| Literature DB >> 28423688 |
Xiaobing Liu1, Xin Liu1, Yuqi Wu1, Qingjian Wu1, Qingqing Wang1, Zhenxing Yang1, Longkun Li1.
Abstract
MicroRNAs (miRNAs) are short non-coding RNAs that play important roles in basic cellular processes, including differentiation, proliferation, apoptosis and autophagy. They are also involved in various stages of tumorigenesis and play key roles in bladder cancer initiation and progression. Notably, the altered expression of miRNAs in the tumors is reflected in body fluids, including blood and urine, which opens avenues for non-invasive diagnosis and prognosis. Many studies have demonstrated that epigenetic changes extensively alter tumoral microRNA expression. The high reproducibility, specificity and sensitivity of miRNA levels in body fluids suggest their potential use as biomarkers for cancer screening and diagnosis. For example, recent technological advances have made it possible to detect miRNAs in urine for bladder cancer screening. In this review, we focus mainly on the current knowledge and future challenges for incorporating miRNAs in body fluids, like urine and blood, for making clinical diagnoses and assessing prognoses in bladder cancer.Entities:
Keywords: biomarker; bladder cancer; blood; microRNAs; urine
Mesh:
Substances:
Year: 2017 PMID: 28423688 PMCID: PMC5458291 DOI: 10.18632/oncotarget.16026
Source DB: PubMed Journal: Oncotarget ISSN: 1949-2553
Figure 1The origin of miRNAs in biofluids
Studies regarding miRNAs in urine as potential biomarkers in bladder cancer
| Study | Year | Sample | Results | BC/Cont(n | clinically relevated findings | Reference |
|---|---|---|---|---|---|---|
| Hanke | 2010 | Whole urine | Upregulate: miR-126,miR182 | 29//11 | AUC=0.768, DS=72%, DSp-83% | 46 |
| Yamada | 2011 | Urine sediment | Upregulate: miR96, miR-183 | 100/74 | AUC=0.831/0.817, DS=71/74%, DSp=79/77% | 47 |
| Miah | 2012 | Urine sediment | Upregulate: miR-15b, miR-1224-3p; downregulate: miR-135 | 68/53 | AUC=0.86, DS=94.1%, DSp=51% | 48 |
| Puerta-Gil | 2012 | Urine (not defined) | Upregulate: miR-222, miR-452; downregulate: miR-143 | 37/57 | AUC=0.718, AUC=0.848 | 49 |
| Snowdon | 2012 | Whole-urine | Upregulate: miR-126; downregulate: miR-125b | 8/5 | without data | 55 |
| Wang | 2012 | Urine sediment and superna | Upregulate: miR-141, miR200a/b/c, miR-429 | 51/24 | AUC=0.706-0.804, DS=100%, DSp=53% | 50 |
| Yun | 2012 | Urine supernatant | Upregulate: miR-145, miR-200a | 207/144 | AUC=0.729 and 0.790, DS=78% and 84%, DSp=61% and 61 | 51 |
| Kim | 2013 | Urine supernatant | Upregulate: miR-214 | 138/144 | without data | 52 |
| Mengual | 2013 | Urine sediment | Upregulate: miR-18a, miR-25, miR-187, miR92a; downregulate: miR-140-5p, miR-142-3p, mi | 151/121 | AUC=0.92, DS-85%, DSp=87% | 53 |
| Shimizu | 2013 | Urine supernatant | Upregulate: miR-9-3, miR-142-2/3, miR-137 | 86/20 | AUC=0.91 | 54 |
| Tolle | 2013 | Whole urine | Upregulate: miR-520e, miR-618, miR-122-5p | 36/19 | AUC=0.679-0.764 | 56 |
| Zhang | 2014 | Urine supernatant | Upregulate: miR-99a, miR-125b | 50/21 | AUC=0.876, DS=79%, DSp=88% | 57 |
| Zhou | 2014 | Urine supernatant | Upregulate: miR-106b | 112/78 | AUC=0.802, DS=76.8%, DSp=72.4% | 58 |
| Eissa | 2015 | Urine sediment | Upregulate: miR-96 | 94/90 | AUC=0.822, DS=76.8%, DSp=88.9% | 59 |
| Eissa | 2015 | Urine sediment | Upregulate: miR-210, miR-96 | 94/56 | AUC=0.933, DS=100%, DSp=89.5% | 60 |
| Liu | 2015 | Urine sediment | Upregulate: miR-141, miR-200b | 78/54 | AUC=0.749 | 61 |
| Long | 2015 | Urine supernatant | Upregulate: let-7b, miR-15a, miR-21, miR-26a, miR-93, miR-101, miR-200c, miR-940 | 85/45 | AUC=0.858, DS=70%, DSp=84% | 62 |
| Wang | 2015 | Urine supernatant | Upregulate: miR-214, | 292/169 | AUC=0.838, DS=90.5%, DSp=65.6% | 63 |
| Spare | 2016 | Whole urine | Upregulate: miR-16, miR-21, miR-34a, miR-200c, miR-205, miR-211 | 60/21 | AUC=0.74, DS=88%, DSp=48% | 64 |
| Urquidi | 2016 | Uriene(not defined) | 25-miRNA model | 88/118 | AUC=0.982 | 66 |
Studies regarding miRNAs in blood as potential biomarkers in bladder cancer
| Study | Year | Sample | Results | BC/Cont(n | clinically relevated findings | Reference |
|---|---|---|---|---|---|---|
| Tolle | 2013 | Whole-bloo | Upregulate: miR-26a-5p, mir-144-5p, miR-374-5p | 38/20 | AUC=0.774-0.824 | 56 |
| Adam | 2013 | Plasma | No different | 20/18 | no difference | 75 |
| Scheffer | 2014 | Serum | miR-141,miR-639 | 126/105 | No different levels between study gr | 73 |
| Feng | 2014 | Plasma | Upregulate: miR-99a | 50/50 | without data | 80 |
| Feng | 2014 | Plasma | Upregulate: miR-19a | 50/50 | without data | 76 |
| Jiang | 2015 | Serum | Upregulate: miR-152; downregulate: miR-1486-3p, miR-3187-3p, miR-15b-5p, miR-27a- | 120/120 | AUC=0.899, DS=80%, DSp=89% | 68 |
| Kreebel | 2015 | Serum | Upregulate: miR-1141 | 34/34 | AUC=0.726, DS=70.5%, DSp=73.5 | 74 |
| Du | 2015 | Plasma | Upregulate: miR-663b; downregulate: miR-497 | 165/175 | AUC=0.711, DS=69.7%, DSp=69.6 | 69 |
| Yang | 2015 | Serum | Upregulate: miR-210 | 168/104 | without data | 79 |
| Tao | 2015 | serum | 13-miRNA model | 46/30 | AUC>0.8 | 81 |
| Motawi | 2016 | Plasma | downregulate: miR-92a, miR-100, miR-143 | 70/62 | AUC=0.926 | 78 |
Characteristics of common methods used in miRNA diagnosis
| Methods | Advantage | Limitation | Reforence |
|---|---|---|---|
| RT-RCR | Easy to operate and high sensi | Low thoughput, Expen | 91-93 |
| Microarray | High throughput | Lack of quantitative dat | 99-102 |
| Nortern blot analysis | Gold standard, High specificity | Poor sensitivity | 86-89 |
| Bioluminescence | High sensitivity | Complex steps | 90 |
| In situ hybridization | High speicificity | Low thoughput, Expen | 95-98 |
| Fluorescence correlation spectro | High sensitivity | Special equipment | 94 |