Glioblastomas are aggressive brain tumors for which few treatments exist and predicting treatment response can be tricky. Because of the tumor location, biopsy requires surgery and sedation, and is generally only performed at the beginning of treatment, during tumor removal surgery, and sometimes at the end of treatment. Currently, standard needle biopsies used in glioblastoma treatment provide only simple information, such as the presence and type of cancer, and basic molecular information.
Working with clinical collaborators, a team of KI researchers has combined multiple analytic tools and methods to show, in a study published in Nature Communications, that standard glioblastoma biopsies contain a wealth of untapped data.
Researchers, including members of the White and Cima labs, as well as Robert A. Swanson (1969) Biotechnology Center Genomics Facility Director Stuart Levine, were able to perform a number of analyses, including single-cell RNA sequencing, spatial transcriptomics, metabolomics, proteomics, phosphoproteomics, T-cell clonotype analysis, and MHC Class I immunopeptidomics on standard biopsy tissue. They also examined biopsies taken from different locations in the brain, providing a framework for measuring spatial and genomic heterogeneity. By integrating data from these analyses the team was able to gain rich insight, for example spatially mapped immune cell-associated metabolic pathways.
Broadly, this project demonstrates that even standard glioblastoma biopsies contain a wealth of untapped data about this tumor, its disease biology, and potential therapeutic response.
This work was supported by a fellowship from the Ludwig Center at MIT and Break Through Cancer.