We will deepen our integrative systems understanding of cancer by investigating genesis, evolution and heterogeneity of cancer, genetic diversity in an individual due to mosaicism of embryonic/somatic cells, unknown functions of non-coding RNAs, and malignancy in regard to cellular context. “Systems Cancer Research” utilized methodologies such as mathematical modeling, large-scale data analysis, and statistical genetics enhanced with supercomputers as the driving force. By newly integrating an innovative information technology “Cognitive Computing” into cancer research, “Systems Cancer in Neo-dimension” will achieve a new paradigm for shuttling skillfully between the targets of interest in individual cancer and the entire pictures of cancer unraveled with the systems cancer research methodologies. Simultaneously, we establish the cancer ELSI that will ensure consistency with not-yet encountered issues springing out from big data, and bolster, sometimes face off against, currently inconceivable future cancer genome research and medicine.

We develop methodologies for acquiring large-scale precise global views of systems disorders in cancer and then pinpointing target parts of interest (genes, pathways, etc.) by cognitive computing utilizing cancer big data.

The first issue is “global view on whole-genomes of human populations” in disease-wise or population-wise way based on large-scale omics data and phenome data. The second issue is “local view on genomes” for understanding the functions of cancer genomes. We deepen our understanding of systems disorders in caner by integrating these two issues with the innovation in genome analysis and supercomputer ability. We investigate cancer systems spatiotemporally and/or topologically from the viewpoints of cellular context, evolution and heterogeneity, and non-coding RNA, that shall lead to innovations for prevention, early-diagnosis, therapeutics, and escape from resistance of therapy.

We develop a framework for mathematical methods (mathematical modelling, data analysis, statistical genetics, etc.) to encounter with cancer big data. Innovative information technologies such as “Cognitive Computing” will be exploited to advance integrative systems understanding of cancer. [A1] will produce personal whole genomes and will unravel mosaicism in cells and how mutations in hematopoietic stem cell are accumulated by aging. To cope with the emergency of cancer big data society, we establish a new cancer ELSI.

We can advance systems understanding of heterogeneity and complexity of cancer in terms of genomes, non-coding RNAs, and cellular context of cancer together with innovative analytics. Applications of cognitive computing to cancer analytics will lead to an innovation, and the establishment of cancer ELSI will have an increasing impact over the aging society.

Systems Cancer Research: An interdisciplinary field to understand cancer as system disease by combining mathematical modeling/simulation, large-scale data analysis and experimental systems analysis.

FY2015-2019