ArticleNPJ precision oncology2018
Adaptive metabolic pattern biomarker for disease monitoring and staging of lung cancer with liquid biopsy.
Article in NPJ precision oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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
4 citing papers in PubMed.
- Paper-based plasmonic substrates as surface-enhanced Raman scattering spectroscopy platforms for cell culture applications.Materials today. Bio · 2021Review
- Optimization of Tumor Disease Monitoring in Medical Big Data Environment Based on High-Order Simulated Annealing Neural Network Algorithm.Computational intelligence and neuroscience · 2021Article
- Present and Future of Surface-Enhanced Raman Scattering.ACS nano · 2020Article
- Review
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Authors and funding
9 authors.
Funding
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Abstract
In this manuscript, we demonstrate the applicability of a metabolic liquid biopsy for the monitoring and staging of patients with lung cancer. This method provides an unbiased detection strategy to establish a more precise correlation between CTC quantification and the actual burden of disease, therefore improving the accuracy of staging based on current imaging techniques. Also, by applying statistical analysis techniques and probabilistic models to the metabolic status and distribution of peripheral blood mononuclear cell (PBMC) populations "perturbed" by the presence of CTCs, a new category of adaptive metabolic pattern biomarker (AMPB) is described and unambiguously correlated to the different clinical stages of the patients. In fact, this strategy allows for classification of different categories of disease within a single stage (stage IV) before computed tomography (CT) and positron emission tomography (PET) scans and with lower uncertainty.
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Registered trials
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