Project 2: Transcriptional Dynamics and Temporal Reprogramming During Radiation Treatment

摘要 放射治疗(RT)是最常用的抗癌药物；近70%的癌症患者将接受 放射治疗在癌症过程中的某个时刻，而RT在几乎一半的癌症治疗中发挥着关键作用。这个 近20年前完成的人类基因组测序，随后是大规模癌症 癌症基因组图谱(TCGA)中的测序工作提供了前所未有的对 原发癌和转移癌。在同一年里，内科肿瘤学经历了三个主要阶段 阶段转变：靶向治疗改变了我们对许多疾病的思维方式，这些疾病具有特定的可操作性 基因突变；免疫疗法彻底改变了许多非基因突变患者的治疗方法；以及抗体药物 结合物增加了我们细胞毒素的特异性。然而，RT治疗决策并没有 从生物学的影响中看到了同样的变化，而不是依赖于医学物理学和 计算机科学来推动我们的进步。虽然最近放射肿瘤学领域的试验数量激增， 受到来自制药公司的鼓励和资金的刺激，这些公司对 免疫检查点抑制剂和抗体药物结合物形式的新型(和有利可图的)化合物， 对于放射治疗，我们对个别患者的相对益处和最佳选择的理解还没有看到 同样的涨幅。事实上，我们一直在努力分析这些新奇组合之间的差异 和第二阶段试验中的标准放化疗，主要是因为我们试验的组合性质，以及 悬而未决的问题的绝对数量。在这个项目中，我们寻求在个性化辐射方面取得进展 治疗选择。利用我们在使用基因签名预测个别患者辐射方面的经验 受益，连同放射组学和基因组学的专业知识，我们将使用4个精心设计的队列来剖析 放射治疗、标准化疗、免疫检查点抑制剂Nivolumab和 抗体-药物结合物Sacituzumab Gowitecan。选择了两个受益于HIGH的疾病地点 (但不是统一的)标准顺铂-放射联合疗法(膀胱和头颈部)的治愈率， 我们组织了两项研究试验，以与标准疗法进行比较。在每个试验中(膀胱，使用SG+RT， 和HNSCC与ICI+RT)，我们将比较和对比肿瘤转录和 原发肿瘤组织及其代用品脱落细胞和循环肿瘤DNA的突变状态变化。这个 这些基因组学随着时间的推移将与高时间密度放射组学特征相结合，以允许 用于翻译和推广到所有使用现代技术治疗的患者。通过这些免费赠送- OMIC模式，我们的目标是利用我们在创建治疗反应签名方面的经验 在预先设置中进行个性化的治疗选择，并使用实时改变路线的机会 从日常成像中收集的信息。为了完成这个项目，我们将进行体外实验进化 揭示每种方法治疗成功和失败的分子机制，并 得出替代疗法敏感性的信号。

SUMMARY Radiation therapy (RT) is the single most utilized anti-cancer agent; nearly 70% of all cancer patients will receive radiation at some point in their cancer journey, and RT plays a crucial role in almost half of all cancer cures. The sequencing of the human genome, completed nearly 20 years ago, followed by the large scale cancer sequencing effort in The Cancer Genome Atlas (TCGA) have provided an unprecedented understanding of cancers in the primary and metastatic setting. In those same years, medical oncology has undergone three major phase transitions: targeted therapies have changed the way we think many diseases with specific actionable mutations; immunotherapy has revolutionized the treatment of many of those without; and antibody-drug conjugates have increased the specificity of our cytotoxics. RT treatment decision making, however, has not seen these same changes from biological influences, instead having relied on advances in medical physics and computer science to drive our advances. While the number of trials has ballooned in radiation oncology of late, spurred on by encouragement, and funding, from pharmaceutical companies interested in the synergy between novel (and profitable) compounds in the form of immune checkpoint inhibitors and antibody-drug-conjugates, with radiation, our understanding of the relative benefits and best choices for individual patients has not seen the same increases. In fact, we have struggled to parse out the differences between these novel combinations and standard chemoradiotherapy in phase II trials, largely because of the combinatorial nature of our trials, and the sheer number of open questions. In this project, we seek to make headway toward personalizing radiation therapy treatment choices. Using our experience in using gene signatures to predict individual patient radiation benefit, together with expertise in radiomics and genomics, we will use 4 carefully crafted cohorts to dissect out the relative contribution of radiation, standard chemotherapy, the immune checkpoint inhibitor Nivolumab and the antibody-drug conjugate Sacituzumab govitecan. Having chosen two disease sites which benefit from high (but not uniform) cure rates with standard cisplatin-radiation combination therapy (bladder and head and neck), we have structured two investigational trials to compare to standard therapy. In each trial (bladder, with SG+RT, and HNSCC with ICI+RT) we will compare and contrast the temporal changes in tumor transcriptomic and mutational state change in primary tumor tissue and surrogates from shed cells and circulating tumor DNA. The ‘ground truth’ of these genomics through time will be married to high temporal density radiomics features to allow for translation and generalization to all patients treated with modern technique. Through these complimentary - omic modalities, we aim to leverage our experience in creating signatures of therapeutic response to admit personalized treatment choice in the up front setting, and opportunities to change course using real-time information gleaned from daily imaging. To round out the project we will perform in vitro experimental evolution to uncover the molecular mechanisms underpinning therapeutic success and failure in each modality, and to derive signatures of alternative therapy sensitivity.