Monica Schenone

Selective killing of cancer cells by a small molecule targeting the stress response to ROS

Malignant transformation, driven by gain-of-function mutations in oncogenes and loss-of-function mutations in tumour suppressor genes, results in cell deregulation that is frequently associated with enhanced cellular stress (for example, oxidative, replicative, metabolic and proteotoxic stress, and DNA damage). Adaptation to this stress phenotype is required for cancer cells to survive, and consequently cancer cells may become dependent upon non-oncogenes that do not ordinarily perform such a vital function in normal cells. Thus, targeting these non-oncogene dependencies in the context of a transformed genotype may result in a synthetic lethal interaction and the selective death of cancer cells. Here we used a cell-based small-molecule screening and quantitative proteomics approach that resulted in the unbiased identification of a small molecule that selectively kills cancer cells but not normal cells. Piperlongumine increases the level of reactive oxygen species (ROS) and apoptotic cell death in both cancer cells and normal cells engineered to have a cancer genotype, irrespective of p53 status, but it has little effect on either rapidly or slowly dividing primary normal cells. Significant antitumour effects are observed in piperlongumine-treated mouse xenograft tumour models, with no apparent toxicity in normal mice. Moreover, piperlongumine potently inhibits the growth of spontaneously formed malignant breast tumours and their associated metastases in mice. Our results demonstrate the ability of a small molecule to induce apoptosis selectively in cells that have a cancer genotype, by targeting a non-oncogene co-dependency acquired through the expression of the cancer genotype in response to transformation-induced oxidative stress.

Lenalidomide Causes Selective Degradation of IKZF1 and IKZF3 in Multiple Myeloma Cells

Drug With a (Re)Purpose Thalidomide, once infamous for its deleterious effects on fetal development, has re-emerged as a drug of great interest because of its beneficial immunomodulatory effects. A derivative drug called lenalidomide significantly extends the survival of patients with multiple myeloma, but the molecular mechanisms underlying its efficacy remain unclear (see the Perspective by Stewart). Building on a previous observation that thalidomide binds to cereblon, a ubiquitin ligase, Lu et al. (p. 305, published online 28 November) and Krönke et al. (p. 301, published online 28 November) show that in the presence of lenalidomide, cereblon selectively targets two B cell transcription factors (Ikaros family members, IKZF1 and IKZF3) for degradation. In myeloma cell lines and patient cells, down-regulation of IKZF1 and IKZF3 was necessary and sufficient for the drugs anticancer activity. Thus, lenalidomide may act, at least in part, by “grepurposing” a ubiquitin ligase. A drug with potent activity in multiple myeloma patients acts by inducing degradation of two specific transcription factors. [Also see Perspective by Stewart] Lenalidomide is a drug with clinical efficacy in multiple myeloma and other B cell neoplasms, but its mechanism of action is unknown. Using quantitative proteomics, we found that lenalidomide causes selective ubiquitination and degradation of two lymphoid transcription factors, IKZF1 and IKZF3, by the CRBN-CRL4 ubiquitin ligase. IKZF1 and IKZF3 are essential transcription factors in multiple myeloma. A single amino acid substitution of IKZF3 conferred resistance to lenalidomide-induced degradation and rescued lenalidomide-induced inhibition of cell growth. Similarly, we found that lenalidomide-induced interleukin-2 production in T cells is due to depletion of IKZF1 and IKZF3. These findings reveal a previously unknown mechanism of action for a therapeutic agent: alteration of the activity of an E3 ubiquitin ligase, leading to selective degradation of specific targets.

Target identification and mechanism of action in chemical biology and drug discovery

Target-identification and mechanism-of-action studies have important roles in small-molecule probe and drug discovery. Biological and technological advances have resulted in the increasing use of cell-based assays to discover new biologically active small molecules. Such studies allow small-molecule action to be tested in a more disease-relevant setting at the outset, but they require follow-up studies to determine the precise protein target or targets responsible for the observed phenotype. Target identification can be approached by direct biochemical methods, genetic interactions or computational inference. In many cases, however, combinations of approaches may be required to fully characterize on-target and off-target effects and to understand mechanisms of small-molecule action.

Identifying the proteins to which small-molecule probes and drugs bind in cells

Most small-molecule probes and drugs alter cell circuitry by interacting with 1 or more proteins. A complete understanding of the interacting proteins and their associated protein complexes, whether the compounds are discovered by cell-based phenotypic or target-based screens, is extremely rare. Such a capability is expected to be highly illuminating—providing strong clues to the mechanisms used by small-molecules to achieve their recognized actions and suggesting potential unrecognized actions. We describe a powerful method combining quantitative proteomics (SILAC) with affinity enrichment to provide unbiased, robust and comprehensive identification of the proteins that bind to small-molecule probes and drugs. The method is scalable and general, requiring little optimization across different compound classes, and has already had a transformative effect on our studies of small-molecule probes. Here, we describe in full detail the application of the method to identify targets of kinase inhibitors and immunophilin binders.

Identification of Regulators of Polyploidization Presents Therapeutic Targets for Treatment of AMKL

The mechanism by which cells decide to skip mitosis to become polyploid is largely undefined. Here we used a high-content image-based screen to identify small-molecule probes that induce polyploidization of megakaryocytic leukemia cells and serve as perturbagens to help understand this process. Our study implicates five networks of kinases that regulate the switch to polyploidy. Moreover, we find that dimethylfasudil (diMF, H-1152P) selectively increased polyploidization, mature cell-surface marker expression, and apoptosis of malignant megakaryocytes. An integrated target identification approach employing proteomic and shRNA screening revealed that a major target of diMF is Aurora kinase A (AURKA). We further find that MLN8237 (Alisertib), a selective inhibitor of AURKA, induced polyploidization and expression of mature megakaryocyte markers in acute megakaryocytic leukemia (AMKL) blasts and displayed potent anti-AMKL activity in vivo. Our findings provide a rationale to support clinical trials of MLN8237 and other inducers of polyploidization and differentiation in AMKL.

Rps14 haploinsufficiency causes a block in erythroid differentiation mediated by S100A8 and S100A9.

Impaired erythropoiesis in the deletion 5q (del(5q)) subtype of myelodysplastic syndrome (MDS) has been linked to heterozygous deletion of RPS14, which encodes the ribosomal protein small subunit 14. We generated mice with conditional inactivation of Rps14 and demonstrated an erythroid differentiation defect that is dependent on the tumor suppressor protein p53 (encoded by Trp53 in mice) and is characterized by apoptosis at the transition from polychromatic to orthochromatic erythroblasts. This defect resulted in age-dependent progressive anemia, megakaryocyte dysplasia and loss of hematopoietic stem cell (HSC) quiescence. As assessed by quantitative proteomics, mutant erythroblasts expressed higher levels of proteins involved in innate immune signaling, notably the heterodimeric S100 calcium-binding proteins S100a8 and S100a9. S100a8—whose expression was increased in mutant erythroblasts, monocytes and macrophages—is functionally involved in the erythroid defect caused by the Rps14 deletion, as addition of recombinant S100a8 was sufficient to induce a differentiation defect in wild-type erythroid cells, and genetic inactivation of S100a8 expression rescued the erythroid differentiation defect of Rps14-haploinsufficient HSCs. Our data link Rps14 haploinsufficiency in del(5q) MDS to activation of the innate immune system and induction of S100A8-S100A9 expression, leading to a p53-dependent erythroid differentiation defect.

Empirical Bayes Analysis of Quantitative Proteomics Experiments

Background Advances in mass spectrometry-based proteomics have enabled the incorporation of proteomic data into systems approaches to biology. However, development of analytical methods has lagged behind. Here we describe an empirical Bayes framework for quantitative proteomics data analysis. The method provides a statistical description of each experiment, including the number of proteins that differ in abundance between 2 samples, the experiments statistical power to detect them, and the false-positive probability of each protein. Methodology/Principal Findings We analyzed 2 types of mass spectrometric experiments. First, we showed that the method identified the protein targets of small-molecules in affinity purification experiments with high precision. Second, we re-analyzed a mass spectrometric data set designed to identify proteins regulated by microRNAs. Our results were supported by sequence analysis of the 3′ UTR regions of predicted target genes, and we found that the previously reported conclusion that a large fraction of the proteome is regulated by microRNAs was not supported by our statistical analysis of the data. Conclusions/Significance Our results highlight the importance of rigorous statistical analysis of proteomic data, and the method described here provides a statistical framework to robustly and reliably interpret such data.

Identifying Cellular Targets of Small-Molecule Probes and Drugs with Biochemical Enrichment and SILAC

Sequencing of the human genome in the last decade has not yet led to a concomitant increase in the numbers of novel drug targets. While the pharmaceutical industry has invested heavily in improving drugs for existing protein targets, it has not tended toward a similar investment in experimental approaches to identify cellular targets of drugs. It is striking that the targets of numerous widely used FDA-approved drugs remain unknown. The development of robust, unbiased methods for target identification would greatly enhance our understanding the mechanisms-of-action of small molecules. Cell-based phenotypic screens followed by unbiased target identification have the potential to identify novel combinations of small molecules and their protein targets, shed light on drug polypharmacology, and enable unbiased screening approaches to drug discovery. Classical biochemical enrichment with immobilized small molecules has been used for over four decades but has been limited by issues concerning specificity and sensitivity. The application of mass spectrometry-based quantitative proteomics in combination with these affinity reagents has proven to be especially useful in addressing these common issues in affinity purification experiments. We describe the use of SILAC in identifying proteins that bind small-molecule probes and drugs in a cellular context.

Identification of cancer-cytotoxic modulators of PDE3A by predictive chemogenomics

High cancer death rates indicate the need for new anti-cancer therapeutic agents. Approaches to discover new cancer drugs include target-based drug discovery and phenotypic screening. Here, we identified phosphodiesterase 3A modulators as cell-selective cancer cytotoxic compounds by phenotypic compound library screening and target deconvolution by predictive chemogenomics. We found that sensitivity to 6-(4-(diethylamino)-3-nitrophenyl)-5-methyl-4,5-dihydropyridazin-3(2H)-one, or DNMDP, across 766 cancer cell lines correlates with expression of the phosphodiesterase 3A gene, PDE3A. Like DNMDP, a subset of known PDE3A inhibitors kill selected cancer cells while others do not. Furthermore, PDE3A depletion leads to DNMDP resistance. We demonstrated that DNMDP binding to PDE3A promotes an interaction between PDE3A and Schlafen 12 (SLFN12), suggesting a neomorphic activity. Co-expression of SLFN12 with PDE3A correlates with DNMDP sensitivity, while depletion of SLFN12 results in decreased DNMDP sensitivity. Our results implicate PDE3A modulators as candidate cancer therapeutic agents and demonstrate the power of predictive chemogenomics in small-molecule discovery.

Integrated genomics of crohn's disease risk variant identifies a role for CLEC12A in antibacterial autophagy

Summary The polymorphism ATG16L1 T300A, associated with increased risk of Crohn’s disease, impairs pathogen defense mechanisms including selective autophagy, but specific pathway interactions altered by the risk allele remain unknown. Here, we use perturbational profiling of human peripheral blood cells to reveal that CLEC12A is regulated in an ATG16L1-T300A-dependent manner. Antibacterial autophagy is impaired in CLEC12A-deficient cells, and this effect is exacerbated in the presence of the ATG16L1∗300A risk allele. Clec12a−/− mice are more susceptible to Salmonella infection, supporting a role for CLEC12A in antibacterial defense pathways in vivo. CLEC12A is recruited to sites of bacterial entry, bacteria-autophagosome complexes, and sites of sterile membrane damage. Integrated genomics identified a functional interaction between CLEC12A and an E3-ubiquitin ligase complex that functions in antibacterial autophagy. These data identify CLEC12A as early adaptor molecule for antibacterial autophagy and highlight perturbational profiling as a method to elucidate defense pathways in complex genetic disease.