The Pan-Cancer analysis of pseudogene expression reveals biologically and clinically relevant tumour subtypes

Although individual pseudogenes have been implicated in tumour biology, the biomedical significance and clinical relevance of pseudogene expression have not been assessed in a systematic way. Here we generate pseudogene expression profiles in 2,808 patient samples of seven cancer types from The Canc...

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Published in:Nature communications 2014-07, Vol.5 (1), p.3963-3963, Article 3963
Main Authors: Han, Leng, Yuan, Yuan, Zheng, Siyuan, Yang, Yang, Li, Jun, Edgerton, Mary E., Diao, Lixia, Xu, Yanxun, Verhaak, Roeland G. W., Liang, Han
Format: Article
Language:English
Subjects:
38/91
631/1647/2017
631/67/68
Biomarkers, Tumor - genetics
Biomarkers, Tumor - metabolism
Gene Expression
Genes, Neoplasm
Humanities and Social Sciences
Humans
multidisciplinary
Neoplasms - classification
Neoplasms - genetics
Neoplasms - metabolism
Pseudogenes
Science
Science (multidisciplinary)
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Summary:Although individual pseudogenes have been implicated in tumour biology, the biomedical significance and clinical relevance of pseudogene expression have not been assessed in a systematic way. Here we generate pseudogene expression profiles in 2,808 patient samples of seven cancer types from The Cancer Genome Atlas RNA-seq data using a newly developed computational pipeline. Supervised analysis reveals a significant number of pseudogenes differentially expressed among established tumour subtypes and pseudogene expression alone can accurately classify the major histological subtypes of endometrial cancer. Across cancer types, the tumour subtypes revealed by pseudogene expression show extensive and strong concordance with the subtypes defined by other molecular data. Strikingly, in kidney cancer, the pseudogene expression subtypes not only significantly correlate with patient survival, but also help stratify patients in combination with clinical variables. Our study highlights the potential of pseudogene expression analysis as a new paradigm for investigating cancer mechanisms and discovering prognostic biomarkers. The contribution of expressed pseudogenes to cancer pathogenesis is unclear. In this study, Han et al. analyse RNA-seq data from The Cancer Genome Atlas and demonstrate the potential of pseudogenes for investigating cancer mechanisms and discovering prognostic biomarkers.
ISSN:2041-1723
2041-1723
DOI:10.1038/ncomms4963