Novel Biomarkers to Risk-Stratify AML Patients with NPM1^Pos/FLT3-IT^Neg Genotype

 描述（由申请人提供）：急性髓性白血病（AML）是最常见的造血系统恶性肿瘤之一，NPM 1突变和FLT 3/ITD是该疾病最具预后的两种生物标志物。携带NPM 1 Pos/FLT 3-ITDNeg基因型的患者约占新发AML病例的25%，目前被归类为风险较高。然而，这些患者中约40%在2年内未获得缓解或复发。我们假设具有NPM 1 Pos/FLT 3-ITDNeg基因型的AML原始细胞具有额外的预后生物标志物，可用于更准确地对具有该基因型的患者进行风险分层。因此，我们将检查具有这种基因型的AML患者的存活白血病原始细胞，以鉴定新的基因组、转录和蛋白质组预后生物标志物。然后，我们将开发结合这些生物标志物和其他预后因素的风险分层模型，并在独立的患者人群中验证这些风险分层模型。具体目标1。鉴定与NPM 1 Pos/FLT 3-ITDNeg基因型AML患者预后相关的新型分子生物标志物将从具有中等风险细胞遗传学和NPM 1 Pos/FLT 3-ITDNeg基因型的患者（N=131）中分离活AML原始细胞。采用创新方法的靶向DNA测序、全局RNA测序和质谱将用于鉴定与临床结果相关的DNA、转录本和蛋白质生物标志物。回归分析，整合分子数据和其他预后因素，将用于确定最具信息性的生物标志物，这些预后生物标志物将被纳入风险分层模型，用于估计总生存概率， 无复发生存率具体目标2。验证来自特定目标1的生物标志物更准确地对具有NPM 1 Pos/FLT 3-ITDNeg基因型的AML患者进行风险分层的能力。将开发风险分层模型中生物标志物的靶向测定。的设计细节 这些分析将取决于目标的特性并依赖于先前开发和优化的技术。然后，我们将在具有该基因型的AML患者的独立人群（N = 194）中检查生物标志物和风险分层模型。将通过估计AUC和c-统计量评价所采用风险分层模型的性能。 该提案的结果可能会导致为具有NPM 1 Pos/FLT 3-ITDNeg基因型的AML患者开发改进的风险分层模型。此外，确定的生物标志物可能具有超出该基因型的预后意义，未来的研究将检查这些发现对其他AML亚群的普遍性。此外，这些研究的全面性，从基因组到蛋白质组，将促进我们对预后生物标志物之间复杂相互作用的理解，为未来的生物标志物研究提供更明智和潜在的指导方法。

 DESCRIPTION (provided by applicant): Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies, with NPM1 mutations and FLT3/ITDs being two of the most prognostic biomarkers for this disease. Patients with the NPM1Pos/FLT3-ITDNeg genotype account for approximately 25% of de novo AML cases and are currently classified as better-risk. However, approximately 40% of these patients do not obtain a remission or relapse within 2 years. We hypothesize that AML blasts with the NPM1Pos/FLT3-ITDNeg genotype harbor additional prognostic biomarkers that can be used to more accurately risk-stratify patients with this genotype. Therefore, we will examine viable leukemic blasts from AML patients with this genotype to identify novel genomic, transcriptional and proteomic prognostic biomarkers. We will then develop risk-stratification models incorporating these biomarkers and other prognostic factors and validate these risk-stratification models in an independent population of patients. Specific Aim 1. Identify novel molecular biomarkers associated with prognosis in AML patients with the NPM1Pos/FLT3-ITDNeg genotype. Viable AML blasts will be isolated from patients with intermediate-risk cytogenetics and the NPM1Pos/FLT3-ITDNeg genotype (N=131). Targeted DNA sequencing, global RNA sequencing, and mass spectrometry employing an innovative approach will be used to identify DNA, transcript, and protein biomarkers that are associated with clinical outcomes. Regression analyses, integrating molecular data and other prognostic factors, will be used to identify the most informative biomarkers, and these prognostic biomarkers will be incorporated into risk-stratification models for estimating the probability of overall survival and relapse-free survival. Specific Aim 2. Validate the ability of the biomarkers from Specific Aim 1 to more accurately risk-stratify AML patients with the NPM1Pos/FLT3-ITDNeg genotype. Targeted assays for biomarkers in the risk- stratification models will be developed. The design specifics of these assays will depend upon the characteristics of the target and rely upon previously developed and optimized technology. We will then examine the biomarkers and risk-stratification models in an independent population of AML patients with this genotype (N = 194). The performance of the risk-stratification model(s) employing will be evaluated by estimating AUCs and c-statistics. The results from this proposal will likely lead to the development of improved risk-stratification model(s) for AML patients with the NPM1Pos/FLT3-ITDNeg genotype. In addition, identified biomarkers may have prognostic significance beyond this genotype, and future studies will examine the generalizability of these findings to other AML subpopulations. Furthermore, the comprehensive nature of these studies, spanning from the genome to the proteome, will advance our understanding of the complex interactions among prognostic biomarkers, leading to more informed and potentially directive approaches for future biomarker research.