# Using [6-13C,6-15N3]-L-Arginine for the molecular imaging of in vivo tumor arginase flux, and towards understanding the role of arginase isoforms in cancer metabolism.

> **NIH NIH F30** · WEILL MEDICAL COLL OF CORNELL UNIV · 2021 · $32,118

## Abstract

Project Summary & Abstract
 The various cellular components of the tumor microenvironment undergo metabolic changes to support
tumor growth and metastasis. Cancer metabolism is a clinically relevant and exciting field of study, as it
provides additional mechanistic insight into the onset and progression of this disease. An improved
understanding of this highly complex process can lead to the development of novel therapies, and
characterization of a tumor's metabolic phenotype may provide additional criteria for determining prognosis
and therapy selection. Towards the latter, the field of hyperpolarized MRI has emerged with the goal of
establishing an imaging modality that can non-invasively measure enzymatic flux in vivo.
 One way in which cancer metabolism is altered involves arginine utilization, stemming from the
overexpression of various arginase isoforms in cancer cells and tumor associated macrophages (TAMs), which
is thought to promote cellular proliferation and immunosuppression. Elevated arginase activity in the plasma of
cancer patients is associated with increasingly aggressive histological grading, and non-invasive quantification
of intratumoral arginase activity with hyperpolarized MRI may be an improved prognostic metric. Furthermore,
with the rising population of TAM-depleting immunotherapies, differences in arginase flux before and after the
initiation of TAM-depleting therapies may correlate to changes in TAM infiltration and provide insight into
therapeutic efficacy, which is another potential application of this modality.
 In addition, two arginase isoforms exist (arginase-1, A1, and -2, A2) which differ in cell-type-specific
expression and subcellular localization. Cytosolic A1 is favorably expressed in TAMs, whereas mitochondrial
A2 is expressed to some degree across most cell types, including cancer cells. The population and
concentrations of downstream enzymes also differs between the cytoplasm and mitochondrion, leading to the
hypothesis that A1 and A2 have different, cell-type-specific, pro-tumor functions in TAMs and cancer
cells. The individual cell-type-specific contributions of A1 and A2 to cellular metabolism and proliferation have
yet to be studied in the setting of cancer. With therapies that target arginine metabolism currently in Phase I
and II clinical trails, this knowledge will support the development of the future iterations of this class of therapy.
 I have optimized the synthesis of [6-13C,6-15N3]-L-arginine as a dual purpose probe for 1) use as a
hyperpolarized MRI probe for in vivo arginase activity measurements, and 2) LC/MS-based isotopic tracing
metabolomics experiments to test the working hypothesis. Information gained from this project may yield new
tools and metrics for patient stratification, and will add to the general understanding of cancer metabolism and
its role in cancer cell proliferation, collectively contributing towards the improvement of patient care and
providing additional mechanistic ...

## Key facts

- **NIH application ID:** 10082445
- **Project number:** 5F30CA225174-04
- **Recipient organization:** WEILL MEDICAL COLL OF CORNELL UNIV
- **Principal Investigator:** Andrew Cho
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $32,118
- **Award type:** 5
- **Project period:** 2018-01-22 → 2021-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10082445

## Citation

> US National Institutes of Health, RePORTER application 10082445, Using [6-13C,6-15N3]-L-Arginine for the molecular imaging of in vivo tumor arginase flux, and towards understanding the role of arginase isoforms in cancer metabolism. (5F30CA225174-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10082445. Licensed CC0.

---

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