# Project 4

> **NIH NIH P50** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2021 · $282,230

## Abstract

PROJECT 4 SUMMARY
Despite recent therapeutic advances, prognosis for metastatic melanoma remains poor. Patients with primary
melanomas that are clinically and histologically similar at diagnosis often have vastly different outcomes:
whereas some are cured after initial surgical resection, others develop loco-regional recurrence(s) and
metastases, and eventually die. Such highly variable outcomes suggest underlying biological differences in
tumors (cell-intrinsic) and/or the patients themselves (host, cell-extrinsic, e.g. immune response). Molecular
alterations in tumors that can be robustly measured at diagnosis could be useful prognostic markers. Moreover,
given that some of these markers may also drive disease progression, their study may yield novel insights into
melanoma biology and generate new therapeutic targets. Recent trials have demonstrated that adjuvant
treatments for advanced melanoma (stage III and IV) reduce rates of melanoma recurrence and metastasis(1-3).
The success of adjuvant immune and small molecule inhibitor therapies has opened the possibility of extending
their use to stage II patients, for whom adjuvant therapy is yet not part of standard care. However, these therapies
have a significant toxicity, monetary cost, and unclear long-term benefit. Companion assays that might accurately
assign a patient’s risk of recurrence and even predict a patient’s benefit from adjuvant therapy—measured as
increased relapse-free survival (RFS)—could transform clinical management, reduce unnecessary morbidity and
toxicity, and dramatically improve patient outcomes. MicroRNAs (miRNAs) are promising biomarkers because
of their stability in tissues and fluids, and their demonstrated roles in cancer biology, including in melanoma. We
hypothesize that a set of candidate miRNAs can be integrated into a relapse-prediction model that can
predict stage II patient outcomes and benefits from adjuvant therapy, and that some prognostic miRNAs
functionally modulate melanoma progression. We identified a tumor tissue-based miRNA signature highly
prognostic of outcome for stage II melanoma patients and used an independent cohort of patients to demonstrate
its excellent discriminatory accuracy for identifying patients with short (<3 years) versus long (>3 years) RFS.
Here we propose to transform melanoma clinical practice and research paradigms by: 1) using NanoString, a
state-of-the-art technology currently employed in clinical labs, to develop a relapse-prediction model for stage II
melanoma patients based on miRNA expression in tumor samples (Aim 1); 2) identifying clinically relevant
miRNA-regulated mechanisms (e.g., cell proliferation, immune evasion) that drive metastatic spread of
melanoma cells from the primary tumor (Aim 2); and 3) testing the clinical validity of the relapse-prediction model
in a randomized, prospective trial, the gold standard for clinical validation of biomarkers (Aim 3). Successful
completion of this project promises to demonstr...

## Key facts

- **NIH application ID:** 10200704
- **Project number:** 5P50CA225450-03
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Eva Hernando
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $282,230
- **Award type:** 5
- **Project period:** 2019-07-19 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10200704

## Citation

> US National Institutes of Health, RePORTER application 10200704, Project 4 (5P50CA225450-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10200704. Licensed CC0.

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