Aberrant Splicing In Patients With AML Is Associated With Over- Expression Of Specific Splicing Factors
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».