Table 1.
Cancer Type | Analytical Approach |
Biomarker’s Candidates/ Findings |
Prediction Model | Validation Characteristics | Reference |
---|---|---|---|---|---|
Urine | |||||
Pancreatic | TD-GC-TOF-MS GC-IMS |
2,6-Dimethyl-octane, nonanal, 4-ethyl-1,2-dimethyl-benzene, 2-pentanone | Repeated 10-Fold CV |
NA | [16] |
Bladder, prostate | GC-TOF-MS and GC-IMS | 35 VOMs | ROC, Repeated 10-Fold CV | GC-IMS Sens: 87% Spec: 92% AUC: 0.95 |
[17] |
Prostate | Urine HS conditioning, followed by e-nose analysis | The e-nose detected alterations in the urine volatilome associated with PCa | ROC | Sens: 85% Spec: 79% AUC: 0.82 |
[18] |
Prostate | Urine HS conditioning, followed by e-nose analysis (Cyranose C320) | The e-nose discriminated the urine smell prints of patients with PCa from healthy controls | PCA, ROC |
Sens: 83% Spec: 88% AUC: 0.90 |
[19] |
Prostate | Urine HS conditioning, followed by e-nose analysis | The e-nose discriminated patients with PCa from healthy controls | PCA | Sens: 82% Spec: 87% AUC: NA |
[20] |
Pancreatic ductal adenocarcinoma | HiSorb probes coupled with GC-TOF-MS | 2-Pentanone, hexanal, 3-hexanone, p-cymene | PLS-DA | AUC: 0.82 CER: 0.18 |
[21] |
Breast | GC-MS analysis of the urine HS. Sample’s smell print by the e-nose prototype | The e-nose software discriminated between early stage breast cancer and healthy controls | Artificial intelligence-based algorithm: CNN | Sens: 100% Spec: 50% Classification rate: 75% |
[22] |
Bladder | HS-SPME/GCxGC TOF-MS | Butyrolactone, 2-methoxyphenol, 3-methoxy-5-methylphenol, 1-(2,6,6-trimethylcyclohexa-1,3-dien-1-yl)-2-buten-1-one, nootkatone, 1-(2,6,6-trimethyl-1-cyclohexenyl)-2-buten-1-one | ANN | NA | [23] |
Lung | GC-IMS | 2-Pentanone, 2-hexenal, 2-hexen-1-ol, hept-4-en-2-ol, 2-heptanone, 3-octen-2-one, 4-methylpentanol, 4-methyl-octane | SVM | GC-IMS Sens: 85% Spec: 90% AUC: 0.91 |
[24] |
Exhaled breath | |||||
Colorectal | Thermal desorption-GC-TOF-MS | 10 VOMs distinguished advanced adenomas from negative controls. Colorectal cancer patients and advanced adenoma combined were discriminated from controls | RF | Colorectal cancer vs. controls Sens: 80% Spec: 70% |
[25] |
Gastric | PTR-TOF-MS | Propanal, aceticamide, isoprene, 1,3-propanediol | ROC | Sens: 61% Spec: 94% AUC: 0.842 |
[26] |
Breast | SIFT-MS | 3,7-Dimethyl-2,6-octadien-1-ol, ethanolamine, ethyl nonanoate | PCA, MLR |
Sens: 86.3% Spec: 55.6% |
[27] |
Hepatocellular | SPME/GC-MS | Phenol 2,2 methylene bis [6-(1,1-dimethyl ethyl)-4-methyl] (MBMBP) | PCA | NA | [28] |
Lung | HPPI-TOFMS | Isoprene, hexanal, pentanal, propylcyclohexane, nonanal, 2,2-dimethyldecane, heptanal, decanal | Hosmer–Lemeshow test | Sens: 86% Spec: 87.2% Acc: 86.9% AUC: 0.931 |
[29] |
Hepatocellular carcinoma | HS-SPME/GC-MS | Acetone, 1,4-pentadiene, methylene chloride, benzene, phenol, allyl methyl sulfide | SVM | Sens: 44% Spec: 75% Acc: 55.4% |
[30] |
Saliva | |||||
Oral | HS-SPME/GC-MS | 1-Octen-3-ol, hexanoic acid, E-2-octenal, heptanoic acid, octanoic acid, E-2-nonenal, nonanoic acid, 2,4-decadienal, 9-undecenoic acid | PCA | Sens: 100% Spec: 100% AUC: 1 |
[31] |
Stomach and colorectal cancer | Capillary GC-FID | Acetaldehyde, acetone, 2-propanol, ethanol | CART | Sens: 95.7% Spec: 90.9% |
[32] |
Oral squamous cell carcinoma | Thin-film microextraction based on a ZSM-5/polydimethylsiloxane hybrid film coupled with GC-MS | 12 VOMs | PCA | Sens: 95.8% Spec: 94% |
[33] |
Legend: Acc: accuracy; ANN: artificial neural networks; AUC: area under the receiver operating characteristic (ROC) curve; CART: classification and regression tree; CER: classification error rate; CNN: convolutional neural network; CV: cross-validation; GC-IMS: gas chromatography–ion migration spectroscopy; GC-MS: gas chromatography–mass spectrometry; GC-TOF-MS: gas chromatography coupled to time-of-flight mass spectrometry; HPPI-TOFMS: high-pressure photon ionization time-of-flight mass spectrometry; HS: headspace; HS-SPME: headspace solid-phase microextraction; MLR: multiple logistic regression; NA: not analyzed; PCa: prostate cancer; PCA: principal component analysis; PLS-DA: partial least-squares discriminant analysis; PTR-TOF-MS: proton-transfer-reaction time-of-flight mass spectrometry; RF: random forest; ROC: receiver operating characteristic; Sens: sensitivity; SIFT-MS: selected ion flow tube–mass spectrometry; Spec: specificity; SVM: support vector machine; TD-GC-MS: thermal desorption gas chromatography–mass spectrometry; TD-GC-TOF-MS: two-dimensional gas chromatography with time-of-flight mass spectrometer.