Prognostic and predictive gene sets in HER2-positive breast cancer:The HERA Trial

描述（由申请人提供）：基于雌激素受体（ER）、孕激素受体（PR）和人表皮生长因子受体2（HER 2）的联合表达，乳腺癌的主要亚组在乳腺癌病因学、处方的全身治疗、此类治疗的有效性以及复发和生存结局方面具有重要意义。HER 2阳性亚型占所有浸润性乳腺癌的15-25%，是一种高度侵袭性的亚型。在靶向治疗之前，HER 2+肿瘤预示着一些最严重的疾病。曲妥珠单抗（赫赛汀（r））的开发已显著改善了HER 2+乳腺癌女性的结局。HERA是一项在已完成辅助化疗的HER 2+原发性乳腺癌女性中比较1年和2年曲妥珠单抗与无曲妥珠单抗的随机化三组多中心研究，结果表明接受2年曲妥珠单抗治疗的HER 2阳性乳腺癌女性的无病生存期显著改善。TransHERA是HERA的补充，旨在收集、储存和分析HERA试验中所有患者的乳腺癌组织和血清。总体而言，TransHERA旨在鉴定可能导致乳腺癌治疗新靶点的蛋白质、遗传和分子因素，或更好地了解与曲妥珠单抗治疗反应差异可能性相关的分子特征。我们的目标是通过分子特征分析确定基因特征，从而选择最有可能从HER 2靶向治疗中获益的患者。为了实现这些目标，我们计划以下内容：具体目标1：在cDNA介导的退火、选择、延伸和连接（DASL）平台上对HERA III期临床试验的FFPE标本进行表达谱分析，以确定HER 2+早期乳腺癌患者中曲妥珠单抗预后结局和疗效预测的生物标志物。将对从HERA临床试验的约1，000份FFPE样本制备的RNA进行DASL分析。监督主成分分析的变体将用于识别差异治疗效应并开发预测模型。将根据其预测结局（总体或治疗组内）的能力选择特征基因集，并使用DFS作为主要终点和总生存期（OS）作为次要终点预测曲妥珠单抗改善的结局。将通过qRT-PCR验证潜在生物标志物。预测性生物标志物将在后续研究中进行前瞻性验证。公共卫生相关性：HER 2阳性亚型占所有浸润性乳腺癌的15-25%，是一种预后不良的高度侵袭性肿瘤。曲妥珠单抗（赫赛汀（r））的开发改善了大多数HER 2+乳腺癌女性的生存期;然而，仍有一定比例的女性没有获得明显的益处。我们假设，癌症相关基因的特定特征的变化可以预测乳腺癌治疗的反应性;因此，我们将研究可能导致个体间治疗反应差异的肿瘤特征。

DESCRIPTION (provided by applicant): The major subgroups of breast cancer, based on combined expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), have important implications in breast cancer etiology, systemic therapies prescribed, effectiveness of such therapies, and both recurrence and survival outcomes. The HER2-positive subtype comprises 15-25% of all invasive breast cancers, and is a highly aggressive subtype. Prior to targeted therapy, HER2+ tumors portended some of the worst prognoses. The development of trastuzumab (Herceptin(r)) has resulted in marked improvement in outcomes for women with HER2+ breast cancers. HERA, a randomized three-arm multi-centre comparison of 1 year and 2 years of trastuzumab versus no trastuzumab in women with HER2+ primary breast cancer that have completed adjuvant chemotherapy, demonstrated a significant improvement in disease-free survival among women with HER2-positive breast cancer who received 2 years of trastuzumab. TransHERA, a supplement to HERA, aims to collect, store and analyze breast cancer tissue and serum from all patients in the HERA trial. Overall, TransHERA aims to allow identification of protein, genetic and molecular factors that might lead to new targets for the treatment of breast cancer or to a better understanding of the molecular characteristics that are associated with the differential likelihood of response to trastuzumab therapy. Our objective is to identify gene signature(s) through molecular profiling that will allow for the selection of patients most likely to derive benefit from HER2-directed therapies. To meet these goals we plan the following: Specific Aim 1: To conduct expression profiling of FFPE specimens from the HERA phase III clinical trial on the cDNA-mediated Annealing, Selection, extension and Ligation (DASL) platform in order to identify biomarkers prognostic of outcome and predictive of response to trastuzumab in HER2+early breast cancer patients. DASL analysis will be performed on RNA prepared from ~1,000 FFPE samples from the HERA clinical trial. A variation of supervised principal component analysis will be used for identifying differential treatment effect and developing a predictive model. A signature set of genes will be selected based upon their ability to prognosticate outcome (overall or within a treatment arm) and predict improved outcome with trastuzumab using DFS as the primary endpoint and overall survival (OS) as the secondary endpoint. Potential biomarkers will be validated by qRT-PCR. Predictive biomarkers will be prospectively validated in a subsequent study. PUBLIC HEALTH RELEVANCE: The HER2-positive subtype comprises 15-25% of all invasive breast cancers, and is a highly aggressive tumor with a poor prognosis. The development of trastuzumab (Herceptin(r)) has resulted in improvements of survival for most women with HER2+ breast cancers; however; a percentage of women still receive no appreciable benefit. We hypothesize that variations in specific characteristics of cancer-related genes could predict responsiveness to breast cancer therapy; therefore, we will investigate tumor features that may contribute to inter-individual variability of response to treatment.