title: Exome-driven characterization of the cancer cell lines at the proteome level: the NCI-60 case study.
abstract: Cancer genome deviates significantly from the reference human genome, and thus a search against standard genome databases in cancer cell proteomics fails to identify cancer-specific protein variants. The goal of this Article is to combine high-throughput exome data [Abaan et al. Cancer Res. 2013] and shotgun proteomics analysis [Modhaddas Gholami et al. Cell Rep. 2013] for cancer cell lines from NCI-60 panel to demonstrate further that the cell lines can be effectively recognized using identified variant peptides. To achieve this goal, we generated a database containing mutant protein sequences of NCI-60 panel of cell lines. The proteome data were searched using Mascot and X!Tandem search engines against databases of both reference and mutant protein sequences. The identification quality was further controlled by calculating a fraction of variant peptides encoded by the own exome sequence for each cell line. We found that up to 92.2% peptides identified by both search engines are encoded by the own exome. Further, we used the identified variant peptides for cell line recognition. The results of the study demonstrate that proteome data supported by exome sequence information can be effectively used for distinguishing between different types of cancer cell lines.
authors.affiliation: Orekhovich Institute of Biomedical Chemistry , 119121, Moscow, Russia.
authors.forename: Maria A
authors.initials: MA
authors.lastname: Karpova
authors.forename: Dmitry S
authors.initials: DS
authors.lastname: Karpov
authors.forename: Mark V
authors.initials: MV
authors.lastname: Ivanov
authors.forename: Mikhail A
authors.initials: MA
authors.lastname: Pyatnitskiy
authors.forename: Alexey L
authors.initials: AL
authors.lastname: Chernobrovkin
authors.forename: Anna A
authors.initials: AA
authors.lastname: Lobas
authors.forename: Andrey V
authors.initials: AV
authors.lastname: Lisitsa
authors.forename: Alexander I
authors.initials: AI
authors.lastname: Archakov
authors.forename: Mikhail V
authors.initials: MV
authors.lastname: Gorshkov
authors.forename: Sergei A
authors.initials: SA
authors.lastname: Moshkovskii
mesh_terms: D000595:Amino Acid Sequence; D014408:Biomarkers, Tumor / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*; D045744:Cell Line, Tumor; D059472:Exome; D006801:Humans; D020125:Mutation, Missense; D010446:Peptide Fragments / Q000737:chemistry; D020641:Polymorphism, Single Nucleotide; D020543:Proteome / Q000737:chemistry / Q000235:genetics / Q000378:metabolism*
chemical_list: D014408:Biomarkers, Tumor; D010446:Peptide Fragments; D020543:Proteome
keywords: cancer cell line; cancer proteomics; exome; mutant proteins; protein identification algorithm; proteome; shotgun proteomics; variant peptides