Contextual Synthetic Lethality of Cancer Cell Kill Based on the Tumor Microenvironment
Bibliographic record
Abstract
Acute and chronic hypoxia exists within the three-dimensional microenvironment of solid tumors and drives therapy resistance, genetic instability, and metastasis. Replicating cells exposed to either severe acute hypoxia (16 hours with 0.02% O(2)) followed by reoxygenation or moderate chronic hypoxia (72 hours with 0.2% O(2)) treatments have decreased homologous recombination (HR) protein expression and function. As HR defects are synthetically lethal with poly(ADP-ribose) polymerase 1 (PARP1) inhibition, we evaluated the sensitivity of repair-defective hypoxic cells to PARP inhibition. Although PARP inhibition itself did not affect HR expression or function, we observed increased clonogenic killing in HR-deficient hypoxic cells following chemical inhibition of PARP1. This effect was partially reversible by RAD51 overexpression. PARP1(-/-) murine embryonic fibroblasts (MEF) showed a proliferative disadvantage under hypoxic gassing when compared with PARP1(+/+) MEFs. PARP-inhibited hypoxic cells accumulated γH2AX and 53BP1 foci as a consequence of altered DNA replication firing during S phase-specific cell killing. In support of this proposed mode of action, PARP inhibitor-treated xenografts displayed increased γH2AX and cleaved caspase-3 expression in RAD51-deficient hypoxic subregions in vivo, which was associated with decreased ex vivo clonogenic survival following experimental radiotherapy. This is the first report of selective cell killing of HR-defective hypoxic cells in vivo as a consequence of microenvironment-mediated "contextual synthetic lethality." As all solid tumors contain aggressive hypoxic cells, this may broaden the clinical utility of PARP and DNA repair inhibition, either alone or in combination with radiotherapy and chemotherapy, even in tumor cells lacking synthetically lethal, genetic mutations.
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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 | 0.000 |
| 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 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".