ReviewMagnetic resonance insights2014
MRS-based Metabolomics in Cancer Research.
Review in Magnetic resonance insights, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02838862 (Identification of Biomarker Profiles for Individualized Prognostic Stratification and Therapy in Patients With Gastroenteropancreatic Neuroendocrine Neoplasia), which is not on this map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
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.
Identification of Biomarker Profiles for Individualized Prognostic Stratification and Therapy in Patients With Gastroenteropancreatic Neuroendocrine Neoplasia (GEP-NEN)
Who cites it
16 citing papers in PubMed, 23 citations in OpenAlex.
- NMR Based Methods for Metabolites Analysis.Analytical chemistry · 2025Review
- Review
- Metabolic Disturbances in a Mouse Model of MPTP/Probenecid-Induced Parkinson's Disease: Evaluation Using Liquid Chromatography-Mass Spectrometry.Neuropsychiatric disease and treatment · 2024Article
- Correlation of MR-Based Metabolomics and Molecular Profiling in the Tumor Microenvironment of Temozolomide-Treated Orthotopic GL261 Glioblastoma in Mice.International journal of molecular sciences · 2023Article
- Recent advances in understanding brain cancer metabolomics: a review.Medical oncology (Northwood, London, England) · 2023Review
- SABRE hyperpolarized anticancer agents for use inMagnetic resonance in medicine · 2022Article
- MR spectroscopy in breast cancer metabolomics.Analytical science advances · 2021Review
- Role of magnetic resonance spectroscopy in differential diagnosis of solitary pulmonary lesions.Diagnostic and interventional radiology (Ankara, Turkey) · 2021Article
- 3T magnetic resonance spectroscopy as a powerful diagnostic modality for assessment of thyroid nodules.Archives of endocrinology and metabolism · 2018Article
- Breast Tissue Metabolism by Magnetic Resonance Spectroscopy.Metabolites · 2017Review
- Transverse Relaxation Rate of Cyst Fluid Can Predict Malignant Transformation of Ovarian Endometriosis.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2017Article
- Diagnostic Applications of Nuclear Magnetic Resonance-Based Urinary Metabolomics.Magnetic resonance insights · 2017Review
- On metabolic reprogramming and tumor biology: A comprehensive survey of metabolism in breast cancer.Oncotarget · 2016Review
- The therapy of gefitinib towards breast cancer partially through reversing breast cancer biomarker arginine.African health sciences · 2015Article
- Biomarkers in preclinical cancer imaging.European journal of nuclear medicine and molecular imaging · 2015Review
- Novel Approaches to Imaging Tumor Metabolism.Cancer journal (Sudbury, Mass.)Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metabolomics is a relatively new technique that is gaining importance very rapidly. MRS-based metabolomics, in particular, is becoming a useful tool in the study of body fluids, tissue biopsies and whole organisms. Advances in analytical techniques and data analysis methods have opened a new opportunity for such technology to contribute in the field of diagnostics. In the MRS approach to the diagnosis of disease, it is important that the analysis utilizes all the essential information in the spectra, is robust, and is non-subjective. Although some of the data analytic methods widely used in chemical and biological sciences are sketched, a more extensive discussion is given of a 5-stage Statistical Classification Strategy. This proposes powerful feature selection methods, based on, for example, genetic algorithms and novel projection techniques. The applications of MRS-based metabolomics in breast cancer, prostate cancer, colorectal cancer, pancreatic cancer, hepatobiliary cancers, gastric cancer, and brain cancer have been reviewed. While the majority of these applications relate to body fluids and tissue biopsies, some in vivo applications have also been included. It should be emphasized that the number of subjects studied must be sufficiently large to ensure a robust diagnostic classification. Before MRS-based metabolomics can become a widely used clinical tool, however, certain challenges need to be overcome. These include manufacturing user-friendly commercial instruments with all the essential features, and educating physicians and medical technologists in the acquisition, analysis, and interpretation of metabolomics data.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.