# Multi-color Mapping of Cancer Molecular Signatures and Tumor microenvironment

> **NIH NIH R33** · GEORGIA STATE UNIVERSITY · 2020 · $80,860

## Abstract

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.

## Key facts

- **NIH application ID:** 10169065
- **Project number:** 3R33CA235319-02S1
- **Recipient organization:** GEORGIA STATE UNIVERSITY
- **Principal Investigator:** Jenny J. Yang
- **Activity code:** R33 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $80,860
- **Award type:** 3
- **Project period:** 2019-07-18 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10169065

## Citation

> US National Institutes of Health, RePORTER application 10169065, Multi-color Mapping of Cancer Molecular Signatures and Tumor microenvironment (3R33CA235319-02S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10169065. Licensed CC0.

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