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Clinical application of proteomics in ovarian cancer prevention and treatment.

机译:蛋白质组学在卵巢癌防治中的临床应用。

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As recent scientific findings using whole-genome mutational scanning technologies have concluded, cancer is a protein pathway disease, which is often diagnosed too late, when the success of therapeutic modalities is very limited. Proteomics has been proposed as the field that can help overcome this limitation and usher in a new era of molecular investigation for early diagnosis and classification of tumors. Proteomics applications in cancer research encompass two general aspects: (i) the study and characterization of protein production; and (ii) the definition of protein function. The first aims to identify qualitative or quantitative differences in the proteome that can help differentiate between healthy and diseased states or achieve a better clinical classification of diseases. The second studies the complexity of protein interactions and their activation states, mapping the network of signaling pathways within and outside the cells. The challenges in translating the findings of proteomics research into clinical practice are numerous. Lack of reproducibility, variable availability of samples and the bias associated with their selection and handling, the need for large, prospective validation trials, and finally the strict requirement for a very high level of clinical sensitivity and specificity are some of the hurdles that need to be overcome to achieve early detection and treatment. Nevertheless, proteomics is a field in rapid progression that has already developed beyond initial criticism and is making its way toward important applications and discoveries. Specifically, there has been an increasing number of reports on the potential clinical application of proteomics for early detection as well as risk assessment and management of ovarian cancer. This disease is the leading cause of death from gynecologic malignancies in the US, with poor prognosis resulting from the lack of reliable, sensitive screening tests and the limited understanding of the mechanisms of chemoresistance and relapse. In the future, serum proteomics applications in the gynecologic oncology field could identify blood-based biomarkers that are predictors of disease presence or progression, and tissue proteomics could help define the optimal targeted agent and effective dose for each patient's disease. These advances will allow improved monitoring of therapy response and disease relapse, and aid in the engineering of new drugs and strategies to circumvent resistance mechanisms while avoiding the adverse effects of traditional chemotherapy.
机译:正如最近使用全基因组突变扫描技术的科学发现所得出的结论,癌症是一种蛋白质途径疾病,通常在治疗方法的成功非常有限的情况下,诊断为时已晚。已经提出了蛋白质组学作为可以克服这一局限性的领域,并开创了分子研究的新纪元,以进行肿瘤的早期诊断和分类。蛋白质组学在癌症研究中的应用包括两个一般方面:(i)蛋白生产的研究和表征; (ii)蛋白质功能的定义。第一个目标是确定蛋白质组中的质或量差异,以帮助区分健康状态和患病状态或实现更好的疾病临床分类。第二篇研究了蛋白质相互作用及其激活状态的复杂性,绘制了细胞内外的信号通路网络。将蛋白质组学研究结果转化为临床实践面临着诸多挑战。缺乏可重复性,样品的可变性以及与样品的选择和处理有关的偏差,需要进行大规模的前瞻性验证试验以及最终对非常高的临床敏感性和特异性提出了严格的要求,这是需要克服的一些障碍被克服以实现早期发现和治疗。然而,蛋白质组学是一个快速发展的领域,已经超越了最初的批评而发展起来,并正在走向重要的应用和发现。具体而言,关于蛋白质组学在早期发现以及卵巢癌风险评估和管理中潜在临床应用的报道越来越多。该疾病是美国妇科恶性肿瘤死亡的主要原因,由于缺乏可靠,敏感的筛查测试以及对化学抗药性和复发机制的了解有限,因此预后较差。将来,血清蛋白质组学在妇科肿瘤学领域的应用可以识别出以血液为基础的生物标志物,这些生物标志物可以预测疾病的存在或发展,组织蛋白质组学可以帮助确定每种患者疾病的最佳靶向药物和有效剂量。这些进展将有助于改善对治疗反应和疾病复发的监测,并有助于设计新药和策略来规避耐药性机制,同时避免传统化学疗法的不利影响。

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