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

 描述(申请人提供)：急性髓系白血病(AML)是最常见的血液系统恶性肿瘤之一，NPM1突变和Flt3/ITDS是两个最能预测该病预后的生物标志物。NPM1Pos/Flt3-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的患者。然而，这些患者中约有40%在两年内没有得到缓解或复发。我们假设，具有NPM1Pos/Flt3-ITDNeg基因的AML细胞具有额外的预后生物标志物，可以用来更准确地对具有该基因的患者进行风险分层。因此，我们将检测具有这种基因的AML患者存活的白血病母细胞，以确定新的基因组、转录和蛋白质组预后生物标记物。然后，我们将开发包含这些生物标记物和其他预后因素的风险分层模型，并在独立的患者群体中验证这些风险分层模型。具体目的1.寻找与NPM1Pos/Flt3-ITDNeg基因AML患者预后相关的新的分子生物学标志物。存活的AML原始细胞将从具有中等风险细胞遗传学和NPM1Pos/Flt3-ITDNeg基因的患者(N=131)中分离出来。靶向DNA测序、全球RNA测序和采用创新方法的质谱学将用于识别与临床结果相关的DNA、转录本和蛋白质生物标记物。回归分析，结合分子数据和其他预后因素，将被用来识别最具信息量的生物标志物，这些预后生物标志物将被纳入风险分层模型，以估计总体生存和 无复发生存。特定目的2.验证来自特定目的1的生物标志物对具有NPM1Pos/Flt3-ITDNeg基因的AML患者进行更准确的风险分层的能力。将开发风险分层模型中生物标记物的有针对性的分析方法。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，我们将在一个独立的AML患者群体中检查生物标记物和风险分层模型(N=194)。采用的风险分层模型(S)的性能将通过估计AUC和c-统计量来评估。这项建议的结果可能会导致针对NPM1Pos/Flt3-ITDNeg基因的AML患者改进的风险分层模型(S)的发展。此外，已识别的生物标记物可能具有超越该基因型的预后意义，未来的研究将检验这些发现对其他AML亚群的普适性。此外，这些研究的综合性，从基因组到蛋白质组，将促进我们对预后生物标记物之间复杂相互作用的理解，从而为未来的生物标记物研究提供更多的信息和潜在的指导性方法。

 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.