MicroRNAs regulate key cell survival pathways and mediate chemosensitivity during progression of diffuse large B-cell lymphoma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite better therapeutic options and improved survival of diffuse large B-cell lymphoma (DLBCL), 30-40% of the patients experience relapse or have primary refractory disease with a dismal prognosis. To identify biological correlates for treatment resistance, we profiled microRNAs (miRNAs) of matched primary and relapsed DLBCL by next-generation sequencing. Altogether 492 miRNAs were expressed in the DLBCL samples. Thirteen miRNAs showed significant differential expression between primary and relapse specimen pairs. Integration of the differentially expressed miRNAs with matched mRNA expression profiles identified highly anti-correlated, putative targets, which were significantly enriched in cancer-associated pathways, including phosphatidylinositol (PI)), mitogen-activated protein kinase (MAPK), and B-cell receptor (BCR) signaling. Expression data suggested activation of these pathways during disease progression, and functional analyses validated that miR-370-3p, miR-381-3p, and miR-409-3p downregulate genes on the PI, MAPK, and BCR signaling pathways, and enhance chemosensitivity of DLBCL cells in vitro. High expression of selected target genes, that is, PIP5K1 and IMPA1, was found to be associated with poor survival in two independent cohorts of chemoimmunotherapy-treated patients (n = 92 and n = 233). Taken together, our results demonstrate that differentially expressed miRNAs contribute to disease progression by regulating key cell survival pathways and by mediating chemosensitivity, thus representing potential novel therapeutic targets.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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