Table 1 Brief information about non-metabolomics studies on urinary biomarkers for hepatocellular carcinoma
From: Urinary biomarkers for hepatocellular carcinoma: current knowledge for clinicians
Author/Year | Nations* | Samples | Platforms | Modeling | Validation | Categories | Biomarkers | Applications a | Results | Evidence from Serum/tissue | Serum AFP |
|---|---|---|---|---|---|---|---|---|---|---|---|
Urinary proteins | |||||||||||
Yeh/ 1987 | Taiwan, China | HCC, 31 Probably HCC, 15 Healthy, 21 | RIA |  |  | TGF | TGF-α↑ | Diagnosis | (Probably) HCC vs. Healthy Cutoff at 10.5 μg/g creatinine Sensitivity 71.7% |  | Cut-off at 400ng/ml Sensitivity 58.7% [TGF-α + AFP] Sensitivity 93.5% |
Tsai/ 1997 | Taiwan, China | HCC, 94 LC, 94 Healthy, 50 | RIA |  |  | TGF | TGF-β1↑ | Diagnosis | HCC vs. LC AUROC 0.730 Cutoff at 50 μg/g creatinine Sensitivity 53.1% Specificity 98.9% |  | AUROC 0.730 Cut-off at 100ng/ml Sensitivity 55.3% Specificity 98.9% OR 1.06 (1.02–1.10) [TGF-β1 + AFP] Sensitivity 84.0% Specificity 97.8% |
Independent risk factor | OR 1.08 (1.04–1.12)b | ||||||||||
Prognosis (Pathological features) | Correlation with diffuse HCC (P = 0.001), larger tumors (≥ 3 cm, P = 0.018), more Child-Pugh C (P = 0.026). | ||||||||||
Tsai/ 1997 | Taiwan, China | HCC, 94 LC, 94 | RIA |  |  | TGF | TGF-β1↑ | Prognosis (Monitor) | After TACE TGF-β1↓ (P = 0.0001) |  |  |
(OS) | TGF-β1↑ vs. TGF-β1 normal OS↓ (P = 0.018) | ||||||||||
Noie/ 2001 | Japan | Partial hepatectomy, 61 HCC, 40 | RIA |  |  | UTI | UTI c | Other | Postoperative ΔuUTImax correlated with: ICG clearance rate (P = 0.002) Operation duration (P = 0.034) Resection rate (P = 0.004) |  |  |
Lin/ 2004 | Japan | HCC, 39 LC, 19 CH, 16 | ELISA |  |  | UTI | UTI* | Other | HCC vs. CH, no significant difference Child-Pugh C vs. Child-Pugh A/B ↓ (P < 0.05/0.01) | HCC vs. LC (P < 0.05) LC vs. CH vs. NC↓ (P < 0.05) Child-Pugh C vs. Child-Pugh A/B ↓ (P < 0.05/0.01) |  |
Abdelsameea/ 2020 | Egypt | HCC, 40 LC, 40 CH, 40 Healthy, 40 | ELISA |  |  | NGAL | NGAL↑ | Diagnosis | HCC vs. LC AUROC 0.95 Cutoff at 1255 ng/mL Sensitivity 90% Specificity 87.5% | Tissue: (Zhang/2012) Expression of NGAL/NGALR↑ (P < 0.05) correlates with: Vascular invasion (P = 0.03) TNM stage (P = 0.004) Recurrence (P < 0.001) Shorter OS (P < 0.001) | AUROC 0.92 Cut-off at 39.6ng/ml Sensitivity 85% Specificity 100% [NGAL + AFP] AUROC 0.997 Sensitivity 95% Specificity 100% |
Suh/ 2014 | South Korea | HCC, 50 (Radiotherapy) | ELISA |  |  | MMP | MMP-2↑ | Prognosis (PFS) | MMP-2 ≥ median → worse PFS (P = 0.04) MMP-2 or serum VEGF/plt ≥ median → worse PFS OR 2.12 (1.01–4.55) |  |  |
Abdalla/ 2012 | Egypt | HCC, 32 HCV, 74 Normal, 12 | LC-MS/MS, RT-qPCR |  |  | Proteomics RNA | DJ-1↑, CAF-1↑, HSP60↑ | Diagnosis | Urinary RNA over-expression of CAF-1 Sensitivity 66% Specificity 90% Accuracy 78% HSP60 Sensitivity 83% Specificity 42% Accuracy 62% [CAF-1 + HSP60] Sensitivity 61% Specificity 92% Accuracy 77% |  |  |
Huang/ 2015 | Taiwan, China | HCC, 44 Healthy, 44 | NanoLC-MS/MS |  |  | Proteomics | S100A9↑, GRN↑ | Diagnosis | S100A9, GRN peptide quantification ratio (D/H) > 1.5 Co-up-regulation (r = 0.5732, P = 0.0066) | Tissue: Gene: S100A9 amplified in 70% HCC, GRN amplified in 27% HCC, S100A9/GRN co-amplification (p = 0.001) mRNA: S100A9/GRN co-expression (r = 0.3651, p < 0.0001) Co-amplification → worse OS (p < 0.001) |  |
Zhao/ 2020 | China | Training set HCC, 36 LC, 29 CH, 14 Test set HCC, 18 LC, 10 CH, 9 MRM set HCC, 20 LC, 15 CH, 5 | LC-MS/MS | RF | Cross-validation External validation MRM | Proteomics | HPX↑, APOH↑, APCS↑, PLG↑, GOT1↓, GLR↓, NCR3LG1↓ | Diagnosis | MRM validation: HCC vs. LC/CH AUROC 0.95 Sensitivity 90.0% Specificity 85.0% |  | HCC vs. LC/CH AUROC 0.56 |
Zhan/ 2020 | China | Training set HCC, 10 LC, 10 CH, 10 Healthy, 10 Validation set HCC, 75 LC, 51 CH, 14 | LC-ESI-MS/MS, WB, ELISA |  | External validation | Proteomics | AFP↑, ORM1↑ | Diagnosis | HCC vs. non-HCC AFP AUROC 0.795 (0.704–0.886) Sensitivity 63.5% Specificity 95.4% ORM1 AUROC 0.705 (0.604–0.807) [AFP + ORM1] AUROC 0.864 (0.791–0.937) Sensitivity 80.9% Specificity 85.5% |  | HCC vs. non-HCC AUROC 0.818 (0.734–0.903) Cutoff at 334.3 ng/ml Sensitivity 62.5% Specificity 93.8% |
Bannaga/2021 | UK | Training set HCC, 18 Non-HCC, 51 Validation set HCC, 39 Non-HCC, 87 | CE-MS/MS, IHC | SVM | External validation | Proteomics | KLK6↑, MMP-3↑, MMP-13↑, CTSD↑, CTSE↑, MEP1A↓, CTSB↓ | Diagnosis Prognosis (OS) | HCC-31 model (31 components) AUROC 0.88 (0.81–0.93) Sensitivity 79.5% Specificity 85.1% OS: OR 4.1 (1.7–9.8 P = 0.0005) | Tissue IHC: KLK6↑ MEP1A↓ |  |
Urinary nucleic acids | |||||||||||
Lin/ 2011 | Taiwan, China | HCC, 17 Healthy, 15 | LNA clamp-mediated PCR |  |  | DNA | TP53 249T↑ | Diagnosis | Sensitivity 52.9% (9/17) Specificity 100% (15/15) |  |  |
Jain/ 2015 | USA Taiwan, China | HCC, 78 LC, 50 CH, 45 | BS-qPCR, qMSP |  |  | DNA | mRASSF1A↑ | Diagnosis | mRASSF1A at P1 HCC vs. LC/CH AUROC 0.705 HCC vs. CH AUROC 0.831 HCC vs. LC AUROC 0.595 | Tissue: mRASSF1A at P1/E2/P2 HCC vs. LC/CH P1 AUROC 0.90 At 90%sensitivity Specificity P1 72.9% E1 38.6% P2 27.1% | In AFP (-) HCC patients 81.8% (36/44) mRASSF1A at P1 (+) |
Hann/ 2017 | USA | HCC, 10 Recurrent, 5 | BS-qPCR |  |  | DNA | mRASSF1A↑, mGSTP1↑, TP53 249T↑ | Prognosis (Recurrence) | MRI-confirmed recurrent cases: TP53 249T / mRASSF1A / mGSTP1 (+) (up to 9 months before MRI confirmation) |  | MRI-confirmed recurrent cases: 3/5 AFP (-) |
Zhang/ 2018 | USA Taiwan, China | HCC, 97 Non-HCC (CH, LC), 112 | qPCR |  |  | DNA | TP53 249T↑, CTNNB1 32–37↑, hTERT 124↑, mRASSF1A↑ | Diagnosis | [TP53 249T + hTERT 124 + mRASSF1A] HCC vs. non-HCC AUROC 0.607 Sensitivity 26.2% Specificity 85.7% | Serum [TP53 249T + hTERT 124 + mRASSF1A] HCC vs. non-HCC AUROC 0.846 Sensitivity 76.2% Specificity 85.7% | HCC vs. non-HCC AUROC 0.799 Sensitivity 71.4% Specificity 81.0% [AFP + urine + serum] AUROC 0.904 Sensitivity 90.5% Specificity 81.0% |
Wang/ 2018 | Taiwan, China | HCC, 137 CH, 224 LC, 207 | Not specified | LR, CART, FS (serum AFP→LR), RF, TS (LR→FS) | Cross-validation | DNA | mRASSF1A↑, mGSTP1↑, TP53 249T↑ | Diagnosis | [serum AFP + ctDNA] (TS) AUC 0.935 (0.930–0.940) Sensitivity 87.9% Specificity 90% |  | AUROC 0.88 Sensitivity 48.2% Specificity 90% |
Kim/ 2022 | USA Taiwan, China | HCC, 186 LC, 144 CH, 279 | qPCR | TS (AFP→LR) | Cross-validation | DNA | TP53 249↑, mRASSF1A↑, mGSTP1↑ | Diagnosis | [ctDNA panel] AUROC 0.715 (0.668–0.762) [serum AFP + ctDNA] (TS) AUROC 0.902 (0.871–0.933) Sensitivity 90% Specificity 79.6% BCLC-A HCC Sensitivity 90% Specificity 77% |  | AUROC 0.8546 (0.8184–0.8908) BCLC-A HCC Sensitivity 90% Specificity 40% |
Abdalla/ 2012 | Egypt | HCC, 32 HCV-positive, 74 Normal, 12 | MicroRNA array RT-qPCR |  |  | RNA | miR-625↑, miR-532↑, miR-618↑, miR-516-5p↓, miR-650↓ | Diagnosis | HCC vs. HCV-positive [miR-618 + miR-650] Sensitivity 58% Specificity 75% Accuracy: 69% |  |  |
Świtlik/ 2019 | Poland | HCC, 65 Healthy, 29 | MicroRNA array RT-qPCR | Exploratory factor analysis |  | RNA | miR-618↑, miR-532-3p↑, miR-625↑, miR-640↑, miR-765↑ | Diagnosis | [miR-532-3p + miR-765] HCC vs. Healthy: Wilks χ [2]  = 0, P < 0.0001 | Different miRNA profiles from tissue/serum/facet |  |
Prognosis (Pathological features) | [miR-532-3p + miR-765] clustering Correlate with histological grade, clinical stage, classification for primary tumor, lymph node, and distant metastasis P < 0.005 | ||||||||||
Zhou/ 2022 | China | Early-HCC, 64 Advanced-HCC, 66 Healthy, 65 | RT-qPCR | GEO2R |  | RNA | miR-93-5p↑ | Diagnosis | Advanced HCC vs. early HCC vs. Healthy 3.6-fold↑, 3.7-fold↑ Early HCC vs. Healthy Sensitivity 87.5% Specificity 97.4% | Tissue miR-93-5p HCC vs. non-HCC 4.0-fold↑ Serum miR-93-5p HCC vs. non-HCC Advanced HCC vs. early HCC vs. Healthy 2.9-fold↑, 2.8-fold↑ Early HCC vs. Healthy Sensitivity 85.9% Specificity 95.4% |  |
Prognosis (Monitor) | 1 month after hepatectomy HCC vs. non-HCC Not significant | ||||||||||
(OS) | miR-93-5p↑ vs. miR-93-5p normal OS↓ (Early HCC, P = 0.0031) miR-93-5p↑ vs. miR-93-5p normal OS↓ (Advanced HCC, P = 0.0014) | ||||||||||
Urinary metabolites | |||||||||||
Antoniello/ 1998 | Italy | HCC, 16 LC, 32 Healthy, 28 | HPLC |  |  | Polyamines | PUT↑, SPM↑, SPD↑ | Diagnosis | PUT (total, free, monoacetylated) ↑ (P < 0.001) SPM (total, free) ↑ (P < 0.001) SPD (total, free, monoacetylated, N1/N8 ratio) ↑ (P < 0.001) |  |  |
Enjoji/ 2004 | Japan | HCC, 53 LC, 50 CH, 89 FL, 22 | ELISA |  |  | Polyamines | DiAcSPM↑ | Diagnosis | Cutoff at 325 nM/g creatinine Sensitivity 65.5% Specificity 76.0% |  | Cutoff at 20 ng/ml Sensitivity 63.8% |
Prognosis (Monitor) | Treated HCC, DiAcSPM↓ (P = 0.0431) Untreated HCC, DiAcSPM↑ | ||||||||||
Liu/ 2013 | China | Hepatic cancer, 20 Healthy, 20 | UHPLC-MS/MS |  |  | Polyamines | NSPD↑, SPM↑, SPD↑ | Diagnosis | Cancer vs. Normal P < 0.05↑ | Serum PUT, SPD↑; L-ornithine, γ-aminobutyric acid↓ |  |
Yu/ 2015 | Animal (Rats) | HCC model, 40 Treated, 20 Normal, 20 | UHPLC-MS/MS |  |  | Polyamines | NSPD↑, NSPM↑, DiAcSPD↑, DiAcSPM↑ | Diagnosis | HCC vs. Normal P < 0.05↑ | Tissue PUT↑ Serum NSPD↑ Serum/Tissue/Urine NSPD↑ |  |
Prognosis (Monitor) | Treated vs. HCC P < 0.05↓ | ||||||||||
Dusheiko/ 1982 | South Africa | HCC, 31 Other malignancies, 16 Liver dysfunction, 16 Healthy, 25 | RIA |  |  | Nucleotides | cGMP↑ | Diagnosis | HCC, liver dysfunction, other malignancies vs. Healthy ↑ (P < 0.0005) Cutoff at 0.95 nmol/100 mL GF Sensitivity 80% in HCC, 68% in other malignancies, 75% in liver dysfunction | cGMP↑ in HCC and liver dysfunction |  |
Sakai/ 1990 | Japan | Mixed, including Hepatic cancer, 41 LC, 21 | Biochemistry |  |  | L-Fucose | L-Fucose↑ | Diagnosis | Cutoff at 215 μmol/g creatinine Hepatic cancer: Sensitivity 90.5% (19/21) LC: Sensitivity 85.4% (35/41) Gastric cancer, lung cancer, and gallbladder cancer ↑ |  |  |
Bannaga/ 2021 | UK | HCC, 31 Prostate cancer, 62 Bladder cancer, 29 Non-cancer, 18 | SPME | PCA RBFN | 50% validation set | VOCs | Not specified | Diagnosis | In AFP ≥ 10 kU/L Sensitivity 83% AUC 0.83 (0.73–0.93) In AFP < 10 kU/L Sensitivity 68% AUC 0.68 (0.54–0.81) |  | Serum AFP alone (cutoff 10 ku/L) Sensitivity 54.8% |
Bannaga/ 2021 | UK | HCC, 20 Healthy/NAFLD, 38 | GC-IMS GC-TOF-MS/MS | RF LR |  | VOCs | 2-Butanone↑, 6 other VOCs↓ | Diagnosis | Significantly different in HCC vs. Non-HCC GC-IMS model (factors not specified): HCC vs. LC AUROC 0.97 (0.91–1.00) Sensitivity 0.43 (0.13–0.75) Specificity 0.95 (0.86–1.00) |  |  |
Etiology/carcinogenesis-related biomarkers | |||||||||||
Ross/ 1992 | China | HCC, 22 Healthy, 140 | HPLC |  |  | Aflatoxin-related | AFP1↑, AFB1-N [7]-Gua↑, AFM1↑, AFB1↑ | Independent risk factor | Any of the compounds RR 3.8 (1.2–12.2) |  |  |
Wang/ 1996 | Taiwan, China | HCC, 56 Healthy, 220 | ELISA |  |  | Aflatoxin-related | Aflatoxin metabolites (mainly AFB1, cross reactivity with AFB2, AFM1, AFG1, AFP1 etc.)↑ | Independent risk factor | 1st half OR 3.8 (1.1–12.8) 1st tertile OR 7.2 (1.5–34.3) | Serum aflatoxin-albumin adducts↑ |  |
Hatch/ 1993 | Taiwan, China | Residents, 250 | ELISA |  |  | Aflatoxin-related | Aflatoxin metabolites (mainly AFB1, cross reactivity with AFB2, AFM1, AFG1, AFP1 etc.)↑ | Independent risk factor | Individual biomarker level & Area HCC mortality: positive correlation P < 0.05 |  |  |
Nair/ 2004 | Thailand | AC, unknown CH, unknown LC, unknown HCC, unknown | Immuno-enriched HPLC- fluorescence |  |  | Oxidative stress-related | ε-dA↑ | Diagnosis | [CH, LC, HCC] vs. [AC] 20-90-fold↑ |  |  |
Wu/ 2008 | Taiwan, China | HCC, 74 Healthy, 290 | ELISA |  |  | Oxidative stress-related & Aflatoxin-related | 15-F2t-IsoP↑, 8-oxodG↑, AFB1↑ | Independent risk factor | AFB1 correlates with 8-oxodG and 15-F2t-IsoP (P < 0.0001) 15-F2t-IsoP: 1st half OR 2.53 (1.30–4.93) 1st tertile OR 6.27 (2.17–18.13) 2nd tertile OR 3.87 (1.32–11.38) |  |  |
Ma/ 2018 | China | HCC, 363 Healthy, 725 | ELISA |  |  | Oxidative stress-related | 15-F2t-IsoP↑ | Independent risk factor | 4th quartile vs. 1st quartile Male OR 8.84 (2.74–28.60) Female OR 1.75 (0.70–4.42) |  |  |
Yuan/ 2019 | China | HCC, 347 Healthy, 691 | LC-ESI-MS/MS |  |  | Oxidative stress-related | 8-epi-PGF2α↑ | Independent risk factor | 4th quartile vs. 1st quartile OR 5.29 (1.92–14.54) |  |  |