Class prediction models of thrombocytosis using genetic biomarkers.

Criteria for distinguishing among etiologies of thrombocytosis are limited in their capacity to delineate clonal (essential thrombocythemia [ET]) from nonclonal (reactive thrombocytosis [RT]) etiologies. We studied platelet transcript profiles of 126 subjects (48 controls, 38 RT, 40 ET [24 contained the JAK2V(617)F mutation]) to identify transcript subsets that segregated phenotypes. Cross-platform consistency was validated using quantitative real-time polymerase chain reaction (RT-PCR). Class prediction algorithms were developed to assign phenotypic class between the thrombocytosis cohorts, and by JAK2 genotype. Sex differences were rare in normal and ET cohorts (< 1% of genes) but were male-skewed for approximately 3% of RT genes. An 11-biomarker gene subset using the microarray data discriminated among the 3 cohorts with 86.3% accuracy, with 93.6% accuracy in 2-way class prediction (ET vs RT). Subsequent quantitative RT-PCR analysis established that these biomarkers were 87.1% accurate in prospective classification of a new cohort. A 4-biomarker gene subset predicted JAK2 wild-type ET in more than 85% patient samples using either microarray or RT-PCR profiling, with lower predictive capacity in JAK2V(617)F mutant ET patients. These results establish that distinct genetic biomarker subsets can predict thrombocytosis class using routine phlebotomy.

Platelet genetic biomarker quantification: comparison of fluorescent microspheres and PCR platforms.

The platelet transcriptome has been extensively characterised using distinct genetic profiling platforms, with evolving evidence for differential expression patterns between healthy individuals and subject cohorts with various haematologic and cardiovascular disorders. Traditional technological platforms for platelet genetic biomarker quantification have limited applicability for clinical molecular diagnostics due to inherent complexities related to RNA isolation and analysis. We have previously established the feasibility of fluorescent microspheres as a simple and reproducible strategy for simultaneous quantification of platelet mRNAs from small volume of blood using intact platelets. We now extend these observations by formally comparing in a 50-member normal cohort the cross-platform behaviour of fluorescent microspheres to the currently accepted Q-PCR standard, using a clinically relevant 15-biomarker gene subset able to discriminate among normal and thrombocytosis cohorts. When compared to Q-PCR, genetic biomarker quantification using fluorescent microspheres demonstrated lower coefficients of variation for low-abundant transcripts, better linearity in serially diluted samples, and good overall between-platform consistency via the geometric mean regression. Neither platform demonstrated age or gender effects for any of the 15 biomarkers studied. Binding site saturation for highly abundant transcripts using fluorescent microspheres can be readily eliminated using an optimal platelet number corresponding to 0.3 ml of peripheral blood, additionally applicable to thrombocytopenic cohorts. These data provide a detailed cross-platform analysis using a relevant biomarker subset, further highlighting the applicability of fluorescent microspheres as potentially superior to Q-PCR for platelet mRNA diagnostics.