Characterizing glioma heterogeneity with novel multiplexed nanoscale imaging technologies

利用新型复合纳米级成像技术表征神经胶质瘤的异质性

• 批准号: 10247568
• 负责人: Fei Chen
• 金额: $ 44.5万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-08 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10247568
• 关键词: Adult Glioblastoma; Architecture; Atlases; Automation; Bar Codes; Biological; Biological Process; Cell Communication; Cells; Complex; Computer software; DNA; Data; Data Set; Diagnostic; Diffuse; Functional disorder; Future; Gene Expression; Genes; Genetic Transcription; Glioblastoma; Glioma; Heterogeneity; Histologic; Human; Image; Imaging technology; Immune; In Situ; Invaded; Libraries; Malignant Neoplasms; Malignant neoplasm of brain; Maps; Messenger RNA; Methods; Microscopy; Modality; Molecular; Morphology; Nature; Non-Malignant; Operative Surgical Procedures; Output; Pathology; Patients; Phenotype; Process; Proteins; Proteomics; Publishing; RNA; Radiology Specialty; Research; Resolution; Sampling; Specimen; Speed; Structure; Techniques; Technology; Therapeutic Intervention; Time; Tissue Expansion; Tissue Sample; Tissue imaging; Tissues; Transcript; Tumor Cell Invasion; Tumor Tissue; Tumor-Derived; antibody libraries; base; brain tissue; cancer cell; cell type; computer framework; conventional therapy; design; feature extraction; innovation; insight; molecular phenotype; multimodality; nanoscale; neoplastic cell; new technology; novel; novel therapeutics; programs; single cell sequencing; single-cell RNA sequencing; success; therapeutic development; therapy resistant; tool; transcriptomics; tumor; tumor heterogeneity

Abstract: Gliomas, with glioblastomas (GBM) in particular, are one of the most lethal human malignancies due to lack of success with current conventional treatments due to their invasive nature and heterogeneity. We will leverage expansion microscopy, a novel super-resolution microscopy method, as a platform to develop novel tools for highly multiplexed in situ analysis to generate comprehensive maps of GBM spatial heterogeneity and structure. We will use these tools to help understand the molecular and morphological phenotypes of GBM invasion and pathology, which we hope will guide future therapeutic interventions. The proposed research will consist of three aims which seeks to develop novel in situ analysis tools driven by biological questions in GBM organization: (1) Comprehensively map cell types and states within GBM tumor tissue with high spatial resolution. To enable this, we will develop an innovative method for highly multiplexed readout of RNA in expanded tissues with tailored in situ gene expression panels based on single-cell RNA sequencing signatures. (2) Study the nanoscale interactions between tumor cells and their surrounding microenvironment that are implicated GBM invasion. To accomplish this, we will develop an approach for multiplexed protein imaging with nanoscale resolution using DNA barcoded antibody libraries. (3) Develop a scalable analysis platform with automation and analysis software to integrate multiplexed RNA and protein imaging in the same sample. We will apply this platform to patient derived tumor samples to understand the molecular and morphological phenotypes of invading GBM tumor cells, as well as build a map of the spatial heterogeneity of GBM. These novel technologies to spatially map molecular information in complex tissues will not only be invaluable for understanding glioma and cancer, they will be broadly applicable to many other spatially complex biological processes.

文摘:

项目成果

Cell type-specific inference of differential expression in spatial transcriptomics.

• DOI: 10.1038/s41592-022-01575-3
• 发表时间: 2022-09
• 期刊: NATURE METHODS
• 影响因子: 48
• 作者: Cable, Dylan M.;Murray, Evan;Shanmugam, Vignesh;Zhang, Simon;Zou, Luli S.;Diao, Michael;Chen, Haiqi;Macosko, Evan Z.;Irizarry, Rafael A.;Chen, Fei
• 通讯作者: Chen, Fei

Spatiotemporal transcriptomic maps of whole mouse embryos at the onset of organogenesis.

在器官发生时，整个小鼠胚胎的时空转录组图。

• DOI: 10.1038/s41588-023-01435-6
• 发表时间: 2023-07
• 期刊: NATURE GENETICS
• 影响因子: 30.8
• 作者: Kumar, Abhishek Sampath;Tian, Luyi;Bolondi, Adriano;Hernandez, Amelia Aragones;Stickels, Robert;Kretzmer, Helene;Murray, Evan;Wittler, Lars;Walther, Maria;Barakat, Gabriel;Haut, Leah;Elkabetz, Yechiel;Macosko, Evan Z.;Guignard, Leo;Chen, Fei;Meissner, Alexander
• 通讯作者: Meissner, Alexander

Dissecting mammalian spermatogenesis using spatial transcriptomics.

• DOI: 10.1016/j.celrep.2021.109915
• 发表时间: 2021-11-02
• 期刊: Cell reports
• 影响因子: 8.8
• 作者: Chen H;Murray E;Sinha A;Laumas A;Li J;Lesman D;Nie X;Hotaling J;Guo J;Cairns BR;Macosko EZ;Cheng CY;Chen F
• 通讯作者: Chen F

Photoselective sequencing: microscopically guided genomic measurements with subcellular resolution.

光选择性测序：具有亚细胞分辨率的显微镜引导基因组测量。

• DOI: 10.1038/s41592-023-01845-8
• 发表时间: 2023
• 期刊: Nature methods
• 影响因子: 48
• 作者: Mangiameli,SarahM;Chen,Haiqi;Earl,AndrewS;Dobkin,JulieA;Lesman,Daniel;Buenrostro,JasonD;Chen,Fei
• 通讯作者: Chen,Fei

Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2.

• DOI: 10.1038/s41587-020-0739-1
• 发表时间: 2021-03
• 期刊: Nature biotechnology
• 影响因子: 46.9
• 作者: Stickels RR;Murray E;Kumar P;Li J;Marshall JL;Di Bella DJ;Arlotta P;Macosko EZ;Chen F
• 通讯作者: Chen F