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Deactivation of ligand-receptor interactions enhancing lymphocyte infiltration drives melanoma resistance to Immune Checkpoint Blockade.

ABSTRACT: Immune checkpoint blockade (ICB) is a promising cancer therapy; however, resistance often develops. To learn more about ICB resistance mechanisms, we developed IRIS (Immunotherapy Resistance cell-cell Interaction Scanner), a machine learning model aimed at identifying candidate ligand-receptor interactions (LRI) that are likely to mediate ICB resistance in the tumor microenvironment (TME). We developed and applied IRIS to identify resistance-mediating cell-type-specific ligand-receptor interactions by analyzing deconvolved transcriptomics data of the five largest melanoma ICB therapy cohorts. This analysis identifies a set of specific ligand-receptor pairs that are deactivated as tumors develop resistance, which we refer to as resistance deactivated interactions (RDI). Quite strikingly, the activity of these RDIs in pre-treatment samples offers a markedly stronger predictive signal for ICB therapy response compared to those that are activated as tumors develop resistance. Their predictive accuracy surpasses the state-of-the-art published transcriptomics biomarker signatures across an array of melanoma ICB datasets. Many of these RDIs are involved in chemokine signaling. Indeed, we further validate on an independent large melanoma patient cohort that their activity is associated with CD8+ T cell infiltration and enriched in hot/brisk tumors. Taken together, this study presents a new strongly predictive ICB response biomarker signature, showing that following ICB treatment resistant tumors turn inhibit lymphocyte infiltration by deactivating specific key ligand-receptor interactions.

SUBMITTER: Sahni S

PROVIDER: S-EPMC10602042 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Deactivation of ligand-receptor interactions enhancing lymphocyte infiltration drives melanoma resistance to Immune Checkpoint Blockade.

Sahni Sahil S Wang Binbin B Wu Di D Dhruba Saugato Rahman SR Nagy Matthew M Patkar Sushant S Ferreira Ingrid I Wang Kun K Ruppin Eytan E

bioRxiv : the preprint server for biology 20230922

Immune checkpoint blockade (ICB) is a promising cancer therapy; however, resistance often develops. To learn more about ICB resistance mechanisms, we developed IRIS (Immunotherapy Resistance cell-cell Interaction Scanner), a machine learning model aimed at identifying candidate ligand-receptor interactions (LRI) that are likely to mediate ICB resistance in the tumor microenvironment (TME). We developed and applied IRIS to identify resistance-mediating cell-type-specif ...[more]

PMID: 37886558

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Project description:BackgroundAlthough immune checkpoint inhibitor (ICI)-based therapy is advantageous for patients with advanced melanoma, resistance and relapse are frequent. Thus, it is crucial to identify effective drug combinations and develop new therapies for the treatment of melanoma. SGN1, a genetically modified Salmonella typhimurium species that causes the targeted deprivation of methionine in tumor tissues, is currently under investigation in clinical trials. However, the inhibitory effect of SGN1 on melanoma and the benefits of SGN1 in combination with ICIs remain largely unexplored. Therefore, this study aims to investigate the antitumor potential of SGN1, and its ability to enhance the efficacy of antibody-based programmed cell death-ligand 1 (PD-L1) inhibitors in the treatment of murine melanoma.MethodsThe antitumor activity of SGN1 and the effect of SGN1 on the efficacy of PD-L1 inhibitors was studied through murine melanoma models. Further, The Cancer Genome Atlas-melanoma cohort was clustered using ConsensusClusterPlus based on the methionine deprivation-related genes, and immune characterization was performed using xCell, Microenvironment Cell Populations-counter, Estimation of Stromal and Immune cells in MAlignant Tumor tissues using Expression data, and immunophenoscore (IPS) analyses. The messenger RNA data on programmed death-1 (PD-1) immunotherapy response were obtained from the Gene Expression Omnibus database. Gene Set Enrichment Analysis of methionine deprivation-up gene set was performed to determine the differences between pretreatment responders and non-responders.ResultsThis study showed that both, the intratumoral and the intravenous administration of SGN1 in subcutaneous B16-F10 melanomas, suppress tumor growth, which was associated with an activated CD8+T-cell response in the tumor microenvironment. Combination therapy of SGN1 with systemic anti-PD-L1 therapy resulted in better antitumor activity than the individual monotherapies, respectively, and the high therapeutic efficacy of the combination was associated with an increase in the systemic level of tumor-specific CD8+ T cells. Two clusters consisting of methionine deprivation-related genes were identified. Patients in cluster 2 had higher expression of methionine_deprivation_up genes, better clinical outcomes, and higher immune infiltration levels compared with patients in cluster 1. Western blot, IPS analysis, and immunotherapy cohort study revealed that methionine deficiency may show a better response to ICI therapy CONCLUSIONS：: This study reports Salmonella-based SGN1 as a potent anticancer agent against melanoma, and lays the groundwork for the potential synergistic effect of ICIs and SGN1 brought about by improving the immune microenvironment in melanomas.

Dataset Information

Deactivation of ligand-receptor interactions enhancing lymphocyte infiltration drives melanoma resistance to Immune Checkpoint Blockade.

Publications

Deactivation of ligand-receptor interactions enhancing lymphocyte infiltration drives melanoma resistance to Immune Checkpoint Blockade.

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