Precision Tool Predicts Immunotherapy Treatment Failure in Melanoma Patients
Posted on 01 Aug 2025
Melanoma, though accounting for only about 4% of skin tumors, is the deadliest form of skin cancer due to its high potential to metastasize. While immunotherapy, especially PD-1 protein blockade, has revolutionized treatment for advanced melanoma, 40% to 60% of patients do not respond effectively. This not only exposes them to significant side effects but also imposes a heavy financial burden. In countries like Brazil, this poses serious challenges to healthcare systems, creating a pressing need to identify which patients will benefit from immunotherapy and to avoid unnecessary costs and treatment failures. Researchers have now developed a precision tool that can predict immunotherapy treatment failure, with the potential to personalize therapies and reduce healthcare costs.
In the study led by the Molecular Oncology Research Center at Hospital de Amor (Barretos, Brazil), researchers analyzed tumor samples from 35 patients with advanced melanoma treated with anti-PD-1 immunotherapy between 2016 and 2021. The team cross-referenced these samples with a panel of 579 genes related to immune system function, ultimately identifying four genes — CD24, NFIL3, FN1, and KLRK1 — whose increased expression correlated with treatment resistance. These genes are involved in immune evasion and suppression of the inflammatory response. For instance, CD24 acts as an immune checkpoint, while FN1 supports tumor growth, KLRK1 loses its immune activation function when dysregulated, and NFIL3 contributes to tumor escape. The study utilized NanoString technology, a cost-effective and accessible genetic analysis platform suitable for clinical use in resource-limited settings. Notably, the genetic signature also showed predictive power for early-stage melanoma patients, indicating its usefulness from the beginning of treatment planning.

The findings, published in the Journal of Molecular Medicine, were validated against two international patient cohorts, where the gene expression signature consistently predicted both treatment response and clinical outcomes. According to the results, patients with high expression of the four genes were 230 times more likely to fail immunotherapy, with only 5.9% surviving after five years compared to 48.1% in those with low gene expression. The research team is now working on patenting a genetic panel based on this signature, with plans to develop a commercial tool that can guide treatment decisions before initiating immunotherapy. Despite the study's small size and retrospective nature, the findings mark a significant advancement in personalized oncology in Brazil. The next step involves conducting larger studies to define a gene expression threshold that can reliably predict treatment failure.
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