The Role of miRNAs to Detect Progression, Stratify, and Predict Relevant Clinical Outcomes in Bladder Cancer
Abstract
1. Bladder Cancer Overview
2. miRNAs as Prognostic Tools in BC
3. Biological Plausibility of Described miRNAs in BC
4. Limitations of miRNA-Based Strategies for BC
5. Future Perspectives
6. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
- Siegel, R.L.; Miller, K.D.; Wagle, N.S.; Jemal, A. Cancer statistics, 2023. CA Cancer J. Clin. 2023, 73, 17–48. [Google Scholar] [CrossRef] [PubMed]
- Jubber, I.; Ong, S.; Bukavina, L.; Black, P.C.; Comperat, E.; Kamat, A.M.; Kiemeney, L.; Lawrentschuk, N.; Lerner, S.P.; Meeks, J.J.; et al. Epidemiology of Bladder Cancer in 2023: A Systematic Review of Risk Factors. Eur. Urol. 2023, 84, 176–190. [Google Scholar] [CrossRef] [PubMed]
- Nardelli, C.; Aveta, A.; Pandolfo, S.D.; Tripodi, L.; Russo, F.; Imbimbo, C.; Castaldo, G.; Pastore, L. Microbiome Profiling in Bladder Cancer Patients Using the First-morning Urine Sample. Eur. Urol. Open Sci. 2024, 59, 18–26. [Google Scholar] [CrossRef] [PubMed]
- Lenis, A.T.; Lec, P.M.; Chamie, K.; Mshs, M.D. Bladder Cancer: A Review. JAMA 2020, 324, 1980–1991. [Google Scholar] [CrossRef] [PubMed]
- Chang, S.S.; Boorjian, S.A.; Chou, R.; Clark, P.E.; Daneshmand, S.; Konety, B.R.; Pruthi, R.; Quale, D.Z.; Ritch, C.R.; Seigne, J.D.; et al. Diagnosis and Treatment of Non-Muscle Invasive Bladder Cancer: AUA/SUO Guideline. J. Urol. 2016, 196, 1021–1029. [Google Scholar] [CrossRef]
- Sanli, O.; Dobruch, J.; Knowles, M.A.; Burger, M.; Alemozaffar, M.; Nielsen, M.E.; Lotan, Y. Bladder cancer. Nat. Rev. Dis. Primers 2017, 3, 17022. [Google Scholar] [CrossRef]
- Amin, M.B.; Greene, F.L.; Edge, S.B.; Compton, C.C.; Gershenwald, J.E.; Brookland, R.K.; Meyer, L.; Gress, D.M.; Byrd, D.R.; Winchester, D.P. The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more “personalized” approach to cancer staging. CA Cancer J. Clin. 2017, 67, 93–99. [Google Scholar] [CrossRef]
- Dobruch, J.; Oszczudlowski, M. Bladder Cancer: Current Challenges and Future Directions. Medicina 2021, 57, 749. [Google Scholar] [CrossRef]
- Krishna, S.R.; Konety, B.R. Current Concepts in the Management of Muscle Invasive Bladder Cancer. Indian J. Surg. Oncol. 2017, 8, 74–81. [Google Scholar] [CrossRef]
- Yeung, C.; Dinh, T.; Lee, J. The health economics of bladder cancer: An updated review of the published literature. Pharmacoeconomics 2014, 32, 1093–1104. [Google Scholar] [CrossRef] [PubMed]
- Bree, K.K.; Shan, Y.; Hensley, P.J.; Lobo, N.; Hu, C.; Tyler, D.S.; Chamie, K.; Kamat, A.M.; Williams, S.B. Management, Surveillance Patterns, and Costs Associated With Low-Grade Papillary Stage Ta Non-Muscle-Invasive Bladder Cancer among Older Adults, 2004–2013. JAMA Netw. Open 2022, 5, e223050. [Google Scholar] [CrossRef] [PubMed]
- Lone, S.N.; Nisar, S.; Masoodi, T.; Singh, M.; Rizwan, A.; Hashem, S.; El-Rifai, W.; Bedognetti, D.; Batra, S.K.; Haris, M.; et al. Liquid biopsy: A step closer to transform diagnosis, prognosis and future of cancer treatments. Mol. Cancer 2022, 21, 79. [Google Scholar] [CrossRef] [PubMed]
- Zeng, Y.; Wang, A.; Lv, W.; Wang, Q.; Jiang, S.; Pan, X.; Wang, F.; Yang, H.; Bolund, L.; Lin, C.; et al. Recent development of urinary biomarkers for bladder cancer diagnosis and monitoring. Clin. Transl. Discov. 2023, 3, e183. [Google Scholar] [CrossRef]
- Yafi, F.A.; Brimo, F.; Steinberg, J.; Aprikian, A.G.; Tanguay, S.; Kassouf, W. Prospective analysis of sensitivity and specificity of urinary cytology and other urinary biomarkers for bladder cancer. Urol. Oncol. 2015, 33, 66.e25–66.e31. [Google Scholar] [CrossRef] [PubMed]
- Batista, R.; Vinagre, N.; Meireles, S.; Vinagre, J.; Prazeres, H.; Leão, R.; Máximo, V.; Soares, P. Biomarkers for Bladder Cancer Diagnosis and Surveillance: A Comprehensive Review. Diagnostics 2020, 10, 39. [Google Scholar] [CrossRef] [PubMed]
- Henry, N.L.; Hayes, D.F. Cancer biomarkers. Mol. Oncol. 2012, 6, 140–146. [Google Scholar] [CrossRef] [PubMed]
- Macfarlane, L.A.; Murphy, P.R. MicroRNA: Biogenesis, Function and Role in Cancer. Curr. Genom. 2010, 11, 537–561. [Google Scholar] [CrossRef]
- O’Brien, J.; Hayder, H.; Zayed, Y.; Peng, C. Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation. Front. Endocrinol. 2018, 9, 402. [Google Scholar] [CrossRef]
- Gebert, L.F.R.; MacRae, I.J. Regulation of microRNA function in animals. Nat. Rev. Mol. Cell Biol. 2019, 20, 21–37. [Google Scholar] [CrossRef]
- Cortez, M.A.; Bueso-Ramos, C.; Ferdin, J.; Lopez-Berestein, G.; Sood, A.K.; Calin, G.A. MicroRNAs in body fluids—The mix of hormones and biomarkers. Nat. Rev. Clin. Oncol. 2011, 8, 467–477. [Google Scholar] [CrossRef]
- Misiak, D.; Bauer, M.; Lange, J.; Haase, J.; Braun, J.; Lorenz, K.; Wickenhauser, C.; Hüttelmaier, S. MiRNA Deregulation Distinguishes Anaplastic Thyroid Carcinoma (ATC) and Supports Upregulation of Oncogene Expression. Cancers 2021, 13, 5913. [Google Scholar] [CrossRef] [PubMed]
- Nam, E.J.; Yoon, H.; Kim, S.W.; Kim, H.; Kim, Y.T.; Kim, J.H.; Kim, J.W.; Kim, S. MicroRNA expression profiles in serous ovarian carcinoma. Clin. Cancer Res. 2008, 14, 2690–2695. [Google Scholar] [CrossRef] [PubMed]
- Le, M.T.; Teh, C.; Shyh-Chang, N.; Xie, H.; Zhou, B.; Korzh, V.; Lodish, H.F.; Lim, B. MicroRNA-125b is a novel negative regulator of p53. Genes Dev 2009, 23, 862–876. [Google Scholar] [CrossRef]
- Ozen, M.; Creighton, C.J.; Ozdemir, M.; Ittmann, M. Widespread deregulation of microRNA expression in human prostate cancer. Oncogene 2008, 27, 1788–1793. [Google Scholar] [CrossRef]
- Wang, H.; Peng, R.; Wang, J.; Qin, Z.; Xue, L. Circulating microRNAs as potential cancer biomarkers: The advantage and disadvantage. Clin. Epigenetics 2018, 10, 59. [Google Scholar] [CrossRef] [PubMed]
- Kim, T.; Croce, C.M. MicroRNA: Trends in clinical trials of cancer diagnosis and therapy strategies. Exp. Mol. Med. 2023, 55, 1314–1321. [Google Scholar] [CrossRef]
- Zou, X.; Wei, J.; Huang, Z.; Zhou, X.; Lu, Z.; Zhu, W.; Miao, Y. Identification of a six-miRNA panel in serum benefiting pancreatic cancer diagnosis. Cancer Med. 2019, 8, 2810–2822. [Google Scholar] [CrossRef] [PubMed]
- Ma, W.; Yu, Q.; Jiang, J.; Du, X.; Huang, L.; Zhao, L.; Zhou, Q.I. miR-517a is an independent prognostic marker and contributes to cell migration and invasion in human colorectal cancer. Oncol. Lett. 2016, 11, 2583–2589. [Google Scholar] [CrossRef]
- Wang, F.; Chang, J.T.; Kao, C.J.; Huang, R.S. High Expression of miR-532-5p, a Tumor Suppressor, Leads to Better Prognosis in Ovarian Cancer Both In Vivo and In Vitro. Mol. Cancer Ther. 2016, 15, 1123–1131. [Google Scholar] [CrossRef]
- Zhang, X.; Zhang, Y.; Liu, X.; Fang, A.; Wang, J.; Yang, Y.; Wang, L.; Du, L.; Wang, C. Direct quantitative detection for cell-free miR-155 in urine: A potential role in diagnosis and prognosis for non-muscle invasive bladder cancer. Oncotarget 2016, 7, 3255–3266. [Google Scholar] [CrossRef]
- Zhang, X.; Zhang, Y.; Liu, X.; Fang, A.; Li, P.; Li, Z.; Liu, T.; Yang, Y.; Du, L.; Wang, C. MicroRNA-203 Is a Prognostic Indicator in Bladder Cancer and Enhances Chemosensitivity to Cisplatin via Apoptosis by Targeting Bcl-w and Survivin. PLoS ONE 2015, 10, e0143441. [Google Scholar] [CrossRef]
- Zhang, H.H.; Qi, F.; Cao, Y.H.; Zu, X.B.; Chen, M.F. Expression and clinical significance of microRNA-21, maspin and vascular endothelial growth factor-C in bladder cancer. Oncol. Lett. 2015, 10, 2610–2616. [Google Scholar] [CrossRef]
- Wang, J.; Zhang, X.; Wang, L.; Yang, Y.; Dong, Z.; Wang, H.; Du, L.; Wang, C. MicroRNA-214 Suppresses Oncogenesis and Exerts Impact on Prognosis by Targeting PDRG1 in Bladder Cancer. PLoS ONE 2015, 10, e0118086. [Google Scholar] [CrossRef]
- Wang, H.; Men, C.P. Correlation of Increased Expression of MicroRNA-155 in Bladder Cancer and Prognosis. Lab. Med. 2015, 46, 118–122. [Google Scholar] [CrossRef]
- Andrew, A.S.; Karagas, M.R.; Schroeck, F.R.; Marsit, C.J.; Schned, A.R.; Pettus, J.R.; Armstrong, D.A.; Seigne, J.D. MicroRNA Dysregulation and Non-Muscle-Invasive Bladder Cancer Prognosis. Cancer Epidemiol. Biomark. Prev. 2019, 28, 782–788. [Google Scholar] [CrossRef] [PubMed]
- Awadalla, A.; Abol-Enein, H.; Hamam, E.T.; Ahmed, A.E.; Khirallah, S.M.; El-Assmy, A.; Mostafa, S.A.; Babalghith, A.O.; Ali, M.; Abdel-Rahim, M.; et al. Identification of Epigenetic Interactions between miRNA and Gene Expression as Potential Prognostic Markers in Bladder Cancer. Genes 2022, 13, 1629. [Google Scholar] [CrossRef]
- Awadalla, A.; Zahran, M.H.; Abol-Enein, H.; Zekri, A.N.; Elbaset, M.A.; Ahmed, A.E.; Hamam, E.T.; Elsawy, A.; Khalifa, M.K.; Shokeir, A.A. Identification of Different miRNAs and Their Relevant miRNA Targeted Genes Involved in Sister Chromatid Cohesion and Segregation (SCCS)/chromatin Remodeling Pathway on T1G3 Urothelial Carcinoma (UC) Response to BCG Immunotherapy. Clin. Genitourin. Cancer 2022, 20, e181–e189. [Google Scholar] [CrossRef] [PubMed]
- Blanca, A.; Sanchez-Gonzalez, A.; Requena, M.J.; Carrasco-Valiente, J.; Gomez-Gomez, E.; Cheng, L.; Cimadamore, A.; Montironi, R.; Lopez-Beltran, A. Expression of miR-100 and miR-138 as prognostic biomarkers in non-muscle-invasive bladder cancer. Apmis 2019, 127, 545–553. [Google Scholar] [CrossRef] [PubMed]
- Braicu, C.; Buiga, R.; Cojocneanu, R.; Buse, M.; Raduly, L.; Pop, L.A.; Chira, S.; Budisan, L.; Jurj, A.; Ciocan, C.; et al. Connecting the dots between different networks: miRNAs associated with bladder cancer risk and progression. J. Exp. Clin. Cancer Res. 2019, 38, 433. [Google Scholar] [CrossRef]
- Borkowska, E.M.; Konecki, T.; Pietrusiński, M.; Borowiec, M.; Jabłonowski, Z. MicroRNAs Which Can Prognosticate Aggressiveness of Bladder Cancer. Cancers 2019, 11, 1551. [Google Scholar] [CrossRef]
- Cavallari, I.; Grassi, A.; Del Bianco, P.; Aceti, A.; Zaborra, C.; Sharova, E.; Bertazzolo, I.; D’Agostino, D.M.; Iafrate, M.; Ciminale, V. Prognostic Stratification of Bladder Cancer Patients with a MicroRNA-based Approach. Cancers 2020, 12, 3133. [Google Scholar] [CrossRef] [PubMed]
- Hao, Y.; Zhu, Y.; Sun, F.; Xu, D.; Wang, C. MicroRNA-30c-5p arrests bladder cancer G2/M phase and suppresses its progression by targeting PRC1-mediated blocking of CDK1/Cyclin B1 axis. Cell. Signal. 2023, 110, 110836. [Google Scholar] [CrossRef]
- Inamoto, T.; Uehara, H.; Akao, Y.; Ibuki, N.; Komura, K.; Takahara, K.; Takai, T.; Uchimoto, T.; Saito, K.; Tanda, N.; et al. A Panel of MicroRNA Signature as a Tool for Predicting Survival of Patients with Urothelial Carcinoma of the Bladder. Dis. Markers 2018, 2018, 5468672. [Google Scholar] [CrossRef]
- Juracek, J.; Stanik, M.; Vesela, P.; Radova, L.; Dolezel, J.; Svoboda, M.; Slaby, O. Tumor expression of miR-34a-3p is an independent predictor of recurrence in non-muscle-invasive bladder cancer and promising additional factor to improve predictive value of EORTC nomogram. Urol. Oncol. 2019, 37, 184.e181–184.e187. [Google Scholar] [CrossRef]
- Khan, M.T.; Irlam-Jones, J.J.; Pereira, R.R.; Lane, B.; Valentine, H.R.; Aragaki, K.; Dyrskjøt, L.; McConkey, D.J.; Hoskin, P.J.; Choudhury, A.; et al. A miRNA signature predicts benefit from addition of hypoxia-modifying therapy to radiation treatment in invasive bladder cancer. Br. J. Cancer 2021, 125, 85–93. [Google Scholar] [CrossRef] [PubMed]
- Lee, E.; Collazo-Lorduy, A.; Castillo-Martin, M.; Gong, Y.; Wang, L.; Oh, W.K.; Galsky, M.D.; Cordon-Cardo, C.; Zhu, J. Identification of microR-106b as a prognostic biomarker of p53-like bladder cancers by ActMiR. Oncogene 2018, 37, 5858–5872. [Google Scholar] [CrossRef] [PubMed]
- Li, Z.; Zhou, L.; Lin, C.; Pan, X.; Xie, J.; Zhao, L.; Quan, J.; Xu, J.; Guan, X.; Xu, W.; et al. MiR-302b regulates cell functions and acts as a potential biomarker to predict recurrence in bladder cancer. Life Sci. 2018, 209, 15–23. [Google Scholar] [CrossRef] [PubMed]
- Li, Z.; Lin, C.; Zhao, L.; Zhou, L.; Pan, X.; Quan, J.; Peng, X.; Li, W.; Li, H.; Xu, J.; et al. Oncogene miR-187-5p is associated with cellular proliferation, migration, invasion, apoptosis and an increased risk of recurrence in bladder cancer. Biomed. Pharmacother. 2018, 105, 461–469. [Google Scholar] [CrossRef]
- Lin, G.B.; Zhang, C.M.; Chen, X.Y.; Wang, J.W.; Chen, S.; Tang, S.Y.; Yu, T.Q. Identification of circulating miRNAs as novel prognostic biomarkers for bladder cancer. Math. Biosci. Eng. 2019, 17, 834–844. [Google Scholar] [CrossRef]
- Lin, T.; Zhou, S.; Gao, H.; Li, Y.; Sun, L. MicroRNA-325 Is a Potential Biomarker and Tumor Regulator in Human Bladder Cancer. Technol. Cancer Res. Treat. 2018, 17, 1533033818790536. [Google Scholar] [CrossRef]
- Liu, G.; Chen, Z.; Danilova, I.G.; Bolkov, M.A.; Tuzankina, I.A.; Liu, G. Identification of miR-200c and miR141-Mediated lncRNA-mRNA Crosstalks in Muscle-Invasive Bladder Cancer Subtypes. Front. Genet. 2018, 9, 422. [Google Scholar] [CrossRef]
- Liu, C.P.; Zhang, J.H.; Zheng, S.C.; Liu, J.; Guo, J.C. A novel clinical multidimensional transcriptome signature predicts prognosis in bladder cancer. Oncol. Rep. 2018, 40, 2826–2835. [Google Scholar] [CrossRef]
- Liu, D.; Zhou, B.; Liu, R. An RNA-sequencing-based transcriptome for a significantly prognostic novel driver signature identification in bladder urothelial carcinoma. PeerJ 2020, 8, e9422. [Google Scholar] [CrossRef]
- Liu, Y.; Zhu, D.Y.; Xing, H.J.; Hou, Y.; Sun, Y. A potential prognostic model based on miRNA expression profile in The Cancer Genome Atlas for bladder cancer patients. J. Biol. Res. 2020, 27, 6. [Google Scholar] [CrossRef]
- Pan, C.; Luo, J.; Zhang, J. Computational Identification of RNA-Seq Based miRNA-Mediated Prognostic Modules in Cancer. IEEE J. Biomed. Health Inform. 2020, 24, 626–633. [Google Scholar] [CrossRef]
- Rabien, A.; Ratert, N.; Högner, A.; Erbersdobler, A.; Jung, K.; Ecke, T.H.; Kilic, E. Diagnostic and Prognostic Potential of MicroRNA Maturation Regulators Drosha, AGO1 and AGO2 in Urothelial Carcinomas of the Bladder. Int. J. Mol. Sci. 2018, 19, 1622. [Google Scholar] [CrossRef]
- Setti Boubaker, N.; Cicchillitti, L.; Said, R.; Gurtner, A.; Ayed, H.; Blel, A.; Karray, O.; Essid, M.A.; Gharbi, M.; Bouzouita, A.; et al. The clinical and prognostic value of miR-9 gene expression in Tunisian patients with bladder cancer. Mol. Biol. Rep. 2019, 46, 4743–4750. [Google Scholar] [CrossRef]
- Shee, K.; Seigne, J.D.; Karagas, M.R.; Marsit, C.J.; Hinds, J.W.; Schned, A.R.; Pettus, J.R.; Armstrong, D.A.; Miller, T.W.; Andrew, A.S. Identification of Let-7f-5p as a novel biomarker of recurrence in non-muscle invasive bladder cancer. Cancer Biomark. 2020, 29, 101–110. [Google Scholar] [CrossRef] [PubMed]
- Tsikrika, F.D.; Avgeris, M.; Levis, P.K.; Tokas, T.; Stravodimos, K.; Scorilas, A. miR-221/222 cluster expression improves clinical stratification of non-muscle invasive bladder cancer (TaT1) patients’ risk for short-term relapse and progression. Genes Chromosomes Cancer 2018, 57, 150–161. [Google Scholar] [CrossRef] [PubMed]
- Urabe, F.; Matsuzaki, J.; Ito, K.; Takamori, H.; Tsuzuki, S.; Miki, J.; Kimura, T.; Egawa, S.; Nakamura, E.; Matsui, Y.; et al. Serum microRNA as liquid biopsy biomarker for the prediction of oncological outcomes in patients with bladder cancer. Int. J. Urol. 2022, 29, 968–976. [Google Scholar] [CrossRef] [PubMed]
- Wang, W.; Liu, Z.; Zhang, X.; Liu, J.; Gui, J.; Cui, M.; Li, Y. miR-211-5p is down-regulated and a prognostic marker in bladder cancer. J. Gene Med. 2020, 22, e3270. [Google Scholar] [CrossRef]
- Ware, A.P.; Kabekkodu, S.P.; Chawla, A.; Paul, B.; Satyamoorthy, K. Diagnostic and prognostic potential clustered miRNAs in bladder cancer. 3 Biotech 2022, 12, 173. [Google Scholar] [CrossRef] [PubMed]
- Wei, X.; Bian, F.; Cai, X.; Wang, Y.; Cai, L.; Yang, J.; Zhu, Y.; Zhao, Y. Multiplexed Detection Strategy for Bladder Cancer MicroRNAs Based on Photonic Crystal Barcodes. Anal. Chem. 2020, 92, 6121–6127. [Google Scholar] [CrossRef] [PubMed]
- Wu, C.L.; Ho, J.Y.; Hung, S.H.; Yu, D.S. miR-429 expression in bladder cancer and its correlation with tumor behavior and clinical outcome. Kaohsiung J. Med. Sci. 2018, 34, 335–340. [Google Scholar] [CrossRef] [PubMed]
- Xiong, J.; Xiong, K.; Bing, Z. Clinical and RNA expression integrated signature for urothelial bladder cancer prognosis. Cancer Biomark. 2018, 21, 535–546. [Google Scholar] [CrossRef] [PubMed]
- Xv, Y.; Qiu, M.; Liu, Z.; Xiao, M.; Wang, F. Development of a 7-miRNA prognostic signature for patients with bladder cancer. Aging 2022, 14, 10093–10106. [Google Scholar] [CrossRef] [PubMed]
- Yang, L.; Sun, H.F.; Guo, L.Q.; Cao, H.B. MiR-10a-5p: A Promising Biomarker for Early Diagnosis and Prognosis Evaluation of Bladder Cancer. Cancer Manag. Res. 2021, 13, 7841–7850. [Google Scholar] [CrossRef] [PubMed]
- Yin, X.H.; Jin, Y.H.; Cao, Y.; Wong, Y.; Weng, H.; Sun, C.; Deng, J.H.; Zeng, X.T. Development of a 21-miRNA Signature Associated With the Prognosis of Patients With Bladder Cancer. Front. Oncol. 2019, 9, 729. [Google Scholar] [CrossRef]
- Zaidi, N.; Siddiqui, Z.; Sankhwar, S.N.; Srivastava, A.N. Urinary microRNA-10a levels in diagnosis and prognosis of urinary bladder cancer. J. Cancer Res. Ther. 2023, 19, 1324–1329. [Google Scholar] [CrossRef]
- Zhang, Z.; Sang, Y.; Liu, Z.; Shao, J. Negative Correlation Between Circular RNA SMARC5 and MicroRNA 432, and Their Clinical Implications in Bladder Cancer Patients. Technol. Cancer Res. Treat. 2021, 20, 15330338211039110. [Google Scholar] [CrossRef]
- Zhu, N.; Hou, J.; Wu, Y.; Liu, J.; Li, G.; Zhao, W.; Ma, G.; Chen, B.; Song, Y. Integrated analysis of a competing endogenous RNA network reveals key lncRNAs as potential prognostic biomarkers for human bladder cancer. Medicine 2018, 97, e11887. [Google Scholar] [CrossRef]
- Qureshi, A.; Fahim, A.; Kazi, N.; Farsi Kazi, S.A.; Nadeem, F. Expression of miR-100 as a novel ancillary non-invasive biomarker for early detection of bladder carcinoma. J. Pak. Med. Assoc. 2018, 68, 759–763. [Google Scholar]
- Patnaik, S.; Mallick, R.; Yendamuri, S. Detection of MicroRNAs in Dried Serum Blots. Nat. Preced. 2010. [Google Scholar] [CrossRef]
- Valadi, H.; Ekström, K.; Bossios, A.; Sjöstrand, M.; Lee, J.J.; Lötvall, J.O. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat. Cell Biol. 2007, 9, 654–659. [Google Scholar] [CrossRef]
- Peltier, H.J.; Latham, G.J. Normalization of microRNA expression levels in quantitative RT-PCR assays: Identification of suitable reference RNA targets in normal and cancerous human solid tissues. Rna 2008, 14, 844–852. [Google Scholar] [CrossRef]
miRNAs Analyzed | Performance | Group Comparison | Type of miRNA | Source | Technique for Analysis | Sample Size | Validation | Authors and Year |
---|---|---|---|---|---|---|---|---|
miR-26b-5p | ↑ miR-26-5p = ↑ RFS miR-26-5p + BF = ↑ AUC of BF alone for recurrence | Low expression vs. High expression | Free and exosomal | Tissue, blood and urine | Microarrays | 231 | Yes | Andrew 2019 [35] |
miR-21, -199, -31, let-7a | ↑ miR-21, -199 and ↓ miR-31, let-7 in BGC non responders ↑ miR-21, -199 and ↓ miR-31, let-7 = ↓ RFS | NMIBC BCG responders vs. non-responders | Free | Tissue | RT-QPCR | 157 | No | Awadalla 2022 [36] |
miR-138-5p and miR-100-5p | ↑ miR-138-5p in LGT ↓ miR-138-5p in recurrent tumors ↑ miR-138-5p = ↑ RFS ↓ miR-100-5p = ↑ RFS and ↑ CSS | Low expression vs. High expression | Free | Tissue | RT-QPCR | 50 | No | Blanca 2019 [38] |
miR-205-5p, -20a-5p, -21-5p, -145-5p and -182-5p | ↑ miR-205-5p, -145-5p, and -21-5p = ↑ risk of death ↑ miR-20a-5p and -182-5p = ↑ risk of recurrence | Stage | Free | Tissue | RT-QPCR | 85 | No | Borkowska 2019 [40] |
miR-143, -139, -141, -205 and -23a | ↑ miR-141 and ↓ miR-143 = ↑ OS | Low grade vs. High grade | Free | Tissue | Microarrays, RT-QPCR and TCGA analysis | 450 | Yes | Braicu 2019 [39] |
miR-30c-5p | ↓ miR-30c-5p = Poor prognosis | Low expression vs. High expression | Free | Tissue | RT-QPCR and TCGA analysis | 445 | Yes | Hao 2023 [42] |
miR-34a-3p | ↓ miR-34a-3p = ↑ OS miR-34a-3p + EORTC nomogram = ↑ SE and SP for progression | Low expression vs. High expression | Free | Tissue | Microarrays and RT-QPCR | 137 | Yes | Juracek 2019 [44] |
miR-106b-5p | ↑ miR-106b-5p = ↑ OS | Low expression vs. High expression | Free | Tissue | TCGA and Choi analysis | 1071 | Yes | Lee 2018 [46] |
miR-302-b | ↓ miR-302-b = ↓ RFS | Low expression vs. High expression | Free | Tissue | RT-QPCR | 39 | No | Li 2018 [47] |
miR-187-5p | ↑ miR-187-5p = ↑ Recurrence risk | Low expression vs. High expression | Free | Tissue | RT-QPCR | 44 | No | Li 2018 [48] |
miR-325 | ↑ miR-325 = ↓ OS | Low expression vs. High expression | Free | Tissue | RT-QPCR | 164 | No | Lin 2018 [50] |
miR-141-5p, -141-3p and -200c-3p | ↑ miR-141-5p, -141-3p and -200c-3p = ↑ OS | Low expression vs. High expression | Free | Tissue | TCGA analysis | 403 | No | Liu 2018 [51] |
AGO1, AGO2 and Drosha | ↑ Drosha = ↑ OS | Low expression vs. High expression | Free | Tissue | Microarrays | 112 | No | Rabien 2018 [56] |
Let-7f-5p | ↑ Let-7f-5p = ↑ RFS | Low expression vs. High expression | Free and exosomal | Tissue, blood and urine | NanoString’s amplification | 207 | Yes | Shee 2020 [58] |
miR-211-5p | ↓ miR-211-5p = ↓ OS and ↑ TNM stage | Low expression vs. High expression | Free | Tissue | Microarrays and RT-QPCR | 58 | No | Wang 2020 [61] |
3 Clusters (miR-200c/miR-141) (miR-216a/miR-217) (miR-15b/miR-16-2) | ↑ (miR-200c/miR-141) = ↑ OS ↑ (miR-216a/miR-217) = ↓ OS | Degree of expression among BC patients | Free | Tissue | Cluster miRNA analysis TCGA analysis | 412 | No | Ware 2022 [62] |
miR-429 | ↓ miR-429 = ↓ 5-year OS and RFS | Low expression vs. High expression | Free | Tissue | In situ hybridization | 76 | No | Wu 2018 [64] |
miR-432 | ↑ miR-432 = ↑ OS and ↑ DFS | Low expression vs. High expression | Free | Tissue | RT-QPCR | 156 | No | Zhang 2021 [70] |
miR-195 | ↑ miR-195 = ↓ OS | Low expression vs. High expression | Free | Tissue | TCGA analysis | 418 | No | Zhu 2018 [71] |
miRNAs Analyzed | Performance | Group Comparison | Type of miRNA | Source | Technique for Analysis | Sample Size | Validation | Authors and Year |
---|---|---|---|---|---|---|---|---|
let-7a-5p, -449a-5p, -124-3p, -138-5p and -23a-5p | ↓ let-7a-5p, miR-449a-5p, -124-3p, and -138-5p = ↓ 1 and 5 yr. CSS and MIBC ↑ miR-23a-5p in MIBC vs. NMIBC | NMIBC vs. MIBC | Free | Tissue | RT-QPCR | 100 | No | Awadalla 2022 [37] |
miR-21, -34a, -141, 193a, -200a and -200c | miR-34a, -193a and -200a classified high vs. low risk SE 0.88, SP 0.8, and ACC 0.82 ↑ All 6-miR expression = ↓ RFS | Low/intermediate risk vs. High risk (For recurrence) | Free | Urine and plasma | RT-QPCR | 100 | No | Cavallari 2020 [41] |
9 miRNA signature | Aggressive BCa =↓OS | Aggressive vs. non aggressive BC | Free | Tissue | Microarray TCGA analysis | 87 | Yes | Inamoto 2018 [43] |
14 miRNA signature | Hypoxic =↓PFS and↓OS | Hypoxic MIBC vs. non-hypoxic MIBC | Free | Tissue | TCGA analysis | 657 | Yes | Khan 2021 [45] |
7 miRNA-based score (-185-5p, -66a, -30c-5p, -3648, -1270, -200c-3p, and -29c-5p) | ↑Score =↓OS | High score BC vs. Low score BC | Free | Serum | Microarrays | 492 | No | Lin 2019 [49] |
Gene, lncmRNAs and miR-3913-1 and -981a score | ↑Score =↓OS Score had↑AUC vs. TNM for survival | High score BC vs. Low score BC | Free | Tissue | TCGA analysis | 239 | No | Liu 2018 [52] |
Genes, lncmRNAs and miR-497-5p | ↑Score =↓OS | Low risk vs. low risk (By score) | Free | Tissue | TCGA analysis | 400 | Yes | Liu 2020 [53] |
7 miRNA-based score (-1247, -1304, -1911, -204, -33b, -3934, and -526b) | ↑Score =↓OS AUC for 3–5-year survival 0.762 | Low risk vs. High risk (By score) | Free | Tissue | TCGA analysis | 428 | No | Liu 2020 [54] |
miR-17-5p, 19a-3p and 19b-3p | ↑Score =↓OS AUC 0.645 for progression | Low risk vs. High risk (By score) | Free | Tissue | TCGA analysis | 405 | No | Pan 2020 [55] |
Score lymph node + (miR-23a-3p, -3679-3p, and -3195) | Score AUC .88, SE 0.87, SP 0.30 for recurrence↓Score =↑OS | High vs. Low index | Free | Tissue | RQ-QPCR | 81 | Yes | Urabe 2022 [60] |
Clinical-mRNA-miRNA signature (miR-200c, -598 and -143) | CPV + signature =↑AUC and HR for↓5-year OS of both alone | Low risk vs. High risk (By score) | Free | Tissue | TCGA analysis | 402 | No | Xiong 2018 [65] |
7 miRNA signature (-151-a-5p, -216a-5p, -337-3p, -let-7c, -125-b, -590-3p, 652-3p) | ↑Score =↓OS and↑AUC of CPV | Low risk vs. High risk (By score) | Free | Tissue | RT-QPCR TCGA Analysis | 432 | No | Xv 2022 [66] |
21 miRNA signature | ↑Score =↓OS | Low risk vs. High risk (By score) | Free | Tissue | TCGA analysis | 427 | No | Yin 2019 [68] |
miRNAs Analyzed | Performance | Group Comparison | Type of miRNA | Source | Technique for Analysis | Sample size | Validation | Authors and Year |
---|---|---|---|---|---|---|---|---|
miR-9 | ↑ miR-9 in MIBC vs. NMIBC ↑ miR-9 in HG NMIBC vs. LG NMIBC | MIBC vs. NMIBC//LG NMIBC vs. HG NMIBC | Free | Tissue | RT-QPCR | 90 | No | Setti 2019 [57] |
miR-222 | ↑ miR-222 in MIBC vs. NMIBC ↑ miR-222 in HG NMIBC vs. LG NMIBC ↑ miR-222 = ↓ RFS, ↓ DFS, ↓ PFS | Low expression vs. High expression | Free | Tissue | RT-QPCR | 387 | No | Tsikrika 2018 [59] |
miR-133a, -143, and -200b | ↓ miR-200b associated with MIBC | Low expression vs. High expression | Free | Tissue | Photonic crystal (PhC) barcodes with hybridization chain reaction (HCR) | 10 | No | Wei 2020 [63] |
miR-10a-5p | ↑ miR-10a-5p in MIBC vs. NMIBC AUC 0.78, SE 0.75, SP 0.64 for MIBC vs. NMIBC, ↓ OS and RFS | Low expression vs. High expression | Free | Tissue and plasma | RQ-QPCR | 244 | Yes | Yang 2021 [67] |
miR-10a | ↑ miR-10a = ↑ Grade and ↑ Stage | Low expression vs. High expression | Free | Tissue and urine | RT-QPCR | 20 | No | Zaidi 2023 [69] |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Torres-Bustamante, M.I.; Vazquez-Urrutia, J.R.; Solorzano-Ibarra, F.; Ortiz-Lazareno, P.C. The Role of miRNAs to Detect Progression, Stratify, and Predict Relevant Clinical Outcomes in Bladder Cancer. Int. J. Mol. Sci. 2024, 25, 2178. https://doi.org/10.3390/ijms25042178
Torres-Bustamante MI, Vazquez-Urrutia JR, Solorzano-Ibarra F, Ortiz-Lazareno PC. The Role of miRNAs to Detect Progression, Stratify, and Predict Relevant Clinical Outcomes in Bladder Cancer. International Journal of Molecular Sciences. 2024; 25(4):2178. https://doi.org/10.3390/ijms25042178
Chicago/Turabian StyleTorres-Bustamante, Maria Iyali, Jorge Raul Vazquez-Urrutia, Fabiola Solorzano-Ibarra, and Pablo Cesar Ortiz-Lazareno. 2024. "The Role of miRNAs to Detect Progression, Stratify, and Predict Relevant Clinical Outcomes in Bladder Cancer" International Journal of Molecular Sciences 25, no. 4: 2178. https://doi.org/10.3390/ijms25042178
APA StyleTorres-Bustamante, M. I., Vazquez-Urrutia, J. R., Solorzano-Ibarra, F., & Ortiz-Lazareno, P. C. (2024). The Role of miRNAs to Detect Progression, Stratify, and Predict Relevant Clinical Outcomes in Bladder Cancer. International Journal of Molecular Sciences, 25(4), 2178. https://doi.org/10.3390/ijms25042178