Application of SMS in the diagnosis, prognosis, and prediction of response to immune checkpoint blockade therapy for liver cancer

Abstract

This invention belongs to the fields of disease diagnosis, prognosis, and molecular biology, specifically relating to the application of spermine synthase (SMS) in the diagnosis, prognosis, and prediction of response to immune checkpoint blockade (ICB) therapy in hepatocellular carcinoma (HCC). Research revealed that, compared to normal liver tissue, the expression of spermine synthase (SMS) is significantly upregulated in HCC; and high SMS expression is associated with poor clinicopathological features of prognosis. Furthermore, compared to the low SMS expression group, HCC patients in the high SMS expression group had significantly shorter overall survival, disease-specific survival, and progression-free survival, thus SMS overexpression predicts unfavorable outcomes. Simultaneously, SMS overexpression affects immune cell infiltration in HCC patients, leading to poor immune checkpoint blockade (ICB) responses and poor treatment efficacy for HCC. In conclusion, SMS can serve as a biomarker for the diagnosis and prediction of clinical outcomes in HCC, and also as a biomarker for predicting ICB treatment response.

Description

Technical Field

[0001] This invention belongs to the field of disease diagnosis, prognosis and molecular biology technology, specifically involving the application of SMS in the diagnosis, prognosis and prediction of response to immune checkpoint blockade therapy for liver cancer. Background Technology

[0002] The information disclosed in this background section is intended only to enhance understanding of the overall background of the invention and is not necessarily to be construed as an admission or in any way implying that such information constitutes prior art known to those skilled in the art.

[0003] Liver cancer is a serious health problem worldwide, with an estimated one million people diagnosed with it each year. Hepatocellular carcinoma (HCC) is the most common primary liver cancer, often occurring in the context of hepatitis virus infection, heavy alcohol consumption, or chronic liver disease caused by metabolic syndrome. Due to limitations in early diagnostic techniques, many HCC patients are diagnosed at an advanced stage at initial diagnosis, losing the opportunity for a cure through surgery or ablation. Currently, immune checkpoint blockade (ICB) is recognized as an encouraging treatment for patients with advanced HCC. Although ICBs targeting PD-1 and CTLA-4 have been approved for second-line treatment of HCC, the efficacy rate of ICB therapy is only 15%–30%. This is because the immunosuppressive tumor microenvironment is promoted by tumor cells, infiltrating stromal cells, and immune cells. Furthermore, the ability of liver cancer cells to evade immune surveillance and potentially resist ICB therapy may be due to the liver environment further enhancing immunosuppression. Currently, the lack of clinically available biomarkers to assess the response to ICB limits its efficacy and narrows the range of patients who can benefit from it. Therefore, there is an urgent need to develop effective biological targets to improve the efficacy of ICB in treating HCC.

[0004] The liver plays a central role in amino acid metabolism, and amino acids are essential for the biochemical processes necessary for cell proliferation. The concentrations of specific amino acids in the bodily fluids of patients with liver disease show significant changes. Recent studies have also demonstrated alterations in specific amino acids in patients diagnosed with hepatocellular carcinoma (HCC). Summary of the Invention

[0005] In response to the aforementioned existing technologies, the inventors, through long-term technical and practical exploration, have developed an application of spermine synthase (SMS) in the diagnosis, prognosis, and prediction of response to immune checkpoint blockade therapy (ICB) for liver cancer. This invention has discovered that SMS can serve as a prospective biomarker for the diagnosis and prediction of HCC clinical outcomes, and also as a potential biomarker for predicting ICB treatment response. Based on these research findings, this invention has been completed.

[0006] To achieve the above technical objectives, the present invention adopts the following technical solution:

[0007] The first aspect of this invention provides the use of substances for detecting the SMS gene and its expression products in the preparation of products for diagnosing, detecting, monitoring, and predicting the prognosis or response to immunotherapy in hepatocellular carcinoma (HCC). This invention has found that SMS expression is significantly upregulated in hepatocellular carcinoma (HCC) compared to normal liver tissue. Further assessment of the prognostic correlation between SMS and HCC revealed that, compared to the low-expression group, the high-expression group had a significantly higher proportion of patients with more severe primary tumor (T) stage, more severe lymph node (N) stage, more severe metastatic (M) stage, poorer pathological stage, poorer tumor status, and higher alpha-fetoprotein (AFP) levels, indicating that high SMS expression is associated with poor clinicopathological features. Furthermore, Kaplan-Meier survival analysis showed that, compared to the low-expression group, the high-expression group had significantly shorter overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS), thus SMS overexpression predicts unfavorable outcomes and is associated with disease progression in HCC patients. Meanwhile, SMS overexpression may affect immune cell infiltration in HCC patients, leading to poor ICB response and poor treatment efficacy for HCC.

[0008] A second aspect of the present invention provides a product for diagnosing, detecting, monitoring, and predicting the prognosis or immunotherapy response of liver cancer, comprising at least a substance for detecting the transcription of the SMS gene in a sample based on high-throughput sequencing and / or quantitative PCR and / or probe hybridization; or for detecting the expression of spermine synthase in a sample based on an immunoassay.

[0009] A third aspect of the present invention provides a detection reagent for detecting the SMS gene and its expression product.

[0010] In a fourth aspect, the present invention provides a detection kit comprising the detection reagents described above.

[0011] A fifth aspect of the present invention provides a system for diagnosing, detecting, monitoring, and predicting the prognosis or immunotherapy response of liver cancer, said system comprising at least:

[0012] The acquisition module is configured to acquire the expression levels of the SMS gene and its expression products in the subject samples.

[0013] The assessment module is configured to determine the subject's disease status based on the expression levels of biomarkers obtained by the acquisition module.

[0014] The output module is configured to output analysis results based on the judgment of the evaluation module.

[0015] A sixth aspect of the present invention provides the use of the above-mentioned SMS as a target in the preparation or screening of liver cancer drugs.

[0016] Compared with existing technical solutions, one or more of the above technical solutions have the following beneficial effects:

[0017] The above-mentioned technical approach revealed that spermine synthase (SMS), an important regulator of polyamine metabolism, is overexpressed in HCC, but is not related to hepatitis virus infection in HCC patients. Furthermore, it is associated with the prognosis of HCC patients. The approach also investigated the impact of SMS expression on immunotherapy response and analyzed its relationship with the degree of immune infiltration and immune checkpoint gene transcription. The approach evaluated SMS expression in the immune microenvironment using publicly available HCC single-cell transcriptome sequencing datasets. Finally, the approach analyzed differentially expressed genes (DEGs) among different SMS expression samples and co-expressed genes of SMS to explore the precise mechanism of SMS in HCC.

[0018] In summary, SMS can effectively differentiate the prognosis and immune characteristics of HCC and may serve as a potential target for improving ICB treatment. It is a good biomarker for the diagnosis, prognosis, and prediction of immunotherapy in HCC, and therefore has good practical application value. Attached Figure Description

[0019] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0020] Figure 1 This is a flowchart illustrating the process of determining the target gene in an embodiment of the present invention.

[0021] Figure 2 This invention illustrates the upregulation of SMS in hepatocellular carcinoma (HCC). (A) SMS mRNA expression in 371 HCC samples (371 from TCGA-LIHC) and 276 normal samples (50 from TCGA-LIHC dataset and 226 from GTEx dataset). (B) SMS mRNA expression in 50 HCC and paired normal specimens. (C) SMS protein expression based on CPTAC. (D) Comparison of SMS transcription levels between HCC tissues and paired normal tissues in HCCDB. *** p < 0.0001 vs. normal control.

[0022] Figure 3In this embodiment of the invention, differential SMS expression can serve as a prospective biomarker for poor prognosis and can be used to differentiate HCC samples. (A) OS, DSS, and PFS of SMS mRNA in an HCC cohort. (B) Time-dependent ROC analysis of SMS expression in HCC. (C) Forrest plots of univariate and multivariate Cox regression analyses in HCC. (D) Nomogram of SMS and other prognostic factors in HCC. (E) ROC curves evaluating the diagnostic efficacy of SMS in HCC.

[0023] Figure 4 This invention provides an example of ICB immunotherapy response prediction and immune infiltration analysis. (A) Differences in TIDE prediction scores among groups. (B) Expression of immune checkpoints among groups. (C) Immune response heatmaps among groups. (D) ssGSEA immune cell scores among groups in box plots. *p<0.05 * *p<0.01 * * *p<0.001 and display controls.

[0024] Figure 5 This is an example of SMS expression in the hepatocellular carcinoma tumor immune microenvironment. (A) UMAP cell type labeling (top panel), with SMS-positive and non-positive cells stained (bottom panel). (BD) Heatmap of SMS gene expression positivity rates in various immune cell subsets of GSE98638 (B), GSE125449 (C), and GSE140228 (D).

[0025] Figure 6 Functional analysis of DEGs in HCC patients with different SMS levels in this embodiment of the invention. (A) Expression of SMS in HCC patients with or without hepatitis virus infection and normal liver tissue (left, hepatitis B virus; right, hepatitis C virus). (B) Heatmap comparing mRNA in HCC samples with normal samples. (C) Volcano plot of gene expression profile data. (D) Analysis of upregulated and downregulated genes in GO terms and KEGG pathways. (E) GSEA of SMS high and low expression clusters. (F) ssGSEA scores of 19 cancer-related functional pathways in each group. *p<0.05 * *p<0.01 * * *p<0.001 * * * * p <0.0001 vs. control.

[0026] Figure 7 These are genes co-expressed with SMS in HCC in this embodiment of the invention. (A) Genes co-expressed with SMS in HCC. (B) Co-expressed genes co-transcribed with SMS in HCC. (C) Analysis of GO terminology and KEGG pathways of genes co-expressed with SMS. Detailed Implementation

[0027] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0028] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0029] This invention reveals that SMS expression is significantly upregulated in hepatocellular carcinoma (HCC) compared to normal liver tissue. Further assessment of the prognostic correlation between SMS and HCC showed that, compared to the low-expression group, the high-expression group had a significantly higher proportion of patients with more severe primary tumor (T) stage, more severe lymph node (N) stage, more severe metastatic (M) stage, worse pathological stage, poorer tumor status, and higher alpha-fetoprotein (AFP) levels, indicating that high SMS expression is associated with poor clinicopathological features and prognosis. Furthermore, Kaplan-Meier survival analysis showed that, compared to the low-expression group, the high-expression group had significantly shorter overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS), thus SMS overexpression predicts unfavorable outcomes and is associated with disease progression in HCC patients. Simultaneously, SMS overexpression may affect immune cell infiltration in HCC patients, leading to poor ICB response and poor treatment efficacy for HCC.

[0030] In view of this, in a typical embodiment of the present invention, the use of a substance for detecting the SMS gene and its expression products in the preparation of products for diagnosing, detecting, monitoring, predicting the prognosis of liver cancer or predicting the response to immunotherapy is provided.

[0031] Specifically, the liver cancer mentioned refers to hepatocellular carcinoma.

[0032] The prediction of liver cancer prognosis includes at least an assessment of the clinicopathological features of liver cancer and the survival of the subjects.

[0033] The subject survival period includes at least the overall subject survival, disease-specific survival, and progression-free interval.

[0034] The clinicopathological features of liver cancer include at least the tumor TNM stage, tumor status, and alpha-fetoprotein (AFP) levels.

[0035] The immunotherapy specifically refers to immune checkpoint blockade therapy.

[0036] The prediction of immunotherapy response includes predicting the efficacy of immune checkpoint blockade therapy in subjects.

[0037] Both the SMS gene and its expression product can be of human origin, and the SMS gene expression product can obviously be spermine synthase.

[0038] In another specific embodiment of the present invention, a product for diagnosing, detecting, monitoring, and predicting the prognosis or immunotherapy response of liver cancer is provided, which at least includes a substance for detecting the transcription of the SMS gene in a sample based on high-throughput sequencing and / or quantitative PCR and / or probe hybridization; or for detecting the expression of spermine synthase in a sample based on an immunoassay.

[0039] In another specific embodiment of the present invention, the substance is a substance required for detecting the transcription of the SMS gene in a sample using methods including but not limited to liquid phase hybridization, Northern hybridization, mRNA expression profiling chips, ribozyme protection analysis, RAKE method, and in situ hybridization; or, the substance is a substance required for detecting the expression of spermine synthase in a sample using methods including but not limited to immunohistochemistry (IHC), ELISA, colloidal gold test strips, and protein chips.

[0040] The sample is the subject's liver (cancer) cells or liver (cancer) tissue; the subject can be a liver cancer patient or a person at potential risk of liver cancer.

[0041] The products include, but are not limited to, primers, probes, reagents, kits, devices (such as oligonucleotide probes or their integration, high-throughput detection chips on chip substrates or detection substrates, and microfluidic detection chips, etc.) and equipment.

[0042] In another specific embodiment of the present invention, a detection reagent is provided, the reagent being used to detect the SMS gene and its expression product.

[0043] In another specific embodiment of the present invention, a detection kit is provided, the kit comprising the above-mentioned detection reagent.

[0044] In another specific embodiment of the present invention, a system for diagnosing, detecting, monitoring, and predicting the prognosis or immunotherapy response of liver cancer is provided, the system comprising at least:

[0045] The acquisition module is configured to acquire the expression levels of the SMS gene and its expression products in the subject samples.

[0046] The assessment module is configured to determine the subject's disease status based on the expression levels of biomarkers obtained by the acquisition module.

[0047] The output module is configured to output analysis results based on the judgment of the evaluation module.

[0048] The subjects may be liver cancer patients or people at potential risk of liver cancer; the samples may be liver (cancer) cells or liver (cancer) tissue of the subjects.

[0049] As mentioned above, the liver cancer specifically refers to hepatocellular carcinoma.

[0050] The prediction of liver cancer prognosis includes at least an assessment of the clinicopathological features of liver cancer and the survival of the subjects.

[0051] The subject survival period includes at least the overall subject survival, disease-specific survival, and progression-free interval.

[0052] The clinicopathological features of liver cancer include at least the tumor TNM stage, tumor status, and alpha-fetoprotein (AFP) levels.

[0053] The immunotherapy specifically refers to immune checkpoint blockade therapy.

[0054] In another specific embodiment of the present invention, the use of the above-mentioned SMS as a target in the preparation or screening of liver cancer drugs is provided.

[0055] The liver cancer drugs mentioned are specifically drugs for the prevention and / or treatment of hepatocellular carcinoma.

[0056] In another specific embodiment of the present invention, the method for screening liver cancer drugs includes:

[0057] 1) Treat the expression and / or SMS-containing systems with candidate substances; set up parallel controls without candidate substance treatment;

[0058] 2) After completing step 1), detect the expression level of SMS in the system; if the expression level of SMS in the system treated with the candidate substance is significantly reduced compared with the parallel control, the candidate substance can be used as a candidate drug for liver cancer.

[0059] In another specific embodiment of the present invention, the system may be a cell system, a subcellular system, a solution system, a tissue system, an organ system, or an animal system.

[0060] In another specific embodiment of the present invention, the cells in the cell system may be hepatocytes;

[0061] In another specific embodiment of the present invention, the tissue in the tissue system may be liver tissue;

[0062] In another specific embodiment of the present invention, the organ in the organ system may be the liver;

[0063] In another specific embodiment of the present invention, the animals in the animal system can be mammals, such as mice, rats, guinea pigs, rabbits, monkeys, humans, etc., without specific limitations.

[0064] The present invention will be further illustrated below with specific examples. These examples are for illustrative purposes only and do not limit the scope of the invention. Experimental conditions not specifically specified in the examples are generally performed under conventional conditions or as recommended by the sales company; unless otherwise specified in the present invention, these conditions are commercially available.

[0065] Example

[0066] Experimental methods:

[0067] Using the GEPIA2 database, the raw sequencing data of hepatocellular carcinoma samples from the TCGA database were compared with adjacent paired normal samples from the Hepatocellular Carcinoma Genome Atlas (TCGA-LIHC) to obtain differentially expressed genes (DEGs) in hepatocellular carcinoma.

[0068] A list of genes related to amino acid and its derivative metabolism (GO:0006519) was downloaded from the GSEA database. These two gene sets were then cross-referenced to obtain the DEGs (genes associated with amino acid metabolism) in HCC. Multivariate Cox regression analysis was used to determine the optimal prognostic gene.

[0069] The differences in target gene mRNA and protein expression levels were assessed using the TCGA-LIHC dataset. The differences in mRNA expression levels of preferred target genes were validated in multiple clinical liver cancer samples.

[0070] Using clinical information from samples collected in the TCGA dataset, HCC patients were divided into high-expression and low-expression groups based on the expression level of the target gene. Prognostic survival analysis was conducted on these patients. Simultaneously, ROC analysis was established using the gene expression level to evaluate the predictive effect of the gene expression level on liver cancer samples, further confirming the clinical significance and value of the target gene.

[0071] The predictive value of target gene expression for response to immune checkpoint blockade (ICB) therapy was evaluated. Subsequently, the correlation between target gene expression and immune infiltration and immune checkpoint gene expression was investigated. Finally, the relationship between immune characteristics and target gene expression in the tumor microenvironment was elucidated by analyzing hepatocellular carcinoma single-cell RNA sequencing (scRNA-seq) datasets.

[0072] Experimental results:

[0073] Identification of amino acid and derivative metabolic genes (AAMGs) in TCGA-LIHC and GEO databases

[0074] Identification of amino acid and derivative metabolic-related genes (AAMGs) from TCGA-LIHC and GEO databases. This study followed... Figure 1 The flowchart shown is followed. In the TCGA-LIHC gene expression profiles obtained by the ANOVA and LIMMA algorithms, the differences between the tumor group and the normal group were 2207 and 3195 DEGs, respectively. Furthermore, a Venn diagram was used to show 607 overlapping genes in the two algorithm groups. Then, the 607 DEGs were cross-referenced with AAMGs (GO:0006519) to obtain three differentially expressed genes (AAMRHGs) related to amino acid and derivative metabolism processes, which were included in subsequent functional classification analysis. Figure 1 Individual genes or suitable genomes for study were identified using multivariate Cox regression analysis in the Tumor Immunology Estimation Resource 2.0 (TIMER2.0) database. SMS was ultimately selected.

[0075] Upregulation of SMS expression in hepatocellular carcinoma

[0076] We used the Wilcoxon rank-sum test to compare SMS expression in 371 HCC tumor tissues and 276 normal tissues (50 from the TCGA-LIHC dataset and 226 from the GTEx dataset). SMS expression in tumor tissues was significantly higher than in unpaired tissues (p < 0.001). Figure 2 A) and pairing (p < 0.001; Figure 2 B) Normal tissues. To clarify the transcriptional and translational levels of SMS in HCC tissues, we performed CPTAC analysis on 11 HCC research cohorts from the UALCAN and HCCDB databases. We found that, compared with normal tissues, the protein levels of SMS in HCC tissues ( Figure 2 C) and mRNA ( Figure 2 D) Significantly elevated expression. Analysis of the UALCAN pan-cancer study cohort showed a consistent trend in the mRNA and protein levels of SMS in pan-cancer tissues. Cancer Cell Line Encyclopedia (CCLE) analysis revealed that SMS expression in hepatocellular carcinoma cell lines was higher than the average level in pan-cancer cell lines. These results indicate a strong correlation between the upregulation of SMS and the occurrence of HCC.

[0077] Assessment of the correlation between SMS and HCC prognosis

[0078] To clarify the role and prominence of SMS expression, the clinicopathological characteristics of HCC patients with different SMS expression levels were studied (Table 1). Compared with the low SMS expression group, the high SMS expression group had a significantly higher proportion of patients with more severe primary tumor (T) stage, more severe lymph node (N) stage, more severe metastatic (M) stage, worse pathological stage, worse tumor status, and higher alpha-fetoprotein (AFP) levels (Table 1). All of these differences were statistically significant.

[0079] Table 1. Clinical characteristics of HCC patients in the TCGA database

[0080]

[0081] Univariate logistic regression analysis showed that SMS expression was associated with clinicopathological features of poor prognosis (Table 2). Elevated SMS expression in HCC was positively correlated with T stage, pathological stage, histological grade, inflammation of adjacent liver tissue, AFP and fibrosis scores, and significantly negatively correlated with race, weight and height (all p < 0.05).

[0082] Table 2 Single-gene binary logistic regression

[0083]

[0084] Next, Kaplan-Meier survival analysis showed that compared with the low-expression group of SMS, the high-expression group of SMS had significantly shorter overall survival [OS, n=370, HR=2.090 (1.477-2.960), log-rank P<0.001], disease-specific survival [DSS, n=362, HR=1.846 (1.180-2.887), log-rank P=0.0056], and progression-free survival [PFS, n=370, HR=1.436 (1.070-1.928), log-rank P=0.0145]. Figure 3 A).

[0085] To test the ability of SMS to predict the occurrence and progression of HCC, time-dependent ROC analysis revealed that SMS can predict HCC patients' 1-, 3-, and 5-year overall survival (OS), disease severity syndrome (DSS), and progression-free survival (PFS) to a certain extent, with AUC mostly between 0.6 and 0.8. Figure 3 B). Univariate and multivariate Cox regression analyses were used to assess the independent prognostic value of six clinicopathological variables—SMS, age, sex, pT stage, pTNM stage, and grade—on HCC OS. SMS and pT stage were independent prognostic markers for OS. Figure 3C). We then used a Nomogram model to estimate these clinicopathological variables. The concordance index of the Nomogram was 0.703 (0.657–0.75). Figure 3 D). Furthermore, SMS expression plays a role in differentiating tumors from normal tissues, with an AUC value of 0.956 (CI = 0.944–0.973). Figure 3 E). The results indicate that SMS is an exciting biomarker for identifying HCC tissue. These results suggest that overexpression of SMS predicts adverse outcomes and is associated with disease progression in HCC patients.

[0086] Correlation between SMS expression and ICB response and immune infiltration in HCC

[0087] Immunotherapy has revolutionized cancer treatment. While some HCC patients benefit from ICB therapy, many do not achieve significant efficacy. Next, we examined whether SMS expression could predict clinical response to ICB using Tumor Immune Dysfunction and Exclusion (TIDE) analysis. Results showed that the SMS overexpression group had a higher median TIDE score, indicating a weakened response to ICB. Figure 4 A). Furthermore, the TIDE prediction score was negatively correlated with the efficacy of anti-pd1 and anti-ctla4 treatment. This prompted us to explore the relationship between SMS expression, immune checkpoints, and immune cell infiltration levels. In HCC with high SMS expression, the transcriptional level of immune checkpoint mRNA was generally elevated, suggesting that immunosuppression is more intense in HCC with high SMS expression. Figure 4 B).

[0088] The number and proportion of infiltrating immune cells play a major role in tumor development and immunotherapy response, and are therefore related to patient prognosis. The relationship between SMS expression and immune infiltration in HCC is shown in the heatmap, analyzed using R-package immune deconvolution (p<0.001). Figure 4 C). Comparative analysis of immune cells confirmed differences in various immune cells between the two groups, such as immature B cells, immature dendritic cells, and macrophages. Figure 4 D).

[0089] The results indicate that strong immunosuppression in the tumor microenvironment is a prerequisite for poor prognosis and tumor development in HCC patients with SMS-overexpression. In conclusion, SMS overexpression may affect immune cell infiltration in HCC patients, leading to poor ICB response and poor treatment efficacy for HCC.

[0090] Expression of SMS in the Hepatocellular Carcinoma Tumor Immune Microenvironment

[0091] To understand the impact of SMS gene expression on the tumor immune microenvironment, we obtained three HCC single-cell transcriptome datasets from the scTIME portal (http: / / sctime.sklehabc.com / ) and analyzed each dataset. In dataset GSE98638, compared with the immune microenvironment from other tissues, tumor tissues showed a higher positive rate of SMS expression in T-cell exhaustion and inflammatory senescence-related cells. Figure 5 B). In dataset GSE125449, malignant tumor cells and TAM tumor-associated macrophages were more positive than other cells in the immune microenvironment (B). Figure 5 C). In the GSE140228 dataset, SMS-expressing cells at the tumor periphery differed from those from other tissues, particularly macrophages. Specifically, tumor-derived macrophages expressed SMS in ascites fluid, which may be associated with cancer metastasis. Figure 5 D). In summary, SMS expression is associated with a strong tumor immunosuppressive effect in the HCC tumor immune microenvironment.

[0092] Comparison of differential gene expression profiles between SMS-low and SMS-high in HCC

[0093] To rule out the influence of hepatitis infection on SMS expression, we examined SMS expression in tumors of HCC patients with and without viral hepatitis in the TCGA-LIHC dataset. SMS expression was not correlated with hepatitis B virus or hepatitis C virus infection. Figure 6 A).

[0094] To uncover the potential mechanisms by which SMS promotes tumor development, we analyzed DEGs in SMS-high and low expression samples. Microarray data were normalized using the limma package. Cluster analysis and expression of DEGs are shown in the heatmap (…). Figure 6 B) and volcano map ( Figure 6 In C), based on the results of pathway analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), we found that DEGs are mostly enriched in processes such as chromosome segregation, mitosis, nuclear division, and the biosynthesis of organic and carboxylic acids. Figure 6 D).

[0095] Furthermore, using WebGestalt's GSEA, we evaluated downstream regulatory pathways related to SMS. Our KEGG analysis under the Functional Database option revealed enrichment of immune-related pathways, such as the intestinal immune network generating IgA, Fcγr-mediated phagocytosis, antigen processing and presentation, and Th1 and Th2 cell differentiation. Figure 6E). This suggests that abnormal expression of SMS may participate in the formation of immunosuppressive function in the HCC immune microenvironment through these immune-related pathways.

[0096] To determine the relationship between SMS and cancer-related functional pathways, we used the ssGSEA algorithm to calculate the functional pathway scores of 19 cancer-related functional pathways between the SMS high-expression group and the low-expression group. The results showed that tumor inflammation characteristics were similar between the two groups. However, in the SMS high-expression group, tumor-related signaling pathways, such as cellular response to hypoxia, tumor proliferation signaling, and EMT, were significantly more active. Figure 6 F). These results suggest that SMS may also influence the occurrence and development of HCC by regulating multiple important tumor-related signaling pathways.

[0097] Co-expression network of hepatocellular carcinoma SMS

[0098] By analyzing the co-expression network of SMS in the LIHC cohort using linkedomics, we aim to reveal gene interactions and thus explore the gene functions of SMS. 12073 genes showed significant positive and 7842 negative correlations with SMS (FDR < 0.01). Figure 7 Then, the top 50 genes selected from the above two related groups were used to create a heatmap. Figure 7 B). SMS expression was strongly positively correlated with ACOT9 (positive rank 1, r = 0.568, p = 3.38E-32), EIF2S3 (r = 0.560, p = 3.65E-31), and TUBA1C (r = 0.512, p = 1.66E-25).

[0099] Next, in the overall survival analysis of HCC, we assessed high- and low-risk genes using hazard ratios (HRs). The results showed that the top 20 positively correlated co-expressed genes and the top 20 negatively correlated co-expressed genes were likely high-risk and low-risk genes for HCC, respectively (p < 0.05, Table 3). Therefore, SMS may promote HCC progression by modulating risk factors for HCC.

[0100] Finally, the top 50 positively correlated genes and the top 50 negatively correlated genes were selected for GO and KEGG enrichment analyses, respectively. The results showed that SMS co-expressed genes were mainly related to neutrophil immune response pathways and organic matter catabolism processes. Figure 7 C). KEGG pathway analysis showed that the co-expressed genes were mainly enriched in pathways related to Salmonella infection and the degradation of valine, leucine, and isoleucine. Figure 7 C). These results suggest that SMS may be involved in the immune-related processes of HCC.

[0101] Table 3. Overall survival analysis of the top 20 genes negatively correlated with SMS in HCC

[0102]

[0103] Through in-depth analysis of RNA-seq data and combined with relevant clinical information on HCC, we observed that elevated SMS expression is associated with poor prognosis in HCC patients. Furthermore, single-gene binary logistic regression and Cox regression analyses showed that this effect was independent of other factors. Based on time-ROC curve analysis, we believe that SMS expression can help infer the survival rate of HCC patients. Simultaneously, SMS expression increases with the progression of HCC tumor stage, suggesting that SMS is related to HCC development. Moreover, when assessing the predictive sensitivity and specificity of SMS expression for HCC and normal tissues using ROC curves, we found that the variable SMS accurately predicted the prognosis of both tumors and normal tissues (AUC = 0.865, CI = 0.823–0.907). In conclusion, we hypothesize that high SMS expression in HCC patients leads to spermine accumulation, which has been confirmed in the urine and plasma of cancer patients. Therefore, SMS can serve as a prospective biomarker for the diagnosis and prediction of clinical outcomes in HCC.

[0104] Due to limitations in HCC diagnostic technology, patients often miss the opportunity for complete treatment, such as surgery or liver transplantation. Therefore, ICB therapy offers hope for a cure to patients with advanced HCC. To assess the impact of SMS expression on ICB efficacy, we used the TIDE algorithm and found that the TIDE score increased in the high SMS expression group. The TIDE score was positively correlated with the incidence of immune escape, which may explain the poor response to ICB treatment. Through public data mining, we found that immune checkpoint mRNA transcription levels were generally elevated in HCC with high SMS expression. Furthermore, SMS expression was shown to be associated with immune infiltration in HCC. There is evidence that SMS can serve as a potential biomarker for predicting ICB treatment response.

[0105] Various stromal cells, cytokines, and chemokines in the tumor microenvironment can regulate tumor development and become potential therapeutic targets. Using publicly available single-cell transcriptome data from hepatocellular carcinoma (HCC), we evaluated the distribution of SMS expression in the HCC immune microenvironment. We found a high proportion of SMS-positive cells among immunosuppressive immune cells in the HCC immune microenvironment. In particular, the liver promotes immune tolerance, preventing antigen overload from certain substances absorbed from the viscera. This study shows that a high proportion of immunosuppressive SMS-positive immune cells can promote the formation of a strong immunosuppressive environment in HCC, defined as a "cold tumor." Some SMS inhibitors can significantly improve the therapeutic efficacy of polyamine depletion therapies, especially in arginine-rich tumors. Tumor cells can consume large amounts of arginine in the tumor microenvironment, leading to arginine deficiency and inhibiting the activation of anti-tumor immune cells. Therefore, inhibiting SMS to prevent arginine degradation in the tumor microenvironment is an attractive strategy for reactivating the immune response. These results suggest that inhibiting SMS expression can promote advancements in therapeutic strategies, thereby reducing immunotherapy resistance in HCC and improving the efficacy of checkpoint blockade therapy.

[0106] To fully understand the activity of SMS in HCC, we used TCGA-LIHC data to obtain DEGs by comparing the expression profiles of two groups (high and low SMS expression). Interestingly, hepatitis virus infection, a potential factor in HCC development, did not affect SMS expression. Furthermore, through GO and KEGG analyses, we found that SMS is associated with chromosome segregation, mitosis, nuclear division, and the biosynthesis of organic and carboxylic acids.

[0107] Furthermore, when using GSEA, GSVA, and ssGSEA to detect the expression level of SMS in HCC, important immune-related pathways such as the intestinal immune network producing IgA, Fcγr-mediated phagocytosis, antigen processing and presentation, and Th1 and Th2 cell differentiation were also observed. Figure 6 E) and cancer-related signaling pathways such as MYC target, G2M checkpoint, activated E2F target and PI3K-AKT-mTOR signaling ( Figure 6 F) were all closely related to the expression level of SMS in HCC. These results suggest that SMS overexpression is not only related to the immunosuppressive effect of the tumor immune microenvironment, but may also be involved in the regulation of multiple tumor-related signaling pathways.

[0108] On the other hand, we analyzed genes significantly associated with SMS expression in HCC. We identified several aberrantly expressed genes that are related to overall HCC survival, and these genes may constitute a network regulating the course of HCC and SMS. Pathway enrichment analysis of these genes indicated that the regulatory network primarily promotes immune cell activity and may further participate in the formation of immunosuppressive functions in the hepatocellular carcinoma immune microenvironment.

[0109] All data indicate that SMS expression plays a crucial role in the occurrence and development of cancer. Further research into the regulatory mechanisms and networks of SMS expression will contribute to elucidating the pathogenesis and immune evasion mechanisms of liver cancer.

[0110] In summary, this study is the first to demonstrate the upregulation of SMS expression in HCC. We believe that SMS can serve as a potential biomarker for poor prognosis, and its expression level can provide a reference for the treatment of relevant HCC patients. Furthermore, the role of SMS in the tumor immune microenvironment makes it a potential target for immunotherapy in liver cancer.

[0111] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. Use of a substance for detecting an expression product of an SMS gene in the preparation of a product for predicting the prognosis of liver cancer or the response of ICB immunotherapy, wherein the liver cancer is hepatocellular carcinoma.

2. The use according to claim 1, characterized in that, The prediction of the prognosis of liver cancer at least includes the evaluation of the clinicopathological features of liver cancer and the survival period of the subject; The clinicopathological features of liver cancer at least include tumor TNM stage, tumor status, and alpha-fetal protein index; The survival period of the subject at least includes overall survival, disease-specific survival, and progression-free interval; The immunotherapy is immune checkpoint blockade therapy.

3. A system for predicting the prognosis of liver cancer or the response to ICB immunotherapy, characterized by, The system at least includes: an acquisition module configured to acquire the expression level of the expression product of the SMS gene in the sample of the subject; an evaluation module configured to determine the disease condition of the subject according to the expression level of the expression product of the SMS gene obtained by the acquisition module; an output module configured to output the analysis result according to the determination of the evaluation module; The liver cancer is specifically hepatocellular carcinoma.

4. The system of claim 3, wherein, The sample is liver cells or liver tissue of the subject; The prediction of the prognosis of liver cancer at least includes the evaluation of the clinicopathological features of liver cancer and the survival period of the subject; The clinicopathological features of liver cancer at least include tumor TNM stage, tumor status, and alpha-fetal protein index; The survival period of the subject at least includes overall survival, disease-specific survival, and progression-free interval; The immunotherapy is specifically immune checkpoint blockade therapy.

5. The system of claim 4, wherein, The sample is liver cancer cells or liver cancer tissue of the subject.

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