Literature DB >> 26831665

DNA methylation status defines clinicopathological parameters including survival for patients with clear cell renal cell carcinoma (ccRCC).

Emma Andersson Evelönn1, Sofie Degerman1, Linda Köhn1, Mattias Landfors1,2, Börje Ljungberg3, Göran Roos4.   

Abstract

Epigenetic alterations in the methylome have been associated with tumor development and progression in renal cell carcinoma (RCC). In this study, 45 tumor samples, 12 tumor-free kidney cortex tissues, and 24 peripheral blood samples from patients with clear cell RCC (ccRCC) were analyzed by genome-wide promoter-directed methylation arrays and related to clinicopathological parameters. Unsupervised hierarchical clustering separated the tumors into two distinct methylation groups (clusters A and B), where cluster B had higher average methylation and increased number of hypermethylated CpG sites (CpGs). Furthermore, tumors in cluster B had, compared with cluster A, a larger tumor diameter (p = 0.033), a higher morphologic grade (p < 0.001), a higher tumor-node-metastasis (TNM) stage (p < 0.001), and a worse prognosis (p = 0.005). Higher TNM stage was correlated to an increase in average methylation level (p = 0.003) and number of hypermethylated CpGs (p = 0.003), whereas a number of hypomethylated CpGs were mainly unchanged. However, the predicted age of the tumors based on methylation profile did not correlate with TNM stage, morphological grade, or methylation cluster. Differently methylated (DM) genes (n = 840) in ccRCC samples compared with tumor-free kidney cortex samples were predominantly hypermethylated and a high proportion were identified as polycomb target genes. The DM genes were overrepresented by transcription factors, ligands, and receptors, indicating functional alterations of significance for ccRCC progression. To conclude, increased number of hypermethylated genes was associated with increased TNM stage of the tumors. DNA methylation classification of ccRCC tumor samples at diagnosis can serve as a clinically applicable prognostic marker in ccRCC.

Entities:  

Keywords:  Clear cell renal cell carcinoma; DNA methylation; Polycomb target genes; Predicted age; Survival

Mesh:

Year:  2016        PMID: 26831665     DOI: 10.1007/s13277-016-4893-5

Source DB:  PubMed          Journal:  Tumour Biol        ISSN: 1010-4283


  37 in total

1.  Genome-wide methylation analysis identifies epigenetically inactivated candidate tumour suppressor genes in renal cell carcinoma.

Authors:  M R Morris; C J Ricketts; D Gentle; F McRonald; N Carli; H Khalili; M Brown; T Kishida; M Yao; R E Banks; N Clarke; F Latif; E R Maher
Journal:  Oncogene       Date:  2010-12-06       Impact factor: 9.867

2.  Genetic and epigenetic analysis of von Hippel-Lindau (VHL) gene alterations and relationship with clinical variables in sporadic renal cancer.

Authors:  Rosamonde E Banks; Prasanna Tirukonda; Claire Taylor; Nick Hornigold; Dewi Astuti; Dena Cohen; Eamonn R Maher; Anthea J Stanley; Patricia Harnden; Adrian Joyce; Margaret Knowles; Peter J Selby
Journal:  Cancer Res       Date:  2006-02-15       Impact factor: 12.701

Review 3.  Treatment options for metastatic renal cell carcinoma: a review.

Authors:  Uzma Athar; Teresa C Gentile
Journal:  Can J Urol       Date:  2008-04       Impact factor: 1.344

4.  Genome-wide methylation profiles reveal quantitative views of human aging rates.

Authors:  Gregory Hannum; Justin Guinney; Ling Zhao; Li Zhang; Guy Hughes; SriniVas Sadda; Brandy Klotzle; Marina Bibikova; Jian-Bing Fan; Yuan Gao; Rob Deconde; Menzies Chen; Indika Rajapakse; Stephen Friend; Trey Ideker; Kang Zhang
Journal:  Mol Cell       Date:  2012-11-21       Impact factor: 17.970

5.  Tumour characteristics and surgical treatment of renal cell carcinoma in Sweden 2005-2010: a population-based study from the national Swedish kidney cancer register.

Authors:  Andreas Thorstenson; Martin Bergman; Ann-Helén Scherman-Plogell; Soheila Hosseinnia; Börje Ljungberg; Jan Adolfsson; Sven Lundstam
Journal:  Scand J Urol       Date:  2014-03-25       Impact factor: 1.612

6.  Genome-wide CpG island methylation analysis implicates novel genes in the pathogenesis of renal cell carcinoma.

Authors:  Christopher J Ricketts; Mark R Morris; Dean Gentle; Michael Brown; Naomi Wake; Emma R Woodward; Noel Clarke; Farida Latif; Eamonn R Maher
Journal:  Epigenetics       Date:  2012-03       Impact factor: 4.528

Review 7.  The Polycomb complex PRC2 and its mark in life.

Authors:  Raphaël Margueron; Danny Reinberg
Journal:  Nature       Date:  2011-01-20       Impact factor: 49.962

8.  Identification of candidate tumour suppressor genes frequently methylated in renal cell carcinoma.

Authors:  M R Morris; C Ricketts; D Gentle; M Abdulrahman; N Clarke; M Brown; T Kishida; M Yao; F Latif; E R Maher
Journal:  Oncogene       Date:  2010-02-15       Impact factor: 9.867

9.  Tumor-specific hypermethylation of epigenetic biomarkers, including SFRP1, predicts for poorer survival in patients from the TCGA Kidney Renal Clear Cell Carcinoma (KIRC) project.

Authors:  Christopher J Ricketts; Victoria K Hill; W Marston Linehan
Journal:  PLoS One       Date:  2014-01-15       Impact factor: 3.240

10.  Key pathways and genes controlling the development and progression of clear cell renal cell carcinoma (ccRCC) based on gene set enrichment analysis.

Authors:  Haipeng Huang; Yanyan Tang; Wenwu He; Qi Huang; Jianing Zhong; Zhanbin Yang
Journal:  Int Urol Nephrol       Date:  2013-08-14       Impact factor: 2.370

View more
  7 in total

1.  Renal cell carcinoma: predicting RUNX3 methylation level and its consequences on survival with CT features.

Authors:  Dongzhi Cen; Li Xu; Siwei Zhang; Zhiguang Chen; Yan Huang; Ziqi Li; Bo Liang
Journal:  Eur Radiol       Date:  2019-03-15       Impact factor: 5.315

Review 2.  The Role of DNA Methylation in Renal Cell Carcinoma.

Authors:  Brittany N Lasseigne; James D Brooks
Journal:  Mol Diagn Ther       Date:  2018-08       Impact factor: 4.074

Review 3.  Combining molecular and imaging metrics in cancer: radiogenomics.

Authors:  Roberto Lo Gullo; Isaac Daimiel; Elizabeth A Morris; Katja Pinker
Journal:  Insights Imaging       Date:  2020-01-03

4.  Combining epigenetic and clinicopathological variables improves specificity in prognostic prediction in clear cell renal cell carcinoma.

Authors:  Emma Andersson-Evelönn; Linda Vidman; David Källberg; Mattias Landfors; Xijia Liu; Börje Ljungberg; Magnus Hultdin; Patrik Rydén; Sofie Degerman
Journal:  J Transl Med       Date:  2020-11-13       Impact factor: 5.531

5.  Identification of DNA methylation signatures associated with poor outcome in lower-risk Stage, Size, Grade and Necrosis (SSIGN) score clear cell renal cell cancer.

Authors:  Louis Y El Khoury; Shuang Fu; Ryan A Hlady; Ryan T Wagner; Liguo Wang; Jeanette E Eckel-Passow; Erik P Castle; Melissa L Stanton; R Houston Thompson; Alexander S Parker; Thai H Ho; Keith D Robertson
Journal:  Clin Epigenetics       Date:  2021-01-18       Impact factor: 6.551

6.  MRI-Based Grading of Clear Cell Renal Cell Carcinoma Using a Machine Learning Classifier.

Authors:  Xin-Yuan Chen; Yu Zhang; Yu-Xing Chen; Zi-Qiang Huang; Xiao-Yue Xia; Yi-Xin Yan; Mo-Ping Xu; Wen Chen; Xian-Long Wang; Qun-Lin Chen
Journal:  Front Oncol       Date:  2021-10-01       Impact factor: 6.244

7.  DNA methylation of Hugl-2 is a prognostic biomarker in kidney renal clear cell carcinoma.

Authors:  Yi Miao; Fang Cao; Pingping Li; Peijun Liu
Journal:  Clin Exp Pharmacol Physiol       Date:  2020-08-05       Impact factor: 2.557

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.