A novel breast cancer therapy based on secreted protein ligands from CD36+ fibroblasts

基于 CD36 成纤维细胞分泌蛋白配体的新型乳腺癌疗法

基本信息

批准号：
10635290
负责人：
Bahram A. Parvin
金额：
$ 45.93万
依托单位：
UNIVERSITY OF NEVADA RENO
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-04-01 至 2028-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10635290
关键词：
3-Dimensional 3D Print Address Agonist Animals Apoptotic Biochemical Biochemical Markers Bioinformatics Biological Assay Breast Cancer Cell Breast Cancer Model Breast Cancer cell line Breast Cancer therapy CD36 gene Cell Death Cell Line Cell Surface Receptors Cell secretion ChIP-seq Clinical Complement Computing Methodologies Coupling Data Development Fatty acid glycerol esters Fibroblasts Goals Growth Heterogeneity Image Immunocompetent Immunocompromised Host Incubated Induction of Apoptosis Ligands Malignant Neoplasms Mammary Neoplasms Mammary gland Microscopy Modeling Molecular Morphology Multi-Drug Resistance Mus Organoids Pathway interactions Patients Pilot Projects Pre-Clinical Model Printing Property Protein Secretion Proteins Proteomics Public Health Recombinant Proteins Regulatory Element Resected Signal Pathway Signal Transduction Specificity System Targeted Research Techniques Technology Testing Therapeutic Time Toxic effect Transplantation Tumor Pathology Tumor Subtype Tumor Suppression Tumor Tissue activin A cancer cell cancer subtypes cancer therapy deep learning established cell line genetic signature genomic signature humanized mouse in vivo Model innovation insight learning strategy malignant breast neoplasm mammary mitochondrial dysfunction mouse model neoplastic cell new technology next generation novel novel therapeutics overexpression patient derived xenograft model physical property recruit response screening side effect systemic toxicity targeted treatment technology platform three dimensional cell culture transcription factor transcriptomics translational impact treatment response tumor tumor growth tumor microenvironment

项目摘要

A novel breast cancer therapy based on secreted protein ligands from CD36+ fibroblasts Cancer cells recruit and alter fibroblasts' biochemical and physical properties (FBs) to benefit their growth. Cancer-associated fibroblasts (CAFs) have emerged as potential targets for reprogramming the tumor microenvironment and for optimizing therapeutic strategies. However, there is a critical gap in research targeting tumors and CAFs simultaneously. Breast cancer tumors have distinct subtypes. And there is a lack of a biochemical marker exclusive to CAFs because of their heterogeneity. In fact, the currently available CAF- targeted therapies succumb to off-target effects, so their applications are limited. We aim to address this conundrum by testing our central hypothesis that factors secreted from non-cancer-associated FBs that express CD36—a cell surface receptor downregulated in CAFs—could be utilized as an alternative strategy to induce growth suppression in subtypes of breast cancer while upregulating CD36 in CAFs. This hypothesis is based on our pilot study showing that co-transplantation of breast cancer cells with CD36+ FBs dramatically suppressed tumor growth in animals. Furthermore, for the first time, we identified three active protein ligands in the secretome of CD36+ FBs and determined the effective concentration of their corresponding recombinant proteins that induce growth suppression in breast cancer cell lines while overexpressing CD36 in at least one CAF model. This study is significant because it will have a positive translational impact on breast cancer therapy with reduced toxicity. We will continue to test our hypothesis through two specific aims and the integration of a novel technological platform: Aim 1a will identify breast cancer subtypes that are sensitive to the three recombinant proteins (RPs). To this end, we will employ 3D cultures of the established cell lines and patient-derived organoids. We will also investigate the overexpression of CD36, by the active ligands, on a panel of CAFs. To facilitate a large number of experimental variables and intrinsic heterogeneity of organoids, we will develop a novel high-throughput imaging and high-content screening by coupling printed 3D cultures or organoids with 3D microscopy and deep learning methods for quantitative profiling of 3D organization and molecular features. Aim 1b will determine the mechanisms by which the three recombinant proteins induce (a) growth suppression in sensitive breast cancer subtypes or (b) upregulate CD36 in CAFs. Mechanistic studies will be anchored by apoptotic pathways, the cis- regulatory networks' prediction, and the application of bioinformatics techniques. It will also include the mechanisms of mitochondrial dysfunction induced by RPs. Aim 2 will use mouse models to investigate tumor suppression in sensitive cell lines, mouse tumors, and PDX models. Resected tumors will also be profiled for tumor morphology and molecular endpoints using advanced computational methods. In addition, in select cases, tumor sections will be complemented with spatial proteomics/transcriptomic for additional mechanistic studies. The study is innovative because it applies, for the first time, factors secreted from CD36+ FBs that confer tumor suppression and could be utilized to treat subtypes of breast cancer with few side effects.

基于 CD36+ 成纤维细胞分泌蛋白配体的新型乳腺癌疗法癌细胞招募并改变成纤维细胞的生化和物理特性（FB）以有利于其生长。癌症相关成纤维细胞（CAF）已成为重新编程肿瘤的潜在靶标然而，在靶向研究方面存在重大差距。乳腺癌和 CAF 肿瘤同时具有不同的亚型。由于其异质性，CAF 独有的生化标记物事实上，目前可用的 CAF-。靶向治疗会受到脱靶效应的影响，因此它们的应用受到限制。通过测试我们的中心假设来解决这个难题，即从表达非癌症相关的 FB 分泌的因子 CD36（一种在 CAF 中下调的细胞表面受体）可用作诱导乳腺癌亚型的生长受到抑制，同时 CAF 中的 CD36 上调。我们的初步研究表明，乳腺癌细胞与 CD36+ FB 的共同移植显着抑制此外，我们首次在分泌蛋白组中鉴定出三种活性蛋白配体。 CD36+ FBs 并确定了其相应重组蛋白的有效浓度，在至少一种 CAF 模型中，乳腺癌细胞系生长受到抑制，同时 CD36 过度表达。意义重大，因为它将对乳腺癌治疗产生积极的转化影响并降低毒性。我们将继续通过两个具体目标和新技术的整合来检验我们的假设平台：目标 1a 将识别对三种重组蛋白 (RP) 敏感的乳腺癌亚型。为此，我们将采用已建立的细胞系和患者来源的类器官的 3D 培养物。研究活性配体在一组 CAF 上的 CD36 过度表达以促进大量。根据实验变量和类器官的内在异质性，我们将开发一种新型的高通量通过将打印的 3D 培养物或类器官与 3D 显微镜和深度结合起来进行成像和高内涵筛选 3D 组织和分子特征定量分析的学习方法将确定目标 1b。三种重组蛋白诱导敏感乳腺癌生长抑制的机制亚型或 (b) CAF 中 CD36 的上调机制研究将以细胞凋亡途径（顺式）为基础。它还将包括监管网络的预测以及生物信息学技术的应用。 Aim 2 将使用小鼠模型来研究肿瘤引起的线粒体功能障碍的机制。敏感细胞系、小鼠肿瘤和 PDX 模型中的抑制也将被分析。此外，在某些情况下，使用先进的计算方法来确定肿瘤形态和分子终点。肿瘤切片将辅以空间蛋白质组学/转录组学，以进行额外的机制研究。该研究具有创新性，因为它首次应用了 CD36+ FB 分泌的因子，这些因子赋予肿瘤抑制并可用于治疗乳腺癌亚型，且副作用很少。