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pmid:39735788
Development of a Prognostic Risk Model for Esophageal Cancer Based on M0 Macrophage-Related Genes.
Xiaoping Zuo · Fuqiang Wang · Guofeng Liu · Shenglong Xie · Senyi Deng · Yun Wang
OncoTargets and therapy · 2024 doi:10.2147/OTT.S483536
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Experiment
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Complete file
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Then, immune cell infiltration was examined with the CIBERSORT algorithm and multiplex fluorescence-based immunohistochemistry (MP-IHC). ESCA-related gene expression data and relevant clinical information were retrieved from TCGA. M0MRGs were identified with TCGA-ESCA based on Spearman's correlation coefficient. Additionally, LASSO and Cox regression analyses were conducted to further construct an M0MRG-related prognostic model. ATP6V0D2 and MMP12 expression in ESCA was analyzed with tissue microarray. Finally, the half maximal inhibitory concentrations (IC50) of commonly used chemotherapeutics in TCGA-ESCA were calculated with the \"oncoPredict\" R package.\nConclusion: In summary, ATP6V0D2 and MMP12 were crucial components in a prognostic risk model for ESCA and were associated with poor prognoses, implicating the involvement of elevated M0 macrophages in disease progression and providing potential therapeutic targets and strategies for ESCA.", "claims": [{"id": "claim-method", "statement": "LASSO and Cox regression analyses were conducted to further construct the prognostic model of M0MRGs in the TCGA-ESCA dataset.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39735788", "locator": "sections[5] \"Establishment of an M0MRG Signature\" paragraph 2", "quote": "LASSO and Cox regression analyses were conducted to further construct the prognostic model of M0MRGs in the TCGA-ESCA dataset."}], "state": "complete"}, {"id": "claim-data-access", "statement": "In this study, the transcriptomic, somatic mutation, and clinical data of the ESCA cohort were obtained from TCGA data portal (https://cancergenome.nih.gov/) and GEO datasets (GSE5364 and GSE17351) (http://www.ncbi.nlm.nih.gov/geo/). 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