Nagi G. Ayad

RAC1 Regulates Shh-Medulloblastoma Growth via GLI-Mediated Transcription

This study identifies RAC1 as a druggable target in Shh-dependent medulloblastoma by showing its role in regulating GLI1 and GLI2 transcription and demonstrating the efficacy of the inhibitor GYS32661 in reducing tumor growth.

Drug and single-cell gene expression integration identifies sensitive and resistant glioblastoma cell populations

The paper integrates single-cell RNA sequencing data with drug response signatures to identify drug-sensitive and resistant glioblastoma cell states and predict synergistic drug combinations.

In silico drug sensitivity predicts subgroup-specific therapeutics in medulloblastoma patients

This paper develops DrugSeq, a computational platform that predicts drug sensitivities in medulloblastoma subgroups, identifying subgroup-specific therapies and potential drug repositioning candidates.

OrthologAL: A Shiny application for quality-aware humanization of non-human pre-clinical high-dimensional gene expression data

OrthologAL converts non-human transcriptomics data to human orthologs for drug discovery, preserving data structure and enabling use with human-annotated databases.

MAT2a and AHCY Inhibition Disrupts Antioxidant Metabolism and Reduces Glioblastoma Cell Survival

This study identifies MAT2A and AHCY as critical for glioblastoma survival by regulating antioxidant metabolism, showing their inhibition reduces cell viability and oxidative stress.

Identification of disease-specific vulnerability states at the single-cell level

The paper identifies three single-cell vulnerability states in glioblastoma using transcriptomic data and CRISPR screens, showing differential drug sensitivity and spatial distribution.