Abstract 617: High-throughput screens identify PARP inhibition as being synthetically lethal with ERCC1 deficiency in non-small cell lung cancer cell lines.
Bibliographic record
Abstract
Abstract Background: Non-small cell lung cancer (NSCLC) harbors frequent DNA-repair defects that represent therapeutic opportunities. Notably, Excision Repair Cross-Complementation group 1 (ERCC1) deficiency has been described in a subset of tumors and correlated with platinum sensitivity. The use of mechanism-based approaches, such as synthetic lethality, could allow targeting more selectively such DNA repair defects, with reduced systemic toxicity. Methods: To identify ERCC1-selective synthetic lethal interactions, we adopted an integrated functional and molecular profiling approach. An isogenic model of ERCC1-deficient NSCLC cells, consisting of one parental ERCC1-proficient cell line and 3 ERCC1-deficient clones, was functionally profiled by high throughput drug sensitivity screening using a library containing commonly used oncology agents as well as a large number of in-development targeted agents. This was integrated with data from molecular profiling, including high throughput siRNA screens. Results: The comparison of functional viability profiles for ERCC1-deficient models enabled the identification of synthetic lethal effects that could represent therapeutic opportunities for ERCC1-deficient tumors. Notably, ERCC1-deficient cells showed increased sensitivity to several PARP inhibitors, representing promising preliminary results that could be translated in the clinical setting. Mechanistic studies revealed a significant delay in double-strand break repair associated with a G2/M arrest following PARP inhibitor treatment in the ERCC1-deficient population only. Further in vitro work is providing deeper insight into the mechanisms underlying this PARP inhibitors sensitivity and in vivo work is underway. Conclusions: ERCC1-deficiency sensitizes human NSCLC cell lines to PARP inhibitors. In vitro and in vivo revalidations of these results and now underway to further dissect the molecular mechanisms responsible for these ERCC1-deficient selective effects, which could represent therapeutic opportunities. Citation Format: Sophie C. Postel-Vinay, Ilirjana Bajrami, Luc Friboulet, Marieke Aarts, Yari Fontebasso, Fabrice Andre, Ken Olaussen, Jean-Charles Soria, Chris Lord, Alan Ashworth. High-throughput screens identify PARP inhibition as being synthetically lethal with ERCC1 deficiency in non-small cell lung cancer cell lines. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 617. doi:10.1158/1538-7445.AM2013-617
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".