Epidemiology of Renal Cell Carcinoma: 2022 Update

Bukavina, Laura; Bensalah, Karim; Bray, Freddie; Carlo, Maria I.; Challacombe, Ben; Karam, Jose A.; Kassouf, Wassim; Mitchell, Thomas J.; Montironi, Rodolfo; O’Brien, Tim; Panebianco, Valeria; Scélo, Ghislaine; Shuch, Brian; Poppel, Hein Van; Blosser, Christopher D.; Psutka, Sarah P.

doi:10.1016/j.eururo.2022.08.019

Cited by 244 publications

(162 citation statements)

References 132 publications

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“…Men have a 2-fold higher incidence of kidney cancer than women. Smoking, obesity, and high blood pressure are deemed as the main risk factors of kidney cancer, all of which are avoidable to reduce the risk of developing kidney cancer [ 3 ]. Renal cell carcinoma (RCC) represents over 80% of all kidney tumors and possesses several subtypes with unique characteristics, such as clear cell (ccRCC), papillary (pRCC), and chromophobe (chRCC), among which ccRCC is the most common subtype and accounts for 70% of all RCC cases [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Identification of Differentially Methylated Genes Associated with Clear Cell Renal Cell Carcinoma and Their Prognostic Values

Wan

Yang

Zhang

2023

Journal of Environmental and Public Health

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Objective. Renal cell carcinoma (RCC) is a heterogeneous disease comprising histologically defined subtypes among which clear cell RCC (ccRCC) accounts for 70% of all RCC cases. DNA methylation constitutes a main part of the molecular mechanism of cancer evolution and prognosis. In this study, we aim to identify differentially methylated genes related to ccRCC and their prognostic values. Methods. The GSE168845 dataset was downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between ccRCC tissues and paired tumor-free kidney tissues. DEGs were submitted to public databases for functional and pathway enrichment analysis, protein-protein interaction (PPI) analysis, promoter methylation analysis, and survival correlation analysis. Results. In the setting of |log2FC| ≥ 2 and adjusted p value <0.05 during differential expression analysis of the GSE168845 dataset, 1659 DEGs between ccRCC tissues and paired tumor-free kidney tissues were sorted out. The most enriched pathways were “T cell activation” and “cytokine-cytokine receptor interaction.” After PPI analysis, 22 hub genes related to ccRCC stood out, among which CD4, PTPRC, ITGB2, TYROBP, BIRC5, and ITGAM exhibited higher methylation levels, and BUB1B, CENPF, KIF2C, and MELK exhibited lower methylation levels in ccRCC tissues compared with paired tumor-free kidney tissues. Among these differentially methylated genes, TYROBP, BIRC5, BUB1B, CENPF, and MELK were significantly correlated with the survival of ccRCC patients ( p < 0.001 ). Conclusion. Our study indicates the DNA methylation of TYROBP, BIRC5, BUB1B, CENPF, and MELK may be promising results for the prognosis of ccRCC.

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Section: Introductionmentioning

confidence: 99%

Identification of Differentially Methylated Genes Associated with Clear Cell Renal Cell Carcinoma and Their Prognostic Values

Wan

Yang

Zhang

2023

Journal of Environmental and Public Health

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“…Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cancer that is associated with different risk factors like smoking, obesity, high blood pressure, germline, somatic mutations, etc. that predispose patients to ccRCC development [3]. Patients with localized RCC receiving treatments like radiofrequency ablation, enucleoresection or simple nephrectomy have improved disease-free survival rates up to 90% [4,5], while the treatment methods for advanced and metastatic ccRCC are still limited.…”

Section: P R E P R I N Tmentioning

confidence: 99%

A novel seven-immune-genes-based model to improve prognosis prediction of clear cell renal cell carcinoma

Chen

Guo

et al. 2022

Arch Med Sci

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IntroductionThe aim of our study is to investigate the correlation of immune-related genes with clear cell renal cell carcinoma (ccRCC) prognosis and the role of immune-related genes in tumor immune microenvironment (TIME) and to build a new prognostic model and prognostic scoring system for renal cancer.Material and methodsWe downloaded the mRNA expression data of 610 samples (538 ccRCC and 72 normal tissues) from TCGA database and constructed a immune-related prognostic model using Cox regression analysis and LASSO analysis. Then we internally verified the scientific validity and accuracy of the model using Kaplan-Meier (KM) analysis and receiver operating characteristic (ROC) curves. Subsequently, Cytoscape was used to construct a TF-miRNA-mRNA network. The "CIBERSORT" package was used to perform the immune-infiltration analysis. Finally, validation of key gene expression was performed by immunohistochemistry (IHC) and quantitative reverse transcription-PCR (qRT-PCR).ResultsThe prognostic model constructed for ccRCC includes 7 genes (KLRC2, PGLYRP2, AGER, CHGA, AVPR1B, IL20RB, LAT). And it was proven to have good prognostic performance through the KM analysis and the ROC curves. We also constructed an accurate prognostic predictive scoring system by establishing a nomogram. Furthermore, the TF-miRNA-mRNA network revealed the potential mechanism of the model and the immune infiltration analysis revealed a correlation between this model and TIME.ConclusionsThe results suggest that the newly developed 7 immune-related genes model can be a practical and reliable prognostic tool for ccRCC. It also shows T cell infiltration characteristics in TIME can therefore be used as an immune biomarker for the diagnosis and treatment of ccRCC.

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“… 4 The incidence of kidney cancer varies widely geographically, and it was relatively higher in Europe and North America. 5 Multiple factors influence the occurrence and progression of kidney cancer, including age, 6 gender, 7 inherited genetic factors (such as Birt–Hogg–Dube syndrome 8 and hereditary leiomyomatosis and renal cell carcinoma 9 ), lifestyle (such as smoking, 10 excess body weight 11 and hypertension 12 ) and so on. The incidence rate of kidney cancer in China was about 4.99/100 000 and the mortality-to-incidence ratio was 0.37.…”

Section: Introductionmentioning

confidence: 99%

Epidemiological Trends of Kidney Cancer Along with Attributable Risk Factors in China from 1990 to 2019 and Its Projections Until 2030: An Analysis of the Global Burden of Disease Study 2019

Xu¹,

Zhang²,

Xia³

et al. 2023

CLEP

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Background Understanding the past and future burden of kidney cancer in China over years provides essential references for optimizing the prevention and management strategies. Methods The data on incidence, mortality, disability-adjusted life-years (DALYs) and age-standardized rates of kidney cancer in China, 1990–2019, were collected from the database of Global Burden of Disease Study 2019. The estimated annual percentage change (EAPC) was calculated to depict the trends of kidney cancer burden, and Bayesian age-period-cohort analysis was used to predict the incidence and mortality in the next decade. Results Over the past 30 years, the number of new kidney cancer cases sharply increased from 11.07 thousand to 59.83 thousand, and the age-standardized incidence rate (ASIR) tripled from 1.16/100,000 to 3.21/100,000. The mortality and DALYs also presented an increasing pattern. Smoking and high body mass index were mainly risk factors for kidney cancer. We predicted that by 2030, the incident cases and deaths of kidney cancer would increase to 126.8 thousand and 41.8 thousand, respectively. Conclusion In the past 30 years, the kidney cancer burden gradually increased in China, and it will continue to rise in the next decade, which reveals more targeted intervention measures are necessary.

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Epidemiology of Renal Cell Carcinoma: 2022 Update

Cited by 244 publications

References 132 publications

Identification of Differentially Methylated Genes Associated with Clear Cell Renal Cell Carcinoma and Their Prognostic Values

Identification of Differentially Methylated Genes Associated with Clear Cell Renal Cell Carcinoma and Their Prognostic Values

A novel seven-immune-genes-based model to improve prognosis prediction of clear cell renal cell carcinoma

Epidemiological Trends of Kidney Cancer Along with Attributable Risk Factors in China from 1990 to 2019 and Its Projections Until 2030: An Analysis of the Global Burden of Disease Study 2019

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