Abstract
Among all diseases of malignant tumors in female genitalia, the ovarian cancer is the disease with highest death rate. However, the early clinical symptoms of this disease are latent, which results in the lack of effective early diagnosis method. Therefore, many patients with this disease have been in the later period clinically at the time of definite diagnosis. According to the statistics, the survival rate of patients with ovarian cancer in the later period within 5 years is only 30%, while the survival rate of patients with ovarian cancer in the early period within 5 years can be 70%-90%. Therefore, the early diagnosis plays an important role in improving the prognosis of ovarian cancer. In recent years, with its high specificity and high sensitivity, the molecular diagnosis technology is widely used to monitor the content of tumor markers in ovarian cancer tissue and also used in screening the high risk group to improve the prognosis of patients with ovarian cancer. The adoption of several methods in the molecular diagnosis technology usually used to monitor tumor markers in ovarian cancer diagnosis is discussed about in this paper.
References
[1] Zhang Q, Yu JP, Xu WW. Value of HE4 in Early Ovarian Cancer Diagnosis. Journal of Molecular Diagnosis & Therapy, 2013;5(1).
[2] Menon U, Jacobs IJ. Recent developments in ovarian cancer screening. Curr Opin Obstet Gynecol 2000;12:39-42.
[3] Zhang H, Kong BH, Qu X. Application of SELDI-TOF-MS in Ovarian Cancer. Journal of International Oncology, 2006;3(3).
[4] Michael EH, Irina P, Kenneth H, et al. Identification of differentially expressed proteins in ovarian cancer using high density protein microarrays[J ]. PNAS, 2007, 104(44) : 17494 - 9.
[5] Jemal A , Siegel R , Ward E , Murray T , Xu J , Smigal C , Thun M. CA Cancer J Clin 2006; 56:106-130.
[6] Fan QC, Li PL. Role of Tiny RNA in Ovarian Cancer. Chinese Journal of Birth Health & Heredity, 2013; 21(5).
[7] Paul E, Blower PE, Chung JH, Verducci JS, Lin S, Park JK, et al. MicroRNAs modulate the chemosensitivity of tumor cells. Mol Cancer Therap 2008;7:1-9.
[8] Huard C, Gaasenbeek M, Mesirov JP, et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 1999;286:531-7.
[9] Iorio MV, Visone R, Di Leva G, Donati V, Petrocca F, Casalini P, et al. MicroRNA signatures in human ovarian cancer. Cancer Res 2007;67: 8699-707.
[10] Bard MP, Hegmans JP, Hemmes A, et al. Proteomic analysis of exosomes isolated from human malignant pleural effusions. Am J Respir Cell Mol Biol 2004;31:114-21.
How to cite this paper
Application of Molecular Diagnosis in Ovarian Cancer Diagnosis
How to cite this paper: Ayanpan Palanisamy, Himani Nandana. (2017). Application of Molecular Diagnosis in Ovarian Cancer Diagnosis. International Journal of Clinical and Experimental Medicine Research, 1(1), 5-9.
DOI: http://dx.doi.org/10.26855/ijcemr.2017.01.002