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Enregistrement W2396679265 · doi:10.1158/1557-3125.metca15-a04

Abstract A04: Differential dependence on sphingolipid metabolism in the normal and leukemic human hematopoietic hierarchy

2016· article· en· W2396679265 sur OpenAlexaff
Stephanie Z. Xie, Elisa Laurenti, Robin Ferrari, John E. Dick

Notice bibliographique

RevueMolecular Cancer Research · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésSphingolipidBiologyHaematopoiesisProgenitor cellStem cellCell biologyMyeloid leukemiaMyeloidSphingosineHematopoietic stem cellCancer researchBiochemistry

Résumé

récupéré en direct d'OpenAlex

Abstract Metabolic alterations are a cancer hallmark that are typically evaluated in bulk tissues. However most normal tissues and cancers are hierarchically organized and the metabolic requirements of both normal and cancer stem cells are poorly understood, particularly beyond energy metabolism. By analyzing a comprehensive transcriptional roadmap of human hematopoiesis, and comparing this to a leukemia stem cell (LSC) signature developed from 84 human acute myeloid leukemia (AML) samples, we found that: (1) several metabolic pathways, specifically in bioactive lipids, distinguish normal hematopoietic stem cells (HSC) from progenitors; and (2) while LSC are similar to HSC, specific metabolic pathways are more comparable to those of normal progenitors. We defined a lipid stem signature of 24 lipid genes, including sphingolipid genes, whose expression is higher in HSC than progenitors. Interestingly, sphingosine-1-phosphate (S1P) is known to play a role in HSC egress, and ceramide vs S1P levels serve as a rheostat to regulate cell growth and survival. To determine if sphingolipids play a functional role in the primitive hematopoietic compartment, we altered sphingolipid signaling by plating sorted populations of HSC or granulocyte-myeloid progenitors (GMP) in methylcellulose containing myriocin, which inhibits the first step of de novo sphingolipid synthesis, or FTY720, a S1P mimetic. Myriocin decreased GMP colony output but did not affect CFC derived from HSC. By contrast FTY720 affected HSC-derived CFC but not those from GMP, suggesting differential sensitivity to sphingolipid pathway inhibition between stem and progenitor cells. In vitro treatment of lineage depleted cord blood (Lin- CB) with myriocin for 8 days limited only myeloid differentiation compared to control treated cells. In contrast, FTY720 treatment reduced levels of immunophenotypic stem cells, erythroid and myeloid cells, as would be expected with inhibition of S1P proliferative signaling. However, in vitro FTY720-treated Lin- CB cells exhibit 16-week engraftment capacity comparable to that of controlled-treated cells, suggesting that any effects on HSC function are reversible after drug withdrawal. Furthermore, in vivo treatment with FTY720 in mice with established CB grafts did not decrease engraftment. Our lipid stem signature is enriched in LSC gene expression profiles from our 84 AML cohort by GSEA analysis, suggesting that differences in lipid metabolism may also exist in LSC vs. non-LSC. To determine if sphingolipids play a functional role in AML biology, we transplanted mice with peripheral blood cells from 13 AML patients, including those with therapy resistant and relapsed disease, and treated engrafted mice with myriocin or FTY720. We observed heterogeneous responses in our cohort, with reduction of leukemic burden in 3 and 5 samples following treatment with FTY720 and myriocin, respectively. Remarkably, serial transplantation of FTY720 responders into untreated secondary mice at limiting dilution demonstrated decreased LSC frequency in FTY720-treated primary mice compared to vehicle-treated controls, whereas myriocin responders showed no alteration of LSC frequency. These results suggest that FTY720 but not myriocin treatment affects LSC number and/or function. To stratify responders from nonresponders, we performed transcriptional analysis of untreated patient samples and compared these data to transcriptional signatures generated from the normal and AML hierarchy. Bioinformatic analysis demonstrated that FTY720 responders had an enriched LSC signature compared to nonresponders. In contrast, myriocin responders exhibited a strong GMP signature compared to nonresponders. Thus, normal human hematopoietic stem and progenitor cells display a variable dependence on sphingolipid biology that is also distinct between LSC and HSC, pointing to targeting of bioactive sphingolipids as a novel therapeutic strategy in AML to eradicate LSC while sparing HSC. Citation Format: Stephanie Z. Xie, Elisa Laurenti, Robin Ferrari, John E. Dick. Differential dependence on sphingolipid metabolism in the normal and leukemic human hematopoietic hierarchy. [abstract]. In: Proceedings of the AACR Special Conference: Metabolism and Cancer; Jun 7-10, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(1_Suppl):Abstract nr A04.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,499
Score d'incertitude au seuil0,673

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,002
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 Opus0,043
Tête enseignante GPT0,372
Écart entre enseignants0,329 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
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

Citations0
Publié2016
Routes d'admission1
Résumé présentoui

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