Annual Report 2023
Division of Bioinformatics
Mamoru Kato, Jo Nishino, Eisaku Furukawa, Momoko Nagai, Iurii Nagornov, Munmee Dutta, Yoko Iwahara, Satsuki Kase, Ritsuko Onuki, Daichi Narushima
Introduction
The research activities of the Division of Bioinformatics are as follows: (1) developing new bioinformatics methods and data analysis for cancer research and medicine, (2) building new mathematical theories in biology through data analysis and computational approaches, and (3) performing bioinformatics analysis for experimental groups at this center and other research institutions.
Research Activities
1. Development of bioinformatics technologies for cancer genome medicine
While improving the functionality and performance of cisCall, which is a gene mutation detection program used in the NCC Oncopanel, we investigated and tested new methods and improved the program. This year's achievements are as follows:
- Update of the public version of cisCall
- Performance evaluation of the mutation detection method based on deep learning
- Development of the analysis pipeline for the whole genome analysis
- Development of a simulation program for reading depth and mutant allele frequency and evaluation of mutation detection performance
- Test of HRD detection program
- Implementation of a known mutation detection program
- Implementation of the TMB reporting function
- Parameter adjustment of SV detection
- Development of cloud infrastructure for accelerating calling calculation
- Test of human T2T reference
- Test of human pan-genome reference
- Development of a highly accurate PCR duplicate read removal program
- Test of software to detect CNVs in the germline
- Test of the pipeline for FFPE artifacts
2. Development of numerical simulation-based personalized medicine
We have been developing tugHall, a simulator of cancer cell evolution in the context of personalized medicine. This fiscal year, we designed and implemented a new model of tugHall, including the following changes:
- Designed and implemented a fast-computing algorithm.
- Designed and implemented the probabilities calculations based on Poisson distributions instead of the binomial distribution.
- Changed the interface and reorganized calculation flow including generation and post processes.
3. Bioinformatics analysis support
- Biomarker analysis using clinical trial data for glioblastoma
- Exome sequencing analysis of chemical-induced lung cancer using a mouse model
- Multi-omics analysis of data released from working groups in Pan-Cancer Analysis of Whole Genomes (PCAWG) and comparative analysis of PCAWG data and the data released from The Cancer Genome Atlas (TCGA)
- ICGC Gastric cancer clinico-genomic data analysis
- Mutational signature analysis of rat, mouse, and bacteria exposed to carcinogens
- Trials of low-frequency mutation analysis tools
- Gene expression analysis of mouse colitis-derived models
- Building a collaborative system and developing analysis methods with the Biostatistics Division of the Center for Research Administration and Support toward clinical research involving omics data
- Building a new system to detect DNA adducts using deep learning
- Estimation of the functions of VUSs utilizing the existing software
- Search for gene pairs associated with synthetic lethality
- Support for evaluating the role of a gene in melanoma using TCGA data
- Search of mutations regarding the NCYM gene in public databases
Education
We have provided bioinformatics education and technical support to the research groups in the NCC and other institutions, as well as research guidance to collaborating graduate students.
Future Prospects
We will continue to develop core bioinformatics technologies for cancer genome medicine and proceed toward the realization of precision medicine by transferring the technologies. We will also conduct basic research. To achieve these goals, we will utilize machine-learning and AI technologies and perform large-scale computational analysis using cloud computing platforms.
List of papers published in 2023
Journal
1. Miyazaki B, Ueno T, Sugiyama M, Kojima S, Arakawa A, Tao K, Tanimura K, Shiraishi K, Yagishita S, Kohsaka S, Kato M, Kiyokawa N, Goto Y, Yatabe Y, Hamada A, Mano H, Ogawa C, Tanaka Y. Promoter swapping of truncated PDGFRB drives Ph-like acute lymphoblastic leukemia. NPJ precision oncology, 7:132, 2023
2. Totoki Y, Saito-Adachi M, Shiraishi Y, Komura D, Nakamura H, Suzuki A, Tatsuno K, Rokutan H, Hama N, Yamamoto S, Ono H, Arai Y, Hosoda F, Katoh H, Chiba K, Iida N, Nagae G, Ueda H, Shihang C, Sekine S, Abe H, Nomura S, Matsuura T, Sakai E, Ohshima T, Rino Y, Yeoh KG, So J, Sanghvi K, Soong R, Fukagawa A, Yachida S, Kato M, Seto Y, Ushiku T, Nakajima A, Katai H, Tan P, Ishikawa S, Aburatani H, Shibata T. Multiancestry genomic and transcriptomic analysis of gastric cancer. Nature genetics, 55:581-594, 2023
3. Saito-Adachi M, Hama N, Totoki Y, Nakamura H, Arai Y, Hosoda F, Rokutan H, Yachida S, Kato M, Fukagawa A, Shibata T. Oncogenic structural aberration landscape in gastric cancer genomes. Nature communications, 14:3688, 2023
4. 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