Abstract 3814: In CLL the U1 snRNA driver mutation alters splicing in multiple genes and pathways
Bibliographic record
Abstract
Abstract 5-10% of patients with the IGHV wild type form of chronic lymphocytic leukemia (CLL) carry a g.3A>C driver mutation in the U1 small nuclear RNA (snRNA). We investigatedthe patterns of mis-splicing and their pathway consequences in three U1-mutant CLL cellline models using long read sequencing in order to better understand the mechanisms ofoncogenicity in tumors carrying this mutation. CLL cell lines (HG3, JVM3 and MEC1) expressing the U1 mutation and their wild-type counterparts were submitted to Oxford Nanopore sequencing to generate full-length RNA transcripts. This transcriptomic datawas evaluated, together with previously obtained short-read data. The g.3A>C mutation occurs at a specific location of the U1 snRNA, a core component of the eukaryotic spliceosome, and acts by altering the 5' splice site (5'SS) recognition sequence to cause consistent patterns of mis-splicing. Long read analysis identified multiple instances of intron retention and suppression of exon skipping, and in silico translation of these mis-splicing events predicted stop-gain and other loss of function mutations in several expressed genes, as well as widespread changes in gene expression levels. We performed a pathway overrepresentation analysis of the altered gene expression patterns in the mutant cells using the Reactome knowledgebase and identified an enrichment in the processes of translation, non-sense mediated decay (NMD) and immune signaling, including interferon signaling. In particular, there was a marked down-regulation of genes related to ribosomal assembly and the translational machinery. A more comprehensiveanalysis of the U1 mutation phenotype in CLL may accelerate the development ofbetter therapeutic and diagnostic approaches in patients. Citation Format: Andrea Senff-Ribeiro, Fatemeh Almodaresi, Quang Trinh, Shimin Shuai, David Spaner, Xose S. Puente, Elias Campo, Lincoln D. Stein. In CLL the U1 snRNA driver mutation alters splicing in multiple genes and pathways. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3814.
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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 | 0.001 |
| 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) | 0.004 | 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".