Personalizing immunotherapy in HER2+ breast cancer through quantitative imaging

通过定量成像对 HER2 乳腺癌进行个性化免疫治疗

基本信息

批准号：
10570913
负责人：
Anna C. Sorace
金额：
$ 40.5万
依托单位：
UNIVERSITY OF ALABAMA AT BIRMINGHAM
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-03-01 至 2025-02-28
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10570913
关键词：
Biological Biological Models Blood Vessels Breast Breast Cancer Patient Calibration Caring Clinical Clinical Trials Combined Modality Therapy Cytotoxic Chemotherapy Data Disease Dose Drug Delivery Systems Drug Kinetics Drug Synergism ERBB2 gene Epidermal Growth Factor Receptor Equilibrium Flow Cytometry Goals Healthcare Histology Human Hypoxia Image Imaging Techniques Immune response Immune system Immunotherapy Infiltration Magnetic Resonance Imaging Mainstreaming Malignant Neoplasms Mammary Neoplasms Maps Measures Medical Imaging Metastatic malignant neoplasm to brain Methods Modality Modeling Mus Myelogenous Myeloid Cells Necrosis Neoplasm Metastasis Pathway interactions Patient Care Patient-Focused Outcomes Patients Perfusion Positron-Emission Tomography Prediction of Response to Therapy Regimen Research Risk Route Schedule Solid Neoplasm Systemic Therapy T-Lymphocyte Techniques Testing Therapeutic Therapeutic Effect Toxic effect Translations Trastuzumab Treatment Efficacy Treatment Protocols Tumor Biology Tumor Cell Invasion Validation anti-PD-1 anti-cancer cancer care cancer therapy cell killing chemotherapy clinically relevant contrast enhanced cytotoxic experience high risk human model immunogenic improved in vivo individual patient malignant breast neoplasm mathematical model mouse model neoplastic cell neovascularization optimal control theory overexpression patient derived xenograft model personalized approach personalized immunotherapy personalized medicine quantitative imaging response serial imaging standard of care synergism systemic toxicity targeted treatment treatment optimization treatment response treatment strategy tumor tumor growth tumor microenvironment

项目摘要

PROJECT SUMMARY/ABSTRACT The overall goal of this proposal is to integrate advanced imaging and mathematical modeling to optimize combination treatments involving immunotherapy in human epidermal growth factor receptor type 2 positive (HER2+) breast cancer. Current standard-of-care therapeutic regimens and even clinical trials are limited because they are not personalized based on the tumor biology of the individual patient, potentially diminishing the efficacy of the treatment. This proposed research will employ noninvasive, quantitative magnetic resonance imaging (MRI) and positron emission tomography (PET) to inform mathematical models to direct timing for multi-modal therapies in HER2+ breast cancer. Overexpression of HER2 is indicative of more aggressive disease with five times higher risk of metastasis, with increased risk of breast-to-brain metastases, compared to HER2- patients. We have extensive experience and expertise in using quantitative medical imaging techniques to assess and predict treatment response to anti-cancer therapies. Additionally, we have shown that trastuzumab dosing prior to cytotoxic treatment (instead of simultaneous dosing of combination therapies) has potential to improve vascular delivery and oxygenation in HER2+ breast cancer tumors, which in turns sensitizes the tumor for cytotoxic therapies, reduces metastatic potential, improves drug delivery and reduces systemic toxicity. As immunotherapy becomes mainstream for many solid tumors, it is essential to develop techniques to both personalize and optimize therapeutic efficacy and decrease systemic toxicity. Thus, our central hypothesis is that quantitative imaging integrated with mathematical modeling can enhance personalization of treatment strategies and increase efficacy (additive and synergistic) of combination therapies with immunotherapy in HER2+ breast cancer. To achieve this goal, we have identified the following specific aims: 1) Quantify biological changes to immuno- and targeted therapy in HER2+ breast cancer with quantitative imaging, 2) Build a mathematical model of biological alterations to immunotherapy in HER2+ breast cancer, and 3) Employ model forecasting and quantitative imaging to guide combination therapy. We will exploit the alterations in biological changes, such as vascular delivery (evaluated with dynamic contrast enhanced (DCE)- MRI pharmacokinetic parameter, Ktrans) and oxygenation (evaluated with fluoromisonidazole (FMISO)-PET imaging metric, SUV) to inform a mathematical model in order to identify (and validate) optimal sequencing (order, timing, dose) to combination therapy (targeted, immunotherapy) for enhanced synergistic effects. Completion of this project provides a pathway to dramatically improve the efficacy of treatment strategies with immunotherapy for primary HER2+ breast cancer. Importantly, the proposed techniques provide a straightforward route for patient translation and potential to enhance care for HER2+ breast cancer patients.

项目概要/摘要该提案的总体目标是将先进的成像和数学建模集成到优化涉及人表皮生长因子受体免疫治疗的联合治疗 2 型阳性 (HER2+) 乳腺癌。当前的护理标准治疗方案甚至临床试验是有限的，因为它们没有根据个体患者的肿瘤生物学进行个性化，可能降低治疗效果。这项拟议的研究将采用非侵入性、定量磁力磁共振成像 (MRI) 和正电子发射断层扫描 (PET) 为数学模型提供指导 HER2+ 乳腺癌多模式治疗的时机。 HER2 的过度表达表明更多侵袭性疾病，转移风险高出五倍，乳腺至脑转移的风险增加，与 HER2- 患者相比。我们在使用定量医学成像方面拥有丰富的经验和专业知识评估和预测抗癌疗法的治疗反应的技术。此外，我们还证明了在细胞毒性治疗之前给予曲妥珠单抗（而不是同时给予联合疗法）具有改善 HER2+ 乳腺癌肿瘤血管输送和氧合的潜力，从而提高敏感性用于细胞毒性疗法的肿瘤，降低转移潜力，改善药物输送并减少全身性毒性。随着免疫疗法成为许多实体瘤的主流，开发技术以既可以个性化并优化治疗效果，又可以降低全身毒性。因此，我们的中心假设定量成像与数学建模相结合可以增强治疗的个性化策略并提高联合疗法与免疫疗法的疗效（相加和协同） HER2+ 乳腺癌。为了实现这一目标，我们确定了以下具体目标：1）量化生物通过定量成像改变 HER2+ 乳腺癌的免疫和靶向治疗，2) 建立 HER2+ 乳腺癌免疫治疗生物学改变的数学模型，以及 3) Employ 模型预测和定量成像来指导联合治疗。我们将利用生物的改变变化，例如血管输送（通过动态对比增强 (DCE) 评估 - MRI 药代动力学参数，Ktrans）和氧合（用氟米索硝唑 (FMISO)-PET 成像指标，SUV 评估）告知数学模型，以便识别（并验证）最佳测序（顺序、时间、剂量）联合治疗（靶向、免疫治疗）以增强协同效应。本项目完成情况提供了一条显着提高原发性免疫疗法治疗策略疗效的途径 HER2+ 乳腺癌。重要的是，所提出的技术为患者提供了一条简单的途径翻译和加强对 HER2+ 乳腺癌患者护理的潜力。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Author Correction: Positron emission tomography imaging with 89Zr-labeled anti-CD8 cys-diabody reveals CD8+ cell infiltration during oncolytic virus therapy in a glioma murine model.

作者更正：使用 89Zr 标记的抗 CD8 cys-双抗体的正电子发射断层扫描成像揭示了胶质瘤小鼠模型中溶瘤病毒治疗期间 CD8 细胞浸润。

DOI：
发表时间：
2021-10-08
期刊：
影响因子：
4.6
作者：
Kasten, Benjamin B;Houson, Hailey A;Coleman, Jennifer M;Leavenworth, Jianmei W;Markert, James M;Wu, Anna M;Salazar, Feli;Tavaré, Richard;Massicano, Adriana V F;Gillespie, G Yancey;Lapi, Suzanne E;Warram, Jason M;Sorace, Anna G
通讯作者：
Sorace, Anna G

Optimizing combination therapy in a murine model of HER2+ breast cancer.

优化 HER2 乳腺癌小鼠模型的联合治疗。

DOI：
发表时间：
2022-12-01
期刊：
影响因子：
7.2
作者：
Lima, Ernesto A B F;Wyde, Reid A F;Sorace, Anna G;Yankeelov, Thomas E
通讯作者：
Yankeelov, Thomas E

CD4 T-cell immune stimulation of HER2 + breast cancer cells alters response to trastuzumab in vitro.

HER2→乳腺癌细胞的 CD4 T 细胞免疫刺激改变了体外对曲妥珠单抗的反应。

DOI：
发表时间：
2020-11-10
期刊：
影响因子：
5.8
作者：
Song, Patrick N;Mansur, Ameer;Dugger, Kari J;Davis, Tessa R;Howard, Grant;Yankeelov, Thomas E;Sorace, Anna G
通讯作者：
Sorace, Anna G

Predicting response to combination evofosfamide and immunotherapy under hypoxic conditions in murine models of colon cancer.

预测结肠癌小鼠模型缺氧条件下对依磷酰胺和免疫疗法联合治疗的反应。

DOI：
发表时间：
2023-09-15
期刊：
影响因子：
0
作者：
Lima, Ernesto A B F;Song, Patrick N;Reeves, Kirsten;Larimer, Benjamin;Sorace, Anna G;Yankeelov, Thomas E
通讯作者：
Yankeelov, Thomas E

[89Zr]-Pertuzumab PET Imaging Reveals Paclitaxel Treatment Efficacy Is Positively Correlated with HER2 Expression in Human Breast Cancer Xenograft Mouse Models.

[89Zr]-帕妥珠单抗 PET 成像显示紫杉醇治疗效果与人乳腺癌异种移植小鼠模型中的 HER2 表达呈正相关。

DOI：
发表时间：
2021-03-12
期刊：
影响因子：
0
作者：
Lu, Yun;Li, Meng;Massicano, Adriana V F;Song, Patrick N;Mansur, Ameer;Heinzman, Katherine A;Larimer, Benjamin M;Lapi, Suzanne E;Sorace, Anna G
通讯作者：
Sorace, Anna G