Multiomics integration analysis identifies tumor cell-derived MIF as a therapeutic target and potentiates anti-PD-1 therapy in osteosarcoma

• Published in: Journal for immunotherapy of cancer Vol. 13; no. 8; p. e011091
• Main Authors: Chen, Weidong, Liao, Yan, Yao, Hao, Zou, Yutong, Fang, Ji, Zhang, Jiongfeng, Guo, Zehao, Tu, Jian, Chen, Junkai, Huo, Zijun, Wen, Lili, Xie, Xianbiao
• Format: Journal Article
• Language: English
• Published: London BMJ Publishing Group Ltd 22.08.2025; BMJ Publishing Group LTD; BMJ Publishing Group
• Subjects: Acidosis; Algorithms; Basic and Translational Cancer Immunology; Biomarkers; Bone Cancer; Cancer therapies; Cell cycle; Cell death; Datasets; Genes; Immune checkpoint inhibitors; Immune modulatory; Immunotherapy; Macrophage; Medical prognosis; Metabolism; Metabolites; Original Research; Survival analysis; Visualization
• ISSN: 2051-1426; 2051-1426
• DOI: 10.1136/jitc-2024-011091

BackgroundOsteosarcoma is a highly aggressive cancer, and the efficacy of existing therapies has plateaued. Multiomics integration analysis can identify novel therapeutic targets for various cancers and therefore shows potential toward osteosarcoma treatment. This study aimed to leverage multiomics integration to develop a new risk model, characterizing the immune features of osteosarcoma to uncover novel therapeutic targets.MethodsMetabolomics profiling was conducted to identify key metabolites in osteosarcoma. Transcriptomic sequencing datasets were analyzed to identify prognostic genes related to key metabolic pathways and develop a prognostic risk model. Patients were then divided into high-risk and low-risk groups with distinct clinical outcomes based on the risk model. The single-sample gene set enrichment analysis, Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) algorithm, and xCell algorithms were used to evaluate the immune cell infiltration and activity. Single-cell RNA sequencing was used to explore cell-to-cell interactions within the tumor microenvironment. In vitro coculture functional assays were performed to validate the role of macrophage migration inhibitory factor (MIF) in macrophage polarization and chemotaxis. In vivo studies were used to evaluate the effectiveness of MIF inhibition in combination with immune checkpoint blockade in murine models.ResultsElevated lactate levels in osteosarcoma patients correlated with poorer overall survival. We identified SLC7A7 and CYP27A1 as prognostic lactate metabolism genes and developed a risk model to stratify patients into high-risk and low-risk groups with distinct outcomes. Bioinformatics analyses highlighted the differences in immune infiltration patterns and activity between the groups. Notably, the infiltration and phenotype of macrophages varied significantly between the groups, and MIF was identified as a critical mediator in this process. In osteosarcoma cells, lactate regulated MIF expression through histone H3K9 lactylation. Combining the MIF inhibitor 4-IPP with a programmed cell death 1 (PD-1) monoclonal antibody treatment demonstrated a significant antitumor effect.ConclusionMIF acts as a novel therapeutic target by regulating macrophage polarization and chemotaxis. Lactate regulated MIF expression through histone lactylation. Targeting MIF holds promise for enhancing the efficacy of anti-PD-1 treatment.