Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures

Abstract

Sampling restrictions have hindered the comprehensive study of invasive non-enhancing (NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present an integrated multi-omic analysis of spatially matched molecular and multi-parametric magnetic resonance imaging (MRI) profiling across 313 multi-regional tumor biopsies, including 111 from the NE, across 68 HGG patients. Whole exome and RNA sequencing uncover unique genomic alterations to unresectable invasive NE tumor, including subclonal events, which inform genomic models predictive of geographic evolution. Infiltrative NE tumor is alternatively enriched with tumor cells exhibiting neuronal or glycolytic/plurimetabolic cellular states, two principal transcriptomic pathway-based glioma subtypes, which respectively demonstrate abundant private mutations or enrichment in immune cell signatures. These NE phenotypes are non-invasively identified through normalized K2 imaging signatures, which discern cell size heterogeneity on dynamic susceptibility contrast (DSC)-MRI. NE tumor populations predicted to display increased cellular proliferation by mean diffusivity (MD) MRI metrics are uniquely associated with EGFR amplification and CDKN2A homozygous deletion. The biophysical mapping of infiltrative HGG potentially enables the clinical recognition of tumor subpopulations with aggressive molecular signatures driving tumor progression, thereby informing precision medicine targeting.

Androgen loss weakens anti-tumor immunity and accelerates brain tumor growth

“…A total of 202 biopsies collected from 58 patients (22 females, 36 males) with high-grade glioma 24 were analyzed for bulk RNA-Seq 51 and underwent CIBERSORTx deconvolution alongside a snRNA-Seq reference 52 with clustered cell states as previously described 53 , producing estimates of T cell abundances in each sample. Due to the limited storage available on the CIBERSORTx online interface, snRNA was downsampled 3 times to produce 100 of each cell state as input into the algorithm, each run 6 times.…”

“…We previously demonstrated a male-biased increase in T cell exhaustion in GBM that contributes to worse outcomes in male patients 15 . To further understand the sex differences in anti-tumor immunity that occur with aging, we analyzed T cell abundance in tumor samples obtained from 58 patients with high grade gliomas (22 females, 36 males) using image-localized biopsies 24 . Bulk RNA sequencing on tumor samples was performed, and data was deconvolved to estimate T cell abundance in each sample.…”

Intrinsic and Microenvironmental Drivers of Glioblastoma Invasion

“…Moreover, Ruggiero and colleagues [ 194 ] conducted a preclinical evaluation of fast-field cycling nuclear magnetic resonance (FFC-NMR) and found that T1-relaxation at very low magnetic field through this sequence can successfully discern between proliferating and invasive/migrating glioma tissue, highlighting the promise of low-magnetic field relaxometry for future implementation in glioma patients. Finally, Hu et al leveraged multi-parametric MRI techniques such as diffusion tensor imaging (DTI) and dynamics susceptibility contrast MRI (DSC-MRI) and combined it with spatially-matched multi-omic analysis to characterize the biology of invasive non-enhancing tumor borders [ 195 ]. This study shows the informative power of advanced multimodal imaging to study glioma invasion in humans at the structural and molecular level to better inform clinical decision making.…”