ArticleCancer research2017
Metabolic Markers and Statistical Prediction of Serous Ovarian Cancer Aggressiveness by Ambient Ionization Mass Spectrometry Imaging.
Article in Cancer research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers.
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Who cites it
65 citing papers in PubMed, 119 citations in OpenAlex.
- Structural Remodeling of Mitochondrial Membranes in Cancerous Colon Cells: Insights from Neutron Scattering and Lipidomics.ACS bio & med chem Au · 2026Article
- Bis(4-(1,3-benzoxazol-2-yl)) phenyl analogues as novel matrices for Fourier transform ion cyclotron resonance mass spectrometric imaging of lipids in dual ion mode in vulvar squamous cell carcinomas.Analytical and bioanalytical chemistry · 2026Article
- Intraoperative Mass Spectrometry in Oncology: Technologies, Clinical Applications, and Challenges.Molecules (Basel, Switzerland) · 2026Review
- Structure-preserving multivariate hypothesis testing for mass spectrometry imaging and single-cell data.Bioinformatics (Oxford, England) · 2026Article
- Multi-Modal Metabolomics Deciphers Pan-Cancer Metabolic Landscapes and Spatial-Niche-Specific Alternations.Metabolites · 2026Article
- Matrix-Assisted Laser Desorption/Ionization Imaging Mass Spectrometry.Nature reviews. Methods primers · 2026Article
- Review
- Metabolomic Analysis of Histological Composition Variability of High-Grade Serous Ovarian Cancer UsingInternational journal of molecular sciences · 2024Article
- A Workflow for Meaningful Interpretation of Classification Results from Handheld Ambient Mass Spectrometry Analysis Probes.International journal of molecular sciences · 2024Review
- CD133, CD47, and PD-L1 Expression in Ovarian High-grade Serous Carcinoma and Its Association with Metastatic Disease: A Cross-sectional Study.Asian Pacific journal of cancer prevention : APJCP · 2024Article
- Analysis of Three Species ofInternational journal of molecular sciences · 2023Article
- In situ profiling reveals metabolic alterations in the tumor microenvironment of ovarian cancer after chemotherapy.NPJ precision oncology · 2023Article
- Aggregated Molecular Phenotype Scores: Enhancing Assessment and Visualization of Mass Spectrometry Imaging Data for Tissue-Based Diagnostics.Analytical chemistry · 2023Article
- Identification of Diagnostic Metabolic Signatures in Thyroid Tumors Using Mass Spectrometry Imaging.Molecules (Basel, Switzerland) · 2023Article
- An Investigation into the Acute and Subacute Toxicity of Extracts ofPlants (Basel, Switzerland) · 2023Article
- Characterisation of hepatic lipid signature distributed across the liver zonation using mass spectrometry imaging.JHEP reports : innovation in hepatology · 2023Article
- Metabolically Active Zones Involving Fatty Acid Elongation Delineated by DESI-MSI Correlate with Pathological and Prognostic Features of Colorectal Cancer.Metabolites · 2023Article
- Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models.Frontiers in chemistry · 2023Article
- Metabolic signature ofFrontiers in veterinary science · 2023Article
- Mass spectrometry imaging in gynecological cancers: the best is yet to come.Cancer cell international · 2022Review
5 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
Abstract
Ovarian high-grade serous carcinoma (HGSC) results in the highest mortality among gynecological cancers, developing rapidly and aggressively. Dissimilarly, serous borderline ovarian tumors (BOT) can progress into low-grade serous carcinomas and have relatively indolent clinical behavior. The underlying biological differences between HGSC and BOT call for accurate diagnostic methodologies and tailored treatment options, and identification of molecular markers of aggressiveness could provide valuable biochemical insights and improve disease management. Here, we used desorption electrospray ionization (DESI) mass spectrometry (MS) to image and chemically characterize the metabolic profiles of HGSC, BOT, and normal ovarian tissue samples. DESI-MS imaging enabled clear visualization of fine papillary branches in serous BOT and allowed for characterization of spatial features of tumor heterogeneity such as adjacent necrosis and stroma in HGSC. Predictive markers of cancer aggressiveness were identified, including various free fatty acids, metabolites, and complex lipids such as ceramides, glycerophosphoglycerols, cardiolipins, and glycerophosphocholines. Classification models built from a total of 89,826 individual pixels, acquired in positive and negative ion modes from 78 different tissue samples, enabled diagnosis and prediction of HGSC and all tumor samples in comparison with normal tissues, with overall agreements of 96.4% and 96.2%, respectively. HGSC and BOT discrimination was achieved with an overall accuracy of 93.0%. Interestingly, our classification model allowed identification of three BOT samples presenting unusual histologic features that could be associated with the development of low-grade carcinomas. Our results suggest DESI-MS as a powerful approach for rapid serous ovarian cancer diagnosis based on altered metabolic signatures.
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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.