ArticleJournal of cancer research and clinical oncology2022
Subtyping non-small cell lung cancer by histology-guided spatial metabolomics.
Article in Journal of cancer research and clinical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.
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Who cites it
27 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Driving innovations in cancer research through spatial metabolomics: a bibliometric review of trends and hotspot.Frontiers in immunology · 2025Pooled it
- Diagnostic value of miR-200 family in non-small cell lung cancer: a meta-analysis.Biomarkers in medicine · 2024Pooled it
- A new era of precision diagnosis and treatment for lung cancer: artificial intelligence-driven multimodal data integration and clinical applications.Cell death & disease · 2026Review
- Radiomics-machine learning model for predicting invasiveness of subcentimeter subsolid lung adenocarcinoma: a validation study with external cohort and SHAP interpretability.Frontiers in oncology · 2026Article
- Metabolic heterogeneity in tumor cells impacts immunology in lung squamous cell carcinoma.Oncoimmunology · 2025Article
- [Applications and Advances of Metabolomics in Lung Cancer Research].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025Review
- Integrated spatial omics of metabolic reprogramming and the tumor microenvironment in pancreatic cancer.iScience · 2025Article
- Recent Developments in Single-Cell Metabolomics by Mass Spectrometry─A Perspective.Journal of proteome research · 2025Review
- Optical sensor for fast and accurate lung cancer detection with tissue autofluorescence and diffuse reflectance spectroscopy.Thoracic cancer · 2025Article
- Fuel for thought: targeting metabolism in lung cancer.Translational lung cancer research · 2024Review
- Article
- Mass spectrometry imaging methods for visualizing tumor heterogeneity.Current opinion in biotechnology · 2024Review
- Predictors of disease recurrence after radical resection and adjuvant chemotherapy in patients with stage IIb-IIIa squamous cell lung cancer: A retrospective analysis.World journal of experimental medicine · 2024Article
- Extracellular Vesicles and Exosomes: Novel Insights and Perspectives on Lung Cancer from Early Detection to Targeted Treatment.Biomedicines · 2024Review
- Metabolomics Analysis and Diagnosis of Lung Cancer: Insights from Diverse Sample Types.International journal of medical sciences · 2024Review
- Spatial metabolomics identifies distinct tumor-specific and stroma-specific subtypes in patients with lung squamous cell carcinoma.NPJ precision oncology · 2023Article
- The Warburg Effect Explained: Integration of Enhanced Glycolysis with Heterogeneous Mitochondria to Promote Cancer Cell Proliferation.International journal of molecular sciences · 2023Review
- Advancing Understanding of Non-Small Cell Lung Cancer with Multiplexed Antibody-Based Spatial Imaging Technologies.Cancers · 2023Review
- Review
- Supervised topological data analysis for MALDI mass spectrometry imaging applications.BMC bioinformatics · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeMost cancer-related deaths worldwide are associated with lung cancer. Subtyping of non-small cell lung cancer (NSCLC) into adenocarcinoma (AC) and squamous cell carcinoma (SqCC) is of importance, as therapy regimes differ. However, conventional staining and immunohistochemistry have their limitations. Therefore, a spatial metabolomics approach was aimed to detect differences between subtypes and to discriminate tumor and stroma regions in tissues.
methodsFresh-frozen NSCLC tissues (n = 35) were analyzed by matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) of small molecules (< m/z 1000). Measured samples were subsequently stained and histopathologically examined. A differentiation of subtypes and a discrimination of tumor and stroma regions was performed by receiver operating characteristic analysis and machine learning algorithms.
resultsHistology-guided spatial metabolomics revealed differences between AC and SqCC and between NSCLC tumor and tumor microenvironment. A diagnostic ability of 0.95 was achieved for the discrimination of AC and SqCC. Metabolomic contrast to the tumor microenvironment was revealed with an area under the curve of 0.96 due to differences in phospholipid profile. Furthermore, the detection of NSCLC with rarely arising mutations of the isocitrate dehydrogenase (IDH) gene was demonstrated through 45 times enhanced oncometabolite levels.
conclusionMALDI-MSI of small molecules can contribute to NSCLC subtyping. Measurements can be performed intraoperatively on a single tissue section to support currently available approaches. Moreover, the technique can be beneficial in screening of IDH-mutants for the characterization of these seldom cases promoting the development of treatment strategies.
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