Abstract B020: <i>SF3B1 </i>hotspot mutations confer sensitivity to PARP inhibition through a defective replication stress response
Bibliographic record
Abstract
Abstract SF3B1 hotspot mutations are highly prevalent in several tumor types, where they lead to a global disruption of canonical splicing and are associated with a poor clinical outcome. Whilst evidence suggests that spliceosomal inhibitors have a therapeutic benefit for specific SF3B1 mutant cancers, recent trials have failed to report any clinical responses. Here we used a myriad of in vitro and in vivo techniques to identify and explore a synthetic lethal vulnerability in SF3B1 mutant cancers. These included a high throughput drug screen with an in-house curated library of 80 small-molecule inhibitors in an isogenic cell line model with the most prevalent SF3B1 mutation, a resistance CRISPR knockout screen and a range of DNA fibre analyses to gain mechanistic insights into the observed sensitivity. We identified that SF3B1 mutant cells are selectively sensitive to multiple PARP inhibitors (PARPi), which validated in numerous cell lines and patient derived models in vitro and in vivo, whereby they prevent metastasis. SF3B1 selective PARPi sensitivity occurs via a previously undescribed mechanism, as a result of excessive dormant origin firing and altered fork dynamics, due to the loss of the canonical replication stress response (pCHK1, pRPA, 53BP1), when SF3B1 mutant cells are treated with PARPi. This was further substantiated by the lack of MUS81 recruitment to under-replicated DNA intermediates, leading to the accumulation of DNA damage and cell cycle stalling, via the induction of the G2/M checkpoint. These findings demonstrate that SF3B1 mutant cells have wild-type-like replication under normal growth conditions, but fail to safeguard replication when exposed to PARPi. High content proteomic profiling identified that the defective ATR response is a direct consequence of the downregulation of CINP in SF3B1 mutant cells, which was confirmed in multiple isogenic models and in primary tumors. The defective ATR response was rescued with CINP re-expression and phenocopied through CINP silencing. In SF3B1 mutant cells G2/M checkpoint activation under PARP inhibition can be further abrogated by the addition of ATM inhibitors, but not by the inhibition of ATR or Chk1. Our discovery defines a unique mechanism underpinning PARPi sensitivity in SF3B1 mutant cancers. This synthetic-lethal relationship is further validated in a Phase 1 clinical trial, which shows that those patients with SF3B1 mutant relapsed leukemia have the longest progression free survival when treated with single agent PARPi. This novel synthetic lethality extends the utility of PARPi beyond BRCA1/2 mutant cancers and introduces a new therapeutic approach ready for proof-of-concept clinical trials. Citation Format: Philip Bland, Harry Saville, Patty T Wai, Lucinda Curnow, Jadwiga Nieminuszczy, Nivedita Ravindran, Holly E Barker, James Wright, Lu Yu, Ioanna Mavrommati, Barrie Peck, Patrycja Gazinska, Helen N Pemberton, Aditi Gulati, Naomi Guppy, Ioannis Roxanis, Guy Pratt, Ceri Oldreive, Tatjana Stankovic, Samantha Barlow, Helen Kalirai, Sarah E Coupland, Ronan Broderick, Samar Alsafadi, Alexandre Houy, Marc-Henri Stern, Stephen Pettit, Jyoti S Choudhary, Syed Haider, Wojciech Niedzwiedz, Christopher J Lord, Rachael Natrajan. SF3B1 hotspot mutations confer sensitivity to PARP inhibition through a defective replication stress response [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr B020.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".