Department of Molecular Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, United States.
Department of Chemical and Biomedical Engineering, College of Engineering, Research Computing, University of South Florida, Tampa, FL, United States.
Gene. 2018 Aug 30;669:91-98. doi: 10.1016/j.gene.2018.05.037. Epub 2018 May 17.
Human mutagenesis has a large stochastic component. Thus, large coding regions, especially cytoskeletal and extra-cellular matrix protein (CECMP) coding regions are particularly vulnerable to mutations. Recent results have verified a high level of somatic mutations in the CECMP coding regions in the cancer genome atlas (TCGA), and a relatively common occurrence of germline, deleterious mutations in the TCGA breast cancer dataset.
The objective of this study was to determine the correlations of CECMP coding region, germline nucleotide variations with both overall survival (OS) and disease-free survival (DFS). TCGA, tumor and blood variant calling files (VCFs) were intersected to identify germline SNVs. SNVs were then annotated to determine potential consequences for amino acid (AA) residue biochemistry.
Germline SNVs were matched against somatic tumor SNVs (i.e., tumor mutations) over twenty TCGA datasets to identify 23 germline-somatic matched, deleterious AA substitutions in coding regions for FLG, TTN, MUC4, and MUC17.
The germline-somatic matched SNVs, in particular for MUC4, extensively implicated in cancer development, represented highly, statistically significant effects on OS and DFS survival rates. The above results contribute to the establishment of what is potentially a new class of inherited cancer-facilitating genes, namely dominant negative tumor suppressor proteins.
人类诱变具有很大的随机成分。因此,大的编码区域,特别是细胞骨架和细胞外基质蛋白(CECMP)编码区域特别容易发生突变。最近的结果证实了癌症基因组图谱(TCGA)中 CECMP 编码区域存在高水平的体细胞突变,以及 TCGA 乳腺癌数据集中性突变的相对常见发生。
本研究的目的是确定 CECMP 编码区域、种系核苷酸变异与总生存(OS)和无病生存(DFS)的相关性。TCGA、肿瘤和血液变异调用文件(VCFs)被交叉以识别种系 SNVs。然后对 SNVs 进行注释,以确定对氨基酸(AA)残基生化的潜在影响。
种系 SNVs 与二十多个 TCGA 数据集的体细胞肿瘤 SNVs(即肿瘤突变)相匹配,以鉴定 FLG、TTN、MUC4 和 MUC17 编码区域中 23 个种系-体细胞匹配的、有害的 AA 取代。
种系-体细胞匹配的 SNVs,特别是在 MUC4 中,广泛涉及癌症的发生,对 OS 和 DFS 生存率有高度的、统计学显著的影响。上述结果有助于建立潜在的一类新的遗传性癌症促进基因,即显性负肿瘤抑制蛋白。