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.

摘要