Measuring Cancer Hallmark Mediation of the TET1 Glioma Survival Effect with Linked Neural-Network Based Mediation Experiments

Abstract

This paper examines the effect of TET1 expression on survival in glioma patients using open-access data from the Genomic Data Commons. A neural network-based survival model was built on expression data from a selection of genes most affected by TET1 knockdown with a median cross-validated survival concordance of 82.5%. A synthetic experiment was then conducted that linked two separately trained neural networks: a multitask model estimating cancer hallmark gene expression from TET1 expression, and a survival neural network. This experiment quantified the mediation of the TET1 survival effect through eight cancer hallmarks: apoptosis, cell cycle, cell death, cell motility, DNA repair, immune response, two phosphorylation pathways, and a randomized gene sets. Immune response, DNA repair, and apoptosis displayed greater mediation than the randomized gene set. Cell motility was inversely associated with only 12.5% mediated concordance. We propose the neural network linkage mediation experiment as an approach to collecting evidence of hazard mediation relationships with prognostic capacity useful for designing interventions.