ArticleImmunogenetics2021
Analyzing the characteristics of immune cell infiltration in lung adenocarcinoma via bioinformatics to predict the effect of immunotherapy.
Article in Immunogenetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.
- Systematic Analyses of a Chemokine Family-Based Risk Model Predicting Clinical Outcome and Immunotherapy Response in Lung Adenocarcinoma.Cell transplantationPooled it
- Automated quantification of tumor-infiltrating lymphocytes by machine learning reveals prognostic and immunogenomic features in lung cancer.Scientific reports · 2026Article
- The role of B cell immunity in lung adenocarcinoma.Genes and immunity · 2025Review
- Integrated radiomics and immune infiltration analysis to decipher immunotherapy efficacy in lung adenocarcinoma.Quantitative imaging in medicine and surgery · 2025Article
- Article
- Integration analysis ofBiochemistry and biophysics reports · 2024Article
- Identification of an immune-related genes signature in lung adenocarcinoma to predict survival and response to immune checkpoint inhibitors.Journal of the Egyptian National Cancer Institute · 2024Article
- Article
- Multi-omics and immunogenomics analysis revealed PFKFB3 as a targetable hallmark and mediates sunitinib resistance in papillary renal cell carcinoma: in silico study with laboratory verification.European journal of medical research · 2024Article
- Exploring Molecular Alterations in Breast Cancer Among Indian Women Using Label-Free Quantitative Serum Proteomics.Biochemistry research international · 2024Article
- MCM4 acts as a biomarker for LUAD prognosis.Journal of cellular and molecular medicine · 2023Article
- Bioinformatics construction and experimental validation of a cuproptosis-related lncRNA prognostic model in lung adenocarcinoma for immunotherapy response prediction.Scientific reports · 2023Article
- Genomic analysis of immunogenic cell death-related subtypes for predicting prognosis and immunotherapy outcomes in glioblastoma multiforme.Open medicine (Warsaw, Poland) · 2023Article
- RASAL3 predicts overall survival and CD8+ T lymphocyte infiltration in lung adenocarcinoma.Journal of cellular and molecular medicine · 2022Article
- Article
- Multi-Omics Approaches for the Prediction of Clinical Endpoints after Immunotherapy in Non-Small Cell Lung Cancer: A Comprehensive Review.Biomedicines · 2022Review
- An immune-related nomogram model that predicts the overall survival of patients with lung adenocarcinoma.BMC pulmonary medicine · 2022Article
- Comprehensive analysis of the prognostic value and immune implications of the TTK gene in lung adenocarcinoma: a meta-analysis and bioinformatics analysis.Animal cells and systems · 2022Article
- Investigating the evolution process of lung adenocarcinoma via random walk and dynamic network analysis.Frontiers in genetics · 2022Article
- The Overexpression of SLC25A13 Predicts Poor Prognosis and Is Correlated with Immune Cell Infiltration in Patients with Skin Cutaneous Melanoma.Disease markers · 2022Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent studies have shown that tumor immune cell infiltration (ICI) is associated with immunotherapy sensitivity and the prognosis of lung adenocarcinoma (LUAD). However, the immunoinfiltrative landscape of LUAD has not been elucidated. We propose two computational algorithms to unravel the ICI landscape to evaluate the efficacy of immunotherapy in LUAD patients. The raw data of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were analyzed. After merging these datasets and removing the batch differences, we used the Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm to obtain the immune cell content of all the samples. The unsupervised consistency clustering algorithm was used to analyze the ICI subtypes, and three subgroups were obtained. In addition, the unsupervised consistency clustering algorithm was used to analyze the differentially expressed genes (DEGs) of the ICI subtypes and obtain three ICI gene clusters. Finally, the ICI score was determined by using principal component analysis (PCA) for the gene signature. The ICI score of LUAD patients ranged from - 32.26 to 12.89 and represents the prognosis and the response to immunotherapy. High ICI scores were characterized by the T cell receptor signaling pathway, B cell receptor signaling pathway, and natural killer cell-mediated cytotoxicity, suggesting that some immune cells were activated and had increased activity, which may be the cause of the better prognosis for patients with high ICI scores. Additionally, patients with higher ICI scores showed a significant immune therapeutic advantage and clinical benefit. This study shows that the ICI score may be a potent prognostic biomarker and predictor of therapy with immune checkpoint inhibitors.
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