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Insight toward the microRNA profiling of laryngeal cancers: Biological role and clinical impact

Articolo
Data di Pubblicazione:
2020
Abstract:
Head and neck squamous cell carcinoma (HNSCC), a heterogeneous disease arising from various anatomical locations including the larynx, is a leading cause of death worldwide. Despite advances in multimodality treatment, the overall survival rate of the disease is still largely dismal. Early and accurate diagnosis of HNSCC is urgently demanded in order to prevent cancer progression and to improve the quality of the patient’s life. Recently, microRNAs (miRNAs), a family of small non-coding RNAs, have been widely reported as new robust tools for prediction, diagnosis, prognosis, and therapeutic approaches of human diseases. Abnormally expressed miRNAs are strongly associated with cancer development, resistance to chemo-/radiotherapy, and metastatic potential through targeting a large variety of genes. In this review, we summarize on the recent reports that emphasize the pivotal biological roles of miRNAs in regulating carcinogenesis of HNSCC, particularly laryngeal cancer. In more detail, we report the characterized miRNAs with an evident either oncogenic or tumor suppressive role in the cancers. In addition, we also focus on the correlation between miRNA deregulation and clinical relevance in cancer patients. On the basis of intriguing findings, the study of miRNAs will provide a new great opportunity to access better clinical management of the malignancies. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Takeuchi, T; Kawasaki, H; Luce, A; Cossu, Am; Misso, G; Scrima, M; Bocchetti, M; Ricciardiello, F; Caraglia, M; Zappavigna, S
Autori di Ateneo:
BOCCHETTI MARCO
Link alla scheda completa:
https://iris.unilink.it/handle/20.500.14085/22309
Pubblicato in:
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
Journal
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https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085470319&doi=10.3390/ijms21103693&partnerID=40&md5=7eeb32d749d58aafc497f36725a04911
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