Larsson, I. | Search bioRxiv

bioRxiv2024

The invasion phenotypes of glioblastoma depend on plastic and reprogrammable cell states

Glioblastoma (GBM), the most common primary brain cancer in adults, is characterized by rapid local invasion along diverse routes, such as infiltration of white matter tracts and penetration of perivascular spaces. We investigate the hypothesis that GBM invasion routes correlate with the transcriptional states of individual cells and identify regulators of route-specific invasion. Utilizing patient-derived GBM xenograft models, we integrate single-cell transcriptomics and spatial proteomics, revealing that mesenchymal and oligodendrocyte progenitor-like GBM cells migrate perivascularly, while neural progenitor and astrocyte-like GBM cells invade diffusely. Computational reconstruction identifies ANXA1 as a perivascular invasion driver and lineage-restricted transcription factors RFX4 and HOPX as drivers of diffuse invasion, predictive of patient survival. Genetic ablation of these genes alters invasion phenotypes and extends survival in xenografted mice, clarifying the role of cell states in GBM invasion, and highlighting potential therapeutic targets for selective invasion route targeting in GBM patients.

cancer biology↗

bioRxiv2023

Reconstructing the regulatory programs underlying the phenotypic plasticity of neural cancers

Nervous system cancers contain a large spectrum of transcriptional cell states, reflecting processes active during normal development, injury response and growth. However, we lack a good understanding of these states regulation and pharmacological importance. Here, we describe the integrated reconstruction of such cellular regulatory programs and their therapeutic targets from extensive collections of single-cell RNA sequencing data (scRNA-seq) from both tumors and developing tissues. Our method, termed single-cell Regulatory-driven Clustering (scRegClust), predicts essential kinases and transcription factors in little computational time thanks to a new efficient optimization strategy. Using this method, we analyze scRNA-seq data from both adult and childhood brain cancers to identify transcription factors and kinases that regulate distinct tumor cell states. In adult glioblastoma, our model predicts that blocking the activity of PDGFRA, DDR1, ERBB3 or SOX6, or increasing YBX1 -activity, would potentiate temozolomide treatment. We further perform an integrative study of scRNA-seq data from both cancer and the developing brain to uncover the regulation of emerging meta-modules. We find a meta-module regulated by the transcription factors SPI1 and IRF8 and link it to an immune-mediated mesenchymal-like state. Our algorithm is available as an easy-to-use R package and companion visualization tool that help uncover the regulatory programs underlying cell plasticity in cancer and other diseases.

cancer biology↗