Christine E. Brown

This study shows that targeting the TGFβ pathway improves CAR T cell efficacy in glioblastoma by enhancing antitumor activity and modulating the tumor microenvironment.

This study develops meditope-enabled CARs to improve T cell functionality and address tumor heterogeneity in CAR therapy.

This study analyzes multi-omic data from gliomas to identify therapeutic escape mechanisms and TME evolution, finding that N-glycosylation classifies tumor grade and immune transcriptome predicts GBM survival.

This paper introduces qOBM for non-destructive, label-free monitoring of T cell cultures, showing strong correlation with traditional assays and potential for improving cell therapy development.

DeepSomatic is a deep learning method for detecting somatic variants from short-read and long-read sequencing data, outperforming existing callers, especially for indels.

This study uses a mathematical model to analyze CAR T-cell and oncolytic virus dynamics in glioblastoma, identifying virus bursting size as a key determinant of combination therapy efficacy.

This study uses a mathematical model to explore combination CAR T-cell treatments for glioblastoma, showing that early intervention and spatially targeted delivery are effective strategies.

The paper develops a high-throughput platform to profile antigen-specific CD4+ T cells at single-cell resolution, identifying immunogenic features and functional heterogeneity in viral and cancer contexts.

This study identifies SPP1+ macrophages as key drivers of resistance to CAR T therapy in solid tumors and shows that targeting SPP1 can overcome this resistance.

This paper presents an organoid-based platform using L-MYC-immortalized human neural stem cells to model cerebral development in vitro, showing similar gene expression patterns to normal cortical development.

This study examines the structural and practical identifiability of compartment models used in DCE-MRI, showing that while all models are structurally identifiable, practical identifiability depends on data characteristics and noise levels.