Prognostic analysis and progression modeling of basal-like breast cancer using multi-region sequencing

项目总结/摘要 乳腺癌是全球女性最常见的癌症，也是第五大常见死亡原因 从癌症的整体。与许多其他癌症一样，乳腺癌以各种形式存在，可以是 广泛地分为四种分子亚型，包括管腔A型、管腔B型、HER2+型和基底型。其中， 基底癌约占原发性乳腺肿瘤的20%，是最具侵袭性和致命性的肿瘤之一。 亚型虽然已经做出了重大的努力，但基底癌如何进展为恶性肿瘤的生物学过程仍然是未知的。 恶性，危及生命的疾病还没有得到很好的理解，和基础的诊断和治疗， 癌症仍然是主要的挑战。具体来说，目前没有可用的预后测试可以帮助 临床管理，并且几乎所有基底癌患者被分类为具有高复发风险。 此外，由于大多数基底部肿瘤缺乏雌激素受体（ER）、孕激素受体（PR）的表达， (PR)和HER2，目前还没有有效的靶向治疗方案可用，并且苛刻， 不加选择的化疗是唯一的治疗选择。因此，大量的基底癌 患者治疗不足或过度。建立在我们以前的工作逻辑上，我们提出了一个大规模的 跨学科研究计划，其中我们将使用多区域测序和先进的计算 技术，以解决一些紧迫的问题和上述未满足的临床需求的基底乳房 癌具体来说，我们将对300例原发性基底部肿瘤和50例匹配的 我们从马约诊所的组织库中鉴定出的转移性肿瘤。通过使用所获得的多区域 通过对肿瘤组织数据进行测序，我们将通过多种方法推导出基底癌的预后评估系统。 实例学习，并构建和验证基底癌的高分辨率进展模型。我们还将 对一系列分子数据进行大规模分析，以系统地寻找遗传决定因素 在基因和途径水平上的基础癌症进展，这将提供丰富的见解， 肿瘤发生的分子机制，使我们能够确定潜在的治疗靶点， 癌如果成功实施，这项工作将大大推进基础癌症的研究，并铺平道路。 将类似的策略应用于研究其他致命癌症的方法。

Project Summary/Abstract Breast cancer is the most common cancer in women worldwide, and the fifth most common cause of death from cancer overall. As with many other cancers, breast cancer presents in a variety of forms and can be broadly divided into four molecular subtypes, including luminal A, luminal B, HER2+ and basal. Among them, basal cancer represents ~20% of primary breast tumors and is one of the most aggressive and deadly subtypes. While significant efforts have been made, the biological process of how basal cancer progresses to a malignant, life-threatening disease is not well understood, and the prognostication and treatment of basal cancer remain major challenges. Specifically, there are currently no prognostic tests available that can assist clinical management, and nearly all basal cancer patients are classified as having a high risk of recurrence. Moreover, as the majority of basal tumors lack expression of estrogen receptor (ER), progesterone receptor (PR) and HER2, there are presently no effective targeted treatment regimens available, and harsh, indiscriminate chemotherapy is the only treatment option. Consequently, a significant number of basal cancer patients are under- or over-treated. Built logically on our previous work, we propose a large-scale interdisciplinary research plan, in which we will use multi-region sequencing and advanced computational techniques to address some pressing issues and the aforementioned unmet clinical needs of basal breast cancer. Specifically, we will perform molecular profiling of 300 primary basal tumors and 50 matched metastatic tumors that we have identified from Mayo Clinic tissue banks. By using the obtained multi-region sequencing tumor tissue data, we will derive a prognostic evaluation system for basal cancer through multiple instance learning, and construct and validate a high-resolution progression model of basal cancer. We will also perform a large-scale analysis on a range of molecular data to systematically search for genetic determinants of basal cancer progression at both gene and pathway levels, which will provide a wealth of insights into molecular mechanisms of tumorigenesis and enable us to identify potential therapeutic targets for basal cancer. If successfully implemented, this work will significantly advance the basal cancer research, and pave the way for applying similar strategies to study other deadly cancers.