Research Focus

Computational Biology Targeting Comprehensive RNA Metabolism

Cells possess characteristic sets of RNA, collectively known as the transcriptome, which are unique to each cell type. The transcriptome not only serves to characterize these cell types but also adapts in response to the external physical environment, the status of cell communication, and various molecular signaling pathways. Moreover, individual differences in the genome, such as single nucleotide polymorphisms (SNPs), can also influence the transcriptome.

RNA is not merely an intermediary between the genome and proteins; it provides various regulatory layers that include stability, translational control, diverse interactions with DNA, RNA, proteins, and regulation of intracellular localization through liquid-liquid phase separation (LLPS). Furthermore, a significant number of non-coding RNAs—RNA molecules that do not translate into proteins—have functions that are not yet clearly defined. These non-coding RNAs contribute to the complexity of RNA-mediated regulation of cellular functions.

Recently, advancements in high-throughput sequencing and related technologies have made it possible to elucidate the transcriptome at the single-cell level. Additionally, spatial information within tissues and detailed intracellular localization data are increasingly analyzable. As a platform grounded in the interdisciplinary fields of life sciences and computer science, we aim to develop and apply methods for the appropriate and extensive analysis of these data. Our goal is to contribute significantly to cancer immunology research through these innovative analytical techniques.

Members

Professors

Selected Publications

Minegishi M, Kuchimaru T, Nishikawa K, Isagawa T, Iwano S, Iida K, Hara H, Miura S, Sato M, Watanabe S, Shiomi A, Mabuchi Y, Hamana H, Kishi H, Sato T, Sawaki D, Sato S, Hanazono Y, Suzuki A, Kohro T, Kadonosono T, Shimogori T, Miyawaki A, Takeda N, Shintaku H, Kizaka-Kondoh S, Nishimura S. Secretory GFP reconstitution labeling of neighboring cells interrogates cell-cell interactions in metastatic niches. Nat Commun. 2023 Dec 5;14(1):8031. DOI: 10.1038/s41467-023-43855-2. PMID: 38052804; PMCID: PMC10697979.

Matsushima S, Ajiro M, Iida K, Chamoto K, Honjo T, Hagiwara M. Chemical induction of splice-neoantigens attenuates tumor growth in a preclinical model of colorectal cancer. Sci Transl Med. 2022 Nov 30;14(673):eabn6056. DOI: 10.1126/scitranslmed.abn6056. Epub 2022 Nov 30. PMID: 36449604.