# Noninvasive prediction of tumor response to gemcitabine using MRI

> **NIH NIH R01** · HUGO W. MOSER RES INST KENNEDY KRIEGER · 2020 · $373,288

## Abstract

The prediction of tumor response to chemotherapy can be achieved by elucidating the efficiency of drug
delivery to the targeted tumor cells, and the effectiveness of the delivered drug to be activated and act on tumor
cells. A non-invasive means that can answer these questions is essential for designing efficient and
personalized therapy, and is especially crucial to improve the efficacy of treating pancreatic ductal
adenocarcinoma (PDAC), one of the most lethal human malignancies. In the present study, we propose to
develop a highly translatable MRI technology to answer the two questions mentioned above in the gemcitabine
treatment of PADC, and hence to predict tumor responses. In particular, Our approach is based on a so-called
Chemical Exchange Saturation Transfer (CEST) MRI contrast mechanism, by which drugs are imaged directly
by their inherently carried exchangeable protons (OH, NH or NH2), at a detectability comparable to that for
Gd-based agents. Formulated on the basis of our preliminary results, we hypothesize that agents that contain
cytosine and cytidine, for instance gemcitabine, can be detected using CEST MRI, namely cytCEST. We
anticipate our approach can be used to predict tumor response to the gemcitabine treatment by assessing the
accumulation, biodistribution and retention of the drug in the tumor, without the need for imaging tags or
additional agents. To achieve our goal, we will first optimize and validate the cytCEST MRI detection of tumor
uptake and biodistribution of gemcitabine. Then we will develop cytCEST MRI as an effective means to detect
the activity of deoxycytidine kinase (dCK), one of the most important drug-resistance-related enzymes. Finally
the potential of cytCEST MRI to predict the response of pancreatic tumors to therapy will be examined on the
treatment in KPC genetically engineered mouse models using three different gemcitabine-based treatments.
Successful completion of this project will result in an imaging tool for the prediction of tumor response to
gemcitabine using the drug or its analog deoxycytidine directly as the imaging agent, namely label-free because
no chemical-modification is needed. It is expected that such a label-free approach can be rapidly translated to
the clinic, allowing clinicians to stratify patients prior to (or immediately after) the administration of gemcitabine
or other cytosine- or cytidine-based chemotherapeutic drugs and to choose the personalized treatment plan for
each group of patients.

## Key facts

- **NIH application ID:** 9878789
- **Project number:** 5R01CA211087-04
- **Recipient organization:** HUGO W. MOSER RES INST KENNEDY KRIEGER
- **Principal Investigator:** Guanshu Liu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $373,288
- **Award type:** 5
- **Project period:** 2017-03-07 → 2022-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9878789

## Citation

> US National Institutes of Health, RePORTER application 9878789, Noninvasive prediction of tumor response to gemcitabine using MRI (5R01CA211087-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9878789. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*