4.6 Article

dbPepVar: A Novel Cancer Proteogenomics Database

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IEEE ACCESS
卷 10, 期 -, 页码 90982-90994

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IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2022.3201897

关键词

Databases; Proteins; Cancer; Peptides; Genetics; Diseases; Amino acids; Biomarkers; Data analysis; Cancer proteomics; genetic variation; proteogenomic database

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This article introduces a proteogenomics database that identifies genetic variations in different cancer patients through a pan-cancer analysis. The database provides query and download functions for the data through an intuitive and dynamic web portal, which can be used to explore new therapeutic targets and characterize variations in samples with unknown genetic backgrounds.
Cancers arise from the acquisition of DNA mutations, such as substitutions, deletions, amplifications, and rearrangements. Understanding the distribution and correlation of such mutations in cancer may aid the characterization of the disease and subsequent identification of biomarkers for diagnosis and treatment. The proteogenomics database (dbPepVar) created here combines genetic variation information from dbSNP with protein sequences from NCBI's RefSeq. Public mass spectrometry datasets (Ovarian, Colorectal, Breast, and Prostate) were used to perform a pan-cancer analysis, allowing the identification of unique genetic variations. As a result, 3,726 variant peptides were identified in samples from patients with ovarian cancer, 2,543 in prostate, 2,661 in breast and 2,411 in colon-rectal cancer patients. Data resulting from the proteogenomics approach employed and connected to other biological databases is now available in an intuitive and dynamic web portal where novice users can explore general aspects of the dataset in graph or table format, or dive in to filter the data with click and select options or using more advanced queries with regex. All data can be downloaded in csv or pdf format. In perspective, the web portal developed may direct studies to identify new therapeutic targets for different cancers, and one can also use our database for characterization of variants in samples of unknown genetic background, such as archived samples.

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