Cell-cell communication in tumor microenvironment (starting)
Wa aim to better understand cell-cell interaction networks in tumor microenvironment by using spatial transcriptomics data and technologies to pave the way for the development of dafe and long-lasting cancer treatments.
Introduction
Effective cell-to-cell communication is essential for maintaining body homeostasis, and disruptions in this process often result in serious diseases, including cancer. In 2015, our Laboratory at RIKEN Yokohama, lead by Prof.
Al Forrest (now at Harry Perkins Medical Research Institute, Australia)
, pioneered large-scale predictions of cell-to-cell communication networks
Ramilowski JA, et al., Nat. Commun. 6, 7866, 2015
Subsequent to our groundbreaking work, various ligand-receptor prediction tools and databases have been actively developed by us
(Hou R, et al., Nat. Commun. 11, 5011, 2020)
and by numerous research groups globally. These research outcomes have been instrumental in investigating diverse biological phenomena and various diseases and in enhancing medical treatments.
Fig: Visualizations of cell-connectivity summary network depict prediction of cell-cell communication via NATMI (Network Analysis Toolkit for the Multicellular Interactions, Hou et. al., 2020)
Project Specific Aims
- discovery tumor microenvironment ligand-receptor interaction network: cancer cells, healthy cells, and infiltrating immune cells within affected tissues or organs
- enhanced spatial transcriptomic technologies & protocols (in collaboration)
- AI and Molecular Dynamics algorithms for simulating ligand-receptor interactions
Methods & Data
We employ a combination of experimental techniques (spatial transcriptomics), bioinformatics/AI algorithms, and mathematical models to enhance the accuracy of ligand-receptor predictions. Our approach integrates both publicly available and proprietary Next-Generation Sequencing (NGS) data, encompassing bulk, single-cell, and spatial transcriptomics, as well as proteomics data.
JSPS Postdoc Needed
We are looking for JSPS Postdoc applicants with skills in:
1. Bioinformatics/AI (willing to learn relevant biology), and/or
2. Biology (willing to learn bioinformatics)
Questions or interested joining us for a JSPS postdoc ? Please email Jordan 📧 .