Magnetic Resonance Spectroscopy-based Metabolomic Biomarkers for Typing, Staging, and Survival Estimation of Early-Stage Human Lung Cancer.
Yannick BerkerLindsey A VandergriftIsabel WagnerLi SuJohannes KurthAndreas SchulerSarah S DingesPiet HabbelJohannes NowakEugene MarkMartin J AryeeDavid C ChristianiLeo L ChengPublished in: Scientific reports (2019)
Low-dose CT has shown promise in detecting early stage lung cancer. However, concerns about the adverse health effects of radiation and high cost prevent its use as a population-wide screening tool. Effective and feasible screening methods to triage suspicious patients to CT are needed. We investigated human lung cancer metabolomics from 93 paired tissue-serum samples with magnetic resonance spectroscopy and identified tissue and serum metabolomic markers that can differentiate cancer types and stages. Most interestingly, we identified serum metabolomic profiles that can predict patient overall survival for all cases (p = 0.0076), and more importantly for Stage I cases alone (n = 58, p = 0.0100), a prediction which is significant for treatment strategies but currently cannot be achieved by any clinical method. Prolonged survival is associated with relative overexpression of glutamine, valine, and glycine, and relative suppression of glutamate and lipids in serum.
Keyphrases
- early stage
- low dose
- endothelial cells
- computed tomography
- end stage renal disease
- emergency department
- healthcare
- public health
- newly diagnosed
- free survival
- ejection fraction
- chronic kidney disease
- lymph node
- image quality
- mass spectrometry
- case report
- high dose
- high resolution
- fatty acid
- risk assessment
- magnetic resonance imaging
- deep learning
- peritoneal dialysis
- big data
- health information
- squamous cell
- lymph node metastasis
- electronic health record
- rectal cancer