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Immune signatures in sentinel lymph nodes to predict distant metastases in malignant melanoma

Project description

Imaging panel for malignant melanoma diagnosis

Malignant melanoma has a 3 % lifetime incidence and lacks effective diagnostic tools for immunotherapy. Evaluating sentinel lymph nodes (sLNs) is crucial for determining the risk of metastasis. A study of 69 patients utilised spatial transcriptomics and machine learning, achieving 93 % accuracy in predicting metastases from involved sLNs and 79 % from uninvolved ones, indicating improved diagnostic potential. The ERC-funded MelanomaLNs project will develop a multiplexed imaging panel to profile immune organisation in primary tumours and lymph nodes, aiding patient diagnosis and stratification. Designed for clinical workflows, it will be tested on 500 patients with melanoma. This diagnostic assay aims to identify high-risk patients for timely intervention while sparing low-risk patients from unnecessary treatments.

Objective

Malignant melanoma is a deadly disease with a 3% lifetime incidence. Currently, no clinically approved companion diagnostics exist for immunotherapy in melanoma, and sentinel lymph node (sLN) evaluation remains the cornerstone of clinical decision-making. A sensitive, robust, and clinically applicable method for identifying patients at risk of developing metastatic disease is urgently needed.
Studies in murine models have shown that lymph nodes (LNs) play a dual role in tumor immunity, both supporting immune activation essential for immunotherapy and paradoxically promoting metastatic spread by inducing systemic tolerance. We hypothesized that sLNs exhibit both pro- and anti-tumorigenic roles, varying across patients and disease stages. In a study of 69 melanoma patients, we applied spatial transcriptomics and proteomics to analyze sLNs, revealing immunological organization patterns associated with these opposing roles. A machine learning model trained on this data predicted distant metastases with 93% and 79% accuracy in involved and uninvolved LNs, respectively, demonstrating strong potential to improve clinical diagnostics.
Building on these findings, we propose developing a multiplexed imaging panel to profile immune organization in both primary tumors and lymph nodes to guide patient diagnosis and stratification. This panel will be designed for compatibility with clinical workflows and tested on an independent validation cohort of 500 melanoma patients. To pave the way for commercialization, we will explore the market and value chain, identify and engage with relevant industry players and set up a commercialization plan with the aim of positioning our innovation as the new standard for diagnosing and managing melanoma patients. Our diagnostic assay will enhance treatment decisions by identifying high-risk patients at diagnosis, ensuring they receive timely intervention while sparing low-risk patients from unnecessary, potentially harmful and costly treatments.

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HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

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Call for proposal

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(opens in new window) ERC-2025-POC

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Host institution

WEIZMANN INSTITUTE OF SCIENCE
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 150 000,00
Address
HERZL STREET 234
7610001 Rehovot
Israel

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Activity type
Higher or Secondary Education Establishments
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Total cost

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Beneficiaries (1)

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