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Enregistrement W3211352653 · doi:10.1182/blood-2021-145854

Transcriptomic Features of Immune Exhaustion and Senescence Predict Outcomes and Define Checkpoint Blockade-Unresponsive Microenvironments in Acute Myeloid Leukemia

2021· article· en· W3211352653 sur OpenAlexaff
Sergio Rutella, Jayakumar Vadakekolathu, Francesco Mazziotta, Stephen Reeder, Tung On Yau, Rupkatha Mukhopadhyay, Heidi Altmann, Michael Krämer, Hanna A. Knaus, Joshua F. Zeidner, Vedran Radojčić, Andrea Arruda, Mark D. Minden, Sarah K. Tasian, Martin Bornhäuser, Ivana Gojo, Leo Luznik

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensPrincess Margaret Cancer CentreUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésImmune checkpointMyeloid leukemiaMedicineOncologyInternal medicineImmunologyImmune systemImmunotherapy

Résumé

récupéré en direct d'OpenAlex

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,249
Écart entre enseignants0,240 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2021
Routes d'admission1
Résumé présentoui

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