Abstract

BackgroundEsophageal carcinoma (ESCA) and Lung adenocarcinoma (LUAD) are the prominent causes of death worldwide. There is an urgent need to identify and characterize potential biomarkers for these malignancies to enhance early cancer prognosis. Integrating computational-based early cancer detection with wet lab-based research offers a promising approach toward early-stage cancer prognosis. MethodologyTwo ESCA datasets (GSE17351, GSE23400) with 58 cancerous and 58 normal samples, along with two LUAD datasets (GSE18842, GSE74706) totaling 64 cancer samples and 63 controls, were used to identify DEGs. Visualization of DEGs was achieved using heat-maps, volcano plots, and Venn diagrams. Hub genes were predicted via PPI analysis and the cytoHubba plugin in Cytoscape. Potential hub gene expressions were evaluated with box plots, stage plots, and survival plots for prognostic assessment via GEPIA2. AutoDockVina wizard of PyRx was utilized for molecular docking to determine optimal binding interactions between proteins and hit compounds. FindingsSixty common DEGs were identified, focusing on significant pathways in ESCA and LUAD. The top ten hub genes (KIF4A, HMMR, CENPF, CDK1, ASPM, CDKN3, KIF2C, TTK, UBE2C, and MELK) were found to be linked to both cancers via PPI analysis. Notably, high expression of CDK1 was significantly associated with ESCA and LUAD progression, as evidenced by box plots, stage plots, and survival analysis. Upregulated expression of the targeted genes (CDK1) promotes multi-variant cancer progression that is observed by analyzing and comparing of all findings. Molecular docking with CDK1 highlighted four top compounds: Tanshinone I, Withanolide, Artemether, and Epigallocatechin, suggesting their potential as drug candidates for ESCA and LUAD treatment. ConclusionsIn conclusion, our discoveries unveil potential biomarker candidates, offer insights into ESCA and LUAD treatment strategies, and outline directions for further investigation, enriching our understanding of the pathogenesis of ESCA and LUAD.

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