Using Low-Density RNA from Blood to Diagnosis CLL

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Clin Chem. 2006 Dec 21; [Epub ahead of print]

Transcriptional Profiling of Hematologic Malignancies with a Low-

Density DNA Microarray.

Alvarez P, Saenz P, Arteta D, ez A, Pocovi M, Simon L, Giraldo

P.

Departamento de Bioquimica y Biologia Molecular y Celular,

Universidad de Zaragoza, Zaragoza, Spain.

BACKGROUND: High-density microarrays are powerful tools for

expression analysis of thousands of genes simultaneously; however,

experience with low-density microarrays in gene expression studies

has been limited.

METHODS: We developed an optimized procedure for gene expression

analysis based on a microarray containing 538 oligonucleotides and

used this procedure to analyze neoplastic cell lines and whole-blood

samples from healthy individuals and patients with different

hematologic neoplasias. Hierarchical clustering and the Welch t-test

with adjusted P values were used for data analysis.

RESULTS: This procedure detects 0.2 fmol of mRNA and generates a

linear response of 2 orders of magnitude, with CV values of <20% for

hybridization and label replicates. We found statistically

significant differences between Jurkat and U937 cell lines, between

blood samples from 15 healthy donors and 59 chronic lymphocytic

leukemia (CLL) samples, and between 6 acute myeloid leukemia

patients and 4 myelodysplastic syndrome patients. A classification

system constructed from the expression data predicted healthy or CLL

status from a whole-blood sample with a 97% success rate.

CONCLUSION: Transcriptional profiling of whole-blood samples was

carried out without any cellular or sample manipulation before RNA

extraction. This gene expression analysis procedure uncovered

statistically significant differences associated with different

hematologic neoplasias and made possible the construction of a

classification system that predicts the healthy or CLL status from a

whole-blood sample.

PMID: 17185367 [PubMed - as supplied by publisher]