Identification of microbial DNA in human cancer View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2009-12

AUTHORS

Christopher G Duncan, Rebecca J Leary, Jimmy Cheng-Ho Lin, Jordan Cummins, Chunhui Di, Carl F Schaefer, Tian-Li Wang, Gregory J Riggins, Jennifer Edwards, Darell Bigner, Levy Kopelovich, Bert Vogelstein, Kenneth W Kinzler, Victor E Velculescu, Hai Yan

ABSTRACT

BACKGROUND: Microorganisms have been associated with many types of human diseases; however, a significant number of clinically important microbial pathogens remain to be discovered. METHODS: We have developed a genome-wide approach, called Digital Karyotyping Microbe Identification (DK-MICROBE), to identify genomic DNA of bacteria and viruses in human disease tissues. This method involves the generation of an experimental DNA tag library through Digital Karyotyping (DK) followed by analysis of the tag sequences for the presence of microbial DNA content using a compiled microbial DNA virtual tag library. RESULTS: To validate this technology and to identify pathogens that may be associated with human cancer pathogenesis, we used DK-MICROBE to determine the presence of microbial DNA in 58 human tumor samples, including brain, ovarian, and colorectal cancers. We detected DNA from Human herpesvirus 6 (HHV-6) in a DK library of a colorectal cancer liver metastasis and in normal tissue from the same patient. CONCLUSION: DK-MICROBE can identify previously unknown infectious agents in human tumors, and is now available for further applications for the identification of pathogen DNA in human cancer and other diseases. More... »

PAGES

22

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1755-8794-2-22

DOI

http://dx.doi.org/10.1186/1755-8794-2-22

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1002204711

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/19426505


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/1755-8794-2-22'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/1755-8794-2-22'

Turtle is a human-readable linked data format.

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RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/1755-8794-2-22'


 

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