A pan-cancer signature for S100A11------ Prognostic and Immunotherapeutic Value

IF 0.5 4区生物学 Q4 BIOCHEMICAL RESEARCH METHODS

Current Proteomics Pub Date : 2023-05-03 DOI:10.2174/1570164620666230503163349

Ping Zhang, Yali Le, Chenchen Geng, Guanghui Zhao, Xiao‐Qiang Gao, Shuzhen Zhu, Ziqiang Liu

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引用次数: 0

Abstract

S100 calcium-binding protein A11 (S100A11) has important roles in tumorigenesis and multiple cancer progression. In this study, we aimed to analyze the expression and prognostic value of S100A11 across cancers and further explore the relationship between S100A11 and the tumor immune microenvironment. We analyzed the differential expression of S100A11 in the TIMER, GEPIA, and BioGPS databases and searched for its prognostic impact in the GEPIA and Kaplan-Meier plotter databases. We used the SangerBox database to investigate the relationship between S100A11 expression and the tumor immune microenvironment. The TIMER database explored the relationship between S100A11 expression and tumor immune-infiltrated cells (TILs). Correlation analysis of S100A11 expression with clinical parameters in thyroid carcinoma (THCA) was performed using the UALCAN database. The co-expression network of S100A11 in THCA was explored through the LinkedOmics database. RT‒qPCR and immunohistochemical (IHC) staining were used to analyze the expression level of S100A11 in THCA. S100A11 expression was higher in many tumors than in paired normal tissues, and increased expression was associated with poor prognosis, including overall survival (OS), recurrence-free survival (RFS), and disease-free survival (DFS). S100A11 was differentially expressed in immune subtypes and molecular subtypes of some cancers. The expression of S100A11 was correlated with immune checkpoints (ICP), tumor mutational burden (TMB), microsatellite instability (MSI), neoantigens, and TILs. The methylation level of S100A11 was negatively correlated with mRNA expression. S100A11 expression had a specific correlation with the clinical parameters of THCA. In THCA, the coexpression network of S100A11 was mainly involved in regulating inflammation and immune responses. RT‒qPCR and IHC staining confirmed that S100A11 was upregulated in THCA. S100A11 may be related to the regulation of the tumor microenvironment. S100A11 may serve as a potential pan-cancer biomarker for prognosis. S100A11 could be a potential target for THCA immunotherapy.

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S100A11的泛癌特征------预后和免疫治疗价值

S100钙结合蛋白A11 (S100A11)在肿瘤发生和多发性肿瘤进展中具有重要作用。本研究旨在分析S100A11在肿瘤中的表达及预后价值，进一步探讨S100A11与肿瘤免疫微环境的关系。我们分析了S100A11在TIMER、GEPIA和BioGPS数据库中的差异表达，并在GEPIA和Kaplan-Meier绘图仪数据库中搜索其预后影响。我们利用SangerBox数据库研究S100A11表达与肿瘤免疫微环境的关系。TIMER数据库探索S100A11表达与肿瘤免疫浸润细胞(tumor immune浸润cells, TILs)之间的关系。使用UALCAN数据库分析甲状腺癌(THCA)患者S100A11表达与临床参数的相关性。通过LinkedOmics数据库探索S100A11在THCA中的共表达网络。采用RT-qPCR和免疫组化(IHC)染色分析S100A11在THCA中的表达水平。S100A11在许多肿瘤中的表达高于配对正常组织，表达升高与预后不良相关，包括总生存期(OS)、无复发生存期(RFS)和无病生存期(DFS)。S100A11在某些肿瘤的免疫亚型和分子亚型中存在差异表达。S100A11的表达与免疫检查点(ICP)、肿瘤突变负荷(TMB)、微卫星不稳定性(MSI)、新抗原和TILs相关。S100A11甲基化水平与mRNA表达呈负相关。S100A11的表达与THCA的临床参数有特定的相关性。在THCA中，S100A11共表达网络主要参与调节炎症和免疫反应。RT-qPCR和免疫组化染色证实S100A11在THCA中表达上调。S100A11可能与肿瘤微环境的调控有关。S100A11可能作为一种潜在的泛癌预后生物标志物。S100A11可能是THCA免疫治疗的潜在靶点。

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来源期刊

Current Proteomics BIOCHEMICAL RESEARCH METHODS-BIOCHEMISTRY & MOLECULAR BIOLOGY

CiteScore

1.60

自引率

0.00%

发文量

审稿时长

>0 weeks

期刊介绍： Research in the emerging field of proteomics is growing at an extremely rapid rate. The principal aim of Current Proteomics is to publish well-timed in-depth/mini review articles in this fast-expanding area on topics relevant and significant to the development of proteomics. Current Proteomics is an essential journal for everyone involved in proteomics and related fields in both academia and industry. Current Proteomics publishes in-depth/mini review articles in all aspects of the fast-expanding field of proteomics. All areas of proteomics are covered together with the methodology, software, databases, technological advances and applications of proteomics, including functional proteomics. Diverse technologies covered include but are not limited to: Protein separation and characterization techniques 2-D gel electrophoresis and image analysis Techniques for protein expression profiling including mass spectrometry-based methods and algorithms for correlative database searching Determination of co-translational and post- translational modification of proteins Protein/peptide microarrays Biomolecular interaction analysis Analysis of protein complexes Yeast two-hybrid projects Protein-protein interaction (protein interactome) pathways and cell signaling networks Systems biology Proteome informatics (bioinformatics) Knowledge integration and management tools High-throughput protein structural studies (using mass spectrometry, nuclear magnetic resonance and X-ray crystallography) High-throughput computational methods for protein 3-D structure as well as function determination Robotics, nanotechnology, and microfluidics.