ArticleAnalytical chemistry2025
AUTO-SP: Automated Sample Preparation for Analyzing Proteins and Protein Modifications.
Article in Analytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Article
- High-Sensitive Spatial Proteomics for Pancreatic Cancer Progression Analysis.Analytical chemistry · 2026Article
- Integrative Analysis of Fucosylated Tetra Glycoforms in Hepatocellular Carcinoma: A NanoLC-PRM-MS/MS and Machine Learning Approach.Journal of proteome research · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Liquid chromatography (LC) tandem mass spectrometry (MS/MS) is one of the widely used proteomic techniques to study the alterations occurring at the protein level as well as post-translational modifications (PTMs) of proteins that are relevant to different physiological or pathological statuses. The mass spectrometric analysis of peptides digested from proteins (bottom-up proteomics) has emerged as one of the major approaches for proteomics. In this approach, proteins are first cleaved by one or more proteases into peptides for MS analysis, and peptides with PTMs are further enriched, followed by the LC-MS/MS analysis. To achieve a reproducible and quantitative proteomic characterization, a well-established protease digestion and PTM peptide enrichment protocol is critical. In this study, we developed AUTO-SP, a sample preparation platform providing automated protocols for BCA analysis, protein digestion, and PTM enrichment for protein and PTM analyses. We utilized patient-derived xenograft (PDX) breast cancer tumor tissues (basal-like and luminal subtypes) to demonstrate the efficacy of AUTO-SP. The protein amount was quantified, and proteins were further digested by using AUTO-SP for each PDX sample. Based on the data-independent acquisition (DIA)-MS data, we observed that samples of the same breast cancer subtypes were highly correlated (≥0.98). Additionally, >25,000 phosphopeptides and >14,000 ubiquitinated peptides were identified in the PDX samples when using AUTO-SP for PTM enrichment, while unique pathways were enriched from the differentially expressed ubiquitinated peptides of basal-like and luminal subtypes. AUTO-SP demonstrated its efficacy to provide a reliable and reproducible sample preparation procedure for MS-based proteomic and PTM analyses.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.