Elucidation of the molecular basis of diversity of pituitary neuroendocrine tumors by multiomics analysis and its application to clinical practice.

2022 Fiscal Year Final Research Report

• Project/Area Number: 21K20825
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Multi-year Fund
• Review Section: 0901:Oncology and related fields
• Research Institution: Chiba University
• Principal Investigator: GAO Yup 千葉大学, 大学院医学研究院, 特任研究員 (70907683)
• Project Period (FY): 2021-08-30 – 2023-03-31
• Keywords: 下垂体神経内分泌腫瘍 / マルチオミクス解析 / Single Cell解析 / 腫瘍特性 / 予測因子

Outline of Final Research Achievements

Pituitary neuroendocrine tumors (PitNETs) produce a variety of anterior pituitary hormones that cause diverse symptoms. However, its biological basis and regulatory mechanisms that define their diversity are largely unknown. Herein, we aim to utilize PitNETs specimens that have been biobanked to date to perform multi-omics analysis to promote integrated analysis with clinical and pathological data using machine learning to identify the molecular basis of invasive types and recurrence-prone tumor characteristics. The results of this research will lead to the identification of predictive factors such as clinical diversity and invasiveness and recurrence susceptibility, which are important for treatment and cannot be interpreted by conventional pathological classification, and are expected to be applied to personalized medicine.

Free Research Field

内分泌学、腫瘍生物学

Academic Significance and Societal Importance of the Research Achievements

希少疾患である下垂体腫瘍は、難易度の高い手術と腫瘍の残存・再発リスクを認めたり、ホルモンの正常化が必要など、治療困難な場合が多い。本研究の学術的意義として、「既存の分類を超えた下垂体神経内分泌腫瘍の多様性を説明しうる分子生物学的な層別化をマルチオミクスによるデータサイエンスの観点から明らかにすることが可能となり、これまでの病理分類では解釈できなかった臨床的多様性および治療の際に重要な浸潤性・再発しやすさなど予測因子の同定につながり、個別化医療への応用が期待できる。また、マルチオミクスと臨床情報とのデータ統合基盤は学術的価値とそれを用いた臨床研究に発展するなど、学術的波及効果を持つ。