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Citation Information
Cancer Treat Res Commun. 2018;14:1-6. doi: 10.1016/j.ctarc.2017.08.002. Epub 2017 Aug 19.
Diagnosis of lung tumor types based on metabolomic profiles in lymph node aspirates.
Sappington D, Helms S, Siegel E, Penney RB, Jeffus S, Bartter T, Bartter T, Boysen G.
Analytical methods | |||
|---|---|---|---|
| Comparative study | #1 | #2 | |
| Chromatography | LC | LC | |
| Ion source | ESI | ESI | |
| Positive/Negative mode | positive | positive | |
| Mass analyzer | Q-TOF | Q-TOF | |
| Identification level | MS/MS | MS/MS | |
Sample information | |||
|---|---|---|---|
| Comparative study | #1 | #2 | |
| Country | US | US | |
| Specimen | lymph node aspirates | lymph node aspirates | |
| Marker function | diagnosis | diagnosis | |
| Participants(Case) | Cancer type | adenocarcinoma, squamous cell carcinoma | adenocarcinoma |
| Stage | II, III, IV | II, III, IV | |
| Number | 50 | 31 | |
| Gender (M,F) | 31, 19 | 17, 14 | |
| Mean age (range) (M,F) | – | – | |
| Smoking status | – | – | |
| Participants(Control) | Type | non-malignant | squamous cell carcinoma |
| Number | 29 | 19 | |
| Gender (M,F) | 15, 14 | 14, 5 | |
| Mean age (range) (M,F) | – | – | |
| Smoking status | – | – | |
Data processing and metabolite identification | |
|---|---|
| Data processing software | MassHunter, MassProfilerProfessional |
| Database search | HMDB |
Statistical analysis | |
|---|---|
| Differential analysis method | OPLS-DA, PLS-DA |
| Classification method | – |
| Survival analysis method | – |
Lung cancer-related metabolites identified in the paper
| Metabolite | Author-emphasized biomarkers | Mean concentration (case) | Mean concentration (control) | Fold change (case/control) | P-value | FDR | VIP |
|---|---|---|---|---|---|---|---|
| reduced glutathione | V | – | – | 4.62 | 0.04 | – | – |
| oxidized glutathione | V | – | – | 2.53 | 9.00e-04 | – | – |
| oxidized glutathione | V | – | – | 1.57 | 0.17 | – | – |
| reduced glutathione | V | – | – | 1.54 | 0.57 | – | – |
| glutamate | V | – | – | 1.44 | 0.04 | – | – |
| kynurenine | V | – | – | 1.36 | 0.14 | – | – |
| glutamate | V | – | – | 1.10 | 0.74 | – | – |
| tryptophan | V | – | – | 0.98 | 0.92 | – | – |
| kynurenine | V | – | – | 0.97 | 0.92 | – | – |
| glutamine | V | – | – | 0.92 | 0.70 | – | – |
| glutamine | V | – | – | 0.69 | 7.60e-03 | – | – |
| tryptophan | V | – | – | 0.59 | 2.70e-03 | – | – |
| Metabolite | Author-emphasized biomarkers | Cutoff value | AUROC (95%CI) | Sensitivity (%) | Specificity (%) | Accuracy (%) |
|---|---|---|---|---|---|---|
| reduced glutathione | V | – | – | – | – | – |
| oxidized glutathione | V | – | – | – | – | – |
| oxidized glutathione | V | – | – | – | – | – |
| reduced glutathione | V | – | – | – | – | – |
| glutamate | V | – | – | – | – | – |
| kynurenine | V | – | – | – | – | – |
| glutamate | V | – | – | – | – | – |
| tryptophan | V | – | – | – | – | – |
| kynurenine | V | – | – | – | – | – |
| glutamine | V | – | – | – | – | – |
| glutamine | V | – | – | – | – | – |
| tryptophan | V | – | – | – | – | – |
Paper graphical summary
