Zinc Finger MYND-Type Containing 8 (ZMYND8) Is Epigenetically Regulated in Mutant Isocitrate Dehydrogenase 1 (IDH1) Glioma to Promote Radioresistance.

PURPOSE: Mutant isocitrate dehydrogenase 1 (mIDH1) alters the epigenetic regulation of chromatin, leading to a hypermethylation phenotype in adult glioma. This work focuses on identifying gene targets epigenetically dysregulated by mIDH1 to confer therapeutic resistance to ionizing radiation (IR). EXPERIMENTAL DESIGN: We evaluated changes in the transcriptome and epigenome in a radioresistant mIDH1 patient-derived glioma cell culture (GCC) following treatment with an mIDH1-specific inhibitor, AGI-5198. We identified Zinc Finger MYND-Type Containing 8 (ZMYND8) as a potential target of mIDH1 reprogramming. We suppressed ZMYND8 expression by shRNA knockdown and genetic knockout (KO) in mIDH1 glioma cells and then assessed cellular viability to IR. We assessed the sensitivity of mIDH1 GCCS to pharmacologic inhibition of ZMYND8-interacting partners: HDAC, BRD4, and PARP. RESULTS: Inhibition of mIDH1 leads to an upregulation of gene networks involved in replication stress. We found that the expression of ZMYND8, a regulator of DNA damage response, was decreased in three patient-derived mIDH1 GCCs after treatment with AGI-5198. Knockdown of ZMYND8 expression sensitized mIDH1 GCCs to radiotherapy marked by decreased cellular viability. Following IR, mIDH1 glioma cells with ZMYND8 KO exhibit significant phosphorylation of ATM and sustained γH2AX activation. ZMYND8 KO mIDH1 GCCs were further responsive to IR when treated with either BRD4 or HDAC inhibitors. PARP inhibition further enhanced the efficacy of radiotherapy in ZMYND8 KO mIDH1 glioma cells. CONCLUSIONS: These findings indicate the impact of ZMYND8 in the maintenance of genomic integrity and repair of IR-induced DNA damage in mIDH1 glioma. See related commentary by Sachdev et al., p. 1648.

Early detection of Alzheimer's disease using neuropsychological tests: a predict-diagnose approach using neural networks.

Alzheimer's disease (AD) is a slowly progressing disease for which there is no known therapeutic cure at present. Ongoing research around the world is actively engaged in the quest for identifying markers that can help predict the future cognitive state of individuals so that measures can be taken to prevent the onset or arrest the progression of the disease. Researchers are interested in both biological and neuropsychological markers that can serve as good predictors of the future cognitive state of individuals. The goal of this study is to identify non-invasive, inexpensive markers and develop neural network models that learn the relationship between those markers and the future cognitive state. To that end, we use the renowned Alzheimer's Disease Neuroimaging Initiative (ADNI) data for a handful of neuropsychological tests to train Recurrent Neural Network (RNN) models to predict future neuropsychological test results and Multi-Level Perceptron (MLP) models to diagnose the future cognitive states of trial participants based on those predicted results. The results demonstrate that the predicted cognitive states match the actual cognitive states of ADNI test subjects with a high level of accuracy. Therefore, this novel two-step technique can serve as an effective tool for the prediction of Alzheimer's disease progression. The reliance of the results on inexpensive, non-invasive tests implies that this technique can be used in countries around the world including those with limited financial resources.