Project 2: Transcriptional Dynamics and Temporal Reprogramming During Radiation Treatment

项目 2：放射治疗期间的转录动力学和时间重编程

基本信息

批准号：
10526304
负责人：
Jacob Gardinier Scott
金额：
$ 19.58万
依托单位：
CLEVELAND CLINIC LERNER COM-CWRU
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-14 至 2027-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10526304
关键词：
Adopted Affect Alternative Therapies Antibodies Antibody-drug conjugates Antineoplastic Agents Basic Science Behavior Bioinformatics Biological Biological Assay Biopsy Bladder Cancer Patient Cell Line Cells Cisplatin Clinic Clinical Combined Modality Therapy Cytology Data Decision Making Discipline Disease Evolution Failure Frequencies Funding Genetic Transcription Genomics Glean Head and Neck Squamous Cell Carcinoma Head and neck structure Image Immune checkpoint inhibitor Immunotherapy In Vitro Intervention Investigation Knowledge Magnetic Resonance Imaging Malignant Neoplasms Malignant neoplasm of urinary bladder Maps Measures Medical Medical Oncology Modality Modernization Modification Molecular Mutation Nature Nivolumab Outcome Pathway interactions Patient-Focused Outcomes Patients Pattern Pelvis Pharmacologic Substance Phase Transition Physics Play Positron-Emission Tomography Prediction of Response to Therapy Primary Neoplasm Radiation Radiation Dose Unit Radiation Oncology Radiation therapy Radiobiology Refractory Regimen Resistance Role Saliva Sampling Site Specificity Structure Techniques Technology The Cancer Genome Atlas Therapeutic Time Translating Translations Treatment Efficacy Treatment Failure Tumor Tissue Urine Variant actionable mutation arm base cell type chemoradiation chemotherapy cohort combinatorial computer science cone-beam computed tomography cytotoxic density experience genetic signature human genome sequencing in vivo individual patient insight interest novel personalized medicine phase II trial radiation effect radiation response radiomics response standard of care success synergism targeted treatment transcriptomics treatment choice treatment response tumor tumor DNA

项目摘要

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.

概括辐射疗法（RT）是唯一使用的抗癌药。在所有癌症患者中，近70％将接受在癌症之旅的某个时刻，RT在几乎所有癌症治疗中都起着至关重要的作用。这人类基因组的测序大约在20年前完成，其次是大规模的癌症癌症基因组图集（TCGA）中的测序工作已经提供了前所未有的理解主要和转移性环境中的癌症。在同一几年中，医学肿瘤学经历了三个主要相变：有针对性的疗法改变了我们认为许多具有特定可行疾病的方式突变；免疫疗法彻底改变了对许多没有人的治疗。和抗体 - 药物结合物提高了我们的细胞毒性的特异性。但是，RT治疗决策尚未从生物学影响中看到这些相同的变化，而是依靠医学物理学的进步和计算机科学来推动我们的进步。虽然最近的试验次数在最近的辐射肿瘤学中激增，但受到对制药公司的鼓励和资金的刺激以免疫切口抑制剂和抗体 - 毒与偶联物的形式形式的新颖（和盈利）化合物，有了辐射，我们对个别患者的相对利益和最佳选择的理解尚未看到同样的增加。实际上，我们一直在努力解析这些新颖组合之间的差异以及II期试验中的标准化学放疗，主要是因为我们的试验的组合性质，并且大量的开放问题。在这个项目中，我们试图迈向个性化辐射治疗选择。利用我们使用基因标志来预测个体患者辐射的经验利益，以及放射组学和基因组学方面的专业知识，我们将使用4个精心制作的同类群体来剖析辐射，标准化疗，免疫检查点抑制剂nivolumab和抗体 - 药物缀合物sacituzumab govitecan。选择了两个从高中受益的疾病部位（但不是均匀的）用标准顺铂辐射组合疗法（膀胱和头颈）治愈速率，我们已经进行了两项研究试验，以与标准疗法进行比较。在每个试验中（膀胱，带有SG+RT，带有ICI+RT的HNSCC）我们将比较和对比肿瘤转录组和原发性肿瘤组织的突变状态变化，并从脱落细胞和循环肿瘤DNA中替代。这些基因组学的“地面真相”将与高临时密度放射素学特征结婚，以允许用于翻译和对所有接受现代技术治疗的患者的概括。通过这些免费 - OMIC模式，我们旨在利用我们在创建治疗反应的签名方面的经验来承认在正面环境中的个性化治疗选择，以及实时改变课程的机会从日常成像中收集的信息。为了完善项目，我们将在体外实验进化执行揭示每种方式中疗法成功和失败的分子机制，以及得出替代治疗敏感性的特征。