Classification of Acute Myeloid Leukemia (AML) Based On Apoptosis and Myeloid Signaling Networks.
Notice bibliographique
Résumé
Abstract Abstract 325 Background: Acute Myeloid Leukemia (AML) is the most common myeloid malignancy in adults and represents an aggressive disease with significant biological and clinical heterogeneity. Currently, cytogenetics and molecular changes are used to inform treatment strategies. However a wide range of clinical responses are observed in these patient subgroups necessitating alternative methodologies to provide information that could inform clinical decisions for AML disease management. Since the net result of the cytogenetic and molecular changes is necessarily a functional alteration of proteins within signal transduction networks the current study was undertaken to understand the diversity of signaling responses in AML patient samples. Critically, in these studies treatment of samples with a variety of input stimuli allowed intracellular phospho-signaling and apoptosis network properties to be revealed that would otherwise remain unseen in resting cells. Objectives: Single cell network profiling (SCNP) using muliparameter flow cytometry was used to identify intracellular pathway responses to treatment with myeloid cytokines and growth factors in addition to apoptosis-inducing agents in individual AML patients. Identification of unique signaling profiles in patient sample sub-groups may inform the choice of specific therapeutic regimens. Methods: JAK/STAT, PI3K/S6 and apoptosis signaling pathways were measured after in vitro exposure of 34 diagnostic non-M3 AML samples to a panel of myeloid growth factors (e.g FLT3L, SCF), cytokines (e.g G-CSF, GM-CSF) interleukins (e.g IL-6, IL-27) and apoptosis-inducing agents (etoposide, staurosporine). Samples were processed for cytometry by paraformaldehyde/methanol fixation and permeabilization followed by incubation with fluorochrome-conjugated antibody cocktails that recognize both cell surface proteins to delineate cell subsets in addition to intracellular signaling molecules. Results: JAK/STAT and PI3K/S6 signaling responses to individual modulators revealed a range of activity in these pathways within individual patients. Analysis of JAK/STAT and PI3K/S6 pathways across individual patient samples identified subgroups of samples with distinct pathway profiles: A) high JAK/STAT activity, B) high PI3K/S6 activity, C) high activity in both pathways, and D) low activity in both pathways. In vitro exposure of samples to staurosporine and etoposide revealed three distinct “apoptosis” profiles: 1) Staurosporine Refractory 2) Etoposide Refractory and samples that were 3) Apoptosis Competent in response to both these agents. In this study, elevated PI3K/S6 pathway activity and elevated IL-27/IL-6 induced JAK/STAT pathway activity was associated with in vitro refractoriness to apoptosis inducing agents. Analysis of JAK/STAT, PI3K/S6 and Apoptosis pathway activities characterized biologically distinct patient-specific signatures, even within cytogenetically and phenotypically uniform patient subgroups. Notable were differences in signaling profiles between samples from different patients and in cell subpopulations within the same sample. Conclusions: SCNP revealed a range of signaling responses within AML samples consistent with the heterogeneity of the disease. The data suggest the importance of characterizing and tracking signaling profiles within the subpopulations of an AML sample over time and in response to therapeutic pressure with the aim of guiding the choice of a targeted agent to be used alone or in combination with chemotherapy to improve patient response rates. Disclosures: Rosen: Nodality, Inc.: Employment, Equity Ownership. Putta:Nodality, Inc.: Employment, Equity Ownership. Covey:Nodality, Inc.: Employment, Equity Ownership. Huang:Nodality Inc.: Employment, Equity Ownership. Cesano:Nodality Inc.: Employment, Equity Ownership. Fantl:Nodality, Inc.: Employment, Equity Ownership.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».