ArticleJournal of proteome research2014
Quantitative analysis of single amino acid variant peptides associated with pancreatic cancer in serum by an isobaric labeling quantitative method.
Article in Journal of proteome research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Solvent Interaction Analysis: A New Lens for Protein Structure and Diagnostics.International journal of molecular sciences · 2026Review
- A Multiplexed Quantitative Analysis of Germline Single Amino Acid Variants by Targeted Proteomics in Nondepleted Human Plasma.Journal of proteome research · 2026Article
- Multibiomarker panels in liquid biopsy for early detection of pancreatic cancer - a comprehensive review.Journal of experimental & clinical cancer research : CR · 2024Review
- Machine learning-based analysis identifies and validates serum exosomal proteomic signatures for the diagnosis of colorectal cancer.Cell reports. Medicine · 2024Article
- David M. Lubman-The University of Michigan-A retrospective in research.Mass spectrometry reviews · 2023Review
- Alpha-1-antichymotrypsin as a novel biomarker for diagnosis, prognosis, and therapy prediction in human diseases.Cancer cell international · 2022Review
- Personalized Proteome: Comparing Proteogenomics and Open Variant Search Approaches for Single Amino Acid Variant Detection.Journal of proteome research · 2021Article
- Comprehensive Detection of Single Amino Acid Variants and Evaluation of Their Deleterious Potential in a PANC-1 Cell Line.Journal of proteome research · 2020Article
- Bacterial DNA induces the formation of heat-resistant disease-associated proteins in human plasma.Scientific reports · 2019Observational
- Beyond Genes: Re-Identifiability of Proteomic Data and Its Implications for Personalized Medicine.Genes · 2019Review
- Single Amino Acid Variant Discovery in Small Numbers of Cells.Journal of proteome research · 2019Article
- Deep-Dive Targeted Quantification for Ultrasensitive Analysis of Proteins in Nondepleted Human Blood Plasma/Serum and Tissues.Analytical chemistry · 2017Article
- Single Amino Acid Variant Profiles of Subpopulations in the MCF-7 Breast Cancer Cell Line.Journal of proteome research · 2017Article
- A Timely Shift from Shotgun to Targeted Proteomics and How It Can Be Groundbreaking for Cancer Research.Frontiers in oncology · 2017Review
- Proteogenomics: Integrating Next-Generation Sequencing and Mass Spectrometry to Characterize Human Proteomic Variation.Annual review of analytical chemistry (Palo Alto, Calif.) · 2016Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Single amino acid variations are highly associated with many human diseases. The direct detection of peptides containing single amino acid variants (SAAVs) derived from nonsynonymous single nucleotide polymorphisms (SNPs) in serum can provide unique opportunities for SAAV associated biomarker discovery. In the present study, an isobaric labeling quantitative strategy was applied to identify and quantify variant peptides in serum samples of pancreatic cancer patients and other benign controls. The largest number of SAAV peptides to date in serum including 96 unique variant peptides were quantified in this quantitative analysis, of which five variant peptides showed a statistically significant difference between pancreatic cancer and other controls (p-value < 0.05). Significant differences in the variant peptide SDNCEDTPEAGYFAVAVVK from serotransferrin were detected between pancreatic cancer and controls, which was further validated by selected reaction monitoring (SRM) analysis. The novel biomarker panel obtained by combining α-1-antichymotrypsin (AACT), Thrombospondin-1 (THBS1) and this variant peptide showed an excellent diagnostic performance in discriminating pancreatic cancer from healthy controls (AUC = 0.98) and chronic pancreatitis (AUC = 0.90). These results suggest that large-scale analysis of SAAV peptides in serum may provide a new direction for biomarker discovery research.
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