Literature DB >> 24476895

Serous ovarian cancer signaling pathways.

Ioannis C Kotsopoulos1, Alexios Papanikolaou, Alexandros F Lambropoulos, Konstantinos T Papazisis, Dimitrios Tsolakidis, Panagiota Touplikioti, Basil C Tarlatzis.   

Abstract

Ovarian cancer is the most lethal malignancy of the female genital tract, mainly due to the failure of early diagnosis and the limitations posed by the conventional chemotherapies. Current research has focused in the study of cascades of various cellular molecular reactions, known as signaling pathways. In this review article, authors try to describe the current knowledge regarding the signaling pathways that influence multiple cellular processes in serous ovarian cancer and especially the pathogenesis. Thorough understanding of the precise role of these pathways can lead to the development of new and more effective targeted therapies as well as novel biomarkers in ovarian cancer.

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Year:  2014        PMID: 24476895     DOI: 10.1097/IGC.0000000000000079

Source DB:  PubMed          Journal:  Int J Gynecol Cancer        ISSN: 1048-891X            Impact factor:   3.437


  5 in total

1.  Functional redundancy of the Notch pathway in ovarian cancer cell lines.

Authors:  Fernanda Silva; Ana Félix; Jacinta Serpa
Journal:  Oncol Lett       Date:  2016-08-05       Impact factor: 2.967

2.  Discover the molecular biomarker associated with cell death and extracellular matrix module in ovarian cancer.

Authors:  Qiang Liu; Jianxin Guo; Jinghong Cui; Jing Wang; Ping Yi
Journal:  Biomed Res Int       Date:  2015-03-16       Impact factor: 3.411

3.  Ex Vivo Expanded Human Vγ9Vδ2 T-Cells Can Suppress Epithelial Ovarian Cancer Cell Growth.

Authors:  Tsui Lien Mao; Carol H Miao; Yi Jen Liao; Ying Jen Chen; Chia Yu Yeh; Chao Lien Liu
Journal:  Int J Mol Sci       Date:  2019-03-06       Impact factor: 5.923

4.  Systematic Identification of Characteristic Genes of Ovarian Clear Cell Carcinoma Compared with High-Grade Serous Carcinoma Based on RNA-Sequencing.

Authors:  Saya Nagasawa; Kazuhiro Ikeda; Kuniko Horie-Inoue; Sho Sato; Atsuo Itakura; Satoru Takeda; Kosei Hasegawa; Satoshi Inoue
Journal:  Int J Mol Sci       Date:  2019-09-04       Impact factor: 5.923

5.  Bayesian graphical models for computational network biology.

Authors:  Yang Ni; Peter Müller; Lin Wei; Yuan Ji
Journal:  BMC Bioinformatics       Date:  2018-03-21       Impact factor: 3.169

  5 in total

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