Abstract 1256: RPL22 is a tumor suppressor in MSI-high cancers and a key splicing regulator of MDM4
Bibliographic record
Abstract
Abstract Microsatellite instability high (MSI-H) tumors are marked by 30% or more mutations in microsatellite regions and are generated by somatic or germline alterations in DNA mismatch repair machinery. Despite a high tumor mutational burden, MSI-H tumors do not frequently harbor mutations in TP53. Notably, a frameshift mutation (p.K15fs) in the gene RPL22 is among the most recurrent mutations in MSI-H tumors. RPL22 and its paralog, RPL22L1, form part of the large subunit of the 60S ribosome and are known to affect protein synthesis as well as splicing of genes and transcription factors that affect development and tumorigenesis. Here we explore the result of RPL22 loss on the regulation of MDM4, an upstream target of p53. MDM4 protein expression is mediated through alternative mRNA splicing of its sixth exon, which leads to two isoforms, the exon 6-inclusive MDM4-FL and the exon 6-exclusive MDM4-S, which is prone to degradation. To date, no mutational events have been associated with this alternative splicing event. We show the prevalence of RPL22fs mutations is more than 70% in certain MSI-H cell lines (e.g. colon, endometrial) and tumors (e.g. stomach adenocarcinoma) in the CCLE and TCGA. RPL22 copy number loss and RPL22 frameshift mutations are strongly correlated with MDM4 exon 6 inclusion in TCGA samples, and RPL22 knockout increases MDM4 exon 6 inclusion and MDM4 protein in multiple cell lines. RPL22 loss increases cell proliferation and augments resistance to the MDM inhibitor Nutlin-3a. Downstream targets of p53 (p21, BBC3) are downregulated due to RPL22 loss and Nutlin-3a inhibition, suggesting mutation of RPL22 and subsequent overexpression of MDM4 promotes resistance to Nutlin-3a. CLIP-seq revealed that RPL22 binds the MDM4 3’-UTR. We find that RPL22 loss is associated with an alternative 3’-splicing event in RPL22L1 adjacent to exon 3 and results in the expression of the full-length transcript of RPL22L1. In summary, we identify RPL22 as a key modulator of MDM4 splicing through an alternative splicing switch in exon 6. Furthermore, RPL22 represses the expression of its paralog, RPL22L1, by mediating the splicing of a cryptic exon corresponding to a truncated functional transcript. Therefore, we propose that damaging mutations in RPL22 drive oncogenic MDM4 induction and reveal a common splicing circuit in MSI-H tumors that may inform therapeutic targeting of the MDM4-p53 axis and oncogenic RPL22L1 induction. Our results also suggest that the presence of RPL22 may act as a rheostat to maintain MDM4 exon 6 skipping under normal cellular contexts. Citation Format: Hannah N. Weinstein, Kevin Hu, Lisa Fish, Yih-An Chen, Paul Allegakoen, Keliana S. Hui, Julia H. Pham, Maria B. Baco, Hanbing Song, Andrew O. Giacomelli, Francisca Vazquez, Mahmoud Ghandi3, Hani Goodarzi, Franklin W. Huang. RPL22 is a tumor suppressor in MSI-high cancers and a key splicing regulator of MDM4 [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 1256.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".