# Strength of spatial correlation between gray matter connectivity and patterns of proto-oncogene and neural network construction gene expression is associated with diffuse glioma survival

## TL;DR

This study links brain connectivity patterns with gene expression to predict survival in glioma patients, suggesting new therapeutic possibilities.

## Contribution

The study identifies novel gene-brain connectivity interactions and their survival predictive power in diffuse glioma patients.

## Key findings

- All 17 genes showed significant co-localization with brain connectivity (p < 0.03).
- Gene-brain co-localization strength predicted survival with high accuracy (AUC = 0.97 for random forest).
- Metabolic processes were overexpressed with high gene-brain co-localization (p < 0.001).

## Abstract

Like other forms of neuropathology, gliomas appear to spread along neural pathways. Accordingly, our group and others have previously shown that brain network connectivity is highly predictive of glioma survival. In this study, we aimed to examine the molecular mechanisms of this relationship via imaging transcriptomics.

We retrospectively obtained presurgical, T1-weighted MRI datasets from 669 adult patients, newly diagnosed with diffuse glioma. We measured brain connectivity using gray matter networks and coregistered these data with a transcriptomic brain atlas to determine the spatial co-localization between brain connectivity and expression patterns for 14 proto-oncogenes and 3 neural network construction genes.

We found that all 17 genes were significantly co-localized with brain connectivity (p < 0.03, corrected). The strength of co-localization was highly predictive of overall survival in a cross-validated Cox Proportional Hazards model (mean area under the curve, AUC = 0.68 +/− 0.01) and significantly (p < 0.001) more so for a random forest survival model (mean AUC = 0.97 +/− 0.06). Bayesian network analysis demonstrated direct and indirect causal relationships among gene-brain co-localizations and survival. Gene ontology analysis showed that metabolic processes were overexpressed when spatial co-localization between brain connectivity and gene transcription was highest (p < 0.001). Drug-gene interaction analysis identified 84 potential candidate therapies based on our findings.

Our findings provide novel insights regarding how gene-brain connectivity interactions may affect glioma survival.