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

• 批准号: 10227792
• 负责人: Kristine Glunde
• 金额: $ 26.64万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 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/10227792
• 关键词: Address; Area; Automobile Driving; Biological Markers; Biopsy; Breast Cancer Patient; Breast-Conserving Surgery; Cancer Patient; Chemotherapy and/or radiation; 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; Prognosis; Prognostic Marker; Proteins; Proteome; Protocols documentation; 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 progression; breast cancer survival; clinical translation; clinically relevant; cohort; imaging approach; improved; innovation; ionization; lipidome; lymph nodes; malignant breast neoplasm; metabolome; molecular mass; molecular pathology; outcome prediction; predictive marker; prognostic; scale up; tool; tumor; tumor hypoxia; tumor microenvironment

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.

项目摘要 这项应用的总体目标是开发低氧衍生的预后生物标志物来预测乳房 来自人类乳腺癌组织样本的癌症进展和患者预后。在之前由NIH资助的 项目已经确定了乳腺肿瘤微环境(TME)中的缺氧驱动信号网络，通过 多模式成像结合组学方法在临床前模型中的应用。乳房TME含有几个 引起转移和驱动血管生成、侵袭的空间异质性缺氧区改变 新陈代谢，对放射和化疗的抵抗力。低氧肿瘤区域也是已知的选择 具有最高转移扩散能力的侵袭性癌症表型。我们已经确定了重要的 在人乳腺癌异种移植模型中，缺氧肿瘤区域的分子特征发生了变化 确认发生重大改变的代谢物、脂质和蛋白质的清单和网络。我们建议 现在，在这些研究的基础上，开发快速可重复的临床样品制备和质谱学 成像(MSI)协议，允许在临床病理实验室中无缝地高通量使用 结合组织学和免疫组织化学方法。我们将在大量的人类乳腺癌组织中进行测试 低氧代谢组、脂组和蛋白质组特征的样本具有预后临床价值。为此， 我们将使用创新的多酶组织上消化蛋白质和多糖，反应解吸 用于增强代谢标志物发现的电喷雾电离(DESI)和基于MSI的臭氧分解(OzID) 飞行中的脂类异构体成像。在目标2中，我们将使用这些MSI方法来分析组织微阵列 从1000多名乳腺癌患者的原发肿瘤活检组织中检测是否存在低氧分子 签名可以预测患者的预后、复发和5年生存率。在目标3中，我们将解决大多数 乳腺癌的生命威胁方面，转移的形成，并调查是否缺氧区 原发人类乳腺肿瘤正在推动转移瘤的发展。拟议的研究将确定 低氧导致乳腺癌预后更差和转移的关键分子网络。 MSI的最新进展显著提高了其成像速度，使其现在可以进行 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 早期关于乳房内缺氧的影响的研究直接在大的患者队列中进行。我们会在临床上 评估基质辅助激光解吸/电离(MALDI)MSI作为诊断工具与 常规临床病理检查有助于准确判断乳腺癌的分子预后。大范围的 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使用 MSI应用于保乳手术中准确的术中边缘检测 使用iKnife进行术中诊断。

项目成果

Clinical importance of high-mannose, fucosylated, and complex N-glycans in breast cancer metastasis.

• DOI: 10.1172/jci.insight.146945
• 发表时间: 2021-12-22
• 期刊: JCI insight
• 影响因子: 8
• 作者: Ščupáková K;Adelaja OT;Balluff B;Ayyappan V;Tressler CM;Jenkinson NM;Claes BS;Bowman AP;Cimino-Mathews AM;White MJ;Argani P;Heeren RM;Glunde K
• 通讯作者: Glunde K

A multimodal pipeline using NMR spectroscopy and MALDI-TOF mass spectrometry imaging from the same tissue sample.

• DOI: 10.1002/nbm.4770
• 发表时间: 2023-04
• 期刊: NMR in biomedicine
• 影响因子: 2.9

Molecular Effects of Doxorubicin on Choline Metabolism in Breast Cancer.

• DOI: 10.1016/j.neo.2017.05.004
• 发表时间: 2017-08
• 期刊: Neoplasia (New York, N.Y.)
• 作者: Cheng M;Rizwan A;Jiang L;Bhujwalla ZM;Glunde K
• 通讯作者: Glunde K

Unlabeled aspirin as an activatable theranostic MRI agent for breast cancer.

• DOI: 10.7150/thno.53147
• 发表时间: 2022
• 期刊: Theranostics
• 影响因子: 12.4
• 作者: Pavuluri K;Yang E;Ayyappan V;Sonkar K;Tan Z;Tressler CM;Bo S;Bibic A;Glunde K;McMahon MT
• 通讯作者: McMahon MT

Cellular resolution in clinical MALDI mass spectrometry imaging: the latest advancements and current challenges.

• DOI: 10.1515/cclm-2019-0858
• 发表时间: 2020-06-25
• 期刊: Clinical chemistry and laboratory medicine
• 影响因子: 6.8