DNA Damage Response Deficiency Enhances Neuroblastoma Progression and Sensitivity to Combination PARP and ATR Inhibition
Bibliographic record
Abstract
Abstract Next generation sequencing of neuroblastoma (NB) tumors have revealed frequent somatic and germline genetic alterations in genes encoding proteins involved in DNA damage response (DDR) pathways. Despite being well-studied in many adult cancers, roles for DDR disruption in pediatric solid tumors remains poorly understood. To address this, patient-relevant loss-of-function mutations in DDR pathway components including Brca2, Atm, and Palb2 were incorporated into an established zebrafish MYCN transgenic model (Tg( dbh :EGFP-MYCN)). These mutations were found to enhance NB formation and metastasis in vivo , and result in upregulation of proliferation, cell cycle checkpoint and DNA damage repair transcriptional signatures, revealing potential molecular vulnerabilities in DDR-deficient NB. Zebrafish DDR-deficient NB and human NB cells with DDR protein knock-down were sensitive to the poly(ADP-ribose)-polymerase (PARP) inhibitor olaparib, and this effect was further enhanced by inhibition of the ataxia telangiectasia and rad3 related (ATR) kinase. Altogether, our data supports a functional role for DDR-deficiency in NB in vivo and therapeutic potential for combination PARP + ATR inhibition in NB patients with alterations in DDR genes. Significance This work provides the first in vivo evidence supporting a functional role for DDR-deficiency in NB by demonstrating that alterations in certain DDR pathway genes promote NB formation and metastasis. NGS and pre-clinical drug testing also provides rationale for PARP + ATR inhibitor therapy combinations for patients with NB and pathogenic DDR pathway alterations.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".