Prognostic Prediction of Cytogenetically Normal Acute Myeloid Leukemia Based on a Gene Expression Model

Abstract

Acute myeloid leukemia (AML) refers to a heterogeneous group of hematopoietic malignancies. The well-known European Leukemia Network (ELN) stratifies AML patients into three risk groups, based primarily on the detection of cytogenetic abnormalities. However, the prognosis of cytogenetically normal AML (CN-AML), which is the largest AML subset, can be hard to define. Moreover, the clinical outcomes associated with this subgroup are diverse. In this study, using transcriptome profiles collected from CN-AML patients in the BeatAML cohort, we constructed a robust prognostic Cox model named NEST (Nine-gEne SignaTure). The validity of NEST was confirmed in four external independent cohorts. Moreover, the risk score predicted by the NEST model remained an independent prognostic factor in multivariate analyses. Further analysis revealed that the NEST model was suitable for bone marrow mononuclear cell (BMMC) samples but not peripheral blood mononuclear cell (PBMC) samples, which indirectly indicated subtle differences between BMMCs and PBMCs. Our data demonstrated the robustness and accuracy of the NEST model and implied the importance of the immune dysfunction in the leukemogenesis that occurs in CN-AML, which shed new light on the further exploration of molecular mechanisms and treatment guidance for CN-AML.

A 4‐gene prognostic index for enhancing acute myeloid leukaemia survival prediction

“…Thus, some gene expression‐based scores have been described as similar or superior in their survival prediction compared to LSC17, like PS29MRC, 20 85‐gene score, 21 3‐gene PI 18 and APS 17 . Furthermore, since AML is a highly heterogeneous disease, some prognostic indexes were developed focusing on CN‐AML or intermediate‐risk patients, like 11‐gene score, 27 NEST, 12 4‐gene score, 11 IRG risk score 49 and MPG6 10 . Here, we found that our 4‐PI stands out among numerous prognostic indexes, particularly for its efficiency and simplicity.…”

“…4,7 Within this context, the identification of markers that could improve the risk prediction is an unmet medical need. 5,6 Several groups have worked on the identification of these markers using transcriptome data, mainly based on microarray and RNA-sequencing technologies, [8][9][10][11][12][13][14][15][16][17][18][19] showing that gene expression profiles can be valuable for risk stratification. However, until today, no gene signature based on gene expression has been incorporated into any risk classification system, mainly due to a lack of validation or reproducibility.…”

Tissue-specific biological aging predicts progression in prostate cancer and acute myeloid leukemia

“…ALOX15B belongs to the lipoxygenase family of nonheme iron dioxygenases, which leads to fatty acid hydroperoxide production. ALOX15B is expressed in human monocyte-derived macrophages, and it is believed that the progression of cytogenetically normal AML could be a dysfunction of immune cells in the bone marrow microenvironment ( 82 , 83 ), directly connecting it to AML progression and nominating it as a possible mechanism of age-related AML therapeutic intervention.…”

Circular RNAs: pivotal role in the leukemogenesis and novel indicators for the diagnosis and prognosis of acute myeloid leukemia

“…Due to normal cytogenetic features, the prognosis of CN-AML must be based solely on genetic mutations. Furthermore, clinical outcomes of patients in this subgroup vary widely and are difficult to determine (195,196). Papaioannou et al (57) developed a novel computational method named Massive Scan for circRNA (MScircRNA) to detect and quantify circRNAs of CN-AMLs.…”