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A disintegrin-like and metalloproteinase domain with thrombospondin type 1 motifs (ADAMTS)-like proteins, including ADAMTSL1-6 and papilin, which are part of the mammalian ADAMTS superfamily, appear to be relevant to extracellular matrix function and the regulation of ADAMTS protease activity. Their roles in tumor initiation and progression and regulating the tumor microenvironment (TME) are now recognized. In the present study, a comprehensive investigation of the pan-cancer effects of ADAMTSLs and their associations with patient survival, drug responses, and the TME was performed by integrating The Cancer Genome Atlas (TCGA) data and annotated data resources. The expression of ADAMTSL family members was found to be dysregulated in many cancer types. More importantly, their expression was frequently associated with patients' overall survival (OS), drug responses, and the TME. ADAMTSL1, ADAMTSL4, and ADAMTSL5 were primarily associated with aggressive phenotypes, while PAPLN was more frequently associated with a favorable prognosis. In a non-small cell lung cancer (NSCLC) cohort, Thrombospondin Type 1 Domain Containing 4 (THSD4) (ADAMTSL6) and Papilin (PAPLN) were associated with immune checkpoint inhibitor (ICI) sensitivity in samples from the Gene Expression Omnibus repository (GSE135222). Twenty and 30 proteins related to THSD4 and PAPLN, respectively, were identified through a proteomic analysis of 18 Chinese lung adenocarcinoma patients. Our findings extend understandings of the role of the ADAMTSL family in cancers and are a valuable resource on their clinical utility. This article provides insight into the clinical importance of next-generation sequencing technology to identify novel biomarkers for prognosis and investigate therapeutic strategy for clinical benefit. 2021 Annals of Translational Medicine. All rights reserved.

Citation

Xiaoyue Zhang, Wendi Yang, Kehong Chen, Taihao Zheng, Zhengjun Guo, Yuan Peng, Zhenzhou Yang. The potential prognostic values of the ADAMTS-like protein family: an integrative pan-cancer analysis. Annals of translational medicine. 2021 Oct;9(20):1562


PMID: 34790768

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