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

Abstract

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.

Keywords

• extracellular matrix (ecm)
• adamts
• prognosis
• tumor immune microenvironment (time)
• signaling pathways
• drug sensitivities