ArticleOncoimmunology2026
Integrating tumor and immune cell transcriptomics to predict immune checkpoint inhibitor primary resistance in metastatic melanoma.
Article in Oncoimmunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Dynamic Time-Resolved Remodeling of the Immune Microenvironment After Resistance to BRAF/MEK Inhibitors in Melanoma: Mechanisms, Biomarkers, and Emerging Therapeutic Strategies.International journal of molecular sciences · 2026Review
- Causal AI for cancer immunotherapy: a narrative framework review of target trial emulation, treatment-effect learning and clinical translation.Frontiers in immunology · 2026Review
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Authors and funding
9 authors.
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Abstract
The emergence of immune checkpoint inhibitors (ICIs) has transformed the treatment landscape of metastatic melanoma. However, despite its success, reliable biomarkers for predicting primary resistance are not available in clinical practice. This study seeks to identify predictors of primary resistance based on novel gene expression signatures. The transcriptomic profile of the tumor microenvironment was analyzed using tissue samples from 46 metastatic cutaneous melanoma patients collected prior to the initiation of ICIs therapy. A primary resistance predictive model was trained with the Discovery FFPE RNA-seq subcohort and validated using an independent external cohort of 54 samples. Additionally, liquid biopsy samples from peripheral blood mononuclear cells were analyzed in 8 patients using single-cell RNA sequencing (scRNA-seq) and in 46 patients using flow cytometry. We identified an 82-gene transcriptomic signature composed of tumor- and immune-related genes that stratifies metastatic cutaneous melanoma patients based on primary resistance to ICIs, with key markers including
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