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Enregistrement W2550339374 · doi:10.1182/blood.v112.11.2685.2685

Iron Overload and Haematopoiesis in MDS: Does Blood Transfusion Promote Progression to AML?

2008· article· en· W2550339374 sur OpenAlexaff
Lap Shu Alan Chan, Rena Buckstein, Marciano D. Reis, Alden Chesney, Adam Lam, Matthew C. Cheung, Eugenia Piliotis, Lilly Gu, Richard A. Wells

Notice bibliographique

RevueBlood · 2008
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensHealth Sciences CentreSunnybrook Health Science CentreSunnybrook Hospital
Organismes subventionnairesnon disponible
Mots-clésHaematopoiesisMyelodysplastic syndromesStem cellProgenitor cellImmunologyBiologyMedicineCancer researchBone marrowCell biology

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: The biology of myelodysplastic syndrome (MDS) is poorly understood, and treatment options are limited. Thus, most MDS patients require chronic red blood cell transfusion, and many develop secondary iron overload. Although the pathophysiological consequences of iron overload to the heart, liver, and endocrine organs have been well characterized, its effects on haematopoiesis have not been studied. However, it has been observed that chelation therapy in iron-overloaded MDS patients may result in reduction of transfusion requirements, and recent studies have suggested a correlation between the use of iron chelation therapy and improvement in leukaemia-free survival in MDS. At the cellular level, iron toxicity is mediated in large part via the generation of reactive oxygen species (ROS). It has been shown in animal models that accumulation of ROS leads to senescence of haematopoietic stem cells, and that ROS cause DNA damage and promote the development of malignancy. These effects of ROS may be particularly important in MDS, in which haematopoiesis is already severely compromised and genetic instability is a striking feature. Hypothesis: We hypothesize that iron overload secondary to transfusion leads to increased levels of intracellular ROS in early haematopoeitic cells in MDS. The increase in intracellular ROS in MDS would be predicted to lead further impairment of haematopoiesis via stem cell exhaustion and while promoting accumulation of DNA damage by myelodysplastic stem cells and early progenitors, thus accelerating progression of MDS to acute leukaemia. Results: To test this hypothesis, we examined the relationship between transfusion-related iron overload and ROS content of CD34+ bone marrow cells in MDS. ROS content was measured in CD34+ cells by flow cytometry in bone marrow aspirates from 34 consecutive MDS patients (CMML=4, MDS/MPD=2, RA=4, RARS=3, RCMD=2, RAEB 1=6, RAEB 2=12, RAEB-t/AML=1). The patients represented a wide range of prior transfusion burden (0->300 units PRBC) and serum ferritin levels (11->10000 μg/L). ROS was strongly correlated with serum ferritin concentration for patients with iron overload (serum ferritin >1000 μg/L; n=14, R=0.733, p<0.005). The correlation between ROS and ferritin level was even stronger in the subset of patients with RAEB 1 or RAEB 2 and iron overload (n=11, R=0.838, p<0.005). In contrast, no correlation between ROS and ferritin level was demonstrated for patients with serum ferritin <1000 μg/L (n=20). Importantly, iron chelation therapy was associated with a reduction in CD34+ cell ROS content in one patient. To assess the effect of iron overload on normal stem cell and progenitor function, we established a mouse model of subacute bone marrow iron overload. B6D2F1 mice were loaded with iron dextran by intraperitoneal injection (150mg total iron load over 21 days), and sacrificed three days after the end of iron loading. Iron staining of tissue sections confirmed iron deposition in the bone marrow, liver, and myocardium. The development of splenomegaly was noted in iron-loaded animals. Flow cytometric analysis revealed increased apoptosis of bone marrow cells in iron loaded mice based on annexin V+/7 AAD-staining (6.26±0.96% versus 3.54±0.99% for control mice, paired student’s t-Test p<0.005). However, ROS content in CD117+ progenitors of iron loaded mice was similar to control mice. Thus, subacute iron loading in mice increases apoptosis but does not alter the ROS content of HSCs; we postulate that chronic iron overload is required to achieve this effect. Conclusions: These results establish a relationship between CD34+ cell ROS content and serum ferritin concentration in MDS patients with iron overload, and indicate that iron chelation therapy in this patient population reverses this ROS accumulation. The physiological consequences of this relationship are currently being investigated in this patient set by haematopoietic colony assays and assessment of DNA damage in CD34+ cells. Nonethelesss, these data may have key implications for the deployment of iron chelation therapy in MDS patients, and may explain the association between the use of iron chelation and improved leukaemia-free survival in MDS.

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)0,000
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: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,072
Score d'incertitude au seuil0,567

Scores Codex et Gemma par catégorie

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)0,0000,000

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 Opus0,013
Tête enseignante GPT0,283
Écart entre enseignants0,269 · 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

Citations19
Publié2008
Routes d'admission1
Résumé présentoui

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