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In Vitro Assay to Study Tumor-macrophage Interaction
Published on: August 1, 2019
Integrated analysis reveals the microenvironment of non-small cell lung cancer and a macrophage-related prognostic
Shenglong Xie1,2, Guixiang Huang3, Weiwei Qian4
1Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China.
Background:
In the treatment of non-small cell lung cancer (NSCLC), recent advances in immunotherapy have heralded a new era. Despite the success of immune therapy, a subset of patients persistently fails to respond. Therefore, to better improve the efficacy of immunotherapy and achieve the purpose of precision therapy, the research and exploration of tumor immunotherapy biomarkers have received much attention.
Methods:
Single-cell transcriptomic profiling was used to reveal tumor heterogeneity and the microenvironment in NSCLC. The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was utilized to speculate the relative fractions of 22 infiltration immunocyte types in NSCLC. Univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were used for the construction of risk prognostic models and predictive nomograms of NSCLC. Spearman's correlation analysis was employed to explore the relationship between risk score and tumor mutation burden (TMB) and immune checkpoint inhibitors (ICIs). Screening of chemotherapeutic agents in the high- and low-risk groups was performed with the "pRRophetic" package in R. Intercellular communication analysis was conducted using the "CellChat" package.
Results:
We found that most tumor-infiltrating immune cells were T cells and monocytes. We also found that there was a significant difference in the tumor-infiltrating immune cells and ICIs across different molecular subtypes. Further analysis showed that M0 and M1 mononuclear macrophages were significantly different in different molecular subtypes. The risk prediction model was shown to have to ability to accurately predict the prognosis, immune cell infiltration, and chemotherapy efficacy of patients in the high and low-risk groups. Finally, we found that the carcinogenic effect of migration inhibitory factor (MIF) is mediated by binding to CD74, CXCR4, and CD44 receptors involved in MIF cell signaling.
Conclusions:
We have revealed the tumor microenvironment (TME) of NSCLC through single-cell data analysis and constructed a prognosis model of macrophage-related genes. These results could provide new therapeutic targets for NSCLC.
Insights
This study reveals the tumor microenvironment in non-small cell lung cancer (NSCLC) and develops a prognostic model based on macrophage-related genes. These findings may offer new therapeutic targets for NSCLC patients, improving immunotherapy efficacy.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Immunotherapy has advanced non-small cell lung cancer (NSCLC) treatment, but some patients do not respond.
- Identifying biomarkers is crucial for improving immunotherapy efficacy and achieving precision therapy in NSCLC.
Purpose of the Study:
- To analyze the tumor microenvironment (TME) in NSCLC using single-cell transcriptomic profiling.
- To construct a prognostic model based on macrophage-related genes for NSCLC.
- To explore potential therapeutic targets for NSCLC.
Main Methods:
- Single-cell transcriptomic profiling and CIBERSORT algorithm to analyze immune cell infiltration in NSCLC.
- Cox and LASSO regression for prognostic model and nomogram construction.
- Analysis of tumor mutation burden (TMB), immune checkpoint inhibitors (ICIs), and intercellular communication.
Main Results:
- T cells and monocytes were the predominant tumor-infiltrating immune cells.
- Significant differences in immune cells and ICIs were observed across molecular subtypes, particularly M0 and M1 macrophages.
- A risk prediction model accurately predicted prognosis, immune cell infiltration, and chemotherapy efficacy.
- Migration inhibitory factor (MIF) exerts its carcinogenic effect via CD74, CXCR4, and CD44 receptors.
Conclusions:
- Single-cell data analysis elucidated the NSCLC tumor microenvironment.
- A novel prognosis model for NSCLC was developed using macrophage-related genes.
- These findings suggest potential new therapeutic targets for NSCLC.
