Aberrant Splicing In Patients With AML Is Associated With Over- Expression Of Specific Splicing Factors
Bibliographic record
Abstract
Abstract Pre-mRNA processing, referred to as alternative RNA splicing (AS), is a critical determinant of protein diversity. AS produces multiple transcripts and, as a result, multiple proteins from a single gene. Recently, frequent mutations in splicing factor genes have been reported in myelodysplasia (MDS) and chronic lymphocytic leukemia (CLL), and less frequently in AML. However, in previous studies, we found that aberrant patterns of splicing were common in cells from 66 AML patients compared to 10 normal donors (NDs), more common than could be explained by mutations in splicing factor genes. Here, we evaluated expression levels of 24 core splicing factors (SFs), which are involved in splicing reactions, in cells from 30 AML patients compared to 10 NDs. Among these SFs we identified three, U2AF2, PTBP, and SFRS12 that were significantly (P<0.001) upregulated in AML samples. Of the 30 patients 65% , 75%, and 25% had increased levels of U2AF2, PTBP, and SFRS12, respectively. We detected increased expression of U2AF2 and PTBP at the protein level in several patient samples as well where sufficient protein was available for immunoblotting. Expression of the SFRS12 protein was not evaluated. We asked if overexpression of U2AF2 or PTBP altered splicing by overexpressing cDNAs encoding these splicing factors in HEK293T cells. To test this hypothesis HEK293T cells stably expressing U2AF2 and PTBPs were transfected with mini-genes derived from two genes, FLT3 and CD13, which we previously found commonly mis-spliced in AML. Overexpression of PTBP but not U2AF2 induced FLT3 and CD13 mini-gene splicing. This study suggest that overexpression of the PTBPs induce FLT3 and CD13 splicing. We also evaluated growth and cell proliferation effects of the U2AF2 and PTBPs. The HEK293T cells expressing U2AF2 formed colonies 11 days later after seeding, while cells expressing PTBPs formed foci in 5 days. Interestingly, overexpression of PTBP, and also U2AF2 to a lesser extent, accelerated growth and colony formation of HEK293T cells in MethoCult. These results suggest that PTBPs may increase cell proliferation and enhance anchorage-independent cell growth. Currently, we are investigating growth and cell proliferation effects of the U2AF2 and PTBPs in AML patient samples and cell lines, and in murine leukemia models. In a preliminary study, PTBP was overexpressed in murine marrow LSK cells, with or without the MLL-AF9 oncogene, and these cells were transplanted into irradiated recipient mice. Reconstitution was monitored measuring donor-specific myeloid and lymphocyte populations. Overexpression of PTPB by itself did not result in the development of leukemia, but was associated with shortened survival in mice co-expressing MLL-AF9 in stem cells. Using RNA-seq analysis we are evaluating effects of PTBP overexpression on genome-wide splicing in the samples obtained from in vivo studies. Results obtained from this will be presented. Taken together, the data suggest that overexpression of splicing factor genes may result in altered splicing, and can accelerate malignant cell growth in vitro and possibly in vivo. Disclosures: Griffin: Novartis: Research Funding; Janssen: Research Funding.
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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 | 0.001 |
| 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) | 0.002 | 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 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".