Identification of potential biomarkers for diagnosis of lung adenocarcinoma

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Background: Lung cancer is the deadliest cancer worldwide. Therapeutic options for lung adenocarcinoma(LUAD) have dramatically increased, but late diagnosis remains a challenge. Differentially expressed genes(DEG) may be employed as biomarkers for LUAD detection. Aim: To identify potential biomarkers for diagnosis of LUAD. Materials and Methods: We evaluated fresh-frozen tumoral tissues from patients with LUAD(n=53). Gene expression analysis was performed using the nCounter® PanCancer Pathways panel(NanoString® Technologies). Upregulated and downregulated genes were selected according to fold-change(FC≥|2|) and p-value(p≤0.01) using the ROSALIND® software. DEG were in silico validated using The Cancer Genome Atlas Lung Adenocarcinoma dataset. Enrichment analysis was performed using STRING database. Median normalized counts were used as cut-offs for stratification of genes for survival analysis. Results: We identified a 78-gene signature comparing LUAD tissue and non-tumoral lung tissue. Seventy-seven out of the 78-gene signature were validated(p<0.05), being considered biologically connected(PPI p-value=1.0e-16). Patients were stratified into groups based on gene expression levels into higher, intermediate and lower groups. An association with survival was noted(p=0.001), whereas the intermediate group had a hazard ratio(HR) of 1.58(95%CI:0.4-5.9;p=0.48) and the lower group had a HR of 4.29(95%CI:1.1-16.5;p=0.034). Notably, the downregulation of CD19, IL1R2, and TLR4 showed HRs of 2.75(95%CI:1.27-5.91;p=0.10), 2.34(95%CI:1.09-5.04;p=0.29), and 2.15(95%CI:1.02-4.55;p=0.043), respectively. Conclusion: We identified a 78-gene signature that might help define a more accurate diagnosis for lung adenocarcinoma.

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