Genetic Progression Factors in Multiple Myeloma and MGUS

描述（由申请人提供）：该项目的长期目标是确定导致骨髓瘤疾病进展的突变，并根据个体患者的基因型制定治疗策略。多发性骨髓瘤（MM）占美国所有癌症死亡人数的2%，占黑人/非裔美国人所有癌症死亡人数的3%。通过与华盛顿大学基因组测序中心（GSC）的合作，我们建议扩展我们目前的突变谱分析，以更好地了解MM的疾病进展。我们将通过对候选基因进行大规模外显子重测序，利用MM患者的骨髓和皮肤（种系）DNA来确定肿瘤基因型。该项目的R21阶段将开发转化研究基础设施，并解决与突变分析相关的技术问题。(1)我们将在我们的综合临床数据库中收集巴恩斯/犹太医院/Siteman癌症中心所有被诊断为多发性骨髓瘤（MM）患者的流行病学数据、疾病相关特征、预后因素、治疗信息和结果。（2A）我们将定义基于phi29聚合酶全基因组扩增（WGA）基因组DNA重测序可实现的突变检测阈值水平。（2B）我们将从46例新诊断的MM患者中收集和储存富含cd138的骨髓瘤细胞和匹配的皮肤活检样本的基因组DNA，并将对通常（10）个候选细胞因子信号基因（NRAS、KRAS、FGFR3、ARAF、RAF1、PTPN11、PIK3CA、LTK、INSR和MERTK）进行完整的外外子重测序。在完成确定的里程碑后，该项目的R33阶段将进行以下目标：(3)我们将使用细胞系转化试验和使用小鼠骨髓转导/移植的疾病模型，对在骨髓瘤患者样本中发现的新的功能获得突变进行功能表征。(4)我们将通过对骨髓瘤患者在疾病进展的不同阶段收集的样本进行细胞因子信号基因突变的高通量重测序来验证突变谱的临床应用。这些目标的实现将提供必要的数据，以检验需要在合作小组环境中大量患者的其他假设。到目前为止，测序分析一直是一种相对未充分利用的工具，但它是一组基因组技术（包括表达微阵列和蛋白质组学）的关键组成部分，这些技术将有助于改善骨髓瘤患者的预后。

DESCRIPTION (provided by applicant): The long-term goal of this project is to identify mutations that contribute to myeloma disease progression and to develop treatment strategies based on individual patient genotypes. Multiple myeloma (MM) accounts for 2% of all cancer deaths in the United States and 3% of all cancer deaths in black/African-Americans. In collaboration with the Washington University Genome Sequencing Center (GSC), we propose to extend our current mutational profiling analyses to better our understanding of disease progression in MM. We will define tumor genotypes using bone marrow and skin (germline) DNA from patients with MM using largescale exonic re-sequencing of candidate genes. The R21 phase of this project will develop the translational research infrastructure and solve technical issues associated with mutational profiling. (1) We will capture epidemiological data, disease-related characteristics, prognostic factors, therapeutic information and outcomes for all patients diagnosed with multiple myeloma (MM) seen at the Barnes/Jewish Hospital/Siteman Cancer Center in our comprehensive clinical database. (2A) We will define the threshold level of mutation detection achievable by re-sequencing based on phi29 polymerase-whole genome amplified (WGA) genomic DNA. (2B) We will collect and bank genomic DNA from CD138-enriched myeloma cells and matched skin biopsy samples from 46 patients with newly diagnosed MM and will perform complete exonic re-sequencing often (10) candidate cytokine signaling genes (NRAS, KRAS, FGFR3, ARAF, RAF1, PTPN11, PIK3CA, LTK, INSR, and MERTK). Upon completion of defined milestones, the R33 phase of this project proceed with the following Aims: (3) We will functionally characterize novel gain-of-function mutations, identified in myeloma patient samples, using cell line transformation assays and in a disease model using murine bone marrow transduction/transplantation. (4) We will validate the clinical utility of mutation profiling by high-throughput re-sequencing of cytokine signaling gene mutations in myeloma patient samples collected at distinct stages of disease progression. Accomplishment of these Aims will provide the data necessary to test additional hypotheses requiring larger numbers of patients in a cooperative group setting. Sequencing analysis has, until now, been a relatively underutilized tool, but is a crucial component of a set of genomic technologies (including expression microarrays and proteomics) that will be required to improve outcome in myeloma patients.