Going beyond the atlas – mapping the tumor landscape with complete genomic signatures

Katherine Kennedy1, Joe Dahl1, Miranda Graybill1, Tatiana Morozova1, Tia Tate1, Jon Zawistowski 1 , Jeff Blackinton1 and Jay West1

1BioSkryb Genomics Inc, Durham NC USA

Glioblastoma multiforme (GBM) represents an aggressive malignancy with dismal outcome. Despite recent advances in tumor biology, there are limited data capable of linking tumor landscape with genomic signatures to improve patient outcomes. Current tissue atlas methods capably identify cellular location and phenotype in tumor sections, however, they woefully underrepresent the totality of the genomic and transcriptomic landscape, frequently focusing on a pre-defined panel of genes or transcripts. One powerful combination capable of revealing such data is the CellCelector platform from ALS paired with ResolveOME to reveal the complete genome and transcriptome of a single cell. Here, we present an unbiased mapping approach that simultaneously allows for the complete assessment of the tumor genome and transcriptome at the single cell level in a highly heterogenous and deadly tumor type.

In this study, GBM tissues were digested in-situ and single cells selected for analysis using the CellCelector platform from ALS. For this pilot project, a total of 88 cells were evaluated in an unbiased survey across the landscape of the tumor. Single cells were selected distanced 10uM apart and importantly, no pre-defined stains were utilized to ensure random cell sampling. Single cells were processed using ResolveOME, enabling simultaneous evaluation of the complete genome and transcriptome. Whole genome and whole transcriptome sequencing was performed targeting 70M PE reads and 2M PE reads respectively. After sequencing, genomic and transcriptomic data were processed using the BaseJumper platform to identify cell type, cellular function, and differential gene expression in relation to genomic heterogeneity. We observe substantial heterogeneity between cells that can be organized into clear lineage tracing relationships between both spatial arrangement and mutational signature. This enables an improved understanding of the development of the tumor, and importantly, key insights into potential treatments.