Molecular Markers of Response to Chemoradiation in Localized Esophageal Cancer

描述（由申请方提供）：本提案的总体目标是确定治疗前活检标本中发现的分子标志物是否可以预测接受术前放化疗（CTRT）的食管癌（EC）患者的病理完全缓解（pathCR）。PathCR定义为切除标本中无残留癌。EC患者的5年生存率<20%。局限性癌（II或III期）通常采用术前CTRT治疗，但这种经验性方法导致异质性且通常不可预测的结果。大约25%的患者达到pathCR，并且倾向于比达到<pathCR的75%的患者存活更长时间（即，有残余癌）。目前的临床参数不能可靠地预测治疗结果，并且修改CTRT类型对pathCR患者的比例几乎没有影响。此外，术前CTRT和手术具有可怕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结局的主要障碍。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患者中进行了初步研究。在一项19名患者的初步分析研究中，使用了Affytron U133 A基因芯片。在微阵列中，无监督分层聚类分析将患者的癌症分成两个亚组（6个pathCR中的5个聚类在亚型I中，6个pathCR中的1个聚类在亚型II中）。这些数据表明pathCR可能基于分子标记从<pathCR分离，但我们的数据需要在更大的患者样本中确认。在扩展的队列中，我们还可以找到一种用于预测pathCR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，以评估是否可以实现pathCR的高（e80%）阳性预测值。该提案的具体目标是1。确定120例接受术前放化疗的食管癌患者的基因表达谱。2：通过120例患者的基因表达谱构建对pathCR具有高阳性预测值的统计模型。建模将包括：（a）通过高度同质的基因表达谱鉴定食管癌亚型;（B）基于2（a）中定义的食管癌亚型以及同质治疗亚组的特异性，构建pathCR预测模型。我们尝试基于分子生物学的个体化患者治疗可以为有效治疗的管理铺平道路，提高安全性，并保留某些患者的食管。公共卫生相关性：该提案是食管癌患者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，以便在某些患者中进行有效的治疗，提高安全性并保留食管。

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.