Abstract SY13-01: Genetic and non-genetic mechanisms contribute to long term clonal growth dynamics and therapy resistance
Notice bibliographique
Résumé
Abstract The cellular and molecular basis for intra-tumoral heterogeneity is poorly understood. Tumor cells can be genetically diverse due to mutations and clonal evolution resulting in intra-tumoral functional heterogeneity. Often proposed as mutually exclusive, cancer stem cell (CSC) models postulate that tumors are cellular hierarchies sustained by CSC heterogeneity due to epigenetic differences (i.e. long term tumor propagation only derives from CSC). The presentation will focus on three lines of evidence showing these models are highly integrated. Gene signatures specific to either AML LSC or normal HSC are highly similar and define a common stemness program. Compared to non-stem cell transcriptional programs, only stem cell signatures were significant independent predictors of patient survival in 4 large clinical databases of >1000 samples. Thus, determinants of stemness influence clinical outcome of AML across a spectrum of mutations indicating that many genetic abnormalities coalesce around stem cell properties. These studies provide strong support that the CSC model is clinically relevant and not an artifact of the xenografts model. Secondly, we have carried out a series of combined genetic and functional studies of the LSC from either B-ALL or AML that point to commonalities between clonal evolution and CSC models of cancer. LSC from diagnostic patient samples were genetically diverse and reconstruction of their genetic ancestry showed that multiple LSC subclones were related through a complex branching evolutionary process and specific genetic events influence L-IC frequency. Also study of paired diagnostic (Dx) and relapse (Rx) samples are revealing that individual subclones possess distinct functional growth properties and that rare Dx subclones are chemotherapy resistant and become enriched at Rx. Thus the clonal evolution models are highly relevant in cancer but need to be extended to adopt the concept that CSC are subject to clonal evolutionary forces. Finally, the combined genetic and functional analysis of AML is revealing fundamental insights into the cell of origin, nature and biological consequences of initiating lesions and order of subsequent mutations; concepts that demonstrate how highly integrated the CSC and genetic evolution models must be. Highly purified hematopoietic stem cells (HSC), progenitor and mature cell fractions from the blood of AML patients were found to contain recurrent DNMT3a mutations (DNMT3amut) at high allele frequency, but without coincident NPM1 mutations (NPM1c) present in AML blasts. DNMT3amut-bearing HSC exhibited multilineage repopulation advantage over non-mutated HSC in xenografts, establishing their identity as pre-leukemic-HSC (preL-HSC). preL-HSC were found in remission samples indicating that they survive chemotherapy. Thus DNMT3amut arises early in AML evolution, likely in HSC, leading to a clonally expanded pool of preL-HSC from which AML evolves. Our findings provide a paradigm for the detection and treatment of pre-leukemic clones before the acquisition of additional genetic lesions engenders greater therapeutic resistance. Collectively, these three lines of evidence show that the CSC and evolution models can be unified. Moreover, these studies point to the need to develop therapies that effective target, all the genetic subclones present in a tumor, the ancestral cell types from which recurrences can arise and ultimately all leukemia and pre-leukemic cells possessing stemness properties, to ensure further evolution and recurrence are prevented. Citation Format: John E. Dick. Genetic and non-genetic mechanisms contribute to long term clonal growth dynamics and therapy resistance. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr SY13-01. doi:10.1158/1538-7445.AM2014-SY13-01
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 | 0,001 | 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».