Abstract IA002: Leveraging synthetic lethality for the development of novel cancer therapies
Bibliographic record
Abstract
Abstract The concept of synthetic lethality has long held promise for the next generation of genetically targeted cancer therapies to follow the success of PARP inhibitors in the treatment of BRCA-mutant cancers. The classical definition of synthetic lethality arose in Drosophila with the observation that loss of either of two genes independently had little effect on cell viability but loss of both led to cell death. This definition has now been expanded to capture pairs of genes in which genetic alteration of one gene and pharmacological inhibition of the other leads to death of cancer cells while sparing the normal cells which lack the genetic alteration, leading to a broad therapeutic index. Functional genomics screening (using unbiased RNAi or CRISPR-based technology) has enabled the systematic discovery of novel synthetic lethal targets for drug discovery. The selective dependence of MTAP-deleted cells on PRMT5 is one of the strongest genetic interactions observed in early RNAi screens. Approximately 10-15% of all human cancer is MTAP-deleted, providing a large and diverse patient population. MTA-cooperative PRMT5 inhibitors, which bind preferentially in the presence of MTA, have been developed by scientists at Tango Therapeutics and elsewhere to leverage the synthetic lethal relationship between PRMT5 and MTAP loss. MTA-cooperative PRMT5 inhibitors inhibit PRMT5 in MTAP-deleted cancer cells and spare MTAP-expressing normal cells leading to clinically well-tolerated and efficacious therapies. MTA-cooperative PRMT5 inhibitors have broad therapeutic potential both as single agent and in combination with other therapies. Citation Format: Kimberly Briggs.Leveraging synthetic lethality for the development of novel cancer therapies. [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Optimizing Therapeutic Efficacy and Tolerability through Cancer Chemistry; 2024 Dec 9-11; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(12_Suppl):Abstract nr IA002.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.017 |
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".