P. Canoll

Electrophysiologically Targeted Biopsies Reveal the Transcriptional Landscape of Focal Epilepsy

This study uses electrophysiologically guided biopsies and single-nucleus RNA sequencing to identify transcriptional differences between seizure focus and ictal penumbra in focal epilepsy.

Biologically-informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post-treatment glioblastoma

This paper develops BioNet, a biologically-informed deep learning model, to predict intratumoral heterogeneity in post-treatment glioblastoma using MRI and biopsy data, showing improved performance over existing methods.

Multiplexed single-cell lineage tracing of mitotic kinesin inhibitor resistance in glioblastoma

This study uses lineage tracing and scRNA-seq to analyze drug resistance in glioblastoma cells treated with KIF11 inhibitor ispinesib, finding resistance-associated phenotypic changes and potential drug combinations.

EZH2 inhibition sensitizes IDH1R132H mutant gliomas to histone deacetylase inhibitor.

This study shows that EZH2 inhibition synergizes with HDAC inhibitors to kill IDH1R132H mutant glioma cells by reducing H3K27me3 and increasing H3K27ac.

Single-Cell Analysis of 5-ALA Intraoperative Labeling Specificity for Glioblastoma

This study shows 5-ALA labeling is not specific to transformed glioma cells but can label untransformed cells directly or via PpIX from surrounding tumor cells.

Mapping multiregional imaging-localized biopsies to MRI habitats reveals biologically significant glioma tissue states and associated patterns of cohabitating cellular subpopulations

The paper maps MRI-localized glioma biopsies to MRI habitats, identifying transcriptional tissue states and their association with cellular subpopulations and MRI features.

Re-convolving the compositional landscape of primary and recurrent glioblastoma reveals prognostic andtargetable tissue states

The paper identifies three tissue states in glioblastoma microenvironments using snRNAseq and spatial transcriptomics, linking them to metabolic pathways and clinical outcomes.

Single Unit Analysis and Wide-Field Imaging Reveal Alterations in Excitatory andInhibitory Neurons in Glioma

The paper uses single unit analysis and wide-field imaging to study excitatory and inhibitory neuron alterations in glioma, finding mTOR inhibition reverses these changes.

Deconvolution of Cell Type-Specific Drug Responses in Human Tumor Tissue with Single-Cell RNA-seq

This study uses single-cell RNA-seq to analyze cell type-specific drug responses in human tumor tissues, revealing personalized therapeutic strategies for solid tumors.

From cells to tissue: How cell scale heterogeneity impacts glioblastoma growth and treatment response

This paper develops a hybrid agent-based model to study how intratumor heterogeneity affects glioblastoma growth and treatment response using multiscale data and mathematical frameworks.

ENvironmental Dynamics Underlying Responsive Extreme Survivors (ENDURES) of Glioblastoma: a Multi-disciplinary Team-based, Multifactorial Analytical Approach

The paper introduces the ENDURES consortium to study extreme survivors of glioblastoma by integrating clinical data and creating patient-specific tumor models.

Sex-specific impact of patterns of imageable tumor growth on survival of primary glioblastoma patients

This study identifies sex-specific predictors of survival in glioblastoma patients using MR imaging and clinical data.

Single-Cell Transcriptome Analysis of Lineage Diversity and Microenvironment in High-Grade Glioma

This study uses single-cell RNA-Seq to analyze lineage diversity and microenvironment in high-grade gliomas, finding links between cellular identity, proliferation, and population structure.