Annual Report 2022
Division of Bioinformatics
Mamoru Kato, Jo Nishino, Daichi Narushima, Eisaku Furukawa, Iurii Nagornov, Momoko Nagai, Yoko Iwahara, Hanako Ono, Munmee Dutta
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, 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, including the verifications of the number of mutations to reach over F-value 0.9
- 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 SNV detection performance
- Test of HRD detection program
- Implementation of known mutation detection program
- Implementation of TMB reporting function
- Parameter adjustment of SV detection
- Development of cloud infrastructure for accelerating calling calculation
- Performance enhancement of indels with soft clips
- Development of highly accurate PCR duplicate read removal program
- Test of software to detect CNVs in the germline
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 developed a new tugHall version which includes calculation of copy number alterations (duplications and deletions) at the gene level, and also developed methods to reduce computation time as well as methods to evaluate the model.
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
- 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
- Monitoring the early stage of tumor using DNA barcode
- Building a new system detecting DNA adducts using deep learning
- Establishment of the VUS functional estimation method utilizing the existing software
- Supporting research on ORF (Open Reading Frame) dominance and RNA expression levels
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 2022
Journal
1. Nagane M, Ichimura K, Onuki R, Narushima D, Honda-Kitahara M, Satomi K, Tomiyama A, Arai Y, Shibata T, Narita Y, Uzuka T, Nakamura H, Nakada M, Arakawa Y, Ohnishi T, Mukasa A, Tanaka S, Wakabayashi T, Aoki T, Aoki S, Shibui S, Matsutani M, Ishizawa K, Yokoo H, Suzuki H, Morita S, Kato M, Nishikawa R. Bevacizumab beyond Progression for Newly Diagnosed Glioblastoma (BIOMARK): Phase II Safety, Efficacy and Biomarker Study. Cancers, 14:5522, 2022
2. Satoh H, Arai Y, Furukawa E, Moriguchi T, Hama N, Urushidate T, Totoki Y, Kato M, Ohe Y, Yamamoto M, Shibata T. Genomic landscape of chemical-induced lung tumors under Nrf2 different expression levels. Carcinogenesis, 43:613-623, 2022
3. Kohno T, Kato M, Kohsaka S, Sudo T, Tamai I, Shiraishi Y, Okuma Y, Ogasawara D, Suzuki T, Yoshida T, Mano H. C-CAT: The National Datacenter for Cancer Genomic Medicine in Japan. Cancer discovery, 12:2509-2515, 2022
4. Suenaga Y, Kato M, Nagai M, Nakatani K, Kogashi H, Kobatake M, Makino T. Open reading frame dominance indicates protein-coding potential of RNAs. EMBO reports, 23:e54321, 2022