Multi-color Mapping of Cancer Molecular Signatures and Tumor microenvironment

癌症分子特征和肿瘤微环境的多色绘图

• 批准号: 10169065
• 负责人: Jenny J. Yang
• 金额: $ 8.09万
• 依托单位: GEORGIA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-18 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10169065
• 关键词: 2019-nCoV; Acute; Address; Advanced Development; Animal Model; Atlas of Cancer Mortality in the United States; Binding; Biological Markers; Biology; Biopsy; COVID-19; Cancer Patient; China; Chronic; Clinical; Collagen; Color; Contrast Media; Coronavirus Infections; Data; Detection; Development; Diagnosis; Diagnostic; Diagnostic Imaging; Disease; Disease Outbreaks; Disease Progression; Early Diagnosis; Exhibits; Fibrosis; Funding; Future; Goals; Heart; High Resolution Computed Tomography; Hospitals; Image; Impairment; Infection; Injury; Ionizing radiation; Lung; Lung Neoplasms; Lung diseases; Lung infections; Magnetic Resonance Imaging; Malignant Neoplasms; Malignant neoplasm of lung; Medical; Metals; Metastatic Neoplasm to the Lung; Methodology; Molecular; Mus; Names; Neoplasm Metastasis; Non-Invasive Cancer Detection; Organ; Oxygen; Patients; Pattern; Penetration; Pharmaceutical Preparations; Pneumonia; Property; Proteins; Pulmonary Fibrosis; Radiation Tolerance; Radiologic Finding; Relaxation; Resolution; SARS coronavirus; Sampling Errors; Satellite Viruses; Sensitivity and Specificity; Severe Acute Respiratory Syndrome; Specificity; Staging; Symptoms; Thoracic Radiography; Tissues; Tumor stage; Validation; Viral; Virus; Virus Diseases; Virus-like particle; X-Ray Computed Tomography; base; cancer heterogeneity; chest computed tomography; density; design; effective therapy; high risk; imaging capabilities; imaging modality; imaging platform; improved; in vivo; in vivo imaging; lung imaging; molecular marker; mouse model; non-invasive imaging; novel; novel coronavirus; pandemic disease; patient stratification; prevent; quantitative imaging; respiratory; response; targeted treatment; treatment strategy; tumor microenvironment; tumor molecular fingerprint; viral detection; viral transmission

Abstract Since the recent identification of a novel coronavirus from the pneumonia outbreak in Wuhan, China, now named as SARS-CoV-2, the virus has spread globally very rapidly. SARS-CoV-2 is closely related to SARS-CoV emerged in 2003. While there are many factors associated the virus transmission, the pattern of SARS-CoV-2 spread is distinctly different from that of SARS-CoV. Evidence shows that there is virus transmission before onset of symptoms in patients. Diagnosis of the virus infection is more difficult because the infection of SARS- CoV-2 may be in the lower respiratory track. This proposal takes advantage of our pioneered imaging platform and protein agents to rapid develop pMRI diagnostic imaging with strong translational potential in facilitating effective treatment to halt further chronic and pandemic lung disease progression. It is highly transformative and specifically address the call of proposal for Urgent Supplement using existing imaging modality and MRI and largely extended its capability. The developed MRI diagnostic imaging with its high resolution, non-radiative, and much improved sensitivity than current CT in clinical will significantly facilitate accurate detection of coronavirus infection in patient and control of Covid-19 and other SARS-like COV infections.

摘要 自从最近从中国武汉的肺炎疫情中鉴定出一种新型冠状病毒，现在被命名为 作为SARS-CoV-2，该病毒在全球范围内传播非常迅速。SARS-CoV-2与SARS-CoV关系密切 出现在2003年。虽然有许多因素与病毒传播有关，但SARS-CoV-2的模式 传播与SARS-CoV明显不同。有证据显示， 患者出现症状。病毒感染的诊断更加困难，因为SARS的感染- CoV-2可能存在于下呼吸道。该提案利用了我们首创的成像平台 和蛋白质试剂来快速开发pMRI诊断成像， 有效的治疗，以阻止进一步的慢性和流行性肺病的进展。它具有高度的变革性， 具体解决使用现有成像模式和MRI的紧急补充提案的呼吁， 在很大程度上扩展了它的能力。MRI诊断成像具有高分辨率，无辐射， 在临床上比目前的CT灵敏度大大提高，将大大有助于准确检测冠状病毒 患者感染和控制Covid-19和其他SARS样COV感染。