Annual Report 2023
Division of Medical AI Research and Development
Ryuji Hamamoto, Syuzo Kaneko, Kazuma Kobayashi, Masaaki Komatsu, Ken Asada, Satoshi Takahashi, Ken Takasawa, Masayoshi Yamada, Masamichi Takahashi, Kyoko Fujioka, Noriko Ikawa, Hiroko Kondo, Shigemi Yamada, Hidenori Machino, Amina Bolatkan, Norio Shinkai, Rina Aoyama, Nobuji Kouno, Naoki Teraya, Yusuke Sakaguchi, Eri Suzuki
Introduction
Our division launched a pioneering large-scale project for medical AI in Japan called "Development of an Integrated Cancer Medical System Using AI” after the decision to promote research and development of artificial intelligence (AI) as a national policy based on the "Fifth Science and Technology Basic Plan" approved by the Cabinet in January 2016. Currently, as the core of medical AI research and development at the Tsukiji Campus, and as a center for medical AI research and development in Japan, the project has been actively promoted. In particular, research activities are focused on the following two points: 1) to promote research for the benefit of patients without falling into research for research's sake, aiming at clinical applications, and 2) to construct an integrated database that contains a wealth of high-quality medical information.
Research Activities
1. Development of new cancer diagnostic methods using AI technology
In close collaboration with physicians from various departments and divisions of the National Cancer Center Hospital, we conducted research and development of AI technology to support endoscopic diagnosis, radiological imaging, ultrasound diagnosis, and skin imaging diagnosis. In particular, the endoscopic diagnosis support AI that we developed has already been clinically applied since its approval by the pharmaceutical affairs bodies in 2020 and conformed to the requirements of the CE Mark. We have further succeeded in developing an AI that automatically and robustly predicts pathological diagnosis based on the revised Vienna Classification. The results of this study show that the AI system developed can support endoscopists in real time, avoid false positives during colonoscopy, and improve the differential diagnosis of colorectal cancer. The results were published in an academic paper and a pharmaceutical affairs application was submitted to the PMDA in December 2023.
2. Development of AI technology to precisely extract areas of suspected glioma from MRI images
We developed an AI development support platform, a research infrastructure system that enables physicians to develop AI technologies, in collaboration with Fujifilm, and commercialized it under the name "Synapse Creative Space" on April 5, 2022. Using this platform, the data was developed by having AI learn from data created by efficiently performing the annotation work of extracting the area of glioma from MRI images of the head, and it was commercialized by Fujifilm after obtaining certification under the Pharmaceutical Affairs Law (Figure). This technology will enable more accurate image evaluation before the treatment of glioma, and in the future, it is expected to be useful for early detection, improving the accuracy of diagnosis, and optimizing treatment plans such as radiation therapy and surgery.
3. Construction of the world's largest integrated database of lung cancer data oriented toward AI analysis and development of a multi-omics analysis platform using AI technology
As part of the BRIDGE project, we have constructed one of the world's largest integrated lung cancer databases oriented toward AI analysis, with more than 1,700 cases. In conjunction with the construction of the integrated database, we have also built a system that efficiently collects medical information from electronic medical records and pathology systems, as well as medical image information from various modalities. In addition, we developed a new analysis method for comprehensive DNA methylation data using machine learning technology called "methPLIER", and published it in the international academic journal "Experimental & Molecular Medicine". It is hoped that this research result will lead to progress in elucidating the epigenetic mechanisms of cancer and searching for drug discovery targets.
Education
A total of five graduate students from The University of Tokyo, Kyoto University, and Showa University belonged to this division and we provided research guidance. Members of the division also actively participated in young researchers' seminars organized by the research institute.
Future Prospects
1. We will continue to promote research and development of novel cancer diagnosis support AI in collaboration with various departments and divisions of the NCC Hospital, aiming for clinical application.
2. We will promote research utilization of the AI development platform in multiple research themes within the National Cancer Center Japan, aiming for regulatory approval of medical devices.
3. We will continue to develop an omics analysis platform using AI technology while expanding the integrated database for lung cancer and working on the construction of integrated databases for cancer types other than lung cancer.
List of papers published in 2023
Journal
1. Shiraishi K, Takahashi A, Momozawa Y, Daigo Y, Kaneko S, Kawaguchi T, Kunitoh H, Matsumoto S, Horinouchi H, Goto A, Honda T, Shimizu K, Torasawa M, Takayanagi D, Saito M, Saito A, Ohe Y, Watanabe SI, Goto K, Tsuboi M, Tsuchihara K, Takata S, Aoi T, Takano A, Kobayashi M, Miyagi Y, Tanaka K, Suzuki H, Maeda D, Yamaura T, Matsuda M, Shimada Y, Mizuno T, Sakamoto H, Yoshida T, Goto Y, Yoshida T, Yamaji T, Sonobe M, Toyooka S, Yoneda K, Masago K, Tanaka F, Hara M, Fuse N, Nishizuka SS, Motoi N, Sawada N, Nishida Y, Kumada K, Takeuchi K, Tanno K, Yatabe Y, Sunami K, Hishida T, Miyazaki Y, Ito H, Amemiya M, Totsuka H, Nakayama H, Yokose T, Ishigaki K, Nagashima T, Ohtaki Y, Imai K, Takasawa K, Minamiya Y, Kobayashi K, Okubo K, Wakai K, Shimizu A, Yamamoto M, Iwasaki M, Matsuda K, Inazawa J, Shiraishi Y, Nishikawa H, Murakami Y, Kubo M, Matsuda F, Kamatani Y, Hamamoto R, Matsuo K, Kohno T. Identification of telomere maintenance gene variations related to lung adenocarcinoma risk by genome-wide association and whole genome sequencing analyses. Cancer communications (London, England), 44:287-293, 2024
2. Kobayashi K, Gu L, Hataya R, Mizuno T, Miyake M, Watanabe H, Takahashi M, Takamizawa Y, Yoshida Y, Nakamura S, Kouno N, Bolatkan A, Kurose Y, Harada T, Hamamoto R. Sketch-based semantic retrieval of medical images. Medical image analysis, 92:103060, 2024
3. Mochizuki A, Shiraishi K, Honda T, Higashiyama RI, Sunami K, Matsuda M, Shimada Y, Miyazaki Y, Yoshida Y, Watanabe SI, Yatabe Y, Hamamoto R, Kohno T. Passive Smoking-Induced Mutagenesis as a Promoter of Lung Carcinogenesis. Journal of thoracic oncology, S1556-0864(24)00074-1, 2024
4. Takasawa K, Asada K, Kaneko S, Shiraishi K, Machino H, Takahashi S, Shinkai N, Kouno N, Kobayashi K, Komatsu M, Mizuno T, Okubo Y, Mukai M, Yoshida T, Yoshida Y, Horinouchi H, Watanabe SI, Ohe Y, Yatabe Y, Kohno T, Hamamoto R. Advances in cancer DNA methylation analysis with methPLIER: use of non-negative matrix factorization and knowledge-based constraints to enhance biological interpretability. Experimental & molecular medicine, 56:646-655, 2024
5. Kato MK, Fujii E, Asami Y, Momozawa Y, Hiranuma K, Komatsu M, Hamamoto R, Ebata T, Matsumoto K, Ishikawa M, Kohno T, Kato T, Yoshida H, Shiraishi K. Clinical features and impact of p53 status on sporadic mismatch repair deficiency and Lynch syndrome in uterine cancer. Cancer science, 115:1646-1655, 2024
6. Kato H, Hayami S, Ueno M, Suzaki N, Nakamura M, Yoshimura T, Miyamoto A, Shigekawa Y, Okada KI, Miyazawa M, Kitahata Y, Ehata S, Hamamoto R, Yamaue H, Kawai M. Histone methyltransferase SUV420H1/KMT5B contributes to poor prognosis in hepatocellular carcinoma. Cancer science, 115:385-400, 2024
7. Shirasawa M, Yoshida T, Shiraishi K, Takigami A, Takayanagi D, Imabayashi T, Matsumoto Y, Masuda K, Shinno Y, Okuma Y, Goto Y, Horinouchi H, Yotsukura M, Yoshida Y, Nakagawa K, Tsuchida T, Hamamoto R, Yamamoto N, Motoi N, Kohno T, Watanabe SI, Ohe Y. Identification of inflamed-phenotype of small cell lung cancer leading to the efficacy of anti-PD-L1 antibody and chemotherapy. Lung cancer (Amsterdam, Netherlands), 179:107183, 2023
8. Shi J, Shiraishi K, Choi J, Matsuo K, Chen TY, Dai J, Hung RJ, Chen K, Shu XO, Kim YT, Landi MT, Lin D, Zheng W, Yin Z, Zhou B, Song B, Wang J, Seow WJ, Song L, Chang IS, Hu W, Chien LH, Cai Q, Hong YC, Kim HN, Wu YL, Wong MP, Richardson BD, Funderburk KM, Li S, Zhang T, Breeze C, Wang Z, Blechter B, Bassig BA, Kim JH, Albanes D, Wong JYY, Shin MH, Chung LP, Yang Y, An SJ, Zheng H, Yatabe Y, Zhang XC, Kim YC, Caporaso NE, Chang J, Ho JCM, Kubo M, Daigo Y, Song M, Momozawa Y, Kamatani Y, Kobayashi M, Okubo K, Honda T, Hosgood DH, Kunitoh H, Patel H, Watanabe SI, Miyagi Y, Nakayama H, Matsumoto S, Horinouchi H, Tsuboi M, Hamamoto R, Goto K, Ohe Y, Takahashi A, Goto A, Minamiya Y, Hara M, Nishida Y, Takeuchi K, Wakai K, Matsuda K, Murakami Y, Shimizu K, Suzuki H, Saito M, Ohtaki Y, Tanaka K, Wu T, Wei F, Dai H, Machiela MJ, Su J, Kim YH, Oh IJ, Lee VHF, Chang GC, Tsai YH, Chen KY, Huang MS, Su WC, Chen YM, Seow A, Park JY, Kweon SS, Chen KC, Gao YT, Qian B, Wu C, Lu D, Liu J, Schwartz AG, Houlston R, Spitz MR, Gorlov IP, Wu X, Yang P, Lam S, Tardon A, Chen C, Bojesen SE, Johansson M, Risch A, Bickeböller H, Ji BT, Wichmann HE, Christiani DC, Rennert G, Arnold S, Brennan P, McKay J, Field JK, Shete SS, Le Marchand L, Liu G, Andrew A, Kiemeney LA, Zienolddiny-Narui S, Grankvist K, Johansson M, Cox A, Taylor F, Yuan JM, Lazarus P, Schabath MB, Aldrich MC, Jeon HS, Jiang SS, Sung JS, Chen CH, Hsiao CF, Jung YJ, Guo H, Hu Z, Burdett L, Yeager M, Hutchinson A, Hicks B, Liu J, Zhu B, Berndt SI, Wu W, Wang J, Li Y, Choi JE, Park KH, Sung SW, Liu L, Kang CH, Wang WC, Xu J, Guan P, Tan W, Yu CJ, Yang G, Sihoe ADL, Chen Y, Choi YY, Kim JS, Yoon HI, Park IK, Xu P, He Q, Wang CL, Hung HH, Vermeulen RCH, Cheng I, Wu J, Lim WY, Tsai FY, Chan JKC, Li J, Chen H, Lin HC, Jin L, Liu J, Sawada N, Yamaji T, Wyatt K, Li SA, Ma H, Zhu M, Wang Z, Cheng S, Li X, Ren Y, Chao A, Iwasaki M, Zhu J, Jiang G, Fei K, Wu G, Chen CY, Chen CJ, Yang PC, Yu J, Stevens VL, Fraumeni JF Jr, Chatterjee N, Gorlova OY, Hsiung CA, Amos CI, Shen H, Chanock SJ,. Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population. Nature communications, 14:3043, 2023
9. Igarashi T, Mazevet M, Yasuhara T, Yano K, Mochizuki A, Nishino M, Yoshida T, Yoshida Y, Takamatsu N, Yoshimi A, Shiraishi K, Horinouchi H, Kohno T, Hamamoto R, Adachi J, Zou L, Shiotani B. An ATR-PrimPol pathway confers tolerance to oncogenic KRAS-induced and heterochromatin-associated replication stress. Nature communications, 14:4991, 2023
10. Hayashi T, Takasawa K, Yoshikawa T, Hashimoto T, Sekine S, Wada T, Yamagata Y, Suzuki H, Abe S, Yoshinaga S, Saito Y, Kouno N, Hamamoto R. A discrimination model by machine learning to avoid gastrectomy for early gastric cancer. Annals of gastroenterological surgery, 7:913-921, 2023
11. Hashimoto T, Takayanagi D, Yonemaru J, Naka T, Nagashima K, Machida E, Kohno T, Yatabe Y, Kanemitsu Y, Hamamoto R, Takashima A, Shiraishi K, Sekine S. A comprehensive appraisal of HER2 heterogeneity in HER2-amplified and HER2-low colorectal cancer. British journal of cancer, 129:1176-1183, 2023
12. Hiranuma K, Asami Y, Kato MK, Murakami N, Shimada Y, Matsuda M, Yazaki S, Fujii E, Sudo K, Kuno I, Komatsu M, Hamamoto R, Makinoshima H, Matsumoto K, Ishikawa M, Kohno T, Terao Y, Itakura A, Yoshida H, Shiraishi K, Kato T. Rare FGFR fusion genes in cervical cancer and transcriptome-based subgrouping of patients with a poor prognosis. Cancer medicine, 12:17835-17848, 2023
13. Machino H, Dozen A, Konaka M, Komatsu M, Nakamura K, Ikawa N, Shozu K, Asada K, Kaneko S, Yoshida H, Kato T, Nakayama K, Saloura V, Kyo S, Hamamoto R. Integrative analysis reveals early epigenetic alterations in high-grade serous ovarian carcinomas. Experimental & molecular medicine, 55:2205-2219, 2023
14. Hamamoto R, Takasawa K, Shinkai N, Machino H, Kouno N, Asada K, Komatsu M, Kaneko S. Analysis of super-enhancer using machine learning and its application to medical biology. Briefings in bioinformatics, 24:bbad107, 2023
15. Kim K, Ryu TY, Jung E, Han TS, Lee J, Kim SK, Roh YN, Lee MS, Jung CR, Lim JH, Hamamoto R, Lee HW, Hur K, Son MY, Kim DS, Cho HS. Epigenetic regulation of SMAD3 by histone methyltransferase SMYD2 promotes lung cancer metastasis. Experimental & molecular medicine, 55:952-964, 2023
16. Ohata H, Shiokawa D, Sakai H, Kanda Y, Okimoto Y, Kaneko S, Hamamoto R, Nakagama H, Okamoto K. PROX1 induction by autolysosomal activity stabilizes persister-like state of colon cancer via feedback repression of the NOX1-mTORC1 pathway. Cell reports, 42:112519, 2023
17. Shirasawa M, Yoshida T, Shiraishi K, Goto N, Yagishita S, Imabayashi T, Matsumoto Y, Masuda K, Shinno Y, Okuma Y, Goto Y, Horinouchi H, Yotsukura M, Yoshida Y, Nakagawa K, Naoki K, Tsuchida T, Hamamoto R, Yamamoto N, Motoi N, Kohno T, Watanabe SI, Ohe Y. Correction: Tumor microenvironment-mediated immune profiles and efficacy of anti-PD-L1 antibody plus chemotherapy stratified by DLL3 expression in small-cell lung cancer. British journal of cancer, 129:2034, 2023