Translational imaging biomarkers of the tumor microenvironment in early prostate cancer

早期前列腺癌肿瘤微环境的转化成像生物标志物

基本信息

批准号：
10698133
负责人：
MARTIN G POMPER
金额：
$ 28.94万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-15 至 2027-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10698133
关键词：
3-Dimensional Acute Animals Appearance Architecture Area Atrophic Benign Carcinoma Cells Chronic Clinical Clinical Research Consent Cytotoxic T-Lymphocytes Data Development Disease Disease Outcome Epithelial-Stromal Communication FOLH1 gene Fibroblasts Future Gene Expression Genetic Genome Genomics Gland Gleason Grade for Prostate Cancer Goals Heterogeneity Histopathology Human Image Image Analysis Immune Immunohistochemistry Inflammation Inflammatory Intercept Lesion Link Longitudinal Studies Machine Learning Macrophage Macrophage Colony-Stimulating Factor Receptor Magnetic Resonance Imaging Malignant - descriptor Malignant Neoplasms Malignant neoplasm of prostate Maps Measures Mutation Neoplasm Metastasis Noninfiltrating Intraductal Carcinoma Outcome PTEN gene Pathologic Pathology Patient imaging Patients Pattern Phenotype Positron-Emission Tomography Primary Neoplasm Prostate Prostate carcinoma Prostatectomy Prostatic Radiochemistry Radiology Specialty Regulatory T-Lymphocyte Series Signal Transduction Signaling Protein Staging Stains TP53 gene Testing Time Tumor Markers X-Ray Computed Tomography cell type combat design epigenomics fibroblast-activating factor high risk image translation imaging agent imaging biomarker indexing mouse model multimodality neoplastic cell novel patient subsets permissiveness prognostic prospective prostate cancer model prostate cancer risk radiomics standard of care translational goal tumor tumor microenvironment whole slide imaging

项目摘要

Project Summary The goal of this translational project is to link the genetic and cellular features of the overarching, proving ground [cancer-permissive tumor microenvironment (TME)] hypothesis of this U54 application to imaging biomarkers that can be used clinically to detect and ultimately intercept prostate cancer. Little is known about the cellular subtypes that participate in the epithelial-stromal interactions in prostate cancer, or about the timing of their appearance during progression. We have developed a series of translational imaging agents designed to measure cancer epithelium and specific cells within the TME. We will leverage a subset of those agents to understand quantitatively the TME in prostate cancer so that it can be detected and reprogrammed early during malignant transformation. In Aim 1 we will image patients with primary prostate cancer prospectively with multi- parametric magnetic resonance imaging (mpMRI) and 18F-DCFPyL (PyL) positron emission tomography/computed tomography (PET/CT), which targets the prostate-specific membrane antigen (PSMA). We will perform standard-of-care PyL PET/CT imaging on patients with intermediate to high-risk prostate cancer prior to prostatectomy. We will quantify and correlate between imaging and pathology with the hypothesis that PSMA-low regions in otherwise high-grade tumors correlate with adverse pathology at prostatectomy in an effort to understand better the heterogeneity of primary disease. We will also compare PyL PET/CT with the cellular composition and spatial architecture of immune and stromal compartments of the prostate cancer TME. We will also retrospectively use prostatectomies from the same patients that were consented for genomic studies in Project 2. We will test the hypothesis that PyL PET/CT measured PSMA levels will directly correlate with MYC expression, MYC copy number gain, PTEN loss, and TP53 mutation. We will also determine in an unbiased manner which gene expression, genomic and epigenomic alterations best correlate with PSMA PET imaging features. We will also employ radiomic and machine-learning approaches not only to subtype patients with prostate cancer into prognostic groups, as we have done before, but also to predict who may have aggressive disease on initial PyL PET/CT staging. For this we will require merging not only the mpMRI and PyL PET/CT data, but also the histopathology, relevant genomics, and available protected historical information. Aims 2 and 3 involve longitudinal studies in the BMPC murine model, which we have developed and recapitulates human prostate cancer according to a specific timetable. We will determine the extent of macrophages and cancer- associated fibroblasts in and around the BMPC tumors as they develop over time and correlate their presence with imaging by small animal PET/MR. We will use novel imaging agents that we have developed, which target CSF1R (macrophages) and FAP (CAFs), and correlate the results with immunohistochemistry and genomics. Through careful radiologic-pathologic correlation, this project will provide rationale for future clinical studies to understand better the TME in prostate cancer, and how it can be reprogrammed to combat this disease.

项目概要这个转化项目的目标是将总体试验场的遗传和细胞特征联系起来 [癌症许可肿瘤微环境 (TME)] U54 在成像生物标志物中应用的假设可用于临床检测并最终拦截前列腺癌。人们对细胞知之甚少参与前列腺癌上皮-间质相互作用的亚型，或它们发生的时间进展过程中的出现。我们开发了一系列转化成像剂，旨在测量 TME 内的癌上皮和特定细胞。我们将利用这些代理的子集来定量了解前列腺癌中的 TME，以便能够在早期检测到并重新编程恶变。在目标 1 中，我们将使用多种方法对原发性前列腺癌患者进行前瞻性成像。参数磁共振成像 (mpMRI) 和 18F-DCFPyL (PyL) 正电子发射断层扫描/计算机断层扫描 (PET/CT)，针对前列腺特异性膜抗原 (PSMA)。我们将为中高危前列腺癌患者进行标准护理 PyL PET/CT 成像前列腺切除术之前。我们将量化成像和病理学之间的关系，并假设：高级别肿瘤中的 PSMA 低区域与前列腺切除术中的不良病理相关更好地了解原发疾病的异质性。我们还将 PyL PET/CT 与细胞前列腺癌 TME 的免疫和基质区室的组成和空间结构。我们将还回顾性地使用来自同意进行基因组研究的同一患者的前列腺切除术项目 2. 我们将检验以下假设：PyL PET/CT 测量的 PSMA 水平将与 MYC 直接相关表达、MYC 拷贝数增加、PTEN 丢失和 TP53 突变。我们还将公正地确定基因表达、基因组和表观基因组改变与 PSMA PET 成像最相关的方式特征。我们还将采用放射组学和机器学习方法，不仅针对亚型患者正如我们之前所做的那样，将前列腺癌分为预后组，而且还可以预测谁可能具有侵袭性初始 PyL PET/CT 分期的疾病。为此，我们不仅需要合并 mpMRI 和 PyL PET/CT 数据，还包括组织病理学、相关基因组学和可用的受保护历史信息。目标 2 和 3 涉及 BMPC 小鼠模型的纵向研究，该模型是我们开发的并概括了人类前列腺癌按照特定的时间表进行。我们将确定巨噬细胞和癌症的程度- BMPC 肿瘤内部和周围的相关成纤维细胞随着时间的推移而发展并与其存在相关联通过小动物 PET/MR 成像。我们将使用我们开发的新型显像剂，其目标是 CSF1R（巨噬细胞）和 FAP（CAF），并将结果与免疫组织化学和基因组学相关联。通过仔细的放射学-病理学相关性，该项目将为未来的临床研究提供理论依据更好地了解前列腺癌中的 TME，以及如何对其进行重新编程以对抗这种疾病。