Acute Myeloid Leukaemia in Elderly: Expression Analysis of DNA Damage Response (DDR) and Anti-Apoptosis Genes Identify Novel Targets for Potential "Synergistic Lethality"
Notice bibliographique
Résumé
Background: Genetic instability and heterogeneity are fundamental to AML biology and pivotal to its prognosis. Acute myeloid leukaemia (AML) is most frequent in older adults (>60 years) and a significant majority are considered "treatment-naïve" given medical comorbidities, high-risk disease biology, and poor tolerance to chemotherapy. These patients receive low-intensity regimens, mostly hypomethylating agents due to impaired tolerance to induction chemotherapy, resulting in low overall survival. Thus, there is a critical need to develop targeted therapies capable of rapidly inducing a high rate of clinical response, with better tolerability and durable responses for these elderly AML patients. DNA damage response (DDR) is a specialized and highly orchestrated signalling cascade to maintain genetic stability and is closely linked to the cell cycle. The cell cycle checkpoints result in arrest and the resumption of cell cycle progression when DNA damage has been repaired. However, the DNA repair failure will direct cells towards cellular senescence or apoptosis. Hence, DDR and apoptosis are intricately related physiological processes. In AML, mutations in key regulators of gene expression and/or chromatin structure, such as p53, K-RAS, and isocitrate dehydrogenase 1 and 2 (IDH1/2) results in defective DDR. Defects in DDR are also age-related; therefore, resulting in an exponential increase in the incidence of cancer with age. The emerging treatment regimens for elderly AML are focusing on synergistic lethality using a combination of DDR inhibitors (PARP1) and/ or anti-apoptotic inhibitors (BCL2) in combination with low dose anthracycline and additional targeted therapies like (IDH2/DNTM etc.). However, the wider implication and influence of DDR genes either alone or in combination with anti-apoptotic genes remains uncharacterized in elderly AML. In this pilot study, we screened a large cohort of AML samples for mRNA expression for a series of DDR and apoptotic genes to investigate the age-related variation in expression of these molecules. We observed distinct differences in DDR and anti-apoptotic gene expression between elderly AML compared to paediatric patients. We anticipate, that these preliminary observations will pave the pathway for future comprehensive studies to expand the employment of synergistic lethality strategy for elderly AML patients. Methods: We employed RNA extracted from formalin-fixed paraffin-embedded (FFPE) diagnostic tissuesamples in 100 AML patients. Age defined the categorization of patients into three groups; a, <18 years (n=34); b,18-60 years (n=32) and c, >60 years (n=34). nCounter (NanoString Technologies) platform was used for the quantification of mRNA. Qlucore Omics Explorer software was employed with defined criteria (fold change >2.0; p<0.01 and q <0.05) for statistical analysis. Results:We noted that several DDR mediators (BRIP1, POLD1, XRCC4) are differentially up-regulated in the AML samples linked with elderly patient group, alongside anti-apoptotic genes (IDH2, IKBKB) when compared with samples from patient <18 years (Figure 1). Moreover, DDR effectors (BRCA1& ATM) were up-regulated in the elderly cohort relative to paediatric AML samples, suggesting potential targets for treating elderly AML (Figure2). Conclusions:This pilot study identifies several additional and novel DDR targets; which can be exploited to enhance chemotherapeutic efficacy in "treatment fit" as well as "treatment naïve" elderly AML patients. Besides, we also report numerous novel anti-apoptotic molecules up-regulated in elderly AML. Taken together the preliminary data, presented here, expand the repertoire for targeted therapy in elderly AML with a specific focus on synergistic lethality. Disclosures No relevant conflicts of interest to declare.
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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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 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 | 0,000 |
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 ».