Evidence map›Paper›PMID 38794205›Full record

ArticlePharmaceuticals (Basel, Switzerland)2024

Evaluating the Role of Neddylation Modifications in Kidney Renal Clear Cell Carcinoma: An Integrated Approach Using Bioinformatics, MLN4924 Dosing Experiments, and RNA Sequencing.

Dequan Liu, Guangzhen Wu, Shijin Wang, Xu Zheng, Xiangyu Che

Abstract read
In one paragraph

Article in Pharmaceuticals (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Dequan LiuDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, China.ORCID 0009-0003-1242-8792
Guangzhen WuDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, China.
Shijin WangDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, China.ORCID 0009-0006-1140-9858
Xu ZhengDepartment of Cell Biology, College of Basic Medical Science, Dalian Medical University, Dalian 116011, China.
Xiangyu CheDepartment of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian 116011, China.

Funding

the Horizontal Project Department Fund of the First Affiliated Hospital of Dalian Medical University No.2022CR015the Liaoning Provincial Education Department No.JYTMS20230577
6 · The paper itself

Abstract

backgroundNeddylation, a post-translational modification process, plays a crucial role in various human neoplasms. However, its connection with kidney renal clear cell carcinoma (KIRC) remains under-researched.

methodsWe validated the Gene Set Cancer Analysis Lite (GSCALite) platform against The Cancer Genome Atlas (TCGA) database, analyzing 33 cancer types and their link with 17 neddylation-related genes. This included examining copy number variations (CNVs), single nucleotide variations (SNVs), mRNA expression, cellular pathway involvement, and methylation. Using Gene Set Variation Analysis (GSVA), we categorized these genes into three clusters and examined their impact on KIRC patient prognosis, drug responses, immune infiltration, and oncogenic pathways. Afterward, our objective is to identify genes that exhibit overexpression in KIRC and are associated with an adverse prognosis. After pinpointing the specific target gene, we used the specific inhibitor MLN4924 to inhibit the neddylation pathway to conduct RNA sequencing and related in vitro experiments to verify and study the specificity and potential mechanisms related to the target. This approach is geared towards enhancing our understanding of the prognostic importance of neddylation modification in KIRC.

resultsWe identified significant CNV, SNV, and methylation events in neddylation-related genes across various cancers, with notably higher expression levels observed in KIRC. Cluster analysis revealed a potential trade-off in the interactions among neddylation-related genes, where both high and low levels of gene expression are linked to adverse prognoses. This association is particularly pronounced concerning lymph node involvement, T stage classification, and Fustat score. Simultaneously, our research discovered that PSMB10 exhibits overexpression in KIRC when compared to normal tissues, negatively impacting patient prognosis. Through RNA sequencing and in vitro assays, we confirmed that the inhibition of neddylation modification could play a role in the regulation of various signaling pathways, thereby influencing the prognosis of KIRC. Moreover, our results underscore PSMB10 as a viable target for therapeutic intervention in KIRC, opening up novel pathways for the development of targeted treatment strategies.

conclusionThis study underscores the regulatory function and potential mechanism of neddylation modification on the phenotype of KIRC, identifying PSMB10 as a key regulatory target with a significant role in influencing the prognosis of KIRC.

Indexed as

GSVAkidney renal clear cell carcinomaMLN4924neddylationPSMB10RNA sequencing

Identifiers

PMID38794205
PMCPMC11125012

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.