Exploiting the fibroblast growth factor receptor-1 vulnerability to therapeutically restrict the MYC-EZH2-CDKN1C axis-driven proliferation in Mantle cell lymphoma
Bibliographic record
Abstract
Mantle cell lymphoma (MCL) is a lethal hematological malignancy with a median survival of 4 years. Its lethality is mainly attributed to a limited understanding of clinical tumor progression and resistance to current therapeutic regimes. Intrinsic, prolonged drug treatment and tumor-microenvironment (TME) facilitated factors impart pro-tumorigenic and drug-insensitivity properties to MCL cells. Hence, elucidating neoteric pharmacotherapeutic molecular targets involved in MCL progression utilizing a global "unified" analysis for improved disease prevention is an earnest need. Using integrated transcriptomic analyses in MCL patients, we identified a Fibroblast Growth Factor Receptor-1 (FGFR1), and analyses of MCL patient samples showed that high FGFR1 expression was associated with shorter overall survival in MCL patient cohorts. Functional studies using pharmacological intervention and loss of function identify a novel MYC-EZH2-CDKN1C axis-driven proliferation in MCL. Further, pharmacological targeting with erdafitinib, a selective small molecule targeting FGFRs, induced cell-cycle arrest and cell death in-vitro, inhibited tumor progression, and improved overall survival in-vivo. We performed extensive pre-clinical assessments in multiple in-vivo model systems to confirm the therapeutic potential of erdafitinib in MCL and demonstrated FGFR1 as a viable therapeutic target in MCL.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".