Abstract A33: Defect in S phase cell cycle checkpoint renders tumours vulnerable to CHK1 inhibitor single-agent treatment in vitro and in vivo
Bibliographic record
Abstract
Abstract CHK1 inhibitors are being investigated as chemosensitizing agents with agents that increase replication stress. Here we have investigated the molecular basis of sensitivity to CHK1 inhibitors as single agents in melanoma and lung cancer. We have found that sensitivity in vitro and in vivo to single agent CHK1 inhibitor is loss of the S phase cell cycle checkpoint response. This is through a number of mechanisms including the uncoupling of CHK1 activation with the destabilization of CDC25A. Loss of checkpoint by over-expressing components of the checkpoint or inhibition of Wee1, covert CHK1 inhibitor insensitive cells to sensitive, and similarly depletion of CDC25A reduces CHK1 inhibitor sensitivity in sensitive lines. Loss of the S phase checkpoint provides cells with an adaptive advantage through introduction of moderate levels of genomic instability. The increased DNA damage found with CHK1 inhibitor treatment is not sufficient to induce cell death, but also involves a mechanism that is dependent in part on DNA-PK activity. Loss of S phase checkpoint function is predicted for <25% of melanomas and non-small cell lung squamous cell cancers. This is independent of other known risk factors, suggesting a significant proportion of melanoma and lung cancer patients could benefit from treatment with these drugs. Note: This abstract was not presented at the conference. Citation Format: Zay Yar Oo, Alexander Stevenson, Catherine Lanagan, Loredana Spoerri, Jill Larsen, Brian Gabrielli. Defect in S phase cell cycle checkpoint renders tumours vulnerable to CHK1 inhibitor single-agent treatment in vitro and in vivo [abstract]. In: Proceedings of the AACR Special Conference on DNA Repair: Tumor Development and Therapeutic Response; 2016 Nov 2-5; Montreal, QC, Canada. Philadelphia (PA): AACR; Mol Cancer Res 2017;15(4_Suppl):Abstract nr A33.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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".