Synthetic lethal screens as a means to understand and treat MYC-driven cancers

Abstract

Although therapeutics against MYC could potentially be used against a wide range of human cancers, MYC-targeted therapies have proven difficult to develop. The convergence of breakthroughs in human genomics and in gene silencing using RNA interference (RNAi) have recently allowed functional interrogation of the genome and systematic identification of synthetic lethal interactions with hyperactive MYC. Here, we focus on the pathways that have emerged through RNAi screens and present evidence that a subset of genes showing synthetic lethality with MYC are significantly interconnected and linked to chromatin and transcriptional processes, as well as to DNA repair and cell cycle checkpoints. Other synthetic lethal interactions with MYC point to novel pathways and potentially broaden the repertoire of targeted therapies. The elucidation of MYC synthetic lethal interactions is still in its infancy, and how these interactions may be influenced by tissue-specific programs and by concurrent genetic change will require further investigation. Nevertheless, we predict that these studies may lead the way to novel therapeutic approaches and new insights into the role of MYC in cancer.

Figure 1.

Graphical representation of synthetic lethal interactions applied to MYC overexpression. (A) Growth/viability of normal cells expressing endogenously controlled levels of MYC^WT (gray) in comparison with cells overexpressing MYC (blue, MYC⁺). A gene is here defined as “synthetic lethal” with MYC overexpression if its knockdown minimally impacts viability/growth in the control cells, MYC^WT, while leading to loss of viability in MYC⁺ cells. (B) Schematic of results obtained from arrayed siRNA screening. Although most of the siRNAs similarly affect MYC^WT and MYC⁺ cells, with a gradient illustrating the lower abundance of highly toxic siRNAs, a small subset confers selective growth inhibition in MYC⁺ (blue oval). “Strong” hits lead to a dramatic loss of viability (below ∼20%) in contrast to “weak” hits, also referred to as “synthetic sick” (see text for details).

Figure 2.

Workflow of RNAi screening approaches to identify synthetic lethal interactions with MYC activation. (A) shRNA pooled approach (Kessler et al. 2012). Breast epithelial cells, HMECs, expressing the conditional MYC–ER fusion were transduced with a genome-wide shRNA lentiviral library in three independent replicates. Following transduction, cells were cultured for 12 population doublings in the presence or absence of tamoxifen to induce MYC–ER activity. To identify hits, genomic DNA was isolated, and the relative change in shRNA-barcode was measured in both states (MYC-ON and MYC-OFF). Approximately 400 genes with more then twofold under-representation were identified as candidate MYC-SL genes. (B) siRNA arrayed approach (Toyoshima et al. 2012). Isogenic HFFs with or without exogenous MYC overexpressed from a retroviral vector were transfected with siRNAs (3/gene) toward a custom collection of about 3000 druggable genes. The screen was performed in triplicate with 384-well plates. Following a 5-d incubation period, cell viability was measured using an automated plate reader; about 100 genes emerged from this screen. Liu et al. (2012) also used the arrayed approach in an osteosarcoma line (see text for details) (Liu et al. 2012).

Figure 3.

Subset of MYC-SL genes functionally linked through network analysis. Direct interactions among a subset of MYC-SL genes from all screens identified using a manually curated human interaction database derived from the merging of BioGRID, Cancer Cell Map, HPRD, HumanCyc, IMID, IntAct, MINT, NCI-Nature, and Reactome (see text for details). To verify the significance of the number of interactions among this MYC-SL gene network, a permutation randomized networks method was applied (Stumpf and Wiuf 2009), which indicated a p value of 2.841 × 10⁻⁰⁷ at a 95% confidence. (Light blue) Toyoshima hits; (dark blue) Kessler hits; (pink) A set of genes known to functionally interact with MYC (“core” genes). MYC-SL genes that intersect between the “core” genes and the Kessler screen (green), between “core” and Toyoshima (yellow), and intersection between Kessler and Toyoshima (orange). Interactions without directionality (blue lines); interactions with known directionality (red lines). Three functional hubs are highlighted in the circular network (A): One is centered around the MYC-MAX network (I); the second includes components of transcription initiation and elongation complexes, including BRD4 (II); and the third encompasses genes involved in cell cycle checkpoint and DNA-damage repair (III). (B) Organic layout of the same network to better visualize the connections between MYC-SL genes.

Figure 3.

Subset of MYC-SL genes functionally linked through network analysis. Direct interactions among a subset of MYC-SL genes from all screens identified using a manually curated human interaction database derived from the merging of BioGRID, Cancer Cell Map, HPRD, HumanCyc, IMID, IntAct, MINT, NCI-Nature, and Reactome (see text for details). To verify the significance of the number of interactions among this MYC-SL gene network, a permutation randomized networks method was applied (Stumpf and Wiuf 2009), which indicated a p value of 2.841 × 10⁻⁰⁷ at a 95% confidence. (Light blue) Toyoshima hits; (dark blue) Kessler hits; (pink) A set of genes known to functionally interact with MYC (“core” genes). MYC-SL genes that intersect between the “core” genes and the Kessler screen (green), between “core” and Toyoshima (yellow), and intersection between Kessler and Toyoshima (orange). Interactions without directionality (blue lines); interactions with known directionality (red lines). Three functional hubs are highlighted in the circular network (A): One is centered around the MYC-MAX network (I); the second includes components of transcription initiation and elongation complexes, including BRD4 (II); and the third encompasses genes involved in cell cycle checkpoint and DNA-damage repair (III). (B) Organic layout of the same network to better visualize the connections between MYC-SL genes.

Figure 4.

MYC-synthetic lethal genes related to transcription initiation and elongation complexes. (A) Schematic of transcription initiation complexes highlighting MYC-SL gene products. (B) Schematic of transcription elongation complexes (green, hits from Kessler; blue, hits from Toyoshima). CDK9, with a established role in phosphorylation of RNA polymerase, was identified through an siRNA screen comparing MYCN amplified versus nonamplified neuroblastoma cells (C Grandori, unpubl.).

Figure 5.

MYC copy number values in a subset of TCGA tumor types. This chart illustrates a recent analysis of The Cancer Genome Atlas data set relating to alterations in gene copy number for c-MYC across different cancer types. Gain indicates copy number change between 0.5 and 1.5; amplification is copy number change >1.5 (numbers reported are continuous, not integer, and may capture subclonality of copy number events). The number to the right of each bar is the GISTIC q value for significance (Beroukhim et al. 2007) of MYC copy number where available.