Identification of a Novel Function of B2M Involving T-Cell Exhaustion Via P-Selectin Ligand Upregulation in Diffuse Large B-Cell Lymphoma
Notice bibliographique
Résumé
Background: Despite improvement of outcomes with current immuno-chemotherapies, approximately 40% of diffuse large B-cell lymphoma (DLBCL) patients suffer from recurrence or relapse, making it a refractory lymphoma. We previously reported that down-regulation of major histocompatibility complex (MHC) molecules contributes to a cold immune microenvironment and treatment resistance (Ennishi D & Takata K et al. Cancer Discov. 2019). However, the detailed mechanisms by which MHC reduction induces a cold immune microenvironment remain unclear. Here, we studied the functional consequences of loss of MHC class I and its major component beta-2-microglobulin (B2M) with a focus on the host immune microenvironment. Methods: We used the CRISPR-Cas9 gene editing system to knock out (KO) the B2M gene in two DLBCL-derived cell lines expressing MHC class I (Pfeiffer and SU-DHL-8). mRNA sequencing was performed and gene signatures that were commonly up- and down-regulated in both cell lines were identified. Concurrently, we conducted multicolor immunohistochemical (IHC) analysis using DLBCL patient samples (N=100) to examine the correlation between candidate molecules, MHC class I, and CD8+ T-cells. We also performed ligand stimulation assays and co-culture experiments in the generated isogeneic cell line systems, and generated an in vivo syngeneic mouse (A20 B2M KO) model to investigate antibody treatment. Results: Filtering the mRNA sequencing data (B2M-wt vs. heterozygous and homozygous KO) with P < 0.05 and a fold change > 1.5 revealed 383 up-regulated genes in Pfeiffer and 111 in SU-DHL-8, with four genes commonly up-regulated in both cell lines. Among these, the SELPLG (P selectin ligand) gene was the top upregulated gene. Additional B2M KO in other DLBCL cell lines (SU-DHL-4 and SU-DHL-10) confirmed the up-regulation of SELPLG. To explore mechanistic links between B2M and SELPLG, we performed gene set enrichment analysis (co-upregulated genes and pathways in B2M KO group), co-immunoprecipitation (co-IP), and ligand stimulation assays, and found that B2M binds to TNFRSF12A (TWEAKR) and up-regulates SELPLG via the NF-kB pathway. IHC of DLBCL patient samples showed an exclusive relationship between MHC class I and SELPLG expression in tumor cells (P < 0.001) without any links to DLBCL subtypes (GCB or non-GCB). Multi-color IHC revealed that SELPLG-positive samples had significantly more CD8+ PD1+ T-cells near tumor cells compared to SELPLG-negative samples, suggesting that SELPLG may cause exhaustion of host T-cells. Next, using B2M wt and KO DLBCL cells, we inhibited P-selectin and its ligand with a SELPLG antibody (Neihulizumab) and a P-selectin inhibitor (PSI-697) and conducted an in vitro co-culture with CD8+ T-cells. CD69-positive activated T-cell population was less abundant in B2M KO compared with B2M wt groups, which supports our previous findings (Cancer Discov. 2019). Inhibition of SELPLG/P-selectin significantly increased the CD69-positive activated T cell population in the KO group, suggesting that inhibition of SELPLG/P-selectin induces restoration of CD8+ T-cell activation. Of note, inhibition of SELPLG by Neihulizumab did not result in tumor growth suppression in DLBCL cell lines. Finally, we examined the therapeutic effects of the SELPLG antibody using a syngeneic mouse model. SELPLG was found to be upregulated in B2M KO A20 cells compared to B2M WT cells. Tumor growth reduction was observed in both A20 B2M wt and KO cell transplanted groups treated with the SELPLG antibody, with a stronger tumor reduction effect in the KO group. Single-cell expression analysis of the formed tumors revealed Th and CTL populations specifically expressing IL-7R, CXCL13, and ITGB in the treated KO group, suggesting their key role in tumor reduction. Conclusion: We discovered a novel function of the major component of MHC class I, B2M, which involves the exhaustion of CD8+ T-cells via SELPLG, contributing to the formation of a cold immune microenvironment. Targeting SELPLG could provide a new therapeutic avenue for refractory DLBCL that evades host immunity.
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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 ».