PRMT1 is a critical dependency in clear cell renal cell carcinoma through its role in post-transcriptional regulation of DNA damage response genes
Bibliographic record
Abstract
Abstract Biallelic inactivation of the Von Hippel-Lindau ( VHL ) tumor suppressor gene occurs in almost all cases of clear cell renal cell carcinoma (ccRCC) and leads to disrupted oxygen sensing and the upregulation of hypoxia-related genetic programs. Although the loss of VHL appears to be a necessary oncogenic driver event in the majority of ccRCC instances, it is not always a sufficient one. Large genomics studies have revealed that co-deletions of VHL with genes involved in chromatin regulation are common and important co-drivers of tumorigenesis. Several conserved evolutionary subtypes have been described clinically and the majority implicate disruptions in epigenetic regulators. It is now clear that impairments in cellular epigenetic mechanisms are important co-drivers of disease and signal a potential vulnerability in the epigenetic network of ccRCC cells relative to their normal counterparts. Using a clinically relevant panel of ccRCC models, we herein sought to exploit this potential vulnerability by screening a library of small molecule inhibitors that target a spectrum of epigenetic regulators. We identified MS023, an inhibitor of type I protein arginine methyltransferases (PRMTs) as an agent with antitumor activity. Using orthogonal genetic technologies, we further validated PRMT1 as the specific critical dependency for cancer growth. Mechanistically, our transcriptomic and functional analyses suggest that MS023 treatment results in substantial impairments to cell cycle and DNA damage repair (DDR) pathways, while spawning an accumulation of DNA damage over time. Our PRMT1 specific proteomics analysis revealed an interactome rich in RNA binding proteins including the specific regulator of DDR mRNA metabolism: the BCLAF1/THRAP3 complex. Further investigation suggests that MS023 treatment may result in impairments to DDR specific mRNA activities including nucleocytoplasmic transport and RNA splicing. Together, our data supports PRMT1 as a compelling target in ccRCC and informs a potential mechanism-based strategy for translational development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".