MicroRNA Expression Profiling in Sorted AML Subpopulations: A Possible Role for miR-155/BIC in Stem Cell Maintenance and Leukemogenesis.
Notice bibliographique
Résumé
Abstract MicroRNAs (miRNAs) are a new class of non-coding small RNAs that negatively regulate the expression of protein-encoding genes. Mature miRNAs are excised sequentially from primary miRNA (pri-miRNA) foldback precursor transcripts, and regulate gene expression at the post-transcriptional level. miRNAs functionally suppress gene expression by either inhibition of protein synthesis or by direct cleavage of the target mRNA. miRNA expression is tissue and developmental stage restricted, suggesting important roles in tissue specification and/or cell lineage determination. miRNAs are implicated in the regulation of diverse processes including cell growth control, apoptosis, fat metabolism and insulin secretion, and may be involved in the maintenance of the embryonic stem cell state. Several recent lines of evidence suggest a role for miRNAs in hematological malignancies. Many characterized miRNAs are located at fragile sites, minimal loss of heterozygosity regions, minimal regions of amplification or common breakpoint regions in human cancers. For example, chromosomal translocation t(8;17) in an aggressive B-cell leukemia results in fusion of miR-142 precursor and a truncated MYC gene. Furthermore, both miR-15 and miR-16 are located within a 30 kb deletion in CLL, and in most cases of this cancer both genes are deleted or underexpressed. In addition, mice transplanted with hematopoietic stem cells (HSC) overexpressing both c-Myc and the miR-17–92 polycistron developed cancers earlier with a more aggressive nature when compared to lymphomas generated by c-myc alone. To address the role of miRNAs in the regulation and maintenance of the hematopoietic stem cell state and leukemogenesis, we sorted 6 primary AML patient samples into 4 populations based on the expression of CD34/CD38 and performed miRNA array analysis. We identified a subset of miRNAs whose expression profile could discriminate the CD34+/CD38- fractions from more mature populations. In particular, BIC/miR-155 was found to be over-expressed in leukemic stem cells (LSC). Validation by qRT-PCR revealed this expression pattern in 5 of the 6 sorted AML samples. Furthermore, within umbilical cord blood (CB) cells, BIC/miR-155 is more highly expressed in the primitive CD34+38- fraction as compared to mature sub-fractions as assessed by Affymetrix microarray. miRNA array analysis also revealed elevated levels of miR-155 in bulk primary AMLs as compared to normal BM. Intriguingly, BIC/miR-155 was first identified as a common retroviral insertion site in avian leucosis virus induced B cell lymphomas, and BIC/miR-155 overexpression has been observed in all subtypes of Hodgkin’s lymphoma. To test the hypothesis that miR-155 is important in LSC/HSC function, we designed lentiviral vectors for RNAi mediated knockdown of BIC/miR-155. Knockdown of BIC/miR-155 within a novel CD34+ leukemic cell line resulted in a loss of CD34 expression and reduced proliferative potential. Additionally, knockdown within CB led to alterations in colony forming capacity. Additionally, we have recently generated lentiviral vectors for the enforced overexpression of BIC/miR-155. In vivo studies to investigate the effects of BIC/miR-155 over-expression and knockdown are ongoing and will be discussed.
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 | 0,001 | 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 | 0,001 |
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 ».