Exploiting RAD54B-deficiency in colorectal cancer cells through synthetic lethal targeting of PARP1
Bibliographic record
Abstract
Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in Canada each year. Currently, most therapeutic approaches target rapidly dividing cancer cells by inhibition of normal cellular processes, however these therapies are not selective for cancer cells and unwanted side effects occur. Accordingly, novel cancer-targeted therapeutic strategies and drug targets are urgently needed to diminish the morbidity and mortality rates associated with CRC. Synthetic lethality is a new therapeutic approach that is designed to better target and kill cancer cells by exploiting a cancer-associated mutation (i.e. RAD54B-deficiency) thereby minimizing adverse side effects. We hypothesize that RAD54B-deficient CRC cells will be selectively killed via a synthetic lethal (SL) interaction with PARP1. We have identified and validated a novel drug target, PARP1, within CRC cells harboring RAD54B-deficiencies through a SL paradigm. This study represents the first steps necessary to identify and develop precision medicine based therapeutic strategies to combat CRC.
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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) | 0.002 | 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".