Acute Myeloid Leukaemia in Elderly: Expression Analysis of DNA Damage Response (DDR) and Anti-Apoptosis Genes Identify Novel Targets for Potential "Synergistic Lethality"
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".