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Non-Coding RNAs and the Development of Chemoresistance to Docetaxel in Prostate Cancer: Regulatory Interactions and Approaches Based on Machine Learning Methods.
Pudova, Elena; Kobelyatskaya, Anastasiya; Emelyanova, Marina; Snezhkina, Anastasiya; Fedorova, Maria; Pavlov, Vladislav; Guvatova, Zulfiya; Dalina, Alexandra; Kudryavtseva, Anna.
Affiliation
  • Pudova E; Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia.
  • Kobelyatskaya A; Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia.
  • Emelyanova M; Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia.
  • Snezhkina A; Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia.
  • Fedorova M; Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia.
  • Pavlov V; Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia.
  • Guvatova Z; Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia.
  • Dalina A; Russian Clinical Research Center for Gerontology, Pirogov Russian National Research Medical University, Ministry of Healthcare of the Russian Federation, 129226 Moscow, Russia.
  • Kudryavtseva A; Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia.
Life (Basel) ; 13(12)2023 Dec 07.
Article in En | MEDLINE | ID: mdl-38137905
ABSTRACT
Chemotherapy based on taxane-class drugs is the gold standard for treating advanced stages of various oncological diseases. However, despite the favorable response trends, most patients eventually develop resistance to this therapy. Drug resistance is the result of a combination of different events in the tumor cells under the influence of the drug, a comprehensive understanding of which has yet to be determined. In this review, we examine the role of the major classes of non-coding RNAs in the development of chemoresistance in the case of prostate cancer, one of the most common and socially significant types of cancer in men worldwide. We will focus on recent findings from experimental studies regarding the prognostic potential of the identified non-coding RNAs. Additionally, we will explore novel approaches based on machine learning to study these regulatory molecules, including their role in the development of drug resistance.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Life (Basel) Year: 2023 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Life (Basel) Year: 2023 Document type: Article Affiliation country: Country of publication: