非编码RNA和前列腺癌中对多塞素的化学抵抗的发展:基于机器学习方法的调控相互作用和方法
Elena Pudova1, Anastasiya Kobelyatskaya1, Marina Emelyanova1
1Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia.
Life (Basel, Switzerland)
|December 23, 2023
概括
纳化学疗法是晚期癌症的标准治疗方法,但抗药性发展. 本综述探讨了非编码RNA如何促进前列腺癌中对分类剂的抗性及其预后潜力.
科学领域:
- 在瘤学瘤学.
- 分子生物学分子生物学
- 遗传学 是一个遗传学.
背景情况:
- 基于taxane的化疗是晚期癌症的基石治疗.
- 瘤细胞经常对税疗法产生抗性,从而限制治疗的疗效.
- 抗分类物耐药性背后的分子机制是复杂的,并未完全理解.
研究的目的:
- 审查非编码RNAs在税种化学抵抗的发展中的作用.
- 突出非编码RNA在前列腺癌中的预后潜力.
- 探索机器学习方法来研究药物耐药性的非编码RNA.
主要方法:
- 关于非编码RNA和化学抵抗的实验研究的文献综述.
- 分析与非编码RNA表达和功能相关的发现.
- 讨论机器学习在非编码RNA研究中的应用.
主要成果:
- 非编码RNAs,包括microRNAs和长非编码RNAs,都涉及到对分类体的耐药性.
- 特定的非编码RNAs在接受税治疗的前列腺癌患者中显示出预后价值.
- 机器学习为识别和理解非编码RNA的调节作用提供了新的途径.
结论:
- 非编码RNAs是关键调节器在发展的税种化学抵抗.
- 向特定的非编码RNA可能为克服抗性提供新的治疗策略.
- 需要在机器学习的帮助下进行进一步的研究,以充分阐明非编码RNA在癌症药物耐药性中的作用.
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