DEVELOPMENT OF AN AUTOMATED CARTRIDGE-BASED BREAST CANCER DETECTION ASSAY- AN ACADEMIC-INDUSTRIAL PARTNERSHIP

开发基于试剂盒的自动化乳腺癌检测方法——学术与工业合作

基本信息

批准号：
10417432
负责人：
SARASWATI SUKUMAR
金额：
$ 59.54万
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：
2022-07-11 至 2027-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10417432
关键词：
2019-nCoV Affect Africa Africa South of the Sahara Age Asia Benign Biological Assay Biopsy Body mass index Breast Breast Cancer Detection Breast Cancer Early Detection Cancer Detection Cessation of life Characteristics Clinic Clinical Clinical Research Collaborations Communicable Diseases Communities Core Biopsy DNA DNA Modification Process Developing Countries Development Diagnosis Diagnostic Disease Early Diagnosis Ensure Equilibrium Female Breast Carcinoma Fine needle aspiration biopsy Future Generations Genes Goals Gold HIV-1 Hour Industrialization Intervention Laboratories Legal patent Lesion Malignant - descriptor Malignant Neoplasms Mammary Neoplasms Manuals Mass in breast Measures Mediating Methods Methylation Modification Molecular Molecular Diagnosis Palpable Pathologist Pathology Patients Performance Persons Population Predictive Value Prospective Studies Publishing Race Reproducibility Resource-limited setting Sampling Savings Sensitivity and Specificity Slide South Africa Specificity Techniques Testing Time Tissues Training Tumor Subtype Underserved Population United States Validation Woman advanced disease base biomarker panel bisulfite breast cancer diagnosis breast lesion clinical practice commercialization cost detection assay diagnostic tool gene panel high risk imaging facilities improved industry partner innovation low and middle-income countries malignant breast neoplasm methylation biomarker mortality operation patient subsets prototype rapid test sample collection screening tumor tumor DNA underserved area

项目摘要

Abstract. In many low- and middle-income countries (LMICs) breast cancer is diagnosed at advanced stages. Many women present with a palpable breast mass, which is rare in communities where breast screening is available. In addition to limited imaging facilities, prolonged diagnostic delays (76-630 days) due in part to the extreme shortage of pathologists (as few as 1 per million/population) contribute to a 5-year mortality rate up to 4 times higher than that in the US. An innovative solution to this problem could be an affordable, easily deployable molecular test to identify and prioritize women likely to have a malignancy for expedited biopsy and pathology review. It is well established that early detection of breast cancer improves survival. With our industrial partner, Cepheid, we propose to build on our published breast cancer detection prototype to develop an affordable, <3- hour, automated breast cancer detection (aBCD) assay that analyzes a panel of hypermethylated genes in breast fine needle aspirates (FNAs).The proposed innovations will cut the assay time in half, and reduce costs by at least 3-fold to provide a single-cartridge assay for quick cancer detection. In Aim 1a, we will optimize the Offboard bisulfite-mediated DNA conversion method and test its efficiency in Patient Set 1 FNAs (N= 29 malignant, 25 benign). In Aim 1b we will select one optimal 5-marker panel and test its performance using first, the gold standard, FFPE samples (N= 30 malignant, 30 benign), and then, Patient Set 2 FNAs (N=35 malignant, 35 benign). In Aim 1c, we will perform technical validation of the aBCD assay. Intra-assay reproducibility will be assessed on multiple sample collections of Patient Set 3 FNAs (N=30 malignant, 30 benign). Inter-operator reproducibility will be determined using replicate FNA slides from Patient Set 2 (N= 35 malignant, 35 benign). The goal of Aim 2a is to perform clinical validation of the aBCD assay. We will first select a threshold in a Training set of FNAs: Patient Set 4 (N=100 malignant, 100 benign) to optimally balance sensitivity and specificity, and validate performance of the selected threshold in a Test set of FNAs: Patient Set 5 (N= 180 malignant, 180 benign). We will measure the accuracy (sensitivity, specificity, and positive- and negative-predictive value) of aBCD-based diagnosis to distinguish benign versus malignant lesions using histopathological diagnosis of the core biopsy as the gold standard. Lastly, in Aim 2b, to determine whether select patient characteristics alter the performance of the aBCD assay, we will test its clinical accuracy among specific patient subgroups based on age, race, BMI, and tumor characteristics (grade, stage, tumor subtype). All these steps are necessary to ensure an accurate and reliable test. This intervention is paradigm shifting, and could revolutionize the current detection of breast cancer in underserved regions of the world by expedited treatment and, in turn, saving thousands of lives yearly. This study will also facilitate further development of the aBCD assay toward commercialization, making it accessible globally.

抽象的。在许多低收入和中等收入国家 (LMIC)，乳腺癌在晚期才被诊断出来。许多女性都出现可触及的乳房肿块，这在进行乳房筛查的社区中很少见可用的。除了有限的成像设施外，诊断延误时间较长（76-630 天），部分原因是病理学家极度短缺（每百万人口只有 1 人）导致 5 年死亡率高达比美国高4倍。这个问题的创新解决方案可能是一种经济实惠、易于部署的解决方案分子测试可识别并优先考虑可能患有恶性肿瘤的女性，以进行快速活检和病理学检查审查。众所周知，早期发现乳腺癌可以提高生存率。与我们的工业合作伙伴一起， Cepheid，我们建议以我们已发布的乳腺癌检测原型为基础，开发一种负担得起的、<3- 小时自动乳腺癌检测 (aBCD) 分析，分析乳房中的一组高甲基化基因细针抽吸 (FNA)。所提出的创新将把检测时间缩短一半，并降低成本至少 3 倍，以提供用于快速癌症检测的单盒测定。在目标 1a 中，我们将优化场外亚硫酸氢盐介导的 DNA 转换方法并测试其在患者组 1 FNA 中的效率（N= 29 恶性，25 良性）。在目标 1b 中，我们将选择一个最佳 5 标记组并首先使用以下方法测试其性能：金标准，FFPE 样本（N= 30 个恶性，30 个良性），然后，患者组 2 FNA（N=35 个恶性，30 个良性） 35 良性）。在目标 1c 中，我们将对 aBCD 测定进行技术验证。测定内重现性将对患者组 3 FNA 的多个样本集合进行评估（N = 30 例恶性，30 例良性）。跨运营商将使用来自患者组 2 的复制 FNA 载玻片（N= 35 例恶性，35 例良性）来确定再现性。目标 2a 的目标是对 aBCD 测定进行临床验证。我们首先选择一个阈值 FNA 训练集：患者集 4（N=100 例恶性，100 例良性），以最佳平衡敏感性和特异性，并验证 FNA 测试集中所选阈值的性能：患者集 5（N= 180 恶性，180 良性）。我们将测量的准确性（敏感性、特异性以及阳性和阴性预测值）基于 aBCD 的诊断，使用组织病理学诊断来区分良性病变和恶性病变核心活检作为金标准。最后，在目标 2b 中，确定选定的患者特征是否会改变 aBCD 检测的性能，我们将根据以下数据在特定患者亚组中测试其临床准确性年龄、种族、BMI 和肿瘤特征（分级、分期、肿瘤亚型）。所有这些步骤都是必要的，以确保准确可靠的测试。这种干预正在转变范式，可能会彻底改变当前的检测通过快速治疗，在世界上服务欠缺的地区减少乳腺癌的发病率，从而挽救数千人的生命每年生活。这项研究还将促进 aBCD 测定的进一步商业化发展，使其在全球范围内都能访问。