MicroRNA Gene Expression Signature in Ovarian Cancer

• Project/Area Number: 16K11159
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Obstetrics and gynecology
• Research Institution: Jikei University School of Medicine
• Principal Investigator: Yanaihara Nozomu 東京慈恵会医科大学, 医学部, 准教授 (20349624)
• Co-Investigator(Kenkyū-buntansha): 山田 恭輔 東京慈恵会医科大学, 医学部, 教授 (30230452) ; 高倉 聡 獨協医科大学, 医学部, 教授 (60256401)
• Project Period (FY): 2016-04-01 – 2019-03-31
• Project Status: Completed (Fiscal Year 2018)
• Budget Amount: ¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000); Fiscal Year 2018: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000); Fiscal Year 2017: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000); Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
• Keywords: 卵巣癌 / microRNA / 癌

Outline of Final Research Achievements

This study aimed to elucidate clinical and biological associations of cancer-related microRNA gene expression profile in ovarian cancer. We investigated 27 ovarian cancers to determine the cancer-related microRNA expressions. An unsupervised hierarchical clustering analysis identified two distinct microRNA expression clusters, with histotypes-related significant differences in the associations between clusters and clinicopathological features. A comparison of microRNA expression in different histotypes identified five microRNAs including miR-9, with ovarian clear cell carcinoma (OCCC) demonstrating a statistically higher expression. Further investigation of the biological significance of miR-9 overexpression in OCCC revealed that miR-9 overexpression may affect its pathogenesis by targeting E-cadherin, thereby inducing an epithelial-mesenchymal transition. Therefore, miR-9 may be a promising therapeutic target strategy for OCCC.

Academic Significance and Societal Importance of the Research Achievements

本研究は、エピジェネテックな発現調節因子として期待されているmicroRNAが、卵巣癌の組織型特異的な早期診断・予後予測のバイオマーカーとして臨床上有用であるかを検討するだけでなく、そのもの自体もしくはそのインヒビターが、治療薬として有用であるかを追求したものである。またこれまで異なる組織型を一様に治療してきた卵巣癌の治療指針に対して、個別的な戦略の下に検討していることも、本研究の特色であると思われる。国内におけるmicroRNAに関する検討、特に基礎研究はその特殊な実験系からいまだ数少なく、今後さらなる努力が必要な分野と考えられる。

Research Products

• [Journal Article] Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers. (2019)
  • Author(s): Kawakami E, Tabata J, Yanaihara N, Ishikawa T, Koseki K, Iida Y, Saito M, Komazaki H, Shapiro JS, Goto C, Akiyama Y, Saito R, Saito M, Takano H, Yamada K, Okamoto A.
  • Journal Title: Clinical Cancer Research Volume: 印刷中 Issue: 10 Pages: 2996-3005
  • DOI: 10.1158/1078-0432.ccr-18-3378
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] MicroRNA Gene Expression Signature Driven by miR-9 Overexpression in Ovarian Clear Cell Carcinoma (2016)
  • Author(s): Yanaihara N, Noguchi Y, Saito M, Takenaka M, Takakura S, Yamada K, Okamoto A.
  • Journal Title: PLoS One Volume: 11 Issue: 9 Pages: e0162584-e0162584
  • DOI: 10.1371/journal.pone.0162584
  • Peer Reviewed / Open Access / Int'l Joint Research / Acknowledgement Compliant
• [Presentation] 卵巣高異型度漿液性癌におけるmicroRNA-34aのバイオマーカーとしての有用性 (2019)
  • Author(s): 横溝陵，矢内原臨，Jason Shapiro 斉藤美里，山口乃里子，川畑絢子，高橋一彰 竹中将貴，山田恭輔，岡本愛光
  • Organizer: 第7回婦人科がんバイオマーカー研究会
• [Presentation] A Machine Learning Algorithm Using Blood Biomarkers for Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer (2018)
  • Author(s): Tabata J, Yanaihara N, Goto C, Akiyama Y, Saito R, Komazaki H, Iida Y, Saito M, Saito M, Takano H, Ishonishi S, Kawakami E, Okamoto A.
  • Organizer: 第70回日本産科婦人科学会学術講演会