A novel multimodal ECM analysis platform for tumor characterization combining morphological and spectrochemical tissue imaging approaches.

一种结合形态学和光谱化学组织成像方法的新型多模式 ECM 分析平台，用于肿瘤表征。

• 批准号: 10710735
• 负责人: Paul J Campagnola
• 金额: $ 20.84万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10710735
• 关键词: Architecture; Area; Biochemical; Biochemistry; Biological; Biomimetics; Breast; Cancer Biology; Cancer Etiology; Carcinoma; Chemicals; Classification; Collagen; Collagen Fiber; Coupling; Cytoskeleton; DNA Sequence Alteration; Data; Diagnostic; Dimensions; Disease; Disease Progression; Etiology; Extracellular Matrix; Fiber; Fibronectins; Gel; Generations; Heterogeneity; Human; Image; In Vitro; Knowledge; Label; Laminin; Libraries; Malignant Neoplasms; Malignant neoplasm of ovary; Methods; Microscopy; Modality; Modeling; Modification; Molecular; Molecular Profiling; Morphology; Multimodal Imaging; Neoplasm Metastasis; Normal tissue morphology; Optics; Ovary; Pancreas; Phosphorylation; Post-Translational Protein Processing; Prognosis; Protein Isoforms; Resolution; Role; Serous; Shapes; Specimen; Spectrum Analysis; Speed; Structure; Surface; Tissue Sample; Tissue imaging; Tissues; Tumor Promotion; carcinogenesis; computerized data processing; crosslink; glycosylation; image reconstruction; imaging approach; imaging modality; imaging platform; insight; migration; multimodality; nanophotonic; novel; ovarian neoplasm; performance based measurement; prognostic; second harmonic; second harmonic generation imaging; self assembly; spectrograph; treatment response; tumor; tumor microenvironment; Architecture; Area; Biochemical; Biochemistry; Biological; Biomimetics; Breast; Cancer Biology; Cancer Etiology; Carcinoma; Chemicals; Classification; Collagen; Collagen Fiber; Coupling; Cytoskeleton; DNA Sequence Alteration; Data; Diagnostic; Dimensions; Disease; Disease Progression; Etiology; Extracellular Matrix; Fiber; Fibronectins; Gel; Generations; Heterogeneity; Human; Image; In Vitro; Knowledge; Label; Laminin; Libraries; Malignant Neoplasms; Malignant neoplasm of ovary; Methods; Microscopy; Modality; Modeling; Modification; Molecular; Molecular Profiling; Morphology; Multimodal Imaging; Neoplasm Metastasis; Normal tissue morphology; Optics; Ovary; Pancreas; Phosphorylation; Post-Translational Protein Processing; Prognosis; Protein Isoforms; Resolution; Role; Serous; Shapes; Specimen; Spectrum Analysis; Speed; Structure; Surface; Tissue Sample; Tissue imaging; Tissues; Tumor Promotion; carcinogenesis; computerized data processing; crosslink; glycosylation; image reconstruction; imaging approach; imaging modality; imaging platform; insight; migration; multimodality; nanophotonic; novel; ovarian neoplasm; performance based measurement; prognostic; second harmonic; second harmonic generation imaging; self assembly; spectrograph; treatment response; tumor; tumor microenvironment

PROJECT SUMMARY The tumor microenvironment (TME) in essentially all epithelial cancers is associated with significant biochemical and structural changes in the extracellular matrix (ECM). Many tumors including those of the breast, pancreas and ovary are characterized by profound changes in the collagen architecture. ECM changes (~micron scale) are below the resolution of conventional imaging modalities but analysis of this structure is critical for understanding carcinogenesis and metastasis. We have used the collagen-specific modality of Second Harmonic Generation (SHG) optical microscopy to discriminate cancer specimens from normal tissues based on changes in supramolecular structure, fibril structure, and fiber morphology, where we have focused on high grade serous ovarian cancer (HGSOC). However, SHG cannot identify the specific molecular alterations, which could provide critical information on disease etiology, prognosis, and response to therapy. Now we will develop a novel method that combines spatially registered SHG and surface enhanced mid-infrared spectral imaging (SE-MIRSI) correlating morphometric and chemometric information to elucidate tumor-promoting ECM alterations. The latter spatially probes specific molecular signatures from vibrational spectroscopy and provides increased sensitivity using nanophotonic substrates, allowing rapid and large-area chemical imaging of whole tissue sections. Specifically, SE-MIRSI can quantitatively identify specific changes in isoform distribution, posttranslational modifications and altered crosslinking of the collagen fibers. Spatial registration of SHG and SE-MIRSI then will provide a comprehensive, ultrasensitive, label free, non-destructive, high-resolution structural and biochemical imaging platform to investigate the role of ECM alterations in promoting tumor carcinogenesis and metastasis. Here, we will develop a multivariate data processing workflow that identifies the specific signatures of collagen and other ECM components from the two modalities establishing the basis of an accurate classifier. We will validate the multimodal characterizations on HSGOC tissue samples. At the end of this project, we will have developed a multimodal imaging platform that will uniquely identify collagen and other ECM biochemical alterations in the TME. We will establish performance measures based on imaging speed and throughput, sensitivity and classification accuracy. These structural and biochemical analyses will provide new insight into carcinogenesis and disease progression in several carcinomas. We propose these Aims: Aim 1. Identify specific structural and biochemical signatures of in vitro ECM models through the combined use of SHG and SE-MIRSI. Aim 2. Validate spatially registered SHG/SE-MIRSI method on high grade serous ovarian cancer and identify specific associated structural morphology and biochemical signatures.

项目摘要 本质上所有上皮癌的肿瘤微环境（TME）均与明显的生化有关 和细胞外基质（ECM）的结构变化。许多肿瘤，包括乳房的肿瘤 卵巢的特征是胶原蛋白结构的深刻变化。 ECM变化（〜micron量表） 低于传统成像方式的分辨率，但对此结构的分析对于 了解癌变和转移。我们使用了第二个谐波的胶原特异性方式 基于变化的变化，生成（SHG）光学显微镜以区分正常组织的癌症标本 在超分子结构，原纤维结构和纤维形态中，我们专注于高级浆液 卵巢癌（HGSOC）。但是，SHG无法识别特定的分子改变，这可以提供 有关疾病病因，预后和对治疗反应的关键信息。现在我们将开发一种新颖的方法 结合了空间注册的SHG和表面增强的中红外光谱成像（SE-MIRSI） 将形态计量和化学计量信息相关联，以阐明促进肿瘤的ECM改变。后者 从振动光谱法探测特定的分子特征，并提供提高的灵敏度 使用纳米光子底物，从而使整个组织切片的快速和大面积化学成像。 具体而言，Se-Mirsi可以定量识别同工型分布的特定变化，翻译后 修饰和改变胶原蛋白纤维的交联。然后，SHG和SE-MIRSI的空间注册将 提供全面，超敏，无标签，无损，高分辨率结构和生化 成像平台，以研究ECM改变在促进肿瘤发生和转移中的作用。 在这里，我们将开发一个多元数据处理工作流程，以识别胶原蛋白的特定签名 以及来自两种模式的其他ECM组件，建立了精确分类器的基础。我们将 验证HSGOC组织样品上的多模式表征。在这个项目结束时，我们将拥有 开发了一个多模式成像平台，该平台将唯一识别胶原蛋白和其他ECM生化 TME的改变。我们将根据成像速度和吞吐量建立绩效指标， 灵敏度和分类精度。这些结构和生化分析将为您提供新的见解 几种癌的致癌作用和疾病进展。我们提出了这些目标： 目标1。通过合并用途确定体外ECM模型的特定结构和生化特征 SHG和Se-Mirsi。 AIM 2。在高级浆液卵巢癌上验证空间注册的SHG/SE-MIRSI方法并确定 特定相关的结构形态和生化特征。