Gene expression profiling vs MRD assessment in Myeloma

描述（由申请人提供）：骨髓瘤治疗取得了重大进展，包括10年无事件生存期（EFS）达到20%。然而，这种疾病在很大程度上仍然无法治愈，骨髓瘤的预后很难预测。目前还没有可靠的早期替代指标来预测长期预后，从而可以调整个别患者的治疗以避免过度或不充分的治疗。为了进一步改善预后，我们必须有更好的工具来测量强化治疗后肿瘤缩小的程度，并更好地了解骨髓瘤特异性与生存差或良好相关的遗传特征。根据目前的定义，完全缓解（CR）不能很好地反映肿瘤负荷，部分原因是骨髓瘤的局灶性以及CR对骨髓瘤(M)蛋白测量的严重依赖，我们知道每个骨髓瘤细胞的免疫球蛋白产生在患者间和患者内部存在主要的可变性。我们假设预测治疗结果不仅取决于对治疗后剩余肿瘤负荷的准确评估，还取决于个体骨髓瘤细胞的遗传特征。在Aim 1中，我们将使用CDR3-PCR技术确定高风险骨髓瘤患者（即首次移植后2年内复发）和低风险骨髓瘤患者（即EFS 4年）串联移植后的肿瘤负荷。我们将评估随机骨髓和外周血中的微小残留疾病（MRD），以及通过MRI/PET扫描确定的局灶性病变。在Aim 2中，我们将确定与早期进展和长期缓解的高风险相关的基因表达谱（GEP），并描述其组成基因和分子途径。我们还将构建经过验证的预测模型。GEP将在基线、诱导治疗后、复发时以及持续缓解的局灶性MRI/PET病变时进行。这将使我们能够评估在诊断时是否已经存在一个主要的耐药克隆，诱导治疗是否选择出一小部分耐药骨髓瘤细胞亚克隆，或者耐药骨髓瘤是否主要作为治疗的结果而发展。与不良结果相关的关键基因因此被识别和验证，可以通过特定的新疗法来维持缓解。区分绝对肿瘤缩小与遗传特征作为治疗失败的主要原因的重要性，以及在基线、随访和复发时解剖遗传特征，将为骨髓瘤的进展提供宝贵的信息。然后，这些信息可用于应用更好的治疗方法，确保一些患者（低风险）不被过度治疗，而其他患者（高风险）得到充分治疗。这些发现可以作为其他慢性淋巴增生性和骨髓增生性恶性肿瘤治疗方法的模型，这些肿瘤表现出类似的疾病进展。

DESCRIPTION (provided by applicant): Significant progress has been made in myeloma therapy, including >20% 10 year event-free survival (EFS). However, the disease remains largely incurable, and outcome in myeloma is difficult to predict. There is no reliable early surrogate marker for long-term outcome that would allow adjustment of treatment in an individual patient to avoid excessive or inadequate treatment. To further improve outcome, we must have better tools to measure the degree of tumor reduction after intensive therapy and a better understanding of the myeloma-specific genetic features related to poor or excellent survival. As currently defined, complete remission (CR) is a poor reflection of tumor load, due in part to the focal nature of myeloma and the heavy reliance of CR on myeloma (M) protein measurements, knowing that there is a major inter- and intra-patient variability in immunoglobulin production per myeloma cell. We hypothesize that predicting treatment outcome will not only depend on accurate assessment of the remaining tumor load after therapy, but also on genetic characteristics of an individual's myeloma cells. In Aim 1, we will determine the tumor burden after tandem transplants using CDR3-PCR technology in patients with high-risk myeloma (i.e., relapsing during the first 2 years after the first transplant) and in patients with low-risk myeloma (i.e., EFS >4 years). We will assess minimal residual disease (MRD) in random bone marrow and in peripheral blood as well as in focal lesions identified by MRI/PET scan. In Aim 2, we will identify the gene expression profile (GEP) associated with high risk of early progression versus prolonged remission and describe its component genes and molecular pathways. We will also construct validated prediction models. GEP will be performed at baseline, after induction therapy, and at relapse, as well as on focal MRI/PET lesions persisting in remission. This will allow us to evaluate whether a major resistant clone is already present at diagnosis, whether induction therapy acts to select out a small subclone of resistant myeloma cells, or whether resistant myeloma develops mainly as the consequence of treatment. Key genes related to poor outcome that are thus identified and validated can be targeted by specific novel therapies to maintain remissions. Distinction between the importance of absolute tumor reduction versus genetic characteristics as the major cause of treatment failure and dissecting genetic characteristics at baseline, follow-up, and relapse will provide invaluable information about the progression of myeloma. This information could then be used to apply better treatment approaches, ensuring some patients (low-risk) are not over-treated and others (high-risk) receive adequate treatment. These findings can serve as a model for treatment approaches in other chronic lymphoproliferative and myeloproliferative malignancies, which exhibit a similar disease progression.