Failure of Iniparib to Inhibit Poly(ADP-Ribose) Polymerase <i>In Vitro</i>
Bibliographic record
Abstract
PURPOSE: Poly(ADP-ribose) polymerase (PARP) inhibitors are undergoing extensive clinical testing for their single-agent activity in homologous recombination (HR)-deficient tumors and ability to enhance the action of certain DNA-damaging agents. Compared with other PARP inhibitors in development, iniparib (4-iodo-3-nitrobenzamide) is notable for its simple structure and the reported ability of its intracellular metabolite 4-iodo-3-nitrosobenzamide to covalently inhibit PARP1 under cell-free conditions. The present preclinical studies were conducted to compare the actions iniparib with the more extensively characterized PARP inhibitors olaparib and veliparib. EXPERIMENTAL DESIGN: The abilities of iniparib, olaparib, and veliparib to (i) selectively induce apoptosis or inhibit colony formation in HR-deficient cell lines, (ii) selectively sensitize HR-proficient cells to topoisomerase I poisons, and (iii) inhibit formation of poly(ADP-ribose) polymer (pADPr) in intact cells were compared. RESULTS: Consistent with earlier reports, olaparib and veliparib selectively induced apoptosis and inhibited colony formation in cells lacking BRCA2 or ATM. Moreover, like earlier generation PARP inhibitors, olaparib and veliparib sensitized cells to the topoisomerase I poisons camptothecin and topotecan. Finally, olaparib and veliparib inhibited formation of pADPr in intact cells. In contrast, iniparib exhibited little or no ability to selectively kill HR-deficient cells, sensitize cells to topoisomerase I poisons, or inhibit pADPr formation in situ. In further experiments, iniparib also failed to sensitize cells to cisplatin, gemcitabine, or paclitaxel. CONCLUSIONS: While iniparib kills normal and neoplastic cells at high (>40 μmol/L) concentrations, its effects are unlikely to reflect PARP inhibition and should not be used to guide decisions about other PARP inhibitors.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".