Macrophage-related molecular subtypes in lung adenocarcinoma identify novel tumor microenvironment with prognostic...

Background: Lung adenocarcinoma (LUAD) is a life-threatening malignant tumor, contributing for the largest cancer burden worldwide. Tumor microenvironment (TME) is composed of various immune cells, stromal cells and tumor cells, which is highly associated with the cancer prognosis and the response to immunotherapy, in which macrophages in TME have been revealing a potential target for cancer treatment. In this study, we sought to further explore the role of macrophages in LUAD progression and establish a risk model related to macrophages for LUAD. Methods: We explored immune-related pathways that might be affected by counting positively associated genes in macrophages. Molecular typing was also constructed by mining macrophage-associated genes with prognostic value through COX regression and other analyses. RiskScore prognostic models were constructed using lasso regression and stepwise multifactorial regression analysis. The differences on clinical characteristics among three subtypes (C1, C2, and C3) and RiskScore subtypes were analyzed in TCGA dataset. Immunological algorithms such as TIMER, ssGSEA, MCP-Counter, ESTIMATE, and TIDE were used to calculate the level of difference in immune infiltration between the different subtypes. The TCGA mutation dataset processed by mutect2 was used to demonstrate the frequency of mutations between different molecular subtypes. Finally, nomograms, calibration curves, and decision curves were created to assess the predictive accuracy and reliability of the model. Results: The C1 subtype demonstrated the best prognostic outcome, accompanied by higher levels of immune infiltration and lower mutation frequency, while the majority of patients in the C1 subtype were women under 65 years of age. Myeloid-derived suppressor cell (MDSC) scores were higher in the C3 subtype, suggesting a more severe immune escape, which may have contributed to the tumor evading the immune system resulting in a poorer prognosis for patients. In addition, our RiskScore prognostic model had good predictive accuracy and reliability. Conclusion: This paper provides a study of macrophage-related pathways, immunosuppression, and their mechanisms of action in lung cancer, along with targets for future treatment to guide the optimal treatment of lung cancer.