Validating a Macrophage Marker Gene Signature (MMGS) in Lung Adenocarcinoma Prognosis and Response to Immunotherapy

Author:

Song Peng1,Wusiman Dilinaer2,Li Wenbin3,Guo Lei3,Ying Jianming3,Gao Shugeng4,He Jie4

Affiliation:

1. Department of Thoracic Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, China

2. Department of Head and Neck Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

3. Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

4. Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

Abstract

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide. Tumor-associated macrophages play pivotal roles in the tumor microenvironment (TME) and prognosis of LUAD. We first used single-cell RNA sequencing data to identify macrophage marker genes in LUAD. Univariate, least absolute shrinkage and selection operator and stepwise multivariate Cox regression analyses were conducted to evaluate macrophage marker genes as prognostic factors and to construct the macrophage marker genes signature (MMGS). A novel 8-gene signature was constructed to predict prognosis based on 465 macrophage marker genes identified by an analysis of single-cell RNA sequencing data of LUAD, and was also verified in 4 independent GEO cohorts. The MMGS significantly classified patients into high-risk and low-risk groups in terms of OS. A prognostic nomogram based on independent risk factors was established to predict the 2-, 3- and 5-year survival, which indicated superior accuracy in predicting prognosis. The high-risk group was correlated to higher tumor mutational burden, number of neoantigens, T-cell receptor richness, and lower TIDE, which suggested that high-risk patients were more likely to benefit from immunotherapy. The prediction of the possibility of immunotherapy efficacy was also discussed. Analysis of an immunotherapy cohort further verified that patients with high-risk scores had better immunotherapy responses than low-risk patients. The MMGS is a promising signature for predicting prognosis and effectiveness of immunotherapy in patients with LUAD, and may be helpful for clinical decision-making.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cancer Research,Pharmacology,Immunology,Immunology and Allergy

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