GENE-47. A 3D ATLAS TO EVALUATE THE SPATIAL PATTERNING OF GENETIC ALTERATIONS AND TUMOR CELL STATES IN GLIOMA. (11th November 2019) - Hilz, Stephanie; Hong, Chibo; Jalbert, Llewellyn; Mazor, Tali; Martin, Michael; Kumar, Anupam; Shelton, Samuel; Wong, Karen; Hayes, Josie; Yu, Yao; Zhang, Michael; Luks, Tracy; et al.
Abstract: BACKGROUND: Previous studies of solid tumors have been restricted in their ability to map how heterogeneous cell populations evolved within the tumor in three-dimensional (3D) space due to insufficient sampling, typically one sample per tumor, and a lack of knowledge of where within the tumor the sample was obtained. Knowledge of the extensivity of heterogeneity and how it is spatially distributed is crucial for assessing whether a therapeutic target is truly tumor-wide, and for exploring how mutations relate to heterogeneity in the local microenvironment. METHODS: We developed a novel platform to integrate and visualize in 3D multi-omics data generated from each of 8–10 spatially mapped samples per tumor. Together, the 171 samples collected using this approach from 16 adult diffuse glioma at diagnosis and recurrence form a novel resource – the 3D Glioma Atlas. RESULTS: By maximally sampling the tumor geography without excluding samples based on low cancer cell fraction (CCF), we identify a subpopulation of glioblastoma with pervasively lower CCF likely excluded by other atlases, such as the TCGA, that used stringent CCF cutoffs. Exome sequencing of 3D-mapped samples from lower-grade tumors revealed that clonal expansions are typically spatially segregated, implying minimal tumor-wide intermixing of genetically heterogenous cells. Heterogeneity is less spatially segregated for faster-growing high-grade tumors, suggesting that cell populations expand in these tumors differently. Recurrent low-grade tumors have greater intratumoral mutational heterogeneity than newly diagnosed tumors, though this did not translate into greater dissimilarity in gene expression profiles for recurrent tumors, suggesting minimal functional impact of this additional mutational diversity on gene expression. CONCLUSIONS: The delineation of spatial patterns of heterogeneity that our work provides enables more informed interpretation of biopsies and greater insight into the factors shaping intratumoral variation of gene expression patterns. Ongoing work is exploring the spatial patterning of amplification events and the tumor microenvironment.