Osteosarcoma immune cell infiltration level assessment system and its construction method and application

Abstract

The present invention belongs to the field of biological information processing technology, and specifically relates to an evaluation system for the level of immune cell infiltration in osteosarcoma, and a construction method and application thereof. The evaluation system includes an immune score calculated based on 11 immune cells, and the 11 immune cells are: Th1, TFH, CD4memory activated, NK cells activated, MDSC, Macrophages M2, Macrophages M0, Immature B cells, Fibroblasts, Activated CD8 and activated B cell. The evaluation system scientifically screens 11 immune cells to construct an evaluation system for the level of immune cell infiltration in osteosarcoma, and the system includes an immune score calculated based on the 11 immune cells. The immune score can effectively reflect the overall content of immune cells in the osteosarcoma microenvironment, which will greatly help the selection and optimization of treatment plans for osteosarcoma patients.

Description

Technical Field

[0001] The present invention belongs to the technical field of biological information processing, and in particular relates to an evaluation system for the level of immune cell infiltration in osteosarcoma, and a construction method and application thereof. Background Art

[0002] Osteosarcoma is a primary malignant bone tumor that commonly occurs in children and adolescents. Modern treatments combining neoadjuvant chemotherapy with surgical resection have significantly improved patient outcomes, increasing survival rates from 20% to over 60% compared to amputation alone. However, survival rates have stagnated in recent years. To further improve prognosis, many studies are shifting their focus to immunotherapy.

[0003] Immune cells are a crucial component of the tumor microenvironment, serving as crucial mediators for the body's anti-tumor effects and forming a crucial foundation for immunotherapy. A lack of effector cells in the tumor microenvironment, or their exhaustion or functional impairment due to local immunosuppression, is a key factor contributing to poor anti-tumor efficacy. Immune cells, particularly T cells, interact with and kill tumor cells. The level of infiltration of these immune cells may be closely correlated with patient prognosis and is a crucial factor in determining the prognosis of osteosarcoma. Therefore, assessing the abundance of immune cells in the osteosarcoma microenvironment is crucial.

[0004] However, the evaluation of the immune cell content in osteosarcoma tissue is currently mainly judged by immunofluorescence, immunohistochemical staining and other methods. For example, the Chinese invention patent with application number 202110963181.8 discloses a staining method, kit and application. By combining P16INK4a immunocytochemical staining with Papanicolaou staining and improving and adjusting the staining steps, the P16INK4a immunocytochemical staining results and the morphological structure of the cells can be observed simultaneously on the same section, which increases the information content of a single slide, reduces the interference of background and non-specific staining, and improves the repeatability of the results and the accuracy of interpretation. However, the evaluation of immune cell content by chemical staining still has the problem of great subjectivity. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an evaluation system for accurately judging the level of immune cell infiltration in osteosarcoma, as well as a construction method and application thereof.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: an osteosarcoma immune cell infiltration level evaluation system, including an immune score calculated based on 11 types of immune cells, the 11 types of immune cells are: Th1, TFH, CD4 memory activated, NK cells activated, MDSC, Macrophages M2, Macrophages M0, Immature B cells, Fibroblasts, Activated CD8 and activated B cells.

[0007] Another technical solution adopted by the present invention is: a method for constructing the above-mentioned osteosarcoma immune cell infiltration level assessment system comprises the following steps:

[0008] S1: ssGSEA (Single sample gene set enrichment analysis) was performed on the immune cells in the osteosarcoma dataset. The results of ssGSEA were standardized to obtain the NES (normalized enrichment score) of each immune cell. Then, a univariate COX regression analysis was performed on each immune cell. The results of the univariate COX regression analysis were then meta-analyzed to obtain the HR of each immune cell. t Value and P t value, select P t Immune cells with a value < 0.05 were used for the construction of immune scores;

[0009] S2: Construct an immune scoring formula based on HRt value.

[0010] Another technical solution adopted by the present invention is: application of the above-mentioned osteosarcoma immune cell infiltration level assessment system in assessing the level of osteosarcoma immune cell infiltration.

[0011] The beneficial effects of the present invention are as follows: the osteosarcoma immune cell infiltration level assessment system of the present invention includes an immune score calculated from 11 types of immune cells: Th1, TFH, CD4 memory activated, NK cells activated, MDSC, Macrophages M2, Macrophages M0, Immature B cells, Fibroblasts, Activated CD8, and activated B cells. This immune score can better assess the degree of immune cell infiltration in osteosarcoma, effectively reflect the overall content of immune cells in the osteosarcoma microenvironment, and greatly help in the selection and optimization of treatment plans for osteosarcoma patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 Shown is the ssGSEA of immune cells in the TARGET dataset in Example 1 of the present invention;

[0013] Figure 2 Shown is the ssGSEA of immune cells in the GSE16091 dataset in Example 1 of the present invention;

[0014] Figure 3 Shown is the ssGSEA of immune cells in the GSE21257 dataset in Example 1 of the present invention;

[0015] Figure 4 Shown is a single factor COX regression analysis diagram of immune cells in the TARGET dataset in Example 1 of the present invention;

[0016] Figure 5 Shown is a single factor COX regression analysis diagram of immune cells in the GSE16091 dataset in Example 1 of the present invention;

[0017] Figure 6 Shown is a single factor COX regression analysis diagram of immune cells in the GSE21257 dataset in Example 1 of the present invention;

[0018] Figure 7 Shown is a Meta-analysis diagram of the single factor COX regression analysis results of immune cells with P≤0.05 in Example 1 of the present invention;

[0019] Figure 8 Shown is a Meta-analysis diagram of the single factor COX regression analysis results of immune cells with P>0.05 in Example 1 of the present invention;

[0020] Figure 9 Shown is a survival analysis diagram obtained using the optimal stage value of the immune score in Example 2 of the present invention;

[0021] Figure 10 Shown is a survival analysis diagram of the pan-cancer analysis in Example 4 of the present invention;

[0022] Figure 11 Shown Figure 10 Summary diagram of survival analysis results;

[0023] Figure 12 Shown is a graph showing the difference in the content of each immune cell between HIOS and LIOS in Example 5 of the present invention;

[0024] Figure 13 Shown is a graph showing the difference in overall immune cell content in Example 5 of the present invention;

[0025] Figure 14 Shown is a correlation analysis diagram between the overall content of immune cells and the immune score in Example 5 of the present invention. DETAILED DESCRIPTION

[0026] To illustrate the technical content, achieved objectives and effects of the present invention in detail, the following description is given in conjunction with the embodiments and accompanying drawings.

[0027] The osteosarcoma immune cell infiltration level assessment system includes an immune score calculated based on 11 immune cell types: Th1, TFH, CD4 memory activated, NK cells activated, MDSC, Macrophages M2, Macrophages M0, Immature B cells, Fibroblasts, Activated CD8, and activated B cells.

[0028] As can be seen from the above description, the beneficial effects of the present invention are: the present invention selects 11 types of immune cells that have an impact on the prognosis of osteosarcoma, and constructs an osteosarcoma immune cell infiltration level assessment system based on the immune scores calculated from the 11 immune cells. Through the immune score, the system can effectively reflect the overall content of immune cells in the osteosarcoma microenvironment, overcoming the problems of rough judgment and large subjective influence of existing assessment methods, and bringing great help to the selection and optimization of treatment plans for osteosarcoma patients.

[0029] Furthermore, the immune score is calculated by dividing the HR of 11 immune cells into t Immune cells with a (hazard ratio) value of <1 were classified into one type of cells, t Immune cells with a value greater than 1 were classified as type II cells, and the immune score of the sample was obtained by subtracting the sum of the NES (normalized enrichment score) of type I cells from the sum of the NES of type II immune cells.

[0030] From the above description, it can be seen that the first type of cells are cells that have a positive impact on patient survival, and the second type of cells are cells that have a negative impact on patient survival. The immune score of the present invention is positively correlated with the overall content of immune cells in osteosarcoma, with a correlation coefficient of 0.9. Therefore, the immune score of the present invention can well represent the overall infiltration level of immune cells in osteosarcoma.

[0031] Furthermore, HR t The calculation method of the value is as follows: the NES of immune cells is subjected to single factor COX regression analysis, and then the results of single factor COX regression analysis are subjected to meta-analysis (Meta-analysis) to obtain HR t value.

[0032] Furthermore, NES was calculated by performing ssGSEA (single sample gene enrichment analysis) on the immune cells, normalizing the results of ssGSEA, and obtaining the NES of each immune cell in each sample.

[0033] Furthermore, the P of 11 immune cells t All values ​​are <0.05.

[0034] From the above description, it can be seen that the evaluation system of the present invention is based on P t The algorithm is scientific and can more accurately reflect the infiltration level of immune cells in osteosarcoma.

[0035] Furthermore, P t The calculation method of the value is to perform single factor COX regression analysis on the NES of immune cells, and then perform meta-analysis on the results of single factor COX regression analysis to obtain P t value.

[0036] Another technical solution adopted by the present invention is: a method for constructing the above-mentioned osteosarcoma immune cell infiltration level assessment system comprises the following steps:

[0037] S1: Perform ssGSEA on the immune cells in the osteosarcoma dataset, standardize the results of ssGSEA to obtain the NES of each immune cell, and then perform univariate COX regression analysis on each immune cell. Then, perform meta-analysis on the results of univariate COX regression analysis and select P t Immune cells <0.05 were used to construct the immune score;

[0038] S2: According to HR t The immune score formula was constructed.

[0039] From the above description, it can be seen that the construction method is simple and efficient, and is conducive to popularization and use.

[0040] Furthermore, the specific construction method of the immune score formula is: t HR in immune cells <0.05 t Immune cells with a value <1 are classified as one type of cells, HR t Immune cells with a value greater than 1 were classified as Class II cells, and the immune scoring formula was constructed as shown in Equation 1;

[0041]

[0042] NES in Formula 1 i is the sum of NES of a type of cell, NES' i is the sum of the NESs of the two types of cells.

[0043] Another technical solution adopted by the present invention is: application of the above-mentioned osteosarcoma immune cell infiltration level assessment system in assessing the level of osteosarcoma immune cell infiltration.

[0044] Furthermore, the application also includes the step of dividing the samples into high immune infiltration osteosarcoma and low immune infiltration osteosarcoma according to the immune score. When the immune score of the sample is ≥ the optimal cutoff value, it is judged as high immune infiltration osteosarcoma (HIOS); when the immune score of the sample is < the optimal cutoff value, it is judged as low immune infiltration osteosarcoma (LIOS).

[0045] Furthermore, the optimal cutoff value was calculated by using the survminer R package to determine the optimal cutoff value of the immune score.

[0046] From the above description, it can be seen that the current method usually chooses the median as the limit to determine high immune infiltration osteosarcoma and low immune infiltration osteosarcoma. Compared with the existing technology, the present invention is more scientific and has a wider range of applications for determining high immune infiltration osteosarcoma and low immune infiltration osteosarcoma based on the optimal cutoff value of survival analysis.

[0047] The mRNA expression profiles and clinical information of osteosarcoma samples used in the following examples were obtained from the publicly available TARGET and GEO databases, ensuring reproducible results. The GEO datasets included were GSE16091 and GSE21257. The mRNA expression profiles and clinical information of ACC, CESC, GMB, HNSC, LGG, LUAD, LUSC, OV, SARC, SKCM, THCA, and UCEC used in the pan-cancer analysis in the examples were obtained from the TCGA database.

[0048] Embodiment 1 of the present invention is:

[0049] A method for constructing a system for evaluating the level of immune cell infiltration in osteosarcoma, comprising the following steps:

[0050] S1. Data processing:

[0051] Osteosarcoma mRNA expression profile IDs from the TARGET and TCGA databases were converted to gene names based on the human gene annotation file (version GRCh38.p13). Read counts and FPKM (fragments per kilobase per million) were converted to TPM (transcripts per kilobase million). Probe names from GSE16091 and GSE21257 were converted to gene names based on the corresponding platform annotation files for GEO data (GPL-96 and GPL10295). The raw (CEL) files from each GEO dataset were processed and normalized using the RMA algorithm in the R package affy.

[0052] S2. Selection of immune cells:

[0053] GSVA R package was used to perform ssGSEA on 50 immune cells in three osteosarcoma datasets: TARGET, GSE16091, and GSE21257. The analysis results are shown in Figures 1 to 3 , Figures 1 to 3 Each row represents a cell type, each column represents a sample, and the color of each small rectangle represents the immune cell content. The darker the color, the more cells there are. The results of ssGSEA were standardized to obtain the NES of 50 immune cells. The NES of each immune cell in the three osteosarcoma datasets was then subjected to univariate COX regression analysis. The analysis results are shown in Figure 2. Figures 4-6 ; Then the results of univariate COX regression analysis were meta-analyzed. The results are shown in Figures 7-8 , get the HR after each immune cell meta t Value and P t Value. Select P among 50 immune cells t Eleven immune cell types with a score < 0.05 were used to calculate the immune score. These 11 immune cell types were Th1, TFH, CD4 memory activated, NK cell activated, MDSC, Macrophages M2, Macrophages M0, Immature B cells, Fibroblasts, Activated CD8, and activated B cells.

[0054] S3. Construction of immune scoring formula:

[0055] HR in 11 immune cells t Immune cells with a value <1 are classified as one type of cells, HR tImmune cells with a value greater than 1 are classified as Class II cells, and an immune score formula is constructed as shown in Formula 1. The immune score is calculated according to the formula in Formula 1.

[0056]

[0057] NES in Formula 1 i NES is the sum of NES of a type of cells (Th1, TFH, CD4 memory activated, NK cells activated, MDSC, Macrophages M2, Macrophages M0, Immature B cells, Fibroblasts and activated Bcells), NES' i It is the sum of NES of type II cells (Activated CD8).

[0058] Embodiment 2 of the present invention is:

[0059] Application of immune scoring: The immune scoring method in Example 1 was used to determine high immune-infiltrating osteosarcoma and low immune-infiltrating osteosarcoma.

[0060] Based on Example 1, the survminer R package was used to determine the optimal cutoff value of the immune score in the two osteosarcoma datasets TARGET and GSE21257. Figure 9 The best cutoff values ​​were 0.69 and 5.14, respectively. Figure 9 It can be seen that when the immune score of the sample is higher than the optimal cutoff value, it can be judged as high immune infiltration osteosarcoma.

[0061] Embodiment 3 of the present invention is:

[0062] A method for evaluating the level of immune cell infiltration in osteosarcoma using an osteosarcoma immune cell infiltration level evaluation system comprises the following steps:

[0063] S1: 95 osteosarcoma samples were selected and ssGSEA was performed on 11 immune cell types in the osteosarcoma samples, including Th1, TFH, CD4 memory activated, activated NK cells, MDSC, Macrophages M2, Macrophages M0, Immature Bcells, Fibroblasts, Activated CD8, and activated B cells. The results of ssGSEA were standardized. The NES analysis results of the 11 immune cell types were substituted into Formula 1 in Example 1 to obtain the immune score of the osteosarcoma sample.

[0064] S2: The optimal cutoff value for the immune score of the osteosarcoma sample was determined using the survminer R package. A sample with an immune score ≥ the optimal cutoff value was classified as a highly immune-infiltrated osteosarcoma (HIOS); a sample with an immune score < the optimal cutoff value was classified as a low immune-infiltrated osteosarcoma (LIOS). The evaluation results of Example 3 are shown in Table 1.

[0065] Table 1

[0066]

[0067]

[0068] Embodiment 4 of the present invention is:

[0069] Pan-cancer analysis was used to verify the rationality of the evaluation system construction method of Example 1.

[0070] The immune scores of various solid tumors were calculated using the method of Example 1 and divided into high immune score group and low immune score group based on the optimal cutoff value of the immune score. The analysis results are shown in Figure 10 and Figure 11 .

[0071] In the survival analysis, the line on the top represents a better prognosis, so Figure 10 and 11 It can be shown that high immune scores are associated with better prognosis in most solid tumors (HR < 1). Grouping based on the optimal cutoff value of the immune score is not only applicable in osteosarcoma, but also in most tumors, and is reasonable.

[0072] Embodiment 5 of the present invention is:

[0073] A validation method for a system for evaluating immune cell infiltration levels in osteosarcoma:

[0074] (1) The accuracy of the immune score in Example 2 was verified using the differential analysis method.

[0075] 1. Kaplan-Meier survival estimate was used to analyze the difference in the content of each immune cell in high immune infiltration osteosarcoma (HIOS) and low immune infiltration osteosarcoma (LIOS). The analysis results are shown in Figure 12 .

[0076] Figure 12 This indicates that the infiltration degree of most immune cells in HIOS is higher than that in LIOS. Therefore, the immune score of the present invention can better reflect the infiltration degree of immune cells in osteosarcoma.

[0077] 2. Kruskal-Wallis Test was used to analyze the difference of the total content of immune cells. The results are shown in Figure 13 .

[0078] Figure 13 This showed that the overall content of immune cells in HIOS was also higher than that in LIOS, further confirming the accuracy of the immune score.

[0079] (2) Spearman correlation was used to analyze the correlation between the overall content of immune cells in osteosarcoma and the immune score of Example 3. The analysis results are shown in Figure 14 ,Depend on Figure 14 It can be seen that the correlation coefficient between the overall content of immune cells in osteosarcoma and the immune score reaches 0.9, and is positively correlated, which indicates that the immune score of the present invention can represent the overall infiltration level of immune cells in osteosarcoma.

[0080] In summary, the osteosarcoma immune cell infiltration level assessment system of the present invention is based on P t Eleven immune cells were screened to construct an evaluation system for the level of immune cell infiltration in osteosarcoma. t Immune cells with a (hazard ratio) value of <1 were classified into one type of cells, t Immune cells with a value greater than 1 are classified as Class II cells, and the sum of the NES (standardized enrichment score) of Class I cells minus the sum of the NES of Class II immune cells is used to obtain the immune score of the sample. These 11 types of immune cells include both immune cells that are unfavorable to the patient's prognosis and cells that are favorable to the patient's prognosis. The algorithm is scientific and can more accurately reflect the infiltration level of immune cells in osteosarcoma. The obtained immune score is positively correlated with the overall content of immune cells in osteosarcoma, with a correlation coefficient of 0.9, which can well represent the overall infiltration level of immune cells in osteosarcoma. Samples can also be divided into high immune infiltration osteosarcoma and low immune infiltration osteosarcoma based on the immune score. When the immune score of the sample is ≥ the optimal cutoff value, it is judged as high immune infiltration osteosarcoma, and when the immune score of the sample is < the optimal cutoff value, it is judged as low immune infiltration osteosarcoma, which is of great help in the selection and optimization of treatment plans for osteosarcoma patients.

[0081] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's description and drawings, directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An evaluation system for the level of immune cell infiltration in osteosarcoma, characterized in that: Including immune scores calculated based on 11 types of immune cells, including: Th1, TFH, CD4 memory activated, NK cells activated, MDSC, Macrophages M2, Macrophages M0, Immature B cells, Fibroblasts, Activated CD8 and activated B cells; The immune score is calculated by dividing the HR t Immune cells with a value less than 1 are classified as one type of cell, HR t Immune cells with a value greater than 1 are classified as type II cells, and the immune score of the sample is obtained by subtracting the sum of the NES of the type II immune cells from the sum of the NES of the type I cells.

2. The osteosarcoma immune cell infiltration level assessment system according to claim 1, characterized in that: The HR t The calculation method of the value is: perform univariate COX regression analysis on the NES of the immune cells, and then perform meta-analysis on the results of univariate COX regression analysis to obtain HR t value.

3. The osteosarcoma immune cell infiltration level assessment system according to claim 1, characterized in that: The NES is calculated by performing ssGSEA on the immune cells, and the results of the ssGSEA are standardized to obtain the NES of the immune cells.

4. The osteosarcoma immune cell infiltration level assessment system according to claim 1, characterized in that: 11 types of immune cells t All values ​​are <0.

05.

5. The osteosarcoma immune cell infiltration level assessment system according to claim 4, characterized in that: The P t The method for calculating the value is to perform a single factor COX regression analysis on the NES of the immune cells, and then perform a meta-analysis on the results of the single factor COX regression analysis to obtain the P t value.

6. The method for constructing the osteosarcoma immune cell infiltration level assessment system according to any one of claims 1 to 5, characterized in that: The following steps are involved: S1: ssGSEA was performed on the immune cells in the osteosarcoma dataset. The results of ssGSEA were standardized to obtain the NES of each immune cell. Then, a univariate COX regression analysis was performed on the NES of each immune cell. The results of the univariate COX regression analysis were then meta-analyzed to obtain the HR of each immune cell. t Value and P t value, select P t Immune cells with values ​​< 0.05 were used for the construction of immune scores; S2: According to HR t The immune score formula was constructed.

7. The method for constructing an osteosarcoma immune cell infiltration level assessment system according to claim 6, characterized in that: The specific construction method of the immune score formula is: t HR in immune cells <0.05 t Immune cells with a value of <1 are classified as one type of cells, HR t Immune cells with values ​​greater than 1 were classified as Class II cells, and the immune scoring formula was constructed as shown in Formula 1; NES in Formula 1 i is the sum of NES of a type of cell, NES i ′ is the sum of NES of the two types of cells.

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