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Transcriptome Profiling of the Cancer, Adjacent Non-Tumor and Distant Normal Tissues from a Colorectal Cancer Patient by Deep Sequencing

Overview of attention for article published in PLOS ONE, August 2012
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Title
Transcriptome Profiling of the Cancer, Adjacent Non-Tumor and Distant Normal Tissues from a Colorectal Cancer Patient by Deep Sequencing
Published in
PLOS ONE, August 2012
DOI 10.1371/journal.pone.0041001
Pubmed ID
Authors

Yan'an Wu, Xuetao Wang, Fangbo Wu, Ruolei Huang, Fangqin Xue, Guantao Liang, Min Tao, Pengwei Cai, Yi Huang

Abstract

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers in the world. A genome-wide screening of transcriptome dysregulation between cancer and normal tissue would provide insight into the molecular basis of CRC initiation and progression. Compared with microarray technology, which is commonly used to identify transcriptional changes, the recently developed RNA-seq technique has the ability to detect other abnormal regulations in the cancer transcriptome, such as alternative splicing, novel transcripts or gene fusion. In this study, we performed high-throughput transcriptome sequencing at ~50× coverage on CRC, adjacent non-tumor and distant normal tissue. The results revealed cancer-specific, differentially expressed genes and differential alternative splicing, suggesting that the extracellular matrix and metabolic pathways are activated and the genes related to cell homeostasis are suppressed in CRC. In addition, one tumor-restricted gene fusion, PRTEN-NOTCH2, was also detected and experimentally confirmed. This study reveals some common features in tumor invasion and provides a comprehensive survey of the CRC transcriptome, which provides better insight into the complexity of regulatory changes during tumorigenesis.

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Mendeley readers

The data shown below were compiled from readership statistics for 158 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 2 1%
United States 2 1%
Germany 1 <1%
United Kingdom 1 <1%
Malaysia 1 <1%
Spain 1 <1%
China 1 <1%
Unknown 149 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 44 28%
Researcher 32 20%
Student > Master 19 12%
Student > Bachelor 12 8%
Professor 10 6%
Other 24 15%
Unknown 17 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 76 48%
Biochemistry, Genetics and Molecular Biology 32 20%
Medicine and Dentistry 11 7%
Engineering 5 3%
Immunology and Microbiology 4 3%
Other 11 7%
Unknown 19 12%