Inactivation of epithelial sodium ion channel molecules serves as effective diagnostic biomarkers in clear cell renal cell carcinoma

Zheng, Qian; Wang, Yifang; Zhao, Ran; Han, Peipei; Zhao, Jun; Li, Limei; Zhou, Xiaohui; Li, Ping; Mo, Yuchang; Pan, Xinli; Luo, Wenqi; Zhou, Xiaoying

doi:10.1007/s13258-023-01376-8

Cited by 3 publications

(5 citation statements)

References 45 publications

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“…We hypothesize that increased levels of ATP in connection with upregulated ATP exporters might lead to the activation of P2RY receptors that in turn could inhibit the sodium transporter ENaC. Additionally, we see downregulation of ENaC subunits (SCNN1 A,B,D,G ), a phenomenon that is associated with hyponatremia and metastasis in ccRCC 41,42,46 . Additionally, we identified several disease-related factors in spatial transcriptomic data of murine AKI using the modular and flexible LIANA+ CCC framework.…”

Section: Discussionmentioning

confidence: 79%

“…3C) and are known to play a role in kidney physiology [36][37][38] or ccRCC 39 . SCNN1B and SCNN1G are both part of the epithelial sodium transporter ENaC 40 , known markers of ccRCC 41 , and are implicated with sodium wasting in a SCNN1B genetic condition 42 . In line with this, the pathway "aldosterone-regulated sodium reabsorption" is downregulated in the pathway analysis (Fig.…”

Section: Metalinksdb Enables Prior Knowledge Contextualization To Spe...mentioning

confidence: 99%

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MetalinksDB: a flexible and contextualizable resource of metabolite-protein interactions

Farr,

Dimitrov,

Turei

et al. 2023

Preprint

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Interactions between proteins and metabolites are key for cellular function, from the catalytic breakdown of nutrients to signaling. An important case is cell-cell communication, where cellular metabolites are secreted into the microenvironment and initiate a signaling cascade by binding to an intra- or extracellular receptor of another cell. While protein-protein mediated cell-cell communication is routinely inferred from transcriptomic data, for metabolite-protein interactions this is challenging due to the limitations of high-throughput single-cell and spatial metabolomics technologies, together with the absence of comprehensive prior knowledge resources that include metabolites. Here we report MetalinksDB, a comprehensive and flexible database of intercellular metabolite-protein interactions that is a magnitude larger than existing ones. MetalinksDB can be tailored to specific biological contexts such as diseases, pathways, or tissue/cellular locations by querying subsets of interactions using the web interface (https://metalinks.omnipathdb.org/) or the knowledge graph adapters. We showcase the use of MetalinksDB by identifying deregulated processes in renal cancer patients from multi-omics data as well as inferring metabolite-mediated cell-cell communication events driving acute kidney injury from spatial transcriptomic data. We anticipate that MetalinksDB will facilitate the study of metabolite-mediated communication processes.

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Section: Discussionmentioning

confidence: 79%

Section: Metalinksdb Enables Prior Knowledge Contextualization To Spe...mentioning

confidence: 99%

MetalinksDB: a flexible and contextualizable resource of metabolite-protein interactions

Farr,

Dimitrov,

Turei

et al. 2023

Preprint

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show abstract

“…All of these are known to play a role in kidney physiology [ 39–41 ] or ccRCC [ 42 ]. For example, SCNN1B and SCNN1G are both part of the epithelial sodium transporter ENaC [ 43 ], known markers of ccRCC [ 44 ], and are implicated with sodium wasting in a SCNN1B genetic condition [ 45 ]. In line with this, the pathway ‘aldosterone-regulated sodium reabsorption’ was downregulated in the pathway analysis ( Fig.…”

Section: Resultsmentioning

confidence: 99%

“…We hypothesize that increased levels of ATP in connection with upregulated ATP exporters might lead to the activation of P2RY receptors, which in turn could inhibit the sodium transporter ENaC. Additionally, we see downregulation of ENaC subunits (SCNN1 A,B,D,G ), a phenomenon that is associated with hyponatremia and metastasis in ccRCC [ 44 , 45 , 49 ].…”

Section: Discussionmentioning

confidence: 99%

MetalinksDB: a flexible and contextualizable resource of metabolite-protein interactions

Farr,

Dimitrov,

Schmidt

et al. 2024

Briefings in Bioinformatics

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From the catalytic breakdown of nutrients to signaling, interactions between metabolites and proteins play an essential role in cellular function. An important case is cell–cell communication, where metabolites, secreted into the microenvironment, initiate signaling cascades by binding to intra- or extracellular receptors of neighboring cells. Protein–protein cell–cell communication interactions are routinely predicted from transcriptomic data. However, inferring metabolite-mediated intercellular signaling remains challenging, partially due to the limited size of intercellular prior knowledge resources focused on metabolites. Here, we leverage knowledge-graph infrastructure to integrate generalistic metabolite-protein with curated metabolite-receptor resources to create MetalinksDB. MetalinksDB is an order of magnitude larger than existing metabolite-receptor resources and can be tailored to specific biological contexts, such as diseases, pathways, or tissue/cellular locations. We demonstrate MetalinksDB’s utility in identifying deregulated processes in renal cancer using multi-omics bulk data. Furthermore, we infer metabolite-driven intercellular signaling in acute kidney injury using spatial transcriptomics data. MetalinksDB is a comprehensive and customizable database of intercellular metabolite-protein interactions, accessible via a web interface (https://metalinks.omnipathdb.org/) and programmatically as a knowledge graph (https://github.com/biocypher/metalinks). We anticipate that by enabling diverse analyses tailored to specific biological contexts, MetalinksDB will facilitate the discovery of disease-relevant metabolite-mediated intercellular signaling processes.

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“…Renin is released by the glomerular stromal cells and cleaves angiotensinogen to produce angiotensin to regulate blood pressure ( 7 , 8 ). Also, hypertension is an established risk factor for ccRCC development ( 9 ) with renin closely associated with the occurrence and progression of malignant tumours ( 10 - 12 ).…”

Section: Introductionmentioning

confidence: 99%

Multiple databases analyzed the prognosis prediction of renin secretion pathway-related genes in renal clear cell carcinoma and immunotherapy

Li,

Bao,

Xiao

et al. 2024

Transl Cancer Res

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Background Clear cell renal cell carcinoma (ccRCC) is a malignant kidney tumour and its progression is associated with the renin secretion pathway, so this study aimed to develop a prognostic model based on renin secretion pathway-related genes. Methods First, 453 renin secretion pathway-related genes were acquired [|log fold change (FC)| >1.5, false discovery rate (FDR) <0.05] from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The data were combined and further screened for 188 genes associated with ccRCC prognosis (P<0.05) by univariate independent prognostic analysis. These genes were subjected to least absolute shrinkage and selection operator regression to identify potential prognostic genes to construct the prognostic model. The stability of the model was externally validated. Combined risk scores and clinical information were used to create nomograms to accurately reflect patient survival. The model-related genes were further mined for subsequent analysis. Results A prognostic model of six renin secretion pathway genes ( IGFBP3 , PLAUR , CHKB-CPT1B , HOXA13 , CDH13 , and CDC20 ) was developed. Its reliability in predicting disease prognosis was confirmed by survival analysis, receiver operating characteristic (ROC) curve analysis and a risk curve. The nomogram and calibration curve showed good accuracy. The immune-related analyses revealed that the low-risk group would benefit more from immunotherapy. Conclusions The prognostic model of ccRCC based on six renin secretion pathway-related genes can be used to guide the precise treatment of ccRCC patients.

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Inactivation of epithelial sodium ion channel molecules serves as effective diagnostic biomarkers in clear cell renal cell carcinoma

Cited by 3 publications

References 45 publications

MetalinksDB: a flexible and contextualizable resource of metabolite-protein interactions

MetalinksDB: a flexible and contextualizable resource of metabolite-protein interactions

MetalinksDB: a flexible and contextualizable resource of metabolite-protein interactions

Multiple databases analyzed the prognosis prediction of renin secretion pathway-related genes in renal clear cell carcinoma and immunotherapy

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