Vibrational Spectroscopy Saliva Profiling as Biometric Tool for Disease Diagnostics: A Systematic Literature Review
Abstract
:1. Introduction
2. Results
2.1. Cancer
2.1.1. Oral Cancer
2.1.2. Nasopharyngeal Cancer
2.1.3. Lung Cancer
2.1.4. Esophageal Cancer
2.1.5. Gastric Cancer
2.1.6. Breast Cancer
2.2. Other Diseases
2.2.1. Periodontitis
2.2.2. Sjögren’s Syndrome
2.2.3. Diabetes
2.2.4. Acute Myocardial Infarction
3. Discussion
4. Material and Methods
4.1. Research Question/Focused Question
4.2. Search Strategy
4.3. Inclusion and Exclusion Criteria/Eligibility Criteria/Study Selection Criteria
4.4. Screening for Eligibility/Inclusion
4.5. Outcomes and Data Extraction
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Diseases | VS Technique | Authors | Year | Number of Patients Included | Algorithm | Spectral Range (in cm−1) | Sensibility | Specificity | Accuracy |
---|---|---|---|---|---|---|---|---|---|
Oral squamous cell carcinoma | Raman | Jaychandran S. et al. [14] | 2016 | 50 Cancers/87 Premalignant lesions/21 Healthy | PCA-LDA | 600 to 1800 | - | - | 93.1% |
Raman | Rekha P. et al. [15] | 2016 | 32 Cancers/28 Premalignant lesions/23 Healthy | PCA-LDA-LOOCV | 800 to 1800 | 93.8% | 82.6% | 89.1% | |
Nasopharynx cancer | SERS | Feng S. et al. [16] | 2014 | 62 Cancers/30 Healthy | PCA-LDA-LOOCV + ROC curve | 500 to 1750 | 98.4% | 73.3% | 90.2% |
SERS | Qiu S. et al. [17] | 2016 | 32 Cancers/30 Healthy | PCA-LDA-LOOCV + ROC curve | 400 to 1750 | 86.7% | 81.3% | 83.9% | |
SERS | Lin X. et al. [18] | 2017 | 170 Cancers/71 Healthy | PCA-LDA-LOOCV + ROC curve | 600 to 1750 | 70.7% | 70.3% | 70.5% | |
Lung cancer | SERS | Li X. et al. [19] | 2012 | 21 Cancers/20 Healthy | PCA-LDA | 500 to 2000 | 78% | 83% | 80% |
SERS | Qian K. et al. [20] | 2018 | 61 Cancers/66 Healthy | Random Forest * (SVM -LOOCV) | 400 to 1800 | 96.7% | 100% | - | |
Œsophagal cancer | ATR-FTIR | Maitra I. et al. [21] | 2019 | 25 OAC/12 HGD/6 LGD/27 Barrett’s/19 Esophageal inflammatory/38 Healthy 24 OAC/10 HGD/5 LGD/26 Barrett’s/18 Esophageal inflammatory/35 Healthy | SPA-QDA * (PCA-QDA, GA-QDA) | 900 to 1800 | 95.4% # | 62.5% # | 88.8% # |
Raman | Maitra I. et al. [22] | 2020 | SPA-QDA * (PCA-QDA, GA-QDA) | 800 to 1800 | 100% # | 80% # | 95.6% # | ||
Gastric cancer | SERS | Chen Y. et al. [23] | 2018 | 84 Late cancer/20 Early cancer/116 Healthy | PCA | Amino acids (400–2000) | 87.7% # | 80% # | - |
Breast cancer | SERS | Feng S. et al. [24] | 2015 | 31 Cancers/33 Benign tumor/33 Healthy | PLS-DA-LOOCV + ROC curve | 500 to 1780 | 72.7% # | 81.3% # | 78.4% # |
SERS | Hernández-Arteaga A. et al. [25] | 2017 | 100 Cancers/106 Healthy | ROC curve analysis | Sialic acid (400–1800) | 94% | 98% | 92% | |
SERS | Hernández-Arteaga A. et al. [26] | 2019 | 35 Cancers/129 Healthy | ROC curve analysis | Sialic acid (400–1800) | 80.6% | 93.1% | - | |
Periodontitis | SERS | Hernandez-Cedillo A. et al. [27] | 2019 | 33 Periodontitis/30 Gingivitis/30 Healthy | ROC curve analysis | Sialic acid (400–1800) | 69.6% | 100% | - |
Sjögren’s syndrome (SjS) | SERS | Stefancu A. et al. [28] | 2019 | 29 SjS/21 Healthy | PCA-LDA-LOOCV | 500 to 1750 | 96.5% | 90.5% | 94% |
SERS | Moisoiu V. et al. [29] | 2020 | 31 SjS/22 Healthy | PCA-LDA-LOOCV | 600 to 1700 | 77% | 74% | 75% | |
Diabetes | FTIR | Scott D.A. et al. [30] | 2010 | 39 Diabetes/22 Healthy | LDA-cross validation | 900 to 1800 | 90.9% | - | 88.2% |
Myocardial infarction (AMI) | Raman | Cao G. et al. [31] | 2015 | 46 AMI/43 Healthy | PCA-LDA-LOOCV + ROC curve | 400 to 1800 | 80.4% | 81.4% | - |
Diseases | Authors | Year | VS Technique | Nature of Substrate (for SERS only) | Peak Wavenumbers (in cm−1) | Major Assignments |
---|---|---|---|---|---|---|
Oral squamous cell carcinoma | Jaychandran S. et al. [14] | 2016 | Raman | - | 767, 1236, 1330, 1662, 1688 | Pyrimidine |
1652 | Amide | |||||
1444 | Mucine | |||||
752 | Hemocyanine | |||||
Rekha P. et al. [15] | 2016 | Raman | - | 806, 1460, 1485 | DNA (O-P-O symmetric stretch, Pentose sugar CH2 deformation vibration, Purine base vibration) | |
829, 1142, 1169, 1660 | Glutathione | |||||
870, 896, 986 | Proline (C-C stretch, na, na) | |||||
918 | Histidine | |||||
935, 948, 964, 969 | Valine (C-C stretch, na, na, na) | |||||
1015, 1338, 1360, 1424, 1556 | Tryptophan (benzene and pyrrole ring breathe out of | |||||
1050, 1090 | phase, Fermi resonance doublet, na, na) | |||||
1066, 1128, 1302, 1735 | Lactic acid (C–CH3 stretch, C–O stretch) | |||||
1509 | Lipid (na, C-C stretch, CH2 twisting and wagging, C=O stretch) | |||||
1180 | Phenylalanine | |||||
1238, 1258, 1276 | Tyrosine, cytosine, guanine, adenine | |||||
1636 | Amide III (C-N stretch) | |||||
806, 1460, 1485 | Amide I (C=O stretch) | |||||
Nasopharynx cancer | Feng S. et al. [16] | 2014 | SERS | Ag-Colloids | 621, 1004, 1031 | Phenylalanine (C-C twisting mode, νs(C-C), δ(C-C)) |
642, 1173 | Tyrosine (ν(C-S)) | |||||
760 | Tryptophan (ring breathing mode) | |||||
933 | Proline (ν(C-C)) | |||||
1123 | Proteins (ν(C-N)) | |||||
1337 | Collagen (CH3CH2 wagging) | |||||
1445 | Collagen, phospholipids (δ(C-H)) | |||||
Qiu S. et al. [17] | 2016 | SERS | Ag-Colloids | 447, 1003 | Phenylalanine (Ring torsion, νs(C-C)) | |
496 | Glycogen | |||||
590 | Ascorbic acid, Amide VI | |||||
635 | L-Tyrosine, Lactose (ν(C-S)) | |||||
725 | Adenine, Coenzyme A (δ(C-H)) | |||||
812 | L-Serine (ν(C-C-O)) | |||||
888 | D-Galactosamine (δ(C-O-H)) | |||||
1052 | Protein (C-O/C-N stretching) | |||||
1134 | D-Mannose (ν(C-N)) | |||||
1204 | L-Tryptophane, Phenylalanine (Ring vibration) | |||||
1270 | Unsaturated fatty acids (ν(C-H)) | |||||
1336 | Nucleic acid bases (ν(C-H)) | |||||
1448 | Collagen, phospholipids (δ(CH2)) | |||||
1619 | Tryptophan (ν(C=C)) | |||||
1662 | Nucleic acid | |||||
Lin X. et al. [18] | 2017 | SERS | Ag-Colloids | 621, 1004, 1031 | Phenylalanine (C-C twisting mode, νs(C-C), δ(C-H)) | |
642, 854, 1175 | Tyrosine (ν(C-S), Ring breathing mode, δ(C-H)) | |||||
760, 1208, 1552 | Tryptophan (Ring breathing mode, ν(C-C6H5), ν(C=C)) | |||||
878 | Hydroxyproline (ν(C-C)) | |||||
935 | Proline (ν(C-C)) | |||||
959 | α-helix Proline, Valine (ν(C-C)) | |||||
1049, 1123 | Proteins (ν(C-O) ν(C-N), ν(C-N)) | |||||
1265 | Amide III, collagen (ν(CN), δ(NH)) | |||||
1337 | Collagen (CH3CH2 wagging) | |||||
1445 | Collagen, lipids | |||||
1684 | Amide I (ν(C=C)) | |||||
Lung cancer | Li X. et al. [19] | 2012 | SERS | Ag-Colloids | 523 | Lysozymes, proteins, guanine, thymine |
622 | Proteins, phenylalanine, adenine | |||||
696 | Methionine, cytosine | |||||
735 | Tryptophan, coenzyme A, adenine, cytosine, thymine, guanine | |||||
789 | Cytosine, uracil, thymine | |||||
822 | - | |||||
884 | Proline, valine, glycine, tryptophan, glutamic acid, hydroxyproline | |||||
909 | Tyrosine | |||||
925 | Proline, glucose | |||||
1009 | Tryptophan, lysine, phenylalanine | |||||
1077 | Lipids, nucleic acids, proteins, carbohydrates | |||||
1280 | Phospholipid, amide III, proteins, lipids | |||||
1369 | Tryptohan, porphyrins, lipids, guanine, thymine, proteins | |||||
1393 | - | |||||
1722 | Ester group | |||||
Qian K. et al. [20] | 2018 | SERS | Gold nano-modified chip (OptoTrace Technologies) | 423 | Glucose, deuterated glucose | |
643 | (C-H torsion, COO- wag; O-C=O in plane deformation; C-C-C in phase deformation) | |||||
672 | Cytosine, guanine (C–S stretch) | |||||
732 | Adenine (C–S (protein)/CH2 rocking) | |||||
852 | Tyrosine (Ring breathing mode), Proline Ring (C–C stretch) | |||||
923 | Proline Ring (C-C stretch), Lactic Acid, glucose | |||||
999 | Phenylalanine (symmetric ring breathing mode) | |||||
1030 | (Stretching vibration of the ring, deformation in plane C-H) | |||||
1046 | N-acetyl glucosamine | |||||
1268 | Amide III (C–N stretching mode of proteins, indicating mainly a-helix conformation) | |||||
1449 | Phenylalanine, Proteins (CH2 bending mode), Bending mode (C=C) | |||||
1600 | Phenylalanine, Tyrosine (C=C in-plane bending mode) | |||||
Œsophagal cancer | Maitra I. et al. [21] | 2019 | ATR-FTIR | 902 | Phosphodiester region | |
991 | Ribose (C-O), (C-C) | |||||
1003 | (Ring stretching vibrations mixed strongly with CH in-plane bending) | |||||
1014, 1107 | Polysaccharides, pectin (ν(CO), ν(CC), δ(OCH), ring) | |||||
1068 | Ribose (Stretching C-O) | |||||
1099 | Phosphate II (Stretching PO2- symmetric) | |||||
1431 | Polysaccharides, cellulose (δ(CH2)) | |||||
1558 | (Ring base) | |||||
1589 | Phenyl (Ring C-C stretch) | |||||
1604 | Adenine (DNA) | |||||
1624, 1689 | Nucleic acids (base carbonyl stretching, ring breathing mode) | |||||
1643 | Amide I (C=O stretching vibrations) | |||||
1697, 1701 | Guanine (C2=O, C5=O) | |||||
1716 | Thymine (C=O) | |||||
1743 | Lipids (C=O stretching mode) | |||||
1778, 1786 | Lipids (ν(C=C), ν(C=C)), fatty acids | |||||
Maitra I. et al. [22] | 2020 | Raman | 902 | Phosphodiester region | ||
991, 1068 | Ribose (C-O), (C-C) | |||||
1003 | (Ring stretching vibrations mixed strongly with CH in-plane bending) | |||||
1014, 1107 | Polysaccharides, pectin (ν(CO), ν(CC), δ(OCH), ring) | |||||
1068 | Ribose (Stretching C-O) | |||||
1099 | Phosphate II (Stretching PO2- symmetric) | |||||
1431 | Polysaccharides, cellulose (δ(CH2)) | |||||
1558 | (Ring base) | |||||
1589 | Phenyl (Ring C-C stretch) | |||||
1604 | Adenine (DNA) | |||||
1624, 1689 | Nucleic acids (base carbonyl stretching, ring breathing mode) | |||||
1643 | Amide I (C=O stretching vibrations) | |||||
1697, 1701 | Guanine (C2=O, C5=O) | |||||
1716 | Thymine (C=O) | |||||
1743 | Lipids (C=O stretching mode) | |||||
1778, 1786 | Lipids (ν(C=C), ν(C=C)), fatty acids | |||||
Gastric cancer | Chen Y. et al. [23] | 2018 | SERS | A/GO NSs | 435 | Glutamine, hydroxylysine, proline, tyrosine |
488 | Taurine, glycine, ethanolamine, hydroxylysine, tyrosine | |||||
530 | Taurine, glutamine, histidine, alanine, glutamic acid | |||||
642 | Histidine, alanine, proline, tyrosine | |||||
725 | Taurine, glutamine, histidine, glutamic acid | |||||
781 | Glycine, glutamic acid, proline, tyrosine | |||||
843 | Taurine, ethanolamine, histidine, alanine, hydroxylysine, proline, tyrosine | |||||
869 | Glycine, glutamine, ethanolamine, glutamic acid | |||||
917 | Glutamine, alanine, glutamic acid, proline | |||||
933 | Histidine, glutamic acid, proline | |||||
961 | Histidine, glutamic acid, proline, tyrosine | |||||
1037 | Taurine, ethanolamine, alanine, proline, tyrosine | |||||
1053 | Taurine, glutamine, ethanolamine, hydroxylysine | |||||
1109 | Taurine, glutamine, ethanolamine, histidine, alanine | |||||
1197 | Histidine, hydroxylysine, proline, tyrosine | |||||
1222 | Hydroxylysine, proline, tyrosine | |||||
1450 | Taurine, glycine, glutamine, ethanolamine, alanine, glutamic acid, hydroxylysine, proline | |||||
1500 | Histidine | |||||
1710 | Glutamine | |||||
Breast cancer | Feng S. et al. [24] | 2015 | SERS | Ag-Colloids | 621, 643, 1004, 1033 | Phenylalanine (C-C twisting mode, C-C twisting mode, νs(C-C), δ(C-H)) |
760, 1208, 1552 | Tryptophan (Ring breathing mode, ν(C-C6H5), ν(C=C)) | |||||
854, 1176 | Tyrosine (Ring breathing mode, δ(C-H)) | |||||
876 | Hydroxyproline (ν(C-C)) | |||||
935 | Proline (ν(C-C)) | |||||
1049, 1084 | Proteins (ν(C-O) ν(C-N), ν(C-N)) | |||||
1265 | Amide III, collagen (ν(CN), δ(NH)) | |||||
1340 | Collagen (CH3CH2 wagging) | |||||
1447 | Collagen, Lipids (δ(C-H)) | |||||
1684 | Amide I (ν(C=C)) | |||||
Hernández-Arteaga A. et al. [25] | 2017 | SERS | Cit-Ag-NP | 1002 | Pyranose (Ring breathing mode) | |
1237 | Amide III (C-N stretching) | |||||
1391 | Carboxyl (stretching mode) | |||||
Hernández-Arteaga A. et al. [26] | 2019 | SERS | Cit-Ag-NP | 1002 | Pyranose (Ring breathing mode) | |
1237 | Amide III (C-N stretching) | |||||
1391 | Carboxyl (stretching mode) | |||||
Periodontitis | Hernandez-Cedillo A. et al. [27] | 2019 | SERS | Cit-Ag-NP | 1002 | Pyranose (Ring breathing mode) |
1237 | Amide III (C-N stretching) | |||||
1391 | Carboxyl (stretching mode) | |||||
Sjögren’s syndrome (SjS) | Stefancu A. et al. [28] | 2019 | SERS | Ag-NP | 724, 1095, 1323, 1450, 1570 | Hypoxanthine (na, R2trigd or bC-H (in-plane), C-O, C-N or C-C, C-N) |
956, 1134, 1245, 1323 | Xanthine (bN-H, R2trigd, C-N, Ring vibrations, C-N, bC-H, C-N) | |||||
884, 1130, 1370 | Uric acid (na, na, na, C-N, C-H bending) | |||||
Moisoiu V. et al. [29] | 2020 | SERS | Cl-Ag-NP | 724, 1097, 1324, 1449, 1581 | Hypoxanthine (na, Ring vibrations, C-O, C-N or C-C, C-N) | |
957, 1132, 1245, 1324 | Xanthine (na, Ring vibrations, C-N, Mixed ring vibrations/C-N) | |||||
812, 886, 1132, 1369 | Uric acid (na, na, C-N, C-N, C-H bending) | |||||
1002, 1032, 1205, 1651 | Proteins (Phe, Phe, Try/Phe, Amide I) | |||||
Diabetes | Scott DA. Et al. [30] | 2010 | FTIR | ≈970 | (C-C/C-O stretching vibrations in sugar moieties) | |
≈1150 | (C-C/C-O stretching vibrations in sugar moieties, C-O-C symmetric and asymmetric vibrations of sugar moieties and phospholipids) | |||||
≈1410 | (vs(COO−1), symmetric and asymmetric carboxyl radical stretching vibrations of carboxylate groups) | |||||
≈1470 | (bending vibration of CH2 group of amino acids in protein side chains) | |||||
≈1695 | (α-helix component in the amide I region, intermolecular antiparallel b-sheets) | |||||
≈1745 | (lipid ester band) | |||||
Myocardial infarction (IMA) | Cao G. et al. [31] | 2015 | Raman | 442 | (N-C-S stretch) | |
509 | Cystein (ν(S–S) gauche–gauche–gauche) | |||||
621, 1002, 1031 | Phenylalanine (C–C twisting mode of phenylalanine, δ(C–H)) | |||||
643, 828, 853 | Tyrosine (C–C twisting, Ring breathing tyrosine, Ring breathing mode of tyrosine) | |||||
755 | Tryptophan (ν(C–C)) | |||||
876 | Hydroxyproline | |||||
925 | (C–H bending) | |||||
1047 | (C–CH3 vibration) | |||||
1210 | Hydroxyproline, Tyrosine | |||||
1330 | Nucleic Acids | |||||
1449 | Proteins (C–H vibration) | |||||
1555 | Amide II | |||||
1670 | Amide I |
MeSH Terms Used for MEDLINE Search | Keywords Used for Scopus Search |
---|---|
(“saliva”[MeSH Terms] OR saliva[Title/Abstract]) AND (“diagnosis”[MeSH Terms] OR diagnosis[Title/Abstract] OR “biomarkers”[MeSH Terms] OR biomarkers[Title/Abstract] OR diagnostic[Title/Abstract]) AND (“spectroscopy, fourier transform infrared”[MeSH Terms] OR “infrared spectroscopy”[Title/Abstract] OR “spectrum analysis, Raman”[MeSH Terms] OR “Raman”[Title/Abstract]) | (saliva) AND (diagnosis OR biomarkers OR diagnostic) AND (“infrared spectroscopy” OR Raman) |
Item | Criteria of Inclusion | Criteria of Exclusion |
---|---|---|
population and conditions of interest | human population with clinical signs of disease with or without histopathologically confirmed disease diagnosis | non-human study |
intervention/exposure/investigation | application of vs. to the analysis of human saliva with the specific aim of disease diagnosis | method other than vs. used as the main method of analysis |
comparison | diseased population versus healthy population as the control group | no control group |
outcomes of interest | performance of diagnostic tool (sensitivity, specificity, accuracy) | n.s. |
study design | any study design fitting the above criteria | study with less than 20 participants in each group (diseased and control) |
type of paper | original paper. manuscript is written in English | review article, opinion, commentary abstract from a conference, or not a peer-reviewed article. |
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Derruau, S.; Robinet, J.; Untereiner, V.; Piot, O.; Sockalingum, G.D.; Lorimier, S. Vibrational Spectroscopy Saliva Profiling as Biometric Tool for Disease Diagnostics: A Systematic Literature Review. Molecules 2020, 25, 4142. https://doi.org/10.3390/molecules25184142
Derruau S, Robinet J, Untereiner V, Piot O, Sockalingum GD, Lorimier S. Vibrational Spectroscopy Saliva Profiling as Biometric Tool for Disease Diagnostics: A Systematic Literature Review. Molecules. 2020; 25(18):4142. https://doi.org/10.3390/molecules25184142
Chicago/Turabian StyleDerruau, Stéphane, Julien Robinet, Valérie Untereiner, Olivier Piot, Ganesh D. Sockalingum, and Sandrine Lorimier. 2020. "Vibrational Spectroscopy Saliva Profiling as Biometric Tool for Disease Diagnostics: A Systematic Literature Review" Molecules 25, no. 18: 4142. https://doi.org/10.3390/molecules25184142
APA StyleDerruau, S., Robinet, J., Untereiner, V., Piot, O., Sockalingum, G. D., & Lorimier, S. (2020). Vibrational Spectroscopy Saliva Profiling as Biometric Tool for Disease Diagnostics: A Systematic Literature Review. Molecules, 25(18), 4142. https://doi.org/10.3390/molecules25184142