Expansion of Tumoroid Models for Precise Treatment of the Rectal Cancer Patient

我们建议将直肠癌类器官(类肿瘤)发展为 个体化模型和建立大型直肠癌肿瘤样库。直肠癌的研究是 受制于模特的匮乏。在现存的为数不多的直肠癌活体模型中，没有一种是将肿瘤 因此，这些模型不能模拟正确的解剖环境和局部侵袭。这个 现有的模型也没有观察到转移。另一个问题是我们缺乏准确的手段 为了预测个别直肠癌患者对化疗或放疗是否有反应，这两种方法都是 这是目前护理标准的一部分。我们认为，无论是模型的缺乏还是预测工具的缺乏 可以通过患者衍生的类肿瘤来解决。类肿瘤可以在体外或三维培养中生长 植入老鼠体内，因此它们提供了一个灵活的研究平台。在初步结果中，我们已经得出了肿瘤样 来自多个患者直肠癌的线条，发现它们与相应的患者肿瘤相似。这个 当类肿瘤植入小鼠体内时(即在直肠内)，形成局部侵袭性肿瘤，能够 转移。此外，我们发现类肿瘤对化疗和 辐射。因此，根据这些初步数据，我们假设直肠癌类肿瘤反映了 他们原始肿瘤的特征，可以用来预测患者对治疗的反应，并且，当植入时 可作为直肠癌的最佳动物模型。 我们计划开发100个新的肿瘤，我们预计它将涵盖人类直肠的大部分多样性 腺癌。类肿瘤将在体外培养和两种小鼠模型中进行分析：腔内 植入模型和传统的侧向注入模型。在这些设置中，我们将测试 类肿瘤在突变、组织学和基因表达方面准确地反映其起源的肿瘤。我们会 确定类肿瘤对患者特定化疗和放射的反应是否可以预测 相应患者的反应。尤其令人感兴趣的是，个体人类直肠癌是否更多 腔内植入比侧翼注射更准确地模拟。最后，为了将我们的发现整合到一个 广泛使用的综合平台，我们将无缝开发直肠癌瘤样生物库 集成了在线病理、基因组和模型特定信息。将搭建在线平台 在我们机构的癌症基因组学门户网站内，然后集成到NCIP中心。我们已经组建了一支 具有结直肠外科肿瘤学、放射肿瘤学和病理学专业知识的协作团队； 老鼠模型；生物统计学；生物信息学。我们预计，拟议的研究将证明 类肿瘤作为直肠癌研究和预测患者治疗反应的准确模型。这个 大型类肿瘤生物库可能会刺激直肠癌新疗法的研究。终极的 结果将是为受这种致命疾病影响的患者提供新的治疗选择和更好的治疗选择。

We propose to develop rectal cancer organoids (tumoroids) as individualized models and to build a large rectal cancer tumoroid repository. Research on rectal cancers is hampered by the paucity of models. Of the few existing in vivo models of rectal cancer, none place the tumors in the rectal lumen, so the models fail to mimic the correct anatomic environment and local invasion. The existing models also have not been observed to metastasize. Another problem is that we lack accurate means to predict whether individual rectal cancer patients will respond to chemotherapy or radiation, both of which are part of the current standard of care. We believe that both the paucity of models and the lack of predictive tools can be addressed by patient-derived tumoroids. Tumoroids can be grown in 3-dimensional culture ex vivo or implanted into mice, so they offer a flexible research platform. In preliminary results, we have derived tumoroid lines from multiple patients' rectal cancers and found them to resemble the corresponding patient tumors. The tumoroids, when implanted in mice endoluminally (i.e. in the rectum), formed locally invasive tumors capable of metastasis. Moreover, we found tumoroids to have clinically relevant responses to chemotherapy and radiation. Thus, drawing from these preliminary data, we hypothesize that rectal cancer tumoroids mirror the traits of their original tumors, can be used to predict patients' response to therapy, and, when implanted endoluminally into mice, can serve as an optimal model of rectal cancer. We plan to develop 100 new tumoroids, which we expect to encompass much of the diversity of human rectal adenocarcinoma. The tumoroids will be analyzed in ex vivo culture and in two mouse models: the endoluminal implantation model and a conventional flank injection model. In these settings, we will test whether the tumoroid accurately reflects its tumor of origin in terms of mutations, histology, and gene expression. We will determine whether response of the tumoroids to patient-specific chemotherapy and radiation can predict the corresponding patient's response. Of particular interest is whether individual human rectal cancers are more accurately modeled by endoluminal implantation than by flank injection. Finally, to integrate our findings into a comprehensive platform for broad use, we will develop a rectal cancer tumoroid biorepository seamlessly integrated with online pathologic, genomic, and model-specific information. The online platform will be built within our institution's cancer genomics portal, then integrated into the NCIP Hub. We have assembled a collaborative team with expertise in colorectal surgical oncology, radiation oncology, and pathology; organoids; mouse models; biostatistics; and bioinformatics. We anticipate that the proposed research will credential tumoroids as accurate models for rectal cancer research and for predicting patient responses to therapy. The large tumoroid biorepository is likely to stimulate research on new treatments for rectal cancer. The ultimate result will be new treatment options and better treatment selection for patients affected by this deadly disease.