From data to discovery in cancer immunology: AI-driven spatial transcriptomics.

Research Project

Project/Area Number	24K15175
Research Category	Grant-in-Aid for Scientific Research (C)
Allocation Type	Multi-year Fund
Section	一般
Review Section	Basic Section 62010:Life, health and medical informatics-related
Research Institution	The University of Tokyo
Principal Investigator	Lysenko Artem 東京大学, 大学院理学系研究科(理学部), 助教 (80753805)
Project Period (FY)	2024-04-01 – 2027-03-31
Project Status	Granted (Fiscal Year 2024)
Budget Amount *help	¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000) Fiscal Year 2026: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000) Fiscal Year 2025: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000) Fiscal Year 2024: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Keywords	cancer immunology / spatial transcriptomics / deep learning
Outline of Research at the Start	This project will develop a novel AI method for improved spatial profiling of cancerous tumor samples. The goal of the method is to detect and characterize different types of anti-cancer immune response. These different types of immune response will then be related to clinically important factors, like prognosis and response to specific treatments. Better understanding of these associations will then allow better therapy optimization (personalized medicine) and facilitate the development of new cancer immunotherapy approaches.