Diurnal proteomics and biomarker discovery in indolent versus aggressive chronic lymphocytic leukemia patients.
Bibliographic record
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".