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. 2023 Nov 4;15(21):5289.
doi: 10.3390/cancers15215289.

Identification of a Complex Karyotype Signature with Clinical Implications in AML and MDS-EB Using Gene Expression Profiling

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Identification of a Complex Karyotype Signature with Clinical Implications in AML and MDS-EB Using Gene Expression Profiling

Cheonghwa Lee et al. Cancers (Basel). .

Abstract

Complex karyotype (CK) is associated with a poor prognosis in both acute myeloid leukemia (AML) and myelodysplastic syndrome with excess blasts (MDS-EB). Transcriptomic analyses have improved our understanding of the disease and risk stratification of myeloid neoplasms; however, CK-specific gene expression signatures have been rarely investigated. In this study, we developed and validated a CK-specific gene expression signature. Differential gene expression analysis between the CK and non-CK groups using data from 348 patients with AML and MDS-EB from four cohorts revealed enrichment of the downregulated genes localized on chromosome 5q or 7q, suggesting that haploinsufficiency due to the deletion of these chromosomes possibly underlies CK pathogenesis. We built a robust transcriptional model for CK prediction using LASSO regression for gene subset selection and validated it using the leave-one-out cross-validation method for fitting the logistic regression model. We established a 10-gene CK signature (CKS) predictive of CK with high predictive accuracy (accuracy 94.22%; AUC 0.977). CKS was significantly associated with shorter overall survival in three independent cohorts, and was comparable to that of previously established risk stratification models for AML. Furthermore, we explored of therapeutic targets among the genes comprising CKS and identified the dysregulated expression of superoxide dismutase 1 (SOD1) gene, which is potentially amenable to SOD1 inhibitors.

Keywords: AML; MDS; SOD1; complex karyotype; gene expression.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Overview of the study design. The flowchart explains the selection and filtering of the patient cohort in the model development, validation, and prediction of clinical outcome.
Figure 2
Figure 2
Differential gene expression profiles between the complex karyotype (CK) and non-CK group. (a) The distribution of differentially expressed genes (DEGs) in the CK group compared to that of the non-CK group based on chromosome location. The y-axis represents chromosome numbers, and the x-axis indicates the proportion of DEGs located on each chromosome out of the total DEGs. The red bars represent the fraction of upregulated genes among all DEGs (a total of 0.55), whereas the blue bars represent the fraction of downregulated genes (a total of 0.45). (b) A heatmap of 404 DEGs between the CK and non-CK groups. (c) The over-representation analysis based on Reactome, Wikipathways, and KEGG databases. The fraction of genes belonging to each term out of total listed genes is shown on the x-axis, and the q-values of ≤ 0.05 are considered significant and plotted accordingly.
Figure 2
Figure 2
Differential gene expression profiles between the complex karyotype (CK) and non-CK group. (a) The distribution of differentially expressed genes (DEGs) in the CK group compared to that of the non-CK group based on chromosome location. The y-axis represents chromosome numbers, and the x-axis indicates the proportion of DEGs located on each chromosome out of the total DEGs. The red bars represent the fraction of upregulated genes among all DEGs (a total of 0.55), whereas the blue bars represent the fraction of downregulated genes (a total of 0.45). (b) A heatmap of 404 DEGs between the CK and non-CK groups. (c) The over-representation analysis based on Reactome, Wikipathways, and KEGG databases. The fraction of genes belonging to each term out of total listed genes is shown on the x-axis, and the q-values of ≤ 0.05 are considered significant and plotted accordingly.
Figure 2
Figure 2
Differential gene expression profiles between the complex karyotype (CK) and non-CK group. (a) The distribution of differentially expressed genes (DEGs) in the CK group compared to that of the non-CK group based on chromosome location. The y-axis represents chromosome numbers, and the x-axis indicates the proportion of DEGs located on each chromosome out of the total DEGs. The red bars represent the fraction of upregulated genes among all DEGs (a total of 0.55), whereas the blue bars represent the fraction of downregulated genes (a total of 0.45). (b) A heatmap of 404 DEGs between the CK and non-CK groups. (c) The over-representation analysis based on Reactome, Wikipathways, and KEGG databases. The fraction of genes belonging to each term out of total listed genes is shown on the x-axis, and the q-values of ≤ 0.05 are considered significant and plotted accordingly.
Figure 3
Figure 3
Evaluation results of complex karyotype signature (CKS) classification performance and prognostic impact. LOOCV-estimated AUC of CKS score for predicting CK in the training cohort (a) and validation cohort (b). (c) Kaplan–Meier curves against overall survival (OS) according to CK (orange line) and non-CK (green line) in KUMC (left), TCGA (middle), and BeatAML (right) cohorts. (d) Kaplan–Meier curves against OS according to predicted as CK by CKS (orange line) and non-CKS (green line) in KUMC (left), TCGA (middle), and BeatAML (right) cohorts.
Figure 4
Figure 4
SOD1 inhibitor treatment leads to reduction in AML cell proliferation. (a) Superoxide dismutase (SOD) enzymatic activity (units/mL) measured after treatment with various concentrations (0, 1, 2.5, and 5 μM) of LCS-1 in HL-60. (b) Cell viability (%) measured after treatment with different concentrations (0, 0.1, 0.5, 1, and 2.5 μM) of LCS-1. (c) The production of dead cells detected by fluorescence intensity measured after treatment with LCS-1 and staining with PI. (d) The production of intracellular reactive oxygen species (ROS) detected by fluorescence intensity measured after treatment with LCS-1 and staining with DCFDA. (e) The production of mitochondrial ROS detected by fluorescence intensity measured after treatment with LCS-1 and staining with mitoSOX. The concentrations of LCS-1 used for (ce) are the same as the concentrations used in b. Bar graphs show mean ± SD of fluorescence intensity quantified by ImageJ. Scale bar represents 100 μm. Statistical analysis: * p < 0.05; ** p < 0.01; *** p < 0.001 vs. untreated control cells.

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