DNA-damaging agents have a long history of use in cancer chemotherapy. The full extent of their cellular mechanisms, which is essential to balance efficacy and toxicity, is often unclear. In addition, the use of many anticancer drugs is limited by dose-limiting toxicities as well as the development of drug resistance. Novel anticancer compounds are continually being developed in the hopes of addressing these limitations; however, it is essential to be able to evaluate these compounds for their mechanisms of action. This review covers the current DNA-damaging agents used in the clinic, discusses their limitations, and describes the use of chemical genomics to uncover new information about the DNA damage response network and to evaluate novel DNA-damaging compounds.

Genome-wide characterization of the in vivo cellular response to perturbation is fundamental to understanding how cells survive stress. Identifying the proteins and pathways perturbed by small molecules affects biology and medicine by revealing the mechanisms of drug action. We used a yeast chemogenomics platform that quantifies the requirement for each gene for resistance to a compound in vivo to profile 3250 small molecules in a systematic and unbiased manner. We identified 317 compounds that specifically perturb the function of 121 genes and characterized the mechanism of specific compounds. Global analysis revealed that the cellular response to small molecules is limited and described by a network of 45 major chemogenomic signatures. Our results provide a resource for the discovery of functional interactions among genes, chemicals, and biological processes.

Elesclomol is a first-in-class investigational drug currently undergoing clinical evaluation as a novel cancer therapeutic. The potent antitumor activity of the compound results from the elevation of reactive oxygen species (ROS) and oxidative stress to levels incompatible with cellular survival. However, the molecular target(s) and mechanism by which elesclomol generates ROS and subsequent cell death were previously undefined. The cellular cytotoxicity of elesclomol in the yeast S. cerevisiae appears to occur by a mechanism similar, if not identical, to that in cancer cells. Accordingly, here we used a powerful and validated technology only available in yeast that provides critical insights into the mechanism of action, targets and processes that are disrupted by drug treatment. Using this approach we show that elesclomol does not work through a specific cellular protein target. Instead, it targets a biologically coherent set of processes occurring in the mitochondrion. Specifically, the results indicate that elesclomol, driven by its redox chemistry, interacts with the electron transport chain (ETC) to generate high levels of ROS within the organelle and consequently cell death. Additional experiments in melanoma cells involving drug treatments or cells lacking ETC function confirm that the drug works similarly in human cancer cells. This deeper understanding of elesclomol's mode of action has important implications for the therapeutic application of the drug, including providing a rationale for biomarker-based stratification of patients likely to respond in the clinical setting.

The advent of therapeutic mRNAs significantly increases the possibilities of protein-based biologics beyond those that can be synthesized by recombinant technologies (eg, monoclonal antibodies, extracellular enzymes, and cytokines). In addition to their application in the areas of vaccine development, immune-oncology, and protein replacement therapies, one exciting possibility is to use therapeutic mRNAs to program undesired, diseased cells to synthesize a toxic intracellular protein, causing cells to self-destruct. For this approach to work, however, methods are needed to limit toxic protein expression to the intended cell type. Here, we show that inclusion of microRNA target sites in therapeutic mRNAs encoding apoptotic proteins, Caspase or PUMA, can prevent their expression in healthy hepatocytes while triggering apoptosis in hepatocellular carcinoma cells.

Platinum-based drugs have been used to successfully treat diverse cancers for several decades. Cisplatin, the original compound of this class, cross-links DNA, resulting in cell cycle arrest and cell death via apoptosis. Cisplatin is effective against several tumor types, yet it exhibits toxic side effects and tumors often develop resistance. To mitigate these liabilities while maintaining potency, we generated a library of non-classical platinum-acridine hybrid agents and assessed their mechanisms of action using a validated genome-wide screening approach in Saccharomyces cerevisiae and in the distantly related yeast Schizosaccharomyces pombe. Chemogenomic profiles from both S. cerevisiae and S. pombe demonstrate that several of the platinum-acridines damage DNA differently than cisplatin based on their requirement for distinct modules of DNA repair.

Dysregulation of RNA splicing by spliceosome mutations or in cancer genes is increasingly recognized as a hallmark of cancer. Small molecule splicing modulators have been introduced into clinical trials to treat solid tumors or leukemia bearing recurrent spliceosome mutations. Nevertheless, further investigation of the molecular mechanisms that may enlighten therapeutic strategies for splicing modulators is highly desired. Here, using unbiased functional approaches, we report that the sensitivity to splicing modulation of the anti-apoptotic BCL2 family genes is a key mechanism underlying preferential cytotoxicity induced by the SF3b-targeting splicing modulator E7107. While BCL2A1, BCL2L2 and MCL1 are prone to splicing perturbation, BCL2L1 exhibits resistance to E7107-induced splicing modulation. Consequently, E7107 selectively induces apoptosis in BCL2A1-dependent melanoma cells and MCL1-dependent NSCLC cells. Furthermore, combination of BCLxL (BCL2L1-encoded) inhibitors and E7107 remarkably enhances cytotoxicity in cancer cells. These findings inform mechanism-based approaches to the future clinical development of splicing modulators in cancer treatment.

BackgroundGenome-wide screening in human and mouse cells using RNA interference and open reading frame over-expression libraries is rapidly becoming a viable experimental approach for many research labs. There are a variety of gene expression modulation libraries commercially available, however, detailed and validated protocols as well as the reagents necessary for deconvolving genome-scale gene screens using these libraries are lacking. As a solution, we designed a comprehensive platform for highly multiplexed functional genetic screens in human, mouse and yeast cells using popular, commercially available gene modulation libraries. The Gene Modulation Array Platform (GMAP) is a single microarray-based detection solution for deconvolution of loss and gain-of-function pooled screens.ResultsExperiments with specially constructed lentiviral-based plasmid pools containing ~78,000 shRNAs demonstrated that the GMAP is capable of deconvolving genome-wide shRNA "dropout" screens. Further experiments with a larger, ~90,000 shRNA pool demonstrate that equivalent results are obtained from plasmid pools and from genomic DNA derived from lentivirus infected cells. Parallel testing of large shRNA pools using GMAP and next-generation sequencing methods revealed that the two methods provide valid and complementary approaches to deconvolution of genome-wide shRNA screens. Additional experiments demonstrated that GMAP is equivalent to similar microarray-based products when used for deconvolution of open reading frame over-expression screens.ConclusionHerein, we demonstrate four major applications for the GMAP resource, including deconvolution of pooled RNAi screens in cells with at least 90,000 distinct shRNAs. We also provide detailed methodologies for pooled shRNA screen readout using GMAP and compare next-generation sequencing to GMAP (i.e. microarray) based deconvolution methods.

Steric-blocking oligonucleotides (SBOs) are short, single-stranded nucleic acids designed to modulate gene expression by binding to RNA transcripts and blocking access from cellular machinery such as splicing factors. SBOs have the potential to bind to near-complementary sites in the transcriptome, causing off-target effects. In this study, we used RNA-seq to evaluate the off-target differential splicing events of 81 SBOs and differential expression events of 46 SBOs. Our results suggest that differential splicing events are predominantly hybridization driven, whereas differential expression events are more common and driven by other mechanisms (including spurious experimental variation). We further evaluated the performance of in silico screens for offtarget splicing events, and found an edit distance cutoff of three to result in a sensitivity of 14% and false discovery rate (FDR) of 99%. A machine learning model incorporating splicing predictions substantially improved the ability to prioritize low edit distance hits, increasing sensitivity from 4% to 26% at a fixed FDR of 90%. Despite these large improvements in performance, this approach does not detect the majority of events at an FDR <99%. Our results suggest that in silico methods are currently of limited use for predicting the off-target effects of SBOs, and experimental screening by RNA-seq should be the preferred approach.