A robust signature associated with patient prognosis and tumor immune microenvironment based on immune-related genes in lung squamous cell carcinoma

2020 ◽  
Vol 88 ◽  
pp. 106856 ◽  
Author(s):  
Hao Zhou ◽  
Haijian Zhang ◽  
Muqi Shi ◽  
Jinjie Wang ◽  
Zhanghao Huang ◽  
...  
2015 ◽  
Vol 10 (9) ◽  
pp. 1301-1310 ◽  
Author(s):  
Kyuichi Kadota ◽  
Jun-ichi Nitadori ◽  
Hideki Ujiie ◽  
Daniel H. Buitrago ◽  
Kaitlin M. Woo ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Jungang Zhao ◽  
Wenming Bao ◽  
Weiyang Cai

Intrinsic cancer cells and the tumor-infiltrating immune cells (TIICs) recruited to the immune microenvironment define the malignant phenotype of lung squamous cell carcinoma (LUSC). Understanding more about the immune microenvironment of LUSC enables the selection of high-risk patients who would derive benefit from immunotherapy. Based on large public LUSC cohorts obtained from TCGA and GEO datasets, 22 types of infiltrating immune cell subgroups were evaluated by CIBERSORT. Meta-analysis, principal component analysis (PCA), single-sample gene set enrichment analysis (ssGSEA), and hierarchical clustering analysis were used to evaluate specific immune responses of LUSC. The distribution of TIICs of LUSC was entirely different from normal. TIIC subpopulations were also found to be closely associated with clinical features and molecular subtypes. Unsupervised clustering analysis revealed that three distinct TIIC subgroups existed with different survival patterns. TIICs are extensively implicated in the pathogenesis and development of LUSC. Characterizing the composition of TIICs influences the metabolism, pathological stage, and survival of tumor patients. It is hoped that this immune landscape could provide a more accurate understanding of the development and immunotherapy of LUSC.


2019 ◽  
Vol 26 (6) ◽  
pp. 1474-1485 ◽  
Author(s):  
Janis V. de la Iglesia ◽  
Robbert J.C. Slebos ◽  
Laura Martin-Gomez ◽  
Xuefeng Wang ◽  
Jamie K. Teer ◽  
...  

2021 ◽  
Vol 15 (4) ◽  
pp. 295-306
Author(s):  
Hansheng Wu ◽  
Shujie Huang ◽  
Weitao Zhuang ◽  
Guibin Qiao

Aim: To build a valid prognostic model based on immune-related genes for lung squamous cell carcinoma (LUSC). Materials & methods: Differential expression of immune-related genes between LUSC and normal specimens from TCGA dataset and underlying molecular mechanisms were systematically analyzed. Constructing and validating the high-risk and low-risk groups for LUSC survival. Results: The immune-related gene-based prognostic index (IRGPI) could predict the overall survival in patients with different clinicopathological characteristics. Functional enrichment analysis of differential expression of immune-related gene signature indicated distinctive molecular pathways between high-risk and low-risk groups. Conclusion: Analysis of IRGs in LUSC enable us to stratify patients into distinct risk groups, which may help to screen LUSC patients at risk and decision making on follow-up therapeutic intervention.


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