Transcriptomic Features of Immune Exhaustion and Senescence Predict Outcomes and Define Checkpoint Blockade-Unresponsive Microenvironments in Acute Myeloid Leukemia
Notice bibliographique
Résumé
Abstract Acute myeloid leukemia (AML) is a molecularly and clinically heterogeneous disease. Reinstating immunological control of AML is highly desirable to eradicate chemotherapy-resistant clones and provide long-term disease control. We recently identified bone marrow (BM) microenvironmental transcriptomic profiles that stratify patients with newly diagnosed AML into an immune-infiltrated and an immune-depleted subtype and that refine the accuracy of survival prediction beyond that afforded by current prognosticators (Vadakekolathu J et al., 2020). We have also shown that CD8 + T cells from patients with AML exhibit features of immune exhaustion and senescence (IES), including heightened expression of killer cell lectin-like receptor subfamily G member 1 (KLRG1) and B3GAT1 (encoding CD57) (Knaus H et al., 2018). Whether deranged T-cell functions affect the likelihood of responding to antitumor therapy, including immune checkpoint blockade (ICB), is an outstanding question in AML. In the current study, we analyzed 183 BM samples collected longitudinally at time of AML onset, response assessment and disease relapse from multiple cohorts of patients with AML treated with standard-of-care induction chemotherapy, and from 33 elderly AML patients with newly diagnosed or chemotherapy-refractory/relapsed AML treated with azacitidine, and the PD-1 checkpoint inhibitor pembrolizumab (NCT02845297). Primary patient specimens and associated clinical data were obtained via informed consent in accordance with the Declaration of Helsinki on research protocols approved by the Institutional Review Boards of the participating Institutions. RNA (150-200 ng) was extracted from BM aspirates and was processed on the nCounter FLEX analysis system (NanoString Technologies, Seattle, WA) using the PanCancer Immune profiling panel, as previously published (Vadakekolathu J et al., 2020). The correlation between transcriptomic features of IES, clinical characteristics, therapeutic response and patient outcome was validated using publicly available RNA-sequencing and NanoString data from 1,698 patients with AML, including samples from the TCGA-AML (n=147 cases), Beat-AML Master Trial (n=264 cases, of which 240 with survival data and 195 with chemotherapy response data) and Children's Oncology Group (COG)-TARGET AML series (n=145 cases). We initially showed that, compared with their non-senescent CD8 +CD57 -KLRG1 - counterpart, senescent CD8 +CD57 +KLRG1 + T cells are functionally impaired in terms of their ability to effect AML-blast killing mediated by an anti-CD33/CD3 bi-specific T-cell engager antibody construct (kindly provided by Amgen, USA; effector/target [E/T] ratio = 1:5). We then used gene set enrichment analysis (GSEA) to derive a transcriptomic signature of IES encompassing natural killer (NK)-cell and stem-like CD8 + T-cell markers, and showed that IES states correlate with lymphoid infiltration, adverse-risk molecular lesions (TP53 and RUNX1 mutations), experimental gene signatures of leukemia stemness (LSC17 score; Ng et al., 2016) and poor outcome in response to standard induction chemotherapy (Fig. 1A). In independent validation cohorts of children and adults with AML, the IES score was higher at baseline in patients with primary induction failure (following a standard 2 cycles of chemotherapy) compared with complete remission, increased in post-chemotherapy BM specimens, and predicted survival with greater accuracy than the ELN cytogenetic risk classifier (Fig. 1B). In the immunotherapy setting, high IES scores at baseline defined a checkpoint blockade-unresponsive AML tumor microenvironment and correlated with significantly shorter overall survival (9.1 versus 15.56 months in patients with high and low IES scores, respectively; HR = 3.32 (95% CI = 1.19-9.25); log-rank P = 0.021; Fig. 1C). Finally, the IES-related gene set also predicted for long-term outcomes and objective responses, based on RECIST criteria, to single-agent nivolumab or pembrolizumab, or combination anti-PD-1 + anti-CTLA-4, in 106 patients with melanoma (PRJEB23709 and GSE93157 series), a tumor type known to derive durable clinical benefit from ICB (Fig. 1D). Our findings encourage the pursuit of immune senescence reversal as a strategy to functionally reinvigorate T cells and could inform the delivery of ICB and other T cell-targeting immunotherapies to patients who are likely to benefit. Figure 1 Figure 1. Disclosures Radojcic: Syndax Pharmaceuticals: Research Funding; Regeneron Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Allakos: Membership on an entity's Board of Directors or advisory committees. Minden: Astellas: Consultancy. Tasian: Aleta Biotherapeutics: Consultancy; Gilead Sciences: Research Funding; Kura Oncology: Consultancy; Incyte Corporation: Research Funding.
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 | 0,000 | 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 ».