# Project 4

> **NIH NIH P50** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2022 · $282,229

## 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 ...

## Key facts

- **NIH application ID:** 10434090
- **Project number:** 5P50CA225450-04
- **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE
- **Principal Investigator:** Eva Hernando
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $282,229
- **Award type:** 5
- **Project period:** 2019-07-19 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10434090

## Citation

> US National Institutes of Health, RePORTER application 10434090, Project 4 (5P50CA225450-04). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10434090. Licensed CC0.

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