Stevens E V, Liotta L A, Kohn E C
Laboratory of Pathology, National Cancer Institute, Center for Cancer Research, NIH, Bethesda, MD 20892, USA.
Int J Gynecol Cancer. 2003 Nov-Dec;13 Suppl 2:133-9. doi: 10.1111/j.1525-1438.2003.13358.x.
Ovarian cancer is a multifaceted disease wherein most women are diagnosed with advanced stage disease. One of the most imperative issues in ovarian cancer is early detection. Biomarkers that allow cancer detection at stage I, a time when the disease is amenable to surgical and chemotherapeutic cure in over 90% of patients, can dramatically alter the horizon for women with this disease. Recent developments in mass spectroscopy and protein chip technology coupled with bioinformatics have been applied to biomarker discovery. The complexity of the proteome is a rich resource from which the patterns can be gleaned; the pattern rather than its component parts is the diagnostic. Serum is a key source of putative protein biomarkers, and, by its nature, can reflect organ-confined events. Pioneering use of mass spectroscopy coupled with bioinformatics has been demonstrated as being capable of distinguishing serum protein pattern signatures of ovarian cancer in patients with early- and late-stage disease. This is a sensitive, precise, and promising tool for which further validation is needed to confirm that ovarian cancer serum protein signature patterns can be a robust biomarker approach for ovarian cancer diagnosis, yielding improved patient outcome and reducing the death and suffering from ovarian cancer.
卵巢癌是一种多方面的疾病，其中大多数女性被诊断为晚期疾病。卵巢癌最紧迫的问题之一是早期检测。能够在I期检测出癌症的生物标志物，此时疾病在超过90%的患者中可通过手术和化疗治愈，这可以极大地改变这种疾病女性患者的前景。质谱和蛋白质芯片技术的最新进展与生物信息学相结合已被应用于生物标志物的发现。蛋白质组的复杂性是一个丰富的资源，可以从中收集模式；模式而非其组成部分才是诊断依据。血清是假定蛋白质生物标志物的关键来源，并且就其性质而言，可以反映器官局限性事件。已证明将质谱与生物信息学结合的开创性应用能够区分早期和晚期疾病患者卵巢癌的血清蛋白质模式特征。这是一种敏感、精确且有前景的工具，需要进一步验证以确认卵巢癌血清蛋白质特征模式可以成为卵巢癌诊断的一种可靠生物标志物方法，从而改善患者预后并减少卵巢癌导致的死亡和痛苦。
