Radiogenomic Biomarkers of Breast Cancer Recurrence

项目摘要 我们项目的主要目标是调查多模式乳房成像在预测预后中的附加值。 对乳腺癌的评估。准确的预后评估是个体化治疗的关键组成部分。 乳腺癌的预后历来是基于肿瘤的组织病理学(即，大小，分级， 免疫组织化学(即雌激素、孕激素、人表皮生长因子受体)。 最近，分子检测也变得可行(即OncotypeDX、MammaPrint等)，以测量 肿瘤基因表达与预后相关。虽然已经取得了很大进展，但仍有必要 在识别因过度或不充分而有发病风险的妇女方面取得实质性进展 积极的治疗。目前主要分析肿瘤的组织病理学和分子特征。 基于选择性组织采样。随着人们越来越多地认识到肿瘤内的异质性对 在肿瘤进展和耐药中的重要作用，选择性组织采样可能不充分 完全捕获这种异质性，潜在地导致用于指导治疗的信息不完整。 成像越来越多地用于乳腺癌的筛查、诊断和治疗的常规护理中， 提供补充信息的不同模式。这种能力，再加上高分辨率的潜力 3D可视化为捕捉体内肿瘤异质性的重要方面提供了一种新的手段，并且 因此，潜在的互补预后信息。我们研究的首要目标是解决 这个基本问题：肿瘤成像表型能否为已建立的 预测乳腺癌复发的组织病理学和新兴分子标志物？我们建议 四个目标：1)开发一种多模式成像表型载体，其捕获结构(例如，形状， 原发肿瘤的形态、质地)和功能异质性(如对比剂摄取)。AIM2)确定 影像特征在预测乳腺癌复发中的预后价值 也将进行探索。AIM3)开发包含肿瘤的增强复发风险评估模型 具有标准肿瘤组织病理学和新兴分子标志物的影像特征，以及AIM4)执行 使用预期收集的数据对我们的模型进行独立验证。在我们的研究中，我们将调查 多模式成像对诊断为原发性浸润性乳腺癌的妇女的预后价值。我们会 利用在我们的NIH完成的一项NIH试验的成像和肿瘤组织生物标记物数据的女性队列 目前可从该机构获得从最初诊断和治疗开始的10年随访。最终， 通过将影像与肿瘤组织病理学和分子标志物相结合，增加复发风险 我们的评估工具将能够帮助更好地指导被诊断为乳腺癌的女性的治疗决定 癌症。此外，考虑到多模式成像作为常规临床护理的一部分越来越多地使用，我们的 这项研究可以提供新的成像生物标记物来改善治疗决策，而额外成本最低。

Project Summary The main goal of our project is to investigate the added value of multi-modality breast imaging in prognostic assessment for breast cancer. Accurate prognostic assessment is a key component of personalized treatment. Breast cancer prognosis has historically been determined based on tumor histopathology (i.e., size, grade, stage, etc) and immunohistochemistry (i.e., estrogen, progesterone, human epidermal growth factor receptors). Recently, molecular assays have also become available (i.e., OncotypeDX, MammaPrint, etc) that measure tumor gene expression as related to prognosis. Although a lot of progress has been made, there is still a need for substantial improvements in identifying women who are at risk for morbidity due to overly or insufficiently aggressive therapy. Currently, histopathology and the molecular characteristics of tumors are mainly analyzed based on selective tissue sampling. As it is increasingly recognized that intra-tumoral heterogeneity plays an important role in tumor progression and resistance to treatment, selective tissue sampling may be inadequate for fully capturing such heterogeneity, potentially resulting in incomplete information for guiding treatment. Imaging is increasingly used in routine care for screening, diagnosis, and treatment of breast cancer, with different modalities offering complementary information. This ability, coupled by a potential for high-resolution 3D visualization, has provided a new means for capturing vital aspects of tumor heterogeneity in-vivo, and therefore potentially complementary prognostic information. The overarching goal of our study is to address this fundamental question: Can tumor imaging phenotypes provide additional information to established histopathologic and emerging molecular markers for predicting breast cancer recurrence? We propose four aims: AIM1) Develop a multi-modality imaging phenotype vector that captures structural (e.g., shape, morphology, texture) and functional heterogeneity (e.g., contrast uptake) of primary tumors. AIM2) Determine the prognostic value of the imaging features in predicting breast cancer recurrence; predictive value of features will also be explored. AIM3) Develop an augmented recurrence risk assessment model that incorporates tumor imaging features with standard tumor histopathology and emerging molecular markers, and AIM4) Perform independent validation of our model with prospectively collected data. In our study, we will investigate the prognostic value of multi-modality imaging for women diagnosed with primary invasive breast cancer. We will utilize a cohort of women with imaging and tumor tissue biomarker data from an NIH trial completed at our institution, from which 10-year follow-up from initial diagnosis and treatment is currently available. Ultimately, by integrating imaging with tumor histopathology and molecular markers in an augmented recurrence risk assessment tool we will be able to help better guide treatment decisions for women diagnosed with breast cancer. Also, considering that multi-modality imaging is increasingly used as part of routine clinical care, our study could provide new imaging biomarkers to improve treatment decisions, at a minimal additional cost.