Aberrant RHAMM Splicing in Multiple Myeloma (MM) and Its Implications for Immunotherapy
Notice bibliographique
Résumé
Background: Receptor for hyaluronan-mediated motility (RHAMM) or CD168 has been a promising target for MM immunotherapy because it is overexpressed in MM cells. RHAMM has been tested as a target for an anti-RHAMM peptide vaccination approach in MM and other hematological malignancies. Although RHAMM peptide-induced immune response in patients, clinical outcomes were mixed, that can be a result of equal expression levels of RHAMM in different subpopulation of bone marrow (BM) cells in MM patients and healthy donors (HD). To enhance current RHAMM-peptide and future immunotherapeutic approaches, we investigated the cause of altered RHAMM mRNA splicing in MM patients. mRNA splicing has the potential to produce numerous mis-spliced genes, creating novel disease markers; some resulting proteins are likely to contain neoantigens selectively expressed on MM tumor cells. Methods/results: Splicing alterations can be caused by single nucleotide variations (SNVs) that affect splicing regulatory elements (SREs), or by deregulated splicing factors (SFs). We evaluated the incidence of SNVs located in the vicinity of the RHAMM. We identified a total of 57 SNVs: 72% SNVs are in the intronic region, and 28% are in the RHAMM coding region. We used the "HEXplorer" tool and predicted that four SNVs have the potential to contribute to aberrant RHAMM splicing in MM either by altering SF binding to SREs or by impacting splice site selection. Predicted SNVs were evaluated using an in vivo splicing assay to identify SNV-clusters causing aberrant RHAMM splicing. We have observed progressive overexpression of core SF PTBP1/2 (polypyrimidine track-binding protein) in MM patients and associated with disease progression. Since SNVs on the RHAMM modulate canonical SF binding sites, we tested the effects of PTBP1/2 deregulation on RHAMM splicing. We expressed PTBP1/2 in H929 cells, and then evaluated the RHAMM splicing pattern in transfected cells at a single cell (SC) level. SC analyses showed that overexpression of PTBP1/2 increased (2.5-fold) the RHAMM-V3:FL ratio in MM cells. SC analyses also identified overexpression of the RHAMM-V3 splice variant in 18% of H929 SCs expressing PTBP1, and in 37% of cells expressing PTBP2, confirmed at the single cell (SC) level. In BM-infiltrating myeloid cells, analyses showed 50% of myeloid cells express the RHAMM-V3 variant alone, and 79% of plasma cells (PCs) express this variant in combination with RHAMM-FL. Moreover, the RHAMM-V3/FL ratio in PCs is elevated (2.6-fold), further confirming a correlation between the RHAMM variant ratio and the clinical outcome. Next, we determined RHAMM-V3/FL ratios in BM stromal cells from 16 MM patients: MM-BMSC samples exclusively express the RHAMM-V3 in combination with RHAMM-FL and the RHAMM-V3:FL is 1.8 fold. In BMSC samples derived from healthy donors (HD), we detected relatively low-level expression of RHAMM-FL as compared to expression levels of RHAMM-FL in MM patients, while RHAMM-V3 transcripts were undetectable. SC analysis of RHAMM FL and splice variant transcripts in MM BMSC and HD-BMSC agreed with the analyses done on the MM HD-BMSC bulk population. We did not detect any MM BMSC cells expressing RHAMM-V3 alone and the RHAMM V3/FL ratio was 1.6-fold, which is lower than that in MM-PCs. MM-BMSC screening also identified a new splice variant of RHAMM, that was absent in MM PCs or in MM myeloid cells. Conclusions: Our study suggests that aberrant RHAMM splicing in MM can result from SNPs/SNVs affecting SRE due to the upregulation of PTBP1/2. Our study is the first to show that the RHAMM-V3 variant is associated with PTBP2 overexpression. The identification of cell type-specific RHAMM splicing events identifies novel targets for improved immunotherapy in MM. Disclosures Chu: Celgene: Honoraria; AstraZeneca: Honoraria; Gilead: Honoraria; Teva: Consultancy; Amgen Inc.: Honoraria. Anderson:C4 Therapeutics: Other: Scientific founder ; OncoPep: Other: Scientific founder ; Gilead Sciences: Other: Advisory Board; Janssen: Other: Advisory Board; Sanofi-Aventis: Other: Advisory Board.
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 | 0,001 | 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 | 0,001 | 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 ».