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Citation Information
Onco Targets Ther. 2016 Apr 26;9:2479-87. doi: 10.2147/OTT.S99099. eCollection 2016.
Tandem mass spectrometry-based newborn screening strategy could be used to facilitate rapid and sensitive lung cancer diagnosis.
Huang T, Cao Y, Zeng J, Dong J, Sun X, Chen J, Gao P.
Analytical methods | |||
|---|---|---|---|
| Comparative study | #1 | #2 | |
| Chromatography | LC | LC | |
| Ion source | ESI | ESI | |
| Positive/Negative mode | positive | positive | |
| Mass analyzer | QTrap | QTrap | |
| Identification level | MS/MS | MS/MS | |
Sample information | |||
|---|---|---|---|
| Comparative study | #1 | #2 | |
| Country | China | China | |
| Specimen | dried blood spot | dried blood spot | |
| Marker function | diagnosis | diagnosis | |
| Participants(Case) | Cancer type | lung cancer | benign lung disease |
| Stage | – | – | |
| Number | 222 | 118 | |
| Gender (M,F) | 94, 128 | 55, 63 | |
| Mean age (range) (M,F) | median: 57.47 (27-81) | median: 59.61 (32-80) | |
| Smoking status | – | – | |
| Participants(Control) | Type | healthy | healthy |
| Number | 96 | 96 | |
| Gender (M,F) | 30, 66 | 30, 66 | |
| Mean age (range) (M,F) | median: 56.07 (32-80) | median: 56.07 (32-80) | |
| Smoking status | – | – | |
Data processing and metabolite identification | |
|---|---|
| Data processing software | Analyst software, ChemoView software |
| Database search | – |
Statistical analysis | |
|---|---|
| Differential analysis method | PLS-DA, ANOVA, student’s t-test |
| 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 |
|---|---|---|---|---|---|---|---|
| Arg | V | – | – | – | 1.00e-03 | – | – |
| Arg | V | – | – | – | 1.00e-03 | – | – |
| C10:1 | V | – | – | – | 1.00e-03 | – | – |
| C12 | – | – | – | – | 1.00e-03 | – | – |
| C14 | – | – | – | – | 1.00e-03 | – | – |
| C14:1 | – | – | – | – | 1.00e-03 | – | – |
| C5DC | – | – | – | – | 1.00e-03 | – | – |
| C5-OH/C0 | V | – | – | – | 1.00e-03 | – | – |
| Pro | V | – | – | – | 1.00e-03 | – | – |
| C12 | – | – | – | – | 0.04 | – | – |
| Pro | V | – | – | – | 0.04 | – | – |
| C14:1 | – | – | – | – | 0.03 | – | – |
| C10:1 | V | – | – | – | 0.03 | – | – |
| C14 | – | – | – | – | 0.02 | – | – |
| Pip | – | – | – | – | 0.02 | – | – |
| C5DC | – | – | – | – | 0.02 | – | – |
| Hcy | – | – | – | – | 9.00e-03 | – | – |
| C5-OH/C0 | V | – | – | – | 5.00e-03 | – | – |
| Pip | – | – | – | – | 3.00e-03 | – | – |
| Hcy | – | – | – | – | 2.00e-03 | – | – |
| Metabolite | Author-emphasized biomarkers | Cutoff value | AUROC (95%CI) | Sensitivity (%) | Specificity (%) | Accuracy (%) |
|---|---|---|---|---|---|---|
| Arg | V | – | – | – | – | – |
| Arg | V | – | – | – | – | – |
| C10:1 | V | – | – | – | – | – |
| C12 | – | – | – | – | – | – |
| C14 | – | – | – | – | – | – |
| C14:1 | – | – | – | – | – | – |
| C5DC | – | – | – | – | – | – |
| C5-OH/C0 | V | – | – | – | – | – |
| Pro | V | – | – | – | – | – |
| C12 | – | – | – | – | – | – |
| Pro | V | – | – | – | – | – |
| C14:1 | – | – | – | – | – | – |
| C10:1 | V | – | – | – | – | – |
| C14 | – | – | – | – | – | – |
| Pip | – | – | – | – | – | – |
| C5DC | – | – | – | – | – | – |
| Hcy | – | – | – | – | – | – |
| C5-OH/C0 | V | – | – | – | – | – |
| Pip | – | – | – | – | – | – |
| Hcy | – | – | – | – | – | – |
Paper graphical summary
