Molecular Markers of Response to Chemoradiation in Localized Esophageal Cancer

描述(由申请人提供)：这项建议的总体目标是确定在预处理活检标本中发现的分子标记物是否可以预测接受术前化疗(CTRT)的食道癌(EC)患者的病理完全缓解(PATCR)。路径CR被定义为切除的标本中没有残留的癌。EC患者的5年存活率为20%。局限性癌(II期或III期)通常在术前接受CTRT治疗，但这种经验性的方法会导致不同的结果，而且往往是不可预测的。大约25%的患者实现了路径CR，并且往往比75%实现路径CR(即有残留癌症)的患者存活得更长。目前的临床参数不能可靠地预测治疗结果，改变CTRT的类型对路径CR患者的比例影响很小。此外，术前的CTRT和手术有严重的毒性和改变生活的后果。缺乏个体化治疗的能力是改善患者预后的主要障碍。通过了解这种癌症的分子生物学，可能会出现一种合理的个体化治疗方法。为此，我们在EC患者中进行了一项初步研究。在一项使用Affymetrix U133A基因芯片的19名患者的试点简档研究中。微阵列，无监督的层级聚类分析将患者的癌症分成两个亚组(6个通路CR中有5个聚集在亚型I中，1个在亚型II中)。这些数据表明，根据分子标记，路径CR可能与路径CR分离，但我们的数据需要在更大的患者样本中得到证实。在扩大的队列中，我们还可能发现用于预测路径CR的改进模型，该模型本身需要验证。我们建议评估120名患者的基因表达谱，以评估是否可以获得较高(E80%)的路径CR阳性预测值。该建议的具体目的是：1.确定120例食道癌患者术前放化疗新队列的基因表达谱。2.根据120例患者的基因表达谱，建立具有较高阳性预测值的统计模型。建模将包括：(A)通过高度同质性的基因表达谱识别食道癌的亚型；(B)根据2(A)中所定义的食道癌亚型以及均质治疗亚组中的特定亚型，建立路径CR预测模型。我们基于分子生物学对患者进行个体化治疗的尝试，可以为在一些患者中实施有效的治疗、提高安全性和保护食道铺平道路。公共卫生相关性：这项建议是对食道癌患者进行基于分子生物学的个体化治疗的早期尝试。我们的目标是为未来的策略铺平道路，该策略将允许对一些患者进行有效的治疗，提高安全性，并保留食道。

DESCRIPTION (provided by applicant): The overall goal of this proposal is to determine if molecular markers found in pretreatment biopsy specimens can predict pathologic complete response (pathCR) in patients with esophageal cancer (EC) undergoing preoperative chemoradiation (CTRT). PathCR is defined as no residual carcinoma in a resected specimen. Patients with EC have a 5-year survival rate of <20%. Localized carcinoma (stage II or III) is frequently treated with preoperative CTRT, but this empirical approach results in heterogeneous and often unpredictable outcomes. Approximately 25% of patients achieve a pathCR and tend to survive longer than do the 75% who achieve <pathCR (i.e., have residual cancer). Current clinical parameters do not reliably predict outcome from therapy and modifying the type CTRT has little impact on the proportion of patients with a pathCR. Moreover, preoperative CTRT and surgery have dire toxicity and life altering consequences. This lack of ability to individualize therapy is a major obstacle in improving patient outcomes. A rational approach to individualized therapy is likely to occur through understanding the molecular biology of this cancer. To that aim, we conducted a preliminary study in EC patients. In a 19-patient pilot profiling study using Affymetrix U133A GeneChip. microarray, unsupervised hierarchical cluster analysis segregated patient's cancers into two subgroups (5 of 6 pathCR clustered in subtype I and 1 of 6 in subtype II). These data suggest that pathCR might segregate from <pathCR based on molecular markers but our data needs confirmation in a larger patient sample. In an expanded cohort, we may also find an improved model for predicting pathCR which would itself require validation. We propose to assess the gene expression profile of 120 patients to assess if a high (e80%) positive predictive value for pathCR can be achieved. The Specific Aims of the proposal are 1. Determine the gene expression profile of the new cohort of 120 patients with esophageal cancer treated with preoperative chemoradiation. 2: Construct statistical models that have a high positive predictive value for pathCR by the gene expression profile of 120 patients. The modeling will include: (a) Identification of subtypes of esophageal cancer by gene expression profiles that are highly homogeneous; (b) Build pathCR prediction models based on specific to subtypes of esophageal cancer as defined in 2(a) and also in the homogeneously treated subgroups. Our attempts to individualize patient's therapy based on molecular biology can pave the way to allow administration of effective therapy, improve safety, and preserve the esophagus in some patients. PUBLIC HEALTH RELEVANCE: This proposal is an early attempt to individualize therapy based on molecular biology for patients with esophageal cancer. Our goal is to pave the way for a strategy in the future that will allow administration of effective therapy, improve safety, and preserve the esophagus in some patients.