کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5649340 | 1407122 | 2017 | 29 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Genetic Variants in WNT2B and BTRC Predict Melanoma Survival
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کلمات کلیدی
موضوعات مرتبط
علوم پزشکی و سلامت
پزشکی و دندانپزشکی
امراض پوستی
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چکیده انگلیسی
Cutaneous melanoma (CM) is the most lethal skin cancer. The Wnt pathway has an impact on development, invasion, and metastasis of CM, thus likely affecting CM prognosis. Using data from a published genome-wide association study from The University of Texas MD Anderson Cancer Center, we assessed the associations of 19,830 common single-nucleotide polymorphisms (SNPs) in 151 Wnt pathway autosomal genes with CM-specific survival and then validated significant SNPs in another genome-wide association study from Harvard University. In the single-locus analysis, 1,855 SNPs were significantly associated with CM-specific survival at P < 0.05, of which 547 SNPs were still considered noteworthy after the correction by the false-positive report probability. In the replication, two SNPs remained significantly associated with CM-specific survival after multiple comparison correction. By performing functional prediction and stepwise selection, we identified two independent SNPs (i.e., WNT2B rs1175649 G>T and BTRC rs61873997 G>A) that showed a predictive role in CM-specific survival, with an effect-allele-attributed hazards ratio (adjusted hazards ratio) of 1.99 (95% confidence interval = 1.41-2.81, P = 8.10 à 10â5) and 0.61 (0.46-0.80, 3.12Ã10â4), respectively. Collectively, these variants in the Wnt pathway genes may be biomarkers for outcomes of patients with CM, if validated by larger studies.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Investigative Dermatology - Volume 137, Issue 8, August 2017, Pages 1749-1756
Journal: Journal of Investigative Dermatology - Volume 137, Issue 8, August 2017, Pages 1749-1756
نویسندگان
Qiong Shi, Hongliang Liu, Peng Han, Chunying Li, Yanru Wang, Wenting Wu, Dakai Zhu, Christopher I. Amos, Shenying Fang, Jeffrey E. Lee, Jiali Han, Qingyi Wei,