Annual Report 2021
Division of Translational Informatics
Katsuya Tsuchihara, Riu Yamashita, Hideki Makinoshima, Sachiyo Mimaki, Izumi Miki, Megumi Iwakura, Chiho Kohno, Junyang Du, Yamato Hamaya, Masato Aoshima, Yutaka Suzuki, Ayako Suzuki, Atsushi Yagishita, Junko Zenko
Introduction
It is necessary to obtain high-quality clinical information for cancer research. In addition, multi-omics data from patient specimens and model systems are indispensable to investigate the carcinogenic mechanism and the effects of therapeutic drugs. Several new multi-omics technologies such as single-cell analysis and microbiome analysis have been developed in recent years, and clinical sequence platforms enable us to obtain a large amount of omics-data with clinical information. Not only clinical and biological knowledge but also bioinformatics which extract meaningful information effectively are essential to integrate and analyze those data.
The Team and What We Do
The Division of Translational Informatics is designing an efficient pipeline for data processing and constructing web database servers for user convenience.
Research activities
This division constructed and began operating a database to store and analyze data mainly from large-scale clinical-omics projects led by Hospital East such as SCRUM-Japan and MONSTAR-SCREEN. To deal with increasingly diverse omics data, a system was constructed to integrate and analyze ctDNA analysis data, transcriptome data including single-cell analysis, and microbiome data with clinical information and information from external databases.
We promoted the formation of a consortium with related companies and academic research institutions based on the concept of a database that can be used for the research and development of cancer therapies and diagnosis. In March 2021, NCC signed a comprehensive collaboration agreement with Fujitsu Limited and constructed a system that pseudonymizes and outputs medical information from Hospital East in accordance with the Fast Healthcare Interoperability Resources (FHIR) standard.
Clinical trials
MONSTAR-SCREEN data center.
Education
Lectures and research guidance were provided for graduate students of cooperating graduate schools (Graduate School of Frontier Sciences, The University of Tokyo and Tokyo University of Science). A bioinformatics education course for multiple professions was conducted for EPOC, the Research Institute, and Hospital East.
Future Prospects
1. Sunami K, Bando H, Yatabe Y, Naito Y, Takahashi H, Tsuchihara K, Toyooka S, Mimori K, Kohsaka S, Uetake H, Kinoshita I, Komine K, Takeda M, Hayashida T, Tamura K, Nishio K, Yamamoto N. Appropriate use of cancer comprehensive genome profiling assay using circulating tumor DNA. Cancer science, 112:3911-3917, 2021
2. Nakamura Y, Fujisawa T, Taniguchi H, Bando H, Okamoto W, Tsuchihara K, Yoshino T, Ohtsu A. SCRUM-Japan GI-SCREEN and MONSTAR-SCREEN: Path to the realization of biomarker-guided precision oncology in advanced solid tumors. Cancer science, 112:4425-4432, 2021
3. Akimoto E, Tokunaga M, Sato R, Yoshida A, Naito Y, Yamashita R, Kinoshita T, Kuwata T. Gastric mesenchymal tumor with smooth muscle differentiation and echinoderm microtubule-associated protein-like 4-anaplastic lymphoma kinase (EML4-ALK) fusion. Pathology international, 71:707-711, 2021
4. Nakasone S, Suzuki A, Okazaki H, Onodera K, Zenkoh J, Ishii G, Suzuki Y, Tsuboi M, Tsuchihara K. Predictive markers based on transcriptome modules for vinorelbine-based adjuvant chemotherapy for lung adenocarcinoma patients. Lung cancer (Amsterdam, Netherlands), 158:115-125, 2021
5. Oiwa H, Aokage K, Suzuki A, Sato K, Kuroe T, Mimaki S, Tane K, Miyoshi T, Samejima J, Tsuchihara K, Goto K, Funai K, Tsuboi M, Nakai T, Ishii G. Clinicopathological, gene expression and genetic features of stage I lung adenocarcinoma with necrosis. Lung cancer (Amsterdam, Netherlands), 159:74-83, 2021
6. Kashima Y, Shibahara D, Suzuki A, Muto K, Kobayashi IS, Plotnick D, Udagawa H, Izumi H, Shibata Y, Tanaka K, Fujii M, Ohashi A, Seki M, Goto K, Tsuchihara K, Suzuki Y, Kobayashi SS. Single-Cell Analyses Reveal Diverse Mechanisms of Resistance to EGFR Tyrosine Kinase Inhibitors in Lung Cancer. Cancer research, 81:4835-4848, 2021
7. Du J, Kageyama SI, Hirata H, Motegi A, Nakamura M, Hirano Y, Okumura M, Yamashita R, Tsuchihara K, Hojo H, Hirayama R, Akimoto T. Comparative analysis of the immune responses in cancer cells irradiated with X-ray, proton and carbon-ion beams. Biochemical and biophysical research communications, 585:55-60, 2021
8. Ishioka K, Yasuda H, Hamamoto J, Terai H, Emoto K, Kim TJ, Hirose S, Kamatani T, Mimaki S, Arai D, Ohgino K, Tani T, Masuzawa K, Manabe T, Shinozaki T, Mitsuishi A, Ebisudani T, Fukushima T, Ozaki M, Ikemura S, Kawada I, Naoki K, Nakamura M, Ohtsuka T, Asamura H, Tsuchihara K, Hayashi Y, Hegab AE, Kobayashi SS, Kohno T, Watanabe H, Ornitz DM, Betsuyaku T, Soejima K, Fukunaga K. Upregulation of FGF9 in Lung Adenocarcinoma Transdifferentiation to Small Cell Lung Cancer. Cancer research, 81:3916-3929, 2021
9. Nagasawa S, Kuze Y, Maeda I, Kojima Y, Motoyoshi A, Onishi T, Iwatani T, Yokoe T, Koike J, Chosokabe M, Kubota M, Seino H, Suzuki A, Seki M, Tsuchihara K, Inoue E, Tsugawa K, Ohta T, Suzuki Y. Genomic profiling reveals heterogeneous populations of ductal carcinoma in situ of the breast. Communications biology, 4:438, 2021
10. Suzuki Y, Sato M, Awazuhara T, Nukui Y, Yoshida A, Terashima T, Watanabe K, Fujioka R, Tsuchihara K, Kishino S, Ohno K. Simultaneous quantification of arctigenin and its glucuronide conjugate in mouse plasma using ultra-high performance liquid chromatography coupled to tandem mass spectrometry. Journal of separation science, 44:1299-1306, 2021
11. Ogishima S, Nagaie S, Mizuno S, Ishiwata R, Iida K, Shimokawa K, Takai-Igarashi T, Nakamura N, Nagase S, Nakamura T, Tsuchiya N, Nakaya N, Murakami K, Ueno F, Onuma T, Ishikuro M, Obara T, Mugikura S, Tomita H, Uruno A, Kobayashi T, Tsuboi A, Tadaka S, Katsuoka F, Narita A, Sakurai M, Makino S, Tamiya G, Aoki Y, Shimizu R, Motoike IN, Koshiba S, Minegishi N, Kumada K, Nobukuni T, Suzuki K, Danjoh I, Nagami F, Tanno K, Ohmomo H, Asahi K, Shimizu A, Hozawa A, Kuriyama S, Fuse N, Tominaga T, Kure S, Yaegashi N, Kinoshita K, Sasaki M, Tanaka H, Yamamoto M. dbTMM: an integrated database of large-scale cohort, genome and clinical data for the Tohoku Medical Megabank Project. Human genome variation, 8:44, 2021
12. Yamauchi T, Ochi D, Matsukawa N, Saigusa D, Ishikuro M, Obara T, Tsunemoto Y, Kumatani S, Yamashita R, Tanabe O, Minegishi N, Koshiba S, Metoki H, Kuriyama S, Yaegashi N, Yamamoto M, Nagasaki M, Hiyama S, Sugawara J. Machine learning approaches to predict gestational age in normal and complicated pregnancies via urinary metabolomics analysis. Scientific reports, 11:17777, 2021