such as via the Internet or other wired or wireless telecommunication systems.

[0116] In a fifth aspect of the present invention, there is provided a kit including components for inferring the activities of three or more cell signaling pathways by determining the expression levels of three or more target gene sets of each cell signaling pathway. The above components are polymerase chain reaction primers and probes targeting three or more target genes of each of the three or more cell signaling pathways. The three or more cell signaling pathways include three or more cell signaling pathways selected from the group consisting of hedgehog (HH), TGFβ, WNT, NOTCH, and JAK-STAT3. Three or more TGFβ target genes are selected from the group consisting of ANGPTL4, CDC42EP3, CDKNIA, CDKN2B, CTGF, GADD45A, GADD45B, HMGA2, ID1, IL11, SERPINE1, INPP5D, JUNB, MMP2, MMP9, NKX2-5, OVOL1, PDGFB, PTHLH, SGK1, SKIL, SMAD4, SMAD5, SMAD6, SMAD7, SNAI1, SNAI2, TIMP1, and VEGFA, Three or more Notch target genes are selected from the group consisting of CD28, CD44, DLGAP5, DTX1, EPHB3, FABP7, GFAP, GIMAP5, HES1, HES4, HES5, HES7, HEY1, HEY2, HEYL, KLF5, MYC, NFKB2, NOX1, NRARP, PBX1, PIN1, PLXND1, PTCRA, SOX9, and TNC, Three or more JAK-STAT3 target genes are selected from the group consisting of AKT1, BCL2, BCL2L1, BIRC5, CCND1, CD274, CDKN1A, CRP, FGF2, FOS, FSCN1, FSCN2, FSCN3, HIF1A, HSP90AA1, HSP90AB1, HSP90B1, HSPA1A, HSPA1B, ICAM1, IFNG, IL10, JunB, MCL1, MMP1, MMP3, MMP9, MUC1, MYC, NOS2, POU2F1, PTGS2, SAA1, STAT1, TIMP1, TNFRSF1B, TWIST1, VIM, and ZEB1, Three or more Hedgehog target genes are selected from the group consisting of GLI1, PTCH1, PTCH2, IGFBP6, SPP1, CCND2, FST, FOXL1, CFLAR, TSC22D1, RAB34, S100A9, S100A7, MYCN, FOXM1, GLI3, TCEA2, FYN, and CTSL1, Three or more Wnt target genes are selected from the group consisting of KIAA1199, AXIN2, RNF43, TBX3, TDGF1, SOX9, ASCL2, IL8, SP5, ZNRF3, KLF6, CCND1, DEFA6, and FZD7 / .

[0117] Optionally, the kit further includes an apparatus including at least one digital processor configured to execute the method of the first aspect, a non-transitory storage medium according to the second aspect, and / or a computer program including program code means for causing the digital processing apparatus to execute the method of the first aspect when executed on the digital processing apparatus.

[0118] Furthermore, there is provided a kit including components for inferring the activities of three or more cell signaling pathways by determining the expression levels of three or more target gene sets of each cell signaling pathway. The above components are polymerase chain reaction primers and probes targeting three or more target genes of each of the three or more cell signaling pathways. The three or more cell signaling pathways include three or more cell signaling pathways selected from the group consisting of AR, ER, FOXO / PI3K, HH, NFkB, TGFβ, WNT, NOTCH, AP1-MAPK, JAK-STAT1 / 2, and JAK-STAT3. Optionally, further included is an apparatus including at least one digital processor configured to execute the method of the first aspect of the present invention, a non-transitory storage medium according to the third aspect of the present invention, and / or a computer program including program code means for causing the digital processing apparatus to execute the method of the first aspect of the present invention when executed on the digital processing apparatus.

[0119] In a sixth aspect of the present invention, there is provided the use of the kit according to the fifth aspect of the present invention for carrying out the method according to the first aspect of the present invention.

[0120] This application describes several preferred embodiments. Those skilled in the art who have read and understood the above detailed description may conceive of modifications and changes. This application is intended to be construed as including all such modifications and changes as long as they are within the scope of the appended claims or their equivalents.

[0121] Other variations of the disclosed embodiments can be understood and realized by those skilled in the art of practicing the claimed invention, from the drawings, the disclosure, and the appended claims.

[0122] The method of the first aspect, the computer-implemented invention of the second aspect, the apparatus of the third aspect, the non-transitory storage medium of the fourth aspect, the computer program of the fifth aspect, and the kit of the sixth aspect have similar and / or identical preferred embodiments, particularly as described in the dependent claims.

[0123] In the claims, the term "comprising" does not exclude other elements or steps, and the singular form does not exclude the plural.

[0124] A single unit or device may perform the functions of multiple items recited in the claims. Just because multiple means are recited in different dependent claims does not necessarily mean that a combination of these means cannot be used advantageously.

[0125] Calculations such as the determination of mortality rate, performed by one or several units or devices, may be performed by any other number of units or devices.

[0126] The computer program may be stored and / or distributed on a suitable medium such as an optical storage medium or a solid-state medium supplied together with or as part of other hardware, or distributed in other forms such as via the Internet or other wired or wireless telecommunication systems.

[0127] It should be understood that the preferred embodiments of the present invention can also be any combination of the dependent claims or the above embodiments and the independent claims.

[0128] The above and other aspects of the present invention will be described and become apparent with reference to the embodiments described below.

Brief Description of the Drawings

[0129] General matters: In all figures where a signal transduction pathway analysis score is shown, the score is given as the log2 odds score of pathway activity derived from the probability score of pathway activity provided by Bayesian pathway model analysis. The log2 odds score indicates the activity level of the signal transduction pathway on a linear scale.

[0130] The analyzed public datasets are shown with their respective GSE numbers (principally at the bottom of each figure), and the individual samples are shown with their GSM numbers (principally in the rightmost column in the case of clustering figures).

[0131] All validation samples for signal transduction pathway models or immune response / system models are independent samples and have not been used for the calibration of each model being validated.

[0132]

Figure 1

[0133]

Figure 2

[0134]

Figure 3

[0135]

Figure 4

[0136]

Figure 5

[0137] During differentiation into neural progenitor cells and during differentiation into differentiated (early and late) neurons, the activities of the MAPK, PI3K, and HH pathways decreased, and the activity of the neuron-specific Notch signaling pathway increased along with the activity of the NFkB pathway. Note: The FOXO activity score is the reciprocal of the PI3K pathway activity. The analyzed Affymetrix expression microarray data are from the GEO dataset GSE74358.

Mode for Carrying Out the Invention

[0138] Examples The Gene Expression Omnibus (GEO) database (https: / / www.ncbi.nlm.nih.gov / gds / ) was used to obtain Affymetrix HG-U133Plus2.0 dataset from clinical and preclinical studies. Information on the datasets used, sample types, and preparations is shown in Table 1 below. The table also includes references related to the original datasets. Pathway analysis was used to determine signaling pathway activities (including AR, ER, PR, GR, HH, Notch, TGFβ, WNT, JAK-STAT1 / 2, JAK-STAT3, NFkB, PI3K, MAPK pathways). For each dataset, various pathway activities were compared within groups. The results for each dataset are described in the figure legends.

[0139] Affymetrix U133Plus2.0 microarray data was downloaded from the public GEO database, and signaling pathway analysis of the PI3K-FOXO, Hedgehog (HH), TGFβ, Wnt, Notch, JAK-STAT, NFkB, and MAPK-AP1 pathways was performed as described above and presented as the log2 odds of the probabilities calculated by each signaling pathway model. The results of each pathway activity are shown for each individual sample. The pathway activity scores are on the log2 odds scale. (Results) Signaling pathway-based pluripotency test.

[0140] Figure 1 shows that signaling pathway analysis detects differences in the activities of signaling pathways important for maintaining pluripotency. One of the envisioned uses is to provide a quality control tool for pluripotent stem cell culture. The results of multiple pathway analyses indicate that the Hedgehog (HH) pathway is always active, while the activities of the TGFβ, Notch, and PI3K pathways are highly dependent on the culture conditions.

[0141] As shown for cancer stem cells (Figure 2) and primary human intestinal stem cells present within the crypt compartment of the intestinal wall (Figure 3), pathway analysis can also be used to quantitatively characterize the stemness of various types of stem cells.

[0142] Figure 2: Results of multiple pathway analysis show higher TGFβ and Wnt pathway activities in EMT cells. PI3K pathway activity (the reciprocal of FOXO transcription factor activity) varies by cell line. Increases in the activities of the TGFβ and Wnt signaling pathways confer stem cell replication characteristics.

[0143] Figure 3. Consistent with the stem cell characteristics of these cells, in combination with the active Notch pathway, the Wnt pathway was highly active. The inactive FOXO transcription factor in these ISCs suggests an active PI3K pathway. Low FOXO activity and high PI3K pathway activity are typically associated with dividing cells and are consistent with the observed high KI67 expression. In contrast, low EPHB2 levels corresponded to differentiated non-dividing cells.

[0144] A signaling pathway-based test for quantitatively characterizing differentiation steps and changes in pathway activity during differentiation.

[0145] Stem cells can differentiate into various cell types under the control of specific signals. As shown in Figure 4, measurement of signaling pathway activity can be used to quantitatively evaluate the differentiation state of cultured cells at the final differentiation stage or between differentiation stages.

[0146] Figure 4 Induction of Wnt activity and reduction of PI3K / mTOR pathway activity were measured. At the stage of differentiation from APS to definitive endoderm (DE), stimulation was performed by high activin and BMP blockade to prevent mesoderm formation. Along with the reduction of PI3K, STAT3, and Wnt pathway activities, an increase in MAPK pathway activity was measured (in contrast to mesoderm). Subsequently, treatment with BMP, Wnt, and FGF was used to differentiate DE cells into various types of foregut cells (AFG / PFG / MHG) over 4 days. In contrast to the anterior pharyngeal endoderm (by inhibition of the BMP / Wnt / FGF pathway), posterior midgut / hindgut progenitor cells showed higher Wnt pathway activity along with Notch, TGFβ, and MAPK-AP1 activities.

[0147] Differentiation of iPS cells into neural progenitor cells was accompanied by induction of FOXO activity and thus reduction of PI3K pathway activity and Notch pathway activity (Figure 5).

[0148] Signal transduction pathway-based tests for quantitatively characterizing the differentiation potential into mesoderm, endoderm, and ectoderm lineages.

[0149] Computational model for interpretation of pathway analysis results Computational model for interpretation of pathway analysis results to provide a quantitative score of pluripotency Linear model The score is composed of 1 point for each of the developmental stem cell pathways (PI3K pathway, Hedgehog pathway, TGFβ pathway, Notch pathway, STAT3 pathway) that should be active in pluripotent stem cells. In the results of Figure 1 [Table 1]

Claims

1. An in vitro or ex vivo computer-implemented method for determining the differentiation state of stem cells based on the results of determining the activity of at least three cell signaling pathways selected from the group consisting of TGFβ, Notch, JAK-STAT3, Hedgehog, and Wnt, the method comprising: Calculating numerical values of the activity of the at least three cell signaling pathways; Comparing the numerical values calculated for the activity of the at least three cell signaling pathways in the stem cells with the numerical values calculated for the activity of the same three cell signaling pathways in the at least three cell signaling pathways in a reference library, the reference library including the activity of the at least three cell signaling pathways determined in at least two reference samples, the reference samples being obtained from the same type of stem cells, the step of making the comparison; Determining the differentiation state of the stem cells based on the compared cell signaling pathway activities, the differentiation state of the stem cells being determined as totipotency, pluripotency, unipotency, or at least partially differentiated, the step of making the determination; and For each cell signaling pathway in the reference library, an average pathway activity and a standard deviation are calculated for each state of the cells; The step of making the comparison is for each cell signaling pathway activity; When the value is within the range of one standard deviation of the average, the value is said to be equal to or equivalent to the pathway activity of the reference sample; When the value is more than one standard deviation higher than the average, the value is considered high, or When the value is more than one standard deviation lower than the average, the value is considered low; Further comprising the step of determining this; The numerical values of the activity of the at least three cell signaling pathways are calculated based on the expression levels of three or more target genes of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway measured in the stem cells, and the calculation is: Determining the level of a TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt transcription factor (TF) element in the stem cell, wherein the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt TF element controls the transcription of three or more of the target genes of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway, and determining the level comprises at least partially based on evaluating a mathematical model that associates the expression levels of the three or more target genes of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway with the level of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt TF element, Inferring the activity of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway in the stem cell based on the determined level of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt TF element in the stem cell, The three or more TGFβ target genes are selected from the group consisting of ANGPTL4, CDC42EP3, CDKNIA, CDKN2B, CTGF, GADD45A, GADD45B, HMGA2, ID1, IL11, SERPINE1, INPP5D, JUNB, MMP2, MMP9, NKX2-5, OVOL1, PDGFB, PTHLH, SGK1, SKIL, SMAD4, SMAD5, SMAD6, SMAD7, SNAI1, SNAI2, TIMP1, and VEGFA, The three or more Notch target genes are selected from the group consisting of CD28, CD44, DLGA5, DTX1, EPHB3, FABP7, GFAP, GIMAP5, HES1, HES4, HES5, HES7, HEY1, HEY2, HEYL, KLF5, MYC, NFKB2, NOX1, NRARP, PBX1, PIN1, PLXND1, PTCR, SOX9, and TNC, The above three or more JAK-STAT3 target genes are selected from the group consisting of AKT1, BCL2, BCL2L1, BIRC5, CCND1, CD274, CDKN1A, CRP, FGF2, FOS, FSCN1, FSCN2, FSCN3, HIF1A, HSP90AA1, HSP90AB1, HSP90B1, HSP A1A, HSP A1B, ICAM1, IFNγ, IL10, JunB, MCL1, MMP1, MMP3, MMP9, MUC1, MYC, NOS2, POU2F1, PTGS2, SAA1, STAT1, TIMP1, TNFRSF1B, TWIST1, VIM, and ZEB1, The above three or more Hedgehog target genes are selected from the group consisting of GLI1, PTCH1, PTCH2, IGFBP6, SPP1, CCND2, FST, FOXL1, CFLAR, TSC22D1, RAB34, S100A9, S100A7, MYCN, FOXM1, GLI3, TCEA2, FYN, and CTSL1, The above three or more Wnt target genes are selected from the group consisting of KIAA1199, AXIN2, RNF43, TBX3, TDGF1, SOX9, ASCL2, IL8, SP5, ZNR F3, KLF6, CCND1, DEFA6, and FZD7, a method.

2. The above three or more cell signaling pathway activities further include one or more cell signaling pathway activities selected from the group consisting of PI3K-FOXO, AR, ER, PR, NFκB, AP1-MAPK, JAK-STAT1 / 2, and PR pathway cell signaling pathway activities, the method according to claim 1.

3. The stem cells are iPS cells, embryonic stem cells, stem cells derived from organs or tissues, or cancer stem cells, the method according to claim 1 or 2.

4. The method further includes the step of determining the cell signaling pathway activities of the above three or more cell signaling pathways, the method according to any one of claims 1 to 3.

5. The method further includes the step of determining the expression levels of three or more target genes for each cell signaling pathway, and the above three or more cell signaling pathway activities are determined based on the above three or more expression levels of the target genes of each cell signaling pathway, the method according to claim 4.

6. The stem cells are embryonic stem cells, The differentiation state of the embryonic stem cells is with high TGFβ signaling, High Notch signaling, High STAT3 signaling, High Hedgehog signaling, When three or more of the criteria of low Wnt signaling are met, it is determined to be pluripotent, or The differentiation state of the embryonic stem cells is determined to be at least partially differentiated when less than three of the criteria are met. The method according to any one of claims 1 to 5.

7. The stem cells are induced pluripotent stem cells, The differentiation state of the induced pluripotent stem cells is High TGFβ signaling, High Notch signaling, High STAT3 signaling, High Hedgehog signaling, When three or more of the criteria of low Wnt signaling are met, it is determined to be pluripotent, or The differentiation state of the induced pluripotent stem cells is determined to be at least partially differentiated when less than three of the criteria are met. The method according to any one of claims 1 to 5.

8. The stem cells are organ stem cells, The differentiation state of the organ stem cells is High Notch signaling, High Wnt signaling, Low Hedgehog signaling, Low MAPK signaling, Low ER signaling, when three or more of the criteria are met, it is determined to be multipotent, or The differentiation state of the organ stem cells is determined to be partially differentiated when less than three of the criteria are met, The method according to any one of claims 1 to 7.

9. The organ stem cells are intestinal stem cells. The method according to claim 8.

10. The cell signaling pathway activity used to determine the differentiation state of the stem cells is used to determine the pluripotency or multipotency of the stem cells, and the pluripotency or multipotency of the stem cells further Maintains stemness and / or predicts the ability of the stem cells to maintain a stem cell phenotype, and / or Predicting the ability of the stem cells to differentiate into any of the ectodermal, endodermal, and mesodermal lineages, or cells or tissue types thereof, and / or Predicting the ability of the stem cells to maintain a balance during quiescence, proliferation, and regeneration, and is used for one or more of them, and / or Determining the differentiation state of the stem cells further includes determining the lineage of the stem cells, The lineage is selected from the group consisting of embryonic stem cells (undifferentiated), anterior primitive streak, mesoderm, intraembryonic endoderm, anterior foregut, posterior foregut, midgut / hindgut, pluripotent stem cells, multipotent stem cells, organ stem cells, intestinal stem cells, neural progenitor cells, and terminally differentiated cells, and / or The method according to any one of claims 1 to 9, which is used to control the quality of the stem cells by comparing the activities of the three or more cell signaling pathways with the activities of three or more desired reference signaling pathways of the stem cells.

11. A computer program executed by a digital processing device to cause the digital processing device to execute the method according to any one of claims 1 to 10.

12. Use of a kit for determining the expression level of a target gene of a cell signaling pathway, the kit including components for inferring the activity of the cell signaling pathway by determining the expression levels of three or more target gene sets of each of the three or more cell signaling pathways, The components are polymerase chain reaction primers and probes for the three or more target genes of each of the three or more cell signaling pathways, The three or more cell signaling pathways include three or more cell signaling pathways selected from the group consisting of Hedgehog (HH), TGFβ, WNT, NOTCH, and JAK-STAT3, The three or more TGFβ target genes are selected from the group consisting of ANGPTL4, CDC42EP3, CDKNIA, CDKN2B, CTGF, GADD45A, GADD45B, HMGA2, ID1, IL11, SERPINE1, INPP5D, JUNB, MMP2, MMP9, NKX2-5, OVOL1, PDGFB, PTHLH, SGK1, SKIL, SMAD4, SMAD5, SMAD6, SMAD7, SNAI1, SNAI2, TIMP1, and VEGFA, The three or more Notch target genes are selected from the group consisting of CD28, CD44, DLGA5, DTX1, EPHB3, FABP7, GFAP, GIMAP5, HES1, HES4, HES5, HES7, HEY1, HEY2, HEYL, KLF5, MYC, NFKB2, NOX1, NRARP, PBX1, PIN1, PLXND1, PTCR, SOX9, and TNC The above three or more JAK-STAT3 target genes are selected from the group consisting of AKT1, BCL2, BCL2L1, BIRC5, CCND1, CD274, CDKN1A, CRP, FGF2, FOS, FSCN1, FSCN2, FSCN3, HIF1A, HSP90AA1, HSP90AB1, HSP90B1, HSP A1A, HSP A1B, ICAM1, IFNγ, IL10, JunB, MCL1, MMP1, MMP3, MMP9, MUC1, MYC, NOS2, POU2F1, PTGS2, SAA1, STAT1, TIMP1, TNFRSF1B, TWIST1, VIM, and ZEB1, The above three or more Hedgehog target genes are selected from the group consisting of GLI1, PTCH1, PTCH2, IGFBP6, SPP1, CCND2, FST, FOXL1, CFLAR, TSC22D1, RAB34, S100A9, S100A7, MYCN, FOXM1, GLI3, TCEA2, FYN, and CTSL1, The above three or more Wnt target genes are selected from the group consisting of KIAA1199, AXIN2, RNF43, TBX3, TDGF1, SOX9, ASCL2, IL8, SP5, ZNR3, KLF6, CCND1, DEFA6, and FZD7, The use includes determining the expression levels of the above three or more target genes of each of the above three or more cell signaling pathways, Calculating numerical values of at least three cell signaling pathway activities, Comparing the numerical values calculated for the at least three cell signaling pathway activities in the stem cells with the numerical values calculated for the same at least three cell signaling pathway activities in the at least three cell signaling pathways in the reference library, wherein the reference library includes the at least three cell signaling pathway activities determined in at least two reference samples, and the reference samples are obtained from stem cells of the same type, the comparing, Determining the differentiation state of the stem cells based on the compared cell signaling pathway activities, wherein the differentiation state of the stem cells is determined to be totipotency, pluripotency, unipotency, or at least partially differentiated, the determining, and includes, For each cell signaling pathway in the reference library, the average pathway activity and standard deviation are calculated for each state of the cells, Said comparing, for each cell signaling pathway activity, when the value is within the range of one standard deviation of the average, the value is said to be equal to or equivalent to the pathway activity of the reference sample, when the value is more than one standard deviation higher than the average, the value is regarded as high, or when the value is more than one standard deviation lower than the average, the value is regarded as low, further comprising determining this, the numerical values of the at least three cell signaling pathway activities are calculated based on the expression levels of three or more target genes of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway measured in the stem cells, and the calculation is determining the levels of TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt transcription factor (TF) elements in the stem cells, wherein the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt TF elements control the transcription of the three or more target genes of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway, and determining the levels is at least partially based on evaluating a mathematical model that associates the expression levels of the three or more target genes of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway with the levels of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt TF elements, determining, inferring the activity of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt cell signaling pathway in the stem cells based on the determined levels of the TGFβ, Notch, JAK-STAT3, Hedgehog, or Wnt TF elements in the stem cells, and including, Furthermore, the use of a kit comprising at least one digital processor configured to execute the method according to any one of claims 1 to 10, or a computer program according to claim 11. **Claim 13**: A kit for determining the expression level of a target gene of a cell signaling pathway, the kit comprising components for inferring the activity of the cell signaling pathway by determining the expression levels of three or more target gene sets of each of three or more cell signaling pathways. The component is a polymerase chain reaction primer and probe targeting each of the three or more target genes of the three or more cell signaling pathways, The three or more cell signaling pathways include three or more cell signaling pathways selected from the group consisting of Hedgehog (HH), TGFβ, WNT, NOTCH, and JAK-STAT3, The three or more TGFβ target genes are selected from the group consisting of ANGPTL4, CDC42EP3, CDKNIA, CDKN2B, CTGF, GADD45A, GADD45B, HMGA2, ID1, IL11, SERPINE1, INPP5D, JUNB, MMP2, MMP9, NKX2-5, OVOL1, PDGFB, PTHLH, SGK1, SKIL, SMAD4, SMAD5, SMAD6, SMAD7, SNAI1, SNAI2, TIMP1, and VEGFA, The three or more Notch target genes are selected from the group consisting of CD28, CD44, DLGA5, DTX1, EPHB3, FABP7, GFAP, GIMAP5, HES1, HES4, HES5, HES7, HEY1, HEY2, HEYL, KLF5, MYC, NFKB2, NOX1, NRARP, PBX1, PIN1, PLXND1, PTCR A, SOX9, and TNC, The three or more JAK-STAT3 target genes are selected from the group consisting of AKT1, BCL2, BCL2L1, BIRC5, CCND1, CD274, CDKN1A, CRP, FGF2, FOS, FSCN1, FSCN2, FSCN3, HIF1A, HSP90AA1, HSP90AB1, HSP90B1, HSP A1A, HSP A1B, ICAM1, IFNγ, IL10, JunB, MCL1, MMP1, MMP3, MMP9, MUC1, MYC, NOS2, POU2F1, PTGS2, SAA1, STAT1, TIMP1, TNFRSF1B, TWIST1, VIM, and ZEB1, The three or more Hedgehog target genes are selected from the group consisting of GLI1, PTCH1, PTCH2, IGFBP6, SPP1, CCND2, FST, FOXL1, CFLAR, TSC22D1, RAB34, S100A9, S100A7, MYCN, FOXM1, GLI3, TCEA2, FYN, and CTSL1, The three or more Wnt target genes are selected from the group consisting of KIAA1199, AXIN2, RNF43, TBX3, TDGF1, SOX9, ASCL2, IL8, SP5, ZNRRF3, KLF6, CCND1, DEFA6, and FZD7, The kit further comprises an apparatus including at least one digital processor configured to execute the method according to any one of claims 1 to 10, or a kit including the computer program according to claim 11.

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