The synergy of BET inhibitors with aurora A kinase inhibitors in MYCN-amplified neuroblastoma is heightened with functional TP53

Yi, Joanna; Sias-Garcia, Oscar; Nasholm, Nicole; Hu, Xiaoyu; Iniguez, Amanda Balboni; Hall, Matthew D.; Davis, Mindy I.; Guha, Rajarshi; Moreno‐Smith, Myrthala; Barbieri, Eveline; Duong, Kevin; Koach, Jessica; Qi, Jun; Bradner, James E.; Stegmaier, Kimberly; Weiss, William A.; Gustafson, W. Clay

doi:10.1016/j.neo.2021.05.003

Cited by 12 publications

(12 citation statements)

References 57 publications

(69 reference statements)

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“…Aurora kinase A ( AURKA ) (also referred to as AIK, STK7 , and PPP1R47 ) is a protein-coding gene that is widely expressed in multiple tissues. High expression of AURKA has been reported in various tumors ( Yan et al, 2016 ; Wu et al, 2018 ; Wang-Bishop et al, 2019 ; Yi et al, 2021 ). Most notably, studies have explored the biological function of AURKA in human cancers, such as diffuse large B-cell lymphoma, glioblastoma, gastric, cervical, colorectal, and liver cancers ( Shen et al, 2019 ; Liu et al, 2021 ; Mesquita et al, 2021 ; Nguyen et al, 2021 ; Wang and Sun, 2021 ; Wu et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Predicting AURKA as a novel therapeutic target for NPC: A comprehensive analysis based on bioinformatics and validation

et al. 2022

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This study comprehensively explored the clinical function of Aurora kinase A (AURKA) gene in nasopharyngeal carcinoma (NPC) and analyzed its potential as a therapeutic target in cancer. Data were downloaded from GEO, STRING, GTEx, and CellMiner databases, and subjected to multiple bioinformatic analyses, including differential expression analysis, WCGNA, gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), miRNA-hub gene regulatory network analysis, immune cell infiltration, and drug sensitivity analysis. In-depth analysis of AURKA gene expression in NPC and its corresponding clinicopathological features was performed to explore its potential as a therapeutic target. Moreover, AURKA gene expression in NPC was validated by qRT-PCR in 21 NPC tissues and 17 normal nasopharyngeal epithelial tissues. AURKA was highly expressed in NPC tissues. Enrichment analysis of AURKA and its co-expressed hub genes indicated their oncogenic role in NPC and their potential involvement in cancer-promoting processes through histone kinase activity and microtubule motility activity, cell cycle, and p53 signaling pathways. AURKA high expression group had greater infiltration of neutrophils, macrophages M2, and dendritic cells resting and less infiltration of T cells CD4+ naïve and T cells γδ. Drug susceptibility analysis found that dacarbazine, R-306465, vorinostat, and other antitumor drugs that act on the cell cycle were closely related to AURKA. qRT-PCR verified the high expression of AURKA in NPC tissues (p < 0.05). We confirmed upregulation of AURKA in NPC tissues. Our results support an oncogenic role of AURKA in the context of NPC, and indicate its potential role as a novel therapeutic target.

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Section: Introductionmentioning

confidence: 99%

Predicting AURKA as a novel therapeutic target for NPC: A comprehensive analysis based on bioinformatics and validation

et al. 2022

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“…Our results also highlighted the association of BET inhibition with AURKA targeting. The therapeutic potential of this combination has been previously shown in neuroblastoma models [58,59]. The synergistic effect has been notably linked to the inhibition of MYCN expression, as also demonstrated in an in vitro GBM study [60].…”

Section: Discussionmentioning

confidence: 83%

Combination drug screen targeting glioblastoma core vulnerabilities reveals pharmacological synergisms

Ariey-Bonnet

Bergès

Montero

et al. 2022

Preprint

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Synergistic drug combinations are an attractive anticancer strategy but prove challenging to identify. Here we present a stepwise approach consisting in revealing core cancer vulnerabilities and exploiting them through drug combination screen to uncover synergistic treatments for glioblastoma patients. Methods: We established an innovative method, based on high-throughput screening, target deconvolution and functional genomics, to reveal core vulnerabilities in glioblastoma. Combination drug screen targeting these vulnerabilities was then designed to unveil synergistic associations. The therapeutic potential of the top drug combination was validated in two different clinically-relevant models: an organotypic ex vivo model and a syngeneic orthotopic mouse model of glioblastoma. Results: Large-scale monotherapy drug screening identified 83 potent anti-glioblastoma compounds. Target deconvolution using public chemoinformatic databases uncovered 1,100 targets and interactors of the hit compounds. Screening of a focused siRNA library targeting the top 292 drug interactors revealed 22 targetable vulnerabilities, 9 of which were confirmed as core glioblastoma vulnerabilities by mining the CRISPR screen cohort data from the online Cancer Dependency Map portal. Six selective inhibitors of the core vulnerabilities were then screened in combination with a custom-made library of 88 compounds and synergies amongst the 528 tested pairwise combinations were predicted. The combinations of CHK1 / MEK and AURKA / BET inhibitors were highlighted and validated in 3D tumor spheroids. Using an organotypic ex vivo model and a syngeneic orthotopic mouse model, we definitively ascertained the efficacy of dual AURKA / BET inhibition in glioblastoma. Conclusions: Collectively, we uncovered that dual inhibition of BET proteins and aurora kinase A is highly synergistic against GBM. Moreover, our study indicates that our approach to exploit drug poly-pharmacology for the rational design of drug combination screens represent a valuable strategy to discover synergistic treatments against refractory cancers.

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“…“Nononcology agents” are drugs approved by the FDA or in clinical trials not explicitly for cancer treatment. These include cardiovascular drugs, antibiotics, antivirals, anti-inflammatory drugs, antipsychotics, and other nononcology drugs ( 55 ) accounted for more than 50% of the total compounds examined (1419 of 2248), and the remaining oncology-focused compounds ( 56 ) with known mechanisms of action (MOAs) belonged to either of the following two classes: targeted oncology compounds (718 of 2248) or chemotherapeutics (111 of 2248) (fig. S7C).…”

Section: Resultsmentioning

confidence: 99%

Pharmacogenomic landscape of head and neck squamous cell carcinoma informs precision oncology therapy

Yao

Yang

et al. 2022

Sci. Transl. Med.

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Head and neck squamous cell carcinoma (HNSCC) is a common and frequently lethal cancer with few therapeutic options. In particular, there are few effective targeted therapies. Development of highly effective therapeutic strategies tailored to patients with HNSCC remains a pressing challenge. To address this, we present a pharmacogenomic study to facilitate precision treatments for patients with HNSCC. We established a large collection of 56 HNSCC patient-derived cells (PDCs), which recapitulated the molecular features of the original tumors. Pharmacological assessment of HNSCCs was conducted using a three-tiered high-throughput drug screening using 2248 compounds across these PDC models and an additional 18 immortalized cell lines. We integrated genomic, transcriptomic, and pharmacological analysis to predict biomarkers, gene-drug associations, and validated biomarkers. These results supported drug repurposing for multiple HNSCC subtypes, including the JAK2 inhibitor fedratinib, for low KRT18 –expressing HNSCC cases, and the topoisomerase inhibitor mitoxantrone, for IL6R -activated HNSCC cases. Our results demonstrated concordance between susceptibility predictions from the PDCs and the matched patients’ responses to standard clinical medication. Moreover, we identified and experimentally confirmed that high expression of ITGB1 elicited therapeutic resistance to docetaxel and high SOD1 expression conferred resistance to afatinib. We further validated ITGB1 as a predictive biomarker for the efficacy of docetaxel therapy in a phase 2 clinical trial. In summary, our study shows that this HNSCC cell resource, as well as the resulting pharmacogenomic profiles, is effective for biomarker discovery and for guiding precision oncology therapies in HNSCCs.

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The synergy of BET inhibitors with aurora A kinase inhibitors in MYCN-amplified neuroblastoma is heightened with functional TP53

Cited by 12 publications

References 57 publications

Predicting AURKA as a novel therapeutic target for NPC: A comprehensive analysis based on bioinformatics and validation

Predicting AURKA as a novel therapeutic target for NPC: A comprehensive analysis based on bioinformatics and validation

Combination drug screen targeting glioblastoma core vulnerabilities reveals pharmacological synergisms

Pharmacogenomic landscape of head and neck squamous cell carcinoma informs precision oncology therapy

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