ArticleJournal of proteome research2020
Comprehensive Detection of Single Amino Acid Variants and Evaluation of Their Deleterious Potential in a PANC-1 Cell Line.
Article in Journal of proteome research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- Polysomal Profiling Coupled to Allele-Specific Proteomics Reveals an EIF4H TranSNP Allele Possessing Higher mRNA Translation Potential.Molecular & cellular proteomics : MCP · 2026Article
- IsoPS-DIA: Dual Functionality of Absolute Targeted Quantification and Global Proteome Profiling.Analytical chemistry · 2026Article
- Fit for Purpose Approach To Evaluate Detection of Amino Acid Substitutions in Shotgun Proteomics.Journal of proteome research · 2024Article
- Recent advances (2019-2021) of capillary electrophoresis-mass spectrometry for multilevel proteomics.Mass spectrometry reviews · 2023Review
- David M. Lubman-The University of Michigan-A retrospective in research.Mass spectrometry reviews · 2023Review
- Deep top-down proteomics revealed significant proteoform-level differences between metastatic and nonmetastatic colorectal cancer cells.Science advances · 2022Article
- Article
- Personalized Proteome: Comparing Proteogenomics and Open Variant Search Approaches for Single Amino Acid Variant Detection.Journal of proteome research · 2021Article
Corrections and comments
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Authors and funding
13 authors at 8 institutions in 2 countries.
Funding
Abstract
Identifying single amino acid variants (SAAVs) in cancer is critical for precision oncology. Several advanced algorithms are now available to identify SAAVs, but attempts to combine different algorithms and optimize them on large data sets to achieve a more comprehensive coverage of SAAVs have not been implemented. Herein, we report an expanded detection of SAAVs in the PANC-1 cell line using three different strategies, which results in the identification of 540 SAAVs in the mass spectrometry data. Among the set of 540 SAAVs, 79 are evaluated as deleterious SAAVs based on analysis using the novel AssVar software in which one of the driver mutations found in each protein of KRAS, TP53, and SLC37A4 is further validated using independent selected reaction monitoring (SRM) analysis. Our study represents the most comprehensive discovery of SAAVs to date and the first large-scale detection of deleterious SAAVs in the PANC-1 cell line. This work may serve as the basis for future research in pancreatic cancer and personal immunotherapy and treatment.
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Registered trials
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