Cellular, molecular and quantitative imaging analysis of screening-detected lung adenocarcinoma

筛查发现的肺腺癌的细胞、分子和定量成像分析

基本信息

批准号：
9338192
负责人：
PIERRE P. MASSION
金额：
$ 72.76万
依托单位：
VANDERBILT UNIVERSITY MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-24 至 2020-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9338192
关键词：
Academic Medical Centers Adenocarcinoma Adjuvant Adjuvant Therapy Aggressive behavior Area Behavior Benign Bioinformatics Biological Biological Markers Biometry Biopsy Blood Cancer Biology Cancer Center Cells Cellular biology Cessation of life Clinical Clinical Data Clinical Management Collaborations Country DNA analysis Data Data Element Databases Discrimination Disease Early Detection Research Network Environment Epidemiology Fertilization Freezing Funding Future Genes Genomics Goals Health Care Costs Heterogeneity Image Image Analysis Indolent Institution Inter-tumoral heterogeneity Intervention Investigation Laboratories Light Lung Adenocarcinoma Lung nodule Malignant - descriptor Malignant Neoplasms Malignant neoplasm of lung Measurement Medical center Modeling Molecular Molecular Analysis Morbidity - disease rate Natural History Nodule Operative Surgical Procedures Pathology Patients Phenotype Positioning Attribute Procedures Prospective Studies Proteomics Provider Pulmonology Research Research Personnel Resected Risk Science Solid Standardization Technology Testing Tissues Work base cancer cell cancer risk cellular imaging chemotherapy circulating DNA circulating biomarkers cohort design follow-up functional genomics high throughput screening improved interdisciplinary approach low-dose spiral CT lung cancer screening molecular imaging molecular marker molecular/cellular imaging multidisciplinary new technology novel phenotypic biomarker predictive modeling programs prospective public health relevance quantitative imaging repository screening single cell analysis standard of care synergism tumor tumor DNA tumor heterogeneity tumor microenvironment

项目摘要

DESCRIPTION (provided by applicant): Suspicious screening-detected lung nodules present a formidable challenge to patients and their providers. The standard of care lacks accuracy in predicting a) malignancy from benign disease and b) indolent vs aggressive behavior. The answer to these questions justifies diametrically opposed strategies (biopsy vs follow up) each of which carries huge consequences including cure of the cancer, risk of death during a procedure or risk of dying from not intervening early in the disease. This application will focus o the behavior of early stage adenocarcinoma of the lung and not on the distinction between benign from malignant nodules. We assembled a unique multidisciplinary group of experts to tackle this problem in an original way. We will develop a retrospective and a prospective repository for both tissue (ADC fresh frozen tissues, blood) and images from which we will derive detailed quantitative structural imaging analysis, targeted genomic analysis and single cell analysis to interrogate the functional genomics of these tumors. The integration of this multidimensional data imaging/molecular/cellular/epidemiology will allow us to identify and validate cellular and molecular determinants of tumor behavior in the context of their inter- and intra-tumor heterogeneity. With these results, we will be able to build integrated models of ADC behavior, validate a new genomic molecular test on circulating DNA and propose prospective studies that would eventually offer a different intervention based on these predictions i.e. surgery, vs no surgery, adjuvant immuno- or chemotherapy vs no adjuvant therapy and therefore reduce overtreatment and ultimately increase the rate of cure and reduce healthcare cost.

描述（由适用提供）：可疑筛查发现的肺结节对患者及其提供者提出了巨大的挑战。护理标准缺乏预测a）良性疾病和b）侵略行为的恶性肿瘤的准确性。这些问题的答案证明了截然相反的策略（活检与跟进）是合理的，每种策略都会带来巨大的后果，包括治愈癌症，在手术过程中死亡的风险或死于疾病早期的死亡风险。该应用将集中于肺的早期腺癌的行为，而不是在恶性结节中的良性之间的疾病。我们组建了一个独特的多学科专家小组，以原始方式解决这个问题。我们将开发一个回顾性和一个前瞻性存储库（ADC新鲜的冷冻组织，血液）和图像，我们将从中得出详细的定量结构成像分析，靶向基因组分析和单个细胞分析，以询问这些肿瘤的功能基因组学。这种多维数据成像/分子/细胞/流行病学的整合将使我们能够在其肿瘤间和肿瘤内异质性的背景下识别和验证肿瘤行为的细胞和分子确定剂。通过这些结果，我们将能够构建ADC行为的综合模型，验证针对循环DNA的新基因组分子测试和建议的前瞻性研究，这些研究最终将根据这些预测（即手术，无手术，调整化学疗法调整免疫或化学疗法）提供不同的干预措施，因此不调整治疗，因此不调整治疗，因此减少了过度处理和最终的成本，并降低了cure的成本。