Functional exploration of copy number alterations in a Drosophila model of triple-negative breast cancer.

Accounting for 10-20% of breast cancer cases, triple-negative breast cancer (TNBC) is associated with a disproportionate number of breast cancer deaths. One challenge in studying TNBC is its genomic profile: with the exception of TP53 loss, most breast cancer tumors are characterized by a high number of copy number alterations (CNAs), making modeling the disease in whole animals challenging. We computationally analyzed 186 CNA regions previously identified in breast cancer tumors to rank genes within each region by likelihood of acting as a tumor driver. We then used a Drosophila p53-Myc TNBC model to identify 48 genes as functional drivers. To demonstrate the utility of this functional database, we established six 3-hit models; altering candidate genes led to increased aspects of transformation as well as resistance to the chemotherapeutic drug fluorouracil. Our work provides a functional database of CNA-associated TNBC drivers, and a template for an integrated computational/whole-animal approach to identify functional drivers of transformation and drug resistance within CNAs in other tumor types.

Cell competition and cancer from Drosophila to mammals.

Throughout an individual's life, somatic cells acquire cancer-associated mutations. A fraction of these mutations trigger tumour formation, a phenomenon partly driven by the interplay of mutant and wild-type cell clones competing for dominance; conversely, other mutations function against tumour initiation. This mechanism of 'cell competition', can shift clone dynamics by evaluating the relative status of clonal populations, promoting 'winners' and eliminating 'losers'. This review examines the role of cell competition in the context of tumorigenesis, tumour progression and therapeutic intervention.

Existing and Developing Preclinical Models for Neurofibromatosis Type 1-Related Cutaneous Neurofibromas.

Neurofibromatosis type 1 (NF1) is caused by a nonfunctional copy of the NF1 tumor suppressor gene that predisposes patients to the development of cutaneous neurofibromas (cNFs), the skin tumor that is the hallmark of this condition. Innumerable benign cNFs, each appearing by an independent somatic inactivation of the remaining functional NF1 allele, form in nearly all patients with NF1. One of the limitations in developing a treatment for cNFs is an incomplete understanding of the underlying pathophysiology and limitations in experimental modeling. Recent advances in preclinical in vitro and in vivo modeling have substantially enhanced our understanding of cNF biology and created unprecedented opportunities for therapeutic discovery. We discuss the current state of cNF preclinical in vitro and in vivo model systems, including two- and three-dimensional cell cultures, organoids, genetically engineered mice, patient-derived xenografts, and porcine models. We highlight the models' relationship to human cNFs and how they can be used to gain insight into cNF development and therapeutic discovery.

A polycistronic transgene design for combinatorial genetic perturbations from a single transcript in Drosophila.

Experimental models that capture the genetic complexity of human disease and allow mechanistic explorations of the underlying cell, tissue, and organ interactions are crucial to furthering our understanding of disease biology. Such models require combinatorial manipulations of multiple genes, often in more than one tissue at once. The ability to perform complex genetic manipulations in vivo is a key strength of Drosophila, where many tools for sophisticated and orthogonal genetic perturbations exist. However, combining the large number of transgenes required to establish more representative disease models and conducting mechanistic studies in these already complex genetic backgrounds is challenging. Here we present a design that pushes the limits of Drosophila genetics by allowing targeted combinatorial ectopic expression and knockdown of multiple genes from a single inducible transgene. The polycistronic transcript encoded by this transgene includes a synthetic short hairpin cluster cloned within an intron placed at the 5' end of the transcript, followed by two protein-coding sequences separated by the T2A sequence that mediates ribosome skipping. This technology is particularly useful for modeling genetically complex diseases like cancer, which typically involve concurrent activation of multiple oncogenes and loss of multiple tumor suppressors. Furthermore, consolidating multiple genetic perturbations into a single transgene further streamlines the ability to perform combinatorial genetic manipulations and makes it readily adaptable to a broad palette of transgenic systems. This flexible design for combinatorial genetic perturbations will also be a valuable tool for functionally exploring multigenic gene signatures identified from omics studies of human disease and creating humanized Drosophila models to characterize disease-associated variants in human genes. It can also be adapted for studying biological processes underlying normal tissue homeostasis and development that require simultaneous manipulation of many genes.

RAS Signaling Gone Awry in the Skin: The Complex Role of RAS in Cutaneous Neurofibroma Pathogenesis, Emerging Biological Insights.

Cutaneous neurofibromas (cNFs) are the most common tumor in people with the rasopathy neurofibromatosis type 1. They number in hundreds or even thousands throughout the body, and currently, there are no effective interventions to prevent or treat these skin tumors. To facilitate the identification of novel and effective therapies, essential studies including a more refined understanding of cNF biology and the role of RAS signaling and downstream effector pathways responsible for cNF initiation, growth, and maintenance are needed. This review highlights the current state of knowledge of RAS signaling in cNF pathogenesis and therapeutic development for cNF treatment.

Colon Cancer Cells Evade Drug Action by Enhancing Drug Metabolism.

Colorectal cancer (CRC) is the second most deadly cancer worldwide. One key reason is the failure of therapies that target RAS proteins, which represent approximately 40% of CRC cases. Despite the recent discovery of multiple alternative signalling pathways that contribute to resistance, durable therapies remain an unmet need. Here, we use liquid chromatography/mass spectrometry (LC/MS) analyses on Drosophila CRC tumour models to identify multiple metabolites in the glucuronidation pathway-a toxin clearance pathway-as upregulated in trametinib-resistant RAS/APC/P53 ("RAP") tumours compared to trametinib-sensitive RASG12V tumours. Elevating glucuronidation was sufficient to direct trametinib resistance in RASG12V animals while, conversely, inhibiting different steps along the glucuronidation pathway strongly reversed RAP resistance to trametinib. For example, blocking an initial HDAC1-mediated deacetylation step with the FDA-approved drug vorinostat strongly suppressed trametinib resistance in Drosophila RAP tumours. We provide functional evidence that pairing oncogenic RAS with hyperactive WNT activity strongly elevates PI3K/AKT/GLUT signalling, which in turn directs elevated glucose and subsequent glucuronidation. Finally, we show that this mechanism of trametinib resistance is conserved in an KRAS/APC/TP53 mouse CRC tumour organoid model. Our observations demonstrate a key mechanism by which oncogenic RAS/WNT activity promotes increased drug clearance in CRC. The majority of targeted therapies are glucuronidated, and our results provide a specific path towards abrogating this resistance in clinical trials.

WNT Signalling Promotes NF-κB Activation and Drug Resistance in KRAS-Mutant Colorectal Cancer.

Approximately 40% of colorectal cancer (CRC) cases are characterized by KRAS mutations, rendering them insensitive to most CRC therapies. While the reasons for this resistance remain incompletely understood, one key aspect is genetic complexity: in CRC, oncogenic KRAS is most commonly paired with mutations that alter WNT and P53 activities ("RAP"). Here, we demonstrate that elevated WNT activity upregulates canonical (NF-κB) signalling in both Drosophila and human RAS mutant tumours. This upregulation required Toll-1 and Toll-9 and resulted in reduced efficacy of RAS pathway targeted drugs such as the MEK inhibitor trametinib. Inhibiting WNT activity pharmacologically significantly suppressed trametinib resistance in RAP tumours and more genetically complex RAP-containing 'patient avatar' models. WNT/MEK drug inhibitor combinations were further improved by targeting brm, shg, ago, rhoGAPp190 and upf1, highlighting these genes as candidate biomarkers for patients sensitive to this duel approach. These findings shed light on how genetic complexity impacts drug resistance and proposes a therapeutic strategy to reverse this resistance.

Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge.

A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets ('polypharmacology'). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology.

Drosophila RASopathy models identify disease subtype differences and biomarkers of drug efficacy.

RASopathies represent a family of mostly autosomal dominant diseases that are caused by missense variants in the rat sarcoma viral oncogene/mitogen activated protein kinase (RAS/MAPK) pathway including KRAS, NRAS, BRAF, RAF1, and SHP2. These variants are associated with overlapping but distinct phenotypes that affect the heart, craniofacial, skeletal, lymphatic, and nervous systems. Here, we report an analysis of 13 Drosophila transgenic lines, each expressing a different human RASopathy isoform. Similar to their human counterparts, each Drosophila line displayed common aspects but also important differences including distinct signaling pathways such as the Hippo and SAPK/JNK signaling networks. We identified multiple classes of clinically relevant drugs-including statins and histone deacetylase inhibitors-that improved viability across most RASopathy lines; in contrast, several canonical RAS pathway inhibitors proved less broadly effective. Overall, our study compares and contrasts a large number of RASopathy-associated variants including their therapeutic responses.

A Drosophila platform identifies a novel, personalized therapy for a patient with adenoid cystic carcinoma.

Adenoid cystic carcinoma (ACC) is a rare cancer type that originates in the salivary glands. Tumors commonly invade along nerve tracks in the head and neck, making surgery challenging. Follow-up treatments for recurrence or metastasis including chemotherapy and targeted therapies have shown limited efficacy, emphasizing the need for new therapies. Here, we report a Drosophila-based therapeutic approach for a patient with advanced ACC disease. A patient-specific Drosophila transgenic line was developed to model the five major variants associated with the patient's disease. Robotics-based screening identified a three-drug cocktail-vorinostat, pindolol, tofacitinib-that rescued transgene-mediated lethality in the Drosophila patient-specific line. Patient treatment led to a sustained stabilization and a partial metabolic response of 12 months. Subsequent resistance was associated with new genomic amplifications and deletions. Given the lack of options for patients with ACC, our data suggest that this approach may prove useful for identifying novel therapeutic candidates.

Inhibition of kinase IKKß suppresses cellular abnormalities induced by the human papillomavirus oncoprotein HPV 18E6.

Human papillomavirus (HPV) is the leading cause of cervical cancer and has been implicated in several other cancer types including vaginal, vulvar, penile, and oropharyngeal cancers. Despite the recent availability of a vaccine, there are still over 310,000 deaths each year worldwide. Current treatments for HPV-mediated cancers show limited efficacy, and would benefit from improved understanding of disease mechanisms. Recently, we developed a Drosophila 'HPV 18 E6' model that displayed loss of cellular morphology and polarity, junctional disorganization, and degradation of the major E6 target Magi; we further provided evidence that mechanisms underlying HPV E6-induced cellular abnormalities are conserved between humans and flies. Here, we report a functional genetic screen of the Drosophila kinome that identified IKK[Formula: see text]-a regulator of NF-κB-as an enhancer of E6-induced cellular defects. We demonstrate that inhibition of IKK[Formula: see text] reduces Magi degradation and that this effect correlates with hyperphosphorylation of E6. Further, the reduction in IKK[Formula: see text] suppressed the cellular transformation caused by the cooperative action of HPVE6 and the oncogenic Ras. Finally, we demonstrate that the interaction between IKK[Formula: see text] and E6 is conserved in human cells: inhibition of IKK[Formula: see text] blocked the growth of cervical cancer cells, suggesting that IKK[Formula: see text] may serve as a novel therapeutic target for HPV-mediated cancers.

Systemic Regulation of Local Cell Competition.

Somatic scribble mutant cells are selectively eliminated from the growing Drosophila tissue through cell competition, a tumor-suppressing mechanism that ensures tissue integrity. In this issue of Developmental Cell, Sanaki et al. demonstrate that organismal hyperinsulinemia promotes tumorigenesis by abrogating local cell competition.

modEnrichr: a suite of gene set enrichment analysis tools for model organisms.

High-throughput experiments produce increasingly large datasets that are difficult to analyze and integrate. While most data integration approaches focus on aligning metadata, data integration can be achieved by abstracting experimental results into gene sets. Such gene sets can be made available for reuse through gene set enrichment analysis tools such as Enrichr. Enrichr currently only supports gene sets compiled from human and mouse, limiting accessibility for investigators that study other model organisms. modEnrichr is an expansion of Enrichr for four model organisms: fish, fly, worm and yeast. The gene set libraries within FishEnrichr, FlyEnrichr, WormEnrichr and YeastEnrichr are created from the Gene Ontology, mRNA expression profiles, GeneRIF, pathway databases, protein domain databases and other organism-specific resources. Additionally, libraries were created by predicting gene function from RNA-seq co-expression data processed uniformly from the gene expression omnibus for each organism. The modEnrichr suite of tools provides the ability to convert gene lists across species using an ortholog conversion tool that automatically detects the species. For complex analyses, modEnrichr provides API access that enables submitting batch queries. In summary, modEnrichr leverages existing model organism databases and other resources to facilitate comprehensive hypothesis generation through data integration.

Modeling Cancer with Flies and Fish.

Cancer has joined heart disease as the leading source of mortality in the US. In an era of organoids, patient-derived xenografts, and organs on a chip, model organisms continue to thrive with a combination of powerful genetic tools, rapid pace of discovery, and affordability. Model organisms enable the analysis of both the tumor and its associated microenvironment, aspects that are particularly relevant to our understanding of metastasis and drug resistance. In this Perspective, we explore some of the strengths of fruit flies and zebrafish for addressing fundamental cancer questions and how these two organisms can contribute to identifying promising therapeutic candidates.

A personalized platform identifies trametinib plus zoledronate for a patient with KRAS-mutant metastatic colorectal cancer.

Colorectal cancer remains a leading source of cancer mortality worldwide. Initial response is often followed by emergent resistance that is poorly responsive to targeted therapies, reflecting currently undruggable cancer drivers such as KRAS and overall genomic complexity. Here, we report a novel approach to developing a personalized therapy for a patient with treatment-resistant metastatic KRAS-mutant colorectal cancer. An extensive genomic analysis of the tumor's genomic landscape identified nine key drivers. A transgenic model that altered orthologs of these nine genes in the Drosophila hindgut was developed; a robotics-based screen using this platform identified trametinib plus zoledronate as a candidate treatment combination. Treating the patient led to a significant response: Target and nontarget lesions displayed a strong partial response and remained stable for 11 months. By addressing a disease's genomic complexity, this personalized approach may provide an alternative treatment option for recalcitrant disease such as KRAS-mutant colorectal cancer.

Integrated computational and Drosophila cancer model platform captures previously unappreciated chemicals perturbing a kinase network.

Drosophila provides an inexpensive and quantitative platform for measuring whole animal drug response. A complementary approach is virtual screening, where chemical libraries can be efficiently screened against protein target(s). Here, we present a unique discovery platform integrating structure-based modeling with Drosophila biology and organic synthesis. We demonstrate this platform by developing chemicals targeting a Drosophila model of Medullary Thyroid Cancer (MTC) characterized by a transformation network activated by oncogenic dRetM955T. Structural models for kinases relevant to MTC were generated for virtual screening to identify unique preliminary hits that suppressed dRetM955T-induced transformation. We then combined features from our hits with those of known inhibitors to create a 'hybrid' molecule with improved suppression of dRetM955T transformation. Our platform provides a framework to efficiently explore novel kinase inhibitors outside of explored inhibitor chemical space that are effective in inhibiting cancer networks while minimizing whole body toxicity.

Restraining Network Response to Targeted Cancer Therapies Improves Efficacy and Reduces Cellular Resistance.

A key tool of cancer therapy has been targeted inhibition of oncogene-addicted pathways. However, efficacy has been limited by progressive emergence of resistance as transformed cells adapt. Here, we use Drosophila to dissect response to targeted therapies. Treatment with a range of kinase inhibitors led to hyperactivation of overall cellular networks, resulting in emergent resistance and expression of stem cell markers, including Sox2. Genetic and drug screens revealed that inhibitors of histone deacetylases, proteasome, and Hsp90 family of proteins restrained this network hyperactivation. These "network brake" cocktails, used as adjuncts, prevented emergent resistance and promoted cell death at subtherapeutic doses. Our results highlight a general response of cells, transformed and normal, to targeted therapies that leads to resistance and toxicity. Pairing targeted therapeutics with subtherapeutic doses of broad-acting "network brake" drugs may provide a means of extending therapeutic utility while reducing whole body toxicity.Significance: These findings with a strong therapeutic potential provide an innovative approach of identifying effective combination treatments for cancer. Cancer Res; 78(15); 4344-59. ©2018 AACR.

Non-mammalian models of multiple endocrine neoplasia type 2.

Twenty-five years ago, RET was identified as the primary driver of multiple endocrine neoplasia type 2 (MEN2) syndrome. MEN2 is characterized by several transformation events including pheochromocytoma, parathyroid adenoma and, especially penetrant, medullary thyroid carcinoma (MTC). Overall, MTC is a rare but aggressive type of thyroid cancer for which no effective treatment currently exists. Surgery, radiation, radioisotope treatment and chemotherapeutics have all shown limited success, and none of these approaches have proven durable in advanced disease. Non-mammalian models that incorporate the oncogenic RET isoforms associated with MEN2 and other RET-associated diseases have been useful in delineating mechanisms underlying disease progression. These models have also identified novel targeted therapies as single agents and as combinations. These studies highlight the importance of modeling disease in the context of the whole animal, accounting for the complex interplay between tumor and normal cells in controlling disease progression as well as response to therapy. With convenient access to whole genome sequencing data from expanded thyroid cancer patient cohorts, non-mammalian models will become more complex, sophisticated and continue to complement future mammalian studies. In this review, we explore the contributions of non-mammalian models to our understanding of thyroid cancer including MTC, with a focus on Danio rerio and Drosophila melanogaster (fish and fly) models.