Literature DB >> 21563232

Frequent genetic abnormalities of the PI3K/AKT pathway in primary ovarian cancer predict patient outcome.

Jia Huang1, Lin Zhang, Joel Greshock, Theresa A Colligon, Yan Wang, Renee Ward, Dionyssios Katsaros, Heini Lassus, Ralf Butzow, Andrew K Godwin, Joseph R Testa, Katherine L Nathanson, Phyllis A Gimotty, George Coukos, Barbara L Weber, Yan Degenhardt.   

Abstract

Identification and characterization of underlying genetic aberrations could facilitate diagnosis and treatment of ovarian cancer. Copy number analysis using array Comparative Genomic Hybridization (aCGH) on 93 primary ovarian tumors identified PI3K/AKT pathway as the most frequently altered cancer related pathway. Furthermore, survival analyses to correlate gene copy number and mutation data with patient outcome showed that copy number gains of PIK3CA, PIK3CB, and PIK3R4 in these tumors were associated with decreased survival. To confirm these findings at the protein level, immunohistochemistry (IHC) for PIK3CA product p110α and p-Akt was performed on tissue microarrays from 522 independent serous ovarian cancers. Overexpression of either of these two proteins was found to be associated with decreased survival. Multivariant analysis from these samples further showed that overexpression of p-AKT and/or p110α is an independent prognostic factor for these tumors. siRNAs targeting altered PI3K/AKT pathway genes inhibited proliferation and induced apoptosis in ovarian cancer cell lines. In addition, the effect of the siRNAs in different cell lines seemed to correlate with the particular genetic alterations that the cell line carries. These results strongly support the utilization of PI3K pathway inhibitors in ovarian cancer. They also suggest identifying the specific component in the PI3K pathway that is genetically altered has the potential to help select the most effective therapy. Both mutation as well as copy number changes can be used as predictive markers for this purpose.
Copyright © 2011 Wiley-Liss, Inc.

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Year:  2011        PMID: 21563232      PMCID: PMC3110626          DOI: 10.1002/gcc.20883

Source DB:  PubMed          Journal:  Genes Chromosomes Cancer        ISSN: 1045-2257            Impact factor:   5.006


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