A high-throughput, multiplex cell death assay using an RNAi screening approach

A genome scale RNAi screen identifies GLI1 as a novel gene regulating vorinostat sensitivity

Vorinostat is an FDA-approved histone deacetylase inhibitor (HDACi) that has proven clinical success in some patients; however, it remains unclear why certain patients remain unresponsive to this agent and other HDACis. Constitutive STAT (signal transducer and activator of transcription) activation, overexpression of prosurvival Bcl-2 proteins and loss of HR23B have been identified as potential biomarkers of HDACi resistance; however, none have yet been used to aid the clinical utility of HDACi. Herein, we aimed to further elucidate vorinostat-resistance mechanisms through a functional genomics screen to identify novel genes that when knocked down by RNA interference (RNAi) sensitized cells to vorinostat-induced apoptosis. A synthetic lethal functional screen using a whole-genome protein-coding RNAi library was used to identify genes that when knocked down cooperated with vorinostat to induce tumor cell apoptosis in otherwise resistant cells. Through iterative screening, we identified 10 vorinostat-resistance candidate genes that sensitized specifically to vorinostat. One of these vorinostat-resistance genes was GLI1, an oncogene not previously known to regulate the activity of HDACi. Treatment of vorinostat-resistant cells with the GLI1 small-molecule inhibitor, GANT61, phenocopied the effect of GLI1 knockdown. The mechanism by which GLI1 loss of function sensitized tumor cells to vorinostat-induced apoptosis is at least in part through interactions with vorinostat to alter gene expression in a manner that favored apoptosis. Upon GLI1 knockdown and vorinostat treatment, BCL2L1 expression was repressed and overexpression of BCL2L1 inhibited GLI1-knockdown-mediated vorinostat sensitization. Taken together, we present the identification and characterization of GLI1 as a new HDACi resistance gene, providing a strong rationale for development of GLI1 inhibitors for clinical use in combination with HDACi therapy.

Genome-wide functional genomic and transcriptomic analyses for genes regulating sensitivity to vorinostat

Identification of mechanisms of resistance to histone deacetylase inhibitors, such as vorinostat, is important in order to utilise these anticancer compounds more efficiently in the clinic. Here, we present a dataset containing multiple tiers of stringent siRNA screening for genes that when knocked down conferred sensitivity to vorinostat-induced cell death. We also present data from a miRNA overexpression screen for miRNAs contributing to vorinostat sensitivity. Furthermore, we provide transcriptomic analysis using massively parallel sequencing upon knockdown of 14 validated vorinostat-resistance genes. These datasets are suitable for analysis of genes and miRNAs involved in cell death in the presence and absence of vorinostat as well as computational biology approaches to identify gene regulatory networks.

High-throughput approaches to measuring cell death

Cell death is integral to developmental and disease processes, and high-throughput screening (HTS) has been instrumental both for understanding biological mechanisms underlying cell death and for discovering novel therapeutic agents targeting these pathways. The various cell death modalities and their distinctive morphological and biochemical features have led to the development of a staggering variety of assays to measure these features, many of which have been adapted to HTS format. Although not all cell death assays are readily amenable to a high-throughput format, the potential power of HTS assays and increasing accessibility to associated technology make it likely that new approaches will continue to emerge. In particular, many recent studies in this field have used multiplex assays and high-content imaging to measure several features concurrently. Here, we discuss a broad array of considerations for designing HTS cell death assays, including some common challenges and pitfalls. We aim to provide a framework for deciding the most appropriate biological readouts, assay strategy and mode, workflow, controls, validation, and bioinformatics.