A 44-gene set constructed for predicting the�prognosis of clear cell renal cell carcinoma

Wang, Yonggang; Wang, Yao; Liu, Feng

doi:10.3892/ijmm.2018.3899

Cited by 12 publications

(13 citation statements)

References 53 publications

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“…CXCL10 is also responsible for reducing the levels of VEGF, fibroblast growth factor and matrix metalloproteinase-9. Higher levels of chemokines bind to CXCR3 in the RCC patients are closely associated with their angiostatic function [ 22 , 23 , 24 , 25 , 26 ]. The significance of CXCL9–11/CXCR3 in renal cell carcinoma is presented in Table 1 .…”

Section: Resultsmentioning

confidence: 99%

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The Role of Chemokine Receptor CXCR3 and Its Ligands in Renal Cell Carcinoma

Gudowska-Sawczuk

Kudelski

Mroczko

2020

IJMS

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The major invasive subtype of kidney cancer is renal cell carcinoma (RCC). The essential components of cancer development are chronic inflammation and neoangiogenesis. It has been suggested that the chemokine ligand 9, -10, –11 (CXCL9–11) and chemokine receptor 3 (CXCR3) chemokines receptor expressed on monocytes, T and NK cells may be involved in the inhibition of angiogenesis. However, to date, little is known about the potential clinical significance of these chemokines and their receptor in renal cell carcinoma. Therefore, in this review, we described the role of CXCR3 and its ligands in pathogenesis of RCC. We performed an extensive search of the current literature in our investigation, using the MEDLINE/PubMed database. The changes of chemokines and their specific receptor in renal cell carcinoma were observed. Published studies revealed an increased expression of CXCR3 and elevated concentration of its ligands in RCC. The association between treatment of RCC and CXCL9–11/CXCR3 concentration and expression was also observed. Moreover, CXCR3 and its ligands levels were related to patient’s prognosis, risk of metastasis and tumor growth. This review describes the potential role of CXCR3 and its ligands in pathogenesis of RCC, as well as their potential immune-therapeutic significance. However, future studies should aim to confirm the clinical and prognostic role of CXCL9–11/CXCR3 in renal cell carcinoma.

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Section: Resultsmentioning

confidence: 99%

“…However, a potential limitations of the study is a relatively small tested group and a lack of previous research studies on this topic. Therefore, the results still require an experimental validation [ 26 ].…”

Section: Resultsmentioning

confidence: 99%

The Role of Chemokine Receptor CXCR3 and Its Ligands in Renal Cell Carcinoma

Gudowska-Sawczuk

Kudelski

Mroczko

2020

IJMS

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“…The Cancer Genome Atlas (TCGA) database ( https://tcga-data.nci.nih.gov/tcga/ ) was used to acquire publicly available messenger RNA (mRNA) profiles and corresponding clinicopathological data from 539 ccRCC tissues and 72 adjacent normal samples, Information recorded included: sex; race; laterality; tumor, node classification, and metastasis classification; tumor, node metastasis (TNM) stage; histologic grade; tumor status; relapse; and vital status. Differentially expressed genes (DEGs) were identified from TCGA database and GEO datasets ( http://www.ncbi.nlm.nih.gov/geo/ ) (including GSE15641 [ 25 ], GSE36895 [ 26 ] and GSE40435 [ 27 ], as well as GSE105261 [ 28 ]) through the “DEseq2” package and via the “Limma” package, respectively. The thresholds were |log2-fold change (FC)| >2.0 and false discovery rate (FDR) <0.01 [ 29 ].…”

Section: Methodsmentioning

confidence: 99%

Overexpression of PKMYT1 Facilitates Tumor Development and Is Correlated with Poor Prognosis in Clear Cell Renal Cell Carcinoma

2020

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Background Protein kinase membrane-associated tyrosine/threonine ( PKMYT1 ) has been found in many tumors, but its association with clear cell renal cell carcinoma (ccRCC) remains unclear. Material/Methods PKMYT1 expression in ccRCC was examined in the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Tumor Immune Estimation Resource databases. The correlation between PKMYT1 expression and clinicopathological parameters was explored via the chi-square test. Receiver operating characteristic curves were used to estimate the diagnostic performance of PKMYT1 . Kaplan-Meier curves, a Cox model, nomogram, time-dependent receiver operating characteristic curves, and decision curve analysis (DCA) were used to evaluate the prognostic value and clinical utility of PKMYT1 . Genes coexpressed with PKMYT1 in ccRCC were identified based on TCGA, the gene expression profiling interactive, and cBioPortal. Gene Set Enrichment Analysis revealed biological pathways associated with PKMYT1 in ccRCC. Results Weighted gene coexpression network analysis identified PKMYT1 as one of the genes most significantly correlated with progression of histological grade. PKMYT1 was significantly upregulated in ccRCC compared with normal tissue (P<0.001), with a trend toward differentiating between individuals with ccRCC and those who were healthy (area under the curve=0.942). High PKMYT1 expression was correlated with unsatisfactory survival (hazard ratio=1.67, P=0.001), indicating that it is a risk factor for ccRCC. A nomogram incorporating PKMYT1 level was created and showed a clinical net benefit. PKMYT1 was strongly positively correlated with the anti-silencing function of 1B histone chaperone ( ASF1B ) gene in ccRCC. Conclusions PKMYT1 is upregulated in ccRCC and its presence indicates poor prognosis, making it a potential therapeutic target for ccRCC.

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“…The polymorphisms of FAM167A-BLK region are linked to susceptibility of autoimmune diseases [ 24 , 25 ]. Low expression of FAM167A is related to longer survival time of ccRCC patients [ 26 ]. FGGY encodes protein FGGY carbohydrate kinase domain containing proteins that phosphorylate carbohydrates [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

A Risk Score Model Based on Nine Differentially Methylated mRNAs for Predicting Prognosis of Patients with Clear Cell Renal Cell Carcinoma

Zhou

Liu

et al. 2021

Disease Markers

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Purpose. DNA methylation alterations play important roles in initiation and progression of clear cell renal cell carcinoma (ccRCC). In this study, we attempted to identify differentially methylated mRNA signatures with prognostic value for ccRCC. Methods. The mRNA methylation and expression profiling data of 306 ccRCC tumors were downloaded from The Cancer Genome Atlas (TCGA) to screen differentially methylated lncRNAs and mRNAs (DMLs and DMMs) between bad and good prognosis patients. Uni- and multivariable Cox regression analyses and LASSO Cox-PH regression analysis were used to select prognostic lncRNAs and mRNAs. Corresponding risk scores were calculated and compared for predictive performance in the training set using Kaplan-Meier OS and ROC curve analyses. The optimal risk score was then identified and validated in the validation set. Function enrichment analysis was conducted. Results. This study screened 461 DMMs and 63 DMLs between good prognosis and bad prognosis patients, and furthermore, nine mRNAs and six lncRNAs were identified as potential prognostic molecules. Compared to nine-mRNA status risk score model, six-lncRNA methylation risk score model, and six-lncRNA status risk score model, the nine-mRNA methylation risk score model showed superiority for prognosis stratification of ccRCC patients in the training set. The prognostic ability of the nine-mRNA methylation risk score model was validated in the validation set. The nine prognostic mRNAs were functionally associated with neuroactive ligand receptor interaction and inflammation-related pathways. Conclusion. The nine-mRNA methylation signature (DMRTA2, DRGX, FAM167A, FGGY, FOXI2, KRTAP2-1, TCTEX1D1, TTBK1, and UBE2QL1) may be a useful prognostic biomarker and tool for ccRCC patients. The present results would be helpful to elucidate the possible pathogenesis of ccRCC.

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A 44-gene set constructed for predicting the�prognosis of clear cell renal cell carcinoma

Cited by 12 publications

References 53 publications

The Role of Chemokine Receptor CXCR3 and Its Ligands in Renal Cell Carcinoma

The Role of Chemokine Receptor CXCR3 and Its Ligands in Renal Cell Carcinoma

Overexpression of PKMYT1 Facilitates Tumor Development and Is Correlated with Poor Prognosis in Clear Cell Renal Cell Carcinoma

A Risk Score Model Based on Nine Differentially Methylated mRNAs for Predicting Prognosis of Patients with Clear Cell Renal Cell Carcinoma

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