Bortezomib Induces an Antioxidant and ER-Stress Response Gene Expression Signature in Mantle Cell Lymphoma: Implications for Response Prediction and Optimized Chemotherapy Regimens.
Notice bibliographique
Résumé
Abstract Mantle cell lymphoma (MCL) is an aggressive and incurable B-cell lymphoma for which new treatment options are needed. Recent phase II clinical trials reported response to the proteasome inhibitor bortezomib (BZM) in up to 50% of pre-treated patients. Despite the successful use of BZM in the clinic, the precise molecular mechanisms underlying sensitivity or resistance to BZM in MCL remain largely unknown. To address this issue, we used U133A 2.0 microarrays to analyze gene expression in MCL cells from peripheral blood of 5 patients with previously untreated leukemic MCL. Samples were collected immediately before (0h) and at 3, 6, 24, and 72 hours after administration of BZM (1.5 mg/m2). After the blood collection at 72 hours, a second dose of BZM was given, and cells were collected 24 hours later. Two patients had major reductions in peripheral ALC already at 24h from dose 2 and normalized their blood counts by day 21 (sensitive), 1 patient had no change over a full course of 4 injections (resistant), and 2 patients had some decrease in ALC (intermediate). Genes differentially expressed with treatment were ranked according to the degree of correlation with time (Pearson). We used gene set enrichment analysis (GSEA) to detect distinct functional gene expression signatures; the most consistently up-regulated of which was a signature composed by proteasome and chaperone genes. To confirm and expand these findings, we exposed 10 MCL cell lines (7 sensitive, IC50<10nM; 3 resistant IC50>10nM) to 10nM of BZM and analyzed gene expression at 1, 3, 6 and 24 hours. The proteasome signature was again dominant, and the majority of the up-regulated genes in both clinical and cell line samples shared binding motifs for the NRF, MAF, ATF and HSF families of transcription factors (TF). Thus genes up-regulated by BZM in vivo and in cell lines predominantly belonged to a functional response to oxidative and/or endoplasmic reticulum (ER) stress. Under physiologic conditions, this is thought to help restore homeostasis and protect from apoptosis. This response could therefore contribute to drug resistance or be a marker of an overwhelming insult before the cells undergo apoptosis. To address this issue, we investigated differences in response to BZM between sensitive and resistant cell lines. The proteasome signature was more strongly up-regulated in sensitive cells than in resistant cells, and the ER-stress response as measured by genes controlled by the NRF and MAF family of TFs was also more highly expressed in the sensitive group. Consistently, expression of HMOX1, which encodes a key enzyme in the antioxidant response, was increased by 32× at 24h in the sensitive group, but only by 4× in the resistant group; the expression of DDIT3, a transcription factor implicated in a pro-apoptotic response to ER-stress was 5.5-fold up-regulated in the sensitive cells but only 1.4-fold in the resistant cells. We conclude that in sensitive cells BZM induces an overwhelming ER-stress response with high expression of proteasome components and chaperone proteins that could serve as a predictor of response to BZM.
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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 ».