Predictive signatures in breast cancer using multiplexed ion beam imaging

描述(申请人提供)：导管原位癌(DCIS)是一种浸润性前病变，每年约占乳腺癌新诊断病例的20%。由于DCIS的病理评估通常依赖于组织学标准，而组织学标准对预测哪些病变将发展为浸润性乳腺癌(IBC)几乎没有价值，因此许多患者接受了不必要的手术和辅助干预，这往往会导致治疗相关的并发症。到目前为止，大多数检测乳腺癌活检组织中DCIS蛋白表达的临床研究都使用了使用单一一抗的免疫过氧化物酶染色，这样每种蛋白都可以在单独的连续活检切片上显示出来。因此，尽管许多研究表明IBC在发病机制中起着关键作用，但将乳腺肿瘤细胞的表型与周围微环境联系起来的多重、定量的单细胞图谱尚未被描述。考虑到这一点，这里提出的工作重点是使用我最近开发的一种新的成像平台，多路离子束成像(MIBI)，以定义新的疾病模型，以绘制与DCIS和IBC发生相关的蛋白质表达和组织组织学中的进行性扰动。多路复用离子束成像(MIBI)能够同时分析多达100个目标，并与标准的福尔马林固定、石蜡包埋(FFPE)组织样本兼容，也是全球临床资料库中最常见的样本类型。我将首先扩展最近的工作，创建一个抗体小组，用于表征人类乳房组织中的成纤维细胞、巨噬细胞和上皮细胞。这个小组将被用来询问先前构建的组织微阵列，该微阵列包括正常乳腺、DCIS和IBC的临床注释活检组织。这些实验将首次在亚细胞水平上同时表征正常和肿瘤人乳腺组织上皮和间质成分的表型和组织学特征。然后将对这些特征进行汇总分析，以构建预测性临床分类器 可用于选择最佳治疗方案，防止进展为IBC，同时也将与治疗相关的发病率降至最低。更广泛地说，这项工作还将建立一个新的平台，以获得对疾病发病机制的前所未有的看法，这可以很容易地在未来的工作中采用，以对其他侵袭前损害进行风险分层。

DESCRIPTION (provided by applicant): Ductal carcinoma in situ (DCIS) is a pre-invasive lesion that comprises approximately 20% of new breast cancer diagnoses each year. Because pathological evaluation of DCIS typically relies on histologic criteria that offer little value in predicting which lesions will progress to invasive breast cancer (IBC), many patients receive unnecessary surgical and adjuvant interventions that often lead to therapy-related complications. To date, most clinical studies examining protein expression of DCIS in breast cancer biopsies have employed immune-peroxidase staining using a single primary antibody, such that each protein is visualized in separate serial biopsy sections. Consequently, despite numerous studies implicating a critical role in the pathogenesis of IBC, multiplexed, quantitative single cell profiles relating the phenotype of breast tumor cells with the surrounding microenvironment have not been described. With this in mind, the work proposed here focuses on using a novel imaging platform that I recently developed, multiplexed ion beam imaging (MIBI), to define new disease models for mapping progressive perturbations in protein expression and tissue histology that correlate with developing DCIS and IBC. Multiplexed ion beam imaging (MIBI) is capable of analyzing up to 100 targets simultaneously and is compatible with standard formalin-fixed, paraffin-embedded (FFPE) tissue specimens, and the most common sample type in clinical repositories worldwide. I will first expand upon recent work to create an antibody panel for characterizing fibroblasts, macrophages, and epithelium in human breast tissue. This panel will be used to interrogate previously constructed tissue microarrays comprised of clinically annotated biopsies of normal breast, DCIS, and IBC. These experiments will, for the first time, simultaneously characterize phenotypic and histologic features of epithelal and stromal components of normal and neoplastic human breast tissue at the subcellular level. These features will then be analyzed in aggregate to construct predictive clinical classifiers that can be used to select optimal therapeutic regimens that prevent progression to IBC while also minimizing treatment-related morbidity. More generally, this work will also establish a novel platform for gaining an unprecedented view into disease pathogenesis that could be easily adapted in future work to risk stratify other pre-invasive lesions.