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Integration of Bioinformatics Approaches and Experimental Validations to Understand the Role of Notch Signaling in Ovarian Cancer
Published on: January 12, 2020
In silico chromosomal clustering of genes displaying altered expression patterns in ovarian cancer
Ofir Israeli1, Ayala Goldring-Aviram, Shlomit Rienstein
1Susanne Levy-Gertner Oncogenetics Unit, Tel-Aviv University, Ramat Aviv, Israel.
Abstract:
Ovarian cancer, the leading cause of death due to gynecological malignancy, is diagnosed in most cases at an advanced stage. Combined with the paucity of symptoms of early-stage disease, the need to develop novel effective markers for the detection of potentially curable, early-stage disease is self-evident. Comprehensive analyses of somatic gene expression patterns in ovarian cancer were reported previously (n=17) and yielded substantial information on somatically altered genes, information that can potentially be useful in developing early detection markers. To further substantiate the role that these genes play in ovarian cancer tumorogenesis, we surveyed these reports and arranged the significantly altered genes from all reported studies by their chromosomal location (in silico chromosomal clustering). Subsequent comparison of this clustering to known genomic somatic alterations at the DNA level from data obtained using comparative genomic hybridization (CGH) was carried out. The major chromosomal regions that displayed overexpressed genes were correlated with the major CGH-detectable DNA amplification areas at 20q (harboring HE4, SLPI, MYBL2, UBE2C, and SDC4) and 1q (harboring MUC1). These genes may provide insights into ovarian cancer pathogenesis and may also prove to be useful as early detection tools.
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