Abstract IA024: RNA-modifying enzyme inhibitors as synthetic lethal cancer therapeutics
Bibliographic record
Abstract
Abstract Over 100 modifications to RNA are known to occur in human cells, where they play critical roles in many aspects of normal cellular physiology, such as cell fate decisions and terminal differentiation, through effects on RNA biology such as protein and nucleic acid interactions. Our survey of human RNA-modifying enzymes suggests many are cancer essential enzymes with striking synthetic lethal profiles, including the XRN1 nuclease and DHX9 helicase. XRN1 degrades single stranded mRNA from the 5′→3′ direction and plays a key role in endogenous cellular mRNA turnover. XRN1 can also degrade double-stranded RNA (dsRNA), and as such plays a role in innate immunity. We identified XRN1 as a selective vulnerability in tumor cells with intrinsic elevation of a Type I Interferon Stimulated Gene (TISG) signature through analysis of publicly available CRISPR data across 483 tumor cell lines. XRN1 KO via CRISPR leads to robust anti-proliferative effects in TISG high cells, but not in TISG low cells, as well as upregulation of Interferon-β mRNA and induction of phosphorylated PKR. Exogenous treatment with Interferon-β to induce elevated Type I Interferon expression sensitizes TISG low cells to XRN1 KO, confirming this synthetic lethal relationship. Enzymatic and biophysical assays for XRN1 were developed and used to identify and optimize XRN1 inhibitors. We identified Compound 1, a substrate-competitive inhibitor with single-digit micromolar affinity for XRN1 which does not bind or inhibit XRN2. High-resolution crystal structures indicate that Compound 1 binds in an allosteric binding site, confirming the mechanism of inhibition and selectivity profile determined by in vitro assays. This data suggests that XRN1, through its regulation of dsRNA burden, is a compelling and druggable oncology target for TISG high tumors. DHX9 is a multifunctional DExH-box RNA helicase which can unwind regions of double-stranded DNA and RNA helices but has a greater propensity for secondary structures such as DNA/RNA hybrids (R-loops) and DNA/RNA G-quadruplexes. DHX9 interacts with and regulates many proteins, including key members of DNA damage repair pathways. We have found that DHX9 knockdown is synthetic lethal in microsatellite high (MSI-H) or defective mismatch repair (dMMR) tumor models. A suite of assays was developed to identify and optimize potent and selective inhibitors of the DHX9 helicase, which recapitulate our findings with genetic tools. Profiling of DHX9 inhibitors across a broad panel of cancer cell lines reveals that tumor cells with mutations in the DNA damage repair genes BRCA1 and/or BRCA2 are also responsive to DHX9 inhibitor treatment in vitro and in vivo. DHX9 inhibition leads to increased RNA/DNA secondary structures such as R-loops and G-quadruplexes, resulting in subsequent DNA damage and increased replication stress, leading to cell cycle arrest and apoptosis. These results suggest that DHX9 inhibitors are a novel treatment modality for patients with defective DNA damage repair pathways such as dMMR and/or BRCA mutations. Citation Format: Serena J Silver, Maureen M. Lynes, Brian A. Sparling, Jennifer Castro, Matthew H. Daniels, Sunaina Pai, Sophie A. Shen, David Brennan, Hyelee Lee, Gordon J. Lockbaum, Kevin Knockenhauer, Deepali Gotur, Simina Grigoriu, Shihua Yao, Shane Buker, Monique Laidlaw, Jie Wu, Stephen J. Blakemore, P. Ann Boriack-Sjodin, Kenneth W. Duncan, Jason A. Sager, Robert A. Copeland. RNA-modifying enzyme inhibitors as synthetic lethal cancer therapeutics [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr IA024.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".