Genetic variants in the metzincin metallopeptidase family genes predict melanoma survival. Issue 1 (28th August 2017)

• Record Type: Journal Article
• Authors: Xu, Yinghui; Wang, Yanru; Liu, Hongliang; Shi, Qiong; Zhu, Dakai; Amos, Christopher I.; Fang, Shenying; Lee, Jeffrey E.; Hyslop, Terry; Li, Xin; Han, Jiali; Wei, Qingyi
• Is Part Of: Molecular carcinogenesis. Volume 57:Issue 1(2018)
• Page Start: 22
• Page End: 31
• Publication Date: 2017-08-28
• Subjects: cutaneous melanoma -- cutaneous melanoma‐specific survival (CMSS) -- genome‐wide association study (GWAS) -- metzincins -- single‐nucleotide polymorphism (SNP); Carcinogenesis -- Molecular aspects -- Periodicals; 616.994071
• DOI: 10.1002/mc.22716
• Languages: English
• ISSNs: 0899-1987

Abstract

Abstract : Metzincins are key molecules in the degradation of the extracellular matrix and play an important role in cellular processes such as cell migration, adhesion, and cell fusion of malignant tumors, including cutaneous melanoma (CM). We hypothesized that genetic variants of the metzincin metallopeptidase family genes would be associated with CM‐specific survival (CMSS). To test this hypothesis, we first performed Cox proportional hazards regression analysis to evaluate the associations between genetic variants of 75 metzincin metallopeptidase family genes and CMSS using the dataset from the genome‐wide association study (GWAS) from The University of Texas MD Anderson Cancer Center (MDACC) which included 858 non‐Hispanic white patients with CM, and then validated using the dataset from the Harvard GWAS study which had 409 non‐Hispanic white patients with invasive CM. Four independent SNPs ( MMP16 rs10090371 C>A, ADAMTS3 rs788935 T>C, TLL2 rs10882807 T>C and MMP9 rs3918251 A>G) were identified as predictors of CMSS, with a variant‐allele attributed hazards ratio (HR) of 1.73 (1.32‐2.29, 9.68E‐05), 1.46 (1.15‐1.85, 0.002), 1.68 (1.31‐2.14, 3.32E‐05) and 0.67 (0.51‐0.87, 0.003), respectively, in the meta‐analysis of these two GWAS studies. Combined analysis of risk genotypes of these four SNPs revealed a decreased CMSS in a dose‐response manner as the number of risk genotypes increased ( P trend < 0.001). An improvement was observed in the prediction model (area under the curve [AUC] = 81.4% vs. 78.6%), when these risk genotypes were added to the model containing non‐genotyping variables. Our findings suggest that these genetic variants may be promising prognostic biomarkers for CMSS.