ArticleDiscover oncology2026
Ligand-receptor pair-based signature score derived from on-treatment tumor specimens predicts immune checkpoint blockade response in metastatic melanoma.
Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Distinct transcriptomic features of tumor and stromal cells in direct contact in luminal and triple-negative breast cancers.Exploration of targeted anti-tumor therapy · 2026Article
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6 authors.
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Abstract
Immune checkpoint blockade (ICB) therapy has transformed the treatment landscape for metastatic melanoma, yet predicting therapeutic response remains a significant challenge. This study hypothesizes that coordinated ligand-receptor (LR) interactions within the tumor microenvironment (TME) critically influence ICB efficacy and proposes that a novel LR pair-based signature score (LRPS) derived from on-treatment samples can predict clinical outcomes. In this study, we analyzed publicly available transcriptomic and clinical datasets comprising 144 patients and 168 on-treatment tumor samples from five independent cohorts (GEO: GSE120575, GSE115821, GSE168204; BioProject: PRJEB23709; dbGaP: phs001919.v1.p1; EGA: EGAD00001005738). We identified seven LR pairs (FLT3-FLT3LG, LY9-LY9, CD5-CD5, CD40LG-ITGA2B/ITGB3, APP-CD74, TNFRSF17-TNFSF13, FCER2-ITGAV/ITGB3) significantly associated with treatment outcomes. LRPS demonstrated strong predictive power, achieving an area under the ROC curve (AUC) exceeding 0.80 in four independent cohorts. Patients in the high-LRPS group exhibited higher ICB response rates (up to 76.2%) and significantly better progression-free survival (PFS) and overall survival (OS) compared with the low-LRPS group. In conclusion, we identified and verified an LRPS signature that provides a theoretical basis for applying such signatures derived from on-treatment tumor samples to predict therapeutic responses to ICB therapies.
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