Distribution bias analysis of germline and somatic single-nucleotide variations that impact protein functional site and neighboring amino acids.
Single nucleotide variations (SNVs) can result in loss or gain of protein functional sites. We analyzed the effects of SNVs on enzyme active sites, ligand binding sites, and various types of post translational modification (PTM) sites. We found that, for most types of protein functional sites, the SNV pattern differs between germline and somatic mutations as well as between synonymous and non-synonymous mutations. From a total of 51,138 protein functional site affecting SNVs (pfsSNVs), a pan-cancer analysis revealed 142 somatic pfsSNVs in five or more cancer types. By leveraging patient information for somatic pfsSNVs, we identified 17 loss of functional site SNVs and 60 gain of functional site SNVs which are significantly enriched in patients with specific cancer types. Of the key pfsSNVs identified in our analysis above, we highlight 132 key pfsSNVs within 17 genes that are found in well-established cancer associated gene lists. For illustrating how key pfsSNVs can be prioritized further, we provide a use case where we performed survival analysis showing that a loss of phosphorylation site pfsSNV at position 105 in MEF2A is significantly associated with decreased pancreatic cancer patient survival rate. These 132 pfsSNVs can be used in developing genetic testing pipelines.
The Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
Yang
Y
Pan
The Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
Cheng
C
Yan
The Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
Yu
Y
Hu
The Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
Yu
Y
Fan
The Department of Statistics, The George Washington University, Washington, DC 20037, United States of America.
Qing
Q
Pan
The Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
Quan
Q
Wan
The Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.
John
J
Torcivia-Rodriguez
The Department of Biochemistry &Molecular Medicine, The George Washington University Medical Center, Washington, DC 20037, United States of America.|McCormick Genomic and Proteomic Center, The George Washington University, Washington, DC 20037, United States of America.
Raja
R
Mazumder
D000107:Acetylation; D020134:Catalytic Domain; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D063990:Gene Ontology; D018095:Germ-Line Mutation; D006031:Glycosylation; D006801:Humans; D008745:Methylation; D058977:Molecular Sequence Annotation; D009363:Neoplasm Proteins / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D009369:Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000401:mortality / Q000473:pathology; D010766:Phosphorylation; D020641:Polymorphism, Single Nucleotide; D011499:Protein Processing, Post-Translational; D016019:Survival Analysis; D054875:Ubiquitination
D009363:Neoplasm Proteins