Transcriptomic Profiling for Prognostic Biomarkers in Early-Stage Squamous Cell Lung Cancer (SqCLC)

Squamous cell lung carcinoma (SqCLC) is associated with high mortality and limited treatment options. Identification of therapeutic targets and prognostic biomarkers is still lacking. This research aims to analyze the transcriptomic profile of SqCLC samples and identify the key genes associated with tumorigenesis, overall survival (OS), and a profile of the tumor-infiltrating immune cells. Differential gene expression analysis, pathway enrichment analysis, and Gene Ontology analysis on RNA-seq data obtained from FFPE tumor samples (N = 23) and healthy tissues (N = 3) were performed (experimental cohort). Validation of the results was conducted on publicly available gene expression data using TCGA LUSC (N = 225) and GTEx healthy donors' cohorts (N = 288). We identified 1133 upregulated and 644 downregulated genes, common for both cohorts. The most prominent upregulated genes were involved in cell cycle and proliferation regulation pathways (MAGEA9B, MAGED4, KRT, MMT11/13), while downregulated genes predominately belonged to immune-related pathways (DEFA1B, DEFA1, DEFA3). Results of the survival analysis, conducted on the validation cohort and commonly deregulated genes, indicated that overexpression of HOXC4 (p < 0.001), LLGL1 (p = 0.0015), and SLC4A3 (p = 0.0034) is associated with worse OS in early-stage SqCLC patients. In contrast, overexpression of GSTZ1 (p = 0.0029) and LILRA5 (p = 0.0086) was protective, i.e., associated with better OS. By applying a single-sample gene-set enrichment analysis (ssGSEA), we identified four distinct immune subtypes. Immune cell distribution suggests that the memory T cells (central and effector) and follicular helper T cells could serve as important stratification parameters.