Tokyo University of Agriculture and Technology Yoshino Lab.
Molecular Biotechnology of Circulating Tumor Cells
Single-cell gene analysis of CTCs (Circulating Tumor Cells)
In our laboratory, we have been utilizing the MCA/GCM method to isolate CTCs and perform single-cell gene analysis. Through collaborative research with medical institutions, we have conducted single-cell transcriptome analysis of CTCs from various types of cancer, including gastric cancer. Our findings revealed that many CTCs in the blood exhibit higher expression of mesenchymal genes compared to epithelial genes, suggesting that the CTCs undergo epithelial-mesenchymal transition (EMT). EMT is a process in which epithelial cells acquire mesenchymal traits, which enhances their motility and is thought to play a key role in promoting cancer cell invasion into blood vessels and facilitating metastasis.
In addition, we also focused on analyzing the interactions between CTCs and platelets or other blood cells. This work is expected to provide valuable insights into the mechanisms of cancer metastasis and contribute to the development of new therapeutic approaches aimed at inhibiting metastasis
Cancer cell diagnosis through organellar analysis of CTCs
Organelles, such as the nucleus, mitochondria, and lipid droplets, are intracellular structures that reflect the physiological functions of cells. As a result, they have long been a focus of study in cell biology and medicine. In cancer research, evaluating the morphology, distribution, and size of organelles has been instrumental in understanding cancer cells. For example, it is known that the nucleus of cancer cells is larger than that of normal cells. Recently, as differences in the properties of individual cells have become clearer, there has been a growing demand for organelle analysis at the single-cell level.
In our laboratory, we have achieved organelle analysis and physical property evaluation of cells arrayed by the MCA using 3D imaging. We are currently advancing the characterization of cancer cells by evaluating various organelles. Furthermore, by integrating single-cell gene expression data with 3D imaging, we aim to provide a comprehensive assessment of rare cells, such as CTCs, and contribute to predicting disease progression and informing treatment decisions for patients.
