Background: Numerous studies have found that infiltrating M2 macrophages play an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of M2 macrophage infiltration and M2 macrophage-related genes in immunotherapy and clinical outcomes remain obscure.
Methods: Sample information was extracted from TCGA and GEO databases. The TIME landscape was revealed using the CIBERSORT algorithm. Weighted gene co-expression network analysis (WGCNA) was used to find M2 macrophage-related gene modules. Through univariate Cox regression, lasso regression analysis, and multivariate Cox regression, the genes strongly associated with the prognosis of LUAD were screened out. Risk score (RS) was calculated, and all samples were divided into high-risk group (HRG) and low-risk group (LRG) according to the median RS. External validation of RS was performed using GSE68571 data information. Prognostic nomogram based on risk signatures and other clinical information were constructed and validated with calibration curves. Potential associations of tumor mutational burden (TMB) and risk signatures were analyzed. Finally, the potential association of risk signatures with chemotherapy efficacy was investigated using the pRRophetic algorithm.
Results: Based on 504 samples extracted from TCGA database, 183 core genes were identified using WGCNA. Through a series of screening, two M2 macrophage-related genes ( and ) strongly correlated with LUAD prognosis were finally selected. RS was calculated, and prognostic risk nomogram including gender, age, T, N, M stage, clinical stage, and RS were constructed. The calibration curve shows that our constructed model has good performance. HRG patients were suitable for new ICI immunotherapy, while LRG was more suitable for CTLA4-immunosuppressive therapy alone. The half-maximal inhibitory concentrations (IC50) of the four chemotherapeutic drugs (metformin, cisplatin, paclitaxel, and gemcitabine) showed significant differences in HRG/LRG.
Conclusions: In conclusion, a comprehensive analysis of the role of M2 macrophages in tumor progression will help predict prognosis and facilitate the advancement of therapeutic techniques.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9352953 | PMC |
http://dx.doi.org/10.3389/fonc.2022.919899 | DOI Listing |
Heliyon
December 2024
Department of Hematology, Guangxi Medical University Cancer Hospital, Nanning, Guangxi, 530021, China.
Purpose: The tumor microenvironment (TME) in lymphoma is influenced by M2 macrophages. This research proposes an novel predictive model that leverages M2 macrophage-associated genes to categorize risk, forecast outcomes, and evaluate the immune profile in patients with newly diagnosed diffuse large B-cell lymphoma (DLBCL) undergoing R-CHOP therapy.
Methods: Gene expression data and clinical information from DLBCL patients were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases.
Onco Targets Ther
December 2024
Department of Thoracic Surgery, West China Hospital of Sichuan University, Chengdu, People's Republic of China.
Background: This study investigates the prognostic value of M0 macrophage-related genes (M0MRGs) in esophageal cancer (ESCA) and identifies novel targets for immunotherapy.
Methods: Differentially expressed genes (DEGs) were screened with ESCA-related expression profile data (GSE5364 and GSE17351) from the GEO database, followed by GO and KEGG pathway enrichment analyses. Then, immune cell infiltration was examined with the CIBERSORT algorithm and multiplex fluorescence-based immunohistochemistry (MP-IHC).
J Inflamm Res
December 2024
Department of Cardiothoracic Surgery, Changzheng Hospital, Naval Medical University, Shanghai, People's Republic of China.
Background: Cardiac macrophages are a heterogeneous population with high plasticity and adaptability, and their mechanisms in heart failure (HF) remain poorly elucidated.
Methods: We used single-cell and bulk RNA sequencing data to reveal the heterogeneity of non-cardiomyocytes and assess the immunoreactivity of each subpopulation. Additionally, we employed four integrated machine learning algorithms to identify macrophage-related genes with diagnostic value, and in vivo validation was performed.
J Inflamm Res
December 2024
Department of Vascular Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People's Republic of China.
Purpose: The relationship between macrophages and the progression of abdominal aortic aneurysms (AAA) remains unclear, and effective biomarkers are lacking. In this study, we elucidated the mechanism whereby macrophages promote AAA development and identified associated biomarkers, with the goal of developing new targeted therapies and improving patient outcomes.
Patients And Methods: Differential expression analysis, weighted gene co-expression network analysis, and single-cell analysis were used to identify macrophage-related genes in an AAA dataset.
Front Immunol
December 2024
Department of Pathology, University of Texas Medical Branch, Galveston, TX, United States.
Background: The inflammatory macrophage response contributes to severe Ebola virus disease, with liver and lung injury in humans.
Objective: We sought to further define the activation status of hepatic and pulmonary macrophage populations in Ebola virus disease.
Methods: We compared liver and lung tissue from terminal Ebola virus (EBOV)-infected and uninfected control cynomolgus macaques challenged via the conjunctival route.
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