4.6 Article

Characterization of the Immune Cell Infiltration Landscape Uncovers Prognostic and Immunogenic Characteristics in Lung Adenocarcinoma

期刊

FRONTIERS IN GENETICS
卷 13, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2022.902577

关键词

immune cell infiltration; prognosis; lung adenocarcinoma; tumor microenvironment; immunotherapy

资金

  1. National Key R&D Program of China [2020AAA0109500]
  2. R&D Program of Beijing Municipal Education Commission [KJZD20191002302]
  3. National Natural Science Foundation of China [82122053, 82188102]
  4. Beijing Municipal Science & Technology Commission [Z191100006619115]
  5. CAMS Initiative for Innovative Medicine [2021-I2M-1-012 2021-I2M-1-015]
  6. Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences [2021-PT310-001]
  7. Key-Area Research and Development Program of Guangdong Province [2021B0101420005]
  8. Aiyou Foundation [KY201701]

向作者/读者索取更多资源

This study aimed to investigate the immune cell infiltration in lung adenocarcinoma (LUAD) and develop a predictive system for clinical outcomes. Through transcriptomic analysis and classification of LUAD samples, it was found that TMEscore is a reliable and independent prognostic biomarker that can distinguish the survival rate and immune phenotype of LUAD patients.
The immune cell infiltration in TME has been reported to be associated with prognosis and immunotherapy efficiency of lung cancers. However, to date, the immune infiltrative landscape of lung adenocarcinoma (LUAD) has not been elucidated yet. Therefore, this study aimed to identify a new transcriptomic-based TME classification and develop a risk scoring system to predict the clinical outcomes of patients with LUAD. We applied CIBERSORT algorithm to analyze the transcriptomic data of LUAD samples and classified LUAD into four discrete subtypes according to the distinct immune cell infiltration patterns. Furthermore, we established a novel predictive tool (TMEscore) to quantify the immune infiltration patterns for each LUAD patient by principal component analysis. The TMEscore displayed as a reliable and independent prognostic biomarker for LUAD, with worse survival in TMEscrore-high patients and better survival in TMEscrore-low patients in both TCGA and other five GEO cohorts. In addition, enriched pathways and genomic alterations were also analyzed and compared in different TMEscore subgroups, and we observed that high TMEscore was significantly correlated with more aggressive molecular changes, while the low TMEscore subgroup enriched in immune active-related pathways. The TMEscore-low subtype showed overexpression of PD-1, CTLA4, and associations of other markers of sensitivity to immunotherapy, including TMB, immunophenoscore (IPS) analysis, and tumor immune dysfunction and exclusion (TIDE) algorithm. Conclusively, TMEscore is a promising and reliable biomarker to distinguish the prognosis, the molecular and immune characteristics, and the benefit from ICIs treatments in LUAD.

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