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Germline Cytoskeletal and ECM Single Nucleotide Variations (SNVs) are Associated with Distinct Survival Rates: The Prominence of MUC4 Germline SNVs
EP27105
Poster Title: Germline Cytoskeletal and ECM Single Nucleotide Variations (SNVs) are Associated with Distinct Survival Rates: The Prominence of MUC4 Germline SNVs
Submitted on 08 Feb 2018
Author(s): Shayan Falasiri, George Blanck
Affiliations: : USF Health Morsani College of Medicine, Tampa, FL
This poster was presented at USF Research Day 2018
Poster Views: 485
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Poster Information
Abstract: 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 caSummary: This project focused on creating workflows capable of identifying tumor and blood genomic pairs in the GDC, downloading them, calling variants on those genomes with respect to hg38, removing known SNPs, intersecting those variants to determine variations present in the germline, and determining biochemical effects on amino acid residues. The project was scaled up to include 20 TCGA datasets, including 7,241 patients. Somatic data was intersected with germline and then mapped to clinical data.References: 1. Narsing S, Jelsovsky Z, Mbah A, Blanck G. Genes that contribute to cancer fusion genes are large and evolutionarily conserved. Cancer genetics and cytogenetics. 2009;191(2):78-84. doi: 10.1016/j.cancergencyto.2009.02.004. PubMed PMID: 19446742.
2. Pava LM, Morton DT, Chen R, Blanck G. Unifying the genomics-based classes of cancer fusion gene partners: large cancer fusion genes are evolutionarily conserved. Cancer genomics & proteomics. 2012;9(6):389-95. PubMed PMID: 23162078.
3. Long K, Abuelenen T, Pava L, Bastille M, Blanck G. Size matters: sequential mutations in tumorigenesis may reflect the stochastic effect of mutagen target sizes. Genes & cancer. 2011;2(10):927-31. doi: 10.1177/1947601911436200. PubMed PMID: 22701759; PubMed Central PMCID: PMC3374629.
4. Parry ML, Blanck G. Flat cells come full sphere: Are mutant cytoskeletal-related proteins oncoprotein-monsters or useful immunogens? Human vaccines & immunotherapeutics. 2015:0. doi: 10.1080/21645515.2015.1073428.
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