PDGFRβ promotes oncogenic progression via STAT3/STAT5 hyperactivation in anaplastic large 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
Abstract Background Anaplastic large cell lymphoma (ALCL) is an aggressive non-Hodgkin T cell lymphoma commonly driven by NPM-ALK. AP-1 transcription factors, cJUN and JUNb, act as downstream effectors of NPM-ALK and transcriptionally regulate PDGFRβ. Blocking PDGFRβ kinase activity with imatinib effectively reduces tumor burden and prolongs survival, although the downstream molecular mechanisms remain elusive. Methods and results In a transgenic mouse model that mimics PDGFRβ-driven human ALCL in vivo, we identify PDGFRβ as a driver of aggressive tumor growth. Mechanistically, PDGFRβ induces the pro-survival factor Bcl-x L and the growth-enhancing cytokine IL-10 via STAT5 activation. CRISPR/Cas9 deletion of both STAT5 gene products, STAT5A and STAT5B, results in the significant impairment of cell viability compared to deletion of STAT5A, STAT5B or STAT3 alone. Moreover, combined blockade of STAT3/5 activity with a selective SH2 domain inhibitor, AC-4-130, effectively obstructs tumor development in vivo. Conclusions We therefore propose PDGFRβ as a novel biomarker and introduce PDGFRβ-STAT3/5 signaling as an important axis in aggressive ALCL. Furthermore, we suggest that inhibition of PDGFRβ or STAT3/5 improve existing therapies for both previously untreated and relapsed/refractory ALK + ALCL patients.
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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 | 0.000 | 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 it