ArticleAnalytical chemistry2016
Combining NMR and LC/MS Using Backward Variable Elimination: Metabolomics Analysis of Colorectal Cancer, Polyps, and Healthy Controls.
Article in Analytical chemistry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 53 citations in OpenAlex.
- Colorectal neoplasia-specific amino acid profiles and their diagnostic potential: a systematic review.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Pooled it
- Oncometabolites in Cancer Metabolism: Mechanistic Insights and Biomarker Potential- A Narrative Review.Health science reports · 2026Article
- CALB2 Expression Is Associated with Tumor Progression and Prognosis in Colorectal Adenocarcinoma.Genes · 2026Article
- High-throughput metabolomics exploring the pharmacological effects and mechanism of icariin on rheumatoid arthritis rat based on ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry.Frontiers in molecular biosciences · 2025Article
- Multiple and Optimal Screening Subset: a method selecting global characteristic congeners for robust foodomics analysis.Briefings in bioinformatics · 2024Article
- Metabolic signatures and potential biomarkers for the diagnosis and treatment of colon cancer cachexia.Acta biochimica et biophysica Sinica · 2023Article
- Metabolomics with multi-block modelling of mass spectrometry and nuclear magnetic resonance in order to discriminate Haplosclerida marine sponges.Analytical and bioanalytical chemistry · 2022Article
- Plasma metabolomic profiles for colorectal cancer precursors in women.European journal of epidemiology · 2022Article
- Serum Colorectal Cancer Biomarkers Unraveled by NMR Metabolomics: Past, Present, and Future.Analytical chemistry · 2022Article
- Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives.Frontiers in molecular biosciences · 2021Review
- Integrating Two-Dimensional Gas and Liquid Chromatography-Mass Spectrometry for Untargeted Colorectal Cancer Metabolomics: A Proof-of-Principle Study.Metabolites · 2020Article
- Profiling of serum metabolites in advanced colon cancer using liquid chromatography-mass spectrometry.Oncology letters · 2020Article
- Identifying Significant Metabolic Pathways Using Multi-Block Partial Least-Squares Analysis.Journal of proteome research · 2020Article
- Polybrominated Diphenyl Ethers and Gut Microbiome Modulate Metabolic Syndrome-Related Aqueous Metabolites in Mice.Drug metabolism and disposition: the biological fate of chemicals · 2019Article
- Global serum metabolomics profiling of colorectal cancer.Molecular and clinical oncology · 2019Review
- An ensemble variable selection method for vibrational spectroscopic data analysis.RSC advances · 2019Article
- Comparative Analyses of Metabolomic Fingerprints and Cytotoxic Activities of Soft Corals from the Colombian Caribbean.Marine drugs · 2019Article
- Metabolomic Study on Nude Mice Models of Gastric Cancer Treated with Modified Si Jun Zi Tang via HILIC UHPLC-Q-TOF/MS Analysis.Evidence-based complementary and alternative medicine : eCAM · 2019Article
- Stratification of cancer and diabetes based on circulating levels of formate and glucose.Cancer & metabolism · 2019Article
- Integrated Serum and Fecal Metabolomics Study of Collagen-Induced Arthritis Rats and the Therapeutic Effects of the Zushima Tablet.Frontiers in pharmacology · 2018Article
Corrections and comments
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Authors and funding
7 authors at 4 institutions in 2 countries.
Funding
Abstract
Both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) play important roles in metabolomics. The complementary features of NMR and MS make their combination very attractive; however, currently the vast majority of metabolomics studies use either NMR or MS separately, and variable selection that combines NMR and MS for biomarker identification and statistical modeling is still not well developed. In this study focused on methodology, we developed a backward variable elimination partial least-squares discriminant analysis algorithm embedded with Monte Carlo cross validation (MCCV-BVE-PLSDA), to combine NMR and targeted liquid chromatography (LC)/MS data. Using the metabolomics analysis of serum for the detection of colorectal cancer (CRC) and polyps as an example, we demonstrate that variable selection is vitally important in combining NMR and MS data. The combined approach was better than using NMR or LC/MS data alone in providing significantly improved predictive accuracy in all the pairwise comparisons among CRC, polyps, and healthy controls. Using this approach, we selected a subset of metabolites responsible for the improved separation for each pairwise comparison, and we achieved a comprehensive profile of altered metabolite levels, including those in glycolysis, the TCA cycle, amino acid metabolism, and other pathways that were related to CRC and polyps. MCCV-BVE-PLSDA is straightforward, easy to implement, and highly useful for studying the contribution of each individual variable to multivariate statistical models. On the basis of these results, we recommend using an appropriate variable selection step, such as MCCV-BVE-PLSDA, when analyzing data from multiple analytical platforms to obtain improved statistical performance and a more accurate biological interpretation, especially for biomarker discovery. Importantly, the approach described here is relatively universal and can be easily expanded for combination with other analytical technologies.
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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 OpenQuestion graph.