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Immune Gene Networks from Lung Cancer Patients Treated with Immune Checkpoint Inhibitors
Kyung Soo Kim1, Taewon Kang2, Dong Wook Jekarl2
1Department of Thoracic and Cardiovascular Surgery, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
Abstract:
The association between immune checkpoint inhibitors (ICIs) and immune gene networks in squamous lung cancer (LUSC) and lung adenocarcinoma (LUAD) was studied. Immune gene networks were constructed using RNA-seq data from the gene expression omnibus (GEO) database. Datasets with more than 10 samples of normal control and tumor tissues were selected; of these, GSE87340, GSE120622, and GSE111907 were suitable for analysis. Gene set enrichment for pathway analysis was performed. For immune gene network construction, 998 unique immune genes were selected from 21 pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG). Gene function annotation was performed based on the KEGG, Gene Ontology, and Reactome databases. Tumor tissues showed decreased coagulation, hematopoiesis, and innate immune pathways, whereas complement- and coagulation-related genes were prominent in the tumor immune gene network. The average numbers of neighbors, clustering coefficients, network diameters, path lengths, densities, and heterogeneities were highest for normal tissue, followed by LUAD and LUSC. Decreased coagulation genes, which were prominent in tumor immune networks, imply functional attenuation. LUAD was deviated from normal tissue, based on network parameters. Tumor tissues showed decreased immune function, and the deviation of LUSC from normal tissue might explain LUSC's better therapeutic response to ICI treatment.
Insights
Immune gene networks in lung cancer reveal decreased immune function in tumors. Squamous lung cancer
Area of Science:
- Oncology
- Immunology
- Bioinformatics
Background:
- Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy.
- Understanding the immune microenvironment in lung cancer subtypes is crucial for optimizing ICI treatment.
- Squamous lung cancer (LUSC) and lung adenocarcinoma (LUAD) exhibit distinct responses to ICIs.
Purpose of the Study:
- To investigate the association between immune checkpoint inhibitors (ICIs) and immune gene networks in LUSC and LUAD.
- To characterize the differences in immune gene network topology between normal lung tissue and lung tumors.
- To explore how these network differences correlate with therapeutic responses to ICIs.
Main Methods:
- Utilized RNA-sequencing data from the Gene Expression Omnibus (GEO) database (GSE87340, GSE120622, GSE111907).
- Constructed immune gene networks using 998 unique immune genes from 21 KEGG pathways.
- Performed gene set enrichment and pathway analysis using KEGG, Gene Ontology, and Reactome databases.
Main Results:
- Tumor tissues exhibited decreased coagulation, hematopoiesis, and innate immune pathways compared to normal tissues.
- Complement- and coagulation-related genes were prominent in tumor immune gene networks.
- Network parameters (neighbors, clustering coefficients, diameter, path length, density, heterogeneity) were highest in normal tissue, followed by LUAD and LUSC, indicating altered network topology in tumors.
- LUAD showed deviation from normal tissue network parameters.
Conclusions:
- Tumor tissues display attenuated immune function, characterized by decreased coagulation and innate immune pathways.
- The distinct immune gene network topology in LUSC, deviating from normal tissue, may underlie its superior therapeutic response to ICIs.
- These findings highlight the importance of immune gene network analysis for predicting ICI efficacy in lung cancer subtypes.
