Metabolic and Cell Cycle Proteins As Novel Targets of Selinexor Activity in Diffuse Large B Cell Lymphoma
Notice bibliographique
Résumé
Background Diffuse large B cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin lymphoma (NHL) and has poor outcomes in the relapsed/refractory (R/R) setting. Recent years have identified Exportin-1 (XPO1), a nuclear export protein, as a negative prognostic factor in several cancer types including DLBCL. Selinexor, an orally-available inhibitor of XPO1 has modest activity in R/R DLBCL, but knowledge gaps in understanding how XPO1 drives DLBCL are preventing effective use of selinexor in the clinic. Specifically, large-scale proteomics studies investigating which proteins are exported to the cytoplasm by XPO1 are lacking, and mechanisms of activity of selinexor-mediated XPO1 inhibition in DLBCL have not been well described. Therefore, we analyzed selinexor's effects on DLBCL metabolism and conducted a mass spectrometry analysis of proteins to determine which pathways are modulated by selinexor-mediated XPO1 inhibition. Methods DLBCL cell lines (HBL-1, OCI-Ly2, OCI-Ly8) were treated with selinexor for 24 hours and changes in mitochondrial and glycolytic ATP production was measured using an XFe 96 Agilent Seahorse bioanalyzer. Cells were treated with 0.5µM selinexor for 24 hours and replicates were subject to proteomic analysis via mass spectrometry. Proteins identified as having significant changes in abundance upon selinexor treatment were interrogated with Reactome to determine which pathways are modulated by the compound in DLBCL (Milacic et al., 2024). The sequences of proteins from the top pathways, as well as those of metabolic proteins of interest, were analyzed using the LocNES nuclear export sequence identifier to determine which of these proteins may be canonical XPO1 cargo molecules (Xu et al., 2014). Results Selinexor significantly reduced both mitochondrial and glycolytic ATP production (p<0.001) in all cell lines, as measured by oxygen consumption rate (OCR) and extracellular acidification rate (ECAR). Cell viability at this time point between cells treated and untreated with selinexor were not statistically significant, indicating that these metabolic changes were due to XPO1 inhibition and not cell death. Mass spectrometry analysis identified 6313 proteins, of which 126 showed a statistically significant change (p<0.05) in abundance with selinexor treatment (87 downregulated and 39 upregulated). The top pathways modified by selinexor included mitotic cell cycle control, mRNA splicing, rRNA modification, and RNA binding proteins, all of which were downregulated by the treatment. Canonical nuclear export sequences were identified in several selinexor-modulated proteins in these pathways, including cyclin B2, ORC1, LMNB1, HNRPC, and GAR1. Several metabolic proteins were affected by selinexor treatment, most notably ACADS, which catalyzes lipid metabolism via fatty acid oxidation. ACADS showed a decreased abundance in response to selinexor treatment, suggesting a mechanism by which the drug exerts its metabolic effects via inhibition of fatty acid oxidation and subsequent ATP production. Upon further analysis, the peptide sequence of the protein was also found to harbour a nuclear export sequence, indicating it is a potentially relevant XPO1 cargo molecule to the anti-lymphoma effects of selinexor. Conclusion Selinexor inhibits glycolytic and mitochondrial metabolism in DLBCL, which appears to be driven by blocking the nuclear export of enzymes involved in metabolism such as ACADS, which catalyzes ATP production via fatty acid oxidation. Selinexor is also able to decrease the abundance of proteins involved in cell cycle progression and RNA metabolism. We have identified several novel proteins that can be modulated by selinexor in DLBCL that may contribute to its mechanisms of anti-cancer activity in lymphoma. We aim to validate XPO1 targets of interest in our dataset. Future work will verify which of these proteins are XPO1 cargo molecules via proximity-ligation assays to reveal how the treatment exerts its cytotoxic effects in DLBCL.
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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 ».