Spatiotemporal modeling of cancer-niche interactions in breast cancer bone metastasis

乳腺癌骨转移中癌症-生态位相互作用的时空模型

• 批准号: 10260556
• 负责人: STEPHEN TC WONG
• 金额: $ 53.37万
• 依托单位: METHODIST HOSPITAL RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10260556
• 关键词: Adopted; Algorithms; Animal Model; Autocrine Communication; Bioinformatics; Biological; Biological Assay; Biology; Bone Marrow; Breast Cancer Cell; Breast Cancer Patient; Breast cancer metastasis; CSPG4 gene; Cancer Model; Cell Differentiation process; Cells; Clinical; Clinical Research; Computational algorithm; Computer Assisted; Computer Models; Data; Development; Diagnosis; Disease; Endothelial Cells; Excision; Exhibits; Foundations; Frequencies; Genetically Engineered Mouse; Goals; Homeostasis; Image; In Situ; Indolent; Knowledge; Laboratories; Lead; Malignant Neoplasms; Maps; Mediating; Mesenchymal Stem Cells; Metastatic Neoplasm to the Bone; Micrometastasis; Microscopic; Microscopy; Modeling; Molecular; Molecular Profiling; Neoplasm Metastasis; Osteogenesis; Osteolysis; Osteolytic; Outcome; Ovarian; Paracrine Communication; Patients; Pharmaceutical Preparations; Play; Primary Neoplasm; Process; Quality of life; Resolution; Role; Seeds; Series; Signal Pathway; Signal Transduction; Stromal Cells; Symptoms; Therapeutic; Transforming Growth Factor beta; base; bioimaging; bisphosphonate; bone; bone cell; cancer cell; cell type; clinical translation; design; drug efficacy; drug repurposing; improved; laser capture microdissection; malignant breast neoplasm; multi-photon; neoplastic cell; osteogenic; predictive modeling; prevent; recruit; repaired; response; spatiotemporal; success; therapeutic target; tool; transcriptome; transcriptomics; tumor; tumor microenvironment

ABSTRACT About 20-40% of breast cancer patients develop metastasis to the bone, years to even decades after surgical removal of primary tumors. Little is known about the biology of the latent, microscopic bone metastases before they outgrow to overt osteolytic macrometastases. This represents a significant gap in our understanding of bone metastasis. Targeting cancer cells that have not fully adapted to the bone microenvironment might provide therapeutic benefit and prevent the occurrence of overt metastases. Bone and bone marrow comprise of several highly distinctive microenvironment niches. Dormant, single disseminated tumor cells (DTCs) reside in the perivascular niche, whereas proliferative, multi-cell bone micrometastases (BMMs) are found in the osteogenic niche that exhibits features of active osteogenesis. Mechanisms through which the transition of different niches occurs to switch fates of metastatic seeds remain elusive. The overall objectives of this project are to investigate the spatiotemporal dynamics, the molecular crosstalk, and the therapeutic targets underlying the interaction between breast cancer cells and different microenvironment niches in bone. We will pursue three specific aims. First, we will dissect the spatiotemporal dynamics of the perivascular and osteogenic niches and the cancer-niche interactions in bone micrometastasis models. We will use high-resolution, whole- bone, multi-photon microscopy and laser-captured microdissection (LCM) followed by transcriptome profiling (LCM-seq) to obtain relative localization and mutual impacts between cancer cells and niche cells in situ. Second, we will integrate transcriptomic and imaging data and develop computational models for discovery of new mechanisms and therapies toward blockade of cancer-niche interactions. Established and new algorithms will be used to uncover the microenvironment molecules, and autocrine and paracrine signaling pathways mediating niche-tumor interactions. Drug-repurposing analyses will be carried out to identify potential therapies that have already been used for other diseases. We will achieve a systematic understanding of early-stage bone colonization and generate testable mechanistic and therapeutic hypotheses. Third, we will validate the discovered mechanisms and predicted drug efficacies in animal models. The Zhang laboratory has adopted and established a series of genetically engineered mouse models and bone metastasis assays, which will be utilized to validate computational predictions generated by computational modeling by the Wong group. Both metastatic burden and frequency/distribution of DTCs and BMMs will be examined as endpoints. This study will unbiasedly profile the molecular process of early stage metastasis progression in the bone from DTCs to BMMs at single-to-few cell resolutions. This knowledge is unprecedented and critical for the ultimate understanding of metastasis latency, a long-standing clinical challenge. The modeling tool developed through this study will likely be applicable to other biological contexts involving highly spatiotemporally specific cancer- niche interaction. The computer-aided drug repurposing will likely lead to fast clinical translation.

抽象的 大约 20-40% 的乳腺癌患者在手术后数年甚至数十年出现骨转移 切除原发肿瘤。在此之前，人们对潜在的微小骨转移的生物学知之甚少。 它们长大后会出现明显的溶骨性大转移。这表明我们的理解存在重大差距 骨转移。针对尚未完全适应骨微环境的癌细胞可能 提供治疗益处并预防明显转移的发生。骨和骨髓包括 几个非常独特的微环境利基。存在休眠、单个播散性肿瘤细胞 (DTC) 血管周围微生境中存在增殖性多细胞骨微转移 (BMM) 具有活跃成骨特征的成骨生态位。过渡的机制 不同的生态位发生改变转移种子的命运仍然难以捉摸。本项目的总体目标 研究时空动力学、分子串扰和潜在的治疗靶点 乳腺癌细胞与骨中不同微环境生态位之间的相互作用。我们将追求 三个具体目标。首先，我们将剖析血管周围和成骨的时空动力学 骨微转移模型中的生态位和癌症-生态位相互作用。我们将使用高分辨率、全 骨、多光子显微镜和激光捕获显微切割 (LCM)，然后进行转录组分析 （LCM-seq）以获得癌细胞和原位细胞之间的相对定位和相互影响。 其次，我们将整合转录组和成像数据并开发计算模型来发现 阻断癌症-生态位相互作用的新机制和疗法。既定算法和新算法 将用于揭示微环境分子以及自分泌和旁分泌信号通路 介导生态位-肿瘤相互作用。将进行药物再利用分析以确定潜在的治疗方法 已被用于治疗其他疾病。我们将对早期阶段有一个系统的了解 骨定植并产生可测试的机制和治疗假设。第三，我们将验证 在动物模型中发现了机制并预测了药物功效。张实验室采用 并建立了一系列基因工程小鼠模型和骨转移检测方法，将 用于验证 Wong 小组通过计算建模生成的计算预测。两个都 DTC 和 BMM 的转移负担和频率/分布将作为终点进行检查。这项研究将 公正地描述骨中从 DTC 到骨转移的早期转移进展的分子过程 单细胞到少数细胞分辨率的 BMM。这些知识是前所未有的，对于最终的结果至关重要 了解转移潜伏期是一个长期存在的临床挑战。建模工具开发通过 这项研究可能适用于涉及高度时空特异性癌症的其他生物学背景 利基互动。计算机辅助药物的重新利用可能会带来快速的临床转化。