Molecular Characterization Trial of Irradiated Rectal Cancer

摘要 分子表征试验 分子特征试验(MCT)是一个临床平台，使组织采集能够进行切割 边缘实验室和影像研究推动放射生物学领域的发展。MCT的首要假设 放射治疗(RT)对癌症预后的贡献取决于串扰的平衡 在受照射的肿瘤和正常组织中，宿主微生物群和宿主的免疫系统。直肠 癌症是检验这一假说的理想模型，因为成像和标本来自于接受 标准短程放射治疗(SCRT)在放疗前和放疗后均可获得 治疗和手术时一样。因此，可以纵向分析每个单项的RT效应 然后在全球范围内集成到一个模型中，以将生物和成像数据与临床结果相关联。 直肠癌也是一个研究重点，因为它的种族发病率和结果的差异。 罗宾私家已经组建了一个由老牌调查人员组成的国际团队，进行同样的审判 同时，在七个中心，以加快应计和发现。因此，MCT代表了知更鸟 项目1和项目2都依赖于它来回答有关RT生物学的基本问题。 将应用新的生物信息学方法将临床和生物数据与成像数据相结合，以 增强发现的潜力。最初的MCT将迭代地为未来的试验创建一个支持结构 根据相关科学项目的结果测试新的干预措施。项目1将重点放在 以确定局部免疫为目标的肿瘤和患者匹配的非肿瘤组织的分子分析 对RT的反应和RT诱导的基因组变化，并阐明治疗如何影响途径 参与细胞命运的决定，以及它对局部结肠粘膜微生物群的影响。项目2将使用血液 在辐射野内外采集的样本和淋巴结，以定量RT诱导的氧化 应激及其对每个免疫细胞亚群的生物学后果。与细胞相关的通路 应激反应、细胞死亡和免疫学适应性也将被评估。此外，粪便样本 将对RT前后收集的数据进行分析，以定性和定量地描绘微生物组的变化。 这两个项目都将使用最先进的基因组和蛋白质组方法来解决这些关键问题 结合患者的临床资料和来自正交放射学研究的多模式成像。 标准化和上传后，所有实验室、临床和影像数据将统一并通过 数据共享和综合分析核心(DSIA)。然后，将使用新颖的集成 生物信息学方法，以确定以前无法检测到的与无线电响应和 评估它们与临床结果的关系。最终输出将汇聚到NIH/NCI数据库和 可供罗宾网络和整个科学界使用。

ABSTRACT Molecular Characterization Trial The Molecular Characterization Trial (MCT) is a clinical platform to enable tissue acquisition to perform cutting edge laboratory and imaging research to advance the field of radiation biology. The MCT overarching hypothesis is that the contribution of radiotherapy (RT) to the outcome of cancer depends on the balance of the crosstalk among the irradiated tumor and normal tissue, the host microbiome, and the host’s immune system. Rectal cancer is an ideal model to test this hypothesis since imaging and specimens, from patients undergoing a standard short course radiotherapy (SCRT) treatment, are accessible and available at pre- and post RT treatment as well as at time of surgery. As such the RT effects can be analyzed longitudinally in each single tissue and then be integrated globally into a model to correlate biological and imaging data with clinical outcome. Rectal cancer is also a research priority because of its disparity in racial incidence and outcome. The ROBIN P.I.s have assembled an international team of established investigators, to conduct the same trial concurrently, at seven centers, to accelerate accruals and discovery. As such, the MCT represents the ROBIN foundation on which both Project 1 and Project 2 rely to answer fundamental questions regarding RT biology. Novel bioinformatic approaches will be applied to integrate clinical and biological data with imaging data, to enhance the potential for discovery. The initial MCT will create a supporting structure for future trials, iteratively testing new interventions informed by the results of the associated scientific projects. Project 1 will focus on the molecular analyses of tumor and patient’s matched non-tumor tissue with the goals of defining the local immune response to RT and the genomic changes induced by RT and elucidate how the treatment affects the pathways involved in cell fate decisions, and its effects on the local colonic mucosal microbiome. Project 2 will use blood specimens and lymph nodes, collected inside or outside the radiation field, to quantify RT-induced oxidative stress and the biological outcome of it on each immune cell subpopulation. Pathways associated with cellular stress responses, cell death, and immunological fitness will also be evaluated. Additionally, stool samples collected before and after RT will be analyzed to qualitatively and quantitatively map changes in the microbiome. Both projects will address these pivotal questions using state-of-the-art, genomic and proteomic approaches integrated with the patients’ clinical data and multi-modal imaging from an orthogonal radiomic study. After standardization and upload, all laboratory, clinical and imaging data will be harmonized and cured by the Data Sharing and Integrative Analysis Core (DSIA). Data will then be analyzed using novel integrative bioinformatics approaches to identify previously undetectable patterns related to radio-responsiveness and assess their association with clinical outcomes. The final output will converge into NIH/NCI databases and becomes available to the ROBIN network and to the scientific community at large.