Glioblastoma is a devastating disease that is among the deadliest of human cancers. One of the factors that make treatment difficult is its inherent heterogeneity, where targeted therapeutics result in eradication of subpopulations of the tumors. It has been shown that glioblastomas consist of four different cellular states driven by different genetic drivers. Another study suggested that immune cell components in the tumors differ among different types of glioblastoma. However, the interactions among tumor cells of different states, and between tumor cells and non-tumor cells, including immune cells, are yet to be unveiled.
Based on their expertise in generating glioblastoma models derived from genome-engineered human iPS cells, these researchers aim to expand their modeling system to generate comprehensive syngeneic models in mice and rats, which covers all four cellular states of glioblastoma. By establishing tumors using those engineered cells in different contexts, such as mixed heterogeneous tumors vs. tumors of single populations, or in immune competent vs. immune deficient environment, the group will decipher interactions among different cells consisting tumors. For this purpose, they will implement RNA-seq, single-cell RNA seq, and whole-genome sequencing of these varieties of models.