Abstract 7130: Dysregulated DNA repaired elicited by type 1 PRMT inhibitor in clear cell renal cell carcinoma enables development of novel combination therapies
Bibliographic record
Abstract
Abstract Clear cell renal cell carcinoma (ccRCC) is the most prevalent form of kidney cancer, notorious for its resistance to treatment and dismal prognosis. Advanced or metastatic cases on average display an 8% 5-year survival rate. Given the considerable number of diagnoses in advanced stages, it is evident that we require innovative therapeutic approaches. Our lab has developed a methodology to establish cell lines from tumors and adjacent normal tissues sourced from patients. Consequently, we've amassed a collection of cell lines, including those from patient-derived ccRCC and normal kidney cells. Using these ccRCC models, we demonstrated that the type I protein arginine methyltransferase inhibitor, MS023, elicits a dysregulated DNA repair phenotype. RNA-Seq analysis of ccRCC cells treated with MS023 unveiled a marked downregulation of genes associated with the homologous recombination (HR) pathway for double-strand break repair and the Fanconi Anemia (FA) pathway for interstrand crosslink (ICL) repair. In a follow-up investigation using paired normal and cancerous cell lines from the same patient, we identified resistance to MS023 in normal kidney cells that is not mirrored in the corresponding ccRCC cell line. This hints at a potential therapeutic window and provides a strong rationale for clinical pursuit. Poly-ADP ribose polymerase (PARP) inhibitors are known to yield a synergistic effect when employed in HR-deficient diseases, such as BRCA-deficient breast cancers. Since MS023 induces an HR-deficient phenotype, we hypothesize that combining it with Talazoparib, a PARP inhibitor, will produce a similar synergistic effect. Additionally, mitomycin C (MMC) is a clinically approved compound that induces ICLs. As MS023 impedes ICL repair by downregulating crucial ICL-repairing genes, combining these two drugs should likewise generate a synergistic effect. Through a drug screen across two of our ccRCC cell lines, we discovered that the cells exhibit sensitivity to various PARP inhibitors. Employing synergy checkerboard assays and the highest single-agent model of synergy, we have found that the combination of MS023 and Talazoparib, as well as the combination of MS023 and MMC, demonstrate synergy, significantly reducing cellular viability at lower doses of the combination treatments compared to mono-treatment conditions at their respective doses. Preliminary in vivo studies using patient-derived xenograft models have revealed that both MS023 and Talazoparib are well-tolerated in mice, both when administered individually and in combination. Our current knowledge base indicates that MS023 holds promise for clinical investigation, both as a standalone treatment and in combination with Talazoparib or MMC. These results present an exciting opportunity to shed new light on the challenging therapeutic landscape faced by ccRCC patients today. Citation Format: Karen Arevalo, Joseph Walton, Jalna Meens, Angel Sau Ni Ng, Laurie Ailles. Dysregulated DNA repaired elicited by type 1 PRMT inhibitor in clear cell renal cell carcinoma enables development of novel combination therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7130.
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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) | 0.001 | 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, 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".