Annual Report 2023
Division of Genome Analysis Platform Development
Yuichi Shiraishi, Yoshitaka Sakamoto, Raúl Nicolás Mateos, Hajime Suzuki
Introduction
We are focusing on the development of algorithms, pipelines, and tools for analyzing cancer genome and transcriptome data using short-read and long-read sequencing technologies. This includes the following: (1) Development of a structural variant detection software called nanomonsv, (2) cancer genome analysis in centromere regions, (3) the development of a new pipeline and algorithm for accurate comprehensive analysis of cancer genomes including difficult-to-analyze regions of the human genome using long-read sequencing data, (4) the construction of workflows for adaptive sampling data, (5) Development of a method for estimating the timing of rare mutations in cancer-related genes, (6) the development of a tool to identify genomic mutations which create new splice sites from transcriptome data, and (7) the development of a tool to predict abnormal activation of the KEAP1-NRF2 pathway related to cancer progression from abnormal splice junctions. As sequencing technologies rapidly advance, along with the development of various methodologies and software worldwide, we are working on the development of platforms which can elucidate a part of cancer progression, causes, and states while continuing to improve in speed and precision.
Research Activities
(1) Development of a structural variant detection software called nanomonsv
We developed a software called nanomonsv, to detect somatic structural variants using long-read sequencing data from tumor and matched-normal sample pairs.
(2) Cancer genome analysis in centromere regions
We are developing and organizing methods to analyze centromeric regions using short-read and long-read sequencing data for cancers in which translocations are commonly observed in these regions.
(3) Development of cancer genome analysis pipelines and algorithms using long-read sequencing data
We are developing a novel cancer genome analysis pipeline for accurate comprehensive cancer genome analysis, including difficult-to-analyze regions in the human genome such as centromeres, by constructing personalized reference genomes using long-read sequencing data. Additionally, we are developing a new algorithm for the de novo assembly to construct a genome sequence from long-read sequencing data.
(4) Construction of adaptive sampling data analysis workflow
We have constructed a data analysis workflow for adaptive sampling, a technique that amplifies specific regions for long-read sequencing.
(5) Development of a method for estimating the timing of rare mutations in cancer-related genes
We are developing a method to estimate when rare mutations in cancer-related genes have occurred genetically in cancer genomes. For the estimation, we are using human normal cohort data as a reference panel.
(6) Development of a tool to identify mutations which create novel splice sites from transcriptome data
We developed a tool called "juncmut" to identify mutations which create novel splice sites from transcriptome data. Juncmut has been applied to large-scale public transcriptome data, where it has successfully identified many mutations which create novel splice sites.
(7) Development of a tool to predict abnormal activation of the KEAP1-NRF2 pathway from abnormal splice junctions
We developed a tool to predict abnormal activation of the KEAP1-NRF2 pathway, which is involved in cancer progression, based on abnormal splice junctions. This prediction tool was trained using large-scale public data from The Cancer Genome Atlas.
Education
We supported many researchers using our analysis pipeline by answering their bioinformatics questions. We hired postdocs and supported their research.
Future Prospects
We have established the technological basis for cancer genome and transcriptome analysis. To develop the application of whole-genome analysis to genomic medicine, we will construct various genome analysis workflows. In addition, we will apply the established analysis flow to large-scale data and conduct knowledge discovery from the obtained information.
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. Nakamura W, Hirata M, Oda S, Chiba K, Okada A, Mateos RN, Sugawa M, Iida N, Ushiama M, Tanabe N, Sakamoto H, Sekine S, Hirasawa A, Kawai Y, Tokunaga K, Tsujimoto SI, Shiba N, Ito S, Yoshida T, Shiraishi Y. Assessing the efficacy of target adaptive sampling long-read sequencing through hereditary cancer patient genomes. NPJ genomic medicine, 9:11, 2024
3. Sato T, Yoshida K, Toki T, Kanezaki R, Terui K, Saiki R, Ojima M, Ochi Y, Mizuno S, Yoshihara M, Uechi T, Kenmochi N, Tanaka S, Matsubayashi J, Kisai K, Kudo K, Yuzawa K, Takahashi Y, Tanaka T, Yamamoto Y, Kobayashi A, Kamio T, Sasaki S, Shiraishi Y, Chiba K, Tanaka H, Muramatsu H, Hama A, Hasegawa D, Sato A, Koh K, Karakawa S, Kobayashi M, Hara J, Taneyama Y, Imai C, Hasegawa D, Fujita N, Yoshitomi M, Iwamoto S, Yamato G, Saida S, Kiyokawa N, Deguchi T, Ito M, Matsuo H, Adachi S Prof, Hayashi Y, Taga T, Moriya Saito A, Horibe K, Watanabe K, Tomizawa D, Miyano S, Takahashi S, Ogawa S, Ito E. Landscape of driver mutations and their clinical effects on Down syndrome-related myeloid neoplasms. Blood, blood.2023022247, 2024
4. Haga Y, Sakamoto Y, Kajiya K, Kawai H, Oka M, Motoi N, Shirasawa M, Yotsukura M, Watanabe SI, Arai M, Zenkoh J, Shiraishi K, Seki M, Kanai A, Shiraishi Y, Yatabe Y, Matsubara D, Suzuki Y, Noguchi M, Kohno T, Suzuki A. Whole-genome sequencing reveals the molecular implications of the stepwise progression of lung adenocarcinoma. Nature communications, 14:8375, 2023
5. Oda S, Ushiama M, Nakamura W, Gotoh M, Tanabe N, Watanabe T, Odaka Y, Aoyagi K, Sakamoto H, Nakajima T, Sugano K, Yoshida T, Shiraishi Y, Hirata M. A complex rearrangement between APC and TP63 associated with familial adenomatous polyposis identified by multimodal genomic analysis: a case report. Frontiers in oncology, 13:1205847, 2023
6. Shiraishi Y, Koya J, Chiba K, Okada A, Arai Y, Saito Y, Shibata T, Kataoka K. Precise characterization of somatic complex structural variations from tumor/control paired long-read sequencing data with nanomonsv. Nucleic acids research, 51:e74, 2023
7. Shimomura K, Hattori N, Iida N, Muranaka Y, Sato K, Shiraishi Y, Arai Y, Hama N, Shibata T, Narushima D, Kato M, Takamaru H, Okamoto K, Takeda H. Sleeping Beauty transposon mutagenesis identified genes and pathways involved in inflammation-associated colon tumor development. Nature communications, 14:6514, 2023
8. Tabata M, Sato Y, Kogure Y, McClure MB, Oshikawa-Kumade Y, Saito Y, Shingaki S, Ito Y, Yuasa M, Koya J, Yoshida K, Kohno T, Miyama Y, Morikawa T, Chiba K, Okada A, Ogawa S, Ushiku T, Shiraishi Y, Kume H, Kataoka K. Inter- and intra-tumor heterogeneity of genetic and immune profiles in inherited renal cell carcinoma. Cell reports, 42:112736, 2023
9. Nannya Y, Tobiasson M, Sato S, Bernard E, Ohtake S, Takeda J, Creignou M, Zhao L, Kusakabe M, Shibata Y, Nakamura N, Watanabe M, Hiramoto N, Shiozawa Y, Shiraishi Y, Tanaka H, Yoshida K, Kakiuchi N, Makishima H, Nakagawa M, Usuki K, Watanabe M, Imada K, Handa H, Taguchi M, Kiguchi T, Ohyashiki K, Ishikawa T, Takaori-Kondo A, Tsurumi H, Kasahara S, Chiba S, Naoe T, Miyano S, Papaemanuil E, Miyazaki Y, Hellström-Lindberg E, Ogawa S. Postazacitidine clone size predicts long-term outcome of patients with myelodysplastic syndromes and related myeloid neoplasms. Blood advances, 7:3624-3636, 2023
10. Hara Y, Shiba N, Yoshida K, Yamato G, Kaburagi T, Shiraishi Y, Ohki K, Shiozawa Y, Kawamura M, Kawasaki H, Sotomatsu M, Takizawa T, Matsuo H, Shimada A, Kiyokawa N, Tomizawa D, Taga T, Ito E, Horibe K, Miyano S, Adachi S, Taki T, Ogawa S, Hayashi Y. TP53 and RB1 alterations characterize poor prognostic subgroups in pediatric acute myeloid leukemia. Genes, chromosomes & cancer, 62:412-422, 2023
11. Nishimura T, Kakiuchi N, Yoshida K, Sakurai T, Kataoka TR, Kondoh E, Chigusa Y, Kawai M, Sawada M, Inoue T, Takeuchi Y, Maeda H, Baba S, Shiozawa Y, Saiki R, Nakagawa MM, Nannya Y, Ochi Y, Hirano T, Nakagawa T, Inagaki-Kawata Y, Aoki K, Hirata M, Nanki K, Matano M, Saito M, Suzuki E, Takada M, Kawashima M, Kawaguchi K, Chiba K, Shiraishi Y, Takita J, Miyano S, Mandai M, Sato T, Takeuchi K, Haga H, Toi M, Ogawa S. Evolutionary histories of breast cancer and related clones. Nature, 620:607-614, 2023
12. Komura K, Tokushige S, Ishida M, Hirosuna K, Yamazaki S, Nishimura K, Ajiro M, Ohno T, Nakamori K, Kinoshita S, Tsujino T, Maenosono R, Yoshikawa Y, Takai T, Tsutsumi T, Taniguchi K, Tanaka T, Takahara K, Inamoto T, Hirose Y, Ono F, Shiraishi Y, Yoshimi A, Azuma H. Tertiary lymphoid structure and neutrophil-lymphocyte ratio coordinately predict outcome of pembrolizumab. Cancer science, 114:4622-4631, 2023
13. Komura K, Hirosuna K, Tokushige S, Tsujino T, Nishimura K, Ishida M, Hayashi T, Ura A, Ohno T, Yamazaki S, Nakamori K, Kinoshita S, Maenosono R, Ajiro M, Yoshikawa Y, Takai T, Tsutsumi T, Taniguchi K, Tanaka T, Takahara K, Konuma T, Inamoto T, Hirose Y, Ono F, Shiraishi Y, Yoshimi A, Azuma H. The Impact of FGFR3 Alterations on the Tumor Microenvironment and the Efficacy of Immune Checkpoint Inhibitors in Bladder Cancer. Molecular cancer, 22:185, 2023