ArticleFrontiers in pharmacology2022
Evaluation of Untargeted Metabolomic Strategy for the Discovery of Biomarker of Breast Cancer.
Article in Frontiers in pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 11 citations in OpenAlex.
- SMART 2.0 Statistical Metabolomics Analysis: An R Tool 2.0.Analytical chemistry · 2025Article
- Integrated plasma and red blood cell membrane lipidomics analysis unveils novel biomarker panel for Alzheimer's disease.Alzheimer's research & therapy · 2025Article
- Predictive analysis of breast cancer response to neoadjuvant chemotherapy through plasma metabolomics.Breast cancer research and treatment · 2024Article
- Assessment of Untargeted Metabolomics by Hydrophilic Interaction Liquid Chromatography-Mass Spectrometry to Define Breast Cancer Liquid Biopsy-Based Biomarkers in Plasma Samples.International journal of molecular sciences · 2024Article
- Fatty Acid Profile and Genetic Variants of Proteins Involved in Fatty Acid Metabolism Could Be Considered as Disease Predictor.Diagnostics (Basel, Switzerland) · 2023Review
- Study of the Chemical Composition and Biologically Active Properties ofLife (Basel, Switzerland) · 2022Article
- Untargeted stable isotope-resolved metabolomics to assess the effect of PI3Kβ inhibition on metabolic pathway activities in a PTEN null breast cancer cell line.Frontiers in molecular biosciences · 2022Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Discovery of disease biomarker based on untargeted metabolomics is informative for pathological mechanism studies and facilitates disease early diagnosis. Numerous of metabolomic strategies emerge due to different sample properties or experimental purposes, thus, methodological evaluation before sample analysis is essential and necessary. In this study, sample preparation, data processing procedure and metabolite identification strategy were assessed aiming at the discovery of biomarker of breast cancer. First, metabolite extraction by different solvents, as well as the necessity of vacuum-dried and re-dissolution, was investigated. The extraction efficiency was assessed based on the number of eligible components (components with MS/MS data acquired), which was more reasonable for metabolite identification. In addition, a simplified data processing procedure was proposed involving the OPLS-DA, primary screening for eligible components, and secondary screening with constraints including VIP, fold change and
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Registered trials
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