Chen Dechang, Liu Alvin J, Sheng Li, Liu Zhenqiu, Elcheva Irina
Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
Department of Cognitive Science, Case Western Reserve University, Cleveland, OH 44106, USA.
Diagnostics (Basel). 2025 Jun 3;15(11):1421. doi: 10.3390/diagnostics15111421.
While adult and pediatric acute myeloid leukemia (AML) exhibit genetic distinctions, investigating their common gene expression program is critical for understanding the fundamental biological mechanisms that drive diverse cellular responses. However, existing gene signatures, predominantly tailored for overall survival (OS), may not adequately forecast event-free survival (EFS). EFS represents the time patients survive without disease recurrence, progression, or further treatment, a crucial metric for evaluating drug efficacy and assessing the clinical benefits of treatment. We performed an integrated analysis of adult TCGA and pediatric TARGET expression datasets to pinpoint genes and pathways associated with EFS in both adult and pediatric AML. Additionally, we constructed a predictive model using one dataset and validated it on the other to unveil a novel gene signature. A five-gene signature comprising F2RL3, IL2RA, MYH15, SIX3, and SOBP was identified for EFS for both adult and pediatric AML. The test Area Under the ROC Curves (AUCs) for the 2-year and 5-year cutoffs of adult TCGA data were 0.851 (95% CI (Confidence Interval): 0.778-0.923) and 0.848 (95% CI: 0.729-0.968), respectively. Similarly, the test AUCs for the 2-year and 5-year cutoffs of Pediatric TARGET data were 0.725 (95% CI: 0.640-0.811) and 0.695 (95% CI: 0.59-0.80), respectively. When patients were stratified into three equal-sized prognostic subtypes based on the five-gene test risk scores, the P-values of tertile partitions for TARGET and TCGA data were 2.32e-6 and 5.12e-14, respectively, indicating superior performance compared to cytogenetic risk stratification within the same data (TARGET: P = 0.0019; TCGA: P = 0.0086). Despite being identified for EFS, the five-gene signature successfully stratified patients into distinct OS groups across two additional independent datasets. This five-gene signature demonstrates robust performance in both EFS and OS risk prediction and might be clinically significant.
虽然成人和儿童急性髓系白血病（AML）表现出基因差异，但研究它们共同的基因表达程序对于理解驱动不同细胞反应的基本生物学机制至关重要。然而，现有的基因特征主要是针对总生存期（OS）定制的，可能无法充分预测无事件生存期（EFS）。EFS代表患者在无疾病复发、进展或进一步治疗的情况下存活的时间，是评估药物疗效和评估治疗临床益处的关键指标。我们对成人TCGA和儿童TARGET表达数据集进行了综合分析，以确定与成人和儿童AML中EFS相关的基因和通路。此外，我们使用一个数据集构建了一个预测模型，并在另一个数据集上进行了验证，以揭示一种新的基因特征。确定了一个由F2RL3、IL2RA、MYH15、SIX3和SOBP组成的五基因特征用于成人和儿童AML的EFS预测。成人TCGA数据2年和5年截断值的ROC曲线下面积（AUC）测试值分别为0.851（95%置信区间（CI）：0.778 - 0.923）和0.848（95%CI：0.729 - 0.968）。同样，儿童TARGET数据两年和5年截断值的测试AUC分别为0.725（95%CI：0.640 - 0.811）和0.695（95%CI：0.59 - 0.80）。当根据五基因测试风险评分将患者分为三个大小相等的预后亚组时，TARGET和TCGA数据三分位数划分的P值分别为2.32e - 6和5.12e - 14，表明与同一数据内的细胞遗传学风险分层相比具有更好的性能（TARGET：P = 0.0019；TCGA：P = 0.0086）。尽管该五基因特征是为EFS确定的，但它成功地将患者在另外两个独立数据集中分为不同的OS组。这种五基因特征在EFS和OS风险预测中均表现出强大的性能，可能具有临床意义。
