Bioinformatics Analysis Reveals Candidate Biomarkers Served As Dendritic Cell-based Lung Squamous CellCarcinoma (LUSC) Treatment
Lung squamous cell carcinoma (LUSC) causes high mortality rates worldwide. The goal of the study is to use bioinformatics approaches to identify candidate genes associated with lung cancer and the ones that could serve as targets for specific immune infiltration.The candidate genes in two significant clusters reported for LUSC based on TCGA database were chosen for analysis. The pattern of gene expression in both clusters shows opposite to their genomic landscape signature: one cluster of genes tends to have longer average gene length and fewer average number of exons than the genes in the other cluster. Functional annotation using The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was performed after genomic information analysis. Groups of genes for their enriched terms having the False Discovery Rate (FDR) value less than 0.1 were further studied. Cancer association for selected genes were confirmed using the Cancer Genetics Web tool. Three genes (RNASE6, CCR1, CMKLR1) from one cluster and 11 genes (DLL4, NID2, ROBO4, COL4A1, VASH1, VWF, BGN, KIT, PRND, OSBPL10, CD34) from the other cluster are prioritized to be top candidate genes.Correlation between gene expression and immune cell infiltration was examined using TIMER2.0. Positive correlations were observed between the expressions of these genes and six different types of immune infiltration, particularly with dendritic cells, according to TIMER2.0 Gene analysis. Mutation analysis revealed varied frequencies, with ROBO4 showing the highest mutation rate (6.6%) among our identified LUSC-associated genes. Five genes (DLL4, CMKLR1, CD34, ROBO4, and NID2) exhibit a strong positive correlation between their expressions with immune infiltration. This suggests that these genes may serve as potential targets for dendritic cell immune infiltration in the treatment of LUSC. The candidate genes prioritized in our study have medical significance.
Authors
- Yongsheng Bai (ORCID: https://orcid.org/0000-0002-9944-5426)
- Wei Yu (ORCID: https://orcid.org/0000-0002-1777-5254)
Institutions
- Eastern Michigan University (US)
- Michigan United (US)
Publication Details
- Published
- 2024-12-03
- DOI
- https://doi.org/10.1109/bibm62325.2024.10821902
- Primary Topic
- Lung Cancer Treatments and Mutations
- Type
- article
- Field-Weighted Citation Impact
- 0.00