A marker combination for identifying a subpopulation of human skin epidermal basal keratinocytes

Abstract

The application discloses a marker combination for identifying a human skin epidermis basal keratinocyte subpopulation, belongs to the technical field of biotechnology, the basal keratinocyte subpopulation is a Basal_IGFBP3 subpopulation, the marker combination at least includes IGFBP3 and ASCL2, further includes KRT5 and / or TP63, and EMP2, and meanwhile, a corresponding identification kit and a method for evaluating the skin aging degree are provided. The application firstly defines the Basal_IGFBP3 subpopulation by co-expression of IGFBP3 and ASCL2, confirms the identification object, and anchors the "epidermis basal layer" by expression of KRT5 and / or TP63, avoids that the basal upper layer cells are mistakenly included in the judgment, and further takes low expression of EMP2 as a positive exclusion condition, so that the specificity of subpopulation definition is greatly improved. An objective and quantifiable skin aging degree evaluation index is further provided, and the skin aging degree can be evaluated in vitro.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, specifically to a combination of markers for identifying a subset of basal keratinocytes in the human epidermis. Background Technology

[0002] The self-renewal of the human epidermis depends on keratinocytes located in the basal cell layer. For a long time, the basal layer of the epidermis has been viewed as a whole, and basal cells have been distinguished from cells in the upper basal layers (spike layer, granular layer) using markers such as ITGA6 (CD49f), ITGB1, ITGB4, KRT15, ​​KRT14, COL17A1, LRIG1, DLL1, and TP63. However, with the application of single-cell resolution analysis methods, it has become increasingly clear that the basal cell layer is not homogeneous, but rather composed of several cell subpopulations with different transcriptional characteristics. The existing technology has the following problems: Existing biomarkers are limited to the "epidermal layer" level, rather than the "basal layer subpopulation" level. These classic biomarkers are widely expressed throughout the basal layer, only answering whether a cell is a basal cell, not which subpopulation within the basal layer it belongs to. While some literature reports that IGFBP3 mRNA is localized to the basal cell layer in normal human epidermis, and some single-cell atlases list IGFBP3 as a marker gene for basal cell clusters, these reports remain at the layer or cluster level, failing to distinguish independent cell subpopulations characterized by IGFBP3 within the basal layer, and providing no operational criteria for defining this subpopulation on in situ sections. Similarly, ASCL2 has previously been reported to be associated with the differentiation degree of keratinocytes, i.e., higher in the basal layer than the suprabasal layer; this report is also at the "layer-to-layer" scale, not addressing the differences in ASCL2 expression among different subpopulations within the basal layer. Therefore, at the resolving scale of subpopulations within the basal layer, current technologies have not yet recognized the co-expression relationship between IGFBP3 and ASCL2 and the cellular subpopulations they define, lacking objective quantitative interpretation standards that can be compared across samples and batches. The absolute signal intensity of in situ immunostaining is affected by various factors such as antibody batch, primary and secondary antibody concentrations, slide thickness, antigen retrieval conditions, incubation time, and microscope excitation power and gain. The absolute gray values ​​between different samples and batches cannot be directly compared. Current technologies mostly rely on the reader's subjective visual judgment of "strong positive / weak positive" or use fixed absolute gray thresholds. The former has poor repeatability, while the latter will systematically overestimate or underestimate the positive proportion due to batch-to-batch drift. This directly leads to the difficulty in establishing comparability between different samples for quantitative applications based on "subpopulation proportion" (such as the evaluation of skin aging), and the inability to form objective and reproducible evaluation indicators. Summary of the Invention

[0003] To address the problems existing in the prior art, this invention provides a combination of markers for identifying a subset of basal keratinocytes in the human epidermis, as well as a kit for identifying such a subset. The basal keratinocyte subset is a subset of keratinocytes exhibiting basal cell characteristics, which are: compared to other cells in the basal layer of the epidermis in the same sample, the subset has lower expression scores for cell cycle-related genes (including S-phase and G2M-phase gene sets), and / or higher expression of COL17A1 and KRT15.

[0004] In a first aspect, the present invention provides a combination of markers for identifying a subset of basal keratinocytes in human epidermis, wherein the basal keratinocyte subset is the Basal_IGFBP3 subset, and the combination of markers includes at least IGFBP3 and ASCL2.

[0005] As an improvement to the first aspect, the above-mentioned combination of markers also includes: KRT5 and / or TP63.

[0006] As an improvement to the first aspect, the above-mentioned combination of markers also includes: EMP2.

[0007] Secondly, the present invention provides a kit for identifying human epidermal basal keratinocyte subsets, including reagents for specifically detecting IGFBP3 and reagents for specifically detecting ASCL2. The reagent for specifically detecting IGFBP3 is an anti-human IGFBP3 antibody or an in situ hybridization probe for detecting IGFBP3 mRNA; the reagent for specifically detecting ASCL2 is an anti-human ASCL2 antibody or an in situ hybridization probe for detecting ASCL2 mRNA.

[0008] As an improvement to the second aspect, the above kit also includes reagents for the specific detection of KRT5 and / or TP63; The reagent for specifically detecting KRT5 is an anti-human KRT5 antibody or an in situ hybridization probe for detecting KRT5 mRNA; the reagent for specifically detecting TP63 is an anti-human TP63 antibody or an in situ hybridization probe for detecting TP63 mRNA.

[0009] As another improvement to the second aspect, the above kit also includes reagents for the specific detection of EMP2; The reagents for specifically detecting EMP2 are human EMP2 antibodies or in situ hybridization probes for detecting EMP2 mRNA.

[0010] Thirdly, the present invention provides a method for identifying a subset of basal keratinocytes in the basal layer of human epidermis, wherein the basal keratinocyte subset is the Basal_IGFBP3 subset, and the method includes: IGFBP3 and ASCL2 were detected in situ on sections of ex vivo human skin tissue samples. When the cells in the basal layer of the epidermis showed both IGFBP3 positivity and ASCL2 positivity, the cells were determined to belong to the Basal_IGFBP3 subpopulation.

[0011] As an improvement to the third aspect, the above method further includes: detecting KRT5 and / or TP63 in situ on sections of ex vivo human skin tissue samples, and determining that the epidermal basal cell layer cells belong to the Basal_IGFBP3 subpopulation based on the presence of KRT5 positivity and / or TP63 positivity.

[0012] As another improvement to the third aspect, the above method further includes: detecting EMP2 in situ on sections of ex vivo human skin tissue samples, and identifying cells with low EMP2 expression as the Basal_IGFBP3 subset.

[0013] Furthermore, the above-mentioned criteria for determining a positive result include: The IGFBP3 and ASCL2 detection signal intensities of epidermal basal cells in the same sample slice were used to construct IGFBP3 and ASCL2 reference distributions, respectively. The corresponding detection signal intensities of each cell were robustly normalized using the median and median absolute deviation (MAD) of each reference distribution to obtain the robust z-scores of IGFBP3 and ASCL2 for that cell. The detection signal intensity is the average signal intensity measured cell by cell in the subcellular compartment corresponding to the target marker. In immunofluorescence detection, it is the average fluorescence intensity; in immunohistochemistry detection, it is the average optical density; and in situ hybridization detection, it is the number of signal points per cell or the average signal intensity. When the robust z-scores of IGFBP3 and ASCL2 in a cell are both not less than the first judgment threshold z0, the cell is judged to be positive for IGFBP3 and ASCL2; where z0 is 0.8 to 2.5. Preferably, the first determination threshold z0 is 1.0.

[0014] Furthermore, the determination of low EMP2 expression includes: The EMP2 detection signal intensity of epidermal basal cells in the same sample slice was used to construct an EMP2 reference distribution. The EMP2 detection signal intensity of each cell was robustly normalized using the median and median absolute deviation (MAD) of the reference distribution to obtain the robust EMP2 z-score of the cell. When the robust EMP2 z-score of the cell is less than the second judgment threshold z0′, the cell is judged to have low EMP2 expression. Here, z0′ is -0.5 to 0.5.

[0015] Preferably, the second determination threshold z0 mentioned above Take 0.

[0016] Fourthly, the present invention also provides a method for evaluating the degree of aging of ex vivo human skin tissue samples for non-disease diagnostic purposes. Based on any combination of markers provided in the first aspect, any reagent kit provided in the second aspect, or any method provided in the third aspect, the method identifies whether the basal keratinocyte subpopulation in the ex vivo human skin tissue sample section is the Basal_IGFBP3 subpopulation. If so, the method further calculates the proportion P of the number of Basal_IGFBP3 subpopulation cells in the ex vivo human skin tissue sample section to the total number of epidermal basal cells in the ex vivo human skin tissue sample section. The lower the proportion P, the higher the degree of skin aging of the ex vivo human skin tissue sample.

[0017] As another improvement in the fourth aspect, the above also includes comparing the ratio P with the age-matched reference value P0. When P is significantly lower than the age-matched reference value P0, it is determined that the skin aging degree of the sample is higher than the level corresponding to its age.

[0018] Compared with the prior art, the beneficial effects of the present invention are reflected in the following aspects: First, this invention is the first to propose defining an independent keratinocyte subpopulation—the Basal_IGFBP3 subpopulation—in the basal layer by using the co-expression of IGFBP3 and ASCL2 at the subpopulation resolution scale. The criteria provided by this invention and the existing technologies’ understanding of “IGFBP3 is located in the basal layer of the epidermis” and “ASCL2 is related to the degree of epidermal differentiation” belong to different resolution scales: detecting IGFBP3 alone or ASCL2 alone is not enough to define this subpopulation in the basal layer; only the co-expression of the two has subpopulation specificity.

[0019] Second, the present invention further anchors the spatial and lineage premise of "epidermal basal layer" by the expression of KRT5 and / or TP63, ensuring that the identified cell set itself is correct and avoiding the misinclusion of upper basal cells in the interpretation.

[0020] Third, this invention further uses low EMP2 expression as an orthogonal exclusion criterion. EMP2 is a membrane protein that increases with keratinocyte differentiation and is expressed at higher levels in most cell populations in the upper basal layer. Therefore, in addition to the double positive criteria of IGFBP3 and ASCL2, an additional reverse screening is added, which can significantly reduce the misjudgment of adjacent subpopulations and improve the specificity of subpopulation definition.

[0021] Fourth, the identification method of this invention is performed in situ on sections that preserve the tissue structure, without the need to dissociate the epidermis, prepare single-cell suspensions, or sort live cells. On the one hand, it completely preserves the spatial position of cells on the basement membrane and their relationship with the epidermal layers; on the other hand, it fundamentally avoids the inherent defect that IGFBP3, as a secreted protein, cannot be used for sorting live cells—on the fixed sections, the antibody recognizes IGFBP3 synthesized by the cell itself and retained intracellularly and near the membrane, and its signal can be used to characterize the cell's own IGFBP3 expression.

[0022] Fifth, this invention provides objective and quantifiable evaluation indicators for the degree of skin aging, enabling in vitro evaluation of the degree of skin aging. Attached Figure Description

[0023] Figure 1 This is a quality control plot for single-cell transcriptome data of human skin epidermal cells; among them... Figure 1 a is a scatter plot with the percentage of non-mitochondrial gene counts on the horizontal axis and the base-2 logarithm of the number of genes detected per cell plus 1 on the vertical axis. Figure 1 b is another way to plot the same quality control relationship. In the figure, the scatter points are cell-by-cell values, and the curves are two-dimensional density contour lines. Figure 1 c is a distribution chart of the quality control indicators for each sample; Figure 1 d is a histogram of the density distribution of mitochondrial gene proportions in all cells, with the horizontal axis representing the proportion of mitochondrial genes and the vertical axis representing density.

[0024] Figure 2 This image shows a single-cell transcriptome atlas of human skin epidermal cells and the results of basal cell re-clustering; among them... Figure 2 a is a UMAP dimension reduction plot of all epidermal cells; Figure 2 b is the UMAP dimensionality reduction plot after re-clustering of basal keratinocytes. Figure 2 c is a UMAP projection of the expression levels of four genes in basal keratinocytes.

[0025] Figure 3 A dot plot showing the expression of marker genes in each basal subpopulation.

[0026] Figure 4 Image showing the in situ identification results of IGFBP3 and TP63, and IGFBP3 and ASCL2 in human skin tissue using dual immunofluorescence; among them... Figure 4 a represents the result of dual immunofluorescence staining for IGFBP3 and TP63; Figure 4 b shows the results of dual immunofluorescence staining for IGFBP3 and ASCL2.

[0027] Figure 5 This is a robust normalized positive determination plot based on the same sample reference distribution; where, Figure 5 a is a histogram of the frequency distribution of IGFBP3 signal intensity in all basal cells of the same slice; Figure 5 b is a histogram of the frequency distribution of ASCL2 signal intensity in all basal cells of the same slice; Figure 5 c is a scatter plot with the IGFBP3 robust z-score on the horizontal axis and the ASCL2 robust z-score on the vertical axis.

[0028] Figure 6 This is a diagram showing the results of excluding cells with relatively high EMP2 expression in the basal layer based on low EMP2 expression; where, Figure 6 a shows the spatial distribution of EMP2-expressing cells and IGFBP3 and ASCL2 double-positive cells in the basal layer; Figure 6 b is a graph comparing the EMP2 robust z-scores of double-positive cells with those of the remaining cells in the basal layer.

[0029] Figure 7 This image shows a comparison of the proportion of the described subpopulations in basal layer cells in skin samples from different age groups; among them, Figure 7 a represents the in situ quantitative results (the horizontal axis represents the age group, and the vertical axis represents the percentage of the subgroup in the basal layer cells). Figure 7 b is a graph comparing the percentage of IGFBP3 and ASCL2 positive cells in this subset across age groups in single-cell transcriptome data. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0031] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0032] Unless otherwise specified, the raw materials and reagents used in the examples are all commercially available.

[0033] In the embodiments of this application, the human skin epidermal basal keratinocyte subpopulation described refers to the subpopulation with lower expression scores of cell cycle-related genes (including S phase gene set and G2M phase gene set) and / or higher expression of COL17A1 and KRT15 compared to the other cells in the epidermal basal layer of the same sample. We call this a keratinocyte subpopulation with basal cell characteristics, specifically the Basal_IGFBP3 subpopulation.

[0034] Five basal subpopulations with distinct transcriptional characteristics exist in the human epidermis, which we have named Basal_IGFBP3, Basal-II, Basal-III, Basal-IV, and Basal-V based on their characteristic genes. Before identifying the basal keratinocyte subpopulations of the human epidermis using the method of this invention, we first need to identify the basal keratinocyte subpopulation to be identified as the Basal_IGFBP3 subpopulation. Specifically, we define the Basal_IGFBP3 subpopulation through the following Example 1.

[0035] Example 1: Delineation of the Basal_IGFBP3 subgroup The specific definition methods include the following S101~S104.

[0036] S101. Collect samples and prepare single-cell suspensions: Discarded human skin tissue from clinical surgeries was collected and divided into two groups according to donor age: a juvenile group and an old group. Each skin sample was soaked overnight at 4°C in Dispase II (2.4 U / mL) to separate the epidermis from the dermis. Epidermal slices were digested with 0.25% trypsin-EDTA at 37°C for 20–30 minutes. Digestion was terminated by adding DMEM containing 10% fetal bovine serum. The samples were filtered through a 40 μm filter, centrifuged (300×g, 5 min), and resuspended in PBS containing 0.04% BSA to obtain a single-cell suspension of epidermal cells with trypan blue viability ≥85%.

[0037] S102, single-cell transcriptome sequencing and basal cell re-clustering Library preparation and sequencing were performed on the single-cell suspensions of the samples prepared in S101 using the 10× Genomics Chromium platform. The raw sequencing data were aligned to the human reference genome (GRCh38) using Cell Ranger software (10× Genomics) and UMI counting was performed. After filtering out low-quality cells (number of genes <200 or mitochondrial gene ratio >20%), the quality control chart of the corresponding single-cell transcriptome data of human skin epidermal cells is shown below. Figure 1 As shown. Among them, Figure 1'a' is a scatter plot with the percentage of non-mitochondrial gene counts on the horizontal axis and the base-2 logarithm of the number of genes detected per cell plus 1 on the vertical axis. Each point in the plot represents a cell, the color indicates the density of cell distribution, and the two dashed lines are reference boundaries for screening out extreme values. Figure 1 b represents another way of plotting the same quality control relationship. In the graph, the scatter points represent cell-by-cell values, the curves represent two-dimensional density contour lines, and the two dashed lines have the same meaning. Figure 1 a; Figure 1 c is the distribution chart of quality control indicators for each sample. The vertical axis is the sample number, and from top to bottom are the proportion of mitochondrial genes, the proportion of ribosome genes, the proportion of heat shock protein genes, the number of detected genes and the count of detected transcripts. Each curve represents the density distribution of a sample, and the dotted line is the filtering threshold of the corresponding indicator. Figure 1 d is a histogram of the density distribution of mitochondrial gene proportions in all cells, with the horizontal axis representing the proportion of mitochondrial genes and the vertical axis representing density.

[0038] Then, using the Seurat package (R language), normalization, selection of highly variable genes (first 2000), principal component analysis (PCA) were performed. Harmony algorithm was used for batch correction between samples, followed by UMAP dimensionality reduction and Louvain clustering to obtain the UMAP dimensionality reduction map of all epidermal cells, as shown below. Figure 2 As shown in a, Figure 2 In diagram a, each dot represents a cell, and different colors represent different cell types. Specifically, number 1 represents basal cells, number 2 represents spinous cells, and number 3 represents granular cells.

[0039] Based on the high expression of KRT5, KRT14, TP63, COL17A1, and ITGA6, and the absence or low expression of KRT1 and KRT10, the basal keratinocyte population was defined.

[0040] The aforementioned basal keratinocytes were individually extracted and subjected to re-selection of hypervariable genes, PCA, Harmony correction, and Louvain clustering, resulting in four basal subpopulations with distinct transcriptional characteristics. The UMAP dimensionality reduction map of the re-clustered basal keratinocytes is shown below. Figure 2 As shown in b. Figure 2 In section b, five basal subpopulations are labeled. Among them, Basal-IGFBP3 is the human skin epidermal basal keratinocyte subpopulation described in this invention, and the other four basal subpopulations are named Basal-II, Basal-III, Basal-IV and Basal-V, respectively.

[0041] UMAP projection diagram of the expression levels of four genes in basal keratinocytes as shown below Figure 2 As shown in c, it includes IGFBP3, FGFR3, IL1R2, and COL17A1.

[0042] S103, Analysis of marker gene expression patterns The FindAllMarkers function was used to calculate the differentially expressed genes of each basal subpopulation relative to the other basal subpopulations, and a dot plot was drawn. The results are as follows: Figure 3 As shown, Figure 3 In the graph, the horizontal axis represents genes, and the vertical axis represents basal subpopulations. The size of the dot represents the percentage of cells expressing that gene in that subpopulation, and the intensity of the dot's color represents the average expression level. Figure 3 The results showed that the percentage of cells expressing IGFBP3 and the average expression level in the Basal_IGFBP3 subpopulation were significantly higher than those in the other three basal subpopulations; ASCL2 was also highly expressed in the Basal_IGFBP3 subpopulation; while EMP2 was relatively highly expressed in the other basal subpopulations such as Basal_III, and relatively lowly expressed in the Basal_IGFBP3 subpopulation.

[0043] It should be noted that examining any single biomarker alone is insufficient to define this subpopulation within the basal layer: IGFBP3 is also expressed in a certain proportion of cells in other basal subpopulations, and ASCL2 expression is not limited to the Basal_IGFBP3 subpopulation; the subpopulation specificity of either biomarker alone is limited. Only by using the co-expression of IGFBP3 and ASCL2 as a combined criterion can the Basal_IGFBP3 subpopulation be specifically defined within the basal layer.

[0044] S104, Definition of Basal Cell Characteristics Gene set scoring was performed on the Basal_IGFBP3 subset. Compared to other cells in the epidermal basal layer, this subset had lower cell cycle-related gene expression scores (S phase and G2M phase scores), exhibiting slow cycle and quiescent transcriptional characteristics. The S phase and G2M phase scoring criteria for the cell cycle-related gene set were performed using the CellCycleScoring function of the Seurat software package. The S phase and G2M phase gene sets were derived from the standard gene set built into the Seurat software package (cc.genes, derived from the 43 S phase genes reported by Tirosh et al. in 2016). Because of the 54 genes in the G2M phase, the S phase gene set includes MCM5, PCNA, TYMS, FEN1, MCM2, MCM4, RRM1, UNG, GINS2, MCM6, CDCA7, DTL, PRIM1, UHRF1, CENPU, HELLS, RFC2, RPA2, NASP, RAD51AP1, GMNN, WDR76, SLBP, CCNE2, UBR7, POLD3, MSH2, ATAD2, RAD51, RRM2, CDC45, CDC6, EX O1, TIPIN, DSCC1, BLM, CASP8AP2, USP1, CLSPN, POLA1, CHAF1B, BRIP1, and E2F8; the G2M phase gene set includes HMGB2, CDK1, NUSAP1, UBE2C, BIRC5, TPX2, TOP2A, NDC80, CKS2, NUF2, CKS1B, MKI67, TMPO, CENPF, TACC3, PIMREG, SMC4, CCNB2, CKAP2L, CKAP2, and AURKB. BUB1, KIF11, ANP32E, TUBB4B, GTSE1, KIF20B, HJURP, CDCA3, JPT1, CDC20, TTK, CDC25C, KIF2C, RANGAP1, NCAPD2, DLGAP5, CDCA2, CDCA8, ECT2, KIF23, HMMR, AURKA, PSRC1, ANLN, LBR, CKAP5, CENPE, CTCF, NEK2, G2E3, GAS2L3, CBX5, and CENPA). The score is a module score, which is the average normalized expression level of each gene within the gene set, minus the average expression level of the control gene set randomly selected by binning according to expression level.

[0045] It is understood that, in the embodiments of this application, the judgment criterion for "low cell cycle-related gene expression score" is as follows: using the remaining cells in the epidermal basal layer of the same sample as controls, the S phase score and G2M phase score of the subpopulation cells are compared with the corresponding scores of the control cells, respectively. A two-sided Wilcoxon rank-sum test is used. When the median score of the subpopulation is lower than that of the control cells and the P value of the test is less than 0.05, the cell cycle-related gene expression score of the subpopulation is determined to be low. The module score is a relative value relative to the control gene set, and its absolute value itself is not used as a judgment basis (the specific value is subject to the actual measurement results).

[0046] Meanwhile, COL17A1 and KRT15 were highly expressed, and basal stem-related genes such as ITGA6 and ITGB1 were enriched. Furthermore, the aging-related scores (CDKN2A, CDKN1A expression, and LMNB1 loss) of this subpopulation were not elevated, suggesting that its high IGFBP3 expression state cannot be explained by cellular senescence. The aging-related gene set was scored using the AddModuleScore function of the Seurat software package, with CDKN2A and CDKN1A as the core components, and the scoring algorithm was the same as above. LMNB1 expression was also examined separately, with decreased LMNB1 expression used as a negative indicator of aging.

[0047] It should be noted that, in the embodiments of this application, the criteria for judging high expression of COL17A1 and KRT15 are as follows: In single-cell transcriptome data, using the remaining cells of the epidermal basal layer in the same sample as controls, when the median of the normalized expression levels of COL17A1 and KRT15 in the subpopulation is higher than that of the control cells, and the P-value of the two-sided Wilcoxon rank-sum test is less than 0.05, it is judged as high expression; in the case of in situ detection of tissue sections, the detection signal intensity of epidermal basal layer cells in the same section is used as a reference distribution and robustly normalized as described in Example 4. When the robust z-score of the cell is greater than or equal to the threshold z0, the corresponding marker expression of the cell is judged to be high. The judgment criteria are consistent with the positive judgment of IGFBP3 and ASCL2 (the specific values ​​are subject to the actual measurement results).

[0048] The above results indicate that the Basal_IGFBP3 subpopulation is a keratinocyte subpopulation with basal cell characteristics within the basal layer. Based on this, the present invention defines the basal cell characteristics as "lower cell cycle-related gene expression scores and / or higher expression of COL17A1 and KRT15".

[0049] Example 2: This example describes the process of in situ immunofluorescence identification of the Basal_IGFBP3 subset, specifically including the following S201~S203.

[0050] S201. Prepare human skin tissue section samples, including paraffin sections and frozen sections.

[0051] (1) Preparation of paraffin sections: Fresh human skin tissue excised surgically was fixed with 4% paraformaldehyde (PFA) at 4°C for 24 hours, dehydrated with a gradient of ethanol (70%→80%→95%→100%), cleared with xylene, and then embedded in paraffin to prepare continuous paraffin sections with a thickness of 4–6 μm. After dewaxing with xylene and rehydration with a gradient of ethanol, the sections were heat-retarded with sodium citrate buffer (pH 6.0) at 95°C for 20 minutes to remove antigens, cooled naturally to room temperature, and washed three times with PBS for later use.

[0052] (2) Preparation of frozen sections: Fresh human skin tissue was directly embedded in OCT, flash-frozen in liquid nitrogen and stored at -80℃; 8-10 μm sections were cut with a cryostat, fixed with acetone for 10 minutes after pre-cooling, and washed three times with PBS for later use.

[0053] It should be noted that when slicing, the junction between the epidermis and dermis (basement membrane) should be perpendicular to the cut surface to ensure that the complete layer structure of the epidermis can be clearly distinguished within the same field of view. This is the premise for in-situ interpretation of the basement layer in this invention.

[0054] S202, immunofluorescence staining.

[0055] The slides prepared by S201 were blocked with PBS containing 5% goat serum and 0.3% Triton X-100 at room temperature for 1 hour. Rabbit anti-human IGFBP3 antibody (1:200) and mouse anti-human ASCL2 antibody (1:100) were added to the samples simultaneously and incubated overnight (12-16 hours) at 4°C. After washing with PBS, double staining was performed using fluorescently labeled secondary antibodies. Specifically, the secondary antibodies were PE-labeled goat anti-rabbit IgG (1:300 dilution, used to detect IGFBP3, showing red / orange fluorescence) and FITC-labeled goat anti-mouse IgG (1:300 dilution, used to detect ASCL2, showing green fluorescence), and incubated at room temperature in the dark for 1 hour. After washing with PBS, the nuclei were stained with DAPI (1 μg / mL) for 5 minutes, mounted with an anti-quenching agent, and images were acquired under a fluorescence microscope or laser confocal microscope. ≥5 random fields of view were acquired for each sample, and each field of view contained ≥100 basal cells.

[0056] A control group was also set up, which included: (i) Isotype control: The primary antibody is replaced with an equal concentration of non-immune IgG of the same species to determine the background signal; (ii) Single staining control (only one primary antibody and its corresponding secondary antibody are added, and no primary antibody is added to the other channel), used to eliminate spectral crosstalk between the two fluorescence channels and non-specific binding of the secondary antibody; (iii) Keratinocytes with IGFBP3 or ASCL2 knocked down by siRNA were used as antibody-specific controls to verify that the staining signal was significantly reduced as the target gene expression was downregulated.

[0057] S203, Result Identification.

[0058] KRT5 positivity was used to define keratinocyte lineages, and TP63 nuclear positivity was used to further confirm undifferentiated cells with preserved proliferative capacity; based on this, a monolayer of KRT5 cells arranged adjacent to the basement membrane was used... + (and / or TP63) + The cells are defined as epidermal basal layer cells, forming cell set B for subsequent interpretation. The location of the basement membrane is determined morphologically (epidermal-dermal junction); if necessary, staining for type IV collagen or laminin 332 can be added to assist in delineating the basement membrane.

[0059] Image results acquired under fluorescence microscopy or laser confocal microscopy, as shown below Figure 4 As shown, Figure 4 In the image, IGFBP3 is shown in green, TP63 and ASCL2 are shown in red, cell nuclei are shown in blue, and double-positive cells in the merged image are shown in yellow.

[0060] in, Figure 4 Image a shows the results of dual immunofluorescence staining with IGFBP3 and TP63. The left image is a low-magnification panoramic image of a representative field of view, and the four cells on the right are magnified images of local areas in that field of view, namely, a single-channel image of IGFBP3, a single-channel image of TP63, a DAPI nuclear staining image, and a combined image of IGFBP3 and TP63, in that order.

[0061] Figure 4 b shows the results of dual immunofluorescence staining for IGFBP3 and ASCL2. The arrangement of the four cells in the left and right images is the same. Figure 4 a. The four cells on the right are, in order, a single-channel image of IGFBP3, a single-channel image of ASCL2, a DAPI nucleostained image, and a merged image of IGFBP3 and ASCL2.

[0062] pass Figure 4 b shows that in the basal layer of the epidermis of human skin tissue sections, some cells are simultaneously positive for IGFBP3 (green, cytoplasm and juxtamembranous region) and ASCL2 (red, nucleus), with cells co-localized to both IGFBP3 and ASCL2 being scattered throughout the basal layer.

[0063] pass Figure 4Magnified localization of b revealed that these double-positive cells were located in a monolayer immediately adjacent to the basement membrane, and were positive for both ASCL2 and TP63 nuclei, consistent with the morphological and lineage characteristics of basal keratinocytes. While ASCL2 signaling was detectable in cells of the upper basal layer (spike layer and above), co-localization with IGFBP3 was lacking. Therefore, the Basal_IGFBP3 subset was identified in situ on sections preserving tissue structure.

[0064] It is understood that in this embodiment, no enzymatic hydrolysis of the epidermis, no preparation of single-cell suspensions, and no live cell sorting were performed throughout the entire process, thus the spatial position of the cells on the basement membrane was completely preserved.

[0065] Example 3: This example describes a specific method for determining the double positivity of IGFBP3 and ASCL2, including the following S301~S303.

[0066] S301, Cell segmentation and signal extraction.

[0067] The multi-channel images acquired in Example 2 were imported into QuPath software. Cell nuclei were segmented using the DAPI channel, and the nuclei were extended outwards by 3 μm to approximate the cytoplasmic region. Basal cell set B was defined as described in Example 2. The average fluorescence intensity of each marker was extracted from each cell i in B: IGFBP3 was the average intensity I(i, IGFBP3) in the cytoplasm and juxtamembrane region; ASCL2 was the average intensity I(i, ASCL2) in the nucleus; and EMP2 was the average intensity I(i, EMP2) in the cell membrane and juxtamembrane region. The average background intensity of isotype control sections under the same acquisition parameters was subtracted from the intensity of each channel.

[0068] S302, robust z-score calculation for each cell.

[0069] For each marker m, using the intensity values ​​of the basal cell set B in the same slice as a reference distribution, calculate the median_B(I_m) and the absolute median difference MAD_B(I_m), and calculate the robust z-score for each cell using the following formula: z(i, m) = [I(i, m) median_B(I_m)] / [1.4826 × MAD_B(I_m)] In the formula, the coefficient 1.4826 is used to ensure that the absolute median deviation is consistent with the standard deviation under a normal distribution. It is understood that in the embodiments of this application, the median and absolute median deviation are used instead of the mean and standard deviation to ensure that the reference distribution is not affected by a few extremely high signal cells; using basal cells within the same slice as a reference ensures that the normalization result is not affected by factors such as staining batch, antibody batch, slice thickness, microscope excitation power and gain.

[0070] Positive results for S303, IGFBP3, and ASCL2.

[0071] Using z0 as the first determination threshold, when z(i, IGFBP3) ≥ z0 and z(i, ASCL2) ≥ z0, cell i is determined to be double positive for IGFBP3 and ASCL2, that is, it belongs to the Basal_IGFBP3 subgroup mentioned above.

[0072] Specifically, the proportion P of the Basal_IGFBP3 subset was first calculated. Then, z0 was set to 0.8, 1.0, 1.2, 1.5, 2.0, and 2.5 respectively. The above determination was repeated for the same batch of slides. The proportion of the Basal_IGFBP3 subset in basal cells as defined by the single-cell transcriptome in Example 1 was used as a reference. The consistency between the proportion P obtained at each z0 value and the reference value was compared. At the same time, the distinguishability of the double-positive cell population and the main distribution at each z0 value was examined.

[0073] The proportion P of the Basal_IGFBP3 subset in basal cells is calculated using the following formula: P = N(IGFBP3 + ASCL2 + ) / N(B) × 100% In the formula, N(B) is the total number of cells in the basal layer of the slice, and each sample should satisfy N(B) ≥ 500.

[0074] The results of the above repeated determinations show that, within the range of z0 = 0.8 to 2.5, the identified double-positive cells are all located in the right tail of the reference distribution and can be clearly distinguished from the main distribution. The obtained proportion P shows a consistent age-group variation trend with the reference value, meaning that the technical effects of the present invention can be achieved within this range. Among them, the consistency between the proportion P obtained in the z0 = 0.8 to 1.5 range and the reference value is the highest, and the consistency is the best when z0 = 1.0 (the specific values ​​are subject to the actual measurement results). When z0 is below 0.8, a large number of moderate-intensity cells in the main distribution are included, and the subpopulation specificity decreases; when z0 is above 2.5, only a very small number of cells with the strongest signal are counted, and the statistical fluctuation of the proportion P increases.

[0075] To ensure the robustness of the above determination method, we took consecutive slices from the same donor and had the P-value determined by three independent staining batches and two independent interpreters using the method described above. The results showed that the inter-batch coefficient of variation was relatively large when using the absolute grayscale threshold interpretation, while the inter-batch coefficient of variation was significantly reduced and the consistency among interpreters was significantly improved when using the robust normalization interpretation of this application (specific values ​​are subject to actual measurement results). These results indicate that the quantification method described in this application makes the subpopulation proportions comparable across different samples and batches.

[0076] Therefore, we use z0 = 1.0 as the first determination threshold to determine the cells. When z(i, IGFBP3) ≥ 1.0 and z(i, ASCL2) ≥ 1.0, cell i is determined to be double positive for IGFBP3 and ASCL2 and belongs to the Basal_IGFBP3 subgroup mentioned above.

[0077] The judgment result is as follows Figure 5 As shown. Among them, Figure 5 a is a histogram of the frequency distribution of IGFBP3 signal intensity in all basal cells of the same slice. In the figure, the solid line m is the median, the dashed line T is the positive threshold calculated by the absolute median difference, and the distance between the two is z0σ. Figure 5 b is a histogram of the frequency distribution of ASCL2 signal intensity in all basal cells of the same slice, labeled in the same way. Figure 5 a; Figure 5 c is a scatter plot with the IGFBP3 robust z-score on the horizontal axis and the ASCL2 robust z-score on the vertical axis. The two dashed lines represent the threshold z0, and the solid dots in the upper right quadrant represent double-positive cells.

[0078] pass Figure 5 a and Figure 5 b shows that the IGFBP3 and ASCL2 signal intensities in the basal layer cells of the same slice are both right-skewed. Thresholds set using the median and absolute median difference clearly distinguish the highly expressed cells in the right tail from the main distribution. Figure 5 c shows that when a scatter plot is made using the robust z-scores of the two markers, the double-positive cells in the upper right quadrant constitute a distinguishable cell population.

[0079] Example 4: This example describes a method for excluding other basal subpopulations by low EMP2 expression.

[0080] Based on the above embodiment 1 Figure 3 The results showed that EMP2 was relatively highly expressed in other basal subpopulations such as Basal_III, but relatively lowly expressed in the Basal_IGFBP3 subpopulation. Based on this, we further considered using low EMP2 expression to exclude other basal subpopulations.

[0081] One additional round of EMP2 staining (rabbit anti-human EMP2 antibody, 1:200, incubated overnight at 4°C, developed with OPAL 480, magenta) is added to the multiplex immunofluorescence system of Example 2, and the robust z-score of EMP2 for each cell in the basal layer is calculated according to the method described in Example 3.

[0082] The results are shown in Figure 6 . In the figures, Figure 6 a is a schematic diagram of the spatial distribution of EMP2-expressing cells and IGFBP3 and ASCL2 double-positive cells in the basal layer, wherein the solid cells are IGFBP3 and ASCL2 double-positive cells, the hatched cells are EMP2-expressing cells, the hollow cells are the remaining cells in the basal layer, and the thick solid line below is the basement membrane. Figure 6 b is a comparison diagram of the robust z-score of EMP2 between the double-positive cells and the remaining cells in the basal layer, wherein the box represents the interquartile range, the horizontal line inside the box represents the median, the whiskers represent the range of 1.5 times the interquartile range, the scattered points represent the per-cell values, and the dashed line represents the second determination threshold z0′.

[0083] It is shown by Figure 6 a that the EMP2 strongly positive cells and the IGFBP3 / ASCL2 double-positive cells in the basal layer are substantially non-overlapping in space; it is shown by Figure 6 b that the IGFBP3 + ASCL2 + cells have a significantly lower robust z-score of EMP2 than the remaining cells in the basal layer.

[0084] Therefore, in addition to the criterion for IGFBP3 and ASCL2 double positivity, the present invention uses z0′ as the second determination threshold, and adds low EMP2 expression as an orthogonal exclusion condition: when a cell satisfies z(i, IGFBP3) ≥ z0, z(i, ASCL2) ≥ z0 and z(i, EMP2) < z0′, it is determined to belong to the said subpopulation, wherein z0′ is taken from -0.5 to 0.5, preferably 0. After adding this condition, the consistency between the identified subpopulation and the Basal_IGFBP3 subpopulation defined by single-cell transcriptome in Example 1 is further improved.

[0085] Example 5: This example describes one of the marker combinations for identifying human skin epidermal basal keratinocyte subpopulations, comprising: IGFBP3 and ASCL2.

[0086] Based on the marker combination of this example, correspondingly, a kit 1 for identifying human skin epidermal basal keratinocyte subpopulations is designed, and the kit 1 comprises: a reagent for specifically detecting IGFBP3 and a reagent for specifically detecting ASCL2.

[0087] The reagents for specifically detecting IGFBP3 are anti-human IGFBP3 antibodies or in situ hybridization probes for detecting IGFBP3 mRNA; the reagents for specifically detecting ASCL2 are anti-human ASCL2 antibodies or in situ hybridization probes for detecting ASCL2 mRNA.

[0088] Understandably, the reagents included with the kit also include: fluorescently labeled secondary antibody or tyramine signal amplification and colorimetric system, DAPI nuclear dye, antigen retrieval solution, blocking solution, anti-quenching mounting medium, and isotype control IgG.

[0089] All of the above-mentioned detection reagents have been specifically disclosed in this invention and their specificity has been verified. For example, the antibodies mentioned above can be the rabbit anti-human IGFBP3 antibody, rabbit anti-human ASCL2 antibody, mouse anti-human KRT5 antibody, rabbit anti-human TP63 antibody, and rabbit anti-human EMP2 antibody (including the corresponding colorimetric system and working dilution ratio) described in Example 2. Their specificity for the subgroups has been confirmed by the single-cell transcriptome analysis in Example 1, the multiplex immunofluorescence in Example 2, and the orthogonal exclusion verification in Example 4.

[0090] Example 6: This example describes the second combination of markers for identifying human epidermal basal keratinocyte subsets, including: IGFBP3, ASCL2 and KRT5.

[0091] Based on the biomarker combination of this embodiment, a kit 2 for identifying human skin epidermal basal keratinocyte subsets is designed accordingly. The kit 2, based on the kit 1 described in Example 5 above, further includes: a reagent for specifically detecting KRT5. Among them, the reagents for specifically detecting KRT5 mentioned above are anti-human KRT5 antibodies or in situ hybridization probes for detecting KRT5 mRNA.

[0092] Example 7: This example describes the third set of markers for identifying human epidermal basal keratinocyte subsets, including: IGFBP3, ASCL2 and TP63.

[0093] Based on the biomarker combination of this embodiment, a kit 3 for identifying human skin epidermal basal keratinocyte subpopulations is designed accordingly. The kit 3, based on the kit 1 described in Example 5 above, further includes: a reagent for specifically detecting TP63. Among them, the reagents for specifically detecting TP63 mentioned above are anti-human TP63 antibodies or in situ hybridization probes for detecting TP63 mRNA.

[0094] Example 8: This example describes the fourth set of markers for identifying human epidermal basal keratinocyte subsets, including: IGFBP3, ASCL2, KRT5 and TP63.

[0095] Based on the biomarker combination of this embodiment, a kit 4 for identifying human skin epidermal basal keratinocyte subsets is designed accordingly. The kit 4, based on the kit 2 described in Example 6 above, further includes: a reagent for specifically detecting TP63. Among them, the reagents for specifically detecting TP63 mentioned above are anti-human TP63 antibodies or in situ hybridization probes for detecting TP63 mRNA.

[0096] Example 9: This example describes the fifth set of markers for identifying human epidermal basal keratinocyte subsets, including: IGFBP3, ASCL2, KRT5, TP63 and EMP2.

[0097] Based on the biomarker combination of this embodiment, a kit 5 for identifying human skin epidermal basal keratinocyte subsets is designed accordingly. The kit 5, based on the kit 4 described in Example 8 above, further includes: a reagent for specifically detecting EMP2. Among them, the reagents for specifically detecting EMP2 mentioned above are anti-human EMP2 antibodies or in situ hybridization probes for detecting EMP2 mRNA.

[0098] In practical applications, the method for identifying the Basal_IGFBP3 subgroup of the human epidermal basal layer using any of the kits described in Examples 5 to 9 above is as follows: Step (1): Take a section of isolated human skin tissue; Step (2): For kit 1, IGFBP3 and ASCL2 are detected in situ using the reagents in kit 1. For kits 2, 3, and 4, KRT5, TP63, or KRT5+TP63 can be detected simultaneously to anchor the basal layer. For kit 5, EMP2 is further detected to exclude other basal subpopulations. Step (3): Using the basal layer cells of the same slice as a reference distribution, perform robust normalization, and determine the positive result according to the first determination threshold z0 described in Example 3 and the second determination threshold z0′ described in Example 4. Step (4): For Kit 1, cells in the basal layer that are positive for both IGFBP3 and ASCL2 are identified as the human epidermal basal keratinocyte subpopulation. For Kits 2, 3, and 4, based on the criteria in Kit 1, cells in the basal layer that are positive for KRT5, TP63, or KRT5+TP63 are identified as the human epidermal basal keratinocyte subpopulation. For Kit 5, based on the aforementioned criteria, cells in the basal layer that are positive for low expression of EMP2 are identified as the human epidermal basal keratinocyte subpopulation.

[0099] Example 10: This example describes a method for evaluating the aging degree of ex vivo human skin tissue samples for non-disease diagnostic purposes. Based on the kits described in Examples 5-9 above, it is determined whether the basal keratinocyte subpopulation in the ex vivo human skin tissue sample section is the Basal_IGFBP3 subpopulation. If so, the proportion P of the number of Basal_IGFBP3 subpopulation cells in the ex vivo human skin tissue sample section to the total number of epidermal basal cells in the ex vivo human skin tissue sample section is further calculated. The lower the proportion P, the higher the skin aging degree of the ex vivo human skin tissue sample.

[0100] Specifically, the above method includes the following S401 to S403.

[0101] S401. Take the isolated human skin tissue sample to be tested and prepare isolated human skin tissue sections according to the method described in Example 2 above; S402. Perform in situ identification according to the method described in Example 2 above, and determine whether the basal keratinocyte subpopulation in the isolated human skin tissue sample section is the Basal_IGFBP3 subpopulation. If so, calculate the proportion P of the Basal_IGFBP3 subpopulation to the epidermal basal layer cells in the isolated human skin tissue sample section according to the method described in Example 4. S403. Using the age-matched reference value P0 as a benchmark, wherein the age-matched reference value P0 is the proportion of ex vivo human skin tissue samples from the same anatomical site and known age group measured using the same method; the obtained proportion P is compared with the age-matched reference value P0. The lower the S404 and P values, the higher the degree of skin aging in the sample is considered. When P is significantly lower than the age-related reference value P0 (for example, when P0 is 30% and SD is 5%, P ≤ 20% is considered significantly lower), the degree of skin aging in the sample is considered to be higher than the level corresponding to its age.

[0102] It should be noted that, since the age-matched reference value P0 of the present invention is obtained by normalizing the internal reference distribution of the same sample, the age-matched reference values ​​P0 measured by different samples and different batches are comparable, and therefore can be used as an objective and quantifiable evaluation index of skin aging.

[0103] Below, we will further explain the above evaluation methods in more detail using actual clinical cases.

[0104] (1) Sampling: Ex vivo human skin tissue samples were taken from juvenile, adult and elderly donors (n≥5 cases in each group, taken from the same anatomical site). (2) Sample processing: Prepare each sample from step (1) above into ex vivo human skin tissue sections according to the method described in Example 2 above; (3) Perform KRT5 / TP63 / IGFBP3 / ASCL2 multiple immunofluorescence staining according to the methods described in Examples 2 to 4 above, and calculate the proportion P of the Basal_IGFBP3 subset in basal cells in each sample according to the method described in Example 3.

[0105] Furthermore, one-way ANOVA and Tukey's post-hoc test were used for inter-group comparisons. The results are as follows: Figure 7 As shown in a, for the juvenile group, the age-matched reference value P0 was 18.06; for the adult group, the age-matched reference value P0 was 13.45; and for the elderly group, the age-matched reference value P0 was 6.27. The age-matched reference value P0 showed a significant decreasing trend with the increase of the donor's age.

[0106] Furthermore, we performed differential expression analysis on the single-cell transcriptome data obtained in Example 1 within the Basal_IGFBP3 subset, categorized by age group. The results are as follows: Figure 7 As shown in b. In the Basal_IGFBP3 subset, IGFBP3 expression was significantly higher in the juvenile group compared to the non-juvenile group (avg_log2FC = 1.313, 88.8% of cells were positive in the juvenile group, 60.2% in the non-juvenile group, corrected P < 1 × 10⁻⁶). -300 ASCL2 expression was also significantly increased (avg_log2FC = 0.513, 74.9% in the juvenile group and 52.8% in the non-juvenile group, corrected P value = 2.52×10). -105 ).

[0107] The above results indicate that with increasing age, the proportion of cells in the Basal_IGFBP3 subset that simultaneously express IGFBP3 and ASCL2 decreases, consistent with the aforementioned... Figure 7 The in-situ quantitative results of a corroborate each other.

[0108] As a control, in the three subgroups Basal_II, Basal_III and Basal_IV, the percentage of IGFBP3-positive cells in the juvenile group was only 47.0%, 49.2% and 28.6%, respectively, all significantly lower than the 88.8% in the Basal_IGFBP3 subgroup, further indicating that the high expression state of IGFBP3 is specifically enriched in the Basal_IGFBP3 subgroup.

[0109] It should be noted that the evaluation methods described in this invention are only for cosmetic research and development, drug screening or in vitro scientific research, and the evaluation results should not be used as the basis for any clinical medical treatment or disease diagnosis.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A set of markers for identifying a subset of basal keratinocytes in human epidermis, characterized in that, The basal keratinocyte subpopulation is the Basal_IGFBP3 subpopulation, and the marker combination includes at least IGFBP3 and ASCL2.

2. The marker combination as described in claim 1, characterized in that, Also includes: KRT5 and / or TP63.

3. The marker combination as described in claim 2, characterized in that, Also includes: EMP2.

4. A kit for identifying subsets of basal keratinocytes in human epidermis, characterized in that, This includes reagents for the specific detection of IGFBP3 and reagents for the specific detection of ASCL2; The reagent for specifically detecting IGFBP3 is an anti-human IGFBP3 antibody or an in situ hybridization probe for detecting IGFBP3 mRNA; the reagent for specifically detecting ASCL2 is an anti-human ASCL2 antibody or an in situ hybridization probe for detecting ASCL2 mRNA.

5. The kit according to claim 4, characterized in that, It also includes reagents for the specific detection of KRT5 and / or TP63; The reagent for specifically detecting KRT5 is an anti-human KRT5 antibody or an in situ hybridization probe for detecting KRT5 mRNA; the reagent for specifically detecting TP63 is an anti-human TP63 antibody or an in situ hybridization probe for detecting TP63 mRNA.

6. The reagent kit as described in claim 5, characterized in that, It also includes reagents for the specific detection of EMP2; The reagents for specifically detecting EMP2 are human EMP2 antibodies or in situ hybridization probes for detecting EMP2 mRNA.

7. A method for identifying a subset of basal keratinocytes in the basal layer of human epidermis, characterized in that, The basal keratinocyte subset is the Basal_IGFBP3 subset, and the method includes: IGFBP3 and ASCL2 were detected in situ on sections of ex vivo human skin tissue samples. When the cells in the basal layer of the epidermis showed both IGFBP3 positivity and ASCL2 positivity, the cells were determined to belong to the Basal_IGFBP3 subpopulation.

8. The method as described in claim 7, characterized in that, The method further includes: in situ detection of KRT5 and / or TP63 on sections of ex vivo human skin tissue samples, and determining that the epidermal basal cell layer cells belong to the Basal_IGFBP3 subpopulation based on the presence of KRT5 positivity and / or TP63 positivity.

9. The method as described in claim 7, characterized in that, The method further includes: detecting EMP2 in situ on sections of ex vivo human skin tissue samples, and identifying cells with low EMP2 expression as the Basal_IGFBP3 subset.

10. The method as described in claim 7, characterized in that, The determination of IGFBP3 and ASCL2 positivity includes: The IGFBP3 and ASCL2 detection signal intensities of epidermal basal cells in the same sample slice were used to construct IGFBP3 and ASCL2 reference distributions, respectively. The corresponding detection signal intensities of each cell were robustly normalized using the median and median absolute deviation (MAD) of each reference distribution to obtain the robust z-scores of IGFBP3 and ASCL2 for that cell. When the robust z-scores of IGFBP3 and ASCL2 in a cell are both not less than the first judgment threshold z0, the cell is judged to be positive for IGFBP3 and ASCL2; where z0 is 0.8 to 2.

5.

11. The method as described in claim 10, characterized in that, The determination of low EMP2 expression includes: constructing an EMP2 reference distribution using the EMP2 detection signal intensity of epidermal basal cells in the same sample slice; and robustly standardizing the EMP2 detection signal intensity of each cell using the median and median absolute deviation (MAD) of the reference distribution to obtain the EMP2 robust z-score of the cell. When the EMP2 robustness z-score of a cell is less than the second threshold z0′, the cell is determined to have low EMP2 expression; where z0′ is -0.5 to 0.

5.

12. A method for evaluating the degree of aging of ex vivo human skin tissue samples for non-disease diagnostic purposes, characterized in that, Based on the biomarker combination according to any one of claims 1 to 3, the kit according to any one of claims 4 to 6, or the method according to any one of claims 7 to 11, identify whether the basal keratinocyte subpopulation in the isolated human skin tissue sample section is the Basal_IGFBP3 subpopulation. If so, further calculate the proportion P of the number of Basal_IGFBP3 subpopulation cells in the isolated human skin tissue sample section to the total number of epidermal basal cells in the isolated human skin tissue sample section. The lower the proportion P, the higher the degree of skin aging of the isolated human skin tissue sample.

13. The method as described in claim 12, characterized in that, It also includes comparing the ratio P with the age-matched reference value P0. When P is significantly lower than the age-matched reference value P0, it is determined that the skin aging degree of the sample is higher than the level corresponding to its age.

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