From: MicroRNA based theranostics for brain cancer: basic principles
miRNA | ↑/↓ | Study, Year, Ref. | Biological fluid and Analysis method | No. of pts. | Significance | Area under the Curve (AUC) Sensitivity (SS) Specificity (SP) |
---|---|---|---|---|---|---|
miR-21 | ↑ | Wang, 2012 [100] | Plasma | 30 Glioma | Distinguishes between GBM and healthy controls | Glioma vs. healthy controls |
qRT-PCR | (10 Gr II) | Expression levels cannot distinguish between glioma grades | AUC = 0.9300 (95% CI: 0.7940–1.066) | |||
 | (10 Gr III) | Cannot distinguish between glioma and other brain tumors | SS = 90.0% | |||
(10 Gr IV) |  | SP = 100% | ||||
10 Meningioma | Â | Â | ||||
10 Hyphophysoma | ||||||
10 Healthy controls | ||||||
miR-29 | ↓ | Wu, 2015 [106] | Serum | 83 Glioma | Distinguishes HGGa from healthy controls | AUC = 0.81 (95% CI, 0.73–0.89). |
qRT-PCR | (36 Gr I-II) | Not a brain cancer specific marker | Â | |||
 | (47 Gr III-IV) |  | ||||
69 Healthy controls | ||||||
miR-21 | ↑ | D’Urso, 2015 [101] | Blood | 30 Glioma | Combined diagnostic tree using miR-15b and miR-21 can distinguish glioma from other conditions | Combined miR-15b and mir21 |
miR-15b | ↑ |  | Microarray | (8 Gr II) | SS = 90% | |
miR-16 | ↓ |  | qRT-PCR | (6 Gr III) | Mir-16 levels could distinguish between grades of Glioma (lowest expression in GBM) | SP = 100% |
(16 Gr IV) | miR-16 to distinguish between Gr IV and II/III | |||||
30 Various neurological | AUC = 0.98 | |||||
disorders | SS = 0.98% | |||||
36 PCNSLc | SP = 99% | |||||
16 Secondary brain | ||||||
metastases | ||||||
miR-21 | ↑ | Santangelo, 2018 | Serum | 100 Glioma | Higher serum levels of 3 miRNA panel in GBM and HGG compared to LGGb and healthy controls | Cumulative 3 miRNA panel; GBM vs healthy: |
miR-222 | ↑ | [102] | Exosomes | (2 Gr I) | Cumulative 3 miRNA panel distinguishes between GBM, HGG, LGG and healthy controls | AUC = 0.87 (95% CI 0.7885–0.9524, p < 0.0001) |
miR-124-3p | ↑ | qRT-PCR | (13 Gr II) | High serum levels return to normal postoperatively | SS = 84% | |
(16 Gr III) | SP = 77% | |||||
(69 Gr IV) | *For HGG, LGG, Metastases vs healthy control, see original article | |||||
11 Brain metastases | ||||||
30 Healthy controls | ||||||
miR-203 | ↓ | Chen, 2017 [107] | Serum | 70 GBMd | Distinguishes between GBM and LGG, GBM and healthy controls | GBM vs LGG |
 |  | qRT-PCR | 30 LGG | Lower serum level correlated with larger tumor size, lower KPSe score, lower OSf and lower PFSg | AUC = 0.814 | |
 | 30 Healthy controls | GBM vs healthy controls | ||||
AUC = 0.862 | ||||||
miR-137 | ↓ | Li, 2016 [108] | Serum | 64 glioma | Downregulated levels in glioma compared to controls | NA |
qRT-PCR | (35 Gr I/II) | Further downregulation in HGG | ||||
 | (29 Gr III/IV) 64 Controls | Low levels associated with lower OS of glioma patients | ||||
miR-185 | ↓ | Tang, 2015 [103] | Serum | 66 Glioma | Downregulation of mir-185 specifically associated with glioma patients compared to oncologic non-glioma patients | NA |
qRT-PCR | (23-Gr I + II) | Lower serum mir-185 levels in Grade III-IV glioma compared to Grade I-II | ||||
(43-Gr III + IV) | Lower mir-185 levels correlated with lower OS | |||||
11 Pituitary adenoma | Up-regulation of mir-185 levels after chemoradiation | |||||
32 Meningioma | ||||||
14 Acoustic neuroma | ||||||
miR-210 | ↑ | Lai, 2015 [109] | Serum | 136 Glioma | Upregulation of mir-210 can distinguish glioma from healthy controls | Overall glioma (Gr I-IV) vs healthy controls |
qRT-PCR | (13 Gr I) | miR-210 levels associated with tumor grade | AUC value of 0.927 (95% CI1/40.889–0.964) | |||
(35 Gr II) | (Upregulation trend in glioma Gr I-II vs healthy controls; Statistical significant upregulation in Gr III-IV vs healthy controls) | NPV = 72.5% | ||||
(46 Gr III) | High mir-210 levels associated with lower OS | PPV = 91.3% | ||||
(32 Gr IV) | SS = 91.27% | |||||
50 Healthy controls | SP = 72.50% | |||||
miR-205 | ↓ | Yue, 2016 [104] | Serum | 64 Glioma | Significant downregulation of mir-205 in all grades glioma compared to healthy controls | Overall glioma (Gr I-IV) vs healthy controls |
qRT-PCR | (7 Gr I) | Stepwise decrease in serum mir-205 levels with ascending pathological grades | AUC = 0.935 | |||
(9 Gr II) | Significantly lower mir-205 levels in glioma versus other brain-tumors | PPV = 96.4%, | ||||
(21 Gr III) | Downregulation of mir-205 correlated with KPS score and OS | NPV = 65.8%, | ||||
(27 Gr IV) | SS = 86.3%, | |||||
45 Healthy controls | SP = 92.2%, | |||||
8 Meningioma | ||||||
6 PCNSL | ||||||
5 Pituitary adenoma | ||||||
miR-221/222 Family | ↑ | Zhang, 2016 [110] | Serum | 50 Glioma | Distinguishes glioma from healthy controls | miR-221: |
qRT-PCR | 51 Healthy controls | AUC = 0.84 (95% CI: 0.74–0.93) | ||||
miR-222: | ||||||
AUC = 0.92 (95% CI 0.87–0.94) | ||||||
miR-301a | ↑ | Lan, 2018 [105] | Serum exosomes | 60 Glioma | Higher levels in glioma vs controls | NA |
qRT-PCR | 43 Heallthy controls | Higher levels in glioma vs other types of cancers | ||||
9 Meningioma | Higher levels correlated with ascending pathological grades and lower KPS | |||||
7 PCNSL | Levels decrease postoperatively | |||||
10 Pituitary adenoma | Secondary increase may reflect local recurrence | |||||
Serum levels in HGG are independently associated with longer OS | ||||||
miR-397a | ↓ | Huang, 2017 [113] | Serum | 100 Glioma | Distinguishes glioma from healthy controls | miR-376a: AUC = 0.872; SS = 81.0%; SP = 82.0% |
miR-397b | ↓ | |||||
miR-397c | ↓ | |||||
qRT-PCR | (10 Gr I) | Decreased levels associated with advanced WHO grade and low KPS | miR-376b: AUC = 0.890; SS = 82.0% SP = 78.0%; | |||
(20 Gr II) | Higher miRNA levels associated with better OS | miR-376c: AUC = 0.837; SS = 90.0%; SP = 70.0% | ||||
(30 Gr III) | ||||||
(40 Gr IV) | ||||||
150 Healthy controls | ||||||
miR-122 | ↓ | Tang, 2017 [114] | Plasma | 74 Glioma | Distinguishes between glioma and healthy controls | AUC = 0.939 |
qRT-PCR | (14 Gr I) | Further downregulation of serum levels in higher grade gliomas | SS = 91.9% | |||
(17 Gr II) | The miRNA level is an independent prognostic factor for OS | SP = 81.1% | ||||
(20 Gr III) | ||||||
(23 Gr IV) | ||||||
74 Healthy controls | ||||||
miR-125b | ↓ | Regazzo, 2016 [112] | Serum | 22 Glioma | Distinguishes between GBM and lower grade (II/III) gliomas | miR-125b: GBM vs lower grade glioma, AUC = 0.75 (95% |
miR-497 | ↓ | |||||
qRT-PCR | (12 Gr II/III) |  | CI = 0.533–0.967) | |||
(10 Gr IV) | miR-497: GBM vs lower grade glioma, AUC = 0.87 (95% | |||||
8 Meningioma | confidence interval (CI) = 0.712–1 | |||||
15 Healthy controls | ||||||
miR-125b | ↓ | Wei, 2016 [111] | Serum | 33 Glioma | Distinguishes between glioma and healthy controls | Glioma vs healthy controls |
qRT-PCR | (11 Gr I) |  | AUC = 0.839 (95% CI: 0.743–0.935) | |||
(11 Gr II) | ||||||
(11 Gr III/IV) | ||||||
33 Healthy controls | ||||||
miR-182 | ↑ | Xiao, 2016 [115] | Serum | 112 Glioma | Distinguishes between glioma and healthy controls | Glioma vs healthy controls |
qRT-PCR | (18 Gr I) | The expression levels associated with KPS score and WHO grade and correlated with lower OS and DFS, | AUC = 0.778 | |||
(23 Gr II) | The level is independent prognostic factor for OS | SS = 58.5% | ||||
(32 Gr II) |  | SP = 85.2% | ||||
(39 Gr IV) | ||||||
54 Healthy controls | ||||||
miR-128 | ↓ | Sun, 2015 [121] | Serum | 151 Glioma | Distinguishes between glioma and healthy controls and meningioma | Glioma vs healthy controls |
qRT-PCR | (24 Gr I) | Distinguishes Gr II-IV from Gr I | AUC = 0.9095 | |||
(23 Gr II) | Levels elevated after surgery and correlate with the pathological grade and KPS | Glioma vs Meningioma | ||||
(43 Gr III) | AUC = 0.8283 | |||||
(61 Gr IV) | Glioma II-IV vs I | |||||
59 Post-op glioma | AUC = 0.7362 | |||||
52 Meningioma | ||||||
53 Healthy controls | ||||||
30 Glioma | ||||||
miR-128 | ↓ | Wang, 2012 [100] | Plasma | (10 Gr II) | Can distinguish between GBM and healthy controls | AUC (miR-128 or miR-342-3p) = 1.000 (95% CI: 1.000–1.000) |
miR-342-3p | ↓ |  | qRT-PCR | (10 Gr III) | Decreased levels correlated with glioma grade | SS = 90.0% |
(10 Gr IV) | Significant upregulation after operation and chemoradiation | SP = 100% | ||||
10 meningioma | ||||||
10 Hyphophysoma | ||||||
10 Healthy controls | ||||||
miR-128 | ↑ | Roth, 2011 [120] | Blood cells | 20 Glioblastoma | Distinguishes between GBM and healthy controls | GBM vs healthy controls |
miR-342-3p | ↓ |  | Microarray | 20 Healthy Controls | Authors apply statistic learning techniques (SVM = Support vector machines) and compute the diagnostic accuracy of miRNA profiles; a 180 miRNA signature calculated to have the highest diagnostic accuracy in distinguishing GBM from healthy controls. | miR-128: |
qRT-PCR |  |  | AUC = 0.828 | |||
miR-342-3p | ||||||
AUC = 0.18 | ||||||
180 miRNA signature: | ||||||
SS = 83% | ||||||
SP = 79% | ||||||
RNU6–1 | ↑ | Manterola, 2014 | Serum exosomes | Initial screening | 3 small non coding RNAs can distinguish between GBM and healthy controls | RNU6–1 |
miR-320 | ↑ | [119] | Low density array | 25 Glioblastoma | (machine learning algorithm) | AUC = 0.852 (95% CI, 0.74–0.96) |
miR-574-3p | ↑ |  | qRT-PCR | 25 Healthy controls |  | SS = 73%; SP = 70% |
Confirmation | Results from initial screening not confirmed is the second study group, only RNU6–1 was found significantly up-regulated! | miR-320 | ||||
50 Glioblastoma | AUC = 0.720 | |||||
30 Healthy controls | (95% CI, 0.56–0.87) | |||||
SS = 65%; SP = 65% | ||||||
miR-574-3p | ||||||
AUC = 0.738 (95% CI, 0.58–0.89) | ||||||
SS = 59%; SP = 59% | ||||||
3 sncRNA signature: | ||||||
AUC = 0.926 (95%[CI], 0.84–1) | ||||||
SS = 87%; SP = 86% | ||||||
miR-454-3p | ↑ | Shao, 2015 [117] | Plasma | 70 Glioma | Distinguishes between glioma and healthy controls | Glioma vs healthy controls |
qRT-PCR | (8 Gr I) | Higher levels in higher WHO grades and the levels decrease significantly postoperatively | AUC = 0.9063 [95% (CI): 0.8487–0.9639)] | |||
(15 Gr II) | Weak correlation between high levels and OS | SS = 99.05% | ||||
(25 Gr III) | SP = 82.86% | |||||
(22 Gr IV) | ||||||
70 Healthy controls | ||||||
miR-451a | ↓ | Zhao, 2016 [116] | Serum | 118 Glioma | Distinguishes between glioma and healthy controls | Glioma vs healthy controls |
qRT-PCR | (27 Gr I) | Levels return to almost healthy control expression 7 days after surgery | AUC = 0.816 | |||
(33 Gr II) | The expression level downregulation correlates with WHO grade and KPS | SS = 81.4% | ||||
(33 Gr III) | SP = 79.7% | |||||
(25 Gr IV) | ||||||
84 Healthy controls | ||||||
miR-15b-5p | ↓ | Yang, 2013 [122] | Serum | 148 Glioma | Significantly decreased in glioma (Gr I-IV) compared to healthy controls | SS = 88.00% |
miR-23a | ↓ | |||||
miR-133a | ↓ | |||||
miR-150* | ↓ | |||||
miR-197 | ↓ | Solexa sequencing | (15 Gr I) | Malignant astrocytoma prediction | SP = 97.87% | |
miR- 497 | ↓ | |||||
miR-548b-5p | ↓ | qRT-PCR | (55 Gr II) | Significant postoperative upregulation of aforementioned miRNAs | ||
(45 Gr III) | ||||||
(33 Gr IV) | ||||||
11 Astrogliosis | ||||||
80 Healthy controls | ||||||
miR-15b-5p | ↑ | Zhi, 2015 [123] | Serum | 90 Glioma | Combined 9 miRNA panel distinguishes glioma from healthy controls | AUC = 0.9722 (95% CI, 0.9501–0.9942) |
miR-16-5p | ↑ | |||||
miR-19a-3p | ↑ | |||||
miR-19b-3p | ↑ | |||||
miR-20a-5p | ↑ | TaqMan | (28 Gr II) | Levels decrease postoperatively | SS = 93.3% | |
miR-106a-5p | ↑ | |||||
miR-130a-3p | ↑ | Low density Array | (38 Gr III) | miR-20a-5p, miR-106a-5p, and miR-181b-5p associated with advanced glioma stages | SP = 94.5% | |
miR-181b-5p | ↑ | |||||
miR-208a-3p | ↑ | |||||
qRT-PCR | (24 Gr IV) | miR-19a-3p, miR-106a-5p, and miR-181b-5p significantly associated lower OS. | ||||
110 Healthy controls | ||||||
miR-17 | ↑ | Xu, 2017 [118] | Serum | 47 Glioma | Distinguishes between glioma and healthy controls | miR-17; AUC = 0.787 [95% (CI): 0.690–0.865)] SS = 89.3%; SP = 55.3% miR-130a AUC = 0.720 [95% (CI): 0.617–0.807)] SS = 70%; SP = 65.2% miR-10b AUC = 0.721 [95% (CI): 0.619–0.808)] SS = 44.6%; SP = 93.6% miR-Score (all three miRNA) AUC = 0.872 [95% (CI): 0.787–0.932)] SS = 72.3%; SP = 85.1% |
miR-130a | ↑ |  | qRT-PCR | (16 Gr I-II) | Higher serum levels in HGG compared to LGG | |
miR-10b | ↑ | (31 Gr III-IV) | ||||
45 Healthy controls | ||||||
miR-93 | ↑ | Goze, 2018 [124] | Whole blood | 15 DLGGh | 3 miRNA signature tree distinguishes DLGG from healthy controls | miRNA-93; AUC = 0.83556 |
miR-590-3p | ↑ | |||||
miR-454 | ↑ | TaqMan OpenArray RT-qPCR platform | 15 Healthy controls | miRNA-590-3p; AUC = 0.8133 | ||
miRNA-454; AUC = 0.75111 |