Purpose: The molecular complexity of acute myeloid leukemia (AML) presents a considerable challenge to implementation of clinical genetic testing for accurate risk stratification. Identification of better biomarkers therefore remains a high priority to enable improving established stratification and guiding risk-adapted therapy decisions. Experimental Design: We systematically integrated and analyzed the genome-wide CRISPR-Cas9 data from more than 1,000 in vitro and in vivo knockout screens to identify the AML-specific fitness genes. A prognostic fitness score was developed using the sparse regression analysis in a training cohort of 618 cases and validated in five publicly available independent cohorts (n = 1,570) and our RJAML cohort (n = 157) with matched RNA sequencing and targeted gene sequencing performed. Results: A total of 280 genes were identified as AML fitness genes and a 16-gene AML fitness (AFG16) score was further generated and displayed highly prognostic power in more than 2,300 patients with AML. The AFG16 score was able to distill downstream consequences of several genetic abnormalities and can substantially improve the European LeukemiaNet classification. The multi-omics data from the RJAML cohort further demonstrated its clinical applicability. Patients with high AFG16 scores had significantly poor response to induction chemotherapy. Ex vivo drug screening indicated that patients with high AFG16 scores were more sensitive to the cell-cycle inhibitors flavopiridol and SNS-032, and exhibited strongly activated cell-cycle signaling. Conclusions: Our findings demonstrated the utility of the AFG16 score as a powerful tool for better risk stratification and selecting patients most likely to benefit from chemotherapy and alternative experimental therapies.

中文翻译：

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大规模体外和体内 CRISPR-Cas9 敲除筛选确定 16 基因健康评分，以改进急性髓系白血病的风险评估

目的：急性髓系白血病 (AML) 的分子复杂性对实施临床基因检测以进行准确的风险分层提出了相当大的挑战。因此，识别更好的生物标志物仍然是改善既定分层并指导风险适应治疗决策的重中之重。实验设计：我们系统地整合和分析了来自 1,000 多个体外和体内敲除筛选的全基因组 CRISPR-Cas9 数据，以识别 AML 特异性的适应基因。在 618 例训练队列中使用稀疏回归分析得出预后健康评分，并在五个公开可用的独立队列 (n = 1,570) 和我们的 RJAML 队列 (n = 157) 中进行验证，并进行匹配的 RNA 测序和靶向基因测序。结果：总共有 280 个基因被鉴定为 AML 适应性基因，并进一步生成了 16 基因 AML 适应性（AFG16）评分，并在 2,300 多名 AML 患者中显示出高度的预后能力。AFG16 评分能够提取多种遗传异常的下游后果，并可以显着改进欧洲白血病网分类。RJAML 队列的多组学数据进一步证明了其临床适用性。AFG16 评分高的患者对诱导化疗的反应明显较差。离体药物筛选表明，AFG16 评分高的患者对细胞周期抑制剂黄吡醇和 SNS-032 更敏感，并表现出强烈激活的细胞周期信号传导。结论：