# Paradoxical roles of tumor lymphangiogenesis on tumor immunity and implications for immunotherapy - Resubmission 01

> **NIH NIH R01** · UNIVERSITY OF CHICAGO · 2020 · $370,575

## Abstract

Project Summary
In melanoma and other cancers, the expansion of the local lymphatic network via expression of VEGF-C in the
tumor microenvironment promotes metastasis and is widely correlated with poor prognosis. We and others
have shown that VEGF-C-activated lymphatic vessels play important immune suppressive roles in the tumor
microenvironment. Paradoxically, we have observed that in mouse melanoma models, lymphangiogenic tu-
mors were more responsive to immunotherapy, including in adoptive T cell therapy, dendritic cell vaccines, and
protein vaccination. Here we propose a research program that explores this other side of tumor lymphangio-
genesis, and suggest a novel hypothesis that while VEGF-C in the tumor microenvironment can induce in-
flammation and immune suppression, it also enhances the infiltration of naïve T cell infiltration, at least in part
by upregulating the lymphoid homing chemokine CCL21. This enhanced infiltration, in turn, can prime the tu-
mor for enhanced responsiveness to immunotherapy. Three aims are proposed to explore (i) validation and
mechanistic underpinnings in mouse models, (ii) relevance to human melanoma, and (iii) translational applica-
tion.

## Key facts

- **NIH application ID:** 9891035
- **Project number:** 5R01CA219304-03
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Melody Ann Swartz
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $370,575
- **Award type:** 5
- **Project period:** 2018-04-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9891035

## Citation

> US National Institutes of Health, RePORTER application 9891035, Paradoxical roles of tumor lymphangiogenesis on tumor immunity and implications for immunotherapy - Resubmission 01 (5R01CA219304-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9891035. Licensed CC0.

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