Tech Core 2

技术核心2

• 批准号: 10532385
• 负责人: Denis Wirtz
• 金额: $ 54.57万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2026-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10532385
• 关键词: 3-Dimensional; Algorithms; Anatomy; Area; Atlases; Bar Codes; Blood Vessels; Cells; Cellular biology; Clinical; Data; Development; Extracellular Matrix; Genes; Goals; Heterogeneity; Histology; Human; Image; Invaded; Malignant Neoplasms; Malignant neoplasm of pancreas; Mammary Neoplasms; Maps; Measures; Messenger RNA; Methods; Microanatomy; Microfluidics; Molecular; Neoplasm Metastasis; Outcome; Play; Process; Proteins; Resolution; Role; Semantics; Site; Subcellular Anatomy; Technology; Therapeutic Intervention; Three-Dimensional Imaging; Time; Tissue Sample; Tissue imaging; Tissues; Training; Tumor Tissue; Tumor Vascular Invasion; Venous; anticancer research; cancer cell; cancer imaging; cancer risk; cost; deep learning; design; genome-wide; histological specimens; image registration; lymphatic Invasion; malignant breast neoplasm; meter; multiple omics; neoplastic cell; new technology; novel; pancreatic neoplasm; protein biomarkers; targeted treatment; technology development; technology platform; technology validation; tissue fixing; tissue mapping; transcriptome; tumor; tumor heterogeneity; tumor progression

Project Summary – Tech Core 2 Spatial tumor heterogeneity plays a critical role in multiple stages of cancer progression and metastasis including the venous invasion that contributes to increased risk of cancer cell dissemination. This process involves spatially distinct interaction between cancer cells and the surrounding microenvironment at multiple sites. In Tech1, PI Wirtz will develop a new 3D multiscale tumor cell mapping method, CODA, which can create a 3D large-scale tumor cell anatomy at single cell level via tissue histology image integration and trained deep-learning semantic algorithms. What is highly desired to further add to this 3D tumor cell anatomic atlas is genome-wide molecular information such as mRNAs and a large panel of proteins for unbiased discovery of cell subtype, state, and interaction, and potentially to infer new mechanisms or targets for therapeutic intervention. TECH2 PI Fan recently developed a novel technology called DBiT-seq for high-spatial-resolution multi-omics mapping via deterministic barcoding in tissue at cellular level (~10µm), whole transcriptome scale (>22,000 genes), high coverage (>2,000 genes per 10µm pixel), and multi-omics profiling (co-mapping of ~300 protein markers), which can be readily applied to FFPE tissue sections and integrated with CODA. In Tech2, we propose the following two aims: AIM 1. A high-throughput, low cost, high quality/coverage, multi-omic mapping method (DBiT-seq) with full compatibility with human PFA and FFPE tissue samples. AIM 2. Integrating CODA and DBiT-seq for 3D multi-omic tumor imaging. Successful completion of these two aims will lead to the first genome-wide multi- omics 3D view of vascular or lymphovascular invasion of human tumors and a powerful technology platform for the consortium to investigate spatial tissue heterogeneity in other human cancers.

项目摘要 - 技术核心2 空间肿瘤异质性在癌症进展和转移的多个阶段起着至关重要的作用 导致癌细胞传播风险增加的静脉侵袭。这个过程涉及空间 癌细胞与周围多个位点的微环境之间的明显相互作用。在Tech1，pi Wirtz将开发一种新的3D多尺度肿瘤细胞映射方法CODA，可以创建3D大规模 通过组织组织学图像整合和经过训练的深度学习语义，在单细胞水平的肿瘤细胞解剖学 算法。高度希望进一步添加到这个3D肿瘤解剖学图集是全基因组分子 诸如mRNA和大量蛋白质的信息，用于无偏见的细胞亚型，状态和状态发现 相互作用，并有可能推断出治疗干预的新机制或目标。 Tech2 Pi迷 最近开发了一项新型技术，称为DBIT-SEQ，用于高空间分辨率的多派映射 细胞水平（〜10µm），整个转录组量表（> 22,000基因）的组织中的确定性条形码，高 覆盖范围（每10µm像素）和多摩学分析（约300个蛋白质标记物） 可以很容易地应用于FFPE组织切片并与Coda集成。在Tech2中，我们建议以下 两个目的：目标1。高通量，低成本，高质量/覆盖范围，多摩尼克映射方法（DBIT-SEQ） 与人PFA和FFPE组织样品完全兼容。 AIM 2。将CODA和DBIT-SEQ集成3D 多摩尼克肿瘤成像。这两个目标的成功完成将导致第一个全基因组多多 OMICS 3D对人类肿瘤的血管或淋巴入侵的视图和强大的技术平台 研究其他人类癌症的空间组织异质性的财团。