Transcriptome-wide signatures of tumor stage in kidney renal clear cell carcinoma: connecting copy number variation, methylation and transcription factor activity

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• 作者：Qi Liu (1) (2)
  Pei-Fang Su (3)
  Shilin Zhao (1)
  Yu Shyr (1) (4) (5) (6)
  
  1. Center for Quantitative Sciences ; Vanderbilt University School of Medicine ; Nashville ; TN ; 37232 ; USA
  2. Department of Biomedical Informatics ; Vanderbilt University School of Medicine ; Nashville ; TN ; 37232 ; USA
  3. Department of Statistics ; National Cheng Kung University ; Tainan ; 70101 ; Taiwan
  4. Department of Cancer Biology ; Vanderbilt University School of Medicine ; Nashville ; TN ; 37232 ; USA
  5. Department of Biostatistics ; Vanderbilt University School of Medicine ; Nashville ; TN ; 37232 ; USA
  6. School of Life Sciences & Biotechnology ; Shanghai Jiao Tong University ; Shanghai ; 200240 ; China
  
• 刊名：Genome Medicine
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：6
• 期：12
• 全文大小：2,836 KB
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• 刊物主题：Human Genetics; Proteomics; Bioinformatics; Internal Medicine;
• 出版者：BioMed Central
• ISSN：1756-994X

文摘

Background Comparative analysis of expression profiles between early and late stage cancers can help to understand cancer progression and metastasis mechanisms and to predict the clinical aggressiveness of cancer. The observed stage-dependent expression changes can be explained by genetic and epigenetic alterations as well as transcription dysregulation. Unlike genetic and epigenetic alterations, however, activity changes of transcription factors, generally occurring at the post-transcriptional or post-translational level, are hard to detect and quantify. Methods Here we developed a statistical framework to infer the activity changes of transcription factors by simultaneously taking into account the contributions of genetic and epigenetic alterations to mRNA expression variations. Results Applied to kidney renal clear cell carcinoma (KIRC), the model underscored the role of methylation as a significant contributor to stage-dependent expression alterations and identified key transcription factors as potential drivers of cancer progression. Conclusions Integrating copy number, methylation, and transcription factor activity signatures to explain stage-dependent expression alterations presented a precise and comprehensive view on the underlying mechanisms during KIRC progression.