Hypoxia-derived molecular MSI signatures to predict breast cancer outcome

缺氧衍生的分子 MSI 特征可预测乳腺癌结果

基本信息

批准号：
9390214
负责人：
Kristine Glunde
金额：
$ 45.21万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-15 至 2022-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9390214
关键词：
Address Area Automobile Driving Biological Markers Biopsy Breast Cancer Patient Breast-Conserving Surgery Cancer Patient Clinical Clinical Pathology Collaborations Deposition Detection Development Diagnosis Diagnostic Digestion Distant Metastasis Electrospray Ionization Extracellular Matrix Formalin Freezing Fresh Tissue Funding Goals Histology Human Hypoxia Image Imaging Techniques Immunohistochemistry Isomerism Laboratories Life Lipids Malignant Neoplasms Mammary Gland Parenchyma Mammary Neoplasms Marker Discovery Mass Spectrum Analysis Measures Metabolic Marker Metabolism Metastatic Neoplasm to Lymph Nodes Molecular Molecular Profiling Multimodal Imaging Necrosis Neoplasm Metastasis Nodule Outcome Paraffin Embedding Pathology Patient-Focused Outcomes Patients Pattern Phenotype Polysaccharides Pre-Clinical Model Preparation Primary Neoplasm Prognostic Marker Proteins Proteome Protocols documentation Radiation Recurrence Reproducibility Research Resistance Resolution Risk Sampling Signal Pathway Signal Transduction Specimen Spectrometry, Mass, Electrospray Ionization Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Speed Structure Technology Testing Time Tissue Microarray Tissue Sample Tissues Translating Treatment outcome United States National Institutes of Health Xenograft Model angiogenesis base breast cancer survival chemotherapy clinical translation clinically relevant cohort imaging approach improved innovation ionization lymph nodes malignant breast neoplasm metabolome molecular mass molecular pathology outcome forecast outcome prediction predictive marker prognostic scale up tool tumor tumor microenvironment tumor progression

项目摘要

Project Summary The overall goal of this application is to develop hypoxia-derived prognostic biomarkers to predict breast cancer progression and patient outcome from human breast cancer tissue samples. In a previous NIH-funded project, have identified hypoxia-driven signaling networks in the breast tumor microenvironment (TME) through multimodal imaging combined with omics approaches in preclinical models. The breast TME contains several spatially heterogeneous hypoxic regions, which induce metastasis and drive angiogenesis, invasion, altered metabolism, and resistance to radiation and chemotherapy. Hypoxic tumor regions are also known to select for aggressive cancer phenotypes with the highest capacity for metastatic spread. We have identified significantly changed molecular signatures in hypoxic tumor regions in human breast tumor xenograft models, with confirmed lists and networks of metabolites, lipids, and proteins that are significantly altered. We propose to now build on these studies by developing fast reproducible clinical sample preparation and mass spectrometry imaging (MSI) protocols that allow for high throughput use in clinical pathology laboratories and seamlessly integrate with histology and immunohistochemistry. We will test in large cohorts of human breast cancer tissue samples if hypoxic metabolome, lipidome, and proteome signatures have prognostic clinical value. To this end, we will employ innovative multi-enzyme on-tissue digestion for proteins and glycans, reactive desorption electrospray ionization (DESI) for enhanced metabolic marker discovery, and MSI-based Ozonolysis (OzID) for on-the-fly lipid isomer imaging. In Aim 2, we will use these MSI approaches for analyzing tissue microarrays with biopsies from the primary tumors of over 1,000 breast cancer patients to test if hypoxic molecular signatures can predict patient outcome, recurrence, and 5-year-survival. In Aim 3, we will address the most life-threatening aspect of breast cancer, the formation of metastases, and investigate if hypoxic regions in primary human breast tumors are driving the development of metastases. The proposed research will identify key molecular networks through which hypoxia drives breast cancers towards worse outcome and metastasis. Recent developments in MSI have significantly improved its imaging speed, making it now possible to perform MSI-based molecular pathology in clinically relevant times. This enables us to translate the results of our earlier studies on the effect of hypoxia in the breast TME directly to large patient cohorts. We will clinically evaluate matrix-assisted laser desorption/ionization (MALDI) MSI as diagnostic tool in conjunction with the routine clinical pathology workup for accurate molecular prognosis of breast cancers. The large-scale metabolite and lipid signatures obtained in our application will support the emerging use of ambient ionization MSI applications for accurate intraoperative margin detection during breast-conserving surgery and intraoperative diagnostics using the iKnife.

项目概要该应用程序的总体目标是开发缺氧衍生的预后生物标志物来预测乳腺癌人类乳腺癌组织样本的癌症进展和患者结果。在之前的 NIH 资助项目中项目，通过确定乳腺肿瘤微环境（TME）中缺氧驱动的信号网络多模态成像与临床前模型中的组学方法相结合。乳房 TME 包含几个空间异质缺氧区域，诱导转移并驱动血管生成、侵袭、改变代谢，以及对放射和化疗的抵抗力。缺氧肿瘤区域也被认为会选择具有最高转移扩散能力的侵袭性癌症表型。我们已经确定了显着改变了人类乳腺肿瘤异种移植模型中缺氧肿瘤区域的分子特征确认了显着改变的代谢物、脂质和蛋白质的列表和网络。我们建议现在以这些研究为基础，开发快速可重复的临床样品制备和质谱分析成像 (MSI) 协议，允许在临床病理实验室中无缝地进行高通量使用与组织学和免疫组织化学相结合。我们将在大量人类乳腺癌组织中进行测试缺氧代谢组、脂质组和蛋白质组特征是否具有预后临床价值的样本。为此，我们将采用创新的多酶组织消化蛋白质和聚糖、反应解吸电喷雾电离 (DESI) 用于增强代谢标记物发现，基于 MSI 的臭氧分解 (OzID) 用于增强代谢标记物发现动态脂质异构体成像。在目标 2 中，我们将使用这些 MSI 方法来分析组织微阵列对 1,000 多名乳腺癌患者的原发肿瘤进行活检，以测试缺氧分子是否特征可以预测患者的结果、复发和 5 年生存率。在目标 3 中，我们将解决最乳腺癌危及生命的方面、转移的形成，并调查是否存在缺氧区域原发性人类乳腺肿瘤正在推动转移的发展。拟议的研究将确定缺氧导致乳腺癌恶化和转移的关键分子网络。 MSI 的最新发展显着提高了其成像速度，使其现在可以执行临床相关时期基于 MSI 的分子病理学。这使我们能够将我们的结果转化为早期关于乳腺 TME 缺氧对大型患者群体的影响的研究。我们将在临床上评估基质辅助激光解吸/电离 (MALDI) MSI 作为诊断工具与常规临床病理学检查，以实现乳腺癌的准确分子预后。大规模的在我们的应用中获得的代谢物和脂质特征将支持环境电离的新兴应用 MSI 应用程序可在保乳手术期间准确检测术中边缘使用 iKnife 进行术中诊断。