Current Concepts of Non-Coding RNAs in the Pathogenesis of Non-Clear Cell Renal Cell Carcinoma

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Publikace nespadá pod Ekonomicko-správní fakultu, ale pod Středoevropský technologický institut. Oficiální stránka publikace je na webu muni.cz.
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BARTH D.A. SLABÝ Ondřej KLEC C. JURÁČEK Jaroslav DRULA R. CALIN G.A. PICHLER M.

Rok publikování 2019
Druh Článek v odborném periodiku
Časopis / Zdroj Cancers
Fakulta / Pracoviště MU

Středoevropský technologický institut

Citace
www https://www.mdpi.com/2072-6694/11/10/1580
Doi http://dx.doi.org/10.3390/cancers11101580
Klíčová slova renal cell carcinoma; non-clear cell; lncRNA; miRNA; long noncoding RNA; microRNA biomarker
Přiložené soubory
Popis Renal cell carcinoma (RCC) is a relatively rare malignancy of the urinary tract system. RCC is a heterogenous disease in terms of underlying histology and its associated underlying pathobiology, prognosis and treatment schedule. The most prevalent histological RCC subtype is clear-cell renal cell carcinoma (ccRCC), accounting for about 70-80% of all RCCs. Though the pathobiology and treatment schedule for ccRCC are well-established, non-ccRCC subtypes account for 20%-30% of RCC altogether, and their underlying molecular biology and treatment options are poorly defined. The class of non-coding RNAs-molecules that are generally not translated into proteins-are new cancer drivers and suppressors in all types of cancer. Of these, small non-coding microRNAs (miRNAs) contribute to carcinogenesis by regulating posttranscriptional gene silencing. Additionally, a growing body of evidence supports the role of long non-coding RNAs (lncRNAs) in cancer development and progression. Most studies on non-coding RNAs in RCC focus on clear-cell histology, and there is a relatively limited number of studies on non-ccRCC subtypes. The aim of this review is to give an overview of the current knowledge regarding the role of non-coding RNAs (including short and long non-coding RNAs) in non-ccRCC and to highlight possible implications as diagnostic, prognostic and predictive biomarkers.
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