Kapinova Andrea, Mazurakova Alena, Halasova Erika, Dankova Zuzana, Büsselberg Dietrich, Costigliola Vincenzo, Golubnitschaja Olga, Kubatka Peter
Biomedical Center Martin, Jessenius Faculty of Medicine, Comenius University in Bratislava, 036 01 Martin, Slovakia.
Department of Anatomy, Jessenius Faculty of Medicine, Comenius University in Bratislava, 036 01 Martin, Slovakia.
EPMA J. 2023 May 22;14(2):249-273. doi: 10.1007/s13167-023-00323-7. eCollection 2023 Jun.
Breast cancer (BC) is the most common female malignancy reaching a pandemic scale worldwide. A comprehensive interplay between genetic alterations and shifted epigenetic regions synergistically leads to disease development and progression into metastatic BC. DNA and histones methylations, as the most studied epigenetic modifications, represent frequent and early events in the process of carcinogenesis. To this end, long non-coding RNAs (lncRNAs) are recognized as potent epigenetic modulators in pathomechanisms of BC by contributing to the regulation of DNA, RNA, and histones' methylation. In turn, the methylation status of DNA, RNA, and histones can affect the level of lncRNAs expression demonstrating the reciprocity of mechanisms involved. Furthermore, lncRNAs might undergo methylation in response to actual medical conditions such as tumor development and treated malignancies. The reciprocity between genome-wide methylation status and long non-coding RNA expression levels in BC remains largely unexplored. Since the bio/medical research in the area is, per evidence, strongly fragmented, the relevance of this reciprocity for BC development and progression has not yet been systematically analyzed. Contextually, the article aims at:consolidating the accumulated knowledge on both-the genome-wide methylation status and corresponding lncRNA expression patterns in BC andhighlighting the potential benefits of this consolidated multi-professional approach for advanced BC management. Based on a big data analysis and machine learning for individualized data interpretation, the proposed approach demonstrates a great potential to promote predictive diagnostics and targeted prevention in the cost-effective primary healthcare (sub-optimal health conditions and protection against the health-to-disease transition) as well as advanced treatment algorithms tailored to the individualized patient profiles in secondary BC care (effective protection against metastatic disease). Clinically relevant examples are provided, including mitochondrial health control and epigenetic regulatory mechanisms involved.
乳腺癌(BC)是全球范围内最常见的女性恶性肿瘤,已呈大流行态势。基因改变与表观遗传区域变化之间的全面相互作用协同导致疾病发展并进展为转移性乳腺癌。DNA和组蛋白甲基化作为研究最多的表观遗传修饰,是致癌过程中常见的早期事件。为此,长链非编码RNA(lncRNA)通过参与DNA、RNA和组蛋白甲基化的调控,被认为是乳腺癌发病机制中强大的表观遗传调节因子。反过来,DNA、RNA和组蛋白的甲基化状态会影响lncRNA的表达水平,这表明相关机制存在相互作用。此外,lncRNA可能会因肿瘤发展和恶性肿瘤治疗等实际医疗状况而发生甲基化。乳腺癌中全基因组甲基化状态与长链非编码RNA表达水平之间的相互作用在很大程度上仍未得到探索。鉴于该领域的生物/医学研究证据显示非常零散,这种相互作用对乳腺癌发展和进展的相关性尚未得到系统分析。在此背景下,本文旨在:整合关于乳腺癌全基因组甲基化状态和相应lncRNA表达模式的积累知识,并强调这种整合的多专业方法对晚期乳腺癌管理的潜在益处。基于大数据分析和机器学习进行个性化数据解读,所提出的方法在具有成本效益的初级医疗保健(次优健康状况和预防健康向疾病转变)中促进预测性诊断和靶向预防以及在继发性乳腺癌护理中针对个性化患者档案定制先进治疗算法(有效预防转移性疾病)方面显示出巨大潜力。文中提供了临床相关实例,包括线粒体健康控制和涉及的表观遗传调控机制。