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Panels of protein biomarkers and non-protein markers in the diagnosis of the ovarian cancer

机译:蛋白质生物标志物和非蛋白质标志物在卵巢癌诊断中的应用

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Ovarian cancer is, not without reason, called the?“silent killer”. It is one of the?most difficult problems in gynecologic oncology. In the?absence of specific symptoms it is recognized in the?advanced stages of the?disease, which greatly reduces the?effectiveness of therapy. Therefore, there is a?need for new methods for early diagnosis of cancer. They can not only assist in the?detection of cancer but also provide information on the?effectiveness of the?treatment. It is important that the?tumour markers are determined in the?least invasive and less expensive way so as to be used for large-scale screening. The?current standard is to use a?protein marker CA125, which is not sufficiently sensitive and specific. So it is supported by determination of additional protein markers and statistical methods. It is reasonable to use the?so-called biomarker panels, the?test of more than one marker to achieve the?highest sensitivity and specificity. The?algorithm ROMA and test OVA1 are used. Currently, studies on the?introduction of further markers, including non-protein markers are underway. With the?rapid development of genetics, proteomics and metabolomics, a?number of compounds are identified which can be used in screening tests for the?early detection of ovarian cancer. This paper presents the?latest news on biomarkers in the?diagnosis and treatment of ovarian cancer. The?analysis of genetic material, including both the?detection of gene mutations and epigenetic changes and microRNA studies, seems to be very promising.
机译:卵巢癌并非毫无道理地被称为“沉默杀手”。这是妇科肿瘤学中最困难的问题之一。在缺乏特定症状的情况下,在疾病的晚期就认识到这一点,这大大降低了治疗的有效性。因此,需要新的方法来早期诊断癌症。它们不仅可以帮助检测癌症,还可以提供有关治疗效果的信息。重要的是,以最小的侵入性和更便宜的方式确定肿瘤标志物,以便用于大规模筛查。当前的标准是使用不够灵敏和特异的蛋白质标记CA125。因此,可以通过确定其他蛋白质标记和统计方法来支持它。使用所谓的生物标志物面板(一种以上的标志物测试)以达到最高的灵敏度和特异性是合理的。使用算法ROMA和测试OVA1。目前,有关引入其他标记物,包括非蛋白质标记物的研究正在进行中。随着遗传学,蛋白质组学和代谢组学的迅速发展,已鉴定出许多化合物,这些化合物可用于筛选检测以早期发现卵巢癌。本文介绍了有关卵巢癌诊断和治疗中生物标志物的最新消息。遗传材料的分析,包括基因突变和表观遗传变化的检测以及microRNA研究,似乎是很有前途的。

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