MétaCan
Menu
Retour à la cohorte
Enregistrement W2983330076 · doi:10.1182/blood-2019-121870

Immune Landscapes Predict Chemotherapy Resistance and Anti-Leukemic Activity of Flotetuzumab, an Investigational CD123×CD3 Bispecific Dart® Molecule, in Patients with Relapsed/Refractory Acute Myeloid Leukemia

2019· article· en· W2983330076 sur OpenAlexaff
Jayakumar Vadakekolathu, Mark D. Minden, Tressa Hood, S. Church, Stephen Reeder, Heidi Altmann, Amy Sullivan, Elena Viboch, Tasleema Patel, Narmin Ibrahimova, Sarah Warren, Andrea Arruda, Marc Schmitz, Yan Liang, Alessandra Cesano, A. Graham Pockley, Peter J.M. Valk, Bob Löwenberg, Martin Bornhäuser, Sarah K. Tasian, Michael P. Rettig, Jan Davidson‐Moncada, John F. DiPersio, Sergio Rutella

Notice bibliographique

RevueBlood · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensPrincess Margaret Cancer CentreUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésImmune systemMedicineInterleukin-3 receptorImmunotherapyChemotherapy regimenMyeloid leukemiaOncologyLeukemiaImmunologyMyeloidInternal medicineChemotherapyCancer research

Résumé

récupéré en direct d'OpenAlex

Background Acute myeloid leukemia (AML) is a molecularly and clinically heterogeneous hematological malignancy. Chemotherapy resistance is common, and relapse is the major cause of treatment failure. Although immunotherapy may be an attractive modality to exploit in patients with AML, the ability to predict the groups of patients and the types of cancer that will respond to immune targeting remains limited. Methods Immune gene expression profiling for the high-dimensional analysis of the immunological landscape of bone marrow (BM) samples from patients with newly-diagnosed (de novo) non-promyelocytic AML (n=387) was employed to analyze the tumor microenvironment (TME). We derived immune scores from mRNA expression levels and devised an RNA-based, quantitative metric of immune infiltration, as previously published (Danaher P, et al. JITC 2017 and 2018). The PanCancer IO360™ gene expression assay was used to profile BM samples collected prior to and during flotetuzumab (FLZ) treatment from 30 AML patients treated at the RP2D (500 ng/kg/day) in the CP-MGD006-01 clinical trial (NCT#02152956), primary refractory, n=23 or relapsed, n=7. IO360 score comparisons are presented as mean ± SD and significance was assessed by the Mann Whitney U test. Results Analysis of pre-treatment BM samples from de novo AML revealed distinct immune signature modules, reflecting the co-expression of genes associated with 1) an IFNγ-dominant TME, 2) adaptive immune responses, and 3) myeloid cell abundance. When considered in aggregate, the relative intensity of gene expression in the immune modules stratified BM samples into two subgroups, which will be herein termed immune-infiltrated and immune-depleted. When AML patients were dichotomized based on median immune scores, high versus low, a higher percentage of primary refractory patients was observed within the IFNγ high module (65.4% versus 34.6%; p=0.0022). In multivariate logistic regression, an IFNγ high profile (derived from the IFNγ-dominant module) was predictive of therapeutic resistance to induction chemotherapy, even more than ELN risk categories (AUROC = 0.815 versus 0.702 with ELN risk only). In a validation cohort, Beat AML series, the IFNγ high profile when compared to other clinically established prognostic indicators in AML, i.e. disease type (primary versus secondary), WBC count, patient age at diagnosis, and ELN risk categories was significantly more predictive of therapeutic resistance to induction chemotherapy (AUROC=0.921 versus 0.709 with ELN cytogenetic risk alone; two-tailed p value=0.002673). Similarly, a higher percentage of patients with an IFNγ high profile AML in the HOVON series failed to achieve CR in response to induction chemotherapy when compared to AML cases with an IFNγ low profile (27.2% versus 15.2%; p=0.0004). We hypothesized that higher expression of IFNγ inducible genes, while underpinning chemotherapy resistance, might identify AML patients who derive benefit from immunotherapy with FLZ. BM samples from 92% of patients with evidence of FLZ anti-leukemic activity (ALA), which was defined as either CR, CRh, CRi, PR or overall benefit (>30% reduction in BM blasts), had an immune infiltrated TME relative to non-responders (SD or PD). Interestingly, the IFNγ-signaling score was significantly higher in patients with chemotherapy-refractory AML compared with relapsed AML at time of FLZ treatment, and in individuals with evidence of ALA compared to non-responders (p<0.0001). Additionally, another IFNγ-related score, the tumor inflammation signature (TIS), had strong predictive power of anti-leukemic activity to FLZ, with an AUROC value of 0.847 (p=0.001). FLZ also modified the TME, and on-treatment BM samples (available in 19 patients at the end of cycle 1) displayed increased expression of antigen presentation and immune activation genes relative to baseline, and had higher TIS scores (6.47±0.22 versus 5.93±0.15, p=0.0006), antigen processing machinery scores (5.67±0.16 versus 5.31±0.12, p=0.002), IFNγ signaling scores (3.58±0.27 versus 2.81±0.24, p=0.0004) and PD-L1 expression (3.43±0.28 versus 2.73±0.21, p=0.0062). Conclusions Our findings to date suggest that microenvironmental immune gene profiles could be used to inform the delivery of personalized immunotherapies to patients with IFNγ-dominant AML subtypes, and identify patients less likely to respond to cytotoxic chemotherapy. Disclosures Minden: Trillium Therapetuics: Other: licensing agreement. Hood:NanoString Technologies, Inc.: Employment. Church:NanoString Technologies, Inc.: Employment, Equity Ownership. Sullivan:NanoString Technologies, Inc.: Employment. Viboch:NanoString Technologies, Inc.: Employment. Warren:NanoString Technologies, Inc.: Employment. Liang:NanoString Technologies, Inc.: Employment. Cesano:NanoString Technologies, Inc.: Employment. Löwenberg:Chairman, Leukemia Cooperative Trial Group HOVON (Netherlands: Membership on an entity's Board of Directors or advisory committees; Agios Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Astex: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Up-to-Date", section editor leukemia: Membership on an entity's Board of Directors or advisory committees; CELYAD: Membership on an entity's Board of Directors or advisory committees; Chairman Scientific Committee and Member Executive Committee, European School of Hematology (ESH, Paris, France): Membership on an entity's Board of Directors or advisory committees; Elected member, Royal Academy of Sciences and Arts, The Netherlands: Membership on an entity's Board of Directors or advisory committees; Editorial Board "European Oncology & Haematology": Membership on an entity's Board of Directors or advisory committees; Clear Creek Bio Ltd: Consultancy, Honoraria; Hoffman-La Roche Ltd: Membership on an entity's Board of Directors or advisory committees; Frame Pharmaceuticals: Equity Ownership; Royal Academy of Sciences and Arts, The Netherlands: Membership on an entity's Board of Directors or advisory committees; Supervisory Board, National Comprehensive Cancer Center (IKNL), Netherland: Membership on an entity's Board of Directors or advisory committees. Tasian:Incyte Corportation: Research Funding; Gilead Sciences: Research Funding; Aleta Biotherapeutics: Membership on an entity's Board of Directors or advisory committees. Rettig:WashU: Patents & Royalties: Patent Application 16/401,950. Davidson-Moncada:MacroGenics, Inc.: Employment, Equity Ownership. DiPersio:Celgene: Consultancy; NeoImmune Tech: Research Funding; Macrogenics: Research Funding, Speakers Bureau; Incyte: Consultancy, Research Funding; Karyopharm Therapeutics: Consultancy; RiverVest Venture Partners Arch Oncology: Consultancy, Membership on an entity's Board of Directors or advisory committees; Cellworks Group, Inc.: Membership on an entity's Board of Directors or advisory committees; Amphivena Therapeutics: Consultancy, Research Funding; Magenta Therapeutics: Equity Ownership; WUGEN: Equity Ownership, Patents & Royalties, Research Funding; Bioline Rx: Research Funding, Speakers Bureau. Rutella:NanoString Technologies, Inc.: Research Funding; MacroGenics, Inc.: 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: Essai non randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,002

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 Opus0,006
Tête enseignante GPT0,225
Écart entre enseignants0,219 · 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'étudeEssai non randomisé
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

Citations3
Publié2019
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueBloodMême sujetAcute Myeloid Leukemia ResearchTravaux en français237 207