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

描述(申请人提供)：在关键的III期试验E2100中，在标准化疗的基础上加用贝伐单抗延长了之前未经治疗的转移性乳腺癌妇女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并没有转化为总体生存(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体验到最佳的益毒比。我们最近证实血管内皮生长因子-A(VEGFA)基因(贝伐单抗的靶点)的扩增和缺失在原发性乳腺癌中相对常见。我们之前还在VEGFA中发现了两个单核苷酸多态(SNPs)，它们强烈预测了中位OS的改善，以及另外两个SNPs，它们预测了在E2100中接受贝伐单抗治疗转移性乳腺癌时，对高血压的保护作用。自这一发现以来，其他非VEGFA SNPs与实施贝伐单抗的其他随机III期试验的结果相关。具体目标1：肿瘤VEGFA扩增或边缘扩增(估计14%的频率)将预测E2100中接受贝伐单抗治疗的转移性乳腺癌患者的较好结果，而VEGFA缺失的患者(估计11%的频率)将预测较差的结果。我们还假设VEGFA扩增/缺失不能预测E2100对照臂的结果。具体目标#2：证明VEGFA单倍型和其他候选SNP将预测在E2100接受贝伐单抗治疗的转移性乳腺癌患者的更好结果(但不是对照组)。具体目标3：根据肿瘤特异性变异(VEGFA扩增/缺失)和宿主特异性变异(SNPs)计算的组合算法将最佳地预测贝伐单抗在E2100的结果(疗效)。影响：贝伐单抗是一种治疗乳腺癌的高活性药物，但并不是所有的患者都受益，而且有一些实质性的毒性，包括：中风和高血压。不幸的是，没有经过验证的生物标记物来指示哪些患者应该接受这种药物。此外，非选择性地实施贝伐单抗对美国卫生保健系统有重大的负面财务影响。这项提议有可能公布一种预测性签名，它将选择应该接受贝伐单抗治疗的亚组。 公共卫生相关性：尽管在E2100试验中，贝伐单抗的应答率和中位无进展存活率有明显改善，但添加贝伐单抗并没有显著提高中位总存活率，并增加了3/4级毒性，包括脑血管缺血、头痛、蛋白尿和高血压。因此，找到一种能够成功预测单个患者的最大益处但毒性最小的特征，并允许选择不应接受治疗的亚组是临床任务。在这项提案中，我们计划研究胚系变异(候选SNPs)和肿瘤特异性变异(VEGFA扩增/缺失)作为贝伐单抗在E2100中的潜在生物标志物的作用。

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.