Development of breast cancer predection model using IgGFc N-glycosylation

2019 Fiscal Year Final Research Report

• Project/Area Number: 17K16505
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: General surgery
• Research Institution: Kyoto University
• Principal Investigator: Kawaguchi Nobuko 京都大学, 医学研究科, 特定病院助教 (60771540)
• Project Period (FY): 2017-04-01 – 2020-03-31
• Keywords: 乳癌 / IgG糖鎖 / 診断予測モデル

Outline of Final Research Achievements

Early detection of breast cancer can result in lower recurrence after surgery. However, today, just half of the breast cancer cases are diagnosed with stage 0 and stage I, therefore development of an easy and highly sensitive diagnostic method is required for early detection. The purpose of this study was to verify a breast cancer prediction model using serum IgG glycosylation developed in a pilot study. First, stability of the IgG sugar chains was confirmed because stability of the target to detect is essential for future clinical application. Next, IgG sugar chains were measured in the verification cohort. At present the prediction model is being improved based on these data, and it is considered that the prediction model using IgG glycosylation will be a promising candidate as an easy and sensitive diagnostic method.

Free Research Field

乳癌

Academic Significance and Societal Importance of the Research Achievements

簡便で感度のよい診断方法は早期診断に有用であり、乳癌では早期発見により手術での高い治癒率が期待でき、患者の負担が大きい抗がん剤治療をせずに済む可能性も高くなる。IgG糖鎖を用いた予測モデルの研究は簡便で感度のよい診断方法開発の第一歩であると考えられる。また学術的には本研究での結果はIgG糖鎖が乳癌の病態に関与している可能性を示しており、その機序を解明することで、IgGN型糖鎖に関与する免疫反応を治療標的やバイオマーカーとするような新規分野を開拓できると考えられる。