Perturbations in <i>HNRNPH1</i> Splicing and Abundance Affect Global Splicing and Proliferation in Mantle Cell Lymphoma
Notice bibliographique
Résumé
Objectives Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established and the features known to contribute to differences in clinical course remain limited. We previously discovered non-coding and silent mutations in HNRNPH1 that affect its splicing and contribute to poor outcomes for patients with MCL. We sought to extend our understanding of the mechanisms by which HNRNPH1 contributes to MCL pathology using a combination of in vitro models and integrative analysis of RNA sequencing from MCL tumors. Methods We previously sequenced ribosomal RNA-depleted RNA from 130 MCL tumors. Based on our earlier identification of mutations in HNRNPH1 and altered splicing of this gene, we performed differential splicing analyses using rMATS and leafcutter. We investigated the functional and phenotypic effect of deregulated hnRNP H1 protein through siRNA knockdown. Results Our previous work identified that splicing of HNRNPH1, and not total mRNA expression, correlated with protein abundance in MCL tumors. As a result, our analysis of alternative splicing focused on events associated with altered splicing of HNRNPH1. We identified 155 unique alternative splicing events (ΔPSI > 0.1, FDR < 0.1). Gene ontology analysis identified various aspects of RNA processing which are significantly enriched within this gene list, including mRNA splicing, transport, and metabolic process. This nominates HNRNPH1 as part of the complex network controlling alternative splicing within MCL. Available CLIP-seq in HeLa cells provides evidence for direct interactions between hnRNP H1 and transcripts identified by our analysis (e.g. RBM25, EIF4A1, HNRNPA2B1). Of the 155 events we identified, more than half involved retained introns. Generally, retained introns result in non-productive RNA species, which indicates that this program of intron retention in MCL is a mechanism by which protein abundance can be regulated by hnRNP H1. For all cases with available Mantle Cell Lymphoma International Prognostic Indicator (MIPI) classification, we determined the splicing ratio for HNRNPH1 and observed a general association between high MIPI scores and a lower ratio of non-productive HNRNPH1 transcripts. This suggested that the increased hnRNP H1 abundance we observed in HNRNPH1-mutant tumors contributes to increased proliferation of MCL cells. We verified this in vitro with siRNA knockdown of HNRNPH1 in HEK cells, which resulted in a significant decrease in cell proliferation. Conclusions We have described a pattern of alternative splicing in MCL that is associated with alterations in HNRNPH1 splicing and related protein abundance. The prevalence of retained introns suggests that hnRNP H1 regulates the abundance of protein-coding transcripts via alternative splicing coupled to nonsense-mediated decay. We continue to explore targets of hnRNP H1, a novel oncoprotein in MCL. Disclosures Morin: Celgene: Consultancy.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,001 | 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 ».