Abstract LB202: Discovery and preclinical characterization of novel small molecule inhibitors of kinesin KIF18A motor protein with potent activity against chromosomally unstable cancers

KIF18A is a mitotic kinesin that localizes to the plus-end tips of kinetochore microtubule (MT) spindle fibers during metaphase, where it regulates chromosome alignment, and promotes the viability of chromosomally unstable cancer cells. KIF18A is overexpressed in a subset of human cancers, and its elevated expression is associated with tumor aggressiveness.

Chromosomal instability (CIN) is a hallmark of human cancers and is caused by persistent errors in chromosome segregation during mitosis. Aggressive types of human cancer such as high-grade serous ovarian cancer (HGSOC) and triple-negative breast cancer (TNBC) have elevated levels of CIN and frequently harbor alterations in TP53 tumor suppressor gene. These two CIN+ cancer subtypes share molecular similarities but have limited treatment options at present. The rationale of pharmacological inhibition of KIF18A motor activity is to selectively target a tumor-specific mitotic spindle vulnerability in CIN+ cancer cells while largely sparing normal diploid dividing somatic cells.

Here, we describe the identification of a novel series of potent and selective small molecule inhibitors of KIF18A MT-ATPase motor activity exemplified by AM-1882, that disrupt the mitotic spindle and selectively kill chromosomally unstable cancer cells. Our KIF18A inhibitors phenocopy genetic ablation of KIF18A and trigger spindle assembly checkpoint activation, multipolarity, and apoptosis in sensitive CIN+ cancer cell lines. The sensitivity profile of AM-1882 is focal-in-nature with cell potency in the low double-digit nanomolar range across a panel of breast and ovarian cancer cell lines, including lines that harbor genetic alterations (e.g., TP53, CCNE1, RB1, BRCA1, whole genome doubling) frequently enriched in CIN+ cancers and in HGSOC and TNBC tumor subtypes. Furthermore, the sensitivity profile of AM-1882 is distinct from comparator test agents ispinesib (Eg5, pan cytotoxic) and palbociclib (CDK4/6, focal cytostatic). The combination of AM-1882 with PARP inhibitor olaparib is synergistic in BRCA1-deficient cancer cell lines, with evidence of increased double-strand DNA breaks (p-H2AX) and apoptosis (cl-PARP). Importantly, KIF18A inhibitors have minimal toxicity on normal dividing somatic cell types in vitro, including proliferating human bone marrow mononuclear cells, distinct from paclitaxel and small molecule inhibitors of essential mitotic kinases and kinesins. In vivo, we demonstrate that administration of KIF18A inhibitors AM-1882 and AM-5308 induce a robust pharmacodynamic response (pH3, mitotic marker) and frank tumor regressions in two TP53 mutant human HGSOC xenograft models (OVCAR-3, OVCAR-8) at well-tolerated doses.

Collectively, our preclinical data provides the first example of a therapeutic strategy to selectively target CIN+ cancers through inhibition of KIF18A motor protein.

Citation Format: Jan Sun, Brain Belmontes, Jodi Moriguchi, Grace Chung, Kui Chen, John D. McCarter, Upendra P. Dahal, Andrew S. Boghossian, Matthew G. Rees, Melissa M. Ronan, Jennifer A. Roth, Sheroy Minocherhomji, Matthew P. Bourbeau, Jennifer R. Allen, Angela Coxon, Paul E. Hughes, Nuria Tamayo, Marc N. Payton. Discovery and preclinical characterization of novel small molecule inhibitors of kinesin KIF18A motor protein with potent activity against chromosomally unstable cancers [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 LB202.

INK4 Tumor Suppressor Proteins Mediate Resistance to CDK4/6 Kinase Inhibitors

Cyclin-dependent kinases 4 and 6 (CDK4/6) represent a major therapeutic vulnerability for breast cancer. The kinases are clinically targeted via ATP competitive inhibitors (CDK4/6i); however, drug resistance commonly emerges over time. To understand CDK4/6i resistance, we surveyed over 1,300 breast cancers and identified several genetic alterations (e.g., FAT1, PTEN, or ARID1A loss) converging on upregulation of CDK6. Mechanistically, we demonstrate CDK6 causes resistance by inducing and binding CDK inhibitor INK4 proteins (e.g., p18^INK4C). In vitro binding and kinase assays together with physical modeling reveal that the p18^INK4C-cyclin D-CDK6 complex occludes CDK4/6i binding while only weakly suppressing ATP binding. Suppression of INK4 expression or its binding to CDK6 restores CDK4/6i sensitivity. To overcome this constraint, we developed bifunctional degraders conjugating palbociclib with E3 ligands. Two resulting lead compounds potently degraded CDK4/6, leading to substantial antitumor effects in vivo, demonstrating the promising therapeutic potential for retargeting CDK4/6 despite CDK4/6i resistance. SIGNIFICANCE: CDK4/6 kinase activation represents a common mechanism by which oncogenic signaling induces proliferation and is potentially targetable by ATP competitive inhibitors. We identify a CDK6-INK4 complex that is resilient to current-generation inhibitors and develop a new strategy for more effective inhibition of CDK4/6 kinases.This article is highlighted in the In This Issue feature, p. 275.

Methionine synthase is essential for cancer cell proliferation in physiological folate environments

Folate metabolism can be an effective target for cancer treatment. However, standard cell culture conditions utilize folic acid, a non-physiological folate source for most tissues. We find that the enzyme that couples folate and methionine metabolic cycles, methionine synthase, is required for cancer cell proliferation and tumour growth when 5-methyl tetrahydrofolate (THF), the major folate found in circulation, is the extracellular folate source. In such physiological conditions, methionine synthase incorporates 5-methyl THF into the folate cycle to maintain intracellular levels of the folates needed for nucleotide production. 5-methyl THF can sustain intracellular folate metabolism in the absence of folic acid. Therefore, cells exposed to 5-methyl THF are more resistant to methotrexate, an antifolate drug that specifically blocks folic acid incorporation into the folate cycle. Together, these data argue that the environmental folate source has a profound effect on folate metabolism, determining how both folate cycle enzymes and antifolate drugs impact proliferation.

Abstract 309: Development of a multi-omic, pooled cancer cell screen for nanoparticle delivery

Background: Nanoparticles (NPs) hold enormous promise for the targeted delivery of therapeutics for cancer, but clinical translation is lacking largely due to limited tumor accumulation. Tumor heterogeneity and NP complexity make it challenging to deconvolute individual factors that contribute to NP-cell interactions. To address this, we developed a competition assay leveraging 500 stably DNA-barcoded adherent cancer cell lines annotated with multi-omic data from the Broad Institute (PRISM cells) to investigate cell association patterns across a library of NPs. We hypothesize that simultaneous screening of hundreds of cancer cell lines will identify factors underlying differential NP-cancer cell interactions.

Methods: We synthesized a library of 40 fluorescently-labeled NPs comprising clinical and experimental formulations. Clinical formulations included liposomal doxorubicin and irinotecan analogs and liposomal or poly(lactide-co-glycolide, PLGA) NPs with and without polyethylene glycol (PEG); these are either FDA-approved or in clinical trials. Experimental formulations included liposomal and PLGA cores electrostatically coated with a range of native and synthetic polymers as well as polystyrene NPs of varying sizes and surface chemistries. Fluorescent antibodies -in free form or NP-conjugated—were included as validation compounds. PRISM cells were pooled and incubated with NPs prior to fluorescence-activated cell sorting (FACS) to bin cells based on strength of NP association. After cell lysis, DNA barcodes were amplified and sequenced. Using appropriate controls to adjust for baseline barcode abundance, we generated an association score for each NP-cell line pair. Next, we performed multi-omic univariate analyses and applied a random forest algorithm to identify factors predictive of NP-cancer cell association.

Results: After pooled screening of PRISM cells, we consistently identified cancer cell lines based on strength of NP-association across technical and biologic replicates. Using antibodies and antibody-conjugated NPs targeting epidermal growth factor receptor (EGFR), we identified EGFR gene and protein expression as highly significant hits, validating our ability to robustly identify relevant biomarkers. Additional hits were evaluated based on strength and direction of association to identify predictive biomarkers by formulation. We also employed k-means clustering to investigate hits across NP formulations, identifying highly interconnected protein association networks that elucidate likely mechanisms of NP-cancer cell association.

Conclusions: We report a new pooled screening platform to investigate factors influencing NP-cancer cell interactions. We validated the screen by identifying known biomarkers, and also identified new predictive biomarkers that may pave the way for more effective nanotherapeutics.

Citation Format: Joelle P. Straehla, Natalie Boehnke, Mustafa Kocak, Melissa Ronan, Hannah Safford, Matthew G. Rees, Jennifer A. Roth, Angela N. Koehler, Paula T. Hammond. Development of a multi-omic, pooled cancer cell screen for nanoparticle delivery [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 309.

Small-Molecule and CRISPR Screening Converge to Reveal Receptor Tyrosine Kinase Dependencies in Pediatric Rhabdoid Tumors

Cancer is often seen as a disease of mutations and chromosomal abnormalities. However, some cancers, including pediatric rhabdoid tumors (RTs), lack recurrent alterations targetable by current drugs and need alternative, informed therapeutic options. To nominate potential targets, we performed a high-throughput small-molecule screen complemented by a genome-scale CRISPR-Cas9 gene-knockout screen in a large number of RT and control cell lines. These approaches converged to reveal several receptor tyrosine kinases (RTKs) as therapeutic targets, with RTK inhibition effective in suppressing RT cell growth in vitro and against a xenograft model in vivo. RT cell lines highly express and activate (phosphorylate) different RTKs, creating dependency without mutation or amplification. Downstream of RTK signaling, we identified PTPN11, encoding the pro-growth signaling protein SHP2, as a shared dependency across all RT cell lines. This study demonstrates that large-scale perturbational screening can uncover vulnerabilities in cancers with "quiet" genomes.

Rhabdoid Tumors Are Sensitive to the Protein-Translation Inhibitor Homoharringtonine

PURPOSE

Rhabdoid tumors are devastating pediatric cancers in need of improved therapies. We sought to identify small molecules that exhibit in vitro and in vivo efficacy against preclinical models of rhabdoid tumor.

EXPERIMENTAL DESIGN

We screened eight rhabdoid tumor cell lines with 481 small molecules and compared their sensitivity with that of 879 other cancer cell lines. Genome-scale CRISPR-Cas9 inactivation screens in rhabdoid tumors were analyzed to confirm target vulnerabilities. Gene expression and CRISPR-Cas9 data were queried across cell lines and primary rhabdoid tumors to discover biomarkers of small-molecule sensitivity. Molecular correlates were validated by manipulating gene expression. Subcutaneous rhabdoid tumor xenografts were treated with the most effective drug to confirm in vitro results.

RESULTS

Small-molecule screening identified the protein-translation inhibitor homoharringtonine (HHT), an FDA-approved treatment for chronic myelogenous leukemia (CML), as the sole drug to which all rhabdoid tumor cell lines were selectively sensitive. Validation studies confirmed the sensitivity of rhabdoid tumor to HHT was comparable with that of CML cell lines. Low expression of the antiapoptotic gene BCL2L1, which encodes Bcl-XL, was the strongest predictor of HHT sensitivity, and HHT treatment consistently depleted Mcl-1, the synthetic-lethal antiapoptotic partner of Bcl-XL. Rhabdoid tumor cell lines and primary-tumor samples expressed low BCL2L1, and overexpression of BCL2L1 induced resistance to HHT in rhabdoid tumor cells. Furthermore, HHT treatment inhibited rhabdoid tumor cell line and patient-derived xenograft growth in vivo.

CONCLUSIONS

Rhabdoid tumor cell lines and xenografts are highly sensitive to HHT, at least partially due to their low expression of BCL2L1. HHT may have therapeutic potential against rhabdoid tumors.

Discovering the anti-cancer potential of non-oncology drugs by systematic viability profiling

Anti-cancer uses of non-oncology drugs have occasionally been found, but such discoveries have been serendipitous. We sought to create a public resource containing the growth inhibitory activity of 4,518 drugs tested across 578 human cancer cell lines. We used PRISM, a molecular barcoding method, to screen drugs against cell lines in pools. An unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines in a manner predictable from the cell lines' molecular features. Our findings include compounds that killed by inducing PDE3A-SLFN12 complex formation; vanadium-containing compounds whose killing depended on the sulfate transporter SLC26A2; the alcohol dependence drug disulfiram, which killed cells with low expression of metallothioneins; and the anti-inflammatory drug tepoxalin, which killed via the multi-drug resistance protein ABCB1. The PRISM drug repurposing resource (https://depmap.org/repurposing) is a starting point to develop new oncology therapeutics, and more rarely, for potential direct clinical translation.

Discovering the anti-cancer potential of non-oncology drugs by systematic viability profiling

Anti-cancer uses of non-oncology drugs have occasionally been found, but such discoveries have been serendipitous. We sought to create a public resource containing the growth inhibitory activity of 4,518 drugs tested across 578 human cancer cell lines. We used PRISM, a molecular barcoding method, to screen drugs against cell lines in pools. An unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines in a manner predictable from the cell lines' molecular features. Our findings include compounds that killed by inducing PDE3A-SLFN12 complex formation; vanadium-containing compounds whose killing depended on the sulfate transporter SLC26A2; the alcohol dependence drug disulfiram, which killed cells with low expression of metallothioneins; and the anti-inflammatory drug tepoxalin, which killed via the multi-drug resistance protein ABCB1. The PRISM drug repurposing resource (https://depmap.org/repurposing) is a starting point to develop new oncology therapeutics, and more rarely, for potential direct clinical translation.

Pooled Genomic Screens Identify Anti-apoptotic Genes as Targetable Mediators of Chemotherapy Resistance in Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is often sensitive to initial treatment with platinum and taxane combination chemotherapy, but most patients relapse with chemotherapy-resistant disease. To systematically identify genes modulating chemotherapy response, we performed pooled functional genomic screens in HGSOC cell lines treated with cisplatin, paclitaxel, or cisplatin plus paclitaxel. Genes in the intrinsic pathway of apoptosis were among the top candidate resistance genes in both gain-of-function and loss-of-function screens. In an open reading frame overexpression screen, followed by a mini-pool secondary screen, anti-apoptotic genes including BCL2L1 (BCL-XL) and BCL2L2 (BCL-W) were associated with chemotherapy resistance. In a CRISPR-Cas9 knockout screen, loss of BCL2L1 decreased cell survival whereas loss of proapoptotic genes promoted resistance. To dissect the role of individual anti-apoptotic proteins in HGSOC chemotherapy response, we evaluated overexpression or inhibition of BCL-2, BCL-XL, BCL-W, and MCL1 in HGSOC cell lines. Overexpression of anti-apoptotic proteins decreased apoptosis and modestly increased cell viability upon cisplatin or paclitaxel treatment. Conversely, specific inhibitors of BCL-XL, MCL1, or BCL-XL/BCL-2, but not BCL-2 alone, enhanced cell death when combined with cisplatin or paclitaxel. Anti-apoptotic protein inhibitors also sensitized HGSOC cells to the poly (ADP-ribose) polymerase inhibitor olaparib. These unbiased screens highlight anti-apoptotic proteins as mediators of chemotherapy resistance in HGSOC, and support inhibition of BCL-XL and MCL1, alone or combined with chemotherapy or targeted agents, in treatment of primary and recurrent HGSOC. IMPLICATIONS: Anti-apoptotic proteins modulate drug resistance in ovarian cancer, and inhibitors of BCL-XL or MCL1 promote cell death in combination with chemotherapy.

Abstract 2867: MDM2 and MDM4 are therapeutic vulnerabilities in malignant rhabdoid tumors

Malignant rhabdoid tumors (MRT) are aggressive cancers of early childhood that are largely resistant to traditional therapies. MRT exhibit a remarkably low mutation rate, with no recurrent mutations beyond the defining biallelic inactivating mutation in SMARCB1, a core subunit of the SWI/SNF (BAF) chromatin-remodeling complex. Thus, MRT do not display traditional oncogenic mutations that are amenable to targeted therapies, limiting their use for this disease. In order to nominate new drug targets for MRT, we screened MRT cell lines with large-scale RNAi, CRISPR-Cas9, and small-molecule libraries. The most significant vulnerabilities consistent across all three screens were MDM2 and MDM4, the major negative regulators of p53. We found that MRT cell lines are more sensitive than other p53 wild-type cancer cell lines to both idasanutlin (MDM2-specific) and ATSP-7041 (MDM2/4-dual) in vitro. Both inhibitors induced substantial activation of the p53 pathway in MRT cell lines, which responded with permanent apoptotic or senescent cell fate decisions. CRISPR-Cas9-mediated inactivation of TP53 caused a significant resistance to these compounds, confirming that on-target mechanisms were responsible for MRT sensitivity. We found that loss of SMARCB1 sensitizes MRT cells to idasanutlin by shifting the p53 response towards apoptosis. In MRT xenograft studies, both idasanutlin and ATSP-7041 slowed tumor growth. Most strikingly, an idasanutlin pulse of only five days was sufficient to induce sizable regression of all tumors, which remained complete and durable in 50% of mice. Finally, gene expression analysis of primary MRT predicts that, like cell lines and xenografts, MRT in patients are likely to be sensitive to MDM2 inhibition. Collectively, these studies describe a genetic link between SWI/SNF complex mutations and p53, while providing evidence to support the use of MDM2 and MDM2/4 inhibitors that have already entered clinical trials for the treatment of this devastating pediatric cancer.

Citation Format: Thomas P. Howard, Taylor E. Arnoff, Melinda R. Song, Andrew O. Giacomelli, Xiaofeng Wang, Andrew L. Hong, Neekesh V. Dharia, Su Wang, Francisca Vazquez, Minh-Tam Pham, Ann M. Morgan, Franziska Wachter, Gregory H. Bird, Guillaume Kugener, Elaine M. Oberlick, Matthew G. Rees, Hong Tiv, Justin H. Hwang, Katherine H. Walsh, April Cook, John M. Krill-Burger, Aviad Tsherniak, Prafulla C. Gokhale, Peter J. Park, Kimberly Stegmaier, Loren D. Walensky, William C. Hahn, Charles W. Roberts. MDM2 and MDM4 are therapeutic vulnerabilities in malignant rhabdoid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2867.

Neuronal differentiation and cell-cycle programs mediate response to BET-bromodomain inhibition in MYC-driven medulloblastoma

BET-bromodomain inhibition (BETi) has shown pre-clinical promise for MYC-amplified medulloblastoma. However, the mechanisms for its action, and ultimately for resistance, have not been fully defined. Here, using a combination of expression profiling, genome-scale CRISPR/Cas9-mediated loss of function and ORF/cDNA driven rescue screens, and cell-based models of spontaneous resistance, we identify bHLH/homeobox transcription factors and cell-cycle regulators as key genes mediating BETi's response and resistance. Cells that acquire drug tolerance exhibit a more neuronally differentiated cell-state and expression of lineage-specific bHLH/homeobox transcription factors. However, they do not terminally differentiate, maintain expression of CCND2, and continue to cycle through S-phase. Moreover, CDK4/CDK6 inhibition delays acquisition of resistance. Therefore, our data provide insights about the mechanisms underlying BETi effects and the appearance of resistance and support the therapeutic use of combined cell-cycle inhibitors with BETi in MYC-amplified medulloblastoma.

MDM2 and MDM4 Are Therapeutic Vulnerabilities in Malignant Rhabdoid Tumors

Malignant rhabdoid tumors (MRT) are highly aggressive pediatric cancers that respond poorly to current therapies. In this study, we screened several MRT cell lines with large-scale RNAi, CRISPR-Cas9, and small-molecule libraries to identify potential drug targets specific for these cancers. We discovered MDM2 and MDM4, the canonical negative regulators of p53, as significant vulnerabilities. Using two compounds currently in clinical development, idasanutlin (MDM2-specific) and ATSP-7041 (MDM2/4-dual), we show that MRT cells were more sensitive than other p53 wild-type cancer cell lines to inhibition of MDM2 alone as well as dual inhibition of MDM2/4. These compounds caused significant upregulation of the p53 pathway in MRT cells, and sensitivity was ablated by CRISPR-Cas9-mediated inactivation of TP53. We show that loss of SMARCB1, a subunit of the SWI/SNF (BAF) complex mutated in nearly all MRTs, sensitized cells to MDM2 and MDM2/4 inhibition by enhancing p53-mediated apoptosis. Both MDM2 and MDM2/4 inhibition slowed MRT xenograft growth in vivo, with a 5-day idasanutlin pulse causing marked regression of all xenografts, including durable complete responses in 50% of mice. Together, these studies identify a genetic connection between mutations in the SWI/SNF chromatin-remodeling complex and the tumor suppressor gene TP53 and provide preclinical evidence to support the targeting of MDM2 and MDM4 in this often-fatal pediatric cancer. SIGNIFICANCE: This study identifies two targets, MDM2 and MDM4, as vulnerabilities in a deadly pediatric cancer and provides preclinical evidence that compounds inhibiting these proteins have therapeutic potential.

Computational Analyses Connect Small-Molecule Sensitivity to Cellular Features Using Large Panels of Cancer Cell Lines

We recently pioneered several analyses of small-molecule sensitivity data collected from large-scale perturbation of hundreds of cancer cell lines with hundreds of small molecules, with cell viability measured as a readout of compound sensitivity. We performed these studies using cancer cell lines previously annotated with cellular, genomic, and basal gene-expression features. By combining small-molecule sensitivity data with these other datasets, we identified new candidate biomarkers of sensitivity, gained insights into small-molecule mechanisms of action, and proposed candidate hypotheses for cancer dependencies (including candidate combination therapies). Nevertheless, given the size of these datasets, we expect that many connections between cellular features and small-molecule sensitivity remain underexplored. In this chapter, we provide a step-by-step account of foundational data-analysis methods underlying our published studies, including working MATLAB code applied to our own public datasets. These procedures will allow others to repeat analyses of our data with new parameters, in additional contexts, and to adapt our procedures to their own datasets.

Abstract 954: Predicting synergistic drug combinations and resistance mechanisms from genomic features and single-agent response profiles

Drug combinations promise to improve clinical responses and/or forestall drug resistance. To capitalize on this promise, we need to know which drugs to combine, and which patients to give them to based on the genetic or pathological features of their disease. However, progress towards this goal has been hindered by the infeasibility of performing comprehensive drug-combination studies across thousands of cellular contexts.

We hypothesized that the basal gene-transcription state of cancer cell lines, in concert with the cell-viability profiles of single-agent small molecules, might be leveraged to nominate specific synergistic drug combinations and identify mechanisms of drug resistance, eliminating the need to test all possible drug/drug combinations across cellular models. Specifically, we predicted that inhibiting the protein product of transcripts associated with drug resistance to a given small molecule might induce drug synergy.

To test this notion, we analyzed nearly 400,000 drug-sensitivity profiles in >800 cancer cell lines to identify candidate compound-gene pairs. We identified over 100 examples where outlier expression of a single transcript was correlated with resistance to a small molecule. Of these gene/drug pairs, 9 genes represented imminently druggable targets, including established clinically-relevant relationships between the alkylating agent temozolomide and MGMT expression, and between a subset of chemotherapeutics including paclitaxel and the efflux pump ABCB1.

Inhibition of candidate “co-targets”, which included 3 previously characterized relationships and 6 novel relationships, resulted in cell-line-specific synergistic cell killing across multiple cell-line models. For validated compound-gene pairs, exogenous expression of the “co-target” was sufficient to confer resistance. For example, we found that high expression of MGLL, encoding monoglyceride lipase, was uniquely associated with lack of response to the histone lysine demethylase inhibitor GSK-J4. Endogenous or exogenous MGLL expression conferred resistance to GSK-J4, while MGLL-proficient cell lines could be sensitized to GSK-J4 up to 50-fold by co-treatment with an irreversible MGLL inhibitor.

These initial studies highlight the potential of integrating basal gene expression features with small-molecule response to nominate rational candidates for drug combinations. As public repositories of single agent response data from diverse cellular contexts continue to expand, so too will our repertoire of therapeutic combinations. Moreover, this approach permits the parallel identification of genomic features that indicate which patient populations are most likely to benefit from such combinations.

Citation Format: Matthew G. Rees, Lisa Brenan, Patrick Duggan, Cory M. Johannessen. Predicting synergistic drug combinations and resistance mechanisms from genomic features and single-agent response profiles [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 954.

Abstract A18: Predicting synergistic drug combinations from genomic features and single-agent response profiles

Drug combinations promise to improve clinical responses and/or forestall drug resistance. To capitalize on this promise, we need to know which drugs to combine, and whom to give them to based on the genetic or pathological features of their disease. However, accomplishing this goal has been precluded by the infeasibility of performing comprehensive drug-combination studies across thousands of cellular contexts. We hypothesized that the basal gene-transcription state of cancer cell lines, in concert with the response profiles of hundreds of single-agent small molecules, might be leveraged to nominate synergistic drug combinations, eliminating the need to test all possible drug/drug combinations across cellular models. Specifically, we predicted that inhibiting the protein product of transcripts associated with drug resistance to a given small molecule might induce drug synergy. To test this notion, we analyzed public cell-line drug-sensitivity data to identify candidate compound-gene pairs. We identified 7 examples in which outlier expression of a druggable candidate protein was associated with lack of single-agent response. Inhibition of 6/7 candidate co-targets resulted in cell-line-specific synergistic cell killing across multiple cell line models, validating the overall approach. For example, consistent with clinical findings, we found that high expression of the MGMT gene, encoding O-6-methylguanine-DNA methyltransferase, was uniquely associated with response to alkylating agents such as temozolomide, and that combination of the MGMT inhibitor O-6-benzylguanine with temozolomide resulted in synergistic killing. These initial studies highlight the potential of integrating basal gene expression features with small-molecule response to nominate rational candidates for drug combinations. As public repositories of single-agent response data from diverse cellular contexts continue to expand, so too will our repertoire of therapeutic combinations. Moreover, this approach permits the parallel identification of genomic features that indicate which patient populations are most likely to benefit from such combinations.

Citation Format: Matthew G. Rees, Lisa Brenan, Amanda Walker, Cory M. Johannessen. Predicting synergistic drug combinations from genomic features and single-agent response profiles [abstract]. In: Proceedings of the AACR Precision Medicine Series: Opportunities and Challenges of Exploiting Synthetic Lethality in Cancer; Jan 4-7, 2017; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2017;16(10 Suppl):Abstract nr A18.

Dependency of a therapy-resistant state of cancer cells on a lipid peroxidase pathway

Plasticity of the cell state has been proposed to drive resistance to multiple classes of cancer therapies, thereby limiting their effectiveness. A high-mesenchymal cell state observed in human tumours and cancer cell lines has been associated with resistance to multiple treatment modalities across diverse cancer lineages, but the mechanistic underpinning for this state has remained incompletely understood. Here we molecularly characterize this therapy-resistant high-mesenchymal cell state in human cancer cell lines and organoids and show that it depends on a druggable lipid-peroxidase pathway that protects against ferroptosis, a non-apoptotic form of cell death induced by the build-up of toxic lipid peroxides. We show that this cell state is characterized by activity of enzymes that promote the synthesis of polyunsaturated lipids. These lipids are the substrates for lipid peroxidation by lipoxygenase enzymes. This lipid metabolism creates a dependency on pathways converging on the phospholipid glutathione peroxidase (GPX4), a selenocysteine-containing enzyme that dissipates lipid peroxides and thereby prevents the iron-mediated reactions of peroxides that induce ferroptotic cell death. Dependency on GPX4 was found to exist across diverse therapy-resistant states characterized by high expression of ZEB1, including epithelial-mesenchymal transition in epithelial-derived carcinomas, TGFβ-mediated therapy-resistance in melanoma, treatment-induced neuroendocrine transdifferentiation in prostate cancer, and sarcomas, which are fixed in a mesenchymal state owing to their cells of origin. We identify vulnerability to ferroptic cell death induced by inhibition of a lipid peroxidase pathway as a feature of therapy-resistant cancer cells across diverse mesenchymal cell-state contexts.

DiSCoVERing Innovative Therapies for Rare Tumors: Combining Genetically Accurate Disease Models with In Silico Analysis to Identify Novel Therapeutic Targets

PURPOSE

We used human stem and progenitor cells to develop a genetically accurate novel model of MYC-driven Group 3 medulloblastoma. We also developed a new informatics method, Disease-model Signature versus Compound-Variety Enriched Response ("DiSCoVER"), to identify novel therapeutics that target this specific disease subtype.

EXPERIMENTAL DESIGN

Human neural stem and progenitor cells derived from the cerebellar anlage were transduced with oncogenic elements associated with aggressive medulloblastoma. An in silico analysis method for screening drug sensitivity databases (DiSCoVER) was used in multiple drug sensitivity datasets. We validated the top hits from this analysis in vitro and in vivo

RESULTS

Human neural stem and progenitor cells transformed with c-MYC, dominant-negative p53, constitutively active AKT and hTERT formed tumors in mice that recapitulated Group 3 medulloblastoma in terms of pathology and expression profile. DiSCoVER analysis predicted that aggressive MYC-driven Group 3 medulloblastoma would be sensitive to cyclin-dependent kinase (CDK) inhibitors. The CDK 4/6 inhibitor palbociclib decreased proliferation, increased apoptosis, and significantly extended the survival of mice with orthotopic medulloblastoma xenografts.

CONCLUSIONS

We present a new method to generate genetically accurate models of rare tumors, and a companion computational methodology to find therapeutic interventions that target them. We validated our human neural stem cell model of MYC-driven Group 3 medulloblastoma and showed that CDK 4/6 inhibitors are active against this subgroup. Our results suggest that palbociclib is a potential effective treatment for poor prognosis MYC-driven Group 3 medulloblastoma tumors in carefully selected patients. Clin Cancer Res; 22(15); 3903-14. ©2016 AACR.

Correlating chemical sensitivity and basal gene expression reveals mechanism of action

Changes in cellular gene expression in response to small-molecule or genetic perturbations have yielded signatures that can connect unknown mechanisms of action (MoA) to ones previously established. We hypothesized that differential basal gene expression could be correlated with patterns of small-molecule sensitivity across many cell lines to illuminate the actions of compounds whose MoA are unknown. To test this idea, we correlated the sensitivity patterns of 481 compounds with ∼19,000 basal transcript levels across 823 different human cancer cell lines and identified selective outlier transcripts. This process yielded many novel mechanistic insights, including the identification of activation mechanisms, cellular transporters and direct protein targets. We found that ML239, originally identified in a phenotypic screen for selective cytotoxicity in breast cancer stem-like cells, most likely acts through activation of fatty acid desaturase 2 (FADS2). These data and analytical tools are available to the research community through the Cancer Therapeutics Response Portal.

Abstract C136: Identification of selective cancer cytotoxic modulators of phosphodiesterase 3a 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 identify 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 demonstrate 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 sensitivity to DNMDP. Our results implicate PDE3A modulators as candidate cancer therapeutic agents and demonstrate the power of predictive chemogenomics in small-molecule discovery.

Citation Format: Lucian de Waal, Timothy A. Lewis, Matthew G. Rees, Aviad Tsherniak, Xiaoyun Wu, Peter S. Choi, Lara Gechijian, Christina Hartigan, Patrick W. Faloon, Mark J. Hickey, Nicola Tolliday, Steven A. Carr, Paul A. Clemons, Benito Munoz, Bridget K. Wagner, Alykhan F. Shamji, Angela N. Koehler, Monica Schenone, Alex B. Burgin, Stuart L. Schreiber, Heidi Greulich, Matthew Meyerson. Identification of selective cancer cytotoxic modulators of phosphodiesterase 3a by predictive chemogenomics. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr C136.

Harnessing Connectivity in a Large-Scale Small-Molecule Sensitivity Dataset

Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset. This analysis reveals insights into small-molecule mechanisms of action, and genomic features that associate with CCL response to small-molecule treatment. We are able to recapitulate known relationships between FDA-approved therapies and cancer dependencies and to uncover new relationships, including for KRAS-mutant cancers and neuroblastoma. To enable the cancer community to explore these data, and to generate novel hypotheses, we created an updated version of the Cancer Therapeutic Response Portal (CTRP v2).

SIGNIFICANCE

We present the largest CCL sensitivity dataset yet available, and an analysis method integrating information from multiple CCLs and multiple small molecules to identify CCL response predictors robustly. We updated the CTRP to enable the cancer research community to leverage these data and analyses.

Discovery of a Small-Molecule Probe for V-ATPase Function

Lysosomes perform a critical cellular function as a site of degradation for diverse cargoes including proteins, organelles, and pathogens delivered through distinct pathways, and defects in lysosomal function have been implicated in a number of diseases. Recent studies have elucidated roles for the lysosome in the regulation of protein synthesis, metabolism, membrane integrity, and other processes involved in homeostasis. Complex small-molecule natural products have greatly contributed to the investigation of lysosomal function in cellular physiology. Here we report the discovery of a novel, small-molecule modulator of lysosomal acidification derived from diversity-oriented synthesis through high-content screening.

Glucokinase regulatory protein: complexity at the crossroads of triglyceride and glucose metabolism

PURPOSE OF REVIEW

Glucokinase regulator (GCKR) encodes glucokinase regulatory protein (GKRP), a hepatocyte-specific inhibitor of the glucose-metabolizing enzyme glucokinase (GCK). Genome-wide association studies have identified a common coding variant within GCKR associated with multiple metabolic traits. This review focuses on recent insights into the critical role of GKRP in hepatic glucose metabolism that have stemmed from the study of human genetics. This knowledge has improved our understanding of glucose and lipid physiology and informed the development of targeted molecular therapeutics for diabetes.

RECENT FINDINGS

Rare GCKR variants have effects on GKRP expression, localization, and activity. These variants are collectively associated with hypertriglyceridaemia but are not causal. Crystal structures of GKRP and the GCK-GKRP complex have been solved, providing greater insight into the molecular interactions between these proteins. Finally, small molecules have been identified that directly bind GKRP and reduce blood glucose levels in rodent models of diabetes.

SUMMARY

GCKR variants across the allelic spectrum have effects on glucose and lipid homeostasis. Functional analysis has highlighted numerous molecular mechanisms for GKRP dysfunction. Hepatocyte-specific GCK activation via small molecule GKRP inhibition may be a new avenue for type 2 diabetes treatment, particularly considering evidence indicating GKRP loss-of-function alone does not cause hypertriglyceridaemia.

NAMPT is the cellular target of STF-31-like small-molecule probes

The small-molecule probes STF-31 and its analogue compound 146 were discovered while searching for compounds that kill VHL-deficient renal cell carcinoma cell lines selectively and have been reported to act via direct inhibition of the glucose transporter GLUT1. We profiled the sensitivity of 679 cancer cell lines to STF-31 and found that the pattern of response is tightly correlated with sensitivity to three different inhibitors of nicotinamide phosphoribosyltransferase (NAMPT). We also performed whole-exome next-generation sequencing of compound 146-resistant HCT116 clones and identified a recurrent NAMPT-H191R mutation. Ectopic expression of NAMPT-H191R conferred resistance to both STF-31 and compound 146 in cell lines. We further demonstrated that both STF-31 and compound 146 inhibit the enzymatic activity of NAMPT in a biochemical assay in vitro. Together, our cancer-cell profiling and genomic approaches identify NAMPT inhibition as a critical mechanism by which STF-31-like compounds inhibit cancer cells.

Inheritance of rare functional GCKR variants and their contribution to triglyceride levels in families

Significant resources have been invested in sequencing studies to investigate the role of rare variants in complex disease etiology. However, the diagnostic interpretation of individual rare variants remains a major challenge, and may require accurate variant functional classification and the collection of large numbers of variant carriers. Utilizing sequence data from 458 individuals with hypertriglyceridemia and 333 controls with normal plasma triglyceride levels, we investigated these issues using GCKR, encoding glucokinase regulatory protein. Eighteen rare non-synonymous GCKR variants identified in these 791 individuals were comprehensively characterized by a range of biochemical and cell biological assays, including a novel high-throughput-screening-based approach capable of measuring all variant proteins simultaneously. Functionally deleterious variants were collectively associated with hypertriglyceridemia, but a range of in silico prediction algorithms showed little consistency between algorithms and poor agreement with functional data. We extended our study by obtaining sequence data on family members; however, functional variants did not co-segregate with triglyceride levels. Therefore, despite evidence for their collective functional and clinical relevance, our results emphasize the low predictive value of rare GCKR variants in individuals and the complex heritability of lipid traits.