Multi-omics analysis reveals a macrophage-related marker gene signature for prognostic prediction, immune landscape, genomic heterogeneity, and drug choices in prostate cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37122696", "kind": "science-record", "revision": 3, "content_hash": "sha256:e5aa84755fe75f3717ad5ee08f24345a5cc95c0045cd7589f3ba4cbeae94f51d", "created_at": "2026-11-01T19:01:47Z", "updated_at": "2026-11-01T22:09:22Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Multi-omics analysis reveals a macrophage-related marker gene signature for prognostic prediction, immune landscape, genomic heterogeneity, and drug choices in prostate cancer.", "doi": "10.3389/fimmu.2023.1122670", "pmid": "37122696", "authors": ["Weian Zhu", "Jianjie Wu", "Jiongduan Huang", "Dongming Xiao", "Fengao Li", "Chenglun Wu", "Xiaojuan Li", "Hengda Zeng", "Jiayu Zheng", "Wenjie Lai", "Xingqiao Wen"], "journal": "Frontiers in immunology", "year": 2023, "abstract": "Introduction: Macrophages are components of the innate immune system and can play an anti-tumor or pro-tumor role in the tumor microenvironment owing to their high heterogeneity and plasticity. Meanwhile, prostate cancer (PCa) is an immune-sensitive tumor, making it essential to investigate the value of macrophage-associated networks in its prognosis and treatment.\nMethods: Macrophage-related marker genes (MRMGs) were identified through the comprehensive analysis of single-cell sequencing data from GSE141445 and the impact of macrophages on PCa was evaluated using consensus clustering of MRMGs in the TCGA database. Subsequently, a macrophage-related marker gene prognostic signature (MRMGPS) was constructed by LASSO-Cox regression analysis and grouped based on the median risk score. The predictive ability of MRMGPS was verified by experiments, survival analysis, and nomogram in the TCGA cohort and GEO-Merged cohort. Additionally, immune landscape, genomic heterogeneity, tumor stemness, drug sensitivity, and molecular docking were conducted to explore the relationship between MRMGPS and the tumor immune microenvironment, therapeutic response, and drug selection.\nResults: We identified 307 MRMGs and verified that macrophages had a strong influence on the development and progression of PCa. Furthermore, we showed that the MRMGPS constructed with 9 genes and the predictive nomogram had excellent predictive ability in both the TCGA and GEO-Merged cohorts. More importantly, we also found the close relationship between MRMGPS and the tumor immune microenvironment, therapeutic response, and drug selection by multi-omics analysis.\nDiscussion: Our study reveals the application value of MRMGPS in predicting the prognosis of PCa patients. It also provides a novel perspective and theoretical basis for immune research and drug choices for PCa.", "claims": [{"id": "claim-method", "statement": "The intersection genes were evaluated by least absolute shrinkage and selection operator (LASSO) Cox proportional hazards regression using the “glmnet” package to eliminate the effect of overfitting.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37122696", "locator": "sections[7] \"Construction and validation of prognostic signature\" paragraph 2", "quote": "The intersection genes were evaluated by least absolute shrinkage and selection operator (LASSO) Cox proportional hazards regression using the “glmnet” package to eliminate the effect of overfitting."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: https://portal.gdc.cancer.gov/ and https://www.ncbi.nlm.nih.gov/.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37122696", "locator": "sections[27] \"Data availability statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found here: https://portal.gdc.cancer.gov/ and https://www.ncbi.nlm.nih.gov/."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The MRMGPS constructed with 9 genes and the predictive nomogram had excellent predictive ability in both the TCGA and GEO-Merged cohorts.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37122696", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We identified 307 MRMGs and verified that macrophages had a strong influence on the development and progression of PCa. 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