Abstract ND04: BAY 2666605: The first PDE3A-SLFN12 complex inducer for cancer therapy

Velcrin compounds are a class of small molecules that induce complex formation between PDE3A and SLFN12, killing cancer cells that express elevated levels of these two proteins by a mechanism independent of PDE3A enzymatic inhibition. Instead, PDE3A binding stimulates the RNase activity of SLFN12, resulting in cleavage of the specific SLFN12 substrate, tRNA-Leu-TAA. Cleavage of tRNA-Leu-TAA in turn causes ribosomal pausing, inhibition of protein synthesis, and cancer cell death. Unlike traditional targeted therapies that leverage dependencies created in cancer cells by genomic alterations, velcrins instead kill cancer cells by a gain-of-function mechanism dependent on the RNase activity of SLFN12.

In a collaboration between the Broad Institute and Bayer Pharmaceuticals, we developed the first velcrin, BAY 2666605, to enter Phase I clinical trials. BAY 2666605 is active in cell line and patient-derived xenografts of several tumor types, specifically where elevated levels of the two biomarkers, PDE3A and SLFN12, are expressed. Biomarker-positive tumors are especially enriched among melanomas, and we have consistently observed tumor regression in biomarker-positive melanoma tumor models in vivo. BAY 2666605 furthermore shows drug-like properties, excellent brain penetration, increased stimulation of SLFN12 RNase activity, and reduced inhibition of PDE3A enzymatic activity compared with most other velcrins and approved PDE3A inhibitors. BAY 2666605 has recently entered a First-in-Human study (NCT04809805) in patients with advanced solid tumors that co-express PDE3A and SLFN12, including melanoma, ovarian cancer, and sarcoma.

Citation Format: Stefan Gradl, Sooncheol Lee, Martin Lange, Xiaoyun Wu, Silvia Goldoni, Timothy Lewis, Charlotte Kopitz, Colin Garvie, Philip Lienau, Stephanie Hoyt, Henrik Seidel, Stephan Kaulfuss, Manuel Ellermann, Luc de Waal, Adrian Tersteegen, Sven Golfier, Detlev Suelzle, Christa Hegele-Hartung, James Carr, Frederick Brookfield, Michael Bruening, Melanie Berthold, Thibaud Jourdan, Monica Schenone, Galen Gao, Joseph McGaunn, Antje Wengner, Elisa Aquilanti, Franziska Siegel, Marine Garrido, Annette Walter, Isabelle Genvresse, Andrew Cherniack, Stuart Schreiber, Knut Eis, Ashley Eheim, Matthew Meyerson, Heidi Greulich. BAY 2666605: The first PDE3A-SLFN12 complex inducer for cancer therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr ND04.

Abstract 54: Cryo-EM structure of the PDE3A-SLFN12 complex reveals requirements for the activation of SLFN12 RNase and DNMDP-induced cancer cell killing

We have identified a novel mechanism of selective cancer cell-killing, whereby small molecules such as DNMDP induce complex formation between phosphodiesterase 3A (PDE3A) and a poorly characterized protein, SLFN12, that leads to downstream cell death (de Waal et al., Nat Chem Biol 2016; Lewis et al., ACS Med Chem Letters, 2019; Wu et al., J Bio Chem 2020). This process therefore relies on the presence and interaction of these two proteins, rather than a pre-existing dependency, as is the mechanism of many currently available cancer therapies. While complex formation is required for cancer cell killing, the molecular basis for complex induction and the activity of the complex that leads to cell death have not been described.

In this study, we employed cryogenic electron microscopy (cryo-EM) to deduce the high-resolution structure of the DNMDP-induced PDE3A-SLFN12 complex. The solved structure includes DNMDP-bound PDE3A at 2.97 Å, as well as the structure of the full length SLFN12 at 2.76 Å. We found that the entire complex consists of a 2:2 hetero-tetramer with the C-terminal alpha-helix of SLFN12 reaching into the DNMDP-occupied substrate binding pocket of PDE3A and contacting both DNMDP and active site residues of PDE3A. The binding of DNMDP to PDE3A does not induce structural changes, but rather creates an adhesive surface at the entrance of the substrate binding pocket, which allows for stable binding of SLFN12. We have named DNMDP and similar PDE3A-SLFN12 complex inducing compounds “velcrins”, after the adhesive fabric. Site-directed mutagenesis confirmed that residues on the SLFN12 C-terminal helix are required for DNMDP-induced cell death.

Based on homology to the SLFN13, we predicted that SLFN12 would also encode an RNase. Indeed, purified SLFN12 protein cleaved ribosomal RNA in vitro and mutation of the putative catalytic residues abolished this activity. Importantly, catalytically dead SLFN12 mutants failed to mediate DNMDP-induced cell killing while retaining the ability to complex with PDE3A. Consistent with the requirement of SLFN12 RNase activity for DNMDP-induced cell death, overexpression of wild-type SLFN12 alone was cytotoxic, whereas overexpression of catalytically dead SLFN12 was not. The RNase activity of SLFN12 in vitro was stimulated in the presence of DNMDP and PDE3A, suggesting that the mechanism of DNMDP-induced cell killing involves activation of the SLFN12 RNase. Intriguingly, SLFN12 homodimer interface mutants were no longer cytotoxic when overexpressed, but still supported DNMDP-induced cell killing. We hypothesize that PDE3A, an obligate dimer, activates SLFN12 RNase activity by stabilizing the dimeric form of SLFN12.

Citation Format: Xiaoyun Wu, Colin Garvie, Sooncheol Lee, Steven Horner, Andrew Baker, Marcus Toetzl, Joseph McGaunn, Bethany Kaplan, Luc de Waal, Martin Lange, Timothy Lewis, Chris Lemke, Matthew Meyerson, Heidi Greulich. Cryo-EM structure of the PDE3A-SLFN12 complex reveals requirements for the activation of SLFN12 RNase and DNMDP-induced cancer cell killing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 54.

Optimization of PDE3A Modulators for SLFN12-Dependent Cancer Cell Killing

6-(4-(Diethylamino)-3-nitrophenyl)-5-methyl-4,5-dihydropyridazin-3(2H)-one, or DNMDP, potently and selectively inhibits phosphodiesterases 3A and 3B (PDE3A and PDE3B) and kills cancer cells by inducing PDE3A/B interactions with SFLN12. The structure-activity relationship (SAR) of DNMDP analogs was evaluated using a phenotypic viability assay, resulting in several compounds with suitable pharmacokinetic properties for in vivo analysis. One of these compounds, BRD9500, was active in an SK-MEL-3 xenograft model of cancer.

Abstract 5880: Small-molecule modulators of PDE3/SLFN12 to kill cancer cells

We have previously reported1 our results with a small molecule called DNMDP which kills certain cancer cells by modulating the interaction of PDE3A and Schlafen 12 (SLFN12), a more recently discovered protein of unknown function. While DNMDP selectively inhibits PDE3, most PDE3 inhibitors have no cell killing effects and in fact rescue cancer cells from DNMDP-induced death. DNMDP is not suitable for advanced studies due to structural liabilities. Optimization of DNMDP to both increase activity and improve pharmacokinetic properties resulted in enantiomerically pure, low molecular weight, metabolically stable compounds which are active at low doses in animal models of cervical cancer and melanoma. While these compounds are selective PDE3A inhibitors and their biochemical activity mirrors their cellular activity, the activity of the compounds results not from PDE3 inhibition and increased cAMP levels, but from increased compound-induced binding of PDE3A to SLFN12, which most PDE3 inhibitors do not effect. Our results suggest that small molecule modulators of PDE3/SLFN12 binding may provide a novel treatment for the treatment of certain cancers.

1Nat. Chem. Bio. 2016, 12, 102-108.

Citation Format: Timothy A. Lewis, Luc de Waal, Xiaoyun Wu, Manuel Ellerman, Charlotte Kopitz, Antje Wengner, Knut Eis, Martin Lange, Adrian Tersteegen, Philip Lienau, Heidi Greulich, Matthew Meyerson. Small-molecule modulators of PDE3/SLFN12 to kill cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5880.

Abstract 2028: PDE3A modulation for cancer therapy

In a differential cytotoxicity screen, we identified a novel small molecule modulator of phosphodiesterase 3A (PDE3A) that kills cancer cells expressing elevated levels of PDE3A and SLFN12 (de Waal, Nat Chem Biol, 2016). Treatment with this cell-selective cytotoxic small molecule, DNMDP, induces complex formation between PDE3A and SLFN12, resulting in apoptosis. Inhibition of PDE3A enzymatic activity is not sufficient for cancer cell killing, and expression of both PDE3A and SLFN12 are required. Although the mechanism of signaling to the apoptosis machinery remains unclear, we examined more closely the role of the PDE3A-SLFN12 complex in cancer cell killing mediated by DNMDP. We found that cancer cell lines made resistant to DNMDP by persistent exposure downregulated SLFN12 expression and that re-expression of SLFN12 was sufficient to restore sensitivity. Furthermore, ectopic expression of PDE3A and SLFN12 are sufficient to sensitize cancer cells to DNMDP. These data underscore the tight correlation of PDE3A-SLFN12 complex formation and cancer cell killing mediated by DNMDP.

Citation Format: Xiaoyun Wu, Timothy Lewis, Luc de Waal, Galen Gao, Jian Zhang, Monica Schenone, Colin Garvie, Brett Diamond, Selena Lorrey, Andrew Cherniack, Steven Corsello, Alex Burgin, Todd Golub, Stuart Schreiber, Matthew Meyerson, Heidi Greulich. PDE3A modulation for cancer therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2028. doi:10.1158/1538-7445.AM2017-2028

Abstract 1115: Targeted RNA sequencing improves transcript analysis in cancer samples

RNA sequencing (RNA-seq) is a transcriptome profiling technology that provides multiple levels of insight into the genome. In addition to expression levels (transcript abundance), it generates endpoints such as alternative splicing, somatic mutations and rearrangements, which may have functional consequences in cancer. Although somatic mutations are generally identified by DNA sequencing, RNA-seq has the advantage of detecting allele-specific expression affecting a variant allele, as well as functional chimeric transcripts that result from structural rearrangements. Compared to microarray technologies, RNA-seq can provide additional information about novel transcripts. Due to the complexity of the human transcriptome and the variability of gene abundance, the cost of whole transcriptome sequencing to achieve sufficient coverage to detect these types of alterations remains high. To explore the feasibility of a more cost-effective method, we compared the performance of three different RNA-seq methods: whole-transcriptome-, exome-, and targeted RNA-seq, using RNA derived from cancer cell lines and Formaldehyde Fixed-Paraffin Embedded (FFPE) samples. For whole-transcriptome preparation, we used the Illumina TruSeq Stranded mRNA and total RNA kits for cell line and FFPE samples, respectively. Exome-RNAseq was performed using the Illumina Access kit. The libraries from whole-transcriptome RNAseq were subjected to hybridization capture using OncoPanel-an Agilent SureSelect baitset of 500 cancer-related genes. Compared to whole-transcriptome, exome- and targeted-RNA-seq demonstrated (1) higher coding exon coverage and multiplexing capability; (2) reduced rRNA composition to 1%; (3) comparable gene abundance information and (4) over 90% of reads aligned to coding exon regions in FFPE samples, compare to ∼30% when using whole transcriptome method. In conclusion, we demonstrated that exome- and targeted RNA-seq provide a cost-effective way to analyze a subset of the transcriptome. Furthermore, targeted RNA-seq can be highly multiplexed and is therefore amenable for large-scale tumor profiling in clinical or research settings.

Citation Format: Ling Lin, Ryan Abo, Deniz Dolcen, Rachel Paquette, Angelica Laing, Luc de Waal, Aaron Thorner, Matthew Ducar, Liuda Ziaugra, Bruce Wollison, Marc Breneiser, William Hahn, Matthew Meyerson, Paul Van Hummelen, Laura MacConaill. Targeted RNA sequencing improves transcript analysis in cancer samples. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1115. doi:10.1158/1538-7445.AM2015-1115

Abstract 4867: Comparative analysis of RNA sequencing methods for characterization of cancer transcriptomics

RNA sequencing (RNASeq) provides the ability to comprehensively assay the transcriptome in a high-throughput manner. Current there are a variety of library preparation methodologies for measuring and sequencing the transcriptome depending on (a) the sample source and (b) outcomes of interest. Beyond protocol selection, the requisite computational tools and resources are significant considerations in processing, analyzing and reporting the experimental results. While there are many resources readily available to effectively perform RNA-seq experiments, optimal protocols and analysis tools for the cancer domain remain to be developed.

We have developed and characterized a set of protocols and analysis procedures that comprise an RNA-seq pipeline that can effectively be used in a cancer research setting. The analysis pipeline consists of a sequence of functions and tools to process and clean the raw data, generate quality control and summary metrics, and perform secondary analyses that include expression quantification, fusion detection and somatic mutation calling. We applied this pipeline to three different RNAseq strategies (whole-transcriptome, exome, and targeted RNA-seq) and performed an in-depth comparative analysis to investigate the implications of the choice of strategy on the downstream analysis and results. More specifically, we investigated the impact of library preparation methods on the dynamic range and expression profiles, variant calling and fusion detection. While the data indicated that capture-based protocols provided efficient methods for sampling transcripts as compared to whole-transcriptome RNA-seq, there are considerations in its use, particularly for duplicate reads and uncaptured transcripts. We illustrate the implications of these issues on downstream analysis, such as somatic mutation and fusion calling and differential expression.

In summary, we have described a RNA-seq analysis platform that provides a varied set of library preparations and analytical components for large-scale clinical or research transcriptomics. Our analysis has characterized the technical features of the different library preparations, providing a necessary understanding of the costs and benefits of each method and the potential effects on the downstream analyses.

Citation Format: Ryan P. Abo, Ling Lin, Samuel S. Hunter, Deniz N. Dolcen, Rachel R. Paquette, Angelica Laing, Luc de Waal, Aaron R. Thorner, Matthew D. Ducar, Liuda Ziaugra, William C. Hahn, Matthew L. Meyerson, Laura E. MacConaill, Paul Van Hummelen. Comparative analysis of RNA sequencing methods for characterization of cancer transcriptomics. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4867. doi:10.1158/1538-7445.AM2015-4867

A pan-cancer analysis of transcriptome changes associated with somatic mutations in U2AF1 reveals commonly altered splicing events

Although recurrent somatic mutations in the splicing factor U2AF1 (also known as U2AF35) have been identified in multiple cancer types, the effects of these mutations on the cancer transcriptome have yet to be fully elucidated. Here, we identified splicing alterations associated with U2AF1 mutations across distinct cancers using DNA and RNA sequencing data from The Cancer Genome Atlas (TCGA). Using RNA-Seq data from 182 lung adenocarcinomas and 167 acute myeloid leukemias (AML), in which U2AF1 is somatically mutated in 3-4% of cases, we identified 131 and 369 splicing alterations, respectively, that were significantly associated with U2AF1 mutation. Of these, 30 splicing alterations were statistically significant in both lung adenocarcinoma and AML, including three genes in the Cancer Gene Census, CTNNB1, CHCHD7, and PICALM. Cell line experiments expressing U2AF1 S34F in HeLa cells and in 293T cells provide further support that these altered splicing events are caused by U2AF1 mutation. Consistent with the function of U2AF1 in 3' splice site recognition, we found that S34F/Y mutations cause preferences for CAG over UAG 3' splice site sequences. This report demonstrates consistent effects of U2AF1 mutation on splicing in distinct cancer cell types.

Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing

Lung adenocarcinoma, the most common subtype of non-small cell lung cancer, is responsible for more than 500,000 deaths per year worldwide. Here, we report exome and genome sequences of 183 lung adenocarcinoma tumor/normal DNA pairs. These analyses revealed a mean exonic somatic mutation rate of 12.0 events/megabase and identified the majority of genes previously reported as significantly mutated in lung adenocarcinoma. In addition, we identified statistically recurrent somatic mutations in the splicing factor gene U2AF1 and truncating mutations affecting RBM10 and ARID1A. Analysis of nucleotide context-specific mutation signatures grouped the sample set into distinct clusters that correlated with smoking history and alterations of reported lung adenocarcinoma genes. Whole-genome sequence analysis revealed frequent structural rearrangements, including in-frame exonic alterations within EGFR and SIK2 kinases. The candidate genes identified in this study are attractive targets for biological characterization and therapeutic targeting of lung adenocarcinoma.