Targeting glioblastoma signaling and metabolism with a re-purposed brain-penetrant drug

Bi, Junfeng; Khan, Atif Ali; Tang, Jun; Armando, Aaron M.; Wu, Sihan; Zhang, Wei; Gimple, Ryan C.; Reed, Alex; Jing, Hui; Koga, Tomoyuki; Wong, Ivy Tsz-Lo; Gu, Yuchao; Miki, Soichiro; Yang, Huijun; Prager, Briana C.; Curtis, Ellis J.; Wainwright, Derek A.; Furnari, Frank B.; Rich, Jeremy; Cloughesy, Timothy F.; Kornblum, Harley I.; Quehenberger, Oswald; Rzhetsky, Andrey; Cravatt, Benjamin F.; Mischel, Paul S.

doi:10.1016/j.celrep.2021.109957

Cited by 56 publications

(49 citation statements)

References 82 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Specifically, Jang et al 41 targeted congestive heart failure, myocardial ischemia, and stroke, Ghalwash et al 32 targeted low-density lipoprotein, which is a risk factor for cardiovascular and vascular diseases, Kim et al 26 targeted dyslipidemia, Cai et al 34 targeted cardiovascular disease, Liu et al 33 targeted coronary artery disease, Nordon et al 29 targeted hypertension, and 366 targeted coronary heart disease, congestive heart failure, heart attack, and stroke. In addition, there are four publications targeting at cancer 18 , 19 , 35 , 45 , three targeting at COVID 36 , 46 , 47 , two targeting at asthma 41 , 42 .…”

Section: Resultsmentioning

confidence: 99%

“…Of those that did subset reported drugs, they were typically sub-selected by certain drug types, such as statins, triptans, PPIs, and nasal steroids in one study, α1‐adrenoceptor antagonists in another, and antihypertensive calcium channel blockers in a third. Of the 33 studies reviewed, only five reported results focused on a single drug, metformin in the case of Xu et al 18 , febuxostat in the case of Muraki et al 48 , terbutaline sulfate in the case of Paik et al 27 , Fluoxetine in the case of Bi et al 45 , and Dextromethorphan in the case of Cummings et al 49 . Intuitively, this finding makes sense as most methods are focused on presenting candidates for further screening rather than having a pre-existing drug that should be further studied, and as such methods would result in a selection of candidates that should then be cross-validated against known clinical indications for method validity, rather than a clinical validation of an individual drug itself selected from said list of candidates.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Computational drug repurposing based on electronic health records: a scoping review

et al. 2022

View full text Add to dashboard Cite

Computational drug repurposing methods adapt Artificial intelligence (AI) algorithms for the discovery of new applications of approved or investigational drugs. Among the heterogeneous datasets, electronic health records (EHRs) datasets provide rich longitudinal and pathophysiological data that facilitate the generation and validation of drug repurposing. Here, we present an appraisal of recently published research on computational drug repurposing utilizing the EHR. Thirty-three research articles, retrieved from Embase, Medline, Scopus, and Web of Science between January 2000 and January 2022, were included in the final review. Four themes, (1) publication venue, (2) data types and sources, (3) method for data processing and prediction, and (4) targeted disease, validation, and released tools were presented. The review summarized the contribution of EHR used in drug repurposing as well as revealed that the utilization is hindered by the validation, accessibility, and understanding of EHRs. These findings can support researchers in the utilization of medical data resources and the development of computational methods for drug repurposing.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Computational drug repurposing based on electronic health records: a scoping review

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Metergoline was reported as a GBM stem cell proliferation inhibitor in a high-throughput screen [ 35 ]. The Inhibition of SMPD1, a gene that regulates “ceramide sphingosine-1-phosphate rheostat” and drives tumour growth and immune escape in different types of cancer [ 59 ], through inhibition of epidermal growth factor receptor (EGFR) signalling and via activation of lysosomal stress has been proposed as the potential anti-tumoral effects of serotonin receptor inhibition, through fluoxidine, in GBM [ 60 ]. In preclinical studies, the effect of 5-HTR2B antagonists on angiogenesis was associated with decreased tumour microvessel density [ 61 ].…”

Section: Discussionmentioning

confidence: 99%

Transcription Profile and Pathway Analysis of the Endocannabinoid Receptor Inverse Agonist AM630 in the Core and Infiltrative Boundary of Human Glioblastoma Cells

et al. 2022

View full text Add to dashboard Cite

Background: We have previously reported that the endocannabinoid receptor inverse agonist AM630 is a potent inhibitor of isocitrade dehydrogenase-1 wild-type glioblastoma (GBM) core tumour cell proliferation. To uncover the mechanism behind the anti-tumour effects we have performed a transcriptional analysis of AM630 activity both in the tumour core cells (U87) and the invasive margin cells (GIN-8), the latter representing a better proxy of post-surgical residual disease. Results: The core and invasive margin cells exhibited markedly different gene expression profiles and only the core cells had high expression of a potential AM630 target, the CB1 receptor. Both cell types had moderate expression of the HTR2B serotonin receptor, a reported AM630 target. We found that the AM630 driven transcriptional response was substantially higher in the central cells than in the invasive margin cells, with the former driving the up regulation of immune response and the down regulation of cell cycle and metastatic pathways and correlating with transcriptional responses driven by established anti-neoplastics as well as serotonin receptor antagonists. Conclusion: Our results highlight the different gene sets involved in the core and invasive margin cell lines derived from GBM and an associated marked difference in responsiveness to AM630. Our findings identify AM630 as an anti-neoplastic drug in the context of the core cells, showing a high correlation with the activity of known antiproliferative drugs. However, we reveal a key set of similarities between the two cell lines that may inform therapeutic intervention.

show abstract

“…Another example of drug repurposing was the recent discovery in vitro that the highly CNS penetrant selective serotonin reuptake inhibitor antidepressant fluoxetine could inhibit sphingomyelin phosphodiesterase 1 resulting in dose-dependent GBM cell death through inhibition of EGFR signaling [ 249 ]. Clinical studies are however required to validate these findings in patients with GBM.…”

Section: Current Approach To Newly Diagnosed Gbmmentioning

confidence: 99%

Updates in IDH-Wildtype Glioblastoma

et al. 2022

View full text Add to dashboard Cite

Glioblastoma is the most aggressive primary brain tumor with a poor prognosis. The 2021 WHO CNS5 classification has further stressed the importance of molecular signatures in diagnosis although therapeutic breakthroughs are still lacking. In this review article, updates on the current and novel therapies in IDH-wildtype GBM will be discussed. Supplementary Information The online version contains supplementary material available at 10.1007/s13311-022-01251-6.

show abstract

Targeting glioblastoma signaling and metabolism with a re-purposed brain-penetrant drug

Cited by 56 publications

References 82 publications

Computational drug repurposing based on electronic health records: a scoping review

Computational drug repurposing based on electronic health records: a scoping review

Transcription Profile and Pathway Analysis of the Endocannabinoid Receptor Inverse Agonist AM630 in the Core and Infiltrative Boundary of Human Glioblastoma Cells

Updates in IDH-Wildtype Glioblastoma

Contact Info

Product

Resources

About