Synthetic lethal interactions of DEAD/H-box helicases as targets for cancer therapy

DEAD/H-box helicases are implicated in virtually every aspect of RNA metabolism, including transcription, pre-mRNA splicing, ribosomes biogenesis, nuclear export, translation initiation, RNA degradation, and mRNA editing. Most of these helicases are upregulated in various cancers and mutations in some of them are associated with several malignancies. Lately, synthetic lethality (SL) and synthetic dosage lethality (SDL) approaches, where genetic interactions of cancer-related genes are exploited as therapeutic targets, are emerging as a leading area of cancer research. Several DEAD/H-box helicases, including DDX3, DDX9 (Dbp9), DDX10 (Dbp4), DDX11 (ChlR1), and DDX41 (Sacy-1), have been subjected to SL analyses in humans and different model organisms. It remains to be explored whether SDL can be utilized to identity druggable targets in DEAD/H-box helicase overexpressing cancers. In this review, we analyze gene expression data of a subset of DEAD/H-box helicases in multiple cancer types and discuss how their SL/SDL interactions can be used for therapeutic purposes. We also summarize the latest developments in clinical applications, apart from discussing some of the challenges in drug discovery in the context of targeting DEAD/H-box helicases

Epigenetic silencing of CREB3L1 by DNA methylation is associated with high-grade metastatic breast cancers with poor prognosis and is prevalent in triple negative breast cancers

Methylation within specific CpG regions of the CREB3L1 gene in different breast tumor subtypes. The relative methylation was plotted for each tumor subtype. Methylation in regions 2 and 3 show an inverse correlation with CREB3L1 mRNA expression (found in Fig. 6b), whereas methylation in regions 16, 19 and 20 show a direct correlation with CREB3L1 mRNA expression. For all panels: normal (n = 97), luminal (n = 357), human epidermal growth factor receptor 2 (HER2) amplified (n = 19), triple negative breast cancer (TNBC) (n = 113). Statistical differences were analyzed using post-hoc pairwise comparison: *p <0.05; **p <0.01; ***p <0.001. (PDF 97 kb

High-throughput testing in head and neck squamous cell carcinoma identifies agents with preferential activity in human papillomavirus-positive or negative cell lines.

Head and neck squamous cell carcinoma (HNSCC) is a common cancer diagnosis worldwide. Despite advances in treatment, HNSCC has very poor survival outcomes, emphasizing an ongoing need for development of improved therapeutic options. The distinct tumor characteristics of human papillomavirus (HPV)-positive vs. HPV-negative disease necessitate development of treatment strategies tailored to tumor HPV-status. High-throughput robotic screening of 1,433 biologically and pharmacologically relevant compounds at a single dose (4 μM) was carried out against 6 HPV-positive and 20 HPV-negative HNSCC cell lines for preliminary identification of therapeutically relevant compounds. Statistical analysis was further carried out to differentiate compounds with preferential activity against cell lines stratified by the HPV-status. These analyses yielded 57 compounds with higher activity in HPV-negative cell lines, and 34 with higher-activity in HPV-positive ones. Multi-point dose-response curves were generated for six of these compounds (Ryuvidine, MK-1775, SNS-032, Flavopiridol, AZD-7762 and ARP-101), confirming Ryuvidine to have preferential potency against HPV-negative cell lines, and MK-1775 to have preferential potency against HPV-positive cell lines. These data comprise a valuable resource for further investigation of compounds with therapeutic potential in the HNSCC

Repurposing Albendazole: new potential as a chemotherapeutic agent with preferential activity against HPV-negative head and neck squamous cell cancer.

Albendazole is an anti-helminthic drug that has been shown to exhibit anti-cancer properties, however its activity in head and neck squamous cell cancer (HNSCC) was unknown. Using a series of in vitro assays, we assessed the ability of albendazole to inhibit proliferation in 20 HNSCC cell lines across a range of albendazole doses (1 nM-10 μM). Cell lines that responded to treatment were further examined for cell death, inhibition of migration and cell cycle arrest. Thirteen of fourteen human papillomavirus-negative HNSCC cell lines responded to albendazole, with an average IC50 of 152 nM. In contrast, only 3 of 6 human papillomavirus-positive HNSCC cell lines responded. Albendazole treatment resulted in apoptosis, inhibition of cell migration, cell cycle arrest in the G2/M phase and altered tubulin distribution. Normal control cells were not measurably affected by any dose tested. This study indicates that albendazole acts to inhibit the proliferation of human papillomavirus-negative HNSCC cell lines and thus warrants further study as a potential chemotherapeutic agent for patients suffering from head and neck cancer

Integrating high-throughput genetic interaction mapping and high-content screening to explore yeast spindle morphogenesis

A combination of yeast genetics, synthetic genetic array analysis, and high-throughput screening reveals that sumoylation of Mcm21p promotes disassembly of the mitotic spindle

Lestaurtinib is a potent inhibitor of anaplastic thyroid cancer cell line models

Anaplastic thyroid cancer (ATC) is a rare and lethal human malignancy with no known effective therapies in the majority of cases. Despite the use of conventional treatments such as chemotherapy, radiation and surgical resection, this disease remains almost universally fatal. In the present study, we identified the JAK2 inhibitor Lestaurtinib as a potent compound when testing against 13 ATC cell lines. Lestaurtinib demonstrated a potent antiproliferative effect in vitro at nanomolar concentrations. Furthermore, Lestaurtinib impeded cell migration and the ability to form colonies from single cells using scratch-wound and colony formation assays, respectively. Flow cytometry was used for cell cycle analysis following drug treatment and demonstrated arrest at the G2/M phase of the cell cycle, indicative of a cytostatic effect. In vivo studies using the chick chorioallantoic membrane xenograft models demonstrated that treatment with Lestaurtinib resulted in a significant decrease in endpoint tumor volume and vascularity using power Doppler ultrasound imaging. Overall, this study provides evidence that Lestaurtinib is a potent antiproliferative agent with potential antiangiogenic activity that warrants further investigation as a targeted therapy for ATC

Systematic exploration of essential yeast gene function with temperature-sensitive mutants

Conditional temperature-sensitive (ts) mutations are valuable reagents for studying essential genes in the yeast Saccharomyces cerevisiae. We constructed 787 ts strains, covering 497 (~45%) of the 1,101 essential yeast genes, with ~30% of the genes represented by multiple alleles. All of the alleles are integrated into their native genomic locus in the S288C common reference strain and are linked to a kanMX selectable marker, allowing further genetic manipulation by synthetic genetic array (SGA)–based, high-throughput methods. We show two such manipulations: barcoding of 440 strains, which enables chemical-genetic suppression analysis, and the construction of arrays of strains carrying different fluorescent markers of subcellular structure, which enables quantitative analysis of phenotypes using high-content screening. Quantitative analysis of a GFP-tubulin marker identified roles for cohesin and condensin genes in spindle disassembly. This mutant collection should facilitate a wide range of systematic studies aimed at understanding the functions of essential genes

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

MAPPING THE GENETIC LANDSCAPE OF THE EPH RECEPTORS AND THEIR LIGANDS IN HUMAN CANCERS

The abstract of this item is unavailable due to an embargo