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 该应用的总体目标是开发缺氧衍生的预后生物标志物来预测乳房 人类乳腺癌组织样本的癌症进展和患者结局。在以前的NIH资助中 项目已经确定了通过乳腺肿瘤微环境（TME）中缺氧驱动的信号网络 多模式成像与临床前模型中的OMICS方法相结合。乳房TME包含几个 在空间异质性低氧区域，诱导转移并驱动血管生成，侵袭，改变 代谢，对放射和化学疗法的抗性。还已知低氧肿瘤区域会选择 转移性扩散能力最高的侵略性癌症表型。我们已经明显地确定了 改变了人类乳腺肿瘤异种移植模型中低氧肿瘤区域的分子特征， 已确认的代谢物，脂质和蛋白质的列表和网络发生了显着改变。我们建议 现在通过开发快速可重复可重复的临床样品制备和质谱法来建立这些研究 成像（MSI）方案，可在临床病理实验室中高通量使用，并且无缝地使用 与组织学和免疫组织化学整合。我们将在大量人类乳腺癌组织中进行测试 样品如果缺氧代谢组，脂肪组和蛋白质组特征具有预后的临床价值。为此， 我们将采用创新的多酶在蛋白质和聚糖上的组织消化，反应性解吸 用于增强代谢标记发现的电喷雾电离（DESI）和基于MSI的臭氧溶解（ozid） 柔脂异构体成像。在AIM 2中，我们将使用这些MSI方法来分析组织微阵列 来自1000多名乳腺癌患者的原发性肿瘤的活检，以测试缺氧分子是否 签名可以预测患者的结果，复发和5年生存。在AIM 3中，我们将解决最多的问题 威胁乳腺癌的生命方面，转移的形成，并研究是否存在低氧区域 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 关键的分子网络通过这些网络使乳腺癌驱动乳腺癌的预后和转移较差。 MSI的最新发展已大大提高了其成像速度，现在可以执行 基于MSI的分子病理学在临床相关时间。这使我们能够翻译我们的结果 早期研究缺氧在乳房TME中对大型患者队列的影响。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 常规的临床病理检查，以准确地分子预后乳腺癌。大规模 我们应用中获得的代谢物和脂质特征将支持新兴的环境电离使用 MSI应用在乳房持续手术期间准确的术中边缘检测和 术中诊断使用IKNIFE。

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

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

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