Leukemic Engraftment In NOD.SCID Mice Is Correlated With Clinical Parameters and Predicts Outcome In Human AML
Notice bibliographique
Résumé
Abstract The NOD.SCID xenotransplantation assay has emerged as a key model system for interrogating the biology of human acute myeloid leukemia (AML). Previous work has established that approximately 50% of AMLs can generate grafts resembling the patient’s leukemia in immunodeficient mice. An understanding of the biologic properties of AML that enable engraftment in xenotransplant assays may aid in the development of prognostic tools and individualized therapy. To investigate these properties in a broad cross-section of human AML, we transplanted bone marrow (BM) or peripheral blood (PB) cells from 307 AML patients intra-femorally into sublethally irradiated NOD.SCID mice pre-treated with an anti-CD122 antibody. Human engraftment in the recipient BM was assessed 8-10 weeks post-transplant via flow cytometry. AML xenografts, defined as a human graft composed of >90% myeloid (CD33+CD19-CD45+) cells, were generated by 134 samples (44%). The remainder (hereafter referred to as non-engrafting samples) generated 3 patterns of non-leukemic engraftment: no human graft, defined as <0.5% CD45+ cells (85 samples, 28%), isolated CD3+CD45+ T-cell engraftment (27 samples, 9%), and multilineage human engraftment, comprised of CD33+CD45+ myeloid cells with at least 10% CD19+CD45+ B-cells (61 samples, 20%). Using this classification scheme, 105 of 264 diagnostic patient samples (40%) generated an AML graft, compared to 29 of 43 relapse samples (66%; P=0.0007). Within our cohort there were 11 pairs of presentation and relapse samples. In 2 patients, the diagnostic sample did not generate a leukemic graft while the relapse sample did; engraftment patterns were congruent in the remainder. Among the diagnostic samples, leukemic engraftment was associated with a higher PB white cell count (mean of 92 x109/L in engrafters vs. 67 x109/L in non-engrafters; P=0.01), but there was no correlation with BM blast percentage (mean of 75% vs. 72%; P=0.38). A strong relationship between cytogenetically defined prognostic groups and engraftment ability was observed: AML xenografts were generated by 4/30 samples (13%) with favorable karyotypes, 63/153 (41%) with intermediate karyotypes and 23/43 (53%) with adverse karyotypes (P=0.002). No diagnostic samples harboring PML-RARα translocations were capable of initiating leukemic engraftment (n=10). Among patients with normal karyotype (NK) AML, the presence of an NPM1 mutation was not related to engraftment ability; however, 17 of 34 diagnostic samples (50%) from FLT3-ITD-positive patients established leukemic xenografts, compared to 11 of 41 (27%) NK FLT3-ITD-negative samples (P=0.04). Of note, AML engraftment ability in NOD.SCID mice was strongly associated with a poor response to standard induction therapy. Complete remission was achieved in only 30 of 59 (51%) patients whose diagnostic samples established AML xenografts, compared to 82 of 103 (80%) non-engrafting samples (P<0.0001). Consistent with this observation, both overall survival (OS) and event-free survival (EFS) post-induction were lower in patients whose diagnostic samples were capable of engraftment compared to non-engrafters (median OS of 9.8 vs. 28.5 months; P<0.0001; median EFS 3.0 vs. 12.5 months; P=0.0001). Similar findings were noted among individuals with NK AML, with AML engrafters having a median OS of 11.4 months vs. 54.1 months in non-engrafters (P=0.002) and a median EFS of 6.3 vs. 15.2 months (P=0.002). Thus, the NOD.SCID xenotransplant assay identifies a subset of AML patients with aggressive disease that responds poorly to standard induction therapy. Further in depth genomic and transcriptional analysis of our dataset will provide insight into the underlying determinants that link xenograft repopulation characteristics with clinical properties and identify those that could be developed into novel prognostic and predictive signatures. Disclosures: Wang: Trillium Therapeutics/Stem Cell Therapeutics: 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 | 0,001 | 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 ».