Sample processing obscures cancer-specific alterations in leukemic transcriptomes.

Proc Natl Acad Sci U S A 2014 Nov 10;111(47):16802-7. Epub 2014 Nov 10.

Computational Biology Program, Public Health Sciences Division, Basic Sciences Division, and

Substantial effort is currently devoted to identifying cancer-associated alterations using genomics. Here, we show that standard blood collection procedures rapidly change the transcriptional and posttranscriptional landscapes of hematopoietic cells, resulting in biased activation of specific biological pathways; up-regulation of pseudogenes, antisense RNAs, and unannotated coding isoforms; and RNA surveillance inhibition. Affected genes include common mutational targets and thousands of other genes participating in processes such as chromatin modification, RNA splicing, T- and B-cell activation, and NF-κB signaling. The majority of published leukemic transcriptomes exhibit signals of this incubation-induced dysregulation, explaining up to 40% of differences in gene expression and alternative splicing between leukemias and reference normal transcriptomes. The effects of sample processing are particularly evident in pan-cancer analyses. We provide biomarkers that detect prolonged incubation of individual samples and show that keeping blood on ice markedly reduces changes to the transcriptome. In addition to highlighting the potentially confounding effects of technical artifacts in cancer genomics data, our study emphasizes the need to survey the diversity of normal as well as neoplastic cells when characterizing tumors.

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http://dx.doi.org/10.1073/pnas.1413374111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4250124PMC
November 2014
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References

(Supplied by CrossRef)
Stabilization of mRNA expression in whole blood samples
Rainen et al.
Clin Chem 2002

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