个性化医疗
癌症
计算生物学
精确肿瘤学
核糖核酸
医学
癌症研究
肿瘤科
生物信息学
内科学
生物
遗传学
基因
作者
Hector Katifelis,Maria Gazouli
出处
期刊:Advances in Clinical Chemistry
日期:2024-01-01
卷期号:: 179-219
标识
DOI:10.1016/bs.acc.2024.06.003
摘要
Cancer therapy is a rapidly evolving and constantly expanding field. Current approaches include surgery, conventional chemotherapy and novel biologic agents as in immunotherapy, that together compose a wide armamentarium. The plethora of choices can, however, be clinically challenging in prescribing the most suitable treatment for any given patient. Fortunately, biomarkers can greatly facilitate the most appropriate selection. In recent years, RNA-based biomarkers have proven most promising. These molecules that range from small noncoding RNAs to protein coding gene transcripts can be valuable in cancer management and especially in cancer therapeutics. Compared to their DNA counterparts which are stable throughout treatment, RNA-biomarkers are dynamic. This allows prediction of success prior to treatment start and can identify alterations in expression that could reflect response. Moreover, improved nucleic acid technology allows RNA to be extracted from practically every biofluid/matrix and evaluated with exceedingly high analytic sensitivity. In addition, samples are largely obtained by minimally invasive procedures and as such can be used serially to assess treatment response real-time. This chapter provides the reader insight on currently known RNA biomarkers, the latest research employing Artificial Intelligence in the identification of such molecules and in clinical decisions driving forward the era of personalized oncology.
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