Towards understanding of disease essence using spatial omics information — Council of Health and Medical Strategy Promotion

Twenty years have passed since the human genome was deciphered to reveal various relevant findings, but at the same time, it has become also clear that there are limits to the fundamental understanding and treatment of diseases only with the genome. Another issue is the genomic information handling, which becomes personal information with sequences of more than 40 bases. Recently, however, research has progressed to a new stage by introducing spatial omics analysis.

Professor Yutaka Suzuki of the Graduate School of Frontier Sciences at the University of Tokyo proposed, at a Health and Medical Strategy Promotion Headquarters meeting, the re-construction of the utilization of the framework of existing data with spatial omics information, which do not correspond to personal information such as genomes, as the node and advocated to the construction of the utilization of such data on an all-Japan basis. The Health and Medical Strategy Promotion Secretariat of the Cabinet Office will set up the study group consisting of experts to proceed with discussions toward implementation.

PMI (Precision Medicine Initiative) in the United States of America invested approximately 11 billion yen to integrate both the resident cohort-studies and the electronic medical-record information for all diseases, to realize of a new research paradigm through open data sharing. In addition, Genomics England in the United Kingdom is conducting, with approximately 33 billion yen, whole-genome sequence analysis of 5 million people, and building a cluster formation business model for private companies.

On the other hand, in Japan as well, data production and analysis environment development are underway for whole genome implementation, and the platform project for realizing genomic medicine is promoting disease-specific genome research; and the clinical genomic information integrated database development project furthermore centered, and the genome research project are promoting data sharing. Cancer genomic medicine was also started, and the Cancer for Cancer Genomics and Advanced Therapeutics (C-CAT) was established.

However, there are limitations of genome-disease association analysis. For example, in ALK-fusion gene lung cancer, genomic mutations and diseases are directly linked, and therapeutic drugs have shown great effects, but the pathological mechanisms of many cancers have not yet been clarified. In a sense, this is a matter of course, and since the genome is a blueprint, and we cannot understand the ever-changing gene expression and its control mechanism. Despite this, it is no longer a dream to see how genes function in the 50 trillion cells in the human body, or to know if there are abnormalities in their function.

In order to analyze gene expression in each individual cell, UK Biobank acquired 3,000 items of data through multiple proteome analysis of blood and monitored changes with the environment and age of the individual. Some positive results have already appeared in diseases such as frailty that were difficult to analyze directly.

Trial research has also started in Japan, for example, it has become clear at the BioBank Japan (BBJ) that when the blood profile is disturbed and the inflammatory reactions are induced, the risk of life-style-related disease increases and links to genomic polymorphisms.

Spatial omics analysis comprehensively investigates the cells by analyzing the gene expression of each cell, and by acquiring simultaneously cell position information in the sections of a tissue. Under spatial omics analysis, which cells are expressing what genes are comprehensively investigated. In the field of basic research, this method has been used in a way close to manual work, and 10x Genomics in the USA recently commercialized the spatial omics analyzer Xenium and delivered the first Asian unit at the Kashiwa Campus of the University of Tokyo to enable large scale sample analysis.

Using this technique, for example, even in the case of lung adenocarcinoma, physiological information from gene expression information in each location of cells can be estimated in detail, and areas where immune checkpoint inhibitors are effective can be deduced through the activity of immune cells, where cancer has tamed immune cells, and where cancer is necrotic, and the metabolic inhibition of these sites are effective, because proliferation is extremely active and because immunity is suppressed. On the other hand, DNA mutations only reveal mutations in Epidermal Growth Factor Receptor (EGFR). Analysis of spatial omics information realizes the personalized medicine that delivers desired drug to the specific cells.

Spatial omics information itself does not contain information to identify individuals. Concretely speaking, it consists of numerical data such as image information of biological sample sections, coordinate information of mRNA, cells and nuclei, gene expression levels aggregated for each cell, gene names by single-cell analysis, cell IDs, expression information, and expression of each protein.

Since individuals cannot be identified even after adding information such as age, gender, residence area, and the International Classification of Diseases (ICD) to this information, it is possible to use the data without personal consent, unlike genome, for research and development.

With the advent of non-arrayed new modality data such as spatial omics information, Suzuki suggests the construction of a functional genome database that handles data not applicable to personal information such as spatial transcriptome, images, and behavior. Providing access to such information to many researchers will lead to clarification of the pathogenesis of various diseases. It is also urgent that a central database be built to increase value by connecting with genome data and medical information of each biobank.