Genome‑wide analysis of gynecologic cancer: The Cancer Genome Atlas in ovarian and endometrial cancer (Review)

Iijima,Moito; Banno,Kouji; Okawa,Ryuichiro; Yanokura,Megumi; Iida,Miho; Takeda,Takashi; Kunitomi‑Irie,Haruko; Adachi,Masataka; Nakamura,Kanako; Umene,Kiyoko; Nogami,Yuya; Masuda,Kenta; Tominaga,Eiichiro; Aoki,Daisuke

doi:10.3892/ol.2017.5582

Genome‑wide analysis of gynecologic cancer: The Cancer Genome Atlas in ovarian and endometrial cancer (Review)

Authors:
- Moito Iijima
- Kouji Banno
- Ryuichiro Okawa
- Megumi Yanokura
- Miho Iida
- Takashi Takeda
- Haruko Kunitomi‑Irie
- Masataka Adachi
- Kanako Nakamura
- Kiyoko Umene
- Yuya Nogami
- Kenta Masuda
- Eiichiro Tominaga
- Daisuke Aoki
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Affiliations: Department of Obstetrics and Gynecology, Keio University School of Medicine, Tokyo 160‑8582, Japan
Published online on: January 10, 2017 https://doi.org/10.3892/ol.2017.5582
Pages: 1063-1070

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Abstract

Cancer typically develops due to genetic abnormalities, but a single gene abnormality cannot completely account for the onset of cancer. The Cancer Genome Atlas (CGA) project was conducted for the cross‑sectional genome‑wide analysis of numerous genetic abnormalities in various types of cancer. This approach has facilitated the identification of novel AT‑rich interaction domain 1A gene mutations in ovarian clear cell carcinoma, frequent tumor protein 53 (TP53) gene mutations in high‑grade ovarian serous carcinoma, and Kirsten rat sarcoma and B‑rapidly accelerated fibrosarcoma proto‑oncogene, serine/threonine kinase gene mutations in low‑grade ovarian serous carcinoma. Genome‑wide analysis of endometrial cancers has led to the establishment of four subgroups: Polymerase ultramutated, microsatellite instability hypermutated, genome copy‑number low and genome copy‑number high. These results may facilitate the improvement of the prediction of patient prognosis and therapeutic sensitivity in various types of gynecologic cancer. The enhanced use of currently available therapeutic agents and the development of novel drugs may be facilitated by the novel classification of ovarian cancer based on TP53 mutations, the efficacy of poly (ADP‑ribose) polymerase inhibitors for tumors with breast cancer 1/2 mutations and the effect of phosphoinositide‑3‑kinase (PI3K)/mammalian target of rapamycin inhibitors for tumors with mutations in the PI3K/protein kinase B signaling pathway. Important results have been revealed by genome‑wide analyses; however, the pathogenic underlying mechanisms of gynecologic cancer will require further studies and multilateral evaluation using epigenetic, transcriptomic and proteomic analyses, in addition to genomic analysis.

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