Delineation of Leukocyte Biomarkers for Human Breast Cancer Outcome

许多实验和临床研究表明，促进肿瘤发展的白细胞基本上调节了癌症发展的各个方面。然而，与发展中的乳腺癌（bc）相关的单个白细胞亚型的分子特性尚不充分了解。我们的首要假设是，人类BC中的白细胞生物标志物可以提供有关BC结果的预后和预测信息，并且这些也可以用作设计新的个性化诊断和治疗药物的平台。项目1的目标是进一步确定与BC和复发性疾病侵袭性和/或特定分子亚型相关的白细胞亚型（项目1，目的1）。确定白细胞生物标志物，预测BC患者的长期预后和治疗反应（项目2，目的2）。确定小鼠BC模型中“高风险”白细胞的分子/细胞促肿瘤活性，以实现抗癌治疗的生物标志物和靶标验证（项目1，目标3）。我们将利用人类BC样本和现有的小鼠模型来确定组织中与肿瘤支持或肿瘤排斥环境相对应的免疫基质生物标志物。预测/预后生物标志物，利用我们对小鼠和人类BC样本的获取和专业知识，将以三种方式定义。首先，我们将根据表面表达和/或肿瘤定位对巨噬细胞和树突状细胞群体进行细分，以定义新的预后遗传特征，然后将其转化为蛋白质试剂（即抗体）。我们将使用检测微环境中白细胞激活状态的蛋白质试剂进一步细分白细胞浸润。最后，在整个过程中，我们将跟踪预后与各种BC亚型的标志物表达，以确定生物标志物是否按BC亚型排序。

It is now well established that chronic infiltration of leukocytes into neoplastic tissue potentiates solid tumor development Many experimental and clinical studies have revealed that tumor-promoting leukocytes regulate essentially all aspects of cancer development. However, the molecular natures of individual leukocyte subtypes associated with developing breast cancers (BCs) are inadequately understood. Our overarching hypothesis is that leukocyte biomarkers in human BC can provide prognostic and predictive information regarding BC outcomes, and that these can also be utilized as platforms for design of new, individualized diagnostic and therapeutic agents. The goals of Project 1 are to further define leukocyte subtypes correlating with aggressiveness and/or specific molecular subtypes of BC and recurrent disease (Project 1, Aim 1). Identify leukocyte biomarkers that predict long-term outcome and response to therapy for patients with BC (Project 2, Aim 2). Define molecular/cellular tumor-promoting activities of "high risk" leukocytes in mouse models of BC to enable biomarker and target validation for anticancer therapy (Project 1, Aim 3), We will leverage human BC samples and existing murine models to define immune-stromal biomarkers in tissues that correspond to tumor-supportive or tumor-rejecting environments. Predictive/prognostic biomarkers, using our access to and expertise in complementary mouse and human BC samples, will be defined in three ways. First we will use the subdivision of macrophage and dendritic cell populations based on surface expression and/or tumor localization to define novel genetic signatures for prognosis that can then be translated into protein reagents (i.e. antibodies). We will further subdivide leukocyte infiltration using protein reagents that detect activation states for leukocytes in the microenvironment. Finally, throughout, we will track prognosis versus marker expression for a variety of BC subtypes to determine whether biomarkers sort by BC subtype.