研究所

トップページ研究所研究分野紹介システム解析学分野Division of Cancer Systems Biology

Division of Cancer Systems Biology

Introduction

Our research purpose is to reveal complex systems in diverse types of cancers by analyzing large-scale personal ‘omics’ profile data and to exploit the extracted knowledge for advancing precision medicine. For that purpose, we have been developing various data analysis methods utilizing machine learning (ML) and artificial intelligence (AI) technologies employing the power of supercomputers.

Research topics

NGS data analysis methods based on Bayesian statistical models

Next-generation sequencing (NGS) technologies have opened new windows for various kinds of biological data with valuable information for both basic and clinical sciences, yet we need sophisticated computational methods to effectively extract the essentials. Therefore, we developed a variety of NGS data analysis methods based on Bayesian statistics and deep learning (DL). Regarding Bayesian models, we have proposed several somatic mutation-calling algorithms. One of them, MultiMuC (Moriyama et al., 2019), utilizes information from multi-site tumor samples from a single patient via a novel Bayes factor-based model construction scheme. We also theoretically analyzed conditions for how and when a kind of multi-regional mutation caller that utilizes phylogeny of tumor clones can work well (Moriyama et al., 2020).

NGS data analysis methods based on deep learning models

We have devised a variety of NGS data analysis methods based on DL models.

One is an algorithm to accurately estimate break points for copy number alteration sites using a deep segmentation model (RDBKE, Zhang et al., 2021). Read-depths (RDs) are frequently used in identifying structural variants (SVs) within sequencing data. For existing RD-based SV callers, it is difficult to determine breakpoints at single-nucleotide resolution due to the general noise of RD data and bin-based calculations. We have therefore proposed the UNet deep segmentation model to identify base-wise RD patterns surrounding breakpoints of known SVs. We integrated model predictions with an RD-based SV caller to enhance breakpoint-detection capabilities at single nucleotide resolution.

We have developed base-calling methods for Oxford nanopore long read sequencing data using new DL models. Long read sequencing technologies allowed us to obtain information difficult to access using conventional short-read sequencers. Raw data from the nanopore sequencer provide a time-series of ionic current signals in which changes are induced when a series of single-stranded DNA molecules proceed through a protein pore on the long-read sequencer. The base-calling problem is to estimate bases in the series of DNA molecules from the ionic current data in which such DNA bases are encoded in complex patterns with various noises. Therefore devising accurate base-callers is a critical task for any downstream analysis. For that purpose, we have proposed two algorithms URnano (Zhang et al., 2020) and Halcyon (Konishi et al., 2021). URnano is a nanopore base-caller that performs base-calling as a multi-label segmentation task. Halcyon is another method exploiting an encoder-decoder model with monotonic attention. The nanopore sequencer can also directly observe signals from methylated DNA molecules. For detecting methylated regions, we have also proposed DL models based on BERT architecture (Zhang et al., 2021).

Members

Rui Yamaguchi ,PhD,
Post
Chief
Profile
・2003 Ph.D. from Kyushu University
・2003-2003 Postdoctoral Fellow, Institute of Statistical Mathematics
・2003-2006 Postdoctoral Fellow, Department of Mathematics, Faculty of Sciences, Kyushu University
・2006-2009 Project Lecturer, Human Genome Center, The Institute of Medical Science, The University of Tokyo
・2009-2015 Lecturer, Human Genome Center, The Institute of Medical Science, The University of Tokyo
・2015-2019 Associate Professor, Human Genome Center, The Institute of Medical Science, The University of Tokyo
・2019-Present Chief, Division of Cancer Systems Biology, Aichi Cancer Center Research Institute
・2019-Present Deputy Director, Precision Medicine Center, Aichi Cancer Center Hospital (Additional post)
・2019-Present Visiting Professor, Division of Cancer Informatics, Nagoya University Graduate School of Medicine (Additional post)
Research fields
・Medical bioinformatics
・Cancer systems biology
・Development of methodologies for next-generation sequencing data analysis
Message
Nowadays medical and data sciences are becoming tightly integrated with continuous emergence of new types of data. The situation provides data scientists unique opportunities and stimuli. I would like to contribute to advancing future cancer medicine by developing new data analysis methods and also by educating young researchers in this exciting research field.
Rui Yamaguchi PhD,
Post
Chief
Zhongliang Guo ,PhD,
Post
Researcher
Profile
・2014 B.S. in Chemistry, The University of Tokyo
・2016 M.S. in Chemistry, The University of Tokyo
・2021 Ph.D. in Statistical Science, The Graduate University for Advanced Studies
・2019-2021 Project Researcher, Data Science Center for Creative Design and Manufacturing, Institute of Statistical Mathematics
・2021-Present Researcher, Division of Cancer Systems Biology, Aichi Cancer Center Research Institute
Research fields
Bayesian inference, machine learning in bioinformatics.
Message
Through the development of statistical methods for the analysis of medical and life science data, our research aims to contribute to the development of medicine, life sciences, and statistical science.
Zhongliang Guo PhD,
Post
Researcher
Osamu Muto ,MD,
Post
Research Resident
Profile
・2017 M.D. from Asahikawa Medical University
・2017-2019 Junior Resident, Asahikawa Medical Center
・2019-2020 PhD student, Hokkaido University School of Medicine
・2020-2021 Public Health Doctor, Nagoya City Public Health Center
・2021-Present Research Resident, Division of Cancer Systems Biology, Aichi Cancer Center Research Institute
Research fields
Bioinformatics, Systems biology, Omics data analysis in the field of oncology.
Message
I would like to propose novel methods for elucidating cancer systems and knowledge extraction from high-dimensional and complex cancer omics data taking advantage of statistics, informatics, and medical biology.
Osamu Muto MD,
Post
Research Resident

Publications

  1. Sugita Y, Muraoka D, Demachi-Okamura A, Komuro H, Masago K, Sasaki E, Fukushima Y, Matsui T, Shinohara S, Takahashi Y, Nishida R, Takashima C, Yamaguchi T, Horio Y, Hashimoto K, Tanaka I, Hamana H, Kishi H, Miura D, Tanaka Y, Onoue K, Onoguchi K, Yamashita Y, Stratford R, Clancy T, Yamaguchi R, Kuroda H, Ishibashi H, Okubo K, Matsushita H. Candidate tumor-specific CD8(+) T cell subsets identified in the malignant pleural effusion of advanced lung cancer patients by single-cell analysis. Oncoimmunology. 2024;13(1):2371556. Epub 20240628. doi: 10.1080/2162402X.2024.2371556. PubMed PMID: 38952674; PMCID: PMC11216099.
  2. Kuwatsuka Y, Kasajima R, Yamaguchi R, Uchida N, Konuma T, Tanaka M, Shingai N, Miyakoshi S, Kozai Y, Uehara Y, Eto T, Toyosaki M, Nishida T, Ishimaru F, Kato K, Fukuda T, Imoto S, Atsuta Y, Takahashi S. Machine Learning Prediction Model for Neutrophil Recovery after Unrelated Cord Blood Transplantation. Transplant Cell Ther. 2024;30(4):444 e1- e11. Epub 20240207. doi: 10.1016/j.jtct.2024.02.001. PubMed PMID: 38336299.
  3. Kuribayashi S, Fukuhara S, Kitakaze H, Tsujimura G, Imanaka T, Okada K, Ueda N, Takezawa K, Katayama K, Yamaguchi R, Matsuda K, Nonomura N. KEAP1-NRF2 system regulates age-related spermatogenesis dysfunction. Reprod Med Biol. 2024;23(1):e12595. Epub 20240624. doi: 10.1002/rmb2.12595. PubMed PMID: 38915913; PMCID: PMC11194679.
  4. Yamaguchi K, Nakagawa S, Saku A, Isobe Y, Yamaguchi R, Sheridan P, Takane K, Ikenoue T, Zhu C, Miura M, Okawara Y, Nagatoishi S, Kozuka-Hata H, Oyama M, Aikou S, Ahiko Y, Shida D, Tsumoto K, Miyano S, Imoto S, Furukawa Y. Bromodomain protein BRD8 regulates cell cycle progression in colorectal cancer cells through a TIP60-independent regulation of the pre-RC complex. iScience. 2023;26(4):106563. Epub 20230401. doi: 10.1016/j.isci.2023.106563. PubMed PMID: 37123243; PMCID: PMC10139981.
  5. Washimi K, Kasajima R, Shimizu E, Sato S, Okubo Y, Yoshioka E, Narimatsu H, Hiruma T, Katayama K, Yamaguchi R, Yamaguchi K, Furukawa Y, Miyano S, Imoto S, Yokose T, Miyagi Y. Histological markers, sickle-shaped blood vessels, myxoid area, and infiltrating growth pattern help stratify the prognosis of patients with myxofibrosarcoma/undifferentiated sarcoma. Sci Rep. 2023;13(1):6744. Epub 20230425. doi: 10.1038/s41598-023-34026-w. PubMed PMID: 37185612; PMCID: PMC10130155.
  6. Suzuki M, Kasajima R, Yokose T, Shimizu E, Hatakeyama S, Yamaguchi K, Yokoyama K, Katayama K, Yamaguchi R, Furukawa Y, Miyano S, Imoto S, Shinozaki-Ushiku A, Ushiku T, Miyagi Y. KMT2C expression and DNA homologous recombination repair factors in lung cancers with a high-grade fetal adenocarcinoma component. Transl Lung Cancer Res. 2023;12(8):1738-51. Epub 20230816. doi: 10.21037/tlcr-23-137. PubMed PMID: 37691868; PMCID: PMC10483084.
  7. Kuwahara T, Hara K, Mizuno N, Haba S, Okuno N, Kuraishi Y, Fumihara D, Yanaidani T, Ishikawa S, Yasuda T, Yamada M, Onishi S, Yamada K, Tanaka T, Tajika M, Niwa Y, Yamaguchi R, Shimizu Y. Artificial intelligence using deep learning analysis of endoscopic ultrasonography images for the differential diagnosis of pancreatic masses. Endoscopy. 2023;55(2):140-9. Epub 20220610. doi: 10.1055/a-1873-7920. PubMed PMID: 35688454.
  8. Komuro H, Shinohara S, Fukushima Y, Demachi-Okamura A, Muraoka D, Masago K, Matsui T, Sugita Y, Takahashi Y, Nishida R, Takashima C, Ohki T, Shigematsu Y, Watanabe F, Adachi K, Fukuyama T, Hamana H, Kishi H, Miura D, Tanaka Y, Onoue K, Onoguchi K, Yamashita Y, Stratford R, Clancy T, Yamaguchi R, Kuroda H, Doi K, Iwata H, Matsushita H. Single-cell sequencing on CD8(+) TILs revealed the nature of exhausted T cells recognizing neoantigen and cancer/testis antigen in non-small cell lung cancer. J Immunother Cancer. 2023;11(8). doi: 10.1136/jitc-2023-007180. PubMed PMID: 37544663; PMCID: PMC10407349.
  9. Kawachi K, Tang X, Kasajima R, Yamanaka T, Shimizu E, Katayama K, Yamaguchi R, Yokoyama K, Yamaguchi K, Furukawa Y, Miyano S, Imoto S, Yoshioka E, Washimi K, Okubo Y, Sato S, Yokose T, Miyagi Y. Genetic analysis of low-grade adenosquamous carcinoma of the breast progressing to high-grade metaplastic carcinoma. Breast Cancer Res Treat. 2023;202(3):563-73. Epub 20230831. doi: 10.1007/s10549-023-07078-9. PubMed PMID: 37650999; PMCID: PMC10564816.
  10. Guo Z, Muto O, Fukushima Y, Demachi-Okamura A, Ota M, Yoshida R, Matsushita H, Yamaguchi R. A multimodal framework combining sequence and topological features for accurate protein-protein binding affinity prediction. GIW ISCB-ASIA 2023; Singapore.
  11. Adachi Y, Kimura R, Hirade K, Yanase S, Nishioka Y, Kasuga N, Yamaguchi R, Ebi H. Scribble mis-localization induces adaptive resistance to KRAS G12C inhibitors through feedback activation of MAPK signaling mediated by YAP-induced MRAS. Nat Cancer. 2023;4(6):829-43. Epub 20230605. doi: 10.1038/s43018-023-00575-2. PubMed PMID: 37277529.
  12. Takeda R, Yokoyama K, Fukuyama T, Kawamata T, Ito M, Yusa N, Kasajima R, Shimizu E, Ohno N, Uchimaru K, Yamaguchi R, Imoto S, Miyano S, Tojo A. Repeated Lineage Switches in an Elderly Case of Refractory B-Cell Acute Lymphoblastic Leukemia With MLL Gene Amplification: A Case Report and Literature Review. Front Oncol. 2022;12:799982. Epub 20220323. doi: 10.3389/fonc.2022.799982. PubMed PMID: 35402256; PMCID: PMC8983914.
  13. Shinohara S, Takahashi Y, Komuro H, Matsui T, Sugita Y, Demachi-Okamura A, Muraoka D, Takahara H, Nakada T, Sakakura N, Masago K, Miyai M, Nishida R, Shomura S, Shigematsu Y, Hatooka S, Sasano H, Watanabe F, Adachi K, Fujinaga K, Kaneda S, Takao M, Ohtsuka T, Yamaguchi R, Kuroda H, Matsushita H. New evaluation of the tumor immune microenvironment of non-small cell lung cancer and its association with prognosis. J Immunother Cancer. 2022;10(4). doi: 10.1136/jitc-2021-003765. PubMed PMID: 35396225; PMCID: PMC8996063.
  14. Shimizu T, Sugihara E, Takeshima H, Nobusue H, Yamaguchi R, Yamaguchi-Iwai S, Fukuchi Y, Ushijima T, Muto A, Saya H. Depletion of R270C Mutant p53 in Osteosarcoma Attenuates Cell Growth but Does Not Prevent Invasion and Metastasis In Vivo. Cells. 2022;11(22):3614. Epub 20221115. doi: 10.3390/cells11223614. PubMed PMID: 36429043; PMCID: PMC9688353.
  15. Park H, Yamaguchi R, Imoto S, Miyano S. Xprediction: Explainable EGFR-TKIs response prediction based on drug sensitivity specific gene networks. PLoS One. 2022;17(5):e0261630. Epub 20220518. doi: 10.1371/journal.pone.0261630. PubMed PMID: 35584089; PMCID: PMC9116684.
  16. Park H, Yamaguchi R, Imoto S, Miyano S. Uncovering Molecular Mechanisms of Drug Resistance via Network-Constrained Common Structure Identification. J Comput Biol. 2022;29(3):257-75. Epub 20220121. doi: 10.1089/cmb.2021.0314. PubMed PMID: 35073162.
  17. Nakano K, Koh Y, Yamamichi G, Yumiba S, Tomiyama E, Matsushita M, Hayashi Y, Wang C, Ishizuya Y, Yamamoto Y, Kato T, Hatano K, Kawashima A, Ujike T, Fujita K, Kiyotani K, Katayama K, Yamaguchi R, Imoto S, Imamura R, Nonomura N, Uemura M. Perioperative circulating tumor DNA enables the identification of patients with poor prognosis in upper tract urothelial carcinoma. Cancer Sci. 2022;113(5):1830-42. Epub 20220324. doi: 10.1111/cas.15334. PubMed PMID: 35293110; PMCID: PMC9128184.
  18. Koh Y, Nakano K, Katayama K, Yamamichi G, Yumiba S, Tomiyama E, Matsushita M, Hayashi Y, Yamamoto Y, Kato T, Hatano K, Kawashima A, Ujike T, Imamura R, Yamaguchi R, Imoto S, Shiotsu Y, Nonomura N, Uemura M. Early dynamics of circulating tumor DNA predict clinical response to immune checkpoint inhibitors in metastatic renal cell carcinoma. Int J Urol. 2022;29(5):462-9. Epub 20220219. doi: 10.1111/iju.14816. PubMed PMID: 35184335; PMCID: PMC9306972.
  19. Kazama S, Yokoyama K, Ueki T, Kazumoto H, Satomi H, Sumi M, Ito I, Yusa N, Kasajima R, Shimizu E, Yamaguchi R, Imoto S, Miyano S, Tanaka Y, Denda T, Ota Y, Tojo A, Kobayashi H. Case report: Common clonal origin of concurrent langerhans cell histiocytosis and acute myeloid leukemia. Front Oncol. 2022;12:974307. Epub 20220916. doi: 10.3389/fonc.2022.974307. PubMed PMID: 36185232; PMCID: PMC9523168.
  20. Kasugai Y, Kohmoto T, Taniyama Y, Koyanagi YN, Usui Y, Iwase M, Oze I, Yamaguchi R, Ito H, Imoto I, Matsuo K. Association between germline pathogenic variants and breast cancer risk in Japanese women: The HERPACC study. Cancer Sci. 2022;113(4):1451-62. Epub 20220307. doi: 10.1111/cas.15312. PubMed PMID: 35218119; PMCID: PMC8990868.
  21. Hikita T, Uehara R, Itoh RE, Mitani F, Miyata M, Yoshida T, Yamaguchi R, Oneyama C. MEK/ERK-mediated oncogenic signals promote secretion of extracellular vesicles by controlling lysosome function. Cancer Sci. 2022;113(4):1264-76. Epub 20220213. doi: 10.1111/cas.15288. PubMed PMID: 35108425; PMCID: PMC8990735.
  22. Hasegawa T, Kakuta M, Yamaguchi R, Sato N, Mikami T, Murashita K, Nakaji S, Itoh K, Imoto S. Impact of salivary and pancreatic amylase gene copy numbers on diabetes, obesity, and functional profiles of microbiome in Northern Japanese population. Sci Rep. 2022;12(1):7628. Epub 20220510. doi: 10.1038/s41598-022-11730-7. PubMed PMID: 35538098; PMCID: PMC9090785.
  23. Guo Z, Yamaguchi R. Machine learning methods for protein-protein binding affinity prediction in protein design. Front Bioinform. 2022;2:1065703. Epub 20221216. doi: 10.3389/fbinf.2022.1065703. PubMed PMID: 36591334; PMCID: PMC9800603.
  24. Fujishita T, Kojima Y, Kajino-Sakamoto R, Mishiro-Sato E, Shimizu Y, Hosoda W, Yamaguchi R, Taketo MM, Aoki M. The cAMP/PKA/CREB and TGFbeta/SMAD4 Pathways Regulate Stemness and Metastatic Potential in Colorectal Cancer Cells. Cancer Res. 2022;82(22):4179-90. Epub 20220906. doi: 10.1158/0008-5472.CAN-22-1369. PubMed PMID: 36066360.
  25. Bai Z, Zhang YZ, Miyano S, Yamaguchi R, Fujimoto K, Uematsu S, Imoto S. Identification of bacteriophage genome sequences with representation learning. Bioinformatics. 2022;38(18):4264-70. Epub 20220803. doi: 10.1093/bioinformatics/btac509. PubMed PMID: 35920769; PMCID: PMC9477532.
  26. Zhang YZ, Yamaguchi K, Hatakeyama S, Furukawa Y, Miyano S, Yamaguchi R, Imoto S. On the application of BERT models for nanopore methylation detection. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM); 2021 9-12 Dec. 2021.
  27. Zhang YZ, Imoto S, Miyano S, Yamaguchi R. Enhancing breakpoint resolution with deep segmentation model: A general refinement method for read-depth based structural variant callers. PLoS Comput Biol. 2021;17(10):e1009186. Epub 20211011. doi: 10.1371/journal.pcbi.1009186. PubMed PMID: 34634042; PMCID: PMC8504719.
  28. Yamaguchi K, Kasajima R, Takane K, Hatakeyama S, Shimizu E, Yamaguchi R, Katayama K, Arai M, Ishioka C, Iwama T, Kaneko S, Matsubara N, Moriya Y, Nomizu T, Sugano K, Tamura K, Tomita N, Yoshida T, Sugihara K, Nakamura Y, Miyano S, Imoto S, Furukawa Y, Ikenoue T. Application of targeted nanopore sequencing for the screening and determination of structural variants in patients with Lynch syndrome. J Hum Genet. 2021;66(11):1053-60. Epub 20210506. doi: 10.1038/s10038-021-00927-9. PubMed PMID: 33958709.
  29. Suzuki M, Kasajima R, Yokose T, Ito H, Shimizu E, Hatakeyama S, Yokoyama K, Yamaguchi R, Furukawa Y, Miyano S, Imoto S, Yoshioka E, Washimi K, Okubo Y, Kawachi K, Sato S, Miyagi Y. Comprehensive molecular analysis of genomic profiles and PD-L1 expression in lung adenocarcinoma with a high-grade fetal adenocarcinoma component. Transl Lung Cancer Res. 2021;10(3):1292-304. Epub 2021/04/24. doi: 10.21037/tlcr-20-1158. PubMed PMID: 33889510; PMCID: PMC8044470.
  30. Sato N, Kakuta M, Hasegawa T, Yamaguchi R, Uchino E, Murashita K, Nakaji S, Imoto S, Yanagita M, Okuno Y. Metagenomic profiling of gut microbiome in early chronic kidney disease. Nephrol Dial Transplant. 2021;36(9):1675-84. Epub 2020/09/02. doi: 10.1093/ndt/gfaa122. PubMed PMID: 32869063.
  31. Park H, Yamaguchi R, Imoto S, Miyano S. Automatic sparse principal component analysis. Canadian Journal of Statistics-Revue Canadienne De Statistique. 2021;49(3):678-97. doi: 10.1002/cjs.11579. PubMed PMID: WOS:000600342700001.
  32. Mizuno S, Yamaguchi R, Hasegawa T, Hayashi S, Fujita M, Zhang F, Koh Y, Lee SY, Yoon SS, Shimizu E, Komura M, Fujimoto A, Nagai M, Kato M, Liang H, Miyano S, Zhang Z, Nakagawa H, Imoto S. Immunogenomic pan-cancer landscape reveals immune escape mechanisms and immunoediting histories. Sci Rep. 2021;11(1):15713. Epub 20210803. doi: 10.1038/s41598-021-95287-x. PubMed PMID: 34344966; PMCID: PMC8333422.
  33. Kuroda H, Sugita Y, Masago K, Takahashi Y, Nakada T, Sasaki E, Sakakura N, Yamaguchi R, Matsushita H, Hida T. Clinical Guideline-Guided Outcome Consistency for Surgically Resected Stage III Non-Small Cell Lung Cancer: A Retrospective Study. Cancers (Basel). 2021;13(11). Epub 20210521. doi: 10.3390/cancers13112531. PubMed PMID: 34064047; PMCID: PMC8196738.
  34. Konishi H, Yamaguchi R, Yamaguchi K, Furukawa Y, Imoto S. Halcyon: an accurate basecaller exploiting an encoder-decoder model with monotonic attention. Bioinformatics. 2021;37(9):1211-7. Epub 2020/11/10. doi: 10.1093/bioinformatics/btaa953. PubMed PMID: 33165508; PMCID: PMC8189681.
  35. Johmura Y, Yamanaka T, Omori S, Wang TW, Sugiura Y, Matsumoto M, Suzuki N, Kumamoto S, Yamaguchi K, Hatakeyama S, Takami T, Yamaguchi R, Shimizu E, Ikeda K, Okahashi N, Mikawa R, Suematsu M, Arita M, Sugimoto M, Nakayama KI, Furukawa Y, Imoto S, Nakanishi M. Senolysis by glutaminolysis inhibition ameliorates various age-associated disorders. Science. 2021;371(6526):265-70. Epub 2021/01/16. doi: 10.1126/science.abb5916. PubMed PMID: 33446552.
  36. Hasegawa T, Yamaguchi R, Kakuta M, Ando M, Songee J, Tokuda I, Murashita K, Imoto S. Application of state-space model with skew-t measurement noise to blood test value prediction. Applied Mathematical Modelling. 2021;100:365-78. doi: 10.1016/j.apm.2021.08.007. PubMed PMID: WOS:000703502900008.
  37. Fujimoto K, Kimura Y, Allegretti JR, Yamamoto M, Zhang YZ, Katayama K, Tremmel G, Kawaguchi Y, Shimohigoshi M, Hayashi T, Uematsu M, Yamaguchi K, Furukawa Y, Akiyama Y, Yamaguchi R, Crowe SE, Ernst PB, Miyano S, Kiyono H, Imoto S, Uematsu S. Functional Restoration of Bacteriomes and Viromes by Fecal Microbiota Transplantation. Gastroenterology. 2021;160(6):2089-102 e12. Epub 20210209. doi: 10.1053/j.gastro.2021.02.013. PubMed PMID: 33577875; PMCID: PMC8684800.
  38. Zhang YZ, Akdemir A, Tremmel G, Imoto S, Miyano S, Shibuya T, Yamaguchi R. Nanopore basecalling from a perspective of instance segmentation. BMC Bioinformatics. 2020;21(Suppl 3):136. Epub 20200423. doi: 10.1186/s12859-020-3459-0. PubMed PMID: 32321433; PMCID: PMC7178565.
  39. Zhang Y, Chen F, Fonseca NA, He Y, Fujita M, Nakagawa H, Zhang Z, Brazma A, Group PTW, Group PSVW, Creighton CJ, Consortium P. High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations. Nat Commun. 2020;11(1):736. Epub 20200205. doi: 10.1038/s41467-019-13885-w. PubMed PMID: 32024823; PMCID: PMC7002524.
  40. Sato N, Kakuta M, Hasegawa T, Yamaguchi R, Uchino E, Kobayashi W, Sawada K, Tamura Y, Tokuda I, Murashita K, Nakaji S, Imoto S, Yanagita M, Okuno Y. Metagenomic analysis of bacterial species in tongue microbiome of current and never smokers. NPJ Biofilms Microbiomes. 2020;6(1):11. Epub 20200313. doi: 10.1038/s41522-020-0121-6. PubMed PMID: 32170059; PMCID: PMC7069950.
  41. Park H, Maruhashi K, Yamaguchi R, Imoto S, Miyano S. Global gene network exploration based on explainable artificial intelligence approach. PLoS One. 2020;15(11):e0241508. Epub 20201106. doi: 10.1371/journal.pone.0241508. PubMed PMID: 33156825; PMCID: PMC7647077.
  42. Moriyama T, Imoto S, Miyano S, Yamaguchi R. Theoretical Foundation of the Performance of Phylogeny-Based Somatic Variant Detection. Lecture Notes in Computer Science. 2020;12508:87-101. doi: 10.1007/978-3-030-64511-3_9.
  43. Matsushita H, Hasegawa K, Oda K, Yamamoto S, Asada K, Karasaki T, Yabuno A, Nishijima A, Nejo T, Kobayashi Y, Sato S, Ikeda Y, Miyai M, Takahashi Y, Yamaguchi R, Fujiwara K, Aburatani H, Kakimi K. Neoantigen load and HLA-class I expression identify a subgroup of tumors with a T-cell-inflamed phenotype and favorable prognosis in homologous recombination-proficient high-grade serous ovarian carcinoma. J Immunother Cancer. 2020;8(1). Epub 2020/05/29. doi: 10.1136/jitc-2019-000375. PubMed PMID: 32461346; PMCID: PMC7254153.
  44. Maeda-Minami A, Yoshino T, Katayama K, Horiba Y, Hikiami H, Shimada Y, Namiki T, Tahara E, Minamizawa K, Muramatsu S, Yamaguchi R, Imoto S, Miyano S, Mima H, Mimura M, Nakamura T, Watanabe K. Discrimination of prediction models between cold-heat and deficiency-excess patterns. Complement Ther Med. 2020;49:102353. Epub 20200220. doi: 10.1016/j.ctim.2020.102353. PubMed PMID: 32147085.
  45. Kawakatsu Y, Koyanagi YN, Oze I, Kasugai Y, Morioka H, Yamaguchi R, Ito H, Matsuo K. Association between Socioeconomic Status and Digestive Tract Cancers: A Case-Control Study. Cancers (Basel). 2020;12(11). Epub 20201104. doi: 10.3390/cancers12113258. PubMed PMID: 33158224; PMCID: PMC7694284.
  46. Kasajima R, Yamaguchi R, Shimizu E, Tamada Y, Niida A, Tremmel G, Kishida T, Aoki I, Imoto S, Miyano S, Uemura H, Miyagi Y. Variant analysis of prostate cancer in Japanese patients and a new attempt to predict related biological pathways. Oncol Rep. 2020;43(3):943-52. Epub 20200127. doi: 10.3892/or.2020.7481. PubMed PMID: 32020225.
  47. Ishida S, Kato K, Tanaka M, Odamaki T, Kubo R, Mitsuyama E, Xiao JZ, Yamaguchi R, Uematsu S, Imoto S, Miyano S. Genome-wide association studies and heritability analysis reveal the involvement of host genetics in the Japanese gut microbiota. Commun Biol. 2020;3(1):686. Epub 20201118. doi: 10.1038/s42003-020-01416-z. PubMed PMID: 33208821; PMCID: PMC7674416.
  48. Imoto S, Hasegawa T, Yamaguchi R. Data science and precision health care. Nutr Rev. 2020;78(12 Suppl 2):53-7. Epub 2020/12/02. doi: 10.1093/nutrit/nuaa110. PubMed PMID: 33259624.
  49. Hijikata Y, Yokoyama K, Yokoyama N, Matsubara Y, Shimizu E, Nakashima M, Yamagishi M, Ota Y, Lim LA, Yamaguchi R, Ito M, Tanaka Y, Denda T, Tani K, Yotsuyanagi H, Imoto S, Miyano S, Uchimaru K, Tojo A. Successful Clinical Sequencing by Molecular Tumor Board in an Elderly Patient With Refractory Sezary Syndrome. JCO Precis Oncol. 2020;4(4):534-60. doi: 10.1200/PO.19.00254. PubMed PMID: 35050744.
  50. Hasegawa T, Yamaguchi R, Niida A, Miyano S, Imoto S. Ensemble smoothers for inference of hidden states and parameters in combinatorial regulatory model. Journal of the Franklin Institute. 2020;357(5):2916-33. doi: 10.1016/j.jfranklin.2019.10.015.
  51. Hasegawa T, Yamaguchi R, Kakuta M, Sawada K, Kawatani K, Murashita K, Nakaji S, Imoto S. Prediction of blood test values under different lifestyle scenarios using time-series electronic health record. PLoS One. 2020;15(3):e0230172. Epub 20200320. doi: 10.1371/journal.pone.0230172. PubMed PMID: 32196517; PMCID: PMC7083324.
  52. Hasegawa T, Hayashi S, Shimizu E, Mizuno S, Niida A, Yamaguchi R, Miyano S, Nakagawa H, Imoto S. Neoantimon: a multifunctional R package for identification of tumor-specific neoantigens. Bioinformatics. 2020;36(18):4813-6. Epub 2020/10/31. doi: 10.1093/bioinformatics/btaa616. PubMed PMID: 33123738; PMCID: PMC7750962.
  53. Fujita M, Yamaguchi R, Hasegawa T, Shimada S, Arihiro K, Hayashi S, Maejima K, Nakano K, Fujimoto A, Ono A, Aikata H, Ueno M, Hayami S, Tanaka H, Miyano S, Yamaue H, Chayama K, Kakimi K, Tanaka S, Imoto S, Nakagawa H. Classification of primary liver cancer with immunosuppression mechanisms and correlation with genomic alterations. EBioMedicine. 2020;53:102659. Epub 20200226. doi: 10.1016/j.ebiom.2020.102659. PubMed PMID: 32113157; PMCID: PMC7048625.
  54. Fujimoto K, Kimura Y, Shimohigoshi M, Satoh T, Sato S, Tremmel G, Uematsu M, Kawaguchi Y, Usui Y, Nakano Y, Hayashi T, Kashima K, Yuki Y, Yamaguchi K, Furukawa Y, Kakuta M, Akiyama Y, Yamaguchi R, Crowe SE, Ernst PB, Miyano S, Kiyono H, Imoto S, Uematsu S. Metagenome Data on Intestinal Phage-Bacteria Associations Aids the Development of Phage Therapy against Pathobionts. Cell Host Microbe. 2020;28(3):380-9 e9. Epub 20200710. doi: 10.1016/j.chom.2020.06.005. PubMed PMID: 32652061.
  55. ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Pan-cancer analysis of whole genomes. Nature. 2020;578(7793):82-93. Epub 20200205. doi: 10.1038/s41586-020-1969-6. PubMed PMID: 32025007; PMCID: PMC7025898.
  56. Akdemir KC, Le VT, Chandran S, Li Y, Verhaak RG, Beroukhim R, Campbell PJ, Chin L, Dixon JR, Futreal PA, Group PSVW, Consortium P. Disruption of chromatin folding domains by somatic genomic rearrangements in human cancer. Nat Genet. 2020;52(3):294-305. Epub 20200205. doi: 10.1038/s41588-019-0564-y. PubMed PMID: 32024999; PMCID: PMC7058537.
  57. Adachi Y, Ito K, Hayashi Y, Kimura R, Tan TZ, Yamaguchi R, Ebi H. Epithelial-to-Mesenchymal Transition is a Cause of Both Intrinsic and Acquired Resistance to KRAS G12C Inhibitor in KRAS G12C-Mutant Non-Small Cell Lung Cancer. Clin Cancer Res. 2020;26(22):5962-73. Epub 20200908. doi: 10.1158/1078-0432.CCR-20-2077. PubMed PMID: 32900796.
  58. Yoshino T, Katayama K, Yamaguchi R, Imoto S, Miyano S, Mima H, Watanabe K. Classification of patients with cold sensation by a review of systems database: A single-centre observational study. Complement Ther Med. 2019;45:7-13. Epub 20190511. doi: 10.1016/j.ctim.2019.05.011. PubMed PMID: 31331585.
  59. Yamaguchi K, Shimizu E, Yamaguchi R, Imoto S, Komura M, Hatakeyama S, Noguchi R, Takane K, Ikenoue T, Gohda Y, Yano H, Miyano S, Furukawa Y. Development of an MSI-positive colon tumor with aberrant DNA methylation in a PPAP patient. J Hum Genet. 2019;64(8):729-40. Epub 20190514. doi: 10.1038/s10038-019-0611-7. PubMed PMID: 31089268.
  60. VanderWeele DJ, Finney R, Katayama K, Gillard M, Paner G, Imoto S, Yamaguchi R, Wheeler D, Lack J, Cam M, Pontier A, Nguyen YTM, Maejima K, Sasaki-Oku A, Nakano K, Tanaka H, Vander Griend D, Kubo M, Ratain MJ, Miyano S, Nakagawa H. Genomic Heterogeneity Within Individual Prostate Cancer Foci Impacts Predictive Biomarkers of Targeted Therapy. Eur Urol Focus. 2019;5(3):416-24. Epub 20180215. doi: 10.1016/j.euf.2018.01.006. PubMed PMID: 29398457; PMCID: PMC6586528.
  61. Tsuda Y, Hirata M, Katayama K, Motoi T, Matsubara D, Oda Y, Fujita M, Kobayashi H, Kawano H, Nishida Y, Sakai T, Okuma T, Goto T, Ogura K, Kawai A, Ae K, Anazawa U, Suehara Y, Iwata S, Miyano S, Imoto S, Shibata T, Nakagawa H, Yamaguchi R, Tanaka S, Matsuda K. Massively parallel sequencing of tenosynovial giant cell tumors reveals novel CSF1 fusion transcripts and novel somatic CBL mutations. Int J Cancer. 2019;145(12):3276-84. Epub 20190531. doi: 10.1002/ijc.32421. PubMed PMID: 31107544.
  62. Takeda R, Yokoyama K, Ogawa M, Kawamata T, Fukuyama T, Kondoh K, Takei T, Nakamura S, Ito M, Yusa N, Shimizu E, Ohno N, Uchimaru K, Yamaguchi R, Imoto S, Miyano S, Tojo A. The first case of elderly TCF3-HLF-positive B-cell acute lymphoblastic leukemia. Leuk Lymphoma. 2019;60(11):2821-4. Epub 20190506. doi: 10.1080/10428194.2019.1602267. PubMed PMID: 31058556.
  63. Takeda R, Yokoyama K, Kobayashi S, Kawamata T, Nakamura S, Fukuyama T, Ito M, Yusa N, Shimizu E, Ohno N, Yamaguchi R, Imoto S, Miyano S, Uchimaru K, Tojo A. An Unusually Short Latent Period of Therapy-Related Myeloid Neoplasm Harboring a Rare MLL-EP300 Rearrangement: Case Report and Literature Review. Case Rep Hematol. 2019;2019:4532434. Epub 20191002. doi: 10.1155/2019/4532434. PubMed PMID: 31662917; PMCID: PMC6791222.
  64. Nakamura S, Yokoyama K, Shimizu E, Yusa N, Kondoh K, Ogawa M, Takei T, Kobayashi A, Ito M, Isobe M, Konuma T, Kato S, Kasajima R, Wada Y, Nagamura-Inoue T, Yamaguchi R, Takahashi S, Imoto S, Miyano S, Tojo A. Prognostic impact of circulating tumor DNA status post-allogeneic hematopoietic stem cell transplantation in AML and MDS. Blood. 2019;133(25):2682-95. Epub 20190401. doi: 10.1182/blood-2018-10-880690. PubMed PMID: 30936070.
  65. Muraoka D, Seo N, Hayashi T, Tahara Y, Fujii K, Tawara I, Miyahara Y, Okamori K, Yagita H, Imoto S, Yamaguchi R, Komura M, Miyano S, Goto M, Sawada SI, Asai A, Ikeda H, Akiyoshi K, Harada N, Shiku H. Antigen delivery targeted to tumor-associated macrophages overcomes tumor immune resistance. J Clin Invest. 2019;129(3):1278-94. Epub 20190211. doi: 10.1172/JCI97642. PubMed PMID: 30628894; PMCID: PMC6391090.
  66. Moriyama T, Imoto S, Miyano S, Yamaguchi R. Accurate and Flexible Bayesian Mutation Call from Multi-regional Tumor Samples. Mathematical and Computational Oncology, Ismco 2019. 2019;11826:47-61. doi: 10.1007/978-3-030-35210-3_4. PubMed PMID: WOS:000611467600004.
  67. Moriyama T, Imoto S, Hayashi S, Shiraishi Y, Miyano S, Yamaguchi R. A Bayesian model integration for mutation calling through data partitioning. Bioinformatics. 2019;35(21):4247-54. Epub 2019/03/30. doi: 10.1093/bioinformatics/btz233. PubMed PMID: 30924874; PMCID: PMC6821361.
  68. Maeda-Minami A, Yoshino T, Katayama K, Horiba Y, Hikiami H, Shimada Y, Namiki T, Tahara E, Minamizawa K, Muramatsu S, Yamaguchi R, Imoto S, Miyano S, Mima H, Mimura M, Nakamura T, Watanabe K. Prediction of deficiency-excess pattern in Japanese Kampo medicine: Multi-centre data collection. Complement Ther Med. 2019;45:228-33. Epub 20190705. doi: 10.1016/j.ctim.2019.07.003. PubMed PMID: 31331566.
  69. Konishi H, Komura D, Katoh H, Atsumi S, Koda H, Yamamoto A, Seto Y, Fukayama M, Yamaguchi R, Imoto S, Ishikawa S. Capturing the differences between humoral immunity in the normal and tumor environments from repertoire-seq of B-cell receptors using supervised machine learning. BMC Bioinformatics. 2019;20(1):267. Epub 20190528. doi: 10.1186/s12859-019-2853-y. PubMed PMID: 31138102; PMCID: PMC6537402.
  70. Ito S, Yadome M, Nishiki T, Ishiduki S, Inoue H, Yamaguchi R, Miyano S. Virtual Grid Engine: a simulated grid engine environment for large-scale supercomputers. BMC Bioinformatics. 2019;20(Suppl 16):591. Epub 20191202. doi: 10.1186/s12859-019-3085-x. PubMed PMID: 31787090; PMCID: PMC6886159.
  71. Hosono Y, Masuishi T, Mitani S, Yamaguchi R, Kato S, Yoshino T, Ebi H. Evaluation of ALK Fusion Newly Identified in Colon Cancer by a Comprehensive Genomic Analysis. JCO Precis Oncol. 2019;3(3):1-5. doi: 10.1200/PO.19.00268. PubMed PMID: 35100727.
  72. Hirata M, Asano N, Katayama K, Yoshida A, Tsuda Y, Sekimizu M, Mitani S, Kobayashi E, Komiyama M, Fujimoto H, Goto T, Iwamoto Y, Naka N, Iwata S, Nishida Y, Hiruma T, Hiraga H, Kawano H, Motoi T, Oda Y, Matsubara D, Fujita M, Shibata T, Nakagawa H, Nakayama R, Kondo T, Imoto S, Miyano S, Kawai A, Yamaguchi R, Ichikawa H, Matsuda K. Integrated exome and RNA sequencing of dedifferentiated liposarcoma. Nat Commun. 2019;10(1):5683. Epub 20191212. doi: 10.1038/s41467-019-13286-z. PubMed PMID: 31831742; PMCID: PMC6908635.
  73. Hayashi S, Moriyama T, Yamaguchi R, Mizuno S, Komura M, Miyano S, Nakagawa H, Imoto S. ALPHLARD-NT: Bayesian Method for Human Leukocyte Antigen Genotyping and Mutation Calling through Simultaneous Analysis of Normal and Tumor Whole-Genome Sequence Data. J Comput Biol. 2019;26(9):923-37. Epub 20190403. doi: 10.1089/cmb.2018.0224. PubMed PMID: 30942618; PMCID: PMC6748403.
  74. Yokoyama K, Shimizu E, Yokoyama N, Nakamura S, Kasajima R, Ogawa M, Takei T, Ito M, Kobayashi A, Yamaguchi R, Imoto S, Miyano S, Tojo A. Cell-lineage level-targeted sequencing to identify acute myeloid leukemia with myelodysplasia-related changes. Blood Adv. 2018;2(19):2513-21. Epub 2018/10/05. doi: 10.1182/bloodadvances.2017010744. PubMed PMID: 30282643; PMCID: PMC6177645.
  75. Takei T, Yokoyama K, Shimizu E, Konuma T, Takahashi S, Yamaguchi R, Imoto S, Miyano S, Tojo A. Azacitidine effectively reduces TP53-mutant leukemic cell burden in secondary acute myeloid leukemia after cord blood transplantation. Leuk Lymphoma. 2018;59(11):2755-6. Epub 20180412. doi: 10.1080/10428194.2018.1443335. PubMed PMID: 29648492.
  76. Ogawa M, Yokoyama K, Hirano M, Jimbo K, Ochi K, Kawamata T, Ohno N, Shimizu E, Yokoyama N, Yamaguchi R, Imoto S, Uchimaru K, Takahashi N, Miyano S, Imai Y, Tojo A. Different clonal dynamics of chronic myeloid leukaemia between bone marrow and the central nervous system. Br J Haematol. 2018;183(5):842-5. Epub 20171219. doi: 10.1111/bjh.15065. PubMed PMID: 29265350.
  77. Nakamura S, Yokoyama K, Yusa N, Ogawa M, Takei T, Kobayashi A, Ito M, Shimizu E, Kasajima R, Wada Y, Yamaguchi R, Imoto S, Nagamura-Inoue T, Miyano S, Tojo A. Circulating tumor DNA dynamically predicts response and/or relapse in patients with hematological malignancies. Int J Hematol. 2018;108(4):402-10. Epub 20180629. doi: 10.1007/s12185-018-2487-2. PubMed PMID: 29959746.
  78. Kobayashi M, Yokoyama K, Shimizu E, Yusa N, Ito M, Yamaguchi R, Imoto S, Miyano S, Tojo A. Phenotype-based gene analysis allowed successful diagnosis of X-linked neutropenia associated with a novel WASp mutation. Ann Hematol. 2018;97(2):367-9. Epub 20170927. doi: 10.1007/s00277-017-3134-3. PubMed PMID: 28956125.
  79. Kiyotani K, Mai TH, Yamaguchi R, Yew PY, Kulis M, Orgel K, Imoto S, Miyano S, Burks AW, Nakamura Y. Characterization of the B-cell receptor repertoires in peanut allergic subjects undergoing oral immunotherapy. J Hum Genet. 2018;63(2):239-48. Epub 20171130. doi: 10.1038/s10038-017-0364-0. PubMed PMID: 29192240.
  80. Ito S, Yadome M, Nishiki T, Ishiduki S, Inoue H, Yamaguchi R, Miyano S. Virtual Grid Engine: Accelerating thousands of omics sample analyses using large-scale supercomputers. 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM); 2018 3-6 Dec. 2018.
  81. Inoue D, Fujino T, Sheridan P, Zhang YZ, Nagase R, Horikawa S, Li Z, Matsui H, Kanai A, Saika M, Yamaguchi R, Kozuka-Hata H, Kawabata KC, Yokoyama A, Goyama S, Inaba T, Imoto S, Miyano S, Xu M, Yang FC, Oyama M, Kitamura T. A novel ASXL1-OGT axis plays roles in H3K4 methylation and tumor suppression in myeloid malignancies. Leukemia. 2018;32(6):1327-37. Epub 20180303. doi: 10.1038/s41375-018-0083-3. PubMed PMID: 29556021.
  82. Hayashi S, Yamaguchi R, Mizuno S, Komura M, Miyano S, Nakagawa H, Imoto S. ALPHLARD: a Bayesian method for analyzing HLA genes from whole genome sequence data. BMC Genomics. 2018;19(1):790. Epub 20181101. doi: 10.1186/s12864-018-5169-9. PubMed PMID: 30384854; PMCID: PMC6211482.
  83. Zhang YZ, Yamaguchi R, Imoto S, Miyano S. Sequence-specific bias correction for RNA-seq data using recurrent neural networks. BMC Genomics. 2017;18(Suppl 1):1044. Epub 20170125. doi: 10.1186/s12864-016-3262-5. PubMed PMID: 28198674; PMCID: PMC5310274.
  84. Zhang YZ, Imoto S, Miyano S, Yamaguchi R. Reconstruction of high read-depth signals from low-depth whole genome sequencing data using deep learning. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM); 2017 13-16 Nov. 2017.
  85. Tsuda Y, Tanikawa C, Miyamoto T, Hirata M, Yodsurang V, Zhang YZ, Imoto S, Yamaguchi R, Miyano S, Takayanagi H, Kawano H, Nakagawa H, Tanaka S, Matsuda K. Identification of a p53 target, CD137L, that mediates growth suppression and immune response of osteosarcoma cells. Sci Rep. 2017;7(1):10739. Epub 20170906. doi: 10.1038/s41598-017-11208-x. PubMed PMID: 28878391; PMCID: PMC5587585.
  86. Tanikawa C, Zhang YZ, Yamamoto R, Tsuda Y, Tanaka M, Funauchi Y, Mori J, Imoto S, Yamaguchi R, Nakamura Y, Miyano S, Nakagawa H, Matsuda K. The Transcriptional Landscape of p53 Signalling Pathway. EBioMedicine. 2017;20:109-19. Epub 20170518. doi: 10.1016/j.ebiom.2017.05.017. PubMed PMID: 28558959; PMCID: PMC5478243.
  87. Takano Y, Masuda T, Iinuma H, Yamaguchi R, Sato K, Tobo T, Hirata H, Kuroda Y, Nambara S, Hayashi N, Iguchi T, Ito S, Eguchi H, Ochiya T, Yanaga K, Miyano S, Mimori K. Circulating exosomal microRNA-203 is associated with metastasis possibly via inducing tumor-associated macrophages in colorectal cancer. Oncotarget. 2017;8(45):78598-613. Epub 20170807. doi: 10.18632/oncotarget.20009. PubMed PMID: 29108252; PMCID: PMC5667985.
  88. Sato R, Shibata T, Tanaka Y, Kato C, Yamaguchi K, Furukawa Y, Shimizu E, Yamaguchi R, Imoto S, Miyano S, Miyake K. Requirement of glycosylation machinery in TLR responses revealed by CRISPR/Cas9 screening. Int Immunol. 2017;29(8):347-55. Epub 2017/10/11. doi: 10.1093/intimm/dxx044. PubMed PMID: 28992181.
  89. Onuki R, Yamaguchi R, Shibuya T, Kanehisa M, Goto S. Revealing phenotype-associated functional differences by genome-wide scan of ancient haplotype blocks. PLoS One. 2017;12(4):e0176530. Epub 20170426. doi: 10.1371/journal.pone.0176530. PubMed PMID: 28445522; PMCID: PMC5406033.
  90. Moriyama T, Shiraishi Y, Chiba K, Yamaguchi R, Imoto S, Miyano S. OVarCall: Bayesian Mutation Calling Method Utilizing Overlapping Paired-End Reads. IEEE Trans Nanobioscience. 2017;16(2):116-22. Epub 20170301. doi: 10.1109/TNB.2017.2670601. PubMed PMID: 28278479.
  91. Miyamoto T, Tanikawa C, Yodsurang V, Zhang YZ, Imoto S, Yamaguchi R, Miyano S, Nakagawa H, Matsuda K. Identification of a p53-repressed gene module in breast cancer cells. Oncotarget. 2017;8(34):55821-36. Epub 20170726. doi: 10.18632/oncotarget.19608. PubMed PMID: 28915555; PMCID: PMC5593526.
  92. Ikeda Y, Kiyotani K, Yew PY, Sato S, Imai Y, Yamaguchi R, Miyano S, Fujiwara K, Hasegawa K, Nakamura Y. Clinical significance of T cell clonality and expression levels of immune-related genes in endometrial cancer. Oncol Rep. 2017;37(5):2603-10. Epub 20170329. doi: 10.3892/or.2017.5536. PubMed PMID: 28358435; PMCID: PMC5428285.
  93. Fujii K, Miyahara Y, Harada N, Muraoka D, Komura M, Yamaguchi R, Yagita H, Nakamura J, Sugino S, Okumura S, Imoto S, Miyano S, Shiku H. Identification of an immunogenic neo-epitope encoded by mouse sarcoma using CXCR3 ligand mRNAs as sensors. Oncoimmunology. 2017;6(5):e1306617. Epub 20170320. doi: 10.1080/2162402X.2017.1306617. PubMed PMID: 28638727; PMCID: PMC5467990.
  94. Yoshino T, Katayama K, Horiba Y, Munakata K, Yamaguchi R, Imoto S, Miyano S, Mima H, Watanabe K, Mimura M. The Difference between the Two Representative Kampo Formulas for Treating Dysmenorrhea: An Observational Study. Evid Based Complement Alternat Med. 2016;2016:3159617. Epub 20160224. doi: 10.1155/2016/3159617. PubMed PMID: 27006676; PMCID: PMC4783569.
  95. Yoshino T, Katayama K, Horiba Y, Munakata K, Yamaguchi R, Imoto S, Miyano S, Mima H, Watanabe K. Predicting Japanese Kampo formulas by analyzing database of medical records: a preliminary observational study. BMC Med Inform Decis Mak. 2016;16(1):118. Epub 20160913. doi: 10.1186/s12911-016-0361-9. PubMed PMID: 27619018; PMCID: PMC5020542.
  96. Yamaguchi K, Nagayama S, Shimizu E, Komura M, Yamaguchi R, Shibuya T, Arai M, Hatakeyama S, Ikenoue T, Ueno M, Miyano S, Imoto S, Furukawa Y. Reduced expression of APC-1B but not APC-1A by the deletion of promoter 1B is responsible for familial adenomatous polyposis. Sci Rep. 2016;6:26011. Epub 20160524. doi: 10.1038/srep26011. PubMed PMID: 27217144; PMCID: PMC4877598.
  97. Tamura K, Hazama S, Yamaguchi R, Imoto S, Takenouchi H, Inoue Y, Kanekiyo S, Shindo Y, Miyano S, Nakamura Y, Kiyotani K. Characterization of the T cell repertoire by deep T cell receptor sequencing in tissues and blood from patients with advanced colorectal cancer. Oncol Lett. 2016;11(6):3643-9. Epub 20160419. doi: 10.3892/ol.2016.4465. PubMed PMID: 27284367; PMCID: PMC4887943.
  98. Sugimachi K, Yamaguchi R, Eguchi H, Ueda M, Niida A, Sakimura S, Hirata H, Uchi R, Shinden Y, Iguchi T, Morita K, Yamamoto K, Miyano S, Mori M, Maehara Y, Mimori K. 8q24 Polymorphisms and Diabetes Mellitus Regulate Apolipoprotein A-IV in Colorectal Carcinogenesis. Ann Surg Oncol. 2016;23(Suppl 4):546-51. Epub 20160707. doi: 10.1245/s10434-016-5374-1. PubMed PMID: 27387680.
  99. Muramatsu T, Kozaki KI, Imoto S, Yamaguchi R, Tsuda H, Kawano T, Fujiwara N, Morishita M, Miyano S, Inazawa J. The hypusine cascade promotes cancer progression and metastasis through the regulation of RhoA in squamous cell carcinoma. Oncogene. 2016;35(40):5304-16. Epub 20160404. doi: 10.1038/onc.2016.71. PubMed PMID: 27041563.
  100. Moriyama T, Shiraishi Y, Chiba K, Yamaguchi R, Imoto S, Miyano S. OVarCall: Bayesian Mutation Calling Method Utilizing Overlapping Paired-End Reads. Bioinformatics Research and Applications, Isbra 2016. 2016;9683:40-51. doi: 10.1007/978-3-319-38782-6_4. PubMed PMID: WOS:000385788800004.
  101. Kayano M, Matsui H, Yamaguchi R, Imoto S, Miyano S. Gene set differential analysis of time course expression profiles via sparse estimation in functional logistic model with application to time-dependent biomarker detection. Biostatistics. 2016;17(2):235-48. Epub 20150928. doi: 10.1093/biostatistics/kxv037. PubMed PMID: 26420796.
  102. Hasegawa T, Niida A, Mori T, Shimamura T, Yamaguchi R, Miyano S, Akutsu T, Imoto S. A likelihood-free filtering method via approximate Bayesian computation in evaluating biological simulation models. Computational Statistics & Data Analysis. 2016;94:63-74. doi: 10.1016/j.csda.2015.08.003. PubMed PMID: WOS:000364798200005.
  103. Chapman CG, Yamaguchi R, Tamura K, Weidner J, Imoto S, Kwon J, Fang H, Yew PY, Marino SR, Miyano S, Nakamura Y, Kiyotani K. Characterization of T-cell Receptor Repertoire in Inflamed Tissues of Patients with Crohn’s Disease Through Deep Sequencing. Inflamm Bowel Dis. 2016;22(6):1275-85. Epub 2016/05/03. doi: 10.1097/MIB.0000000000000752. PubMed PMID: 27135481.
  104. Yew PY, Alachkar H, Yamaguchi R, Kiyotani K, Fang H, Yap KL, Liu HT, Wickrema A, Artz A, van Besien K, Imoto S, Miyano S, Bishop MR, Stock W, Nakamura Y. Quantitative characterization of T-cell repertoire in allogeneic hematopoietic stem cell transplant recipients. Bone Marrow Transplant. 2015;50(9):1227-34. Epub 20150608. doi: 10.1038/bmt.2015.133. PubMed PMID: 26052909; PMCID: PMC4559843.
  105. Yamaguchi K, Komura M, Yamaguchi R, Imoto S, Shimizu E, Kasuya S, Shibuya T, Hatakeyama S, Takahashi N, Ikenoue T, Hata K, Tsurita G, Shinozaki M, Suzuki Y, Sugano S, Miyano S, Furukawa Y. Detection of APC mosaicism by next-generation sequencing in an FAP patient. J Hum Genet. 2015;60(5):227-31. Epub 20150226. doi: 10.1038/jhg.2015.14. PubMed PMID: 25716913.
  106. Nakata A, Yoshida R, Yamaguchi R, Yamauchi M, Tamada Y, Fujita A, Shimamura T, Imoto S, Higuchi T, Nomura M, Kimura T, Nokihara H, Higashiyama M, Kondoh K, Nishihara H, Tojo A, Yano S, Miyano S, Gotoh N. Elevated beta-catenin pathway as a novel target for patients with resistance to EGF receptor targeting drugs. Sci Rep. 2015;5:13076. Epub 20150813. doi: 10.1038/srep13076. PubMed PMID: 26268703; PMCID: PMC4535059.
  107. Iwakawa R, Kohno T, Totoki Y, Shibata T, Tsuchihara K, Mimaki S, Tsuta K, Narita Y, Nishikawa R, Noguchi M, Harris CC, Robles AI, Yamaguchi R, Imoto S, Miyano S, Totsuka H, Yoshida T, Yokota J. Expression and clinical significance of genes frequently mutated in small cell lung cancers defined by whole exome/RNA sequencing. Carcinogenesis. 2015;36(6):616-21. Epub 2015/04/12. doi: 10.1093/carcin/bgv026. PubMed PMID: 25863124; PMCID: PMC4462675.
  108. Ikenoue T, Yamaguchi K, Komura M, Imoto S, Yamaguchi R, Shimizu E, Kasuya S, Shibuya T, Hatakeyama S, Miyano S, Furukawa Y. Attenuated familial adenomatous polyposis with desmoids caused by an APC mutation. Hum Genome Var. 2015;2:15011. Epub 2015/01/01. doi: 10.1038/hgv.2015.11. PubMed PMID: 27081525; PMCID: PMC4785566.
  109. Hasegawa T, Mori T, Yamaguchi R, Shimamura T, Miyano S, Imoto S, Akutsu T. Genomic data assimilation using a higher moment filtering technique for restoration of gene regulatory networks. BMC Syst Biol. 2015;9:14. Epub 2015/04/19. doi: 10.1186/s12918-015-0154-2. PubMed PMID: 25890175; PMCID: PMC4371723.
  110. Chikahara Y, Niida A, Yamaguchi R, Imoto S, Miyano S. Integrative clustering of cancer genome data using infinite relational models. Proceedings of the 7th International Conference on Bioinformatics and Computational Biology, BICOB 2015. 2015:11-8.

Education & Training

We have been developing computational methodologies to gain valuable insights from huge and heterogeneous biomedical datasets, especially from next-generation sequencing technologies, and applying them to large-scale datasets for various cancers. A tutorial in this lab provides a unique opportunity for experiencing cancer sequencing data analysis with real-data sets in collaboration with other labs in ACCRI.

We are looking for highly motivated graduate students and postdoctoral fellows.

Positions for Postdoctoral fellows

Postdoctoral positions are available for highly motivated candidates with a background in data science related fields and/or biomedical sciences. Postdoctoral Fellows can be supported for salary, health insurance, and VISA application. Informal inquiries can be sent to Rui Yamaguchi at r.yamaguchi@aichi-cc.jp.

Graduate students

The lab is affiliated with the Nagoya University Graduate School of Medicine. Foreign applicants may be supported by the Japanese Government Monbusho (MEXT) scholarship.