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Sensitive detection of viral transcripts in human tumor transcriptomes.
- Source :
-
PLoS computational biology [PLoS Comput Biol] 2013; Vol. 9 (10), pp. e1003228. Date of Electronic Publication: 2013 Oct 03. - Publication Year :
- 2013
-
Abstract
- In excess of 12% of human cancer incidents have a viral cofactor. Epidemiological studies of idiopathic human cancers indicate that additional tumor viruses remain to be discovered. Recent advances in sequencing technology have enabled systematic screenings of human tumor transcriptomes for viral transcripts. However, technical problems such as low abundances of viral transcripts in large volumes of sequencing data, viral sequence divergence, and homology between viral and human factors significantly confound identification of tumor viruses. We have developed a novel computational approach for detecting viral transcripts in human cancers that takes the aforementioned confounding factors into account and is applicable to a wide variety of viruses and tumors. We apply the approach to conducting the first systematic search for viruses in neuroblastoma, the most common cancer in infancy. The diverse clinical progression of this disease as well as related epidemiological and virological findings are highly suggestive of a pathogenic cofactor. However, a viral etiology of neuroblastoma is currently contested. We mapped 14 transcriptomes of neuroblastoma as well as positive and negative controls to the human and all known viral genomes in order to detect both known and unknown viruses. Analysis of controls, comparisons with related methods, and statistical estimates demonstrate the high sensitivity of our approach. Detailed investigation of putative viral transcripts within neuroblastoma samples did not provide evidence for the existence of any known human viruses. Likewise, de-novo assembly and analysis of chimeric transcripts did not result in expression signatures associated with novel human pathogens. While confounding factors such as sample dilution or viral clearance in progressed tumors may mask viral cofactors in the data, in principle, this is rendered less likely by the high sensitivity of our approach and the number of biological replicates analyzed. Therefore, our results suggest that frequent viral cofactors of metastatic neuroblastoma are unlikely.
- Subjects :
- Cell Line, Tumor
High-Throughput Nucleotide Sequencing methods
Humans
Neoplasms metabolism
Neuroblastoma
Phylogeny
RNA analysis
RNA classification
RNA genetics
RNA, Viral analysis
RNA, Viral genetics
Sequence Analysis, RNA methods
Sequence Homology, Nucleic Acid
Viruses genetics
Viruses metabolism
Computational Biology methods
Neoplasms genetics
Neoplasms virology
Transcriptome genetics
Viruses isolation & purification
Subjects
Details
- Language :
- English
- ISSN :
- 1553-7358
- Volume :
- 9
- Issue :
- 10
- Database :
- MEDLINE
- Journal :
- PLoS computational biology
- Publication Type :
- Academic Journal
- Accession number :
- 24098097
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1003228