ArticleNature communications2024
A machine learning model reveals expansive downregulation of ligand-receptor interactions that enhance lymphocyte infiltration in melanoma with developed resistance to immune checkpoint blockade.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed.
- Comprehensive overview of AI methodologies in nano-drug delivery Optimization and Design.NPJ precision oncology · 2026Review
- ICIsAtlas reveals a suppressive NK cell niche in pan-cancer immunotherapy profiles.Communications biology · 2026Article
- BRAF inhibitor resistance in melanoma: from resistance mechanisms to therapeutic innovations.Molecular biomedicine · 2026Review
- Cholesterol efflux protein, ABCA1, supports anticancer functions of myeloid immune cells.Science advances · 2026Article
- Combined assessment of ERO1A expression and CD163Frontiers in oncology · 2026Article
- From Slide to Insight: The Emerging Alliance of Digital Pathology and AI in Melanoma Diagnostics.Cancers · 2025Review
- Drug resistance in cancer: molecular mechanisms and emerging treatment strategies.Molecular biomedicine · 2025Review
- Artificial Intelligence for the Diagnosis and Management of Cancers: Potentials and Challenges.MedComm · 2025Review
- Overcoming resistance to anti-PD-L1 immunotherapy: mechanisms, combination strategies, and future directions.Molecular cancer · 2025Review
- Molecular stratification of prostate cancer through sensory perception-related multi-omics analysis reveals chemoresistant mechanisms.Cellular oncology (Dordrecht, Netherlands) · 2025Article
- Article
- Enhanced prediction of breast cancer patient response to chemotherapy by integrating deconvolved expression patterns of immune, stromal and tumor cells.bioRxiv : the preprint server for biology · 2025Article
- Optimizing Immunotherapy: The Synergy of Immune Checkpoint Inhibitors with Artificial Intelligence in Melanoma Treatment.Biomolecules · 2025Review
- Review
- Stratified analysis identifies HIF-2bioRxiv : the preprint server for biology · 2024Article
- A machine learning model reveals expansive downregulation of ligand-receptor interactions that enhance lymphocyte infiltration in melanoma with developed resistance to immune checkpoint blockade.Nature communications · 2024Article
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10 authors.
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Abstract
Immune checkpoint blockade (ICB) is a promising cancer therapy; however, resistance frequently develops. To explore ICB resistance mechanisms, we develop Immunotherapy Resistance cell-cell Interaction Scanner (IRIS), a machine learning model aimed at identifying cell-type-specific tumor microenvironment ligand-receptor interactions relevant to ICB resistance. Applying IRIS to deconvolved transcriptomics data of the five largest melanoma ICB cohorts, we identify specific downregulated interactions, termed resistance downregulated interactions (RDI), as tumors develop resistance. These RDIs often involve chemokine signaling and offer a stronger predictive signal for ICB response compared to upregulated interactions or the state-of-the-art published transcriptomics biomarkers. Validation across multiple independent melanoma patient cohorts and modalities confirms that RDI activity is associated with CD8 + T cell infiltration and highly manifested in hot/brisk tumors. This study presents a strongly predictive ICB response biomarker, highlighting the key role of downregulating chemotaxis-associated ligand-receptor interactions in inhibiting lymphocyte infiltration in resistant tumors.
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