Prediction of drug candidates for clear cell renal cell carcinoma using a systems biology-based drug repositioning approach

Li, Xiangyu; Shong, Ko Eun; Kim, Woonghee; Yuan, Meng; Yang, Hong; Sato, Yusuke; Kume, Haruki; Ogawa, Seishi; Türkez, Hasan; Shoaie, Saeed; Borén, Jan; Nielsen, Jens; Uhlén, Mathias; Zhang, Cheng Cheng; Mardinoğlu, Adil

doi:10.1016/j.ebiom.2022.103963

Cited by 17 publications

(8 citation statements)

References 69 publications

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“…In our proposed drug repositioning method, we hypothesize that a drug has an inhibitory effect on a target gene if the drug treatment led to expressional changes highly positively correlated to expressional changes caused by the knockdown of this target gene [ 13 ]. We screened for drugs targeting GLS as explained in Methods.…”

Section: Resultsmentioning

confidence: 99%

“…In this method, a drug is considered to be useful if it can potentially reverse the disease-induced gene expression dysregulation [ 1 , 12 ]. This approach has been successful in drug discovery studies in clear cell renal carcinoma, liver cancer, SARS-COV-2, and AD [ 13 – 16 ]. However, a drug repurposed in this way usually has multiple gene targets mixed by disease driver and passenger genes, limiting the identification and validation of mechanisms of drug effect.…”

Section: Introductionmentioning

confidence: 99%

“…In this study, to identify the therapeutic gene targets, we referred to our preliminary systems biology study, where genetic and metabolic changes occurring in the AD brain were examined using gene co-expression network (GCN) analysis and genome-scale metabolic modelling [ 17 ]. Then, we applied our previously proposed drug repositioning method which aims to repurpose useful drugs for targeting a specific gene based on the similarity analysis of the perturbations induced by the target gene knockdown and candidate drug treatment on the available human cell lines [ 13 , 18 ]. To our knowledge, drug repositioning studies using perturbagens are targeted to a limited set of drugs on certain cell lines, where the condition occurs; this brings two handicaps: (i) drug repositioning is under-performing due to being restricted on under-studied cell lines, (ii) fewer compounds are screened and restrains the potential solutions for many conditions including the AD [ 19 – 21 ].…”

Section: Introductionmentioning

confidence: 99%

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Drug repositioning targeting glutaminase reveals drug candidates for the treatment of Alzheimer’s disease patients

Bayraktar

Kim

et al. 2023

J Transl Med

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Background Despite numerous clinical trials and decades of endeavour, there is still no effective cure for Alzheimer's disease. Computational drug repositioning approaches may be employed for the development of new treatment strategies for Alzheimer’s patients since an extensive amount of omics data has been generated during pre-clinical and clinical studies. However, targeting the most critical pathophysiological mechanisms and determining drugs with proper pharmacodynamics and good efficacy are equally crucial in drug repurposing and often imbalanced in Alzheimer’s studies. Methods Here, we investigated central co-expressed genes upregulated in Alzheimer’s disease to determine a proper therapeutic target. We backed our reasoning by checking the target gene’s estimated non-essentiality for survival in multiple human tissues. We screened transcriptome profiles of various human cell lines perturbed by drug induction (for 6798 compounds) and gene knockout using data available in the Connectivity Map database. Then, we applied a profile-based drug repositioning approach to discover drugs targeting the target gene based on the correlations between these transcriptome profiles. We evaluated the bioavailability, functional enrichment profiles and drug-protein interactions of these repurposed agents and evidenced their cellular viability and efficacy in glial cell culture by experimental assays and Western blotting. Finally, we evaluated their pharmacokinetics to anticipate to which degree their efficacy can be improved. Results We identified glutaminase as a promising drug target. Glutaminase overexpression may fuel the glutamate excitotoxicity in neurons, leading to mitochondrial dysfunction and other neurodegeneration hallmark processes. The computational drug repurposing revealed eight drugs: mitoxantrone, bortezomib, parbendazole, crizotinib, withaferin-a, SA-25547 and two unstudied compounds. We demonstrated that the proposed drugs could effectively suppress glutaminase and reduce glutamate production in the diseased brain through multiple neurodegeneration-associated mechanisms, including cytoskeleton and proteostasis. We also estimated the human blood–brain barrier permeability of parbendazole and SA-25547 using the SwissADME tool. Conclusions This study method effectively identified an Alzheimer’s disease marker and compounds targeting the marker and interconnected biological processes by use of multiple computational approaches. Our results highlight the importance of synaptic glutamate signalling in Alzheimer’s disease progression. We suggest repurposable drugs (like parbendazole) with well-evidenced activities that we linked to glutamate synthesis hereby and novel molecules (SA-25547) with estimated mechanisms for the treatment of Alzheimer’s patients.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Drug repositioning targeting glutaminase reveals drug candidates for the treatment of Alzheimer’s disease patients

Bayraktar

Kim

et al. 2023

J Transl Med

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“…9 Elevated levels of these TAMs correlate with worse overall survival (OS) and progression-free survival (PFS), suggesting that TAMs could serve as potential biomarkers for prognosis and novel targets for immunotherapy in ccRCC. 10,11 In the context of molecular factors influencing ccRCC, amyloid precursor protein (APP) has emerged as a significant player. APP, historically associated with Alzheimer's disease, has recently been linked to the pathogenesis of various cancers, including ccRCC.…”

Section: Introductionmentioning

confidence: 99%

“…In ccRCC, the prognostic value of TAMs has been particularly noted; high densities of CD68 + TAMs and M2‐polarized TAMs are identified as risk factors for poor prognosis 9 . Elevated levels of these TAMs correlate with worse overall survival (OS) and progression‐free survival (PFS), suggesting that TAMs could serve as potential biomarkers for prognosis and novel targets for immunotherapy in ccRCC 10,11 …”

Section: Introductionmentioning

confidence: 99%

Single‐cell transcriptomic analysis in clear cell renal cell carcinoma: Deciphering the role of APP within the tumour microenvironment

Guan,

Li,

Cui

et al. 2024

J Cellular Molecular Medi

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Clear cell renal cell carcinoma (ccRCC) represents a significant challenge in oncology, primarily due to its resistance to conventional therapies. Understanding the tumour microenvironment (TME) is crucial for developing new treatment strategies. This study focuses on the role of amyloid precursor protein (APP) in tumour‐associated macrophages (TAMs) within the ccRCC TME, exploring its potential as a prognostic biomarker. Basing TAM‐related genes, the prognostic model was important to constructed. Employing advanced single‐cell transcriptomic analysis, this research dissects the TME of ccRCC at an unprecedented cellular resolution. By isolating and examining the gene expression profiles of individual cells, particularly focusing on TAMs, the study investigates the expression levels of APP and their association with the clinical outcomes of ccRCC patients. The analysis reveals a significant correlation between the expression of APP in TAMs and patient prognosis in ccRCC. Patients with higher APP expression in TAMs showed differing clinical outcomes compared to those with lower expression. This finding suggests that APP could serve as a novel prognostic biomarker for ccRCC, providing insights into the disease progression and potential therapeutic targets. This study underscores the importance of single‐cell transcriptomics in understanding the complex dynamics of the TME in ccRCC. The correlation between APP expression in TAMs and patient prognosis highlights APP as a potential prognostic biomarker. However, further research is needed to validate these findings and explore the regulatory mechanisms and therapeutic implications of APP in ccRCC.

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Non-canonical NLRC4 inflammasomes in astrocytes contribute to glioma malignancy

et al. 2023

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Prediction of drug candidates for clear cell renal cell carcinoma using a systems biology-based drug repositioning approach

Cited by 17 publications

References 69 publications

Drug repositioning targeting glutaminase reveals drug candidates for the treatment of Alzheimer’s disease patients

Drug repositioning targeting glutaminase reveals drug candidates for the treatment of Alzheimer’s disease patients

Single‐cell transcriptomic analysis in clear cell renal cell carcinoma: Deciphering the role of APP within the tumour microenvironment

Non-canonical NLRC4 inflammasomes in astrocytes contribute to glioma malignancy

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