Transcriptome profiling of whole blood cells identifies PLEK2 and C1QB in human melanoma.

BACKGROUND: Developing analytical methodologies to identify biomarkers in easily accessible body fluids is highly valuable for the early diagnosis and management of cancer patients. Peripheral whole blood is a "nucleic acid-rich" and "inflammatory cell-rich" information reservoir and represents systemic processes altered by the presence of cancer cells. METHODOLOGY/PRINCIPAL FINDINGS: We conducted transcriptome profiling of whole blood cells from melanoma patients. To overcome challenges associated with blood-based transcriptome analysis, we used a PAXgene™ tube and NuGEN Ovation™ globin reduction system. The combined use of these systems in microarray resulted in the identification of 78 unique genes differentially expressed in the blood of melanoma patients. Of these, 68 genes were further analyzed by quantitative reverse transcriptase PCR using blood samples from 45 newly diagnosed melanoma patients (stage I to IV) and 50 healthy control individuals. Thirty-nine genes were verified to be differentially expressed in blood samples from melanoma patients. A stepwise logit analysis selected eighteen 2-gene signatures that distinguish melanoma from healthy controls. Of these, a 2-gene signature consisting of PLEK2 and C1QB led to the best result that correctly classified 93.3% melanoma patients and 90% healthy controls. Both genes were upregulated in blood samples of melanoma patients from all stages. Further analysis using blood fractionation showed that CD45(-) and CD45(+) populations were responsible for the altered expression levels of PLEK2 and C1QB, respectively. CONCLUSIONS/SIGNIFICANCE: The current study provides the first analysis of whole blood-based transcriptome biomarkers for malignant melanoma. The expression of PLEK2, the strongest gene to classify melanoma patients, in CD45(-) subsets illustrates the importance of analyzing whole blood cells for biomarker studies. The study suggests that transcriptome profiling of blood cells could be used for both early detection of melanoma and monitoring of patients for residual disease.

Limited dynamic range of immune response gene expression observed in healthy blood donors using RT-PCR.

The use of quantitative gene expression analysis for the diagnosis, prognosis, and monitoring of disease requires the ability to distinguish pathophysiological changes from natural variations. To characterize these variations in apparently healthy subjects, quantitative real-time PCR was used to measure various immune response genes in whole blood collected from blood bank donors. In a single-time-point study of 131 donors, of 48 target genes, 43 were consistently expressed and 34 followed approximately log-normal distribution. Most transcripts showed a limited dynamic range of expression across subjects. Specifically, 36 genes had standard deviations (SDs) of 0.44 to 0.79 cycle threshold (C(T)) units, corresponding to less than a 3-fold variation in expression. Separately, a longitudinal study of 8 healthy individuals demonstrated a total dynamic range (> 2 standard error units) of 2- to 4-fold in most genes. In contrast, a study of whole blood gene expression in 6 volunteers injected with LPS showed 15 genes changing in expression 10- to 90-fold within 2 to 5 h and returning to within normal range within 21 hours. This work demonstrates that (1) the dynamic range of expression of many immune response genes is limited among healthy subjects; (2) expression levels for most genes analyzed are approximately log-normally distributed; and (3) individuals exposed to an infusion of bacterial endotoxin (lipopolysaccharide), show gene expression profiles that can be readily distinguished from those of a healthy population. These results suggest that normal reference ranges can be established for gene expression assays, providing critical standards for the diagnosis and management of disease.

Mice lacking tissue plasminogen activator and urokinase plasminogen activator genes show attenuated matrix metalloproteases activity after sciatic nerve crush.

Plasminogen activators (PAs), tissue PA (tPA) and urokinase PA (uPA), have been shown to be induced in sensory neurons after sciatic nerve crush. These findings suggested that PAs facilitate peripheral nerve regeneration by digesting adhesive cell contacts and by activation of other proteases, thereby initiating a proteolytic cascade. Both tPA and uPA activate some matrix metalloproteases (MMPs), indirectly via plasminogen activation or directly, such as the uPA activation of MMP-2. In this study, we demonstrated, by using tPA and uPA knockout mice, that a lack of a plasminogen activator affected MMP-9 and MMP-2 activity after crushing of the sciatic nerve. These findings show that the PAs are important for MMP-9 and MMP-2 activity at the crush site.