Quantitative analysis of nucleoside transporter and metabolism gene expression in chronic lymphocytic leukemia (CLL): identification of fludarabine-sensitive and -insensitive populations
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Bibliographic record
Abstract
Resistance to fludarabine is observed in the clinic, and molecular predictive assays for benefit from chemotherapy are required. Our objective was to determine if expression of nucleoside transport and metabolism genes was associated with response to fludarabine therapy in patients with chronic lymphocytic leukemia (CLL). CLL cells from 56 patients were collected prior to treatment with fludarabine. Quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) was performed on sample RNA to determine the relative levels of mRNA of 3 nucleoside transporters that mediate fludarabine uptake (human equilibrative nucleoside transporter 1 [hENT1], human equilibrative nucleoside transporter 2 [hENT2], and human concentrative nucleoside transporter 3 [hCNT3]), deoxycytidine kinase (dCK), and 3 5'-nucleotidases (ecto-5'nucleotidase [CD73], deoxynucleotidase-1 [dNT-1], and cytoplasmic high-Km 5-nucleotidase [CN-II]). Two-dimensional hierarchical cluster analysis of gene expression identified 2 distinct populations of CLL. Cluster 2 patients experienced a 3.4-fold higher risk of disease progression than cluster 1 patients (P = .0058, log-rank analysis). Furthermore, independent analysis of the individual genes of interest revealed statistically significant differences for risk of disease progression (adjusted hazard ratios [HRs]) with underexpression of dNT-1 (HR = 0.45; P = .042), CD73 (HR = 0.40; P = .022), and dCK (HR = 0.0.48; P = .035), and overexpression of hCNT3 (HR = 4.7; P = .0007) genes. Subjects with elevated hCNT3 expression experienced a lower complete response rate to fludarabine therapy (11% vs 69%; P = .002). No hCNT3-mediated plasma membrane nucleoside transport was detected in CLL samples expressing hCNT3 message, and hCNT3 protein was localized to the cytoplasm with immunohistochemical and confocal microscopy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it