VEGF Gene Amplification/Haplotype as Biomarkers for Bevacizumab in Breast Cancer

描述（由申请人提供）：在关键III期试验E2100中，在标准化疗中加入贝伐单抗比单独化疗延长了先前未治疗的转移性乳腺癌女性的中位无进展生存期（PFS）。这些发现导致FDA加速批准贝伐单抗联合紫杉醇作为转移性疾病的初始化疗。然而，E2100中优越的PFS并没有转化为总生存期（OS）的改善，许多患者经历了显著的药物相关毒性。不幸的是，目前还没有经过验证的生物标志物来帮助选择哪些患者将经历最佳的利毒比。我们最近证明血管内皮生长因子- a （VEGFA）基因（贝伐单抗的靶标）扩增和缺失在原发性乳腺癌中相对常见。我们之前还发现了VEGFA中的两个单核苷酸多态性（snp），这两个snp强烈预测了中位OS的改善，另外两个snp预测了在E2100年接受贝伐单抗治疗转移性乳腺癌时对显著高血压的保护。自该发现以来，其他非vegfa snp已与其他随机III期试验中实施贝伐单抗的结果相关。特异性目标#1：肿瘤VEGFA扩增或临界扩增（估计频率为14%）将预测转移性乳腺癌患者在E2100年接受贝伐单抗的良好结果，而VEGFA缺失（估计频率为11%）的患者将预测不良结果。我们还假设VEGFA扩增/缺失不能预测E2100对照组的结果。特定目标#2：证明VEGFA单倍型和其他候选snp将预测转移性乳腺癌患者在E2100接受贝伐单抗（但不适用对照组）的更好结果。特异性目标#3：根据肿瘤特异性变异性（VEGFA扩增/缺失）和宿主特异性变异性（snp）计算的组合算法将最佳地预测贝伐单抗在E2100中的预后（疗效）。作用：贝伐单抗是一种高活性的乳腺癌药物，但并不是所有患者都受益，而且有一些严重的毒性，包括：中风和高血压。不幸的是，没有经过验证的生物标志物来指导哪些患者应该接受这种药物。此外，贝伐单抗的非选择性实施对美国医疗保健系统具有显著的负面财务影响。这一建议有可能揭示一种预测性特征，它将选择一个应该接受贝伐单抗的亚组。

DESCRIPTION (provided by applicant):The addition of bevacizumab to standard chemotherapy prolonged the median progression free survival (PFS) over chemotherapy alone for women with previously untreated metastatic breast cancer in the pivotal phase III trial, E2100. These findings led to the FDA accelerated approval for bevacizumab in combination with paclitaxel as initial chemotherapy for metastatic disease. The superior PFS in E2100, however, did not translate into an improvement in overall survival (OS) and many patients experienced significant drug-related toxicities. Unfortunately there are no validated biomarkers to help select which patients will experience the optimal benefit to toxicity ratio. We recently demonstrated that vascular endothelial growth factor-A (VEGFA) gene (the target for bevacizumab) amplification and deletion is relatively common in primary breast cancers. We also previously identified two single nucleotide polymorphisms (SNPs) in VEGFA which predicted strongly for an improved median OS and two additional SNPs which predicted protection from significant hypertension when receiving bevacizumab for metastatic breast cancer in E2100. Since that finding, other non-VEGFA SNPs have been correlated with outcome in other randomized phase III trials implementing bevacizumab. Specific Aim #1: Tumor VEGFA amplification or borderline amplification (estimated 14% frequency) will predict superior outcome for patients with metastatic breast cancer receiving bevacizumab in E2100 whereas those with VEGFA deletion (estimated 11% frequency) will predict inferior outcome. We also hypothesize that VEGFA amplification/deletion will not predict outcome in the control arm of E2100. Specific Aim #2: To demonstrate that VEGFA haplotypes and other candidate SNPs will predict superior outcome for patients with metastatic breast cancer receiving bevacizumab in E2100 (but not for the control arm). Specific Aim #3: A combined algorithm calculated from tumor-specific variability (VEGFA amplification/deletion) and host-specific variability (SNPs) will optimally predict outcome (efficacy) with bevacizumab in E2100. Impact: Bevacizumab is a highly active agent in breast cancer but not all patients benefit and there are some substantial toxicities including: stroke and hypertension. Unfortunately there are no validated biomarkers that direct which patients should receive this agent. Additionally, non-selective implementation of bevacizumab has significant negative financial implications on the United States health care system. This proposal has the potential to unveil a predictive signature which will select a subgroup who should receive bevacizumab. PUBLIC HEALTH RELEVANCE: Despite demonstrating a clear improvement in response rate and median progression free survival in E2100, the addition of bevacizumab did not significantly improve median overall survival and increased grade 3/4 toxicity including: cerebrovascular ischemia, headaches, proteinuria, and hypertension. Thus, finding a signature that would successfully predict the most benefit but least toxicity for an individual patient and allow for the selection of the subgroup who should NOT receive therapy is a clinical mandate. In this proposal, we plan to study the role of germline variability (candidate SNPs) and tumor-specific variability (VEGFA amplification/ deletion) as potential biomarkers for bevacizumab in E2100.