肿瘤细胞治疗研究
英文原题：Multi-Omics Pan-Cancer Analysis of Procollagen N-Propeptidase Gene Family of ADAMTS as Novel Biomarkers to Associate with Prognosis, Tumor Immune Microenvironment, Signaling Pathways, and Drug Sensitivities.
PNPSA与肿瘤发展相关，可能是潜在的肿瘤生物标志物和治疗靶点。
金属蛋白酶诱导的细胞外基质（ECM）重塑是肿瘤进展的重要特征。既往研究主要关注金属蛋白酶的两个亚群：基质金属蛋白酶（MMPs）和去整合素金属蛋白酶（ADAMs）在肿瘤中的功能。另一个重要群体——含血小板反应蛋白基序的ADAMs（ADAMTS）的作用仍不明确。本研究旨在对ADAMTS的原胶原N-前肽酶亚群（PNPSA）进行泛癌分析。
我们基于多个整合的开放数据库，系统分析了PNPSA在泛癌中的表达图谱、基因组变异、预后价值及细胞表达簇。此外，我们还基于免疫相关开放数据库，分析了PNPSA成员的表达和基因组变异对泛癌肿瘤免疫微环境（TIME）及免疫相关分子的影响。采用基因集变异分析（GSVA）评估整个PNPSA与预后、肿瘤指标、TIME及药物敏感性的关联。同时，采用京都基因与基因组百科全书（KEGG）揭示相关信号通路。最后，使用免疫组化染色验证差异分析结果。
我们发现PNPSA成员在泛癌中具有双重预后作用，且它们与TIME和免疫相关分子显著相关。有趣的是，所有PNPSA成员的拷贝数变异（CNVs）在大多数癌症中被揭示与NK细胞浸润呈负相关。单细胞测序分析揭示，除成纤维细胞外，PNPSA基因家族成员还在一些特定的肿瘤细胞和免疫细胞上表达。发现GSVA评分对脑低级别胶质瘤（LGG）、间皮瘤（MESO）和葡萄膜黑色素瘤（UVM）的生存状态具有一定预测价值，并与PI3K-Akt、AGE-RAGE等肿瘤发生相关通路显著相关。GSVA评分还对某些肿瘤的化疗和免疫治疗疗效显示出一定预测价值。
BACKGROUND: The extracellular matrix (ECM) modeling induced by the metalloproteinases is a vital characteristic for tumor progression. Previous studies mainly focus on the functions of two subgroups of metalloproteinases: matrix metalloproteinases (MMPs) and a disintegrin and metalloproteases (ADAMs) in tumors. The roles of another important group: the ADAMs with thrombospondin motifs (ADAMTS) remain unclear. This study aimed to perform a pan-cancer analysis of procollagen N-propeptidase subgroup of ADAMTS (PNPSA). METHODS: We systematically analyzed expression landscape, genomic variations, prognostic value, and cell expression clusters of PNPSA in pan-cancer based on the multiple integrated open databases. Besides, we also analyzed the impacts of expressions and genomic variations of PNPSA members on tumor immune microenvironment (TIME) and immune-related molecules in pan-cancer based on the immune-related open databases. The Gene Set Variation Analysis (GSVA) was performed to evaluate the associations of the whole PNPSA with prognosis, tumor indicators, TIME, and drug sensitivities. Meanwhile, the Kyoto Encyclopedia of Genes and Genomes (KEGG) was performed to reveal related signaling pathways. Finally, immunohistochemical staining was used to validate the differential analysis results. RESULTS: We found a dual prognostic role of PNPSA members in pan-cancer and they were significantly correlated with TIME and immune-related molecules. Interestingly, the copy number variations (CNVs) of all PNPSA members were revealed to be negatively correlated with NK cell infiltration in most cancers. Single-cell sequencing analysis reveals expressions of PNPSA gene family members on some specific tumor and immune cells in addition to the fibroblasts. The GSVA score was found to have some predictive value for survival status in Brain Lower Grade Glioma (LGG), Mesothelioma (MESO), and Uveal Melanoma (UVM) and to be significantly correlated with tumorigenesis-related pathways such as PI3K-Akt, AGE-RAGE, etc. The GSVA score also shows some predictive value for chemotherapy and immunotherapy efficacy in some tumors. CONCLUSIONS: PNPSA was correlated with tumor development and might be potential tumor biomarker and therapeutic target.
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