Diurnal proteomics and biomarker discovery in indolent versus aggressive chronic lymphocytic leukemia patients.

Abstract

10622 Background: In rodents, 10-20% of the genome has a 24-hour (h) rhythm in RNA expression. A molecular clock consisting of transcription / translation feedback loops of clock-genes controls this rhythmicity. In a microarray study (Affymetrix HG_U133_Plus2 chip) on RNA extracted from CLL cells sampled every 4 hours over 24 hours (6 samples) from 3 male (M) and 6 female (F) patients (pts) with chronic lymphocytic leukemia (CLL) we found 15,094 and 13,415 rhythmic transcripts (Cosinor analysis) in M and F respectively, only 6,629 of which were common to both M and F. We hypothesized that these gender differences in rhythmic RNA expression might have clinical implication for biomarker discovery with some important biomarkers only found at a certain times of day and with gender differences. Methods: Sampling was performed again at 6 time points in M and F CLL patients with indolent CLL (10pts, 5 M, 5F) and aggressive CLL (10 pts, 5M, 5F). An 8-plex iTRAQ kit was employed for mass spectrometry (MS) based relative quantification. Each iTRAQ block comprised all time-points for a single patient including a universal control. Results: At least 300 proteins were identified at a 95% confidence level in each iTRAQ experiment. Of these, 74 proteins displayed significant change between aggressive and indolent pts in 24-hour average or single time point normalized expression based on a non-parametric U-test (p<0.05). The JTK_CYCLE algorithm was used to detect 24-hour rhythmic patterns in the proteomic datasets. Significant rhythmic expression was found for 44 proteins (p<0.10) identified by iTRAQ. Data for each time point were independently analyzed using an in-house Butterfly clustering algorithm based on discrete dynamical systems. The 4 PM time point was found to be optimal for stratifying aggressive and indolent disease. Cellular pathways with significant association to differentially expressed proteins included PPAR signaling, fatty acid metabolism, and granzyme-A signaling. Confirmation by selected reaction monitoring (SRM) MS is ongoing. Conclusions: Rhythmic protein expression may have clinical implications for biomarker discovery.