Comprehensive Analysis of the Prognosis and Correlations With Immune Infiltration of S100 Protein Family Members in Hepatocellular Carcinoma

Knockdown of S100A2 inhibits the aggressiveness of endometrial cancer by activating STING pathway

BACKGROUND

Endometrial cancer is a kind of gynaecological cancer. S100A2 is a newfound biomarker to diagnose endometrial cancer. This study was to investigate the role of S100A2 on regulating migration and invasion of endometrial cancer.

METHODS

The mRNA and protein levels of S100A2 were obtained by quantitative real-time polymerase chain reaction, immunohistochemistry and western blot methods. Cell viability was measured by the Cell Counting Kit-8 assay. Cell migration and invasion were quantified using transwell assays. Western blot assay was conducted to quantify protein expressions of epithelial to mesenchymal transition-related proteins (N-cadherin and E-cadherin). Furthermore, in vivo tumour formation experiments were performed to evaluate the role of S100A2 on tumour xenografts.

RESULTS

S100A2 was significantly up-regulated in endometrial cancer tissues. Knockdown of S100A2 inhibited cell viability, migration and invasion of endometrial cancer cells. Meanwhile, STING pathway was activated by the inhibited S100A2. STING inhibitor C-176 significantly reversed the effects of S100A2 knockdown on aggressive behaviours of endometrial cancer cells. Inhibition of S100A2 dramatically suppresses the tumour growth in vivo.

CONCLUSIONS

S100A2 functions as an oncogene in endometrial cancer. Targeting S100A2 may be a promising therapeutic method to treat endometrial carcinoma.

Prognostic Value of S100 Family mRNA Expression in Hepatocellular Carcinoma

BACKGROUND/AIMS

 The S100 family contains more than 20 Ca2+-binding proteins that participate in numerous cellular biological processes. However, the prognostic value of individual S100s in hepatocellular carcinoma (HCC) remains unclear. Therefore, we comprehensively assessed the prognostic value of S100s in HCC.

MATERIALS AND METHODS

 The mRNA level of S100s in distinct types of cancer was analyzed through Oncomine. The clinical prognostic significance of each S100 was evaluated using Kaplan-Meier plotter and OncoLnc. The expression and mutation of S100s were determined through cBioPortal. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were used to predict the functions and pathways of S100s.

RESULTS

 The analyses revealed that, relative to normal tissues, liver cancer tissues showed aberrant mRNA expression of most S100s. In the survival analysis with Kaplan-Meier plotter, elevated expression levels of S100PBP, S100A2, S100A7, S100A10, and S100A13 were related to shorter overall survival (OS), whereas increased S100A5 expression was associated with longer OS. Moreover, results obtained using OncoLnc showed that increased expression levels of S100P, S100PBP, S100A13, S100A11, S100A10, and S100A2 were related to shorter OS. Thus, S100PBP, S100A13, S100A10, and S100A2 exhibited the same prognostic trend in the 2 databases. However, all S100 member gene mutational changes had no considerable prognostic value in OS and disease-free survival of HCC patients.

CONCLUSION

 Although the findings need to be further confirmed by experiments, they provide new evidence for the prognostic significance of the S100s in HCC.

Exploring the prognostic value of S100A11 and its association with immune infiltration in breast cancer

Breast cancer (BC) is a severe danger to women's lives and health globally. S100A11 is aberrantly expressed in many carcinomas and serves a crucial function in cancer development. However, the role of S100A11 in BC is unclear. In this study, we utilized multiple databases and online tools, including the TCGA database, cBioPortal, and STRING, to evaluate the significance of S100A11 in BC prognosis and immune infiltration. We found that S100A11 was considerably more abundant in BC tissues. Survival analysis indicated that individuals with S100A11 high expression of BC had shorter overall survival. Multivariate Cox regression analysis revealed that high S100A11 expression independently influenced the poor outcome of patients with BC (HR = 1.738, 95%CI 1.197-2.524). Our nomogram incorporating five factors, including S100A11, age, clinical stage, N, and M, was developed to anticipate the survival probability in BC prognosis. The model demonstrated good consistency and accuracy. Furthermore, the mutation rete of S100A11 was 14%. Survival analysis suggested that breast cancer patients with S100A11 mutation had a worse prognosis. KEGG pathway enrichment analysis revealed that S100A11 may be mainly involved in the IL-17 signaling pathway. Finally, we discovered a correlation between S100A11 expression and immune cell infiltration on BC. S100A11 expression was positively associated with 17 immune checkpoint-related genes. In conclusion, this study indicates that S100A11 may contribute to a worse prognosis for BC and potentially has a significant impact through its influence on immune cell infiltration and the IL-17 signaling pathway.

Novel piperazine-1,2,3-triazole leads for the potential treatment of pancreatic cancer

From lead 1, (N-(4-((4-(3-(4-(3-methoxyphenyl)-1H-1,2,3-triazol-1-yl)propyl)piperazin-1-yl)sulfonyl)-phenyl)acetamide), a S100A2-p53 protein-protein interaction inhibitor based on an in silico modelling driven hypothesis, four focused libraries were designed and synthesised. Growth inhibition screening was performed against 16 human cancer cell lines including the pancreatic cell lines MiaPaCa2, BxPC3, AsPC-1, Capan-2, HPAC, PANC-1 and the drug resistant CFPAC1. Modification of 1's phenylacetamide moiety, gave Library 1 with only modest pancreatic cancer activity. Modification of the 3-OCH3Ph moiety (Library 2) gave 4-CH3 (26), 4-CH2CH3 (27), 4-CF3 (31) and 4-NO2 (32) with sterically bulky groups more active. A 4-CF3 acetamide replacement enhanced cytotoxicity (Library 3). The 4-C(CH3)336 resulted in a predicted steric clash in the S100A2-p53 binding groove, with a potency decrease. Alkyl moieties afforded more potent analogues, 34 (4-CH3) and 35 (CH2CH3), a trend evident against pancreatic cancer: GI50 3.7 (35; BxPC-3) to 18 (40; AsPC-1) μM. Library 4 analogues with a 2-CF3 and 3-CF3 benzenesulfonamide moiety were less active than the corresponding Library 3 analogues. Two additional analogues were designed: 51 (4-CF3; 4-OCH3) and 52 (4-CF3; 2-OCH3) revealed 52 to be 10-20 fold more active than 51, against the pancreatic cancer cell lines examined with sub-micromolar GI50 values 0.43 (HPAC) to 0.61 μM (PANC-1). MOE calculated binding scores for each pose are also consistent with the observed biological activity with 52. The obtained SAR data is consistent with the proposed interaction within the S100A2-p53 bonding groove.

S100A family is a group of immune markers associated with poor prognosis and immune cell infiltration in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common human cancers with poor prognosis in the world. HCC has become the second leading cause of cancer-related death in China. It is urgent to identify novel biomarker and valid target to effectively diagnose, treat or predict the prognosis of HCC. It has been reported that S100A family is closely related to cell proliferation and migration of different cancers. However, the values of S100As in HCC remain to be further analyzed.

METHODS

We investigated the transcriptional and translational expression of S100As, as well as the value of this family in HCC patients from the various databases.

RESULTS

S100A10 was most relevant to HCC.

CONCLUSIONS

The results from HCC patients' tissues and different cells also confirmed the role of S100A10 in HCC. Furthermore, we proved that S100A10 could influenced the cell proliferation of HCC cells via ANXA2/Akt/mTOR pathway. However, it would appear that the relationship between S100A10 and HCC is complex and requires more research.

S100A10 promotes HCC development and progression via transfer in extracellular vesicles and regulating their protein cargos

OBJECTIVE

Growing evidence indicates that tumour cells exhibit characteristics similar to their lineage progenitor cells. We found that S100 calcium binding protein A10 (S100A10) exhibited an expression pattern similar to that of liver progenitor genes. However, the role of S100A10 in hepatocellular carcinoma (HCC) progression is unclear. Furthermore, extracellular vesicles (EVs) are critical mediators of tumourigenesis and metastasis, but the extracellular functions of S100A10, particularly those related to EVs (EV-S100A10), are unknown.

DESIGN

The functions and mechanisms of S100A10 and EV-S100A10 in HCC progression were investigated in vitro and in vivo. Neutralising antibody (NA) to S100A10 was used to evaluate the significance of EV-S100A10.

RESULTS

Functionally, S100A10 promoted HCC initiation, self-renewal, chemoresistance and metastasis in vitro and in vivo. Of significance, we found that S100A10 was secreted by HCC cells into EVs both in vitro and in the plasma of patients with HCC. S100A10-enriched EVs enhanced the stemness and metastatic ability of HCC cells, upregulated epidermal growth factor receptor (EGFR), AKT and ERK signalling, and promoted epithelial-mesenchymal transition. EV-S100A10 also functioned as a chemoattractant in HCC cell motility. Of significance, S100A10 governed the protein cargos in EVs and mediated the binding of MMP2, fibronectin and EGF to EV membranes through physical binding with integrin αⅤ. Importantly, blockage of EV-S100A10 with S100A10-NA significantly abrogated these enhancing effects.

CONCLUSION

Altogether, our results uncovered that S100A10 promotes HCC progression significantly via its transfer in EVs and regulating the protein cargoes of EVs. EV-S100A10 may be a potential therapeutic target and biomarker for HCC progression.

Specific S100 Proteins Bind Tumor Necrosis Factor and Inhibit Its Activity

Tumor necrosis factor (TNF) inhibitors (anti-TNFs) represent a cornerstone of the treatment of various immune-mediated inflammatory diseases and are among the most commercially successful therapeutic agents. Knowledge of TNF binding partners is critical for identification of the factors able to affect clinical efficacy of the anti-TNFs. Here, we report that among eighteen representatives of the multifunctional S100 protein family, only S100A11, S100A12 and S100A13 interact with the soluble form of TNF (sTNF) in vitro. The lowest equilibrium dissociation constants (K_d) for the complexes with monomeric sTNF determined using surface plasmon resonance spectroscopy range from 2 nM to 28 nM. The apparent K_d values for the complexes of multimeric sTNF with S100A11/A12 estimated from fluorimetric titrations are 0.1-0.3 µM. S100A12/A13 suppress the cytotoxic activity of sTNF against Huh-7 cells, as evidenced by the MTT assay. Structural modeling indicates that the sTNF-S100 interactions may interfere with the sTNF recognition by the therapeutic anti-TNFs. Bioinformatics analysis reveals dysregulation of TNF and S100A11/A12/A13 in numerous disorders. Overall, we have shown a novel potential regulatory role of the extracellular forms of specific S100 proteins that may affect the efficacy of anti-TNF treatment in various diseases.

Influence of S100A2 in Human Diseases

S100 proteins are a family of low-molecular-weight proteins characterized by two calcium-binding sites with a helix-loop-helix (“EF-hand-type”) domain. The S100 family of proteins is distributed across various organs and can interact with diverse molecules. Among the proteins of the S100 family, S100 calcium-binding protein A2 (S100A2) has been identified in mammary epithelial cells, glands, lungs, kidneys, and prostate gland, exhibiting various physiological and pathological actions in human disorders, such as inflammatory diseases and malignant tumors. In this review, we introduce basic knowledge regarding S100A2 regulatory mechanisms. Although S100A2 is a tumor suppressor, we describe the various influences of S100A2 on cancer and inflammatory diseases.

Target and drug predictions for SARS-CoV-2 infection in hepatocellular carcinoma patients

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the coronavirus disease (COVID-19), which poses a major threat to humans worldwide. With the continuous progress of the pandemic, a growing number of people are infected with SARS-CoV-2, including hepatocellular carcinoma (HCC) patients. However, the relationship between COVID-19 and HCC has not been fully elucidated. In order to provide better treatment for HCC patients infected with SARS-CoV-2, it’s urgently needed to identify common targets and find effective drugs for both. In our study, transcriptomic analysis was performed on both selected lung epithelial cell datasets of COVID-19 patients and the datasets of HCC patients to identify the synergistic effect of COVID-19 in HCC patients. What’s more, common differentially expressed genes were identified, and a protein-protein interactions network was designed. Then, hub genes and basic modules were detected based on the protein-protein interactions network. Next, functional analysis was performed using gene ontology terminology and the Kyoto Encyclopedia of Genes and Genomes pathway. Finally, protein-protein interactions revealed COVID-19 interaction with key proteins associated with HCC and further identified transcription factor (TF) genes and microRNAs (miRNA) with differentially expressed gene interactions and transcription factor activity. This study reveals that COVID-19 and HCC are closely linked at the molecular level and proposes drugs that may play an important role in HCC patients with COVID-19. More importantly, according to the results of our research, two critical drugs, Ilomastat and Palmatine, may be effective for HCC patients with COVID-19, which provides clinicians with a novel therapeutic idea when facing possible complications in HCC patients with COVID-19.

Alarm Signal S100-Related Signature Is Correlated with Tumor Microenvironment and Predicts Prognosis in Glioma

Glioma are the most common malignant central nervous system tumor and are characterized by uncontrolled proliferation and resistance to therapy. Dysregulation of S100 proteins may augment tumor initiation, proliferation, and metastasis by modulating immune response. However, the comprehensive function and prognostic value of S100 proteins in glioma remain unclear. Here, we explored the expression profiles of 17 S100 family genes and constructed a high-efficient prediction model for glioma based on CGGA and TCGA datasets. Immune landscape analysis displayed that the distribution of immune scores, ESTIMATE scores, and stromal scores, as well as infiltrating immune cells (macrophages M0/M1/M2, T cell CD4+ naïve, Tregs, monocyte, neutrophil, and NK activated), were significant different between risk-score subgroups. Overall, we demonstrated the value of S100 protein-related signature in the prediction of glioma patients’ prognosis and determined its relationship with the tumor microenvironment (TME) in glioma.

Osteoclasts differential-related prognostic biomarker for osteosarcoma based on single cell, bulk cell and gene expression datasets

Osteosarcoma (OS) is one of the most common primary bone malignant tumors. Osteoclasts have been shown to have a valuable role in OS. In the present study, we analyzed the differentiation states of osteoclasts in OS and their prognostic significance based on integrated scRNA-seq and bulk RNA-seq data. Osteoclasts in distinct differentiation states were characterized, and 661 osteoclasts differentiation-related genes (ODRGs) were obtained. ORDGs in distinct differentiation states were enriched in distinct functions and pathways. TPM1, S100A13, LOXL1, PSMD10, ST3GAL4, PEF1, SERPINE2, TUBB, FAM207A, TUBA1A, and DCN were identified as the significant survival-predicting ODRGs. We successfully developed a risk score model based on these survival-predicting ODRGs. In addition, we generated a nomogram applicable for clinical with both ODRGs signatures and clinicopathological parameters, and validated in OS cohorts to predict OS patient outcome. This study proposed and verified the important roles of osteoclasts differentiation in the prognosis of patients with OS, suggesting promising therapeutic targets for OS.

A Pancancer Analysis of the Oncogenic Role of S100 Calcium Binding Protein A7 (S100A7) in Human Tumors

Background: Although emerging studies support the relationship between S100 calcium binding protein A7 (S100A7) and various cancers, no pancancer analysis of S100A7 is available thus far. Methods: We investigated the potential oncogenic roles of S100A7 across 33 tumors based on datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Moreover, a survival prognosis analysis was performed with the gene expression profiling interactive analysis (GEPIA) web server and Kaplan–Meier plotter, followed by the genetic alteration analysis of S100A7 and enrichment analysis of S100A7-related genes. Results: S100A7 was highly expressed in most types of cancers, and remarkable associations were found between S100A7 expression and the prognosis of cancer patients. S100A7 expression was associated with the expression of DNA methyltransferase and mismatch repair genes in head and neck squamous cell carcinoma, the infiltration of CD8+ T cells and cancer-associated fibroblasts in different tumors. Moreover, glycosaminoglycan degradation and lysosome-associated functions were involved in the functional mechanisms of S100A7. Conclusions: The current pancancer study shows a relatively integrative understanding of the carcinogenic involvement of S100A7 in numerous types of cancers.

Gene Expression-Based Predication of RNA Pseudouridine Modification in Tumor Microenvironment and Prognosis of Glioma Patients

Aberrant expression of methyltransferases and demethylases may augment tumor initiation, proliferation and metastasis through RNA modification, such as m⁶A and m⁵C. However, activity of pseudouridine (Ψ) modification of RNA remains unknown in glioma, the most common malignant intracranial tumor. In this study, we explored the expression profiles of the Ψ synthase genes in glioma and constructed an efficient prediction model for glioma prognosis based on the CGGA and TCGA datasets. In addition, the risk-score signature was positively associated with malignancy of gliomas and the abundance of tumor-infiltrating immune cells such as macrophages M0 and regulatory T cells (Tregs), but negatively associated with the abundance of monocytes, NK cell activation and T cell CD4⁺ naive. In terms of mechanism, the risk-score signature was positively associated with the expression of inflammatory molecules such as S100A11 and CASP4 in glioma. Overall, this study provided evidence for the activity of RNA Ψ modification in glioma malignancy and local immunity.

CircRNA circ_0006156 inhibits the metastasis of prostate cancer by blocking the ubiquitination of S100A9

Circular RNAs (circRNAs) have been demonstrated to play vital roles in cancer development and progression. However, studies on the association between circRNAs and prostate cancer (PCa) are still lacking. CircRNA sequencing of two pairs of PCa tissues and adjacent normal tissues was conducted in the present study, and qRT-PCR was performed to verify the results. Functional experiments were performed to investigate cellular functions after specific changes. Mass spectrometry analysis after RNA pull-down experiments and Co-IP assays were further conducted. Downstream target proteins were predicted via online databases and detected in vitro by Western blot analysis and in vivo by immunohistochemistry. Hsa_circ_0006156 (subsequently named circ_0006156) expresses at low levels in both PCa tissues and cells, and it significantly inhibits the migration and invasion of PCa cells. Circ_0006156 binds to and blocks the ubiquitination of S100A9. Moreover, functional assays revealed that circ_0006156 represses the malignant progression of PCa by binding to S100A9. Finally, in vivo experiments showed that circ_0006156 suppresses PCa migration and invasion by increasing S100A9, revealing circ_0006156 as a potential novel effective target for PCa treatment.

Identification of Rad51 as a prognostic biomarker correlated with immune infiltration in hepatocellular carcinoma

Rad51, a DNA-repair-related gene, has been reported to be involved in multiple cancers. However, its link with immune infiltration in liver cancer still unknown. Therefore, more research into the roles and activities of Rad51 in hepatocellular carcinoma (HCC) is required. The International Cancer Genome Consortium (ICGC) was used to identify the DNA repair gene Rad51, and has been proved to be overexpressed in HCC patients. We plotted the Kapan-Meier curve, demonstrating that patients with high expression of Rad51 have a poor prognosis. By analyzing the patient data, we discovered that high expression of Rad51 in HCC is linked to clinical stage, pathological T stage, grade, and age. Rad51 was found to be an independent prognostic factor for HCC patients using the multivariate cox model. Moreover, Rad51 expression was found to be associated with the infiltration of immune cells (B cells, CD4 + T cells, CD8 + T cells, neutrophils, macrophages, and dendritic cells) and was intimately linked to the expression of immune cell markers in HCC. Through the analysis of differentially coexpressed genes (DCGs) of Rad51, GO and KEGG enrichment analyses suggested that the expression level of Rad51 might be relevant to neuroactive ligand-receptor interactions, the cell cycle, DNA replication, homologous recombination, oocyte meiosis, and the Fanconi anemia pathway. These findings indicated that Rad51 is a valuable biomarker for the prognosis of patients with liver cancer and that its expression has a significant correlation with immune infiltrations.Abbreviations: HCC: hepatocellular carcinoma; ICGC: International Cancer Genome Consortium TCGA: The Cancer Genome Atlas; TIMER: Tumor Immune Estimation Resource; CAF: Cancer-associated fibroblast; GEPIA: Gene Expression Profiling Interactive Analysis; GSEA: Gene set enrichment analysis; OS: overall survival; PFS: progression-free survival; RFS: relapse-free survival; DSS: disease-specific survival. Partial cor: partial correlation coefficient; HPA: Human Protein Atlas; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; CAF: Cancer-associated fibroblast; DCGs: differentially co-expressed genes.

Identification S100A9 as a potential biomarker in neuroblastoma

BACKGROUND

More than half of Neuroblastoma (NB) patients presented with distant metastases and the relapse of metastatic patients was up to 90%. It is urgent to explore a biomarker that could facilitate the prediction of metastasis in NB patients.

METHODS AND RESULTS

In the present study, we systematically analyzed Gene Expression Omnibus datasets and focused on identifying the critical molecular networks and novel key hub genes implicated in NB metastasis. In total, 176 up-regulated and 19 down-regulated differentially expressed genes (DEGs) were identified. Based on these DEGs, a PPI network composed of 150 nodes and 452 interactions was established. Through PPI network identification combined with qRT-PCR, ELISA and IHC, S100A9 was screened as an outstanding gene. Furthermore, in vitro tumorigenesis assays demonstrated that S100A9 overexpression enhanced the proliferation, migration and invasion of NB cells.

CONCLUSIONS

Taken together, our findings suggested that S100A9 could participate in NB tumorigenesis and progression. In addition, S100A9 has the potential to be used as a promising clinical biomarker in the prediction of NB metastasis.